Entrepreneurial Communication in Agriculture: The Probing and Perception 9352220471, 9789352220472

Citation preview

ENTREPRENEURIAL COMMUNICATION IN AGRICULTURE

THE AUTHORS Dr. Sankhyashree Roy, born on 20th June 1991,Agartala, Tripura, completed her Ph D (2019) in Agricultural Extension, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, West Bengal under the guidance of Prof S K Acharya. The thesis was entitled, Entrepreneurial communication: the process, factors and impact in agriculture and allied sectors of selected blocks of Tripura and West Bengal. Her profile follows a brilliant academic career including the University Gold Medal for securing highest OGPA in M.Sc (Ag). She has qualified ICAR NET thrice, UGC NET twice, SRF (UPS Rank 3), JRF (UPS Rank 1) and appeared for ARS viva-voce twice. She participated in several national and international conferences and presented valuable research papers. She has also been conferred with the “Young Scientist” award.. She has worked as Junior Research Fellow in a project of FRC – LE under ICFRE, and also as Assistant Professor in LPU, Punjab. She is currently associated with a project under ICAR. Prof. (Dr.) Sankar Kr Acharya, former Head, Dept. of Agril Extension and Director, Extension Education, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, WB. He started his career as Assistant Professor at BCKV in 1988 and has been in teaching, research and extension over 30 years. He has published 209 research paper in National and International Journals and 95 books. He has so far been awarded with 9 best paper awards in National and International Conferences. He has also been honoured to be selected as the Convener of Panel (PE-32) entitled The hunger , poverty and silence, of IUAES, University of Manchester, UK, 2013 .Co-PI of ICAR and World bank funded project on Conservation Agriculture. So, far he has successfully guided 16 Ph D scholars from BCKV, CU, KU, Vidyasagar University.

ENTREPRENEURIAL COMMUNICATION IN AGRICULTURE The Probing and Perception Authors —

Dr. Sankhyashree Roy Ph.D. in Agricultural Extension, Dept. of Agricultural Extension Bidhan Chandra Krishi Viswavidyala, Mohanpur, Nadia, West Bengal

Prof. (Dr.) Sankar Kr Acharya Former Head, Dept. of Agril Extension and Director, Extension Education, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, West Bengal Maharashtra, India

Scholars World A Division of

Astral International Pvt. Ltd. New Delhi – 110 002

© 2023 AUTHORS ISBN : 9789354614644 (EB) Publisher’s Note: Every possible effort has been made to ensure that the information contained in this book is accurate at the time of going to press, and the publisher and author cannot accept responsibility for any errors or omissions, however caused. No responsibility for loss or damage occasioned to any person acting, or refraining from action, as a result of the material in this publication can be accepted by the editor, the publisher or the author. The Publisher is not associated with any product or vendor mentioned in the book. The contents of this work are intended to further general scientific research, understanding and discussion only. Readers should consult with a specialist where appropriate. Every effort has been made to trace the owners of copyright material used in this book, if any. The author and the publisher will be grateful for any omission brought to their notice for acknowledgment in the future editions of the book. All Rights reserved under International Copyright Conventions. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise without the prior written consent of the publisher and the copyright owner.

Published by

:

Scholars World A Division of Astral International Pvt. Ltd. – ISO 9001:2015 Certified Company – 4736/23, Ansari Road, Darya Ganj New Delhi-110 002 Ph. 011-4354 9197, 2327 8134 E-mail: [email protected] Website: www.astralint.com

Preface

Communication is the process that transfers and receives messages, shares and creates opinions; while entrepreneurial communication incubates, mentors and propagates enterprises. The way a teacher communicates to the students is equally important the way an investor talks to the customers, because, in a sense, both are entrepreneurs and behaves through entrepreneurial communication. This is immensely important for the growth and sustainability in agriculture or in any production process wherein the prime interaction reigns between source and receiver. There has been need to extract the marker variables impacting on and characterizing the entrepreneurial communication including information seeking as well as sharing behavior of farmers in different operating social ecologies. The social ecology of entrepreneurial communication is comprising of farm production process, technology back up, input and credit delivery mechanism, operating supply chain, market segmentation, decision support system and policy formulation for both micro and macro sociological realities. I think, the book is of a worth creation to redefine the value and importance of entrepreneurial communication, an integral part of behavioral psyche and response mechanism to a score of stimuli. BCKV, Mohanpur

Prof. S K Acharya, Ph.D. Dr. Sankhyashree Roy

Contents

Preface 1.

v

Prologue 1-8 1.1. Entrepreneurship: The concept and definitions 1.2. Rural entrepreneurship in India 1.3. Opportunities of Rural Entrepreneurship 1.4. Challenges for Rural Entrepreneurs 1.5. Rural enterprise development 1.6. Entrepreneurship and Information Communication Technology 1.7. Communication and Entrepreneurship 1.8. Communication pattern of linkers 1.9. Business communication 1.10. Subliminal method of communication 1.11. Dialogue social enterprise 1.12. Need for Entrepreneurial class 1.13. Need for Technical Business Incubators 1.14. Entrepreneurial process: The stages 1.15. Entrepreneurial behaviour 1.16. Role of incentives and subsidy for encouraging Entrepreneurial behaviour 1.17. Conceptual framework of Entrepreneurship 1.18. New concept of Entrepreneurs 1.19. Entrepreneurship: Steps of creative process 1.20. Need of the study

viii



1.21. General objective 1.22. Specific objectives

2.

Review of Literature 2.1. Concept of Review of Literature 2.2. Contributions of Review of Literature 2.3. Concept of Entrepreneurship 2.4. Concept of Entrepreneurial behaviour 2.5. Entrepreneurial behaviour and social ecology 2.6. Dimensions of Entrepreneurial behavior 2.7. Framework of Entrepreneurial venture 2.8. Entrepreneurship and constrained environment 2.9. A 4-P framework of Entrepreneurship 2.10. Relationship among 4 2.11. Mediation effect 2.12. Entrepreneurial or Business communication

9-34

3.

Theoretical Orientation 35-49 3.1. Entrepreneurship: The concept and definitions 3.2. Rural Entrepreneurship 3.3. Rural Entrepreneurship in India 3.4. Role of Rural Entrepreneurship in India 3.5. Opportunities for Rural Entrepreneurship 3.6. Challenges faced by Rural Entrepreneurship 3.7. Types of Rural Entrepreneurship 3.8. Rural enterprise development 3.9. Entrepreneurial behaviour 3.10. Entrepreneurial process 3.11. Role of incentives and Subsidy for encouraging Entrepreneurial behaviour 3.12. Entrepreneurship: Steps of creative process 3.13. Entrepreneurship and Information Communication Technology 3.14. ICT Entrepreneurship Model: A New approach for Information Technology 3.15. Need for Entrepreneurial class 3.16. Communication and Entrepreneurship 3.17. Communication pattern 3.18. Communication pattern of linkers 3.19. Entrepreneurial communication 3.20. Business communication 3.21. Subliminal method of communication

ix



3.22. Dialogue Social Enterprise 3.23. Need for Technical Business Incubators 3.24. Reservation versus Dereservation of items for small scale sectors 3.25. Entrepreneurship: The Dynamic need 3.26. New concept of entrepreneurs 3.27. Conceptual framework of Entrepreneurship

4. Research setting and social ecology 4.1. Area of study 4.2. Tripura at a glance 4.2.1. Mythological period 4.2.2. Historical period 4.2.3. Modern period 4.2.4. Climate of the State 4.2.5. Agriculture 4.2.6. Economy 4.2.7. General information of district West Tripura 4.3. West Bengal at a glance 4.3.1. District Nadia at a glance 4.3.2. General information about the district 4.3.3. Rainfall and temperature 4.3.4. Topography and agro-climatic Characteristics 4.3.5. Irrigation and ground water

50-63

5.

64-75

Research Methodology 5.1. Concept of Research Methodology 5.2. Locale of Research 5.2.1. Selection of the states 5.2.2. Selection of the districts 5.2.3. Selection of the blocks 5.2.4. Selection of the villages 5.2.5. Selection of the respondents 5.3. Pilot Study 5.4. Methods of Sampling 5.5. Variables and Measurements 5.5.1. The Independent Variables 5.5.2. The Dependent Variables 5.6. Preparation of the schedule 5.7. Tools and Techniques of data collection 5.8. Statistical analysis and interpretation of data

x



5.8.1. Range 5.8.2. Mean 5.8.3. Median 5.8.4. Mode 5.8.5. Standard Deviation (S.D.) 5.8.6. Coefficient of Variation (C.V.) 5.8.7. Correlation Coefficient 5.8.8. Step wise Regression Analysis 5.8.9. Factor Analysis 5.8.9.1. Use of Factor Analysis 5.8.9.2. Eigenvalues 5.8.9.3. Factor loading 5.8.9.4. Varimax rotation 5.8.10. Path analysis 5.9 Matrix Ranking

6. 7.

Results and Discussion 75-175 Summary and Conclusion 176-199 7.1. Summary 351-382 7.1.1. Findings from the villages Bamutia and Kamalghat of Tripura 7.1.2. Findings from the villages Bhawanipore and Ghoragacha of West Bengal 7.1.3. Findings from the pooled villages of two states, Tripura and West Bengal 7.1.4. Findings from the comparative study of two States, Tripura and West Bengal 7.2. Epilogue

8. Recommendation and Limitations 9. Bibliography

200-201 202-213

Chapter

1

PROLOGUE INTRODUCTION Albeit adventuring a journey through the meandering pathways of growth, decline and stagnation, Indian agriculture has been sustaining around 60 per cent of her population by providing livelihood and social security. Indian agriculture caters the responsibility of providing national as well as household food and nutritional security to her teeming millions. Wide spread occurrence of deleterious effect of green revolution technologies in all intensively cultivated areas like Punjab and Haryana, is threatening the sustainability of the important agricultural production systems and national food security. The declining trend in size of land holding and its subsequent fragmentation poses a serious challenge to the sustainability and profitability of agriculture. The average size of the landholding has declined to 1.16 ha during 2010-11 from 2.28 ha in 1970-71. If this trend continues for a longer period, the average size of holding in India would be mere 0.68 ha in 2020 and would be further reduced to 0.32 ha in 2030 (Agriculture Census, 2010-11). It is most important to develop strategies and agricultural technologies that enable adequate employment and income generation, especially for small and marginal farmers who constitute more than 80 per cent of the farming community. Agricultural policy focus in India across decades has been focusing on self-reliance in food grain which we achieved through Green Revolution. The national economy of India is heading for an inclusive growth and in making this progress a reality of livelihood generation from core agricultural and rural sector must have to go all out the sustainable livelihood generation, mentoring, customization and value addition have got both intrinsic and extrinsic dynamism. One of the major objectives of developmental policies in India is to provide employment to millions of unemployed rural youth. The core of the problem in countries like India is surplus agricultural labour and closure of traditional village industries, resulting in increased unemployment in rural areas and migration of rural youth to urban areas in search of jobs, in turn putting more pressure on the urban infrastructure and amenities. Rural industries generated employment for 47.97

2

Entrepreneurial Communication in Agriculture

lakhs people in the year 1996-97, as against 37.21 lakhs people in the year 1992-93. There are a large number of products and services available in rural areas, which can be leveraged by entrepreneurs to set-up new and small micro enterprises. In fact, entrepreneurship can be pursued in virtually any economic field. The fundamental role is to provide employment opportunities and consequently, applying a check on migration. Industries in rural areas are mostly micro or tiny in structure and quick yielding. Rural industries are labour intensive and provide substantial employment opportunities to rural people of all age groups. For example, Food Processing industry, Poultry industry, Cottage and Handicrafts industry, etc. This also helps in balanced regional growth and promotion of artistic activities. India is one of the oldest, culturally richest and diverse country full of colors and boasts of civilization with rich flora and fauna. Our cuisine is mouth watering, scenic beauty is breathtaking, folk dances are simply enchanting, and there is a wide array of places of tourist attraction. These are just a few of the reasons why Government has termed us as Incredible India. Nearly two-thirds of our fellow Indians live in the villages where our roots are contained. There is the wealth of craft, performing art, vivid lifestyle and cultural diversity contained in our rural India. Thus, rural entrepreneurship will further help bridge this gap between the rural and urban areas, and the development of urban areas will not happen at the cost of our rural areas.

1.1: Entrepreneurship: The Concept and Definitions Entrepreneur is a person who has the ability to find and act upon opportunities to translate inventions or technology into new products, and the entrepreneur is able to recognize the commercial potential of the invention, the entrepreneur organizes the capital, talent, and other resources that turn an invention into a commercially viable innovation. In this sense, the term "entrepreneurship" captures innovative activities on the part of established firms, in addition to similar activities on the part of new businesses, also it is the act of being an entrepreneur, or "the owner or manager of a business enterprise who, by risk and initiative, attempts to make profits". Entrepreneurs act as managers and oversee the launch and growth of an enterprise. Entrepreneurship is also the process of designing, launching and running a new business, which is often initially a small business. Entrepreneurship has been described as the capacity and willingness to develop, organize and manage a business venture along with any of its risks in order to make profit. It is also the process by which either an individual or a team identifies a business opportunity and acquires and deploys the necessary resources required for its exploitation.

1.2: Rural Entrepreneurship in India Local leaders and NGOs, who are committed to the cause of the rural people, have been catalytic agents for development. Though their efforts need to be recognized yet, much more needs to be done to reverse the direction of movement of people, i.e. to attract people to the rural areas. It means not only stopping the outflow of rural people but also attracting them back from the towns and cities where they

Prologue

3

had migrated. This is possible only when young generation consider rural areas as places of opportunities. Despite all the inadequacies in rural areas, people should assess their strengths and build on them to make rural areas places of opportunities. This is much to do with the way one sees the reality of the rural areas.

1.3: Opportunities of Rural Entrepreneurship (i) Free entry into world trade. (ii) Improved risk taking ability. (iii) Governments of nations withdrawn some restrictions. (iv) Technology and inventions spread into the world. (v) Encouragement to innovations and inventions. (vi) Promotion of healthy competitions among nations. (vii) Considerable increase in government assistance for international trade. (viii) The establishment of other national and international institutes to support business among the nations of the world. (ix) Benefits of specialization. (x) Social and cultural development. (xi) Generation of sustainable livelihood.

1.4: Challenges for Rural Entrepreneurs (i) Growth of Mall Culture. (ii) Poor Assistance. (iii) Power Failure. (iv) Lack of Technical knowhow. (v) Capacity Utilization. (vi) Infrastructure Sickness. (vii) Low self-image and confidence. (viii) No faith on others, including friends. (ix) No exposure to industry/business.

1.5: Rural Enterprise Development A rural enterprise can be any economic unit engaged in producing and distributing goods and services, from individual households to larger operations, and they play a vital role in poverty reduction and economic development. But there are many things that businesses need to do to flourish in today’s competitive world. The field of entrepreneurship has been thoroughly studied for decades. Since it was determined that entrepreneurship is a major factor of economic growth, it has also attracted many researchers, who have produced an ample amount of literature. Entrepreneurship is also the process which helps an individual to recognize the opportunities inorder to satisfy needs. Entrepreneurs are regarded as innovative individuals who are responsible for the change and growth.

4

Entrepreneurial Communication in Agriculture

1.6: Entrepreneurship and Information Communication Techno-logy (ICT) Many national, regional or local policies have been developed to support entrepreneurship both generally and in specific industries related to information and communication technology (ICT). Some perspectives on the meaning of entrepreneurship are considered. These are: a function in the economy (with a three-stage model); a new business start-up; an owner-manager of a small business; a set of personal characteristics; and, a form of behaviour. These perspectives have differing implications for policies to promote entrepreneurship. These policies also include predominantly macro-level policies such as economic stability, taxation and regulations; micro-level policies focusing upon advice, training, finance, technology transfer, markets access, physical infrastructure and the characteristics of the locality; and creating an entrepreneurial culture.

1.7: Communication and Entrepreneurship The journey of communication, even from the prehistoric phases, has so far been full of revolutions, plateauing and resurrections.(Acharya,S K, Adhikary, M M et.al, 2013). Communication is any act by which one person gives to or receives from another person, the information about that person’s needs, desires, perceptions, knowledge, or affective states. Communication may be intentional or unintentional, it may involve conventional or unconventional signals, may take linguistic or non-linguistic (non verbal) forms, and may occur through spoken or other modes. Communication is the utmost need for entrepreneurship because in doing any type of business, be it a small or large, first of all comes the need of communication between the seller and the customer. If both the seller and the buyer don’t understand the meaning intended, the enterprise will survive difficulties to sustain.

1.8: Communication Pattern of Linkers It helps learning the nature of relationship between communication behavior of linker and his effectiveness in facilitating research dissemination and utilization. Information input amount; Information input diversity; Peer communication amount; Peer communication diversity; Linker network centrality; Opinion leadership; Information output amount; Information output diversity, etc.

1.9: Business Communication Business Communication is information sharing between people within and outside an organization that is performed for the commercial benefit of the organization. It is also the relaying of information within a business by its people. Business communication contains marketing, brand management, customer relations, consumer behavior, advertising, public relations, corporate communication community engagement, reputation management, interpersonal communication, employee engagement, event management, etc.

1.10: Subliminal Method of Communication Subliminal perception refers to the individual ability to perceive and respond to stimuli that are below the threshold or level of consciousness, which proved to influence thoughts, feelings or actions altogether or separately. There are four

Prologue

5

distinct methods of subliminal communication. These are, visual stimuli in movies, accelerated speech, embedded images in a print advertisement and suggestiveness. Subliminal method of communication first made its debut in a 1957 advertisement, during which a brief message flashed, telling viewers to eat popcorn and drink Coca-Cola. Since that time, subliminal communication has occupied a controversial role in the advertising landscape, with some people claiming it's omnipresent, while others emphasize it's not real. As of publication, there is still an ongoing scientific debate about whether subliminal advertising works. Subliminal messaging is a form of advertising in which a subtle message is inserted into a standard advertisement.

1.11: Dialogue Social Enterprise It is a social enterprise operating worldwide. Its mission is to facilitate social inclusion of disabled, disadvantaged and elderly people on a global basis. Disability is a rising issue and demographic change is considered to be a mega trend. The number of people with disability is growing due to an aging population and an increase in chronic illnesses related to higher life cycle expectancies. The construction of social enterprise is ongoing, and fought by a range of actors promoting different languages and practices tied to different political beliefs. That is, social enterprise is politically contested by different actors around competing discourses.

1.12: Need for Entrepreneurial Class The age of classical agriculture is facing a sharp redundancy and will be losing relevance in a shorter frame of time unless in is uplifted to a level of income and livelihood generation (Acharya et.al,2015). Balanced development of a country, extension of the benefits of economic progress to the backward areas and widespread diffusion of industrial units are the important dimensions of planned development. Experience of less developed countries also shows that their efforts for achieving the balanced regional development would not succeed until such time they are able to initiate a widely diffused, yet viable industrialization process which demands for promotion of new entrepreneurship, a vital factor of production for the success of any adventure. Some potential entrepreneurs prefer their own business in place of their successful careers in other organizations.

1.13: Need for Technical Business Incubators Technical Business Incubators (TBIs) have evolved from the convergence of two global movements, namely, the recognition that small and medium enterprises are the instruments of economic growth and the accelerated pace of technical change. Technical Business Incubators are making a significant contribution to the economic development of various nations and era of it has just begun in India as well. In India, however, Technical Business Incubators are associated with and are aided and supported by centres of Educational and Technological excellence. Technical Business Incubators model has a great scope for creation of a new generation of entrepreneurs, who in turn would provide jobs and generate national wealth as well. (Schumpter, J.A.1934)

6

Entrepreneurial Communication in Agriculture

1.14: Entrepreneurial Process: The Stages (i) Task presentation (ii) Preparation (iii) Incubation (iv) Idea Generation (v) Verified Idea Validation (vi) Outcome Assessment (M.C. Gupta, 1987)

1.15: Entrepreneurial Behavior (i) Information Seeking Here the entrepreneur becomes inquisitive to seek more and more information to start a new business/venture. (ii) Information Processing Then the entrepreneur process the information gained and generate a database which will be beneficial to run the business. (iii) Information Disseminating After processing of information, the piled up information is disseminated to the outer sources, which will be beneficial for the business and the new initiatives.

1.16: Role of Incentives and Subsidy for Encouraging Entrepreneu-rial Behaviour Incentives are motivational forces which improve productivity of entrepreneurs. They enable the entrepreneurs to take appropriate decision and give capacity to implement them. In practice, incentives are concerned with actions to encourage productivity. Incentives include three variables, concessions, subsidies and bounties. (Gupta. C.B., and Khanka, S.S., 2000)

1.17: Conceptual Framework of Entrepreneurship Entrepreneurship “involves combining to initiate changes in the production”. Entrepreneurship is a discontinuous phenomenon appearing until it reappears to initiate another change. Wilken categorizes five key types of changes: (i) Initial Expansion (ii) Subsequent Expansion (iii) Factor Innovations (iv) Production Innovations (v) Market Innovations (Prashad Awadesh, 1988)

Prologue

7

1.18: New Concept of Entrepreneurs After the execution of financial reforms and the opening up of the economy, the term ‘entrepreneur’ has been defined as the one, who detects and evaluates a new situation in his environment, and, directs the necessary adjustment in the economic system. He is the person who conceives of an industrial enterprise for the purpose, displays initiatives, takes risks, makes determination in bringing his project to the success and in the process, performs one or more of the perceived opportunities, for profitable investments, explores the prospects of starting of manufacturing, obtains necessary industrial licences, etc. (Vasant Desai, 1999)

1.19: Entrepreneurship:Steps of Creative Process (i) Intrinsic motivation The motivation that works within, and , which comes from the inner core and self of an individual. (ii) Skills in the task domain Delineation and acquisition of skills in terms of task domain. (iii) Skills in creative thinking Which deals with innovation and creativity, including out of the box thinking?

1.20: Need of The Study With this background, the present research, as being designed with the above stated topical expanse, have envisaged to study the entrepreneurial communication and its process, factors and impact in agriculture and allied sectors in Tripura and West Bengal. There is a need to generate comprehensive micro, small and medium enterprises through proper entrepreneurial communication. Different endeavour has been taken from the Pre-Independence era to uplift the economy of the rural poor. But till now livelihood security is a burning issue. Now the situation demands diversification of agriculture and allied sources through Integrated Farming System to secure livelihood, along with entrepreneurship.

1.21: General Objective To study the “Entrepreneurial communication: The process, factors and impact in agriculture and allied sectors of selected blocks of Tripura and West Bengal”.

1.22: Specific Objectives (i) To conceptualize the premise and perspectives of farm entrepreneurial communication with special reference to Tripura and West Bengal. (ii) To elucidate the variables characterizing the level of entrepreneurial communication as dependent variable as against a set of exogenous variables, agro-economic and socio-ecological nature.

8

Entrepreneurial Communication in Agriculture

(iii) To estimate the level of interaction between level of entrepreneurial communication and the sets of exogenous variables selected for the proposed study. (iv) To organize participatory learning action and analysis on the scope and status of entrepreneurial communication and community level. (v) To generate micro level policy implication for the research locales resultant to the empirical study. 

Chapter

2

REVIEW OF LITERATURE 2.1: Concept of Review of Literatures The Review of literature is a systematic, explicit, and reproducible method for identifying, evaluating, and synthesizing the existing body of completed and recorded work produced by researchers, scholars, and practitioners. The Review of literature is also a resource paper, which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic. These are available mostly in academic and scholastic journals. Review of literature provide the basics for research in nearly every academic field. The aim of review of literature is to highlight what has been done so far in the field of interest and how our findings are related to earlier research. The review of literature also indicates the following by providing referential inputs. (i) Approaches (ii) Methods (iii) Variables used (iv) Statistical procedure (v) Expected results

2.2: Contributions of Review of Literature (i) Provides theoretical background to our study. (ii) Helps justify how our findings are related to our body of knowledge in our field of research. (iii) Establishes a link between what we propose to study and what has already been found. It helps us to refine our research methodology.

2.3: Concept of Entrepreneurship Entrepreneurs are a product of the particular social conditions in which they live, and it is the society which shapes the personality of individuals as entrepreneurs, stated by According to Weber (1930).

10

Entrepreneurial Communication in Agriculture

According to Cole (1949), Entrepreneur represents an individual or a group of individuals, who conceive, initiate and maintain for a sufficiently long period of time a social institution which produces economic goods or to put it differently. According to Richard Cantillon (1955), the concept has some analytical treatment and assigned the entrepreneur an economic role by emphasizing on ‘risk’ as a prominent entrepreneurial function. According to Diamond (1957), entrepreneurship is equivalent to “enterprise” which involves the willingness to assume risk in undertaking an economic activity particularly new one it may involve an innovation but not necessary so. It always involves risk taking and decision-making, although neither risk nor decision making may be of great significance. It was observed by Hostelits (1957), that entrepreneurship was associated with personality pattern in which achievement motivation was strong. But the presence of strong achievement motivation in a group of individuals did not necessarily produce an abundance of entrepreneurs unless certain other conditions of social structure and cultural strongly favour achievement oriented individuals. Cole (1959), described entrepreneur as decision maker and indicated the following functions of an entrepreneur: (i) The determination of those objectives of the enterprise and the change of those objectives as conditions required or made advantages. (ii) The development of an organisation including efficient relationship with subordinates and all employees. (iii) The securing of adequate financial resources the relation with existing and potential investors. (iv) The requisition of efficient technological equipment and the revision of it as new machinery appeared. (v) The development of market for the products and devising of new products to meet or anticipate consumer demand. (vi) The maintenance of good relationship with public authorities and with society at large. An entrepreneur was a dynamic agent of change, or catalyst who transformed increasingly physical, natural and human resources into corresponding production possibilities, stated by Schumpter (1961). According to Schumpter (1961), if a person is starting a new organisation, developing it or expanding it, the very act of understanding these activities qualifies him to be called entrepreneur. David (1962), opined that the prime motive of the entrepreneurs was to accumulate and without motive there should be no accumulation to facilitate capital formation and economic development. Entrepreneurs universally acknowledged as new men, provide the industrial push to a society and project it in to the path of economic growth and modernisation.

Review of Literature

11

Hagen (1962), described the entrepreneur as a creative problem solver interested in things in the practical and technological realm most entrepreneurial activities do not involve innovative techniques to any considerable degree but rather involve coping with the method of doing business and of combining inputs quite similar to those combinations already in existence. According to Harbison and Hyers (1964), capital cannot itself produce anything. It must be harnessed for producing goods and the capital goods into harnessed for producing consumer goods and this investment process requires the services of some agent or intermediary who initiates, organises, makes decision, takes risk, innovates and sometime also manages. According to Cole (1968), the term entrepreneur represents an individual or a group of individuals who conceive, initiate and maintain for a sufficiently long period of time a social institution which produces economic goods or to put it differently, who perceive a business opportunity and create an organisation to pursue it. Hegan (1968), concluded that entrepreneurship is not only the conceiving of the idea behind a venture but also designing and maintaining the organisation for carrying it out. According to Schumpeter (1970), entrepreneurship is: (i) A function of group level pattern. (ii) A function of managerial skill and leadership. (iii) An organisational building function. (iv) A function of high achievement. (v) Input-completing and gap filling. (vi) A function of status withdrawal function. (vii) A function of social, political and economic structure. Nandi (1973), found that for successful entrepreneurship, a high need for independence and a high need for influencing other is required. According to Joshi and Kapur (1973), farm entrepreneur is the person or a group of persons who organises and operates the business and is responsible for the results i.e. losses and gains from the business and is pioneer in organising and developing the farmers. Bhatt (1974), described at broad level the entrepreneurship in social organisation as a highly complex process. It is the result of interaction of various characteristics like natural endowments, historical traditions, educational and cultural standards, and social stratification, religious and moral values, and family organisations development at any given period of time. According to Leeds and Stainton (1978), entrepreneur as a person who initiates production, takes decision bears risks and involve in organising and coordinating the other factors.

12

Entrepreneurial Communication in Agriculture

Pareek and Nadkarni (1978), defined entrepreneur as one who initiates, establishes an economic activity or enterprise. Entrepreneurship thus refers to the general trend setting up new enterprise in a society. Operationally entrepreneurship development could mean development of entrepreneurs and promotion of increased flow of individuals to entrepreneurial ranks. Gaikwad (1978), stated that, entrepreneurship connotes innovativeness, an urge to take risk in face of uncertainties, and intuition i.e. a capacity of seeing things in a way which afterwards proves to be true. Rao and Mehta (1978), observed that, entrepreneurship can be described as a creative and innovative response to the environment. Such response can take place in any field of social endeavour-business, industry, agriculture, education, social work and the like. Being new things or doing things that are already being done in a new way is therefore, a simple definition of entrepreneurship. Entrepreneurship is also a package of personality characteristics of entrepreneurs. Haredero (1979), described agricultural entrepreneur as a person who introduces changes which directly or indirectly lead to higher agricultural inputs. Kirzner (1979), stated the entrepreneurs as performing various functional roles as risk takers, decision maker, organiser or coordinator, innovator, employer of factors of production, gap seeker and input completer, arbitrageur. According to him, entrepreneur being alert to economic opportunities uses information advantages for his own profits. According to De (1981), Entrepreneurship is a package of personality characteristics of entrepreneurs. The characteristics conventionally associated with entrepreneurship – leadership, innovativeness, risk taking and so on- are so associated precisely because in a profitable farming culture, they are essential features of effective farm business. Massie (1982), stated that entrepreneur means a risk taker one who promotes a business activity. It can be concluded that the South-East Asian Countries in their efforts for developing agriculture have provided some areas of their countryside with better infrastructure in relation to other area’s irrigation, communication, and cooperative institutions. Some farmers have responded to the new enterprise commonly associated with the use of fertiliser, pesticides better than other farmers in these areas of those countries. The farmer group of farmers were known as agricultural entrepreneur, opined by Bhattacharya (1983). Carland (1984), stated that nature or intensity of entrepreneurship would depend on the intensity of the complete set of behavioural dispositions related to being an entrepreneur. According to Drucker (1985), entrepreneur is one who always searches for change, responds to it, and exploits it as on opportunity. Entrepreneurs innovate and innovation is a specific instrument if entrepreneurship. De (1986), observed that a farmer does not become an entrepreneur only by adopting a new agricultural technology but he becomes an entrepreneur only

Review of Literature

13

when he comes to be an operator of a farm business. A business involves rational decisions on investment after assessing risk, other alternatives and possibilities or profit and loss. An entrepreneur is a dynamic agent of change or the catalyst who increasingly transforms the physical, natural and human resources into corresponding production possibilities. Singh (1986), stated that those were the concepts of individuals who grasped an idea, developed it and perused its success doggedly with unflagging spirit. These individuals were entrepreneurs or the man who organises the business unit and increases its productive capacity. It was observed that women took up entrepreneurship to fulfil economic needs and to satisfy some of their personal needs like power and achievement and to gain a novel experience, opined by Rani (1986). Singh (1986), stated that doing new things or doing things that are already being done in a new way is entrepreneurship. It was revealed by Vemze (1987), that emergence of entrepreneurship depends on certain personality traits. The traits and attributes like involvement, decision making, access to and control over resources, calculated risk taking, innovativeness, need for achievement, placing family and friends second to business etc. increase probability of an entrepreneur emerging out successful and therefore, should be possessed by them to be able to perceive an opportunity and translate that into productive enterprise. According to Morky (1988), entrepreneur as “a symbol of individualism and mysterious link between idea and product, has gained visibility as attention on began to focus on innovation competitiveness and productivity. According to Himachalam (1990), importance of development of entrepreneurship as an ingredient of economic development has been recognised long time back. It was as early as in 1950 that the need for entrepreneurial behaviour development was first felt and since then substantial amount of research has been done in this sphere. It was observed by Shailendra (1990), that a rural entrepreneur is someone who is prepared to take risk for self-betterment but is also willing to give of himself for the community by staying and creating local wealth. According to Stevenson and Jarillo (1990), entrepreneurship is a process by which individuals either on their own or inside organisations pursue opportunities without regard to the resources they currently control. Stevenson and Jarillo (1990), observed that entrepreneurship literature can be identified to address by and large three main questions. (i) What happens to the business and the economy when entrepreneurs act? i.e. the outcome of entrepreneurial activities. (ii) Why do they act as entrepreneur? i.e. the cause of entrepreneurial action of individuals.

14

Entrepreneurial Communication in Agriculture

(iii) How do they act as entrepreneurs? i.e. the process of entrepreneurship. Entrepreneurship broadly involves identification of market opportunities and innovative creation of combination of resources for altering the aggregate economy. Bisht and Sharma (1991), stated that increased production and small industry strategy is obviously the outcome of human activity. Human activity in this context is known as entrepreneurship. Bisht and Sharma (1991), stated that economic development is the outcome of production or industrialisation, and production or industrialisation leads us to man-known in the business world as an “Entrepreneur” the change producing force in economic life. Entrepreneurs are the persons who initiate, organise, manage and control the affairs of a business unit that combine the factors of production to supply goods and services, whether business pertains to agriculture, industry, trade or profession. It was concluded by Covin and Slevin (1991), that entrepreneurship is a firm behaviour. According to Gartner et al. (1992), and Learned (1992), Entrepreneurship is a phenomenon of emergence; it evolves overtime. Gupta and Srinivasan (1992), had come to the conclusion that entrepreneurship is described as the function of handling economic activity, undertaking risk, creating something new and organising and coordinating resources. Singh (1992), concluded that important business motivation for women is the need to provide security and to the family. Women entrepreneurs are often motivated by the desire to have flexibility in their work and family. The major sources of motivation for women could thus be need to achieve, desire to be independent, need for job satisfaction, economic necessity, desire to make use of one’s talent or skill and the desire to be one’s own boss. According to Bull and Willard (1993), entrepreneurship is the carrying out of new combinations causing discontinuity. It was proposed by Mall (1993), that entrepreneurship is an important factor in economic development. It is now widely recognised. While economic development depends largely on the rate of applied technical advancement, innovation and the level of technical progress in the economy, indicating applied technical advancement depend on the supply of entrepreneurs in society. Jyothi and Prasad (1993), stated that an entrepreneur is that person who puts together resources and takes great strain to start a new business venture. Entrepreneurship in an individual is to productively integrated resources and enhances economic growth. Need for achievement (n-Ach) as the factor that instigates people to be entrepreneurial and venture into innovative and productive activities is enhancing economic growth. Entrepreneurship is that factor which urges an individual to take advantage of favourable situations by understanding

Review of Literature

15

innovative practices with a concern for excellence and assessment of self and the environment. Entrepreneurship is a way of life, a thought process to bring any sustainable change; effort has to be broader based, stated by Thomas and Padmakar (1993). According to Ali (1995), entrepreneurship is considered to be process with entrepreneurs making the links between opportunities and resources. According to Gopakumar (1995), an overview of literature pertaining to concept of entrepreneur is absolutely essential. The word entrepreneur is derived from French word “Entreprendre” and the German word ‘Unternehmen’, both mean “to undertake”. For a long time, there was no equivalent for the term ‘entrepreneur’ in the English language. Three words were commonly used to connote the sense the French term carried: adventurer, undertaker and projector; these were used interchangeably and lacked the precision and characteristics of a scientific expression. Hence the term ‘entrepreneur’ did not find any prominence in the history of economic thought. Khanka (1995), stated that making the entrepreneurship is a complex phenomenon. This is a crystallisation of social milieu from which entrepreneurs come, family imbibes make up of their minds, personal attitudes, caste system, educational background, family occupation and so on. In fact, several factors go in to the making of an entrepreneur and thereby entrepreneurial society. These are grouped under three major headings: Stimulation; Support and Sustaining. According to Pareek and Rao (1995), entrepreneurship is not only a career but also a way of life. A person taking up this career undergoes a transformation in his or her life style. Entrepreneurship would lead to generation of more income, reduce unemployment/underemployment, minimise incidence of poverty, reduce regional imbalance and promote export trade. This is the area which can provide self-employment to illiterate, literate, semiskilled men and women. Entrepreneurs in rural areas, may they be men or women, can now very well, through adoption of new agricultural strategy/technology, not only improve the productivity and production of rural resources (viz, land, labour. Livestock, vegetation, forestry, water, fisheries, fruits, flowers, vegetables, milk, mushrooms sericulture etc.) but also enhance income substantially, beyond one can expect. Hi-tech projects in the area of aquaculture, floriculture, micro-irrigation, bio-fertiliser, embryo-transfer technology etc. have established their unique place in the wake of liberalisation and globalisation of Indian economy, stated by Patel (1995). According to Sundari (1995), an entrepreneur is a person who organises, runs and is responsible for a business enterprise to make a profit. In the process, he/she has different roles to play and differentiation to take. Bankston and Zhou (1996), examined the development of the fishing industry as a factor for ethnic entrepreneurship among the Vietnamese in using 1980 and 1999 census data. Findings demonstrated that the fishing industry became a major occupational concentration of Vietnamese, 1980 and 90, and self-employment in this new ethnic group increased sharply during the decade. This extractive industry

16

Entrepreneurial Communication in Agriculture

also became largest single source of self-employment for Vietnamese, since 33.4 per cent of all self-employed Vietnamese were in fishing, and 66% of those were self-employed. Acording to Busenitz (1996), entrepreneurs are more alert to new opportunities and use information differently. It further indicated that entrepreneurs make a habit of scanning their environment for information that may lead to new business opportunities. Entrepreneurship was a method of stimulating innovation and using he creative energy of employees by giving them the resources and independence they needed to innovative within the firm or the introduction and implementation of a significant innovation by one or more employees working within an organisation, stated by Carrier (1996). It was observed by Jhamtani (1996), that entrepreneur is a person who organises, manages and assumes the risk of a business entrepreneurs are self- employed and income generating persons. But all self-employed and income generating persons may not necessarily be self-employed. According to Jhamtani (1996), entrepreneurship refers to identifying innovative ideas, product and services, mobilising resources, organising production/services and finally marketing those covering the risk with constant strive for growth and excellence. Lumpkin and Dess (1996), stated that entrepreneurship constituted new entry. The strategic role of the entrepreneur in the current economic and socio cultural context. A complex and articulated entrepreneurial function has come to play a crucial role in modern enterprise, particularly in public companies with many shareholders, specified by Pollo (1996). Prasad (1996), concluded that the objective of the entrepreneurship development agency (EDA) was to promote general awareness among the rural masses about setting up a small business or it might be to attract a specific target group like women for an entrepreneurship development programming (EDP). According to Ray and Rama Chandran (1996), entrepreneurship is an individual’s response to a situation i.e. the environment around him, and the creation of an organisation is essential for carrying through of that response, the entrepreneur, the environment and the organisation must be regarded as crucial elements in a nay frame work relating to entrepreneurship. There has been rapid globalisation of the Indian economy, so much so that growth and prosperity on the years ahead call for a totally new breed of managers. We now need manager entrepreneurs, not manager administrators. It has become essential for professional management training institutes to impart new skills to manager who will have to be more people/customer oriented rather than boss oriented. They will have to identify themselves the quality rather than quantity, specified by Agarwal (1997).

Review of Literature

17

According to Banerjee and Talukdar (1997), entrepreneurship means a quality destined to increase production spontaneously. Patel and Sanoria (1997), stated that, entrepreneurship is a form of human behaviour and this in turn is a manner of acting of an individual in a given situation to achieve certain results. Entrepreneurship is the propensity of mind to take calculated risks with confidence to achieve a predetermined enterprise objective. In instance, it is risk taking ability of the individual broadly coupled with rational decision making to increase production in agriculture business, industry etc. Richart and Maurer (1997), stated that, entrepreneurs are defined as those individuals who have started or purchased a small business and who are still leading the business they started or purchased. According to Scott (1997), entrepreneur is one who takes risks to initiate business activity. Khanka (1998), opined that who has an urge to do (or) create something new, organise production, undertake risk and handle the economic uncertainty involved in running enterprise is called entrepreneur. The set of such attributes the entrepreneur possesses is called entrepreneurship. Entrepreneurship refers to enterprising or achieving attitude. Krishnan and Kumar (1998), defined entrepreneurship as buying labour and materials at uncertain prices and selling the resultant output at contracted prices. Manimala (1998), concluded that the entrepreneurial process involves organising scarce resources from the environment. Personal networks are an important means for the entrepreneur to secure such resources. Entrepreneurs make use of their personal and professional networks. The analyses of the anecdotes are grouped as: Search for new ideas; Expertise development; Mobilising funds; Organising for the initial production; Marketing through networks; Acquiring/developing people; Building the corporate image; Management of risk and Management of growth. Manimekalai (1998), opined that entrepreneurship development among the rural labour force would strengthen the village economy, promote regional development, bring job diversification, and relieve the dependence on agriculture. The small scale agricultural production in Trichy district was becoming increasingly unprofitable due to the continuing drought and large scale agricultural production has been transforming itself into agro business in Trichy district. All these suggest that, there has been a need for self-employed industrial employment as agriculture fails to support the dependent population. Prakasam (1998), concluded that the entrepreneur, being an economic man aims to optimise his profits through innovative means. He has a will to act, is ready to assume risk and to organise human resources for production of foods and services which in turn generate and multiply economic and social activities that induce change in the area and in the society. Ramachandran and Ray (1998), described the typology of entrepreneurs based in the outcome of entrepreneurial ventures. Empirical evidence suggests that existence of following four types of entrepreneurs:

18

Entrepreneurial Communication in Agriculture

(i) Mobile Entrepreneurs: They are the persons who leave the ventures as soon as venture is created. They are the true Schumpeterian entrepreneurs, as according to Schumpeter (1934) the entrepreneurial activity ends as soon as the venture is created. As for example, Ted Nierenberg, founder of Dansk designs in the US, Mohan of Good Knight and Vikram Sarabhai both from India comes closer to this type. (ii) Managerial Entrepreneurs: They are the persons who prefer to continue in the same venture by transforming themselves to fit the changing demands. As for example, persons like Henry Ford of Ford Motors, Pierre S Du Pont and George Eastman of Kodak. (iii) Innovative Entrepreneurs: They are the persons who created an organisation and remain engaged in their pursuits of innovation and creation of novel products and technology. As for example, Walt Disney, Ibuka and Akio Morita of Sony Corporation, Sochiro Llinda of Llinda motor company and Bill Gates of Microsoft, are some of the notable entreprenuers belonging to this type. (iv) Empire Builders: They are the persons engaged in creating chain of new ventures having an ownership. They have the qualities of vast vision, flair of innovation and managerial capability to build an empire for themselves. As for example, John D Rockefeller of the US, J N Tata and Ghanshyam Birla, both from India, Konosuke Matsushita of Japan and Chung Ju Yung of Hyundai and Kim Woo Chong of Daewoo, both from South Korea are the entrepreneurs belonging to this type. An entrepreneur is an economic leader who possess the ability to recognise opportunities for the successful introduction of new commodities, new techniques and new source of supply, and to assemble the necessary plant and equipment, management and labour force and organise them into a running concern. Whatever be the economic and political set up of a country, entrepreneurship is essential for economic development. According to them entrepreneur as a recipient of pore profit and is bearing the cost of uncertainty and identifies uncertainty with a situation where the probabilities of alternative outcomes cannot be determined either by a prior reasoning or by statistical inference. A prior reasoning is simply irrelevant to economic situation involving a unique event or the entrepreneur is the prime mover in economic development his function to innovate or carry out new combinations or entrepreneurs are individuals motivated by a will for power. Their special characteristic being an inherent capacity to select correct answers, energy, will and mind to overcome fixed talents of thoughts and a capacity to withstand social opposition, stated by Ramana and Papaiah (1998). According to Ripsas (1998), entrepreneur is a bearer of uncertainty who is compensated for by the residual income called profits. According to him, primary function of the entrepreneur is to decide what to do and how to do it without being certain about possible future benefits but according to Schumpeter entrepreneur is not the risk bearer but the driving force in economic development from within the economy: According to him entrepreneurship as the carrying out of innovations.

Review of Literature

19

For an entrepreneur the motivation is intrinsic and not driven by the desire to make profit. Farm household productivity was a major factor in enabling the survival of small scale agricultural production. Many farm businesses combine agricultural production with other income generating activities and such multiplicity of activities have always been an important and distinctive feature of the farming sector. That’s why the farer must be treated as a part of rural entrepreneurial class, concluded by Sara (1998). Wick (1998), stated that entrepreneurship refers to the intentional creation or transformation of an organisation for the purpose of creating or adding value through organisation of resources values added by entrepreneurial behaviour result in increases in personal wealth, increases in cash flow for a region, new or better jobs and new or better products or services. Entrepreneurs are defined as those people who work for themselves are called “entrepreneurs”. The word entrepreneur is derived from French word “Entreprendre” meaning “Undertake”. The entrepreneur is thus a person who organises and manages in an activity/organisation, undertaking the risks for fulfilling some of his needs, his job involves the quality of boldness, courage, dynamism and risks taking in sufficient measure. The entrepreneur in this context is defined as one who could start a new activity or a new enterprise which is a deviation from his traditional family occupation or profession, stated by Ramana (1999). According to Ramanna (1999), entrepreneurship is a purposeful activity indulged in initiating, promoting and maintaining economic activities for the production and distribution of wealth, the individual as an entrepreneur is a critical factor in economic development and an integral part of socio-economic transformation, therefore, the basic concept of entrepreneurship connotes effectiveness, an urge to take risks in the face of uncertainties and intuition.

2.4: Concept of Entrepreneurial Behaviour Parsons and Shills (1951), proposed a theory of action which assumes that the actor strives to achieve goals. The theory of action is conceptual scheme for the analysis of behaviour of living organisms. There are four points to be noted in the conceptualisation of behaviour: Behaviour is oriented to the attainments of end or goals or other anticipated states of affair; It takes place in a situation; It is normatively regulated and It involves expenditure of energy or effort or motivation. According to Legans (1961), behaviour is response to stimuli refers to what an individual knows (knowledge), what he can do (skill), mental and physical, what he thinks (attitude) and what he actually does (action). Calder and Ross (1976), stated that behaviour was a function of many personal factors - motives, habits, attitudes, and so on - and of many environmental factors, such as norms, laws, rewards and punishments. Behaviour is a function of continuous process of multi-directional interaction between the person and the situations, including other persons that he or she encounters, according to Fisher (1982).

Entrepreneurial Communication in Agriculture

20

Behaviour was a function of its consequences and found that people would most likely engage in desired behaviour if they were rewarded for doing so, these rewards were most effective if they immediately followed the desired response, and behaviour that was not rewarded, or was punished, was less likely to be repeated, reported by Robbins (1996).

2.5: Entrepreneurial Behaviour and Social Ecology Fishbein (1965), reported that entrepreneurial behaviour was a function of the surrounding social structure both past and present, which could be readily influencing by manipulability economic and social incentives. Mc Clelland (1965), stated that casual sequences of entrepreneurial behaviour were as follows: Ideological values – Family socialisation – need for achievement – E.B. Javillionar and Peters (1973), listed three dimensions of entrepreneurial behaviour viz.: Risk taking ability; Novel or energetic instrumental activity and Individual responsibility as indicators of entrepreneurial performance. According to Rao (1985), entrepreneurial behaviour is the result of an interaction of individual, situational, psychological, social and experiential factors. Singh (1986), stated that entrepreneurial behaviour (EB) was a function of an individual’s personality characteristics and environmental factors. This could be represented as EB = f (PE) ; where, P = Personality characteristics E = Environmental factors Manjula (1995), stated that entrepreneurial behaviour was the change in knowledge, skill and attitude of entrepreneurs towards the selected enterprise. Patel and Sanoria (1997), stated that the activity of and individual to decide for adopting certain enterprise to make profit was regarded as entrepreneurial behaviour. Paul (1998), revealed that majority of respondents in all the groups of small (65%), medium (50%) and big farmers (55%) had medium entrepreneurial behaviour whereas low entrepreneurial behaviour constitutes more among small farmers (22.5%) and medium farmers (32.5%). The high entrepreneurial behaviour (32.5%) of big farmers might be due to their sound financial condition to take risk and adopt new technologies and also more innovativeness and leadership abilities.

2.6: Dimensions of Entrepreneurial Behavior Murry (1938), conceived achievement motivation as a desire ordendency to do things rapidly and or as well as possible. For specified the desire as to accomplish things something difficult to master, manipulate or organize physical objects, human beings or ideas to overcome obstacle and attain a high standard, to excel one-‘s self to rival and surpass others.

Review of Literature

21

Edwards (1954), while dealing with the theory of decision making, explains that the crucial factor about economic man is that he is rational. This means two things, can weakly order that states into which he can get and he can also make his choice so as to maximize something. He further states that the fundamental content of the maximization is that economic man always choose the best alternative from among those open to him, as he sees it. He also defined achievement motivation to do one’s best, to be successful, to accomplish tasks requiring skill and efforts, to be recognized authority and the like. Entrepreneurship was associated with personality pattern in which the achievement motivation was strong. But the presence of string achievement motivation in a group of individuals did not necessarily produce an abundance of entrepreneurs unless certain other conditions of social structure and culture strongly favor achievement oriented individual to enter economic pursuits, stated by Hoselitz (1957). English and English (1958), defined knowledge as a body of understand information possessed by an individual or by culture. Knowledge is generally understood as intimate acquaintance of an individual with facts. According to Atkinson and Litwin (1960), persons with high need to achieve, by and large tend to take moderate risks i.e. they do not avoid risk and also that they do not like situations and commitments where the probability of desired outcome is very low. This behavior emanates from a conflict between “hope of success” and “fear of failure” resulting a positive net balance of hope and success. Entrepreneurial behavior flourishes where absolute certainty of both success and failure is absent. Fraser (1961), conducted an investigation on small line entrepreneurs in a rural village in Orissa and found that people with high need achievement showed more entrepreneurial spirit and less involvement in traditional cultivation of the soil than those with low n-Ach. According to Mc Clelland (1961), achievement motivation is the individual need or desire to perform or to do better not so much for the sake of social recognition or prestige but to attain an inner feeling of personal accomplishment and proposed a model of achievement motivation, usually referred as A-T-D model. This model in brief, can be explained as that a rise in the level of n-Ach (A) in society will be associated with a rise in the rate of development (D) with a time lag (T) which will be always positive. Neill and Rogers (1963), considered achievement motivation as the value instilled in an individual through the sociological process in which the individual feels a need or desire to excel in reaching certain goals only for the satisfaction of reaching goal and not for rewards of the goals or ends involved. Farmer’s achievement motivation leads to the individual excellence in farming. They found significant correlation between need for achievement of Ohio state farmers (U.S.A) and some of the indicators of excellence in farming such as production man work units, man days of labor on the farm and number if acres in the farm. Kogan and Wallach (1964), stated the decision making involves the weighing of alternatives in terms of their desirability’s and their likelihood issues concerning

22

Entrepreneurial Communication in Agriculture

the avoidance and acceptance of risk in arriving at decisions hence are likely to be importance ingredients in things process. Rogers and Neill (1966), reported correlations between n-Ach scores and agricultural innovativeness in farming communities in both India and Columbia. The correlations were significantly positive in six out of eight Indian farming communities yielding or a total correlation for all individuals of 0.32 (N=702). Among 302 farmers in six different villages in Columbia the average correlation was 0.18 indicating that farmers who think about doing better (high n-Ach) do in fact respond more to greater opportunities by adopting new farm practices. Subsistence farmers responded as quickly to economic stimuli as the most commercial farmers in the modern world and it was precisely those with high achievement who were responsible to economic stimuli and who found ways of making a better living at farming from adopting new practices, observed by Wharton (1966). Mc Clelland (1969), stated the characteristics/dimensions of entrepreneurs as follows: Need achievement; Desire for responsibility; Preference for moderate risk; Perception of probability of risk; Stimulation by feedback; Energetic activity; Future oriented; Skill in organizing and Attitude towards money. Rogers and Svenning (1969), defined achievement motivation as a spontaneously expressed desire to do something well for its own sake rather than to gain power or love or recognition. They concluded that farm production was positively related to achievement motivation. Innovativeness is the degree to which a individual adopts new ideas relatively earlier than others in his social system. They further stated that innovativeness was one of the most important indicators of farm excellence. The adoption of technological innovations indicated one way in which a peasant could improve. Sharma (1970), concluded that self-confidence was considered as one of the important characteristics of entrepreneurs. Singh (1970), pointed out that mean n-Ach scores of the business entrepreneurs were statistically high than the agricultural entrepreneurs. Basavanna (1971), stated that self-confidence was a consistent behaviour pattern which revealed that one has faith in one’s abilities. Support system for developing entrepreneurial capabilities assumed considerable importance. Further, they stated that a business enterprise had internal and external managerial functions and it was the external managerial role that assumed crucial importance, particularly in relation to the procurement of finance, raw material and marketing of products, stated by Basu and Moulik (1971). Hornaday and Aboud (1971), reported that need fir achievement, support; independence and leadership were the most significant entrepreneurial characteristics. Kilby (1971), indicated that one of the integral parts of entrepreneurial behaviour was introduction of new products or new technology.

Review of Literature

23

Rogers and Shoemaker (1971), reported that innovations were more likely to have a commercial rather than a subsistence economic orientation, they had more favourable attitude towards risk, high level of achievement motivation, greater exposure to change agent, mass media, sought more information, and had a greater knowledge of innovations. Knowledge of farmers with reference to adoption of innovation divided knowledge into three types: Awareness- knowledge, how-toknowledge (information necessary to use knowledge) and principles knowledge (Functioning principles under lying innovations). Singh and Singh (1971), stated that successful farm entrepreneurs made better use of resources. Hence it was expected that utilisation of available resources by farmers was likely to be related to their farming performance. Business entrepreneurs had high score on need for achievement and risk taking when compared with agricultural entrepreneurs. Progress entrepreneurs had moderate risk taking. In a study on risk taking ability of farmers they found that progressive agricultural entrepreneurs exhibited moderate risk taking scores further observed that positive but not significant trend of relationship was found between anxiety and risk taking scores in case of successful agricultural entrepreneurs, whereas significant reverse relationship was found in case of unsuccessful agricultural entrepreneurs. Sinha and Mehta (1972), indicated that the middle land holders showed greater motivation to achieve and greater readiness to change than both smaller and bigger land holders. They also found that younger farmers were better disposed to achieve and change irrespective of size of land holding. The results identified a curvilinear relationship between size of holding and n-Ach and change proneness. Javillionar and Peters (1973), reported three dimensions of entrepreneurial behavior viz., risk taking ability, novel or energetic instrumental activity and individual entrepreneurial performance. Singh and Pal (1974), observed significant association between n-Ach and socio economic status of the farmers. They also found that achievement motivation was significantly correlated with education but not land size. The result of the study also indicated that the respondents belonging to progressive and non progressive villages significantly differed in their achievement motivation. Battacharjee and Akhouri (1975), indicated that propensity to take risk was found significantly associated characteristic of entrepreneurs. Often it is compared to gambling in India, since farmers have to face so many risks and uncertainties in their day to day agricultural operations. Some of the uncertainties that effect the farm production can be weather variations – failure, excess, untimely, attack of pests and disease, adulterated, failure of electricity etc., market conditions – low prices and government policies, social responses and values. Hundal and Singh (1975), opined that achievement motivation was particularly associated with farm success. Other characteristics linked with success were intelligence, aspiration to advance, need for power, tender minded temperament, and radial outlook. All these factors except need for power were within the wider concept of achievement motivation. Farmers showed n-Ach, n-power and, n-affiliation in the descending order.

24

Entrepreneurial Communication in Agriculture

Singh and Kumar (1975), while studying wheat farmers in three districts of Uttar Pradesh (India) concluded that achievement motivation of farmers was weakly related to adoption of innovations in wheat cultivation (only two percentage of variance was explained by achievement motivation out of 25% of total variance explained by all the variable included in the study. Sisodia (1976), reported higher motivational intensity within increase in size of land holding. East West Centre (1977), Honolulu, had identified self-confidence as one of the 19 most frequent characteristics of entrepreneurs. The task force also grouped confidence, independence individuality, optimism, leadership, dynamism under self-confidence. Rousmasset (1977), stated that risk and uncertainty arouse because production was not an instantaneous process. Time lapses between when entrepreneurs decide to go in a line of production and when the product finally reaches the market. The entrepreneurs have to assess cost and price and physical performance before he embarks on his enterprise, and these may change with time. People with high n-Ach were known to seek and assume high degree of personal responsibility, set challenging but realistic goals, work with concrete feedback, research their environment and choose partner with expertise in their work, stated by Kanungo and Bhatnagar (1978). It was observed by Rao and Mehta (1978), that the need for independence and the sense of determination were the two chief characteristics that drive the entrepreneurs to start their own business and prefer not to be controlled by others. Further they observed “entrepreneurs are inclined to approach their tasks with a hope of success they attempt any tack in the hope that they will succeed rather than with a fear of failure. Such hope of success enhances their confidence. Singh (1978), in their study of modernization of farmers found that economic motives was most important followed by prestige and recognition, self actualization, innovativeness and affiliation in the decreasing order of importance. It was also observed that achievement motivation was least motive as ranked by the farmers. He also identified that cautious decision making was associated with progressive farm behavior. Ramakrishnan (1979), observed that risk- taking was one of the characteristics of the entrepreneurs. Schwartz (1979), observed that achievement motivation was a potential factor affecting entrepreneurship significantly. Kourilsky (1980), concluded that delineated persistence, academic ability and creativity were critical characteristics. Prasad (1983), stated that decision making ranked second in contributing to achievement motivation of rice growing farmers in Southern states. He also reported that the same variable has taken third place in discriminating between high and low achievement motivation.

Review of Literature

25

Rao (1985), concluded that innovativeness and self-confidence were in second position in explaining variance of entrepreneurial behavior, while predicting farming performance. He also stated that risk taking was positively and significantly related to farming performance. While studying the farming performance of farmers in Andhra Pradesh found significant and positive correlation between farming performance and the entrepreneurial characteristics such as education farm size, cosmopoliteness, caste, training, social participation, knowledge, innovativeness, information seeking, decision making, self confidence, n-Ach, Utilization of assistance, result orientedness and risk orientation. The environmental form conduct is the aggregate and dynamic interaction of those external factors which interact with the entrepreneur, the resultant organization and also among themselves to have an impact on the functioning of the venture. It encompasses the political, economic, legal, social, cultural, demographic, competitive, technological, physical, natural, ecological and all other environment components, according to Tripathi (1985). De (1986), revealed that socio-economic status, education knowledge of HYV of wheat practices, sources of information utilized, innovative orientation and progressive values had positive and significant association with entrepreneur characteristics farmers. Tushman and Anderson (1986), stated that product innovator might involve shifting to new technologies. Harper and Vyakaranam (1988), stated that a shift from a family management to enterprise management might be easier than a shift from paid employment to self-employment. Swamy (1988), concluded that the farmers were most innovative and enterprise migrated early by identifying the existence of income generating opportunities outside the village and provided information for their success. Rao (1989), found significant relationship between innovativeness and income of small, medium and big farmers while studying entrepreneurial behavior characteristics of vegetable growers of Andhra Pradesh. Jyothi (1990), stated that entrepreneurs of Guntur district, about 73 per cent of the sample entrepreneurs were either graduates or post graduates. Downing (1991), concluded that majority of women (69%) independently took their own decisions. Sons (31%) took decisions with the help of spouses, friends or other family members. This pattern of behavior may be common with men entrepreneurs as well. If the family members fail to give relevant advice then a cooperative effort of the staff and other sources are often sought. However, most of the time of final decision is made by the entrepreneurs. According to Shaver and Scott (1991), the need for achievement (n-Ach) is responsible for economic development. Greater the development of n-Ach, during early socialization of people, the more likely that economic development will be achieved. A society with a generally high level of n-Ach will produce more rapid

26

Entrepreneurial Communication in Agriculture

economic growth. Achievement motivation could be inculcated through training in self-reliance, rewarding, hard work and persistence in goal achievement and creating interest in excellence. Ricky (1992), stated that managers were carrying out entrepreneurial roles through which they initiated changes to take advantage of opportunities, although it was common to search for the entrepreneurial personality. Jyothi and Prasad (1993), observed that rural women had little knowledge regarding projects or field of business. They seemed to have limited knowledge of the traditional occupations. Mall (1993), opined that people particularly in backwards areas suffered from low achievement motivation due to socio cultural and institutional factors. Kanungo and Mendonca (1994), stated that entrepreneurs played both the roles of managership and leadership. Managerial role was exhibited by entrepreneur in their capacity as head of the enterprise. They also played leadership role when they were driven by their own vision to innovate or bring in a change in the manager events took place. Leadership behavior had been usually visualized in the context of change. The change might be driven by environmental pressures or values of the leader, but was often related to a vision of a more desirable future state shared by leader and follower. It was observed by Koontz (1994), that entrepreneurs took personal risks in initiating change and they expected to be rewarded for it. They needed some degree of freedom to pursue their ideas; this in turn required that sufficient authority be delegated. Zahir (1994), opined that a large majority of the entrepreneurs (82.5%) were below the age of 40 years. Over half of these (42.5%) were in the age group of 2030 years. These figures support the assumption that the younger generation is relatively more adventurous, prepared to take more risk, dynamic and innovative the characteristics required of a successful entrepreneur. Moreover 30 of the entrepreneur’s understudy (75%) were graduates or above of these, 17 were technically/professionally qualified. New generation of entrepreneurs thus possess better educational qualifications and consider it an important factor for the success of any business venture in the changing environment. Finally, only 2 entrepreneurs (5%) belonged to families engaged in agriculture and allied activities, which show that entrepreneurial development programmes/schemes do not seem to be very effective in decreasing the dependency of Indian people in agriculture. Bell and Pavitt (1995), stated that innovation was treated as development and initial commercialization of new technology. Jha and Shiyani (1995), concluded that different socio economic factors, education status, infrastructural facilities influenced adoption of dairy innovation positively and significantly. Kanungo and Conger (1995), opined that entrepreneur engaged in visioning with a practical bent of mind. A leader’s vision was often idealized; where as an entrepreneur’s vision was more pragmatic and deeply rooted in the environmental

Review of Literature

27

realities representing constraints and opportunities. Hence, he was highly resourceful and innovative, always seeking opportunities to materialize his vision. Keshari and Kota (1995), opined that the entrepreneurial attributes in the presence of economic factors did not have any significant impact on a firm’s propensity to export. Among the economic factors, propensity to export was positively influenced by size and negatively affected by capital intensity. Kumar (1995), stated that entrepreneurs were seen as performing various functional roles as risk taker, decision maker, organizer or coordinator, innovator, employer of factors of production, arbitrageur and allocator of resources to alternative uses. Manjula (1995), concluded that management orientation was positively and significantly related to entrepreneurial behavior of participant and non participant women under DWACRA programme. According to Pareek and Rao (1995), different types of entrepreneurs may have different characteristics. For example, rural entrepreneurs are more likely to be community oriented, less acquainted with business related matters and more dependent. Those who set up business with their own capital may be somewhat different from those who get loans to set up their enterprises. There will also be a difference between the first generation, (new) entrepreneurs and those who come from families with entrepreneurial experience. The enterprise may be small or big but it demands management abilities in its owner/manager. The various facts of management such as production, marketing, financial management etc. are crucial for entrepreneurs, according to Akhouri (1996). Sinha (1996), stated that human factors were central to entrepreneurial effectiveness. Human factors may comprise (a) background and demographic characteristics (b) their beliefs, values orientation and manipulative skills and (c) style of leadership. These factors together play critical role in the birth. Personality characteristics like manipulative skill, achievement motivation, belief in functional values and positive work value played a greater role in the healthy growth of the enterprise. Stoner et al. (1996), stated that certain psychological and sociological factors were characteristics of entrepreneurs. The psychological factors are need achievement, focus control, tolerance of risk, tolerance of ambiguity, lack of viable concept, lack of market familiarity, lack of technical skills, lack of seed capital, lack of business know-how, non-motivation, social stigma, time pressers, legal constraints, monopoly, and patent inhibitions, which are barriers to entrepreneurship. Market contact, local incubator companies, capable local manpower, technical education and support, supplier assistance and credit, local venture capitalists, capable local advisors, education and successful role models were environmental helps to entrepreneurship.

2.7: Framework of Entrepreneurial Venture According to Schumpeter (1970), entrepreneurship is a function of group level pattern, a function of managerial skill and leadership, an organisational building function, a function of high achievement, input complementing and gap filling,

28

Entrepreneurial Communication in Agriculture

a function of status withdrawal and a function of social, political and economic structure. Singh (1986), stated that entrepreneurial behaviour (EB) was a function of an individual’s personality characteristics and environmental factors, it was represented as EB = f (PE); where, EB = Entrepreneurial Behaviour, P = Personality characteristics and E = Environmental factors. According to Learned (1992), the authors believe that many individuals are born with “entrepreneurial DNA” i.e., they exhibit a predisposition to entrepreneurship. In fact, early studies found a strong correlation between entrepreneurial predisposition or propensity and firm start-up decisions (There is a distinct difference between possessing entrepreneurial tendencies and acting on them. Ramana (1999), defined entrepreneurs as those people who work for themselves. The word entrepreneur is derived from French word “Entreprendre” meaning “Undertake”. The entrepreneur is thus a person who organises and manages an activity/organisation, undertaking the risks for fulfilling some of his needs. His job involves the quality of boldness, courage, dynamism and risks taking in sufficient measure. The entrepreneur in this context is defined as one who could start a new activity or a new enterprise which is a deviation from his traditional family occupation or profession. According to Knudson et al. (2004), other researchers have not reached the same conclusion as Jacobowitz. There is a growing number of researchers who eschew to a more dynamic approach to entrepreneurship in which personality traits and subsequent behavior are shaped by a variety of factors including the interaction between personal characteristics, perception, values, beliefs, background and environment. They conclude that the intention to initiate and continue entrepreneurial behavior is influenced by the interaction of various factors. These include individual characteristics, individual environment, business environment, an individual’s personal goal set, and the existence of a viable business idea. Through these interaction factors, individuals make several comparisons between their perceptions of a probable outcome, their intended goals, intended behavior and actual outcomes. Many latent entrepreneurs reach a level of comfort in their jobs and careers that may never result in an outward expression of entrepreneurship, while others grow bored of routine and seek out new challenges. Many entrepreneurs are born out of an “event”. This event could take many forms including: losing one’s job, threat of bankruptcy, loss of a significant other, frustration on the job and discovering a marketplace gap.

2.8: Entrepreneurship and Constrained Environment Kirzner (1973), argued that ownership of capital is not necessary to provoke its movement or change of application. According to Saylor (1987), indeed, an important quality of entrepreneurs is their ability to be creative with limited resources. Ownership of resources is not a mandatory requirement for entrepreneurs to make use of them. Bryant (1989), argues that entrepreneurs are characteristically people who go beyond the limits of resources over which they have direct control.

Review of Literature

29

According to Sexton and Bowman (1991), absence of resources with poor households of developing countries is considered an insurmountable obstacle to developing an entrepreneurial culture. However, availability of resources under control has not been found to necessarily be an impediment to growth and success of an entrepreneur. Bygrave (1994), similarly contends that entrepreneurs find ways to control critical resources without owning them. Advocated by Shane and Venkataraman (2000), our framework emphasizes entrepreneurship as a process in which pioneers for innovation and change, guided not by social norms but by a unique set of creative perspectives, engage in the practice of wealth creation and convert opportunities into performance. Kodithuwakku and Rosa (2002), stated that entrepreneurship is a process by which individuals pursue opportunities without regard to resources they control.

2.9: A 4-P framework of Entrepreneurship Ma and Tan (2006), in an effort to present a more integrated and coherent and comprehensive framework of entrepreneurship, propose a 4 P framework of entrepreneurship. The four major components of entrepreneurship are – Pioneer, denoting entrepreneur as an innovator or champion for innovation; Perspective, denoting the entrepreneurial mind-set; Practice, denoting the entrepreneurial activities; and Performance, denoting the outcome or result of entrepreneurial actions and activities. They defined entrepreneurship as the process in which pioneers, innovators or champions of innovation, immersed in and guided by the creativity-oriented perspective, engaged in the practice of creation and innovation driven activities, which leads to a certain level of performance as indicated by the realized creation and innovation. The specific form of entrepreneurship depends on the patterns of interaction among the pioneer, perspective and practice, whose effects jointly determine entrepreneurial performance. They also identified factors that are necessary but not independently sufficient for entrepreneurship.

2.10: Relationship Among 4 Ps According to Ireland et al. (2001), wealth creation characterises the fundamental mission of entrepreneurship and stands as a critical criterion for judging entrepreneurship performance. Following the convention in the literature, authors treat performance as the dependent variable in building their models. They examine the individual as well as the joint effects of pioneer, perspective, and practice on performance, respectively, in the direct effect model, mediation model, interaction model, and the full model. According to Shane and Venkataraman (2006), it is important to recognise the relationships among those factors that compose entrepreneurship.

2.11: Mediation Effect Schumpeter (1934), suggested that an entrepreneur needs to be innovative, creative, and should be able to take risk.

30

Entrepreneurial Communication in Agriculture

According to Schumpter (1961), an entrepreneur was a dynamic agent of change, or the catalyst who transformed increasingly physical, natural and human resources into corresponding production possibilities. The prime motive of the entrepreneurs was to accumulate and without motive there should be no accumulation to facilitate capital formation and economic development. Entrepreneurs universally acknowledged as a new man, provide the industrial push to a society and project it into the path of economic growth and modernization, stated by David (1962). It can be concluded that entrepreneur is a creative problem solver interested in things in the practical and technological realm most entrepreneurial activities do not involve innovative techniques to any considerable degree but rather involve coping with the method of doing business and of combining inputs quite similar to those combinations already in existence, Hagen (1962). Rao (1975), stated that, any person actively engaged in inventing or developing or expanding or effectively maintaining an organisation is an entrepreneur. If a person is starting a new organisation, developing it or expanding it, the very act of understanding these activities qualifies him to be called as an entrepreneur. According to Bird (1988) and Hamel and Prahalad (1989), it is argued that a strong sense of purpose and intention will help the entrepreneurs enlist commitment and support of stakeholders to implement their entrepreneurial agendas. Jones and Cohen (1990), stated that Innovation was the key factor in entrepreneurship. Innovation, creation of new products, markets, services, sources of supply, or of individual organizations, was viewed as the dynamic force that moved the capitalist system. According to Ghemawat (1991), practically, it is also reasonable to conjecture that entrepreneurs with strong passion and great perseverance will be more committed to their entrepreneurial pursuit. According to Bhagat and Singh (1995), Training intervention had certainly played an overwhelming effect to make the trainees to learn and acquire necessary knowledge and skill required for successful business (An entrepreneur is a person who organises, runs and is responsible for a business enterprise to make profit. According to Morris and Lewis (1995) and Morris and Sexton (1996), It is not surprising that there are rarely studies examining the direct relationship between actual entrepreneurial activities and entrepreneurial performance (e.g., While pioneers and perspective each may have a direct effect on entrepreneurial performance, it could also have a direct effect on entrepreneurial performance, it could also be argued that their effects on performance are mediated by the entrepreneurial practice. That is, pioneer and perspective primarily determine entrepreneurial practice, which in turn determines entrepreneurial performance. According to Collins and Porras (1996), we expect that entrepreneurs who are goal-driven and possessing a clear vision are better at focusing on the essential entrepreneurial activities that are likely to create superior performance.

Review of Literature

31

According to Morris and Sexton (1996), practical reasons in research design and data collection, some variables are often difficult and tedious to capture and measure empirically, including the specific amount, scope and intensity of entrepreneurial actions As such, researchers typically use relevant antecedents of consequence variables, such as entrepreneurs’ personal traits, either theoretically grounded or empirically derived, as necessary surrogates for theory testing. Palmer and Ahiamadu (1997), stated that task oriented and people oriented leadership were really helping as far as the sustainability and prosperity of the public enterprises in developing countries were concerned. The entrepreneurial process involves organization of scarce resources from the environment. According to Carton et al. (1998), entrepreneurship is all about the identification of an opportunity, creation of new organization, and pursuing new ventures. According to Kumar (1998), many small enterprises experienced difficulties in marketing their products and consequently their financial performance suffers. This created the need for developing marketing skills among entrepreneurs. Vijaya and Kamalanabhan (1998), stated that, power, self actualization and achievement motivation were significantly higher in entrepreneurs compare to economic and affiliation motivation. Barringer and Bluedorn (1999), stated that, entrepreneurs are the individuals who can explore the environment, discover the opportunities, and exploit them after proper evaluation. As advocated by McGrath and MacMillan (2000), the discipline of entrepreneurs affects the quality and effectiveness of their entrepreneurial pursuit in that habitual entrepreneurs pursue only the best opportunities. As such, we expect that the relationship between practice and performance will be qualified by the characteristics of the pioneers. Baul et al. (2001), theoretically argued for and empirically demonstrated the indirect effect of personal characteristics of entrepreneurs, such as tenacity and passion, on firm performance through other intermediate variables of entrepreneurial action. De and Rao (2001), stated that, higher the value orientation, marketing facilities, education and socio-economic status lead to higher entrepreneurial behaviour of farmers. Pajarinen et al. (2006), observed that, entrepreneurs with higher academic background are more innovative and will use modern techniques and models to do business. According to Narendra P. and Sharma V.P. (2007), the values of entrepreneurial behavioral index for peripheral and distant poultry farmers were 45.20 and 41.96 respectively. The respondents had excellent degrees of regularity and dedication in their enterprises followed by market orientations, technical background, time management and coordinating ability. Very low levels of goal setting ability,

32

Entrepreneurial Communication in Agriculture

competitiveness, future orientation, challenge acceptance, tolerance to uncertainty/ failure and managerial ability was found among the respondents. It was observed that majority of the poultry farmers had low level of entrepreneurial behaviour with respect to the major components studied. Kuratko (2009), in his book, distinguished between entrepreneurs and small business owners. He highlighted that these two terms are often used interchangeably, but both have a lot of differences in their reaction under certain situations. An entrepreneur aggressively focuses on innovation profit and growth of the enterprise. On the other hand, a small business owner's objective and focus is mostly on managing stable growth, sales, and profits. Polo P. and Frias J. (2010), opined that, the deployment of information and communication technologies (ICT) is crucial for the competitiveness of rural tourism businesses. It is therefore important to know the relation between a firm's characteristics and ICT deployment. The study made two hierarchical segmentations to predict the behaviour of those firms when deploying the Web and e-mail. This work determines which characteristics are related to ICT deployment. Activity and category are the two characteristics that most effectively predict a firm's behaviour, whereas location and size are less effective. These results have implications for entrepreneurial behaviour and for public agents working in rural tourism. According to Olajide B.R. (2011), the use of combined media to minimize the time lag for both awareness and adoption of best practices for food crop production in Oyo State, Nigeria had been observed. One hundred and eighteen registered farmers in the Iddo District were sampled and interviewed. Results showed that the majority of the farmers were male (83.9%) and married (67.8%), and about one third (27.1%) completed elementary education. Fellow farmers (76.3%), extension agents (63.3%), friends (49.2%), and radio (48.3%) readily served as information sources for farmers. The quantum of agricultural information to which farmers had access was significantly related to varieties of information sources (r=.26, p=.05) used by farmers. The empowerment of elite farmers and capacity strengthening for extension agents are advocated for improved agricultural information dissemination. According to Senarathna R. P. and Wickramasuriya H.V.A (2011), the use of e-commerce in SMEs has become an important topic in information systems research. Despite the enormous attention given to encourage SMEs to adopt e-commerce by governments, research undertaken to identify strategies of e-commerce adoption for SMEs in developing countries, especially in Sri Lanka is minimal. The primary objective was to examine the relationship between organizational factors and e-commerce adoption to understand the factors that contribute to e-commerce adoption. Quantitative approaches were considered in this research. The research draws on the data obtained from a sample of 200 SMEs in Colombo District using a postal survey. But, of late, reluctance is observed among youth to enter the farming sector. At the same time the youth unemployment rates in India are on rise. Also, the country is witnessing a mass exodus of youth from villages to cities in the recent years. To restrict this exodus and to mitigate the unemployment rate, development of rural areas is essential and most appropriate action for this is entrepreneurship development. In case of villages, it is the farming sector which can act as potential

Review of Literature

33

source of entrepreneurship development. For these rural agripreneurs, needs to be developed. Hari R. and Mahesh C. (2014), stated that, in case of agripreneurship, credit, market and risk orientation plays an important role in the development of an agripreneur. Yadav D.S, Chahal V.P, Arvind K. and Ummed S. (2014), analyzed various dimensions of entrepreneurial behaviour of dairy women farmers and identified their constraints encountered by them in dairy farming in Mandi district of Himachal Pradesh State of India. Performance of majority of respondents on 10 dimensions of entrepreneurial behaviour was moderate to high except in case of innovativeness and knowledge about enterprise. The overall entrepreneurial behaviour of respondents was of medium level. Except age and family size, all other personal attributes of dairy farm women were observed to be positively and significantly correlated with overall entrepreneurial behaviour. A large majority of respondents (83%) encountered medium to high extent of constraints in dairy farming. The major constraints encountered by women included lack of technical knowhow about improved technology; lack of financial institutions; difficulty in getting loan; high cost of improved milch breed, feed, concentrate and medicines; non-availability of improved seed of fodder crops; lack of proper marketing facility, lack of entrepreneurship development oriented training; low price of milk and repeat breeding in cows.

2.12: Entrepreneurial or Business Communication According to W. C. Kim and R. Mauborgne (2005), the business based literature on entrepreneurship communication genres is relatively thin and non academic guides to these genres have proliferated. Guides on business plans are too numerous to mention. Guides on how to develop a start up, tends to describe and model many such genres, including a large number of heuristics and ideation techniques. Other guides focus on specific parts of the product development and marketing process, focusing on genres, heuristics, and ideation techniques that relate to those tasks. Still, others describe genres that coordinate internal efforts to sustain innovation. Finally, many guides provide advice on creating pitch decks and delivering verbal pitches. Although these lines of inquiry have delivered insights into narrative and identity, culture and community, and specific communication genres, these insights have not been grounded in the field of professional communication. It was observed by J.R and Beebe S.A. (2007), that effective communication is a primary means whereby entrepreneurs achieve the desired levels of excellence in the development of their organizations. According to them, research suggested that the major reflections of excellence in entrepreneurial organizations focus primarily on the care of customers, constant innovation, committed people and managerial leadership. The keys to achieving acceptable levels of excellence involve four key entrepreneurial leadership strategies: attention through vision, meaning through communication, trust through positioning and confidence through respect. Research also suggested that at the heart of successful entrepreneurial management, leadership strategies must be communication, based upon key values and a concern

34

Entrepreneurial Communication in Agriculture

for people that provide the foundational core and a paradigm of interactive cues for the fulfilment of those strategies. Newman, Amy and Scott Ober (2013), opined that when choosing a media of communication for doing business, it is important to consider who are the respective audience and the objective of the message itself. Rich media are more interactive than lean media and provide the opportunity for two-way communication: the receiver can ask questions and express opinions easily in person. To help such decision, one may roughly refer to the continuum, viz., Face-to-Face meeting, Interpersonal, Oral presentation, Online meeting, Video conferencing, Tele conferencing, Phone Call, Voice Message, Video, Blog, Report, Brochure, Newsletter, Flier , Email and Memo. Eileen Fischer and A. Rebecca Reuber (2014), proposed that research shows some narratives and symbolic actions produced by entrepreneurial firms can help to reduce audience uncertainty about their quality and differentiate them from rivals. This seems debatable, given that such streams comprise multiple, brief messages (a) that encode signals lacking narrative cohesion; (b) are only fleetingly accessible; and (c) are minimally customized. They addressed this puzzle using qualitative methods to compare the communications enacted by eight firms that are using Twitter in order to pursue growth. Their theoretical contribution rests in posting links between specific types of communicative streams and audience responses that reflect reduced uncertainty or enhanced differentiation. It was observed by Freddy J. and Nager (2017), that today's entrepreneurs can launch a business within a single day by leveraging internet-based tools and communication platforms, yet new venture viability now requires far more than "building a better mousetrap." Not only are major markets saturated, competition is now global, and potential customers are widely dispersed across countless media channels. While large corporations can combine established brand awareness with substantial investment in promotional communication, most entrepreneurs need to draw on research, critical analysis, and innovative communication practices simply to convey their value, vision, and viability to key stakeholders. In today's markets, only media and messages that combine both creativity and strategy can successfully deliver brand awareness and differentiation, compel desired audience behaviour, and stand any chance of generating a word-of-mouth "buzz." 

Chapter

3

THEORETICAL ORIENTATION 3.1: Entrepreneurship: The Concept and Definition Entrepreneur is a person who has the ability to find and act upon opportunities to translate inventions or technology into new products, and is also able to recognize the commercial potential of the invention and organize the capital, talent, and other resources that turn an invention into a commercially viable innovation. The term "Entrepreneurship" involves innovative activities on the part of established firms, in addition to similar activities on the part of new businesses, also it is the act of being an entrepreneur, or "the owner or manager of a business enterprise who, by risk and initiative, attempts to make profits". Entrepreneurship is also the process of designing, launching and running a new business, which is initially a small business. Entrepreneurship is the capacity and willingness to develop, organize and manage a business venture along with any of its risks in order to make profit. It is also the process by which either an individual or a team identifies a business opportunity and acquires and deploys the necessary resources required for its exploitation. The study of entrepreneurship reaches back to the work of Richard Cantillon and Adam Smith in the late 17th and early 18th centuries. However, entrepreneurship was largely ignored theoretically until the late 19th and early 20th centuries and empirically until a profound resurgence in business and economics since the late 1970s. In the 20th century, the understanding of entrepreneurship owes much to the work of economist, Joseph Schumpeter in the 1930s and other Austrian economists, Carl Menger, Ludwig von Mises and Friedrich von Hayek. According to Schumpeter, “An entrepreneur is a person who is willing and able to convert a new idea or invention into a successful innovation”. The supposition that entrepreneurship leads to economic growth is an interpretation of the residual in endogenous growth theory and as such is hotly debated in academic economics. An alternate description posited by Israel Kirzner, suggested that the majority of innovations may be much more incremental improvements such as the replacement of paper with plastic in the making of drinking straws, etc. Entrepreneurship is the crucial need for the development of rural areas. Young people with innovative perspectives and with the help of rightly channelized

36

Entrepreneurial Communication in Agriculture

efforts would usher in an era of rural entrepreneurship. In India, successful rural entrepreneurs would solve many of the chronic problems within a short time. enterprising people who prefer rural entrepreneurship, may or may not themselves belong to rural areas. Entrepreneurs taking to rural entrepreneurship should not only set up enterprises in rural areas but should awake rural produce as raw material and employing rural people in their production processes. Rural entrepreneurship is, in essence, that entrepreneurship, which ensures value addition to rural resources in rural areas engaging largely rural human resources. In other words, this means that finished products are produced in rural areas out of resources obtained in rural areas by largely rural people. The entrepreneur may or may not be of rural origin. The entrepreneurs may be from anywhere, but their enterprises have to be located in a rural area, using mainly local resources both material as well as human. Also, the enterprises have to be located in a rural area though it need not be actually using 100 per cent local material and human resources. Some amount of material and some people may be from urban cities also. But certainly large portion of material used has to be locally produced and an appreciable number of people engaged in the production of finished goods should be people based or living in rural areas. Even a unit set up by the government or a large company in a rural area could promote rural entrepreneurship depending on how much opportunities it throws up for entrepreneurs to use local resources, to fulfill the demands of such large units and the multiplier effect such large units create. Any large unit coming up in rural areas more or less does have an impact inactivating the surrounding economy for entrepreneurs to take advantage of. This is precisely the reason why it is recommended to shift industries from urban centers to neighboring rural areas. Shifting initially may be a difficult proposition but in the long run beneficial in many ways. Moreover, it would throw up lots of opportunities in the rural areas and result in decongestion of the urban centers. Urban slums would start disappearing with large number of industries getting shifted to rural areas resulting in increasing opportunities in the rural areas. Thus, both the rural as well as urban areas get benefited by setting up more industrial units in the rural areas, making rural areas attractive locations for investments.

3.2: Rural Entrepreneurship One of the major objectives of developmental policies in India is to provide employment to millions of unemployed rural youth. The core of the problem in countries like India is surplus agricultural labour and closure of traditional village industries, resulting in increased unemployment in rural areas and migration of rural youth to urban areas in search of jobs, in turn putting more pressure on the urban infrastructure and amenities. Rural industries generated employment for approximately 47.97 lakhs people in the year 1996-97, as against 37.21 lakhs people in the year 1992-93. There are a large number of products and services available in rural areas, which can be leveraged by entrepreneurs to set-up new and small micro enterprises. In fact, entrepreneurship can be pursued in virtually any economic field. Entrepreneurs play a crucial role in the rural development of the region. Rural development is linked to entrepreneurship more than ever before. Rural development

Theoretical Orientation

37

promoters see entrepreneurship as a development strategy. Rural entrepreneurship means the same as a rural industrialization. Rural entrepreneurship can be regarded as an attempt to create the management for risk-taking appropriate to opportunity, as well as to mobilize human resources, material and financial resources in order to fulfill the project in rural areas. Rural areas are disadvantaged in some ways when compared to the urban areas. There is a huge difference in the economic performance between rural regions. Nevertheless, the rural milieu imposes specific challenges and opportunities that finally change the outcome of entrepreneurial efforts. The success of the entrepreneur in the rural area is determined by specific environmental circumstances as well as characteristics of the entrepreneur. The following factors distinguish circumstances for entrepreneurs in rural areas: Physical Environment - Distance from densely populated centers is a drawback, since it means smaller market size, low demand, poor accessibility to customers, suppliers and institutions. On the other hand, accessible rural areas are rather advantageous for businesses. Natural resources and landscape, rich natural resources may present new business opportunities for both manufacturing and recreation. Pleasant surroundings lead to greater work satisfaction, healthier lifestyles and a more ethical office environment, considered attractive to many people. Rural areas, which possess remarkable amenities, may cause entrepreneurs to start businesses there, even though it may not be a rational option from an economical point of view. Social Environment - Relationships and trust among people created by developed social capital facilitate regional business cooperation and networking that can benefit entrepreneurs as well as rural peoples. Rural governance - Policies introduced by local governance structures are often directed towards promoting entrepreneurship. Local Culture - Rural entrepreneurs can benefit from using unique local characteristics to differentiate and market their products and services. These can be represented as distinct specialty products, or healthy organic ones. Economic Environment - Remoteness and high transportation costs make country businesses less competitive and attractive to customers, suppliers and employees. Adequate infrastructure is highly desirable and helpful to rural entrepreneurs. Due to close relationships among residents of rural location, business networking becomes more easier and efficient. Local networks are crucial to development of rural firms. These networks can together reach larger markets, increase resilience, and give ability for every member to take more risks. Even internationally oriented rural businesses rely heavily on their local networks. In addition, close relations with friends and family provide supportive atmosphere inside rural firms. Information and Communication Technologies (ICT) are generally acknowledged. ICT opens unprecedented opportunities for SMEs in rural locations. Information is easily collectable, market boundaries are broadened, cooperation is assisted, resources are much easier reachable with the help of ICT. All these combat disadvantages imposed on rural areas by distance and small market size.

38

Entrepreneurial Communication in Agriculture

3.3: Rural Entrepreneurship in India Local leaders and NGOs, who are committed to the cause of the rural people have been catalytic agents for development. Though their efforts need to be recognized yet, much more need to be done to reverse the direction of movement of people, i.e. to attract people to the rural areas. It means not only stopping the outflow of rural people but also attracting them back from the towns and cities where they had migrated. This is possible only when young people consider rural areas as places of opportunities. Despite all the inadequacies in rural areas one should assess their strengths to make rural areas places of opportunities. This is much to do with the way one sees the reality of the rural areas. The way a job seeker would see things would be certainly different from those who would like to do something worthwhile and are ready to go through a difficult path to achieve their goals.

3.4: Role of Rural Entrepreneurship in India The fundamental role of rural entrepreneurship is to provide employment opportunities and consequently, applying a check on migration. Industries in rural areas are mostly micro or tiny in structure and quick yielding. In other words, their gestation period is much less as compared to large scale industries of urban areas. Rural industries are also labour intensive and provide substantial employment opportunities to rural people of all age groups. Few examples of such type of industries are, Food Processing industry, Poultry industry, cottage and handicrafts industry, etc. This also helps in balanced regional growth and promotion of artistic activities. India is one of the oldest, culturally richest and diverse country, full of colours and boasts of civilization with rich flora and fauna. Our cuisine is mouth watering, scenic beauty is breathtaking, folk dances are simply enchanting, and there is a wide array of places of tourist attraction. These are just a few of the reasons why Government has termed us as Incredible India. Nearly two-thirds Indians live in the villages where our roots are contained. There is the wealth of craft, performing art, vivid lifestyle and cultural diversity contained in our rural India. Thus, rural entrepreneurship will further help bridge this gap between the rural and urban areas, and the development of urban areas won’t happen at the cost of our rural areas. Human resources are amongst the essential resources that are required for fostering rural entrepreneurship. The importance of human resources cannot be overemphasized, for it is this resource alone that makes the greatest impact on socio-economic development of rural areas. Childhood reading, upbringing, exposure to challenging situations, self-study, apprenticeship, coaching and training, all contribute to achievement motivation, which is a key to entrepreneurship development. This will help us by applying a check on social evils (like poverty, the growth of slums, etc.), awakening the rural youth (to expose them to various avenues and adopt entrepreneurship and promote it as a career) and also improve the standard of living of the rural youth.

3.5: Opportunities for Rural Entrepreneurship (i) Free entry into world trade.

Theoretical Orientation

39

(ii) Improved risk taking ability. (iii) Governments of nations withdrawn some restrictions. (iv) Technology and inventions spread into the world. (v) Encouragement to innovations and inventions. (vi) Promotion of healthy completions among nations. (vii) Consideration increase in government assistance for international trade. (viii) Establishment of other national and international institutes to support business among the nations of the world. (ix) Benefits of specialization. (x) Social and cultural development. (xi) Crashed Scheme for Rural Development. (xii) Food for Work Program. (xiii) National Rural Employment Program. (xiv) Regional Rural Development Centers. (xv) Entrepreneurship Development Institute of India. (xvi) Bank of Technology. (xvii) Rural Innovation Funding. (xviii) Social Rural Entrepreneurship.

3.6: Challenges Faced by Rural Entrepreneurship The changing global environment raises questions about the ability of traditional, small-scale businesses in rural areas to share the potential benefits offered by the changing environment. The rapid population growth, coupled with even faster urbanization, creates increasing demands. In India, urban populations, in general, grow about twice as fast as the overall total, and by 2020, they may exceed the size of the rural population. Such a significant demographic trend challenges the capacities of some traditional small-scale businesses to cope with the increasing demands. And this is why rural entrepreneurship is becoming more important rapidly in India, and already, there is a changing trend in how things happen. Other challenges are: (i) Growth of Mall Culture. (ii) Poor Assistance. (iii) Power Failure. (iv) Lack of Technical knowhow. (v) Capacity Utilization. (vi) Infrastructure Sickness.

3.7: Types of Rural Entrepreneurship Rural entrepreneurial activity can be broadly classified in four types such as

Entrepreneurial Communication in Agriculture

40

(i) Individual Entrepreneurship It is basically called proprietary i.e. single ownership of the enterprise. (ii) Group Entrepreneurship It mainly covers partnership, private limited company and public limited company. (iii) Cluster Formation It covers NGOs, VOs, CBOs, SHGs and even networking of these groups. These also cover formal and non-formal association of a group of individuals on the basis of caste, occupation, income, etc. (iv) Cooperatives It is an autonomous association of persons united voluntarily for a common purpose. An entrepreneur has to decide on a particular type of entrepreneurship based on the various options available. (v) Individual Entrepreneurship/Proprietorship It is the entrepreneur who is the only owner. The entrepreneur bears full responsibility for each and every activity and is alone the strategic thinker, innovator and decision maker to make the unit viable as well as profitable. There is hardly any difference between personal assets and business assets.

(vi) Group Entrepreneurship

It is classified into mainly three types such as i) Partnership ii) Private Limited Company and iii) Public Limited Company. (vii) Partnership Here, there is no individual ownership of the unit. There are partners who bears the responsibility and shares profit. For partnership type of entrepreneurship, mutual trust is most important. Besides, both the partners in partnership understand their respective responsibilities and complement each other for common objectives and goal. The requirements of ideal partnership are good faith, common approach, written agreement, registration, adequate capital, skills and stability. Partnership is governed by Indian Partnership Act, 1932.

3.8: Rural Enterprise Development A rural enterprise can be any economic unit engaged in producing and distributing goods and services, from individual households to larger operations, and they play a vital role in poverty reduction and socio-economic development of a country. But there are many things that businesses need to do to flourish in today’s complex, competitive world. Since it was determined that entrepreneurship is a major factor of economic growth, it has been attracting researchers who have produced an ample amount of literature. Entrepreneurship is describing individuals that recognize the

Theoretical Orientation

41

opportunities and their potentials in order to satisfy needs and who gather resources to meet them. Indeed, researchers agree that entrepreneurship is performed by individuals and that it is a dynamic phenomenon. Entrepreneurs in a company is one (or sometimes a few) person whose influence shapes the entire business. Due to the fact that such centralized management is usually a feature of small firms, the tight link between entrepreneurs and small business is established. However, employers are more satisfied with their job than employees and have much higher autonomy. It is well known that entrepreneurs are associated with particular personality and mindset, which must be inquisitive in nature. Among “entrepreneurial” traits are creativity, innovativeness, achievement orientation, risk-tolerance, openness and self-confidence. Moreover, entrepreneurs are shaped by family from childhood, environment and society in which they are brought up. Entrepreneurship is also a process with entrepreneur and the environment being inputs, and a variety of outputs among which are self-actualization, making profit and economic growth. As for more economy-wide outputs, strong positive influence of entrepreneurship is helpful on economic development of a region. It is argued that fostering entrepreneurship contributes to growth more than investing in traditional factors, such as R & D and education. This finding goes in line with the economics model of entrepreneurship, according to which entrepreneurship is an integral part of economic growth and social growth, and economic situation in turn, creates incentives/obstacles for entrepreneurship to flourish. This process of entrepreneurship is influenced by specific opportunities and challenges imposed on it by factors of environment. Therefore business location is a major force of fostering or inhibiting entrepreneurship. Obviously, rural areas form a specific milieu with its own opportunities and challenges to entrepreneurship. Small businesses of all types are needed, those with high growth potential and also those formed for life style purposes, or self sufficiency that primarily serves local needs.

3.9: Entrepreneurial Behaviour (i) Information Seeking Here the entrepreneur becomes inquisitive to seek more and more information to start a new business/venture. (ii) Information Processing Then the entrepreneur process the information gained and generate a database which will be beneficial to run the business. (iii) Information Disseminating After processing of information, the piled up information is disseminated to the outer sources, which will be beneficial for the business and the new initiatives.

3.10: Entrepreneurial Process (i) Task presentation. (ii) Preparation.

42

Entrepreneurial Communication in Agriculture

(iii) Incubation. (iv) Idea Generation. (v) Verified Idea Validation. (vi) Outcome Assessment. (M.C. Gupta, 1987)

3.11: Role of Incentives and Subsidy for Encouraging Entrepreneu-Rial Behaviour Incentives are motivational forces which improve productivity of Entrepreneurs. They enable the entrepreneurs to take up initiatives and appropriate decision and give capacity to implement them. In practice, incentives are concerned with actions to encourage productivity. Generally, incentives include three variables; concessions, subsidies and bounties. (Gupta. C.B., and Khanka, S.S., 2000)

3.12: Entrepreneurship: Steps of Creative Process (i) Intrinsic motivation The motivation that works within and which comes from the inner core and self of an individual. (ii) Skills in the task domain Delineation and acquisition of skills in terms of task domain. (iii) Skills in creative thinking Which deals with innovation and creativity, including out of the box thinking.

3.13: Entrepreneurship and Information Communication Techno-logy (ICT) Many national, regional or local policies have been developed to support entrepreneurship, both generally and in specific industries related to information and communication technology (ICT). Five perspectives on the meaning of entrepreneurship are considered, as: a function in the economy (with a threestage model); a new business start-up; an owner-manager of a small business; a set of personal characteristics; and, a form of behaviour. These perspectives have different implications for policies to promote entrepreneurship. These policies include: predominantly macro-level policies, like, economic stability, taxation and regulations; micro-level policies stressing upon advice, training, finance, technology transfer, markets access, physical infrastructure and the characteristics of the locality; and creating an entrepreneurial environment.

3.14: ICT Entrepreneurship Model: A New Approach for IT The ICT sector is one of the most dynamic areas of the European economy, a key source of growth and employment. 5.3 million people were employed in the ICT sector in 2006, in 5,20,000 enterprises. There is a growing demand for ‘soft’ skills in

Theoretical Orientation

43

ICT work. These are increasingly emphasized in recruitment and selection processes. ‘Soft skills’ generally refer to: business skills, communications skills, team-working skills, competencies, personal attributes, individual qualities, transferable skills, social skills, interpersonal skills, human skill, design skill, conceptual skill, etc. People working in this field cannot base their skills (or expertise) on technical knowledge gained from the university. They have to learn to learn and think on their own, which forms a real challenge to our educational system. We have to develop learning environments, that activate and arouse students to take up initiatives. Societies need entrepreneurs. It is said, that entrepreneurship forms a future of every country. Educational system has to train young people who want to learn entrepreneurial skills. ICT business needs new entrepreneurs and innovative business cultures, such as in Silicon Valley in California. These thoughts were a starting point to develop a team learning and entrepreneurship (TLE) environment to study information technology at Finnish University of Applied Sciences. The environment is based on theories of learning organization and knowledge creation. We should apply a mixed method approach in ICT team entrepreneurs. (IFAC Proceedings, Volume 45)

3.15: Need for Entrepreneurial Class Balanced development of a country, extension of the benefits of economic progress to the backward areas and widespread diffusion of industrial units are the important dimensions of planned development and economic growth. However, experience of less developed countries shows that their efforts for achieving the balanced regional development would not succeed until such time they are able to initiate a widely diffused, yet viable industrialization process which demands for promotion of new entrepreneurship, a vital factor of production for the success of any adventure. Some potential entrepreneurs prefer their own business in place of their successful careers in other organizations.

3.16: Communication and Entrepreneurship Communication is an act by which one person gives to or receives from another person, the information about that person’s needs, desires, perceptions, knowledge, or affective states. Communication may be intentional or unintentional. It is complex, complicated and contextual. It involves conventional or unconventional signals, linguistic or non-linguistic forms, and may occur through spoken or other modes (non-verbal communication). Communication is the utmost need for entrepreneurship because in doing any type of business, be it a small or large, first of all comes the need of communication between the seller and the customer. If both the seller and the buyer do not understand the meaning intended, the enterprise will survive difficulties to sustain.

3.17: Communication Pattern Communication pattern includes those communication behavior of an individual, dyad, group or social system that are systematic or exhibit some form of regularity.

44

Entrepreneurial Communication in Agriculture

3.18: Communication Pattern of Linkers It helps learning the nature of relationship between communication behavior of linker and his effectiveness in facilitating research dissemination and utilization: (i) Information input amount. (ii) Information input diversity. (iii) Peer communication amount. (iv) Peer communication diversity. (v) Linker network centrality. (vi) Opinion leadership. (vii) Information output amount. (viii) Information output diversity.

3.19: Entrepreneurial Communication When man goes innovative, risk bearing and keeps on hunting for options, he is becoming more and more entrepreneur. So, entrepreneurial communication helps an individual build up information inventory and at the same time, goes on integrating needful information for landing on the valley of success. Entrepreneurial communication, for this study has been conceived in terms of information generation, information receiving, information sharing, for both entrepreneurial incubations and entrepreneurial management with constant flow of innovation and refinement. It takes care of unique entrepreneurial behavior, as well as, pursuits that breeds on unique enterprise generation. Two farmers can be differentiated from each other based on their unique entrepreneurial communication, while one farmer is happy with clichés of information, the other farmer is rather unhappy with the clichés of conventional information, instead he is in constant movement in hunting information of innovation and uniqueness. It is through Entrepreneurial communication, one can find the answers, why and what the enterprise is for, along with how and where one should drive himself to earn a success in entrepreneurial proficiency. Entrepreneurial communication has got both intrinsic and extrinsic behavioural disposition and integrity therewith, that leads to entrepreneurial accomplishment, a process of achieving success in both competitions and comparability.

3.20: Business Communication Business Communication is any communication used to promote a product, service, or organization, with the objective of making profit. In business communication, message is conveyed through various channels of communication including internet, print (publications), radio, television, outdoor, and word of mouth. In business, communication is considered core among business, interpersonal skills and etiquette. Good business communication is essential for building a team that will make business a success. Communication is especially important if members of a company are to work as a team towards the same goal. There are many reasons why

Theoretical Orientation

45

good communication skills are vital when it comes to running a successful company or business. Here are some of them. Interaction amongst employees of the company builds an efficient team. In order to have a good team, a good leader is essential. The leader must be able to communicate well with every member that is involved in the business in order to convey to each employee their jobs, growth and expectations. He or she must be a motivating person who encourages people to work hard and to have a mindset of achieving various goals. A leader that communicates well creates a team that performs well in all departments. When employees are able to converse efficiently with each other, misunderstandings are resolved in an amicable manner. Furthermore, unnecessary friction is avoided. This means that employees will be able to concentrate better on their work. The process of coming up with that finished product requires occasional interactional meetings where issues are discussed and there is also improvement in the service quality. This is in terms of the relationship between the company and the customers. If the company interacts well with the clients and attends to their needs promptly, the customers are bound to continue doing business with the company. The company will also be in a position to provide better service. This is because as we communicate with the clients, we will be able to figure out exactly what they want from us. This way, we can make the necessary improvements to products or services that the customers require. Customer surveys and feedback help improve market sales. There are various hierarchies in companies. A company that has good communication between the top management and the junior employees creates an inclusive atmosphere. When members of a company communicate efficiently, a positive atmosphere is created. If there is a positive atmosphere in the workplace, internal problems are sorted out easily and quickly. People who run successful businesses know that the customers are always the priority. It is the customer who brings in the profits. That is why it is important for the company to interact well with each other and the customers in order to reach business goals. Good business communication is vital if we want our company to be a success. Business Communication is information sharing between people within and outside an organization that is performed for the commercial benefit of the organization. It can also be defined as relaying of information within a business by its people.

There are Several Methods of Business Communication. They are:

• Web-based communication - For better and improved communication, anytime anywhere communication can occur through the vast network.



• Video conferencing - It allows people in different locations to hold interactive meetings.



• Reports - These are important in documenting the activities of any department.



• Presentations - It is a very popular method of communication in all types of organizations, usually involving audiovisual material, like copies of reports, or material prepared in Microsoft PowerPoint or Adobe Flash.



• Telephone meetings - This also allows for long distance speech.

Entrepreneurial Communication in Agriculture

46



• Forum boards - It helps people to instantly post information at a centralized location.



• Face-to-face meetings - They are personal and should be succeeded by a written follow up.

Business communication is primarily used for upward communication, because some people may hesitate to communicate with management directly, so they opt to give suggestions by drafting one and putting it in the suggestion box. Business Communication can take place in four different directions in an organization:

• Top-Down - This kind of communication takes place when the management passes the order to the subordinates to perform certain task. Usually this kind of communication takes place using circulars, newsletters, memos, e-mails, etc.



• Bottom-Up - This kind of communication takes place when the subordinates submit an outcome, result, request, application, etc. Usually this kind of communication takes place using, reports, e-mails, proposals, etc.



• Lateral or Horizontal - This kind of communication takes place when employees in same management level communicate. The usual mode of communication is e-mail, circular, etc.



• Diagonal Communication - When different management levels communicate who have no direct reporting relationships, it is called Diagonal Communication. This kind of communication takes place using normal meetings, circular, notice, newsletter, etc.



• Formal Communication - The communication held in systematic manner. It has rules and regulations. It gets completed on decided time.



• Informal Communication - The communication held in proper way and in non-systematic manner. It does not get completed on decided time of communication. Communication does not conduct any rules and regulation.



• Gesture Communication - The communication takes place between peoples via symbols and signs.

A two way information sharing process which involves one party sending a message that is easily understood by the receiving party. Effective communication by business managers facilitates information sharing between company employees and can substantially contribute to its commercial success. Face-to-Face Face-to-face communication helps to establish a personal connection and will help to sell the product or service to the customer. These interactions can articulate a whole different message than written communication as tone, pitch, and body language is observed. Information is easier to access and delivered immediately with interactions rather than waiting for an email or phone call. Conflicts are also easily and quickly resolved, as verbal and non-verbal cues are observed and acted upon.

Theoretical Orientation

47

Email When using email to communicate in the business world, one should be very cautious with the choice of words. Miscommunication is frequent as the reader does not have access to the non-verbal cues that are available in face to face spoken communication, the pitch, tone, body language and facial expression. Before beginning an email, one should make sure that the email address using is appropriate and professional, as is the message one has composed. Telephone When making a business call, one should make it clear who is on the line and where one is from as well as one's message when on the phone. When leaving a message, it should be clear and brief. One should state their name and who they are and the purpose for contacting them. If replying to a voicemail, we should try to respond as soon as possible and take into consideration the time of day. Also we should be careful of where one is and the noise level as well as the people around, when trying to reach someone by phone. Listening Listening is the ‘art’ of communication. When listening to another employee or customer it is important to be an active listener. Here are some obstacles that we might have to overcome:

• Filters and Assumptions



• Biases and Prejudices



• Inattention and Impatience



• Surrounding Environment

3.21: Subliminal Method of Communication Subliminal perception refers to the individual ability to perceive and respond to stimuli that are below the threshold or level of consciousness, which proved to influence thoughts, feelings or actions altogether or separately. There are four distinct methods of communicating subliminally. These are visual stimuli in movies, accelerated speech, embedded images in a print advertisement, and suggestiveness which is not normally seen at first glance. Focusing on Subliminal Communication through visual stimuli, Marketing people have adopted this method even incorporating it films and television shows. Subliminal method of communication first made its debut in a 1957 advertisement, during which a brief message flashed, telling viewers to eat popcorn and drink Coca-Cola. Since that time, subliminal communication has occupied a controversial role in the advertising landscape, with some people claiming it's omnipresent, while others emphasize it's not real. As of publication, there is still an ongoing scientific debate about whether subliminal advertising works. Subliminal messaging is a form of advertising in which a subtle message is inserted into a standard advertisement. This subtle message affects the consumer's behavior, but the consumer does not know she's seen the message. For example, a marketer might incorporate a single frame telling consumers to drink tea in a movie. In print media, advertisers might put hidden images or coded messages into ad text.

48

Entrepreneurial Communication in Agriculture

3.22: Dialogue Social Enterprise It is a social enterprise operating worldwide. The mission is to facilitate social inclusion of disabled, disadvantaged and elderly people on a global basis. Disability is a rising issue and demographic change is considered to be a mega trend. The number of people with disability is growing due to an aging population and an increase in chronic illnesses related to higher life cycle expectancies. The goals are: (i) To raise awareness about the contribution to society by people with disability and elderly people, leading to an inclusive behavior (ii) To improve the social economic condition of handicapped people, especially blind, visually and hearing impaired people The construction of social enterprise is ongoing, and fought by a range of actors promoting different languages and practices tied to different political beliefs. That is, social enterprise is politically contested by different actors around competing discourses.

3.23: Need for Technical Business Incubators Technical Business Incubators (TBIs) have evolved from the convergence of two global movements namely, the recognition that small and medium enterprises are the instruments of economic growth and the accelerated pace of technical change. Technical Business Incubators are making a significant contribution to the economic development of various nations and era of Technical Business Incubators has just now begun in India as well. In India, however, Technical Business Incubators are associated with and are aided and supported by centres of Educational and Technological excellence. Technical Business Incubator model has a great scope for creation of a new generation of entrepreneurs, who in turn would provide jobs and generate national wealth as well. (Schumpter, J.A, 1934)

3.24: Reservation versus Dereservation of Items for Small Scale Sectors The policy of reservation was primarily initiated in 1967 as a promotional and protective measure for the small scale sector vis-à-vis large scale sector. Selected products are identified for exclusive production in small scale industries. The overwhelming consideration for reservation are whether the item is economically viable and technically feasible for manufacture in the small scale, whether the manufacturing price is of a simple nature, that is, essentially labour intensive and whether the small scale units can meet up all the requirements of the consumers both in terms of quantity and quality. (Raipuria Kalyan, 1996)

3.25: Entrepreneurship: The Dynamic Need Entrepreneur is a Business leader who has a pivotal role in fostering economic growth. Entrepreneurship helps solving the following problems: (i) Employment Generation. (ii) National Production.

Theoretical Orientation

49

(iii) Dispersal of Economic power. (iv) Balance Regional development. (Satish Tanuja and Dr. S.L. Gupta, 1999)

3.26: New Concept of Entrepreneurs After the execution of financial reforms and the opening up of the economy, the term entrepreneur has been defined as the one, who detects, identifies and evaluates a new situation in his environment and directs the necessary adjustment in the economic system. He is the person who conceives of an industrial enterprise for the purpose, displays initiatives, takes risks, makes determination in bringing his project to the success and in the process, performs one or more of the perceived opportunities, for profitable investments, explores the prospects of starting of manufacturing and also obtains necessary industrial licenses, etc. (Vasant Desai, 1999)

3.27: Conceptual Framework of Entrepreneurship Entrepreneurship “involves combining to initiate changes in the production”. Entrepreneurship is a discontinuous phenomenon appearing until it reappears to initiate another change. Wilken categorizes five key types of changes: (i) Initial Expansion. (iii) Factor Innovations. (v) Market Innovations. (Prashad Awadesh (1988)

(ii) Subsequent Expansion. (iv) Production Innovations.

Research Paradigm Communication Support Resource

Enterprise Incubation

Support

Successful Enterprise

Entrepreneurial communication behaviour

Innovative

Refined

Enterprise

enterprise

enterprise

socialization

Model 3.1: Structure of Research paradigm



Chapter

4

RESEARCH SETTING AND SOCIAL ECOLOGY INTRODUCTION Research setting is basically the functional social-ecology, the objectives and condition wherein all possible socio-economic and communication processes are generated, and again gets regenerated. In any social science research, it is hardly possible to conceptualize and perceive the data and interpret the data more accurately until and unless a clear understanding of the characteristics in the area and attitude or behaviour of people is at command of the interpreter. The researcher intends to unveil an understanding of the implications and behavioural complexes of the individuals who live in the area under reference and from a representative part of the larger community. The socio- demographic background of the local people in a rural setting has been critically administered in this chapter. A research setting is a surrounding in which inputs and elements of research are contextually imbibed, interactive and mutually contribute to the system performance. Research setting is immensely important because it is characterizing and influencing the interplays of different factors and components. Thus, a study on perception of farmer about the issues of persuasive and other topics, certainly demands a local unique with natural set up, demography, crop ecology, institutional set up and other socio cultural milieus. It comprises of two types of research setting viz., Macro research setting and Micro research setting.Macro research setting encompasses the state as a whole, whereas micro research setting starts off from the boundaries of the chosen districts to the block or village periphery. The notion behind this form of presentation is to internalize the study environment in terms of broader perspectives with state as reference frame and district, block profile as units for in depth study.

Research setting and Social Ecology

51

4.1: Area of Study The present study was taken up in two states, Tripura and West Bengal. From Tripura, District West Tripura, Blocks Shantipara and Mohanpur, Villages Bamutia and Kamalghat were selected respectively. From West Bengal, District Nadia, Blocks Haringhata and Chakdaha, Villages Bhawanipore and Ghoragacha were selected respectively.

4.2: Tripura at A Glance Tripura is a hilly and land locked state located in the south-west extreme corner of the north eastern region of India. The state has a long international border (nearly 84%) surrounded on three sides by Bangladesh. It stretches from latitude 22°56’ and 24°32’ north to longitude 91°10’ and 92°21’ east, with a total geographical area of about 10.491 sq. k.m, of which 70% is hill with dense forest and 27% is under cultivation. The agro-climatic conditions favours the cultivation of different minor and major fruit crops like jackfruit, bael, Indian jujube, elephant apple, jamun, fig, jalpai, loquat, karonda, star apple or caimito, star aonla, amrat, wood apple and tamarind. The land holding pattern in Tripura reveals that nearly 90% of the farmers are small and marginal, hence, the minor crops are ideal for cultivation because of their low input requirement, less production cost, higher nutritive value and high yield. Apart from nutritive value, minor fruits are particularly more important for medicinal properties and famous for the retentive value in Ayurvedic medicine. Paddy is also cultivated here, as it is the staple crop of the state. The region is one of the richest reservoirs of genetic variability and diversity of different minor fruits, which exists in plant types, morphological and physiological variations, resistance to disease and pests, adaptability and distribution.

4.3: Mythological Period The origins of the kingdom are shrouded in the myths written in Rajmala, the chronicle of the Kings of Tripura, which meanders from Hindu mythologies and Tripuri folklores. The ancient period can be said from around 7th century when the Tripuri kings ruled from Kailashahar in North Tripura and they used "Fa" as their title, "pha" in Kokborok means "Father" or "Head".

4.4: Historical Period The Kings of Tripura adopted the title "MANIKYA" and shifted their capital to Udaipur (formerly Rangamati) on the banks of river Gomati in South Tripura in the 14th century. These were their most glorious period and their power and fame were even acknowledged by the Mughals, who were their contemporaries in North India

52

Entrepreneurial Communication in Agriculture

Map 4.1: Map of Tripura

4.5: Modern Period During this period the capital of the kingdom was shifted to Agartala, in West Tripura, the present state capital, in the early part of 19th century. After India's Independence, the princely state Tripura was merged with the Union of India in 1949. Tripura became a Union Territory on 1st July 1963 and attained the status of a full-fledged state on 21st January 1972.The Tripura Tribal Areas Autonomous District Council (TTAADC) was set up in 1982 under the 7th Schedule of the Constitution, which brought under the 6th Schedule in 1985. The State has rich natural resources including gas and forests. The local flora and fauna bears a very close affinity and resemblance with floral and faunal components of Indo-Malayan and Indo-Chinese sub-regions. The prominent hill ranges are Jampui, Sakhantang, Longtharai, Atharamura, Baramura, Deotamura, Belkum and Kalajhari. The Bethling Shib (939 metres), situated in the Jampui range, is the highest peak of Tripura. The important forest products include Sal, Teak, Gamai, Garjan and Champa. The bamboo is available in the State abundantly, and is traditionally being used for multi-purpose by the tribal people. The Gomati, Howrah, Dhalai, Muhuri, Feni and Juri are the major rivers which swell in monsoon but they become shallow during the rest of the year. The people of Tripura are mostly tribal. The tribes of this state are of TibetoBurmese origin. The Tripuris, the largest tribe lives in the west while large numbers

Research setting and Social Ecology

53

of Reangs and Jamatias live in the north and south respectively. Many ethnic and scheduled tribal communities in Tripura are found here. These people speak Bengali, kokborok, Tripuri and Manipuri. Though it is a tribal dominating state, but a huge number of Bengali communities also reside there. Most of the Bengalis of Tripura had come from the neighbouring country, Bangladesh, after the partition. The tribal and Bengali peoples live together in peace and harmony. Tripura is home to a major number linguistics groups, and thus, it has avery complex culture. Dominant cultures in the state are Tripuri, Bengali, Murasing, Munda, Koloi, Halam, Kuki, Garo, Mizo, Chakma, Uchoi, Mogh, Noatia, Jamatia, Oraon and Santhal. Table 4.1: Demographic Information of Tripura (according to 2011 census) Demographic Information of Tripura Area

10,486 sq. k.m.

Population

36,71,032 persons (2011 census)

Male population

18,71,867 persons (2011 census)

Female population

17,99,165 persons (2011 census)

Decadal growth rate

14.75%

Population density

350 person per sq. k.m.

Literacy rate

87.75%

Male Literacy rate

92.18%

Female Literacy rate

83.15%

No. of Districts

8

No. of Sub Divisions

23

No. of Block

45

No. of Municipals

16

Table 4.1: Demographic Information of Tripura (according to 2011 census) Land utilization pattern Total geographical area (ha)

10,49,169

Net area sown (ha)

2,55,524

Forest area (ha)

6,29,429

Area sown more than once (ha)

1,92,968

Current fallow land (ha)

2,125

Gross area sown (ha)

4,48,492

Net Cropped area (ha)

2,55,524

Gross Cropped area (ha)

4,48,492

4.6: Climate of the State Tripura has a tropical climate and receives heavy rainfall during the monsoons. The state receives an average annual rainfall of 2,197m.m. Temperature in the state varies from 10 to 35 degree Celsius.

4.7: Agriculture Tripura is an agrarian state known worldwide for its production of rubber, tea, coffee, raw silk, jute, bamboo and sandalwood. The state has a 75 per cent share of the total

54

Entrepreneurial Communication in Agriculture

floriculture industry of thecountry. About 70 per cent of the people live in the villages and 71 per cent of the population depends on agriculture. The crops like rice, ragi, jowar, maize and pulses besides oilseeds and number of cash crops are grown here. Other crops like cashew nut, coconut, areca nut, chillies, cotton, sugarcane, and tobacco are also grown in the state. Pineapple is the state fruit of Tripura.

4.8: Economy The economy of the state is primarily agrarian. The primary sector i.e. agriculture contributes about 64 per cent of total employment in the state and about 48 percent of the State Domestic Product (SDP). A variety of horticultural and plantation crops are produced in here, like pineapple, oranges, cashew nut, jackfruit, mango, banana, coconut, tea, rubber, forest plantation etc. There is an ample scope for increasing the area under such productions as wells as productivity.

4.9: General Information of District West Tripura District West Tripura, one of the eight districts of the state, is an administrative district. Agartala is the administrative headquarters of the district. In the year 2011, this district holds the first position in the list of the district of Tripura having the maximum number of inhabitants. The northern and western side of the district border with Bangladesh, and the eastern face borders with the North Tripura District, while the southern part of the district is surrounded by the district of South Tripura.

Map 4.2: District map of Tripura

Research setting and Social Ecology

55

Table 4.3: West Tripura district at a glance West Tripura district Total geographical area

10,486 Sq. km.

Total population

17,24,619 persons (2011 census)

Male

8,77,930 persons (2011 census)

Female

8,46,689 persons (2011 census)

Literacy rate

88.91 % (2011 census)

Number of Sub-divisions

3

Number of Blocks

9

Number of Municipal corporation

1

Number of Nagar Panchayat

3

Number of Gram Panchayat

70

Number of Autonomous District Council village

77

Annual Rainfall

2,818 m.m.

Maximum Temperature

29.86 degree celsius

Minimum Temperature

20.20 degree celsius

Table 4.4: Profile of Block Shantipara of District West Tripura, Tripura Block profile Geographical area

13,664 ha

Area under SRI rice cultivation

60 ha

Area under forest

6,222 ha

Barren and uncultivated land

12 ha

Land put to non- agricultural use

750 ha

Cultivable Area

5,243 ha

Net Cropped Area

5,616 ha

Gross Cropped Area

7,234 ha

Cropping intensity

139%

Forest patta land

148 ha

Total population

40,712 persons (2011 census)

Male

22,450 persons (2011 census)

Female

18,262 persons (2011 census)

Autonomous District Council village

15

Tripura Grameen Bank

1

Central bank

1

Junior Basic school

20

Senior basic school

39

High school

5

Higher secondary school

3

Pre Primary health centre

8

Entrepreneurial Communication in Agriculture

56 Primary health centre

2

Lift irrigation

5

Mini deep tube well

6

Holda pump (baring)

5

Dark well

1

Table 4.5: Profile of Village Bamutia of Block Shantipara, Tripura Village profile Total population

1,674 persons (2011 census)

Male

822 persons (2011 census)

Female

852 persons (2011 census)

Number of Farmers involved in Entrepreneurial ventures

180 persons (approximately)

Total geographical Area

96.53 sq. k.m.

Protected Forest Area

20.57 ha

Total High Land

156.59 ha

Total cultivable area

1,230 ha

Total area under Integrated Farming System

245 ha

Literacy rate

88% (2011 census)

I.C.D.S

8

Primary School

2

Senior Basic School

3

Dispensary

1

VLW pesticide and Fertilizer delivery office

1

Tehshil Office

1

Govt. Ration shop

2

Table 4.6: Profile of Mohanpur Block of District West Tripura, Tripura Block profile Geographical area

15, 652 ha

Area under SRI rice cultivation

75 ha

Area under forest

7,422 ha

Barren and uncultivated land

15 ha

Land put to non-agricultural use

974 ha

Cultivable Area

7,253 ha

Net Cropped Area

7,016 ha

Gross Cropped Area

9,734 ha

Cropping intensity

122%

Forest patta land

164 ha

Research setting and Social Ecology

57

Total population

51,715 persons (2011 census)

Male

26,131 persons (2011 census)

Female

25,584 persons (2011 census)

Autonomous District Council village

20

Tripura Grameen Bank

1

Central bank

1

Junior Basic school

27

Senior basic school

49

High school

7

Higher secondary school

3

Pre Primary health centre

11

Primary health centre

2

Lift irrigation

6

Mini deep tube well

9

Holda pump (baring)

8

Dark well

1

Electric shallow

5

Table 4.7: Profile of Village Kamalghat of Block Mohanpur, Tripura Village profile Total population

3,444 persons (2011 census)

Male

1,596 persons (2011 census)

Female

1,848 persons (2011 census)

Number of Farmers involved in Entrepreneurial ventures

170 persons (approximately)

Total geographical Area

107.53 sq. k.m.

Protected Forest Area

41.57 ha

Total High Land

473.59 ha

Total cultivable area

1,941 ha

Total area under Integrated Farming System

300 ha

Literacy rate

88% (2011 census)

I.C.D.S

13

Senior Basic School

4

Dispensary

1

VLW pesticide and Fertilizer delivery office

1

Tehshil Office

1

Govt. Ration shop

2

Number of Self help group

16

Entrepreneurial Communication in Agriculture

58

Map 4.3: Map of West Tripura district of Tripura

4.10: Profile of West Bengal West Bengal is located between 21031o and 27014o North latitude and 85051o and 890o East Longitudes. It is flanked by the Bay of Bengal in the south, Sikkim on the north, Assam on the east and Jharkhand and Orissa on the west. It covers an area of 8.85 million ha, representing only 2.7% of the total area of the country. The State is divided into 20 administrative districts, viz. Bankura, Birbhum, Burdwan, Kolkata, Coochbehar, Darjeeling, Hooghly, Howrah, Jalpaiguri, Malda, Midnaporeeast, Midnapore-west, Murshidabad, Nadia, North 24 Parganas, North Dinajpur, Purulia, South 24 Parganas, South Dinajpur and Alipurduar. The economy of West Bengal is well diversified and according to the economic survey 2003-04, West Bengal contributes 7.7% to National NDP. Agriculture in West Bengal contributes 24% of State GDP and employs 57% of total work force. The Net sown area is 61% of the total geographic area against national average of 46%, the gross cropped area exceeds 92 lakh ha with cropping intensity of 171%. Small and marginal farmers account for 92% of the total farmer population and own 70% of net cultivated land. Irrigation covers 45% of net cropped area, though there is a high reliance on monsoons. West Bengal is the highest producer of vegetables in the country and 7th in the production of fruits. Horticultural crop covers 21% of net cultivable area in the State. West Bengal covers 88,752 sq. k.m. and is the 3rd largest economy of

Research setting and Social Ecology

59

India. Kolkata is the state capital. There are over 23 towns with a population of over 1,00,000. The largest cities are, Kolkata, Howrah, Asansol, Durgapur and Siliguri. Other important towns include Darjeeling, Kharagpur and Haldia. The state shares international boundaries with Bangladesh, Bhutan and Nepal. The River Ganga and its numerous tributaries have contributed to some of the most fertile regions in the world. In West Bengal, agriculture is the mainstay for about 70 per cent of the population. Land usage planning is: arable land 62.8 per cent; forests 13.38 per cent; the rest is for other purposes. The state West Bengal has been a centre of a rich history, culture and heritage. With a population of over 90 million, West Bengal is the fourth most populous state in India, and ranks 1st in terms of population density. West Bengal is predominantly an agriculture driven state, however, there has been a rich tradition of industry since the start of the industrial age.

Map 4.4: Map of West Bengal

4.11: District Nadia at a Glance District Nadia is agriculture based district and is located in the heart of West Bengal. The entire district lies in the rich alluvial zone of the Ganga and its tributaries. Nadia or Nabadwip is rich by the memory of Lord Shri Chaitanya Mahaprabhu, who was born on 1486 A.D.

4.12: General Information About the District The district is bounded in the north and north-west by the district Murshidabad. On the north-east, it is bounded by the Republic of Bangladesh and in the south

60

Entrepreneurial Communication in Agriculture

and south-east, by the district of North 24 Parganas. The present district was formed by the notification No. 545 – GA, dated 23rd February 1948.There are four administrative subdivisions – Krishnanagar sadar, Ranaghat, Tehatta and Kalyani. However, the district has three agricultural subdivisions, Krishnagar sadar, Ranaghat and Tehatta. Population wise, Nadia ranks 8th, area wise 11th and stands 5th on the basis of population density. The district occupies 4.42 per cent of the total area of the state. Nadia district includes 1,250 villages in 17 blocks under three subdivisions, 96 villages are un-inhabited. An area of 3,927 sq. k.m. is the span of the human habitation. The district has a population of 4,60,4827 (2011 census), of which 51.39 per cent is male and 48.61 per cent is female. It is also recorded that 29.66 per cent of the population belongs to Schedule Caste category and 2.47 per cent belongs to Schedule Tribe category. The Climate of Nadia is characterized by an oppressively hot summer, high humidity all the year round and well-distributed rainfall during the monsoon. The winter sets in the middle of November and continues till the end of February. This district has the highest cropping intensity and crop diversity. Nadia district has a large percentage of agricultural area. Out of total 3,73,414 ha area, about 85,733 ha is not available for agriculture, which is 23 per cent of the total land of the district. Forest area consists of 2,534 ha, which is only 0.67 per cent of the total land. 79.48 percent of the total available cultivable land is irrigated, of which74.9 per cent area is under shallow tube well, 14.9 per cent of the area is irrigated by deep tube well and 5.7 per cent area is covered by river lift irrigation system.

Map 4.5: District Map of West Bengal

Research setting and Social Ecology

61

4.13: Rainfall and Temperature It can be seen that almost each alternative year has maximum rainfall in the month of January. It can also be noted that from 2014 onwards, the total rainfall has a declining trend. The summer is hot and winter is moderate. May is the hottest month of the year. The average temperature ranges from 37.60 degree celsius to 25.40 degree celsius during summer months and between 23.70 degree celsius to 8.5 degree celsius during winter months. Pre-monsoon rain is common in the month of April to May. Monsoon stops by October. Nadia district has 160 to 170 rainy days each year and an average rainfall of 1,300 m.m. annually.

4.14: Topography and Agro-Climatic Characteristics The course of the old Bhairab, shows that the general slope of the district is towards South-east. The slope at present is very gradual and the area is so interspersed with water bodies and marshes and old beds of rivers that the general slope is not easily found. The topographical features of rivers in Nadia district shows that the district has no drainage facility and there is a severe chance of inundation. Flood is almost of regular occurrence. The district comes under Lower Gangetic Plain Region Zone III. This Agro climatic zone has a sub region which is Gangetic Flood Plain. Nadia represents the biggest agro-climatic zone in West Bengal, the new Alluvium Zone. The alluvium zone spreads southward approximately from the head of the delta formed by the succession of rivers. This district has the highest cropping intensity and crop diversity.

4.15: Irrigation and Ground Water The irrigation potential has been generated mostly by minor irrigated projects wherein, more than 693 deep tube wells are opening along with more than 38,540 shallow tube wells with annual draft of 0.893 million ha in the district. In turn, food grain production reached to surplus. But ground water table is being declining at an alarming rate due to over exploitation of ground water resources. As per Agriculture Annual Report, 3,98,212 ha, which is 79.48 per cent of the total cultivable land is under irrigation. Table 4.8: Profile of Haringhata Block of District Nadia, West Bengal Block Profile Location

22.95o North and 88.57o East

Average elevation

10 metres (33ft.)

Creation of municipality

Year 2015

Police station

Haringhata

Population

43,989 persons (2011 census)

Male

21,554 persons (49%) (2011 census)

Female

22,434 persons (51%) (2011 census)

Population below 6 years

4,650 persons (2011 census)

Literacy percentage

78.49 % (2011 census)

Educational institutes

B.C.K.V.,IISER, Haringhata mahavidyalaya, Maulana Abul Kalam Azad University

Entrepreneurial Communication in Agriculture

62

Table 4.9: Profile of Village Bhawanipore of Block Haringhata, West Bengal Geographical area Population Male Female Children below 6 years age Number of household Sex ratio Percentage of literacy Total workers Main workers Main workers cultivators Agricultural labourers Household industries Other workers Marginal workers

Village Profile 360 ha 2,438 persons (2011 census) 1,240 persons (2011 census) 1,198 persons (2011 census) 361 persons (2011 census) 581 1000:966 61.63% (2011 census) 666 persons (male 627, female 39) 393 persons (male 375, female 18) 150 persons (male 148, female 2) 210 persons (male 207, female 3) 3 (male 1, female 2) 30 (male 19, female 11) 273 (male 252, female 21)

Table 4.10: Profile of Chakdaha Block, West Bengal Village Profile Location Average elevation Located in Police station Population Male Female Population below 6 years Literacy percentage Educational institutes 2nd largest vegetable market in the state Biggest industrial economy Health care facility

23.08o North and 88.52o East 11 metres (36 ft.) NH 12 (Earlier NH 34) Chakdaha 1,32,855 persons (2011 census) 67,135 persons (2011 census) 65,720 persons (2011 census) 9,829 persons (2011 census) 90.95% (2011 census) Chakdaha college established in 2002 Singher hat Supreme paper mills Ltd. Chakdaha general hospital

Other workers

30 (male 19, female 11)

Marginal workers

273 (male 252, female 21)

Table 4.11: Profile of Village Ghoragacha of Block Chakdaha, West Bengal Village Profile Population Male Female General category people Schedule Caste category people Children under 6 years age Number of households Sex ratio (According to 2011 census) Literacy rate

1,757 persons (2011 census) 880 persons (50%) (2011 census) 877 persons(50%) (2011 census) 56% (2011 census) 44% (2011 census) 9 % of the population (51% boys and 49% girls) Approximately 272 1000:967 52% (2011 census)

Research setting and Social Ecology

63

Map 4.6: Map of Nadia district of West Bengal



Chapter

5

RESEARCH METHODOLOGY 5.1:

Research Methodology

Research Methodology is the systematic and theoretical analysis and applicability of the methods applied to a field of study. It contains the theoretical analysis of the body of methods and principles associated with a branch of knowledge. The deliberation on the methodology has been made to understand the concept, methods and techniques which were utilized to design the study, collection and analysis of the data and interpretation of the findings for the revelation of truth and formulation of theories. This chapter deals with the methods and procedures used in the study and consist of mainly seven parts. (i) Locale of research. (ii) Pilot study. (iii) Methods of sampling. (iv) Variables and Measurement. (v) Preparation of schedule. (vi) Tools and Techniques of Data collection. (vii) Statistical Analysis and interpretation of data.

5.2: Locale of Research 5.2.1: Selection of the States Two states, Tripura and West Bengal were selected through Purposive sampling method for the study because the researcher has close familiarity with these states. Tripura is her birth place and native land, and West Bengal is her current place of education. So, these two states are easily accessible to the researcher. Also the research involves a comparative study of entrepreneurial communication process of these two states. Therefore, two states, Tripura and West Bengal were selected for the present study.

Research Methodology

65

5.2.2: Selection of the Districts Keeping in view agriculturally and socio-economically developing areas and the area where most of the villagers are engaged in entrepreneurial activities, West District of Tripura and Nadia district of West Bengal were selected for the study.

5.2.3: Selection of the Blocks Shantipara and Mohanpur Blocks from West Tripura district of Tripura and Haringhata and Chakdaha Blocks from Nadia district of West Bengal were purposively selected for the study. These blocks were selected because the researcher has close familiarity with these areas, the people, their culture and the local dialect, which facilitate the study and the process of data collection. The area was also easily accessible to the researcher in terms of transportation and place of residence.

5.2.4: Selection of the Villages Villages Bamutia and Kamalghat under the Blocks Shantipara and Mohanpur respectively from West Tripura district of Tripura and villages Bhawanipore and Ghoragacha under the Blocks Haringhata and Chakdaha respectively from Nadia district of West Bengal were selected purposively for the study. The main reason behind the selection of these villages was due to the presence of large number of farmers involved in entrepreneurial activities.

5.2.5: Selection of the Respondents 38 respondents from each of the four villages, and in total 152 respondents were selected for the study through Systematic Random sampling method.

5.3: Pilot Study Before going for the collection of data, Pilot study was conducted to understand the area, institution, communication facilities, Extension system and attitude of people. Basic situational and background information were collected during the period of pilot study from different sources, including, Panchayat office, Block office, ADO office and other institutions. After the Pilot study, data were collected from the samples and the period of data collection was approximately from August 2016 to January 2018.

5.4: Methods of Sampling Purposive as well as Systematic Random Sampling method were adopted for the study. A Purposive sampling is a non-probability sampling, which is selected based on characteristics of a population and the objective of the study. Purposive sampling is also known as judgmental, selective or subjective sampling. Systematic Random sampling is a sampling method involving the selection of elements from an ordered sampling frame and the most common form of this sampling is an equiprobability method. In this approach, progression through the list is treated circularly, after which it will return to the top once the end of the list is passed. The sampling starts by selecting an element from the list at random and then every nth element in the frame is selected, where ‘n’ is the sampling interval.

Entrepreneurial Communication in Agriculture

66

For selection of State, District, Block and Village, Purposive sampling technique was employed and for the selection of respondents, Systematic Random sampling was employed. The first respondent was selected randomly and after that, all therespondent were selected systematically. In total, 152 respondents were selected, 76 respondents from Tripura and 76 respondents from West Bengal, that is, 38 respondents from each of the four villages were selected.The Systematic Random sampling was done by the following way:

• Effective respondents from each village = 114



• Total number of respondents selected from each village = 38



• Class interval = 114/38 = 3



• By applying class interval of 3, let’s say 18, then 21, 24, 27,.……….N respondents were selected from each of the four villages (N = Number of respondents) Table 5.1: Types and process of sampling (Tripura) Step

Level

Approach

I

State Tripura

Purposive sampling

II

District West Tripura

Purposive sampling

III

Blocks Shantipara and Mohanpur

Purposive sampling

IV

Villages Bamutia and Kamalghat

Purposive sampling

V

Respondents 76

Systematic Random sampling

District West Tripura

Village Kamalghat

Respondents 38 no.

Block Shantipara

Village Bamutia

Respondents 38 no.

Systematic Random Sampling Method

Block Mohanpur

Purposive Sampling Method

Tripura

Research Methodology

67

Table 5.2: Types and process of sampling (West Bengal) Step

Level

Approach

State West Bengal

Purposive sampling

II

District Nadia

Purposive sampling

III

Blocks Haringhata and Chakdaha

Purposive sampling

IV

Villages Bhawanipore and Ghoragacha

Purposive sampling

V

Respondents 76

Systematic Random sampling

West Bengal District Nadia

Village Bhawanipore

Respondents 38 no.

Block Chakdaha

Village Ghoragacha

Respondents 38 no.

Systematic Random Sampling Method

Block Haringhata

Purposive Sampling Method

I

Figure 5.2: Types and process of sampling (West Bengal)

5.5: Variables and Measurement After reviewing various literatures related to the field of present study and by consulting with my respected chairman and other advisory committee members and by keeping in mind the objectives of the research, a list of variables, both Independent and Dependent, was prepared. On the basis of selected variables, a schedule was formed.

5.5.1: The Independent Variables Age (x1), Education (x2), No. of enterprise (x3), Year of enterprise (x4), Training exposure (x5), Family size (x6), Family education (x7), Material possessed (x8), Size ­­of holding (x9), Size of homestead land (x10), Size of cultivable land (x11), Size of land under irrigation (x12), No. of fragments (x13), Crop yield (x14), Livestock yield (x15), Cropping intensity (x16), Income (on farm & off farm) (x17), Family expenditure (x18), Marketable surplus (x19), Marketed surplus (x20), Family labour (x21), No. of male workers (x22) and No. of female workers (x23).

Entrepreneurial Communication in Agriculture

68

Table 5.3: List of Independent variables with their empirical measurement Sl. No.

Variables

Empirical measurement

1

Age (x1)

Chronological age of the respondent (count)

2

Education (x2)

Year of schooling of the respondent (count)

3

No. of enterprise (x3)

Number of enterprises one manage in his farm (count)

4

Year of enterprise (x4)

Number of years associated with the enterprise (count)

5

Training exposure (x5)

Number of trainings attended till date (count)

6

Family size (x6)

Total no. of family members (count)

7

Family education (x7)

Total count of educational scores of family members divided by family size

8

Material possessed (x8)

By asking the respondents whether they possess T.V., Fridge, Car, etc (count)

9

Size of holding (x9)

Total area of land owned by a family divided by family size, in bigha

10

Size of homestead land (x10)

Total area of land surrounding the dwelling house owned by a family divided by family size, in bigha

11

Size of cultivable land (x11)

Total area of land under cultivation of crop, rearing of livestock, fishery, etc. in bigha

12

Size of land under irrigation (x12)

Size of irrigated land in bigha

13

No. of fragments (x13)

Arithmetic count of pieces of the land (fragments) under the ownership of the family.

14

Crop yield (x14)

In Rs/bigha/month

15

Livestock yield (x15)

In Rs/bigha/month

16

Cropping intensity (x16)

(Gross Cropped Area/Net Cropped Area) x 100 {in percentage}

17

Income (on farm & off farm) (x17)

The income expressed in monetary value generated from an unit area of farm and from off farm pursuits (Rs/capita/ month)

18

Family expenditure (x18)

Total expenditure incurred in monetary value per month by family members divided by family size

19

Marketable surplus (x19)

Assessment over the produce to generate marketable surplus in Rs/month (predicted value)

20

Marketed surplus (x20)

Quantity of yield proportionate to total yield as already disposed off to the market in Rs/month (realised value)

21

Family labour (x21)

Labour of adult family members equivalent to hired labours per month

22

No. of male workers (x22)

Number of adult male labours working per month in the field and their level of interaction

23

No. of female workers (x23)

Number of adult female labours working per month in the field and their level of interaction

Research Methodology

69

5.5.2: The Dependent Variables Farm enterprise information from cosmopolite sources (y1), Farm enterprise information from localite sources (y2), Information seeking and responding behavior (y3), Entrepreneurial communication behavior (y4), Value addition (y5), Economical communication (y6) and Transportation cost (y7). Table 5.4: List of Dependent variables with their empirical measurement Farm enterprise information from cosmopolite sources (y1) Source

Access (10 point scale rating hypothetically, according to ‘z’ scale)

Bank, Expert, Institution, Scientists, NGO

By rating in 10 point scale

Farm enterprise information from localite sources (y2) Source

Access (10 point scale rating hypothetically, according to ‘z’ scale)

Friends, Neighbour, Relatives, Family, members, Local leader, Dealer Market

By rating in 10 point scale

Information seeking and responding behavior (y3) a. Come to know

Through self initiative (3)

b. Motivation process

Through peer interaction (2)

c. Adoption process

Through mass media (1)

d. Perceptional process Entrepreneurial communication behavior (y4) a.

Communication flow out

1) 2) 3)

Informed to Advised to Persuaded for adoption

b.

Communication flow in

1) 2) 3)

Received from Advised by Persuaded by

c.

Communication interactive

1) 2) 3)

Self mobilization Mutually shared Mobilized by counterpart

Person

Institution

Information given to Information given to others persons others institutions

Person Information given to others persons

Person Information given to others persons

Frequency Calculating their frequency by multiplying categories of communication flow out process with person and institution

Institution

Frequency

Information given to others institutions

Calculating their frequency by multiplying categories of communication flow in process with person and institution

Institution

Frequency

Information given to others institutions

Calculating their frequency by multiplying categories of communication interactive process with person and institution

Entrepreneurial Communication in Agriculture

70

Value addition (y5) Crops and livestocks

Rs/year

Field crops, Vegatables, Fruits, Livestocks, Others

It is expressed in monetary value in Rs/year (also Rs/month)

Economical communication (y6) Source

Volume

Number of visits

Frequency

Bank, Cooperatives, Private money lenders, Post office, Others

Volume of transactions done

Number of times they visit the sources

Calculating their frequency of visit by multiplying the volume with the number of visits per year (also per month)

Transportation cost (y7) Mode Truck, Bike, Van, Auto, Cycle, Manual, Others

Volume disposed Amount send to the market

Distance covered Distance of market from village

the the

Cost Cost incurred for transportation in Rs/year (also Rs/month)

5.6: Preparation of the schedule After quantifying the variables (both dependent and independent) for measurement, a structured interview schedule was prepared with the help of respected chairman.

5.7: Tools and Techniques of data collection The major tool used for collection of primary data in the study was structured interview schedule. The primary data in the present study were collected from the farmers with the help of structured interview schedule. Only the functional farmers were taken as respondents for the study and secondary data were collected from the Agriculture Department of Tripura and West Bengal, Bidhan Chandra Krishi Viswavidyalaya, College of Agriculture, Tripura, departmental library, journals, Central library of Bidhan Chandra Krishi Viswavidyalaya, etc.

5.8: Statistical analysis and interpretation of data After collection of data, they were processed and analyzed in accordance with the outline laid down for the purpose at the time of developing the research plan. Processing implies editing, coding, classification and tabulation of collected data. The main statistical techniques and tools used in the present study are given below:

5.8.1: Range It means the measure of maximum and minimum value of variables.

5.8.2: Mean The mean is the arithmetic average and is the result obtained when the sum of the value of the individual in the data is divided by the number of individuals in the

Research Methodology

71

data. Mean is simplest and relatively stable measure of central tendency. When the data are expressed in a frequency distribution (grouped), the mean calculated by the formula used was as follows:

∑ x= Where,

N i =1

fi. xi.

N

(i) x = Mean of the observation (ii) fi = Frequency of the class (iii) xi = Mid value of the class (iv) N = Total number of observations

5.8.3: Median Median is the mid-value separating the higher half of a data sample, a population, or a probability distribution from the lower half. For example, in the data set {1, 3, 3, 6, 7, 8, 9}, the median is 6, the fourth largest, and also the fourth smallest, number in the sample. For situation of a continuous probability distribution, the median is the value such that a number is equally likely to fall above or below it.

5.8.4: Mode Mode is the value that appears most often. It is the value at which its probability mass function takes its maximum value. In other words, it is the value that is most likely to be sampled. Like the statistical mean and median, the mode is a way of expressing, in a (usually) single number, important information about a random variable or a population. The numerical value of the mode is same as that of the mean and median in a normal distribution, and it may be very different in highly skewed distributions.The mode is not necessarily unique to a given discrete distribution, since the probability mass function may take the same maximum value at several points x1, x2, etc. The most extreme case occurs in uniform distributions, where all values occur equally frequently.

5.8.5: Standard Deviation (S.D.) Standard deviation is a measure of dispersion which implies the extent to which observation vary among themselves. Standard deviation (SD) of a set of observation is the square root of the arithmetic mean of squares or deviations from arithmetic mean. It is denoted by a Sigma. For frequency distribution, standard deviation is measured as follows:

σ=± Where,

1

Nfi ( xi − x )2

(i) sσ = Standard Deviation (ii) N = Total no of observation in a particular cell (iii) x = Value of observation in a particular cell

Entrepreneurial Communication in Agriculture

72

(iv) f = Frequency of observation (v) x = Mean number of observation (vi) I = Any number (e.g. 1,2,3) denoting position

5.8.6: Coefficient of Variation (C.V.) A measure of variation which is independent of the unit of measurement is proved by the coefficient of variation. Being unit free, this is useful for comparison of variability between different populations. The Coefficient of variation is standard deviation expressed as percentage of the mean. Coefficient of variation is measured by the formula:

C.V. =

S.D. × 100 Mean

5.8.7: Correlation Coefficient When an increase or decrease in one variety is accompanied by an increase or decrease in other variety, the two are said to be correlated and the phenomenon is known as correlation. Correlation coefficient (r) is a measure of the relationship between two variables, which are at the interval or ratio level of measurement and are linearly related. A pearson product-moment “r” is computed by the formula:

rxy = Where,

N ∑ XY(∑ X )(∑ Y ) [N ∑ X − (∑ X )2 ][N ∑ Y 2 − (∑ Y )2 ] 2

(i) X and Y = Original scares in variables X and Y (ii) N = Number of paired scores (iii) ∑XY = Each X multiplied by its corresponding Y, then summed (iv) ∑X = Sum of X scores (v) ∑X2 = Each of X squared, then summed (vi) (∑X)2 = Sum of X score squared (vii) ∑Y = Sum of Y scores (viii) ∑Y2 = Each of Y squared, then summed (ix) (∑Y)2 = Sum of Y score squared The range of Correlation coefficient is between -1 to +1. This means that -1 is perfect negative correlation, +1 is perfect positive correlation. If the numbers of errors increase with increase in typing speed, it indicates positive correlation and if the numbers of correct words decrease with increase in typing speed, it is indicated as negative correlation.

5.8.8: Step wise Regression Analysis Generally a number of antecedent variables simultaneously contribute to influence the consequent variables, as in the case under study. It is most important to know

Research Methodology

73

the extent to which the exogenous variables, individually or jointly, could predict or contribute towards the consequent variable. This was done by computing Step wise Regression Analysis. If Y is the consequent variable and X1, X2, X3 are the exogenous variables, then the Step wise Regression equation is given by the following formula: Y = a + b1X1 + b2X2+ b3X3..… Or,

Y = a + ∑bx

Where, (i) a = Intercept point of the regression line which is in the y-axis. (ii) b = Slope of the regression line is also called as regression coefficient.

5.8.9: Factor Analysis Factor analysis is a very useful and popular method of multivariate research technique, mostly used in social sciences. This technique allows the researcher to group variables into factors (based on correlation between variables). The factors so derived may be treated as new variables (often termed as latent variables) and their value derived by summing the values of the original variables, which had been grouped into the factor. The meaning and name of such new variable is subjectively determined by the researcher.

5.8.9.1: Factor Analysis is used (i) To reduce the dimensionality of large number of variables to a fewer number of factors. (ii) To confirm the hypothesized factor structure by way of testing of hypothesis about the structure of variables in terms of expected number of significant factor loading.

5.8.9.2: Eigenvalues Eigenvalues are a special set of scalars associated with a linear system of equations (i.e., a matrix equation) that are sometimes also known as characteristic roots, characteristic values, proper values, or latent roots. The determination of the eigenvalues and eigenvectors of a system is very important in Principal component analysis. Each eigenvalue is paired with a corresponding so-called eigenvector.

5.8.9.3: Factor loading Factor loadings are part of the outcome from factor analysis, which serves as a data reduction method designed to explain the correlations between observed variables, using a smaller number of factors. Because factor analysis is a widely used method in social science research, an in-depth examination of factor loadings and the related factor-loading matrix facilitates a better understanding and use of the technique. Factor loadings are coefficients found in either a factor pattern matrix or a factor structure matrix. The former matrix consists of regression coefficients that multiply common factors to predict observed variables, also known as manifest variables, whereas the latter matrix is made up of product-moment correlation coefficients between common factors and observed variables.

Entrepreneurial Communication in Agriculture

74

5.8.9.4: Varimax rotation In statistics, a varimax rotation is used to simplify the expression of a particular sub-space in terms of just a few major items each. The actual coordinate system is unchanged. It is the orthogonal basis that is being rotated to align with those coordinates. The sub-space found with principal component analysis or factor analysis is expressed as a dense basis with many non-zero weights which makes it hard to interpret. Varimax is so called because it maximizes the sum of the variances of the squared loadings (squared correlations between variables and factors). Preserving orthogonality requires that it is a rotation that leaves the subspace invariant.

5.8.10: Path analysis In statistics, path analysis is used to describe the directed dependencies among a set of variables. This includes models equivalent to any form of multiple regression analysis, factor analysis, as well as more general families of models in the multivariate analysis of variance and covariance analyses (MANOVA, ANOVA, ANCOVA). In addition to being thought of as a form of multiple regression focusing on causality, path analysis can be viewed as a special case of structural equation modeling (SEM) - one in which only single indicators are employed for each of the variables in the causal model. That is, path analysis is SEM with a structural model, but no measurement model. Other terms used to refer to path analysis include causal modeling, analysis of covariance structures, and latent variable models. Path analysis was developed around 1918 by geneticist Sewall Wright, who wrote about it more extensively in the 1920s. Variables in Interaction Tripura 23 Independent Variables 7 Dependent Variables

West Bengal 23 Independent Variables

Pooled States (Tripura and West Bengal) 23 Independent Variables 7 Dependent Variables

7 Dependent Variables Dependent variables under study Y1 = Farm enterprise information from cosmopolite sources Y2 = Farm enterprise information from localite sources Y3 = Information seeking and responding behaviour Y4 = Entrepreneurial communication behaviour Y5 = Values addition Y6 = Economical communication Y7 = Transporation cost

Model 5.1: Structure of variables in interaction



Chapter

6

RESULTS AND DISCUSSION 6.1: Results and discussion: concept Result is the outcome, consequences or conclusion of a problem, probe or experiment organized after a period of time. This conclusion can be one result, multiple results or no result as such. The length of time taken to find a result can vary from less than a second to many years. In this chapter the result of the Research has been elaborated and also discussed later. The purpose of the discussion/revelation is to interpret and describe the significance of our findings in light of what was already known about the research problem being investigated, and to explain any new understanding or insights about the problem, after we have taken the findings into consideration. The discussion will always connect to the introduction by way of the research questions or hypothesis we posed and the literature we reviewed, but it does not simply repeat or rearrange the introduction and the discussion always explain how our study has moved towards the research problem. Table 6.1: Distribution of variables in terms of Range, Mean, Median, Mode, standard Deviation and Coefficient of variation of villages Bamutia and Kamalghat, Tripura [N=76] Sl. No.

Variables

Range Min

1

Age (x1)

2

Range

Mean

Median

Mode

S.D.

Max

C.V. (%)

32

75

43

49.18

48

52

10.93

22.22

Education (x2)

4

15

11

7.94

8

8

2.47

31.10

3

No. of enterprise (x3)

1

8

7

5.63

6

6

1.22

21.66

4

Year of enterprise (x4)

12

62

50

31.22

28

26

12.23

39.17

5

Training exposure (x5)

3

52

49

19

15

15

11.65

61.09

Entrepreneurial Communication in Agriculture

76 6

Family size (x6)

2

7

5

4

4

5

1.36

30.42

7

Farm education (x7)

13

80

67

39.50

34.50

32

16.72

42.32

8

Material possessed (x8)

23

65

42

38.01

35

34

10.03

26.38

9

Size of holding (x9)

1.25

12

10.75

4.71

4.50

4

1.82

38.64

10

Size of homestead land (x10)

0.18

2.50

2.32

0.68

0.50

0.50

0.51

75

11

Size of cultivable land (x11)

0.75

9.50

8.75

4.02

4.02

4.50

1.51

37.56

12

Size of land under irrigation (x12)

0.75

9.50

8.75

4.03

3.97

4.50

1.57

38.95

13

No. of fragments (x13)

2

14

12

8.02

8

4

3.13

39.02

14

Crop yield (x14)

1782

30613

28831

7282

5857

2333

4991.99

68.55

15

Livestock yield (x15)

1336

37426

36090

8755

7829

9430

5387.66

61.53

16

Cropping intensity (x16)

101

204

103

130.94

119

125

27.40

20.92

17

Income (on farm & off farm) (x17)

24065 143548

119483 56982.29

52444 52000 24205.41

42.47

18

Family expenditure (x18)

40000 101000

100996

30938

25174 36963

15437

49.89

19

Marketable surplus (x19)

10000

77500

67500

26935

24900 30000 12409.52

46.07

20

Marketed surplus (x20)

9500

75500

66000 25872.58

23375 22000 12408.31

47.95

21

Family labour (x21)

1

2

1

1

1

1

0.49

34

22

No. of male workers (x22)

50

110

60

80

84

85

14.23

17.60

23

No. of female workers (x23)

20

104

84

47

50

50

18.43

38.62

24

Farm enterprise information from cosmopolite sources (y1)

1

8

7

4.70

5

5

1.53

32.55

Results and Discussion

77

25

Farm enterprise information from localite sources (y2)

2

9.50

7.50

6

5.80

5

1.70

28.33

26

Information seeking and responding behavior (y3)

1

3

2

2.40

2.40

3

0.50

20.83

27

Entrepreneurial communication behavior (y4)

10

45

35

23.11

22.25

25

8.94

38.68

28

Value addition (y5)

1200

6525

5325

3235.61

2729.5

2500

1672.06

51.67

29

Economical communication (y6)

20

3630

3610

90.51

40

36

411.74

45.40

30

Transportation cost (y7)

4320

9600

5280

6698.35

6500

8500

1606.36

23.98

Table 6.1 presents the distribution of variables in terms of Range, Mean, Median, Mode, Standard Deviation and Coefficient of Variation of two villages of Tripura. It has been found that for the independent variable, Age (x1), the maximum value of age is 75 years and the minimum value of age is 32 years. The mean value of age group was found to be 49.18 years with the Standard Deviation 10.93 for the total distribution taken for the study. Coefficient of Variation for this variable is 22.22 per cent, which shows that the level of consistency in the distribution of Age (x1) is high. It has been found that for the independent variable, Education (x2), the maximum years of education is 15 years and the minimum years of education is 4 years. The mean value of year of education was found to 7.94 years, with the Standard Deviation 2.47 for the total distribution taken for the study. Coefficient of Variation for this variable is 31.10 per cent, which shows that the level of consistency in the distribution of Education (x2) is high. It has been found that for the independent variable, No. of enterprise (x3), the maximum value is 8 numbers of enterprises and the minimum value is 1 number of enterprise. The mean value of number of enterprise was found to be 5.63, with the Standard Deviation 1.22 for the total distribution taken for the study. Coefficient of Variation for this variable is 21.66 per cent, which shows that the level of consistency in the distribution of No. of enterprise (x3) is high. It has been found that for the independent variable, Year of enterprise (x4), the maximum number of years is 62 years and the minimum number of years is 12 years. The mean of number of years was found to be 31.22 years, with the Standard Deviation 12.33 for the total distribution taken for the study. Coefficient of Variation for this variable is 39.17 per cent, which shows that the level of consistency in the distribution of Year of enterprise (x4) is high.

78

Entrepreneurial Communication in Agriculture

It has been found that for the independent variable, Training exposure (x5), the maximum number of trainings attended is 52 and the minimum number of trainings attended is 3 trainings. The mean of number of trainings attended was found to be 19, with the Standard Deviation 11.65 for the total distribution taken for the study. Coefficient of Variation for this variable is 61.09 per cent, which shows that the level of consistency in the distribution of Training exposure (x5) is medium. It has been found that for the independent variable, Family size (x6), the maximum number of family members is 7 and the minimum number of family members is 2. The mean of number of family members was found to be 4, with the Standard Deviation 1.36 for the total distribution taken for the study. Coefficient of Variation for this variable is 30.42 per cent, which shows that the level of consistency in the distribution of Family size (x6) is high. It has been found that for the independent variable, Family education (x7), the maximum value is 80 after adding the educational years of all the family members and the minimum value is 13 after adding the educational years of all the family members. The mean value of education was found to be 39.50, with the Standard Deviation 16.72 for the total distribution taken for the study. Coefficient of Variation for this variable is 42.32 per cent, which shows that the level of consistency in the distribution of Family education (x7) is high. It has been found that for the independent variable, Material possessed (x8), the maximum scoring of material possessed is 65 and the minimum scoring of material possessed is 23. The mean scoring of material possessed was found to be 38.01, with the Standard Deviation 10.03 for the total distribution taken for the study. Coefficient of Variation for this variable is 26.38 per cent, which shows that the level of consistency in the distribution of Material possessed (x8) is high. It has been found that for the independent variable, Size of holding (x9), the maximum size of holding is 12 bigha and the minimum size of holding is 1.25 bigha. The mean of size of holding was found to be 4.71 bigha, with the Standard Deviation 1.82 for the total distribution taken for the study. Coefficient of Variation for this variable is 38.64 per cent, which shows that the level of consistency in the distribution of Size of holding (x9) is high. It has been found that for the independent variable, Size of homestead land (x10), the maximum size of homestead land is 2.50 bigha and the minimum size of homestead land is 0.18 bigha. The mean of size of homestead land was found to be 0.68 bigha, with the Standard Deviation 0.51 for the total distribution taken for the study. Coefficient of Variation for this variable is 75 per cent, which shows that the level of consistency in the distribution of Size of homestead land (x10) is medium. It has been found that for the independent variable, Size of cultivable land (x11), the maximum size is 9.50 bigha and the minimum size is 0.75 bigha. The mean of size of cultivable land was found to be 4.02 bigha, with the Standard Deviation 1.51 for the total distribution taken for the study. Coefficient of Variation for this variable is 37.56 per cent, which shows that the level of consistency in the distribution of Size of cultivable land (x11) is high.

Results and Discussion

79

It has been found that for the independent variable, Size of land under irrigation (x12), the maximum size of land is 9.50 bigha and the minimum size of land is 0.75 bigha. The mean of size of land under irrigation was found to be 4.03 bigha, with the Standard Deviation 1.57 for the total distribution taken for the study. Coefficient of Variation for this variable is 38.95 per cent, which shows that the level of consistency in the distribution of Size of land under irrigation (x12) is high. It has been found that for the independent variable, No. of fragments (x13), the maximum number of fragments is 14 and the minimum number of fragments is 2. The mean of number of fragments was found to be 8.02, with the Standard Deviation 3.13 for the total distribution taken for the study. Coefficient of Variation for this variable is 39.02 per cent, which shows that the level of consistency in the distribution of No. of fragments (x13) is high. It has been found that for the independent variable, Crop yield (x14), the maximum yield is Rs 30,613 per year (Rs 2,551 per month) and the minimum yield is Rs 1,782 per year (Rs 148.5 per month). The mean of crop yield was found to be Rs 7,282 per year (Rs 606.83 per month), with the Standard Deviation 4991.99 for the total distribution taken for the study. Coefficient of Variation for this variable is 68.55 per cent, which shows that the level of consistency in the distribution of Crop yield (x14) is medium. It has been found that for the independent variable, Livestock yield (x15), the maximum yield is Rs 37,426 per year (Rs 3,118.83 per month) and the minimum yield is Rs 1,336 per year (Rs 111.33 per month). The mean of livestock yield was found to be Rs 8,755 per year (Rs 731.25 per month), with the Standard Deviation 5387.66 for the total distribution taken for the study. Coefficient of Variation for this variable is 61.53 per cent, which shows that the level of consistency in the distribution of Livestock yield (x15) is medium. It has been found that for the independent variable, Cropping intensity (x16), the maximum intensity is 204 per cent and the minimum intensity is 101 per cent. The mean value of cropping intensity was found to be 130.94 per cent, with the Standard Deviation 27.40 for the total distribution taken for the study. Coefficient of Variation for this variable is 20.92 per cent, which shows that the level of consistency in the distribution of Cropping intensity (x16) is high. It has been found that for the independent variable, Income (on farm & off farm) (x17), the maximum amount of income is Rs 1,43,548 per year (Rs 11,962.33 per month) and the minimum amount of income is Rs 24,065 per year (Rs 2,005.41 per month). The mean value of income was found to be Rs 56,982.29 per year (Rs 4,748.52 per month), with the Standard Deviation 24205.41 for the total distribution taken for the study. Coefficient of Variation for this variable is 42.47 per cent, which shows that the level of consistency in the distribution of Income (on farm & off farm) (x17) is high. It has been found that for the independent variable, Family expenditure (x18), the maximum amount of expenditure is Rs 1,01000 per year (Rs 8,416.66 per month) and the minimum amount of expenditure is Rs 40,000 per year (Rs 3,333.33 per month). The mean amount of expenditure was found to be Rs 30,938 per year (Rs

80

Entrepreneurial Communication in Agriculture

2,578.16 per month), with the Standard Deviation 15437 for the total distribution taken for the study. Coefficient of Variation for this variable is 49.89 per cent, which shows that the level of consistency in the distribution of Family expenditure (x18) is high. It has been found that for the independent variable, Marketable surplus (x19), the maximum value of marketable surplus is Rs 77,500 per year (Rs 6,458.33 per month) and the minimum marketable surplus is Rs 10,000 per year (Rs 833.33 per month). The mean of marketable surplus was found to be Rs 26,935 per year (Rs 2,244.58 per month), with the Standard Deviation 12409.52 for the total distribution taken for the study. Coefficient of Variation for this variable is 46.07 per cent, which shows that the level of consistency in the distribution of Marketable surplus (x19) is high. It has been found that for the independent variable, Marketed surplus (x20), the maximum marketed surplus is Rs75,500 per year (Rs 6,291.66 per month) and the minimum value of marketed surplus is Rs 9,500 per year (Rs 791.66 per month). The mean value of marketed surplus was found to be Rs 25,872.58 per year (Rs 2,156 per month), with the Standard Deviation 12408.31 for the total distribution taken for the study. Coefficient of Variation for this variable is 47.95 per cent, which shows that the level of consistency in the distribution of Marketed surplus (x20) is high. It has been found that for the independent variable, Family labour (x21), the maximum number of family labour is 2 and the minimum number of family labour is 1. The mean of number of family labour was found to be 1, with the Standard Deviation 0.49 for the total distribution taken for the study. Coefficient of Variation for this variable is 34 per cent, which shows that the level of consistency in the distribution of Family labour (x21) is high. It has been found that for the independent variable, No. of male workers (x22), the maximum number of male workers required is 110 per year (approximately 10 workers per month) and the minimum number of male workers required is 50 per year (approximately 5 workers per month). The mean of male worker required was found to be 80 per year (approximately 7 workers per month), with the Standard Deviation 14.23 for the total distribution taken for the study. Coefficient of Variation for this variable is 17.60 per cent, which shows that the level of consistency in the distribution of No. of male workers (x22) is high. It has been found that for the independent variable, No. of female workers (x23), the maximum number of female workers required is104 per year (approximately 9 workers per month) and the minimum number of female workers required is 20 per year (approximately 2 workers per month). The mean of female workers required was found to be 47 per year (approximately 4 workers per month), with the Standard Deviation 18.43 for the total distribution taken for the study. Coefficient of Variation for this variable is 38.62 per cent, which shows that the level of consistency in the distribution of No. of female workers (x23) is high. It has been found that for the dependent variable, Farm enterprise information from cosmopolite sources (y1), the maximum frequency of information is 8 and the minimum frequency of information is 1. The mean frequency of information was

Results and Discussion

81

found to be 4.70, with the Standard Deviation 1.53 for the total distribution taken for the study. Coefficient of Variation for this variable is 32.55 per cent, which shows that the level of consistency in the distribution of Farm enterprise information from cosmopolite sources (y1) is high. It has been found that for the dependent variable, Farm enterprise information from localite sources (y2), the maximum frequency of information is 9.50 and the minimum frequency of information is 2. The mean frequency of information was found to be 6, with the Standard Deviation 1.70 for the total distribution taken for the study. Coefficient of Variation for this variable is 28.33 per cent, which shows that the level of consistency in the distribution of Farm enterprise information from localite sources (y2) is high. It has been found that for the dependent variable, Information seeking and responding behavior (y3), the maximum frequency of information seeking is 3 and the minimum frequency of information seeking is 1. The mean frequency of information seeking was found to be 2.40, with the Standard Deviation 0.50 for the total distribution taken for the study. Coefficient of Variation for this variable is 20.83 per cent, which shows that the level of consistency in the distribution of Information seeking and responding behavior (y3) is high. It has been found that for the dependent variable, Entrepreneurial communication behavior (y4), the maximum frequency of communication behavior is 45 and the minimum frequency of communication behavior is of 10. The mean frequency of communication behavior was found to be 23.11, with the Standard Deviation 8.94 for the total distribution taken for the study. Coefficient of Variation for this variable is 38.68 per cent, which shows that the level of consistency in the distribution of Entrepreneurial communication behavior (y4) is high. It has been found that for the dependent variable, Value addition (y5), the maximum amount of value addition is Rs 6,525per year (Rs 543.75 per month) and the minimum amount of value addition is Rs 1,200 per year (Rs 100 per month). The mean amount of value addition was found to be Rs 3,235.61 per year (Rs 269.63 per month), with the Standard Deviation 1672.06 for the total distribution taken for the study. Coefficient of Variation for this variable is 51.67 per cent, which shows that the level of consistency in the distribution of Value addition (y5) is high. It has been found from the study that for the dependent variable, Economical communication (y6), the maximum frequency is 36 and the minimum frequency is of 20. The mean of frequency was found to be 90.51, with the Standard Deviation 411.74 for the total distribution taken for the study. Coefficient of Variation for this variable is 45.40 per cent, which shows that the level of consistency in the distribution of Economical communication (y6) is high. It has been found that for the dependent variable, Transportation cost (y7), the maximum value of transportation cost is Rs 9,600 per year (Rs 800 per month) and the minimum value of transportation cost is Rs 4,320 per year (Rs 360 per month). The mean value of transportation cost was found to be Rs 6,698.35 per year (Rs 558.19 per month), with the Standard Deviation 1606.36 for the total distribution taken for the study. Coefficient of Variation for this variable is 23.98 per cent, which shows that the level of consistency in the distribution of Transportation cost (y7) is high.

Entrepreneurial Communication in Agriculture

82

Table 6.2: Distribution of variables in terms of Range, Mean, Median, Mode, standard Deviation and Coefficient of variation of villages Bhawanipore and Ghoragacha, West Bengal [N=76] Sl. No.

Variables

Range Min

Range

Mean

Median

Mode

S.D.

Max

C.V. (%)

1.

Age (x1)

27

75

48

49.98

50

50

10.28

20.56

2.

Education (x2)

4

15

11

8.07

8

8

2.65

32.83

3.

No. of enterprise (x3)

1

8

7

4.97

5

5

1.28

25.75

4.

Year of enterprise (x4)

9

60

51

32.75

34

35

10.75

32.82

5.

Training exposure (x5)

2

200

198

22

22

22

22.70

100

6.

Family size (x6)

2

8

6

4

5

5

1.56

32.36

7.

Farm education (x7)

13

76

63

41.93

44

44

18.30

43.64

8.

Material possessed (x8)

23

74

51

40.05

36

34

11.67

29.13

9.

Size of holding (x9)

1.25

30

28.75

5.16

4

4

3.57

69.18

10.

Size of homestead land (x10)

0.10

2

1.90

0.61

0.50

0.50

0.41

67.21

11.

Size of cultivable land (x11)

0.75

29.5

28.75

4.57

3.81

5.50

3.45

75.49

12.

Size of land under irrigation (x12)

0.75

29.50

28.75

4.52

3.82

5.50

3.47

76.76

13.

No. of fragments (x13)

2

15

13

7.39

7

4

3.16

42.76

14

Crop yield (x14)

1708

78666

76958

11992

8590

8300 11821.34

98.57

15

Livestock yield (x15)

9240

32397

23157

6310.89

5061.5

3333

5218.71

82.69

16

Cropping intensity (x16)

102

233

131

126.13

118

116

23.02

18.25

17

Income (on farm & off farm) (x17)

16072 176399

160327 60183.82

57829 57500 27534.57

45.73

18

Family expenditure (x18)

12181

88278

76097 30318.25

27045 40000 13982.64

46.11

19

Marketable surplus (x19)

11322

88121

76799 29371.95

28895 41333 13104.36

44.61

20

Marketed surplus (x20)

11068

86121

75053 28496.42

25326 40000 12986.82

45.57

Results and Discussion 21

Family labour (x21)

22

83 1

3

2

1

1

1

0.52

37.14

No. of male workers (x22)

60

120

60

86

85

85

10.63

12.26

23

No. of female workers (x23)

20

102

82

50

50

50

14.17

28.12

24

Farm enterprise information from cosmopolite sources (y1)

2

8

6

5.32

5

5

1.36

25.56

25

Farm enterprise information from localite sources (y2)

2

9.60

7.60

5.79

5.10

5

1.94

33.50

26

Information seeking and responding behavior (y3)

1

3

2

2.46

2.5

3

0.56

22.76

27

Entrepreneurial communication behavior (y4)

10

48

38

25.56

24

20

10.29

40.25

28

Value addition (y5)

1200

9000

7800

4744.85

4523.5

4500

1873.72

39.48

29

Economical communication (y6)

24

156

132

54.73

45

40

25.27

46.17

30

Transportation cost (y7)

4500

9850

5350

7016.71

7200

4500

1759.31

25.07

Table 6.2 presents the distribution of variables in terms of Range, Mean, Median, Mode, Standard Deviation and Coefficient of Variation of two villages of West Bengal. It has been found that for the independent variable, Age (x1), the maximum value of age is 75 years and the minimum value of age is 27 years. The mean value of age group was found to be 49.98 years with the Standard Deviation 10.28 for the total distribution taken for the study. Coefficient of Variation for this variable is 20.56 per cent, which shows that the level of consistency in the distribution of Age (x1) is high. It has been found that for the independent variable, Education (x2), the maximum years of education is 15 years and the minimum years of education is 4 years. The mean year of education was found to 8.07 years, with the Standard Deviation 2.65 for the total distribution taken for the study. Coefficient of Variation for this variable is 32.83 per cent, which shows that the level of consistency in the distribution of Education (x2) is high. It has been found that for the independent variable, No. of enterprise (x3), the maximum number of enterprises is 8 numbers and the minimum number of

84

Entrepreneurial Communication in Agriculture

enterprises is 1 number. The mean number of enterprise was found to be 4.97, with the Standard Deviation 1.28 for the total distribution taken for the study. Coefficient of Variation for this variable is 25.75 per cent, which shows that the level of consistency in the distribution of No. of enterprise (x3) is high. It has been found that for the independent variable, Year of enterprise (x4), the maximum number of year of enterprises is 60 years and the minimum number of year of enterprises is 9 years. The mean number of year of enterprises was found to be 32.75 years, with the Standard Deviation 10.75 for the total distribution taken for the study. Coefficient of Variation for this variable is 32.82 per cent, which shows that the level of consistency in the distribution of Year of enterprise (x4) is high. It has been found that for the independent variable, Training exposure (x5), the maximum number of trainings attended is 200 and the minimum number of trainings attended is 2. The mean of number of trainings attended was found to be 22, with the Standard Deviation 22.70 for the total distribution taken for the study. Coefficient of Variation for this variable is 100 per cent, which shows that the level of consistency in the distribution of Training exposure (x5) is medium. It has been found that for the independent variable, Family size (x6), the maximum number of family members is 8 and the minimum number of family members is 2. The mean of number of family members was found to be 4, with the Standard Deviation 1.56 for the total distribution taken for the study. Coefficient of Variation for this variable is 32.36 per cent, which shows that the level of consistency in the distribution of Family size (x6) is high. It has been found that for the independent variable, Family education (x7), the maximum value is 76 after adding the educational years of all the family members and the minimum value is 13 after adding the educational years of all the family members. The mean value was found to be 41.93 years, with the Standard Deviation 18.30 for the total distribution taken for the study. Coefficient of Variation for this variable is 43.64 per cent, which shows that the level of consistency in the distribution of Family education (x7) is high. It has been found that for the independent variable, Material possessed (x8), the maximum scoring of material possessed is 74 and the minimum scoring of material possessed is 23. The mean scoring of material possessed was found to be 40.05, with the Standard Deviation 11.67 for the total distribution taken for the study. Coefficient of Variation for this variable is 29.13 per cent, which shows that the level of consistency in the distribution of Material possessed (x8) is high. It has been found that for the independent variable, Size of holding (x9), the maximum size of holding is 30 bigha and the minimum size of holding is 1.25 bigha. The mean of size of holding was found to be 5.16 bigha, with the Standard Deviation 3.57 for the total distribution taken for the study. Coefficient of Variation for this variable is 69.18 per cent, which shows that the level of consistency in the distribution of Size of holding (x9) is medium. It has been found that for the independent variable, Size of homestead land (x10), the maximum size of homestead land is 2 bigha and the minimum size of homestead land is 0.10 bigha. The mean of size of homestead land was found to be

Results and Discussion

85

0.61 bigha, with the Standard Deviation 0.41 for the total distribution taken for the study. Coefficient of Variation for this variable is 67.21 per cent, which shows that the level of consistency in the distribution of Size of homestead land (x10) is medium. It has been found that for the independent variable, Size of cultivable land (x11), the maximum size is 29.50 bigha and the minimum size is 0.75 bigha. The mean of size of cultivable land was found to be 4.57 bigha, with the Standard Deviation 3.45 for the total distribution taken for the study. Coefficient of Variation for this variable is 75.49 per cent, which shows that the level of consistency in the distribution of Size of cultivable land (x11) is medium. It has been found that for the independent variable, Size of land under irrigation (x12), the maximum size of land is 29.50 bigha and the minimum size of land is 0.75 bigha. The mean of size of land under irrigation was found to be 4.52 bigha, with the Standard Deviation 3.47 for the total distribution taken for the study. Coefficient of Variation for this variable is 76.76 per cent, which shows that the level of consistency in the distribution of Size of land under irrigation (x12) is medium. It has been found that for the independent variable, No. of fragments (x13), the maximum number of fragments is 15 and the minimum number of fragments is 2. The mean of number of fragments was found to be 7.39, with the Standard Deviation 3.16 for the total distribution taken for the study. Coefficient of Variation for this variable is 42.76 per cent, which shows that the level of consistency in the distribution of No. of fragments (x13) is high. It has been found that for the independent variable, Crop yield (x14), the maximum value of yield is Rs 78,666 per year (Rs 6,555.5 per month) and the minimum value of yield is Rs 1,708 per year (Rs 142.33 per month). The mean value of crop yield was found to be Rs 11,992 per year (Rs 999.33 per month), with the Standard Deviation 11821.34 for the total distribution taken for the study. Coefficient of Variation for this variable is 98.57 per cent, which shows that the level of consistency in the distribution of Crop yield (x14) is medium. It has been found that for the independent variable, Livestock yield (x15), the maximum value of yield is Rs 32,397 per year (Rs 2,699.75 per month) and the minimum value of yield is Rs 9,240 per year (Rs 770 per month). The mean of livestock yield was found to be Rs 6,310.89 per year (Rs 525.83 per month), with the Standard Deviation 5218.71 for the total distribution taken for the study. Coefficient of Variation for this variable is 82.69 per cent, which shows that the level of consistency in the distribution of Livestock yield (x15) is medium. It has been found that for the independent variable, Cropping intensity (x16), the maximum value of intensity is 233 per cent and the minimum value of intensity is 102 per cent. The mean value of cropping intensity was found to be 126.13 per cent, with the Standard Deviation 23.02 for the total distribution taken for the study. Coefficient of Variation for this variable is 18.25 per cent, which shows that the level of consistency in the distribution of Cropping intensity (x16) is high. It has been found that for the independent variable, Income (on farm & off farm) (x17), the maximum amount of income is Rs 1,76,399 per year (Rs 14,700 per month) and the minimum amount of income is Rs 16,072 per year (Rs 1,339.33 per

86

Entrepreneurial Communication in Agriculture

month). The mean amount of income was found to be Rs 60183.82 per year (Rs 5,015.31 per month), with the Standard Deviation 27524.57 for the total distribution taken for the study. Coefficient of Variation for this variable is 45.73 per cent, which shows that the level of consistency in the distribution of Income (on farm & off farm) (x17) is high. It has been found that for the independent variable, Family expenditure (x18), the maximum amount of expenditure is Rs 88,278 per year (Rs 7,356.5 per month) and the minimum amount of expenditure is Rs 12,181 per year (Rs I,015.98 per month). The mean amount of expenditure was found to be Rs 30,318.25 per year (Rs 2,526.52 per month), with the Standard Deviation 13982.64 for the total distribution taken for the study. Coefficient of Variation for this variable is 46.11 per cent, which shows that the level of consistency in the distribution of Family expenditure (x18) is high. It has been found that for the independent variable, Marketable surplus (x19), the maximum value of marketable surplus is Rs 88,121 per year (Rs 7,343.41 per month) and the minimum value of marketable surplus is Rs 11,322 per year (Rs 943.5 per month). The mean value of marketable surplus was found to be Rs 29,371.95 per year (Rs 2,447.66 per month), with the Standard Deviation 13104.36 for the total distribution taken for the study. Coefficient of Variation for this variable is 44.61 per cent, which shows that the level of consistency in the distribution of Marketable surplus (x19) is high. It has been found that for the independent variable, Marketed surplus (x20), the maximum value of marketed surplus is Rs 86,121 per year (Rs 7,176.75 per month) and the minimum value of marketed surplus is Rs 11,068 per year (Rs 922.33 per month). The mean value of marketed surplus was found to be Rs 28496.42 per year (Rs 2,374.70 per month), with the Standard Deviation 12986.82 for the total distribution taken for the study. Coefficient of Variation for this variable is 45.57 per cent, which shows that the level of consistency in the distribution of Marketed surplus (x20) is high. It has been found that for the independent variable, Family labour (x21) the maximum number of family labour is 3 and the minimum number of family labour is 1. The mean of number of family labour was found to be 1, with the Standard Deviation 0.52 for the total distribution taken for the study. Coefficient of Variation for this variable is 37.14 per cent, which shows that the level of consistency in the distribution of Family labour (x21) is high. It has been found that for the independent variable, No. of male workers (x22), the maximum number of male workers required is 120 per year (approximately 10 workers per month) and the minimum number of male workers required is 60 per year (5 workers per month). The mean of male worker required was found to be 86 per year (approximately 8 workers per month), with the Standard Deviation 10.63 for the total distribution taken for the study. Coefficient of Variation for this variable is 12.26 per cent, which shows that the level of consistency in the distribution of No. of male workers (x22) is high. It has been found that for the independent variable, No. of female workers (x23), the maximum number of female workers required is 102 per year (approximately 9

Results and Discussion

87

workers per month) and the minimum number of female workers required is 20 per year (approximately 2 workers per month). The mean of female workers required was found to be 50 per year (approximately 5 workers per month), with the Standard Deviation 14.17 for the total distribution taken for the study. Coefficient of Variation for this variable is 28.12 per cent, which shows that the level of consistency in the distribution of No. of female workers (x23) is high. It has been found that for the dependent variable, Farm enterprise information from cosmopolite sources (y1), the maximum frequency of information is 8 and the minimum frequency of information is 2. The mean frequency of information was found to be 5.32 year, with the Standard Deviation 1.36 for the total distribution taken for the study. Coefficient of Variation for this variable is 25.56 per cent, which shows that the level of consistency in the distribution of Farm enterprise information from cosmopolite sources (y1) is high. It has been found that for the dependent variable, Farm enterprise information from localite sources (y2), the maximum frequency of information is 9.60 and the minimum frequency of information is 2. The mean frequency of information was found to be 5.79, with the Standard Deviation 1.94 for the total distribution taken for the study. Coefficient of Variation for this variable is 33.50 per cent, which shows that the level of consistency in the distribution of Farm enterprise information from localite sources (y2) is high. It has been found that for the dependent variable, Information seeking and responding behavior (y3), the maximum frequency of information seeking is 3 and the minimum frequency of information seeking is 1. The mean frequency of information seeking was found to be 2.46, with the Standard Deviation 0.56 for the total distribution taken for the study. Coefficient of Variation for this variable is 22.76 per cent, which shows that the level of consistency in the distribution of Information seeking and responding behavior (y3) is high. It has been found that for the dependent, variable Entrepreneurial communication behavior (y4), the maximum frequency of communication behavior is 48 and the minimum frequency of communication behavior is of 10. The mean frequency of communication behavior was found to be 25.56, with the Standard Deviation 10.29 for the total distribution taken for the study. Coefficient of Variation for this variable is 40.25 per cent, which shows that the level of consistency in the distribution of Entrepreneurial communication behavior (y4) is high. It has been found that for the dependent variable, Value addition (y5), the maximum amount of value addition is Rs 9,000 per year (Rs 750 per month) and the minimum amount of value addition is Rs 1,200 per year (Rs 100 per month). The mean amount of value addition was found to be Rs 4,744.85 per year (Rs 395.40 per month), with the Standard Deviation 1873.72 for the total distribution taken for the study. Coefficient of Variation for this variable is 39.48 per cent, which shows that the level of consistency in the distribution of Value addition (y5), is high. It has been found that for the dependent variable, Economical communication (y6), the maximum frequency is 56 and the minimum frequency is of 24. The mean of frequency was found to be 54.73, with the Standard Deviation 25.27 for the total

Entrepreneurial Communication in Agriculture

88

distribution taken for the study. Coefficient of Variation for this variable is 46.17 per cent, which shows that the level of consistency in the distribution of Economical communication (y6) is high. It has been found that for the dependent variable, Transportation cost (y7), the maximum value of transportation cost is Rs 9,850 per year (Rs 820.83 per month) and the minimum value of transportation cost is Rs 4,500 per year (Rs 375 per month). The mean value of transportation cost was found to be Rs 7,016.71 per year (Rs 584.72 per month), with the Standard Deviation 1759.31 for the total distribution taken for the study. Coefficient of Variation for this variable is 25.07 per cent, which shows that the level of consistency in the distribution of Transportation cost (y7) is high. Table 6.3: Distribution of variables in terms of Range, Mean, Median, Mode, standard Deviation and Coefficient of variation of pooled villages of two states (Tripura and West Bengal) [N=152] Sl. No.

Variables

Range Min

Range

Mean

Median

Mode

S.D.

Max

C.V. (%)

1.

Age (x1)

27

75

48

49.55

50

44

10.59 21.37

2.

Education (x2)

4

15

11

8.01

8

8

2.55 31.83

3.

No. of enterprise (x3)

1

8

7

5.30

5

5

1.29 24.33

4.

Year of enterprise (x4)

9

62

53

31.99

30

26

11.50 35.94

5.

Training exposure (x5)

2

200

198

20

18.50

15

18.07 86.79

6.

Family size (x6)

2

8

6

4

5

5

7.

Farm education (x7)

13

80

67

40.72

37.50

44

17.51

8.

Material possessed (x8)

23

74

51

39.03

35.50

34

10.89 27.90

9.

Size of holding (x9)

1.25

30

28.75

4.93

4.10

4

2.84 57.60

10.

Size of homestead land (x10)

0.10

2.50

2.40

0.65

0.50

0.50

0.46 70.76

11.

Size of cultivable land (x11)

0.75

29.50

28.75

4.30

3.82

5.50

2.67 62.09

12.

Size of land under irrigation (x12)

0.75

29.50

28.75

4.28

3.82

4.50

2.69 62.85

13.

No. of fragments (x13)

2

15

13

7.71

8

4

3.15 40.85

1.47 31.61 43

14

Crop yield (x14)

1708

78666

76958

9637.36 7267.50

2333

9347.09 96.98

15

Livestock yield (x15)

9240 37426.25

28186

7533.26

6462

3333

5426.66 72.03

16

Cropping intensity (x16)

132

128.54

118

116

25.33 19.70

101

233

Results and Discussion

89

17

Income (on 16072 farm & off farm) (x17)

176399

18

Family expenditure (x18)

50000

101000

19

Marketable surplus (x19)

10000

20

Marketed surplus (x20)

21

160327 58583.05

51000

53434 16072 25882.08 44.18

75500

25192 14093 14682.22 47.93

88121

78121 28153.51

25000 30000 12777.95 45.38

9500

86121

76621 27184.50

24055 22000 12726.98 46.81

Family labour (x21)

1

3

2

1

1

1

0.50 35.21

22

No. of male workers (x22)

50

120

70

83

85

85

12.86 15.35

23

No. of female workers (x23)

20

104

84

49

50

50

16.44 33.51

24

Farm enterprise information from cosmopolite sources (y1)

1

8

7

5.02

5

5

1.47 29.28

25

Farm enterprise information from localite sources (y2)

2

9.60

7.60

5.90

5.55

5

1.82 30.84

26

Information seeking and responding behavior (y3)

1

3

2

2.43

2.42

3

0.53 21.81

27

Entrepreneurial communication behavior (y4)

10

48

38

24.34

22.50

20

9.69 39.81

28

Value addition (y5)

1200

9000

7800

3990.24 4122.50

4500

1925 48.24

29

Economical communication (y6)

20

36

16

72.63

44

36

30

Transportation cost (y7)

4320

9860

5530

6857.53

6525

4500

29.12

44

1686.56 24.59

Table 6.3 presents the distribution of variables in terms of Range, Mean, Median, Mode, Standard Deviation and Coefficient of Variation of pooled states, that is, Tripura and West Bengal. It has been found that for the independent variable, Age (x1), the maximum value of age is 75 years and the minimum value of age is 27 years. The mean value of age group was found to be 49.5 years with the Standard Deviation 10.59 for the total distribution taken for the study. Coefficient of Variation for this variable is 21.37 per cent, which shows that the level of consistency in the distribution of Age (x1) is high.

90

Entrepreneurial Communication in Agriculture

It has been found that for the independent variable, Education (x2), the maximum number of years of education is 15 years and the minimum number of years of education is 4 years. The mean number of years of education was found to 8.01 years, with the Standard Deviation 2.55 for the total distribution taken for the study. Coefficient of Variation for this variable is 31.83 per cent, which shows that the level of consistency in the distribution of Education (x2) is high. It has been found that for the independent variable, No. of enterprise (x3), the maximum number of enterprise is 8 numbers and the minimum number of enterprise is 1 number. The mean number of enterprise was found to be 5.30, with the Standard Deviation 1.29 for the total distribution taken for the study. Coefficient of Variation for this variable is 24.33 per cent, which shows that the level of consistency in the distribution of No. of enterprise (x3) is high. It has been found that for the independent variable, Year of enterprise (x4), the maximum number of year of enterprise is 62 years and the minimum number of year of enterprise is 9 years. The mean number of year of enterprise was found to be 31.99 years, with the Standard Deviation 11.50 for the total distribution taken for the study. Coefficient of Variation for this variable is 35.94 per cent, which shows that the level of consistency in the distribution of Year of enterprise (x4) is high. It has been found that for the independent variable, Training exposure (x5), the maximum number of trainings attended is 200 and the minimum number of trainings attended is 2. The mean of number of trainings attended was found to be 20.82, with the Standard Deviation 18.07 for the total distribution taken for the study. Coefficient of Variation for this variable is 86.79 per cent, which shows that the level of consistency in the distribution of Training exposure (x5) is medium. It has been found that for the independent variable, Family size (x6), the maximum number of family members is 8 and the minimum number of family members is 2. The mean of number of family members was found to be 4.65, with the Standard Deviation 1.47 for the total distribution taken for the study. Coefficient of Variation for this variable is 31.61 per cent, which shows that the level of consistency in the distribution of Family size (x6) is high. It has been found that for the independent variable, Family education (x7), the maximum value is 80 after adding the educational years of all the family members and the minimum value is 13 after adding the educational years of all the family members. The mean value was found to be 40.72, with the Standard Deviation 17.51 for the total distribution taken for the study. Coefficient of Variation for this variable is 43 per cent, which shows that the level of consistency in the distribution of Family education (x7) is high. It has been found that for the independent variable, Material possessed (x8), the maximum scoring of material possessed is 74 and the minimum scoring of material possessed is 23. The mean scoring of material possessed was found to be 39.03, with the Standard Deviation 10.89 for the total distribution taken for the study. Coefficient of Variation for this variable is 27.90 per cent, which shows that the level of consistency in the distribution of Material possessed (x8) is high.

Results and Discussion

91

It has been found that for the independent variable, Size of holding (x9), the maximum size of holding is 30 bigha and the minimum size of holding is 1.25 bigha. The mean of size of holding was found to be 4.93 bigha, with the Standard Deviation 2.84 for the total distribution taken for the study. Coefficient of Variation for this variable is 57.60 per cent, which shows that the level of consistency in the distribution of Size of holding (x9) is medium. It has been found that for the independent variable, Size of homestead land (x10), the maximum size of homestead land is 2.50 bigha and the minimum size of homestead land is 0.10 bigha. The mean of size of homestead land was found to be 0.65 bigha, with the Standard Deviation 0.46 for the total distribution taken for the study. Coefficient of Variation for this variable is 70.76 per cent, which shows that the level of consistency in the distribution of Size of homestead land (x10) is medium. It has been found that for the independent variable, Size of cultivable land (x11), the maximum size is 29.50 bigha and the minimum size is 0.75 bigha. The mean of size of cultivable land was found to be 4.30 bigha, with the Standard Deviation 2.67 for the total distribution taken for the study. Coefficient of Variation for this variable is 62.09 per cent, which shows that the level of consistency in the distribution of Size of cultivable land (x11) is medium. It has been found that for the independent variable, Size of land under irrigation (x12), the maximum size of land under irrigation is 29.50 bigha and the minimum size of land under irrigation is 0.75bigha. The mean of size of land under irrigation was found to be 4.28 bigha, with the Standard Deviation 2.69 for the total distribution taken for the study. Coefficient of Variation for this variable is 62.85 per cent, which shows that the level of consistency in the distribution of Size of land under irrigation (x12) is medium. It has been found that for the independent variable, No. of fragments (x13), the maximum number of fragments is 15 and the minimum number of fragments is 2. The mean of number of fragments was found to be 7.71, with the Standard Deviation 3.15 for the total distribution taken for the study. Coefficient of Variation for this variable is 40.85 per cent, which shows that the level of consistency in the distribution of No. of fragments (x13) is high. It has been found that for the independent variable, Crop yield (x14), the maximum value of yield is Rs 78,666 per year (Rs 6,555.5 per month) and the minimum value of yield is Rs 1,708 per year (Rs 142.33 per month). The mean value of crop yield was found to be Rs 9,637.36 per year (Rs 803.11 per month), with the Standard Deviation 9347.09 for the total distribution taken for the study. Coefficient of Variation for this variable is 96.98 per cent, which shows that the level of consistency in the distribution of Crop yield (x14) is medium. It has been found that for the independent variable, Livestock yield (x15), the maximum value of yield is Rs 37,426 per year (Rs 3118.83 per month) and the minimum value of yield is Rs 9,240 per year (Rs 770 per month). The mean value of livestock yield was found to be Rs 7,533.26 per year (Rs 627.77 per month), with the Standard Deviation 5426.66 for the total distribution taken for the study. Coefficient of Variation for this variable is 72.03 per cent, which shows that the level of consistency in the distribution of Livestock yield (x15) is medium.

92

Entrepreneurial Communication in Agriculture

It has been found that for the independent variable, Cropping intensity (x16), the maximum value of intensity is 233 per cent and the minimum value of intensity is 101 per cent. The mean value of cropping intensity was found to be 128.54 per cent, with the Standard Deviation 25.33 for the total distribution taken for the study. Coefficient of Variation for this variable is 19.70 per cent, which shows that the level of consistency in the distribution of Cropping intensity (x16) is high. It has been found that for the independent variable, Income (on farm & off farm) (x17), the maximum amount of income is Rs 1,76,399 per year (Rs 14,700 per month) and the minimum amount of income is Rs 16,072 per year (Rs 1,339.33 per month). The mean amount of income was found to be Rs 58,583.05 per year (Rs 4,881.91 per month), with the Standard Deviation 25882.08 for the total distribution taken for the study. Coefficient of Variation for this variable is 44.18 per cent, which shows that the level of consistency in the distribution of Income (on farm & off farm) (x17) is high. It has been found that for the independent variable, Family expenditure (x18), the maximum amount of expenditure is Rs 1,01000 per year (Rs 8,416.66 per month) and the minimum amount of expenditure is Rs 50,000 per year (Rs 4,166.66 per month). The mean of amount of expenditure was found to be Rs 75,500 per year (Rs 6,291.66 per month), with the Standard Deviation 14682.22 for the total distribution taken for the study. Coefficient of Variation for this variable is 47.93 per cent, which shows that the level of consistency in the distribution of Family expenditure (x18) is high. It has been found that for the independent variable, Marketable surplus (x19), the maximum value of marketable surplus is Rs 88,121 per year (Rs 7,343.41 per month) and the minimum value of marketable surplus is Rs 10,000 per year (Rs 833.33 per month). The mean value of marketable surplus was found to be Rs 28,153.51 per year (Rs 2,346.12 per month), with the Standard Deviation 12777.95 for the total distribution taken for the study. Coefficient of Variation for this variable is 45.38 per cent, which shows that the level of consistency in the distribution of Marketable surplus (x19) is high. It has been found that for the independent variable, Marketed surplus (x20), the maximum value of marketed surplus is Rs 86,121 per year (Rs 7,176.75 per month) and the minimum value of marketed surplus is Rs 9,500 per year (Rs 791.66 per month). The mean value of marketed surplus was found to be Rs 27,184.50 per year (Rs 2265.37 per month), with the Standard Deviation 12726.98 for the total distribution taken for the study. Coefficient of Variation for this variable is 46.81 per cent, which shows that the level of consistency in the distribution of Marketed surplus (x20) is high. It has been found that for the independent variable, Family labour (x21), the maximum number of family labour is 3 and the minimum number of family labour is 1. The mean of number of family labour was found to be 1, with the Standard Deviation 0.50 for the total distribution taken for the study. Coefficient of Variation for this variable is 35.21 per cent, which shows that the level of consistency in the distribution of Family labour (x21) is high.

Results and Discussion

93

It has been found that for the independent variable, No. of male workers (x22), the maximum number of male workers required is 120 per year (10 workers per month) and the minimum number of male workers required is 50 per year (approximately 5 workers per month). The mean of male worker required was found to be 83 per year (approximately 7 workers per month), with the Standard Deviation 12.86 for the total distribution taken for the study. Coefficient of Variation for this variable is 15.35 per cent, which shows that the level of consistency in the distribution of No. of male workers (x22) is high. It has been found that for the independent variable, No. of female workers (x23), the maximum number of female workers required is 104 per year (approximately 7 workers per month) and the minimum number of female workers required is 20 per year (approximately 2 workers per month). The mean of female workers required was found to be 49 per year (approximately 4 workers per month), with the Standard Deviation 16.44 for the total distribution taken for the study. Coefficient of Variation for this variable is 33.51 per cent, which shows that the level of consistency in the distribution of No. of female workers (x23) is high. It has been found that for the dependent variable, Farm enterprise information from cosmopolite sources (y1), the maximum frequency of information is 8 and the minimum frequency of information is 1. The mean frequency of information was found to be 5.02 year, with the Standard Deviation 1.47 for the total distribution taken for the study. Coefficient of Variation for this variable is 29.28 per cent, which shows that the level of consistency in the distribution of Farm enterprise information from cosmopolite sources (y1) is high. It has been found that for the dependent variable, Farm enterprise information from localite sources (y2), the maximum frequency of information is 9.60 and the minimum frequency of information is 2. The mean frequency of information was found to be 5.90, with the Standard Deviation 1.82 for the total distribution taken for the study. Coefficient of Variation for this variable is 30.84 per cent, which shows that the level of consistency in the distribution of Farm enterprise information from localite sources (y2) is high. It has been found that for the dependent variable, Information seeking and responding behavior (y3), the maximum frequency of information seeking is 3 and the minimum frequency of information seeking is 1. The mean frequency of information seeking was found to be 2.43, with the Standard Deviation 0.53 for the total distribution taken for the study. Coefficient of Variation for this variable is 21.81 per cent, which shows that the level of consistency in the distribution of Information seeking and responding behavior (y3) is high. It has been found that for the dependent variable, Entrepreneurial communication behavior (y4), the maximum frequency of communication behavior is 48 and the minimum frequency of communication behavior is of 10. The mean frequency of communication behavior was found to be 24.34, with the Standard Deviation 9.69 for the total distribution taken for the study. Coefficient of Variation for this variable is 39.81 per cent, which shows that the level of consistency in the distribution of Entrepreneurial communication behavior (y4) is high.

94

Entrepreneurial Communication in Agriculture

It has been found that for the dependent variable, Value addition (y5), the maximum amount of value addition is Rs 9,000 per year (Rs 750 per month) and the minimum amount of value addition is Rs 1,200 per year (Rs 100 per month). The mean amount of value addition was found to be Rs 3,990.24 per year (Rs 332.52 per month), with the Standard Deviation 1925 for the total distribution taken for the study. Coefficient of Variation for this variable is 48.24 per cent, which shows that the level of consistency in the distribution of Value addition (y5) is high. It has been found that for the dependent, variable Economical communication (y6), the maximum frequency is 36 and the minimum frequency is of 20. The mean of frequency was found to be 72.63, with the Standard Deviation 291.27 for the total distribution taken for the study. Coefficient of Variation for this variable is 44 per cent, which shows that the level of consistency in the distribution of Economical communication (y6) is high. It has been found that for the dependent variable, Transportation cost (y7), the maximum value of transportation cost is Rs 9,860 per year (Rs 821.66 per month) and the minimum value of transportation cost is Rs 4,320 per year (Rs 360 per month). The mean value of transportation cost was found to be Rs 6,857.53 per year (Rs 571.46 per month), with the Standard Deviation 1686.56 for the total distribution taken for the study. Coefficient of Variation for this variable is 24.59 per cent, which shows that the level of consistency in the distribution of Transportation cost (y7) is high. Model 6.1: Coefficient of Correlation between Farm enterprise information from cosmopolite sources (y1) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Results and Discussion

95

Model 6.1 presents the Coefficient of correlation between Farm enterprise information from cosmopolite sources (y1) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., age (x1), education (x2), year of enterprise (x4), material possessed (x8), size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23), have recorded positive and significant correlation with the consequent variable, Farm enterprise information from cosmopolite sources (y1).

Important Revelation When one person is cosmopolite in his outlook, he will come to know the value of education and other virtues. In other words, when one person’s income, land holding, surplus, education go up, he will understand the value of outer world and will be more cosmopolite in nature to seek more diverse informations sources to increase one’s cognitive and functional skills. So, when the above stated exogenous variables goes on increasing, one’s information gathering from cosmopolite sources will also increase. Model 6.2: Coefficient of Correlation between Farm enterprise information from cosmopolite sources (y1) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

96

Entrepreneurial Communication in Agriculture

Model 6.2 presents the Coefficient of correlation between Farm enterprise information from cosmopolite sources (y1) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., cropping intensity (x 16), family labour (x21) and no. of female workers (x23), have recorded negative and significant correlation with the consequent variable, Farm enterprise information from cosmopolite sources (y1).

Important Revelation Here we can see that the variables, cropping intensity and man power are negatively correlated with the dependent variable, Farm enterprise information from cosmopolite sources (y1). This is because the female workers or the female counterparts have less mobility to the outer world and so their interaction remains localite and within themselves only. Females have less interaction with cosmopolite sources and they tend to communicate among themselves only. For farms having lesser cropping intensity, they tend to show higher propensity to collect information for further intensification of crop enterprises. Model 6.3: Coefficient of Correlation between Farm enterprise information from cosmopolite sources (y1) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Results and Discussion

97

Model 6.3 presents the Coefficient of correlation between Farm enterprise information from cosmopolite sources (y1) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., training exposure (x5), material possessed (x8), crop yield (x14) and marketed surplus (x20) have recorded positive and significant correlation with the consequent variable Farm enterprise information from cosmopolite sources (y1).

Important Revelation Exposure to training has helped the respondents enrich their domain of cognitive learning and improving their scales. This also involves a mobility of the entrepreneurs across the geo-spatial expanse. So, both innovations and intuitions have earned through training exposure (x5) a higher level of farm enterprise innovation. Material possessed (x8) has also been correlated to suggest that those who are having higher level of farm innovations, are also having better material possessions as well. Both the variables, crop yield (x14) and marketed surplus (x20) have gone correlated with higher level of enterprise information through inventory generated or incubated by the farm entrepreneurs. So, the entrepreneurial behavior of the respondents could well be predicted through marketed surplus (x20) and money value generated of crop entrepreneurs. Model 6.4: Coefficient of Correlation (r): Farm enterprise informa-tion from cosmopolite sources (y1) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

98

Entrepreneurial Communication in Agriculture

Model 6.4 presents the comparative study of Tripura and West Bengal for Farm enterprise information from cosmopolite sources (y1).

Results The joint delineation of ‘r’ value implies that for Tripura, there are 17 positively significant variables and these are, age (x1), education (x2), year of enterprise (x4), material possessed (x8), size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23) but there is no negatively significant variable. For West Bengal, there is no positively significant variable but there are 3 negatively significant variables and these are, cropping intensity (x16), family labour (x21) and no. of female workers (x23). The common variables between these two states are, family labour (x21) and no. of female workers (x23), when correlated with the dependent variable, Farm enterprise information from cosmopolite sources (y1).

Important Revelation This shows that Tripura has got a lot of scope to improve their entrepreneurial competencies, wherein for West Bengal, it has reached a level of maturity and saturation in farm entrepreneurship. There are 17 positively significant variables incase of Tripura, which means that by increasing or improving the efficacy of these variables, the information sources can be improved. Again, there are no positively significant variables incase of West Bengal, which means that a saturation level has reached and it requires very less improvement. Also, the common variables between the two states are manpower. Which implies, whatever place or situation may be concerned, manpower is of great importance. The upward movement of agriculture in West Bengal has now landed on a valley of stagnation and is now experiencing a plateauing effect. That is how, cropping intensity (x16), as against Tripura instance has recorded a negative bearing on the dependent variable, Farm enterprise information from cosmopolite sources (y1). Model 6.5: Coefficient of Correlation between Farm enterprise information from localite sources (y2) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Results and Discussion

99

Model 6.5 presents the Coefficient of correlation between Farm enterprise information from localite sources (y2) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., education (x2), no. of enterprise (x3), family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), crop yield (x14), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21) have recorded positive and significant correlation with the consequent variable, Farm enterprise information from localite sources (y2).

Important Revelation The ambience of localite sources of anyone increases mainly when family members are involved. As family education(x7), family size (x6), increases, information sources and interactions operate within the family members keep scaling up. As the members of the family are well educated, they each other tend to behave like the information source and there is little need of outside interference. The results also indicated that, families in Tripura are coming up more of entrepreneurial characters and dents to form a family basket of localite information and gone intrigued with entrepreneurial behavior.

100

Entrepreneurial Communication in Agriculture

Model 6.6: Coefficient of Correlation between Farm enterprise information from localite sources (y2) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Model 6.6 presents the Coefficient of correlation between Farm enterprise information from localite sources (y2) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., size of homestead land (x10) has recorded positive and significant correlation with the consequent variable, Farm enterprise information from localite sources (y2) and the variables like livestock yield (x15), family expenditure (x18), no. of male workers (x22) and no. of female workers (x23) have recorded negative and significant correlation with the consequent variable, Farm enterprise information from localite sources (y2).

Important Revelation Agriculture in West Bengal has advanced in modernization process now, focusing more on non-descript lands like homestead and off type farm lands. The variable, size of the homestead land (x10) increases along with the increase in Farm enterprise information from localite sources (y2) and this is because local peoples tend to

Results and Discussion

101

understand the pattern of soil, locally available farming products and the need of the local people very clearly. Localite sources of information will help the people to understand how much land should be devoted for the cultivation and how much land should be used for their dwelling and living purposes. So, when localite sources of information increases, the size of homestead land (x10) also shows a higher up scaling propensity. Model 6.7: Coefficient of Correlation between Farm enterprise information from localite sources (y2) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Model 6.7 presents the Coefficient of correlation between Farm enterprise information from localite sources (y2) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., no. of fragments (x13) and livestock yield (x15) have recorded positive and significant correlation with the consequent variable, Farm enterprise information from localite sources (y2) and the variable, no. of female workers (x23) has recorded negative and significant correlation with the consequent variable, Farm enterprise information from localite sources (y2).

102

Entrepreneurial Communication in Agriculture

Important Revelation The need for collecting Farm enterprise information from localite sources (y2) increases with the increase of number of fragments and yield, mainly of livestock, because increasing number of fragments will give rise to more amount of information from local sources. Local people understand better the pattern of cultivation and fragments. Information seeking behavior has also got some gender dimension, and when the number of female workers (x23) decrease, more information is needed from local sources, in order to improve the information and technology gap generated for the female farmers. Model 6.8: Coefficient of Correlation (r): Farm enterprise informa-tion from localite sources (y2) versus 23 Independent Variables (x1to x23): A comparative delineation: Tripura versus West Bengal

Model 6.8 presents the comparative study of Tripura and West Bengal for Farm enterprise information from localite sources (y2).

Results The joint delineation of ‘r’ value implies that for Tripura, there are 14 positively significant variables and these are, education (x2), no. of enterprise (x3), family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), crop yield

Results and Discussion

103

(x14), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21) but there is no negatively significant variable. For West Bengal, there is only 1 positively significant variable and this is, size of homestead land (x10) but there are 4 negatively significant variables and these are, livestock yield (x15), family expenditure (x18), no. of male workers (x22) and no. of female workers (x23). The common variables between these two states are, livestock yield (x15) and family expenditure (x15) when correlated with the consequent variable, Farm enterprise information from localite sources (y2).

Important Revelation The study reveals that in case of Tripura, there are 14 positively significant variables and in case of West Bengal there is 1 positively significant variable and 4 negatively significant variables, bearing on the consequent variable, Farm enterprise information from localite sources (y2). In case of Tripura, variables, education, enterprise, family size, etc. increase with the increase of the dependent variable, Farm enterprise information from localite sources (y2), but incase of West Bengal, the positive variables are not the same. The common variables are livestock yield (x15) and family expenditure (x15). Livestock has come up as an important determinant for both the states in characterizing the behavior of entrepreneurial communication. Model 6.9: Coefficient of Correlation between Information seeking and responding behaviour (y3) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

104

Entrepreneurial Communication in Agriculture

Model 6.9 presents the Coefficient of correlation between Information seeking and responding behavior (y3) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23) have recorded positive and significant correlation with the consequent variable, Information seeking and responding behavior (y3).

Important Revelation One’s Information seeking and responding behavior (y3) goes on increasing when one’s education, enterprises, exposure, land holding, yield, income, surplus, manpower increase. When these variables are on higher side, a person will incubate a more heterophyle and cosmopolite information seeking behavior. Hence, with the increase of all the above stated independent variables, one’s need for information seeking and responding to it also increases. Model 6.10: Coefficient of Correlation between Information seeking and responding behavior (y3) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results and Discussion

105

Model 6.10 presents the Coefficient of correlation between Information seeking and responding behavior (y3) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., material possessed (x8), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20) have recorded positive and significant correlation with the consequent variable, Information seeking and responding behavior (y3) and the variable,family size (x6) has recorded negative and significant correlation with the consequent variable, Information seeking and responding behavior (y3).

Important Revelation One’s Information seeking and responding behavior (y3) changes along with the change in his materials owned, fragments, yield, income, expenditure and surplus. When one possesses more number of enterprises and materials, he needs correct information regarding the maintenance, availability of those enterprises and entrepreneurial inputs. When one’s farm is fragmented into many pieces, one needs information for the maintenance and integration of the farm properly. Proper information will help a person to diverse his products into various items and as a result, his income and surplus will increase. Model 6.11: Coefficient of Correlation between Information seeking and responding behaviour (y3) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

106

Entrepreneurial Communication in Agriculture

Model 6.11 presents the Coefficient of correlation between Information seeking and responding behaviour (y3) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., family education (x7), crop yield (x14), income (on farm & off farm) (x17) and no. of male workers (x22), have recorded positive and significant correlation with the dependent variable, Information seeking and responding behaviour (y3).

Important Revelation Information seeking and responding behaviour (y3) changes positively along with the change in one’s family status and education, yield, income and number of male workers. With the increase in education, one tends to collect more and relevant information to broaden his outlook regarding all types of interventions, including entrepreneurial ventures. Education helps to shape one’s outlook to think beyond his horizon. Also when yield and income increases, one tends to gather more information for the effective use of the yield and income and hence his Information seeking and responding behaviour (y3) increases. Male workers also tend to move more responsive to the information seeking and responding to them. Model 6.12: Coefficient of Correlation (r): Information seeking and responding behaviour (y3) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

Results and Discussion

107

Model 6.12 presents the comparative study of Tripura and West Bengal for Information seeking and responding behavior (y3).

Results The joint delineation of ‘r’ value implies that for Tripura, there are 20 positively significant variables and these are, age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23) but there is no negatively significant variable. For West Bengal, there are 8 positively significant variables and these are, material possessed (x8), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20), and there is only 1 negatively significant variable and this is, family size (x6). The common variables between these two states are material possessed (x8), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20), when correlated with the consequent variable, Information seeking and responding behavior (y3).

Important Revelation The study evinces that, 20 variables have been found to be positively significant in case of Tripura and only 8 variables are positively significant in case of West Bengal. This implies that West Bengal, as because a larger state than Tripura, has already attained almost saturation level of information seeking for entrepreneurial ventures. In Tripura, entrepreneurial ventures in agriculture has recently started and keeps evolving, so it needs to consider many factors to attain that saturation level. There are some common variables in operation between these two states, like, materials owned, fragments, yield, income, expenditure, surplus, etc. Therefore, the positive indicators need to be improved in case of both the states to attain a desired level of entrepreneurship. Model 6.13: Coefficient of Correlation between Entrepreneurial communication behavior (y4) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

108

Entrepreneurial Communication in Agriculture

Model 6.13 presents the Coefficient of correlation between Entrepreneurial communication behavior (y4) and 23 independent variables (x1 to x23).

Results It has been found that the variables, age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), family education (x7), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21), have recorded positive and significant correlation with the consequent variable, Entrepreneurial communication behavior (y4).

Important revelation Entrepreneurial communication behavior (y4) increases with the upward movement of age, education, training, education status of family members, land owned, yield, income, surplus, manpower, etc. When all these variables are in upward movement,

Results and Discussion

109

one needs to communicate more with the outside world as well inside echelon. He needs to communicate more about the entrepreneurial ventures, about peer how to maintain the high status of the above stated variables in order to maintain his entrepreneurial characteristics. Entrepreneurial behavior includes, information seeking, information processing and information disseminating. A person is in the high need for Entrepreneurial communication behavior (y4) to maintain his resources and entrepreneurship. Model 6.14: Coefficient of Correlation between Entrepreneurial communication behavior (y4) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

FigModel 6.14 presents the Coefficient of correlation between Entrepreneurial communication behavior (y4) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12) and income (on farm & off farm) (x17), have recorded negative and significant correlation with the consequent variable, Entrepreneurial communication behavior (y4).

110

Entrepreneurial Communication in Agriculture

Important Revelation Entrepreneurial communication behavior (y4) changes in negative direction along with the increase of one’s land holding, size of cultivable land and land under irrigation and income. We know that entrepreneurial behavior involves information seeking, processing and disseminating behavior and when these things goes up, sometimes one gets less time to devote towards his own personal interventions and vice versa. Like, when one’s size of holding, cultivable land, irrigation facility increase, one gets less time to devote towards his entrepreneurial ventures because most of his time and energy are consumed by his personal interventions.

Model 6.15: Coefficient of Correlation between Entrepreneurial communication behaviour (y4) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Model 6.15 presents the Coefficient of correlation between Entrepreneurial communication behaviour (y4) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., size of homestead land (x10), no. of fragments (x13) income (on farm & off farm) (x17), marketable surplus (x19) and marketed surplus (x20), have recorded positive and significant correlation with

Results and Discussion

111

the consequent variable, Entrepreneurial communication behaviour (y4) and the variables, family size (x6), family education (x7) and no. of female workers (x23), have recorded negative and significant correlation with the consequent variable, Entrepreneurial communication behaviour (y4).

Important Revelation With change of Entrepreneurial communication behaviour (y4), that is, information seeking, information processing and information responding behavior, the variables, homestead land, number of fragments, income and surplus also changes. When surplus, homestead land, and income increase, one’s entrepreneurial behavior will also change positively. Also, with increasing number of fragments, different types of crops can be grown, different types of animals can be reared, such as fishery, goatery, cattle rearing, sericulture, etc., which will also need increase of Entrepreneurial communication behaviour (y4). On the other hand, family size (x6), family education (x7) and number of female workers (x23) decrease with the increasing of Entrepreneurial communication behaviour (y4). When family size (x6) and family education (x7) increase, they gain the capacity to interact and communicate among themselves and the requirement of Entrepreneurial communication behaviour (y4) from outside interference will be less. Also, female workers tend to interact less with the outside world because they have low access to mobility.

Model 6.16: Coefficient of Correlation (r): Entrepreneurial communication behavior (y4) versus 23 Independent Variables (x1to x23): A comparative delineation: Tripura versus West Bengal

112

Entrepreneurial Communication in Agriculture

Model 6.16 presents the comparative study of Tripura and West Bengal for Entrepreneurial communication behavior (y4).

Results The joint delineation of ‘r’ value implies that for Tripura, there are 18 positively significant variables and these are, age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21) and there is only 1 negatively significant variable and this is, family education (x7). For West Bengal, there is no positively significant variable but there are 4 negatively significant variables and these are, size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12) and income (on farm & off farm) (x17). The common variables between these two states are, size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12) and income (on farm & off farm) (x17), when correlated with the consequent variable, Entrepreneurial communication behavior (y4).

Important Revelation The result evinces that 18 variables have been found positively significant in case of Tripura and only 1 variable is negatively significant. In case of West Bengal, 4 variables are negatively significant and none is positively significant.The common variables in operation between these two states are land owned and income. West Bengal is already quite developed incase of entrepreneurship as it is a larger state than Tripura, so there is less need to improve already established variables. While Tripura is running at an initial phase of entrepreneurial development in agriculture, the factors identified as critical, need to be considered with emphasis.

Model 6.17: Coefficient of Correlation between Value addition (y5) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Results and Discussion

113

Model 6.17 presents the Coefficient of correlation between Value addition (y5) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., age (x1), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23), have recorded positive and significant correlation with the consequent variable, Value addition (y5).

Important Revelation Value addition (y5) is the process of adding more attributes in addition to its initial production, so that the product can derive desired market responses. With the up scaling of the variables like age, enterprise, training, materials owned, land owned, income, surplus, manpower, the Value addition (y5) also keeps on increasing. When an individual is exposed to some kind of trainings regarding Value addition (y5), in return he will increase his Value addition (y5) functions like grading and sorting of farm products.The farmers want some of his items to be value added. With increasing

114

Entrepreneurial Communication in Agriculture

income, land holding capacity, yield and materials owned, the farmer will have the need, power and sufficient money to continue the value added production. So, Value addition (y5) is positively and significantly correlated with the above stated independent variables.

Model 6.18: Coefficient of Correlation between Value addition (y5) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Model 6.18 presents the Coefficient of correlation between Value addition (y5) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., age (x1), year of enterprise (x4), training exposure (x5), cropping intensity (x16), family labour (x21) and no. of female workers (x23), have recorded positive and significant correlation with the consequent variable, Value addition (y5) and the variable, no. of male workers (x22), has recorded negative and significant correlation with the consequent variable, Value addition (y5).

Results and Discussion

115

Important Revelation Value addition (y5) changes positively with the increase of a person’s age, enterprise, training, cropping intensity and man power. Through training one gets to know about the importance of Value addition (y5). Also, female workers are more efficient than male workers in value addition process. So, Value addition (y5) is positively and significantly related with the above stated independent variables. Again, number of male workers decreases with the increase in Value addition (y5) and this is because, males are not much efficient like females in this matter. Model 6.19: Coefficient of Correlation between Value addition (y5) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Model 6.19 presents the Coefficient of correlation between Value addition (y5) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., age (x1), marketable surplus (x19) and no. of male workers (x22), have recorded positive and significant correlation

116

Entrepreneurial Communication in Agriculture

with the consequent variable, Value addition (y5) and the variable, no. of enterprise (x3), has recorded negative and significant correlation with the consequent variable, Value addition (y5).

Important Revelation Value addition (y5) is the basic process in entrepreneurial communication, as well as behavior. So, marketable surplus and man power have come up as important determinants to the value addition process and products as well. Model 6.20: Coefficient of Correlation (r): Value addition (y5) versus 23 Independent Variables (x1-x23): A comparative delineation: Tripura versus West Bengal

Model 6.20 presents the comparative study of Tripura and West Bengal for Value addition (y5).

Results The joint delineation of ‘r’ value implies that for Tripura, there are 18 positively significant variables and these are, age (x1), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), livestock yield (x15), income (on farm & off farm) (x17), family

Results and Discussion

117

expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23) but there is no negatively significant variable. For West Bengal, there are 6 positively significant variables and these are, age (x1), year of enterprise (x4), training exposure (x5), cropping intensity (x16), family labour (x21) and no. of female workers (x23) but there is only 1 negatively significant variable and this is, no. of male workers (x22). The common variables between these two states are, age (x1), year of enterprise (x4), training exposure (x5), family labour (x21), no. of male workers (x22) and no. of female workers (x23), when correlated with the consequent variable, Value addition (y5).

Important Revelation The result reveals that 18 variables are positively significant incase of Tripura and only 6 variables are positively significant incase of West Bengal. So, there are many variables incase of Tripura which needs to be improved or increased to attain the saturation level. Also there are some common variables between both the states, like, age, enterprise, training and manpower. While agripreneurship in West Bengal is moving at a faster rate, it needs more market-led extension, rather than a production-led extension. Model 6.21: Coefficient of Correlation between Economical communication (y6) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

118

Entrepreneurial Communication in Agriculture

Model 6.21 presents the Coefficient of correlation between Economical communication (y6) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), family size (x6), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21), have recorded positive and significant correlation with the consequent variable, Economical communication (y6).

Important Revelation Economical communication (y6) means the communication over the transaction of financial business affairs. It has been estimated through the frequency at which the farmers visit the bank, post office, local money lenders, input dealers, etc. and transact on entrepreneurial matters. Here, the variables, age, qualification, enterprise, family, land owned, income, expenditure, surplus, etc. increase with the increase of loan borrowed. A farmer will perceive the value of bank and other institutions with the up scaling quality of his education. Model 6.22: Coefficient of Correlation between Economical communication (y6) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results and Discussion

119

Model 6.22 presents the Coefficient of correlation between Economical communication (y6) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., education (x2), no. of enterprise (x3), livestock yield (x15), income (on farm & off farm) (x17), marketable surplus (x19) and marketed surplus (x20), have recorded positive and significant correlation with the consequent variable, Economical communication (y6) and the variables, age (x1), year of enterprise (x4) and training exposure (x5), have recorded negative and significant correlation with the consequent variable, Economical communication (y6).

Important Revelation When one’s Economical communication (y6) increases, his surplus will also increase because he can use the extra income and products more economically, effectively and efficiently. Therefore, Economical communication (y6) is positively correlated with the above stated independent variables. On the other hand, variables, age, year of enterprise and exposure to training decrease with the increase of Economical communication (y6) and this is because, with the increase of a person’s age, or a traditional person mostly does not rely upon banks and other financial institutions for financial transactions. Model 6.23: Coefficient of Correlation between Economical communication (y6) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Table 6.26 and Model 6.23 present the Coefficient of correlation between Economical communication (y6) and 23 independent variables (x1 to x23).

120

Entrepreneurial Communication in Agriculture

Results It has been found that the exogenous variables, viz., education (x2), income (on farm & off farm) (x17) and family labour (x21), have recorded positive and significant correlation with the consequent variable, Economical communication (y6).

Important Revelation Economical communication (y6) deals with the financial matters, frequency of visiting banks, borrowing loans, business transaction, etc. When the variables, education, income and manpower increase, one’s Economical communication (y6) also increases and this is because, with increasing education, one will understand the importance of bank and other enterprise and financial institutions, and will get more economically attached to those. Model 6.24: Coefficient of Correlation (r): Economical communi-cation (y6) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

Model 6.24 presents the comparative study of Tripura and West Bengal for Economical communication (y6).

Results The joint delineation of ‘r’ value implies that for Tripura, there are 17 positively significant variables and these are, age (x1), education (x2), no. of enterprise (x3), year

Results and Discussion

121

of enterprise (x4), family size (x6), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21) but there is no negatively significant variable and for West Bengal, there are 6 positively significant variables and these are, education (x2), no. of enterprise (x3), livestock yield (x15), income (on farm & off farm) (x17), marketable surplus (x19) and marketed surplus (x20) and there are 3 negatively significant variables and these are, age (x1), year of enterprise (x4) and training exposure (x5). The common variables between these two states are, age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), livestock yield (x15), income (on farm & off farm) (x17), marketable surplus (x19) and marketed surplus (x20), when correlated with the consequent variable, Economical communication (y6).

Important Revelation The study reveals that 17 variables are positively significant in case of Tripura and 6 variables are positively significant in case of West Bengal. There is a lot of scope to increase the Economical communication (y6) of Tripura. This is because it’s a small state and economical activities are yet to usher properly. By improving the positively significant variables, the Economical communication (y6) of the farmers can be improved. On the other hand, only 6 variables need to be increased in case of West Bengal and this is because, Economical communication (y6) has already to some extent flourished there as it is a big state and also has metropolitan city. The common variables between these two states are age, education, enterprise, yield, income and surplus. In both the states, these variables need to be dealt with proper attention. Model 6.25: Coefficient of Correlation between Transportation cost (y7) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

122

Entrepreneurial Communication in Agriculture

Model 6.25 presents the Coefficient of correlation between Transportation cost (y7) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., age (x1), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), livestock yield (x15), cropping intensity (x16), family labour (x21), no. of male workers (x22) and no. of female workers (x23), have recorded positive and significant correlation with the consequent variable, Transportation cost (y7).

Important Revelation In all types of marketing and entrepreneurial ventures, some Transportation cost (y7) is involved. When the variables like age, enterprises, training, family size and education, material owned, yield, manpower changes, one needs to transport more items to the market and other places. In case the enterprises go up, income will be more and so one needs to transport more volume of farm products to the market to earn profit. The geo-spatial, especially, terrains of Tripura are undulating and uneven. It has got a coercive impact on the cost of transportation and cost of transportation in turn has got a negative impact on the expected return to be accrued to the expected return from the enterprise. Model 6.26: Coefficient of Correlation between Transportation cost (y7) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results and Discussion

123

Model 6.26 presents the Coefficient of correlation between Transportation cost (y7) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variables, viz., size of homestead land (x10), livestock yield (x15) and family labour (x21), have recorded positive and significant correlation with the consequent variable, Transportation cost (y7) and the variables, size of land under irrigation (x12), cropping intensity (x16) and income (on farm & off farm) (x17), have recorded negative and significant correlation with the consequent variable, Transportation cost (y7).

Important Revelation Transportation cost (y7) changes with the change of one’s size of land owned, yield and family labour because when the yield increases, one will have maximum surplus to send to the market and as a result, his Transportation cost (y7) will also increase. Also with large homestead land, one can cultivate kitchen garden, which will sometimes give extra production and that may be send to the market, as a result increasing the Transportation cost (y7). Model 6.27: Coefficient of Correlation between Transportation cost (y7) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Model 6.27 presents the Coefficient of correlation between Transportation cost (y7) and 23 independent variables (x1 to x23).

Results It has been found that the exogenous variable, viz., family education (x7), has recorded positive and significant correlation with the consequent variable, Transportation cost (y7).

124

Entrepreneurial Communication in Agriculture

Important Revelation Education improves upon knowledge, skill, attitude and mobility too. The mobility for entrepreneurial innovation, excellence, applicability, drives a farmer geo-spatially. This geo-spatial movement in turn involves higher cost of transportation, vis-à-vis, transactional services in the realm of business communication. Model 6.28: Coefficient of Correlation (r): Transportation cost (y7) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

Model 6.28 presents the comparative study of Tripura and West Bengal for the Transportation cost (y7).

Results The joint delineation of ‘r’ value implies that, for Tripura, there are 13 positively significant variables and these are, age (x1), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), family size (x6), family education (x7), material possessed

Results and Discussion

125

(x8), no. of fragments (x13), livestock yield (x15), cropping intensity (x16), family labour (x21), no. of male workers (x22) and no. of female workers (x23) but there is no negatively significant variable. For West Bengal, there are 3 positively significant variables and these are, size of homestead land (x10), livestock yield (x15) and family labour (x21) and 3 negatively significant variables and these are, size of land under irrigation (x12), cropping intensity (x16) and income (on farm & off farm) (x17). The common variables between these two states are, livestock yield (x15), cropping intensity (x16) and family labour (x21), when correlated with the consequent variable, Transportation cost (y7).

Important Revelation The study reveals that in Tripura, 13 variables are positively significant and in West Bengal, there is a mixture of positively and negatively significant variable, but the number is only 3. As Tripura is a small hilly state, transportation system is not that good. There are many rough and hilly terrains and so the transportation system is not well developed. So, there is a lot of scope to improve the transportation system by improving or increasing the positively significant variables. With increasing no. of enterprises, education, materials owned, yield, etc., the Transportation cost (y7) will also increase. When one’s yield increases, automatically surplus increases and need to transfer more products to the market, as a result the cost increases. Incase of West Bengal, when variables like land owned, yield and man power increase, Transportation cost (y7) also increases and the common variables between these states are yield, cropping intensity and manpower. Model 6.29: Stepwise Regression analysis: Farm enterprise information from cosmopolite sources (y1) versus 23 Causal variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

126

Entrepreneurial Communication in Agriculture

Results Model 6.29 presents the Stepwise regression analysis, wherein the variables, training exposure (x5), family size (x6), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), livestock yield (x15) and marketed surplus (x20), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Farm enterprise information from cosmopolite sources (y1). The causal variables have explained 45 per cent of variance embedded with the consequent variable.

Important Revelation The causal variables retained at the last step are, training exposure (x5), family size (x6), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), livestock yield (x15) and marketed surplus (x20). They have contributed 45 per cent of variance in the consequent variable, Farm enterprise information from cosmopolite sources (y1). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Farm enterprise information from cosmopolite sources (y1). Model 6.30: Stepwise Regression analysis: Farm enterprise information from cosmopolite sources (y1) versus 23 Causal variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

28%

Results Model 6.30 presents the Stepwise regression analysis, wherein the variables, no. of enterprise (x3) and material possessed (x8), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Farm enterprise information from cosmopolite sources (y1). The causal variables have explained 28 per cent of variance embedded with the consequent variable.

Results and Discussion

127

Important Revelation The causal variables retained at the last step are, no. of enterprise (x3) and material possessed (x8). They have contributed 28 per cent of variance in the consequent variable, Farm enterprise information from cosmopolite sources (y1). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Farm enterprise information from cosmopolite sources (y1). Model 6.31: Stepwise Regression analysis: Farm enterprise information from cosmopolite sources (y1) versus 23 Causal variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

5.6%

Results Model 6.31 presents the Stepwise regression analysis, wherein the variable no. of enterprise (x3), has been retained at the last step to elicit its determining and critical contribution to the dependent variable, Farm enterprise information from cosmopolite sources (y1). The variable, no. of enterprise (x3), has explained 5.6 per cent of variance embedded with the consequent variable.

Important Revelation The more the number of enterprises, the higher is the need for information seeking and generation. The intensity and count of enterprises here has been found to have substantive contribution to Farm enterprise information from cosmopolite sources (y1).

Strategic Importance So, the enterprises must be increased in number to generate information from the cosmopolite sources. When there will be more number of enterprises, there will be less cost generated in involving outside institutions for information generation.

128

Entrepreneurial Communication in Agriculture

Model 6.32: Stepwise Regression analysis: Farm enterprise information from cosmopolite sources (y1) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

Results Model 6.32 presents the differential variable performance and comparative delineation between Tripura and West Bengal in terms of Farm enterprise information from cosmopolite sources (y1), through Step wise regression analysis.

Important Revelation The comparative delineation and depiction between Tripura and West Bengal shows that, Farm enterprise information from cosmopolite sources (y1), has been uniquely contributed by 7 variables in Tripura and these are training exposure (x5), family size (x6), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), livestock yield (x15) and marketed surplus (x20). For the comparing state West Bengal, same dependent variable, Farm enterprise information from cosmopolite sources (y1) has been uniquely contributed by 2 variables and these are no. of enterprise (x3) and material possessed (x8) and it can be seen that none of the causal variables are

Results and Discussion

129

found to be common between these two states. So, in terms of strategic implication for both the states, respective functional variables as identified through Step wise regression analysis, should be focused and regressed adequately. Model 6.33: Stepwise Regression analysis: Farm enterprise information from localite sources (y2) versus 23 Causal variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

37%

Results Model 6.33 presents the Stepwise regression analysis, wherein the variables, age (x1), year of enterprise (x4), size of homestead land (x10), crop yield (x14) and no. of male workers (x22), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Farm enterprise information from localite sources (y2). The causal variables have explained 37 per cent of variance embedded with the consequent variable.

Important Revelation The causal variables retained at the last step are, age (x1), year of enterprise (x4), size of homestead land (x10), crop yield (x14) and no. of male workers (x22). They have contributed 37 per cent of variance in the consequent variable, Farm enterprise information from localite sources (y2). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Farm enterprise information from localite sources (y2). Model 6.34: Stepwise Regression analysis: Farm enterprise information from localite sources (y2) versus 23 Causal variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Entrepreneurial Communication in Agriculture

130

22%

Results Model 6.34 presents the Stepwise regression analysis, wherein the variable, no. of female workers (x23) has been retained at the last step to elicit its determining and critical contribution to the dependent variable, Farm enterprise information from localite sources (y2). The causal variable has explained 22 per cent of variance embedded with the consequent variable.

Important Revelation The causal variable retained at the last step is, no. of female workers (x23). It has contributed 22 per cent of variance in the consequent variable, Farm enterprise information from localite sources (y2). So, this variable must be considered emphatically while a strategic intervention will be delineated for improving access to farm enterprise information from localite sources (y2). Model 6.35: Stepwise Regression analysis: Farm enterprise infor-mation from localite sources (y2) versus 23 Causal variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

3%

Results and Discussion

131

Results Model 6.35 presents the Stepwise regression analysis, wherein the variable, no. of female workers (x23), has been retained at the last step to elicit its determining and critical contribution to the dependent variable, Farm enterprise information from localite sources (y2). The variable, no. of female workers (x23), has explained 3 per cent of variance embedded with the consequent variable.

Important Revelation More the number of female workers (x23), the higher has been the Farm enterprise information from localite sources (y2). Female workers have got some limitations to move around or go across at their liberty. They have to contend with their peers and the information sources are mainly localite.

Strategic Importance So, to improve the access and efficacy of entrepreneurial communication, it is better to go for capacity building within the peer groups, wherein women opinion leaders, cosmopolite by nature or a successful women entrepreneur can play the pivotal role for ushering insitu and cross cultural communication. Model 6.36: Stepwise Regression analysis: Farm enterprise infor-mation from localite sources (y2) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

Results Model 6.36 presents the differential variable performance and comparative delineation between Tripura and West Bengal in terms of Farm enterprise information from localite sources (y2), through Step wise regression analysis.

132

Entrepreneurial Communication in Agriculture

Important Revelation The comparative delineation between Tripura and West Bengal shows that, Farm enterprise information from localite sources (y2), has been uniquely contributed by 5 variables in Tripura and these are, age (x1), year of enterprise (x4), size of homestead land (x10), crop yield (x14) and no. of male workers (x22). For the comparing state West Bengal, same dependent variable, Farm enterprise information from localite sources (y2) has been uniquely contributed by 1 variable and this is, no. of female workers (x23) and it can be seen that none of the causal variable are found to be common between these two states. So, in terms of strategic implication for both the states, respective functional variables as identified through Step wise regression analysis, should be focused and regressed adequately. Model 6.37: Stepwise Regression analysis: Information seeking and responding behavior (y3) versus 23 Causal variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

43%

Results Model 6.37 presents the Stepwise regression analysis, wherein the variables, material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), cropping intensity (x16) and no. of male workers (x22), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Information seeking and responding behavior (y3). The causal variables have explained 43 per cent of variance embedded with the consequent variable.

Important Revelation The causal variables retained at the last step are, material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), cropping

Results and Discussion

133

intensity (x16) and no. of male workers (x22). They have contributed 43 per cent of variance in the consequent variable, Information seeking and responding behavior (y3). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Information seeking and responding behavior (y3). Model 6.38: Stepwise Regression analysis: Information seeking and responding behavior (y3) versus 23 Causal variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

33%

Results Model 6.38 presents the Stepwise regression analysis, wherein the variables, age (x1) and training exposure (x5), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Information seeking and responding behavior (y3). The causal variables have explained 33 per cent of variance embedded with the consequent variable.

Important Revelation The causal variables retained at the last step are, age (x1) and training exposure (x5). They have contributed 33 per cent of variance in the consequent variable, Information seeking and responding behavior (y3). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Information seeking and responding behavior (y3). Model 6.39: Stepwise Regression analysis: Information seeking and responding behavior (y3) versus 23 Causal variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

134

Entrepreneurial Communication in Agriculture

6.5%

Results Model 6.39 presents the Stepwise regression analysis, wherein the variables, family education (x7) and no. of female workers (x23), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Information seeking and responding behavior (y3). The variables, family education (x7) and no. of female workers (x23), have explained 6.5 per cent of variance embedded with the consequent variable.

Important Revelation The revelation implies that, more the family education status of entrepreneurs and female workers, the higher and diverse has been the Information seeking and responding behavior (y3).

Strategic Importance So, to increase the information seeking and responding behavior (y3), the education level of the women farmers and other entrepreneurs must be increased through proper formal, non formal and informal educational intervention, wherein progressive farmers and successful entrepreneurs must play a vital role in ushering the Information seeking and responding behavior (y3), as well as creating an entrepreneurial behavior. Model 6.40: Stepwise Regression analysis: Information seeking and responding behavior (y3) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

Results and Discussion

135

Results Model 6.40 presents the differential variable performance and comparative delineation between Tripura and West Bengal in terms of Information seeking and responding behavior (y3), through Step wise regression analysis.

Important Revelation The comparative delineation between Tripura and West Bengal shows that, Information seeking and responding behavior (y3) has been uniquely contributed by 6 variables in Tripura and these are, material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), cropping intensity (x16) and no. of male workers (x22). For the comparing state West Bengal, same dependent variable, Information seeking and responding behavior (y3), has been uniquely contributed by 2 variables and these are, age (x1) and training exposure (x5) and it can be seen that none of the causal variables are found to be common between these two states. So, in terms of strategic implication for both the states, respective functional variables as identified through Step wise regression analysis, should be focused and regressed adequately. Model 6.41: Stepwise Regression analysis: Entrepreneurial communication behavior (y4) versus 23 Causal variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

42%

136

Entrepreneurial Communication in Agriculture

Results Model 6.41 presents the Stepwise regression analysis, wherein the variables, family education (x7), no. of male workers (x22) and no. of female workers (x23), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Entrepreneurial communication behavior (y4). The causal variables have explained 42 per cent of variance embedded with the consequent variable.

Important revelation The causal variables retained at the last step are, family education (x7), no. of male workers (x22) and no. of female workers (x23). They have contributed 42 per cent of variance in the consequent variable, Entrepreneurial communication behavior (y4). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Entrepreneurial communication behavior (y4). Model 6.42: Stepwise Regression analysis: Entrepreneurial commu-nication behavior (y4) versus 23 Causal variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

35%

Results Model 6.42 presents the Stepwise regression analysis, wherein the variables, size of land under irrigation (x12), no. of fragments (x13) and income (on farm & off farm) (x17), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Entrepreneurial communication behavior (y4). The causal variables have explained 35 per cent of variance embedded with the consequent variable.

Results and Discussion

137

Important Revelation The causal variables retained at the last step are, size of land under irrigation (x12), no. of fragments (x13) and income (on farm & off farm) (x17). They have contributed 35 per cent of variance in the consequent variable, Entrepreneurial communication behavior (y4). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Entrepreneurial communication behavior (y4). Model 6.43: Stepwise Regression analysis: Entrepreneurial commu-nication behavior (y4) versus 23 Causal variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

3%

Results Model 6.43 presents the Stepwise regression analysis, wherein the variable, no. of enterprise (x3), has been retained at the last step to elicit its determining and critical contribution to the dependent variable, Entrepreneurial communication behavior (y4). The variable, no. of enterprise (x3), has explained 3 per cent of variance embedded with the consequent variable.

Important Revelation The revelation implies that, more the number of enterprises an entrepreneur has to manage, the more would be the need for entrepreneurial communication. This will further drive the entrepreneur to diverse

Strategic Importance With the increasing number of enterprises, one needs to increase his communication behavior, inorder to gather information about diverse types of enterprises regarding fishery, livestock, crop, etc. One needs to know from where he or she should get the proper information about his or her enterprises. So, to manage one’s enterprises properly, one needs to have higher Entrepreneurial communication behavior (y4).

138

Entrepreneurial Communication in Agriculture

Model 6.44: Stepwise Regression analysis: Entrepreneurial commu-nication behavior (y4) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

Results Model 6.44 presents the differential variable performance and comparative delineation between Tripura and West Bengal in terms of Entrepreneurial communication behavior (y4), through Step wise regression analysis.

Important Revelation The comparative delineation between Tripura and West Bengal shows that, Entrepreneurial communication behavior (y4) has been uniquely contributed by 3 variables in Tripura and these are, family education (x7), no. of male workers (x22) and no. of female workers (x23). For the comparing state West Bengal, same dependent variable, Entrepreneurial communication behavior (y4) has been uniquely contributed again by 3 variables and these are, size of land under irrigation (x12), no. of fragments (x13) and income (on farm & off farm) (x17) and it can be seen that none of the causal variables are found to be common between these two states. So, in terms of strategic implication for both the states, respective functional variables as identified through Step wise regression analysis, should be focused and regressed adequately. Model 6.45: Stepwise Regression analysis: Value addition (y5) versus 23 Causal variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Results and Discussion

139

29%

Results Model 6.45 presents the Stepwise regression analysis, wherein the variables, family size (x6) and crop yield (x14), have been retained at the last step to elicit their determining and critical contribution to dependent variable, Value addition (y5). The causal variables have explained 29 per cent of variance embedded with the consequent variable.

Important Revelation The causal variables retained at the last step are, family size (x6) and crop yield (x14). They have contributed 29 per cent of variance in the consequent variable, Value addition (y5). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Value addition (y5). Model 6.46: Stepwise Regression analysis: Value addition (y5) versus 23 Causal variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

22%

140

Entrepreneurial Communication in Agriculture

Results Model 6.46 presents the Stepwise regression analysis, wherein the variables, livestock yield (x15) and income (on farm & off farm) (x17), have been retained at the last step to elicit their determining and critical contribution to Value addition (y5).The causal variables have explained 22 per cent of variance embedded with the consequent variable.

Important Revelation The causal variables retained at the last step are, family size (x6) and crop yield (x14). They have contributed 29 per cent of variance in the consequent variable, Value addition (y5). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Value addition (y5). Model 6.47: Stepwise Regression analysis: Value addition (y5) versus 23 Causal variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

4.90%

Results Model 6.47 presents the Stepwise regression analysis, wherein the variables, no. of enterprise (x3), family education (x7), family expenditure (x18) and marketable surplus (x19) have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Value addition (y5). The variables, no. of enterprise (x3), farm education (x7), family expenditure (x18) and marketable surplus (x19), have explained 4.90 per cent of variance embedded with the consequent variable.

Important Revelation TheValue addition (y5) process is conditioned by supportive branding, market positioning, customer choices and marketability. This is especially important for

Results and Discussion

141

agricultural entrepreneurship because the concept is just upcoming and subsequent perceptions are running in the incubation process. That’s why, and as logical as would have been, the causal variables, no. of enterprise (x3), family education (x7), family expenditure (x18) and marketable surplus (x19), are behaving with a symphony of operational osmosis and functional networking in marketing Value additions (y5) as an integral part of entrepreneurial communication.

Strategic Importance When number of enterprises goes up, there are both risk and opportunity. When the number of enterprises are more catered by a single entrepreneur, the risks are shared and opportunities are collectively absorbed to make entrepreneurial communication more diverse and mutually synchronized amongst the plethora of enterprises within the realm of entrepreneurial communication. Model 6.48: Stepwise Regression analysis:Value addition (y5) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

Results Model 6.48 presents the differential variable performance and comparative delineation between Tripura and West Bengal in terms of Value addition (y5), through Step wise regression analysis.

Important Revelation The comparative delineation between Tripura and West Bengal shows that, Value addition (y5) has been uniquely contributed by 2 variables in Tripura and these are, family size (x6) and crop yield (x14). For the comparing state West Bengal, same dependent variable, Value addition (y5), has been uniquely contributed again by 2

142

Entrepreneurial Communication in Agriculture

variables and these are, livestock yield (x15) and income (on farm & off farm) (x17) and it can be seen that none of the causal variables are found to be common between these two states. So, in terms of strategic implication for both the states, respective functional variables as identified through Step wise regression analysis, should be focused and regressed adequately. Model 6.49: Stepwise Regression analysis: Economical communi-cation (y6) versus 23 Causal variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

32%

Results Model 6.49 presents the Stepwise regression analysis, wherein the variables, income (on farm & off farm) (x17), marketed surplus (x20) and no. of male workers (x22), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Economical communication (y6). The causal variables have explained 32 per cent of variance embedded with the consequent variable.

Important Revelation The causal variables retained at the last step are, income (on farm & off farm) (x17), marketed surplus (x20) and no. of male workers (x22). They have contributed 32 per cent of variance in the consequent variable, Economical communication (y6). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Economical communication (y6). Model 6.50: Stepwise Regression analysis: Economical communi-cation (y6) versus 23 Causal variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results and Discussion

143

46%

Results Model 6.50 presents the Stepwise regression analysis, wherein the variables, age (x1), education (x2), year of enterprise (x4), size of homestead land (x10), livestock yield (x15) and family labour (x21), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Economical communication (y6). The causal variables have explained 46 per cent of variance embedded with the consequent variable.

Important Revelation The causal variables retained at the last step are, age (x1), education (x2), year of enterprise (x4), size of homestead land (x10), livestock yield (x15) and family labour (x21). They have contributed 46 per cent of variance in the consequent variable, Economical communication (y6). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Economical communication (y6). Model 6.51: Stepwise Regression analysis: Economical communi-cation (y6) versus 23 Causal variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

10.80%

144

Entrepreneurial Communication in Agriculture

Results Model 6.51 presents the Stepwise regression analysis, wherein the variables, family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), income (on farm & off farm) (x17), family labour (x21,) and no. of female workers (x23), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Economical communication (y6). The variables, family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), income (on farm & off farm) (x17), family labour (x21) and no. of female workers (x23), have explained 10.80 per cent of variance embedded with the consequent variable.

Important Revelation The revelation implies that the economical activities, family economy, number of fragments, income, productive function, catered by the family, are well relegated to the Economical communication (y6). This is not just a causal relation between the set of variables and the consequent one, rather they provide and bestow an interactive communication between economic behavior and the contributory economic factors emanating from productive functions and characters cater and retain at the family level.

Strategic importance So, to maintain one’s Economical communication (y6), one must try to improve the education level of both himself and of his family members, income, number of fragments, manpower and female workers. As the dependent variable and the above stated independent variables have causal effect relationship, the causal variables must be maintained properly in order to maintain the Economical communication (y6). Model 6.52: Stepwise Regression analysis: Economical communi-cation (y6) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

Results and Discussion

145

Results Model 6.52 presents the differential variable performance and comparative delineation between Tripura and West Bengal in terms of Economical communication (y6), through Step wise regression analysis.

Important Revelation The comparative delineation between Tripura and West Bengal shows that, Economical communication (y6) has been uniquely contributed by 3 variables in Tripura and these are, income (on farm & off farm) (x17), marketed surplus (x20) and no. of male workers (x22). For the comparing state West Bengal, same dependent variable, Economical communication (y6) has been uniquely contributed by 6 variables and these are age (x1), education (x2), year of enterprise (x4), size of homestead land (x10), livestock yield (x15) and family labour (x21) and it can be seen that none of the causal variables are found to be common between these two states. So, in terms of strategic implication for both the states, respective functional variables as identified through step wise regression analysis, should be focused and regressed adequately. Model 6.53: Stepwise Regression analysis: Transportation cost (y7) versus 23 Causal variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

47%

Results Model 6.53 presents the Stepwise regression analysis, wherein the variables, age (x1), income (on farm & off farm) (x17) and no. of female workers (x23), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Transportation cost (y7). The causal variables have explained 47 per cent of variance embedded with the consequent variable.

146

Entrepreneurial Communication in Agriculture

Important Revelation The causal variables retained at the last step are,age (x1), income (on farm & off farm) (x17) and no. of female workers (x23). They have contributed 47 per cent of variance in the consequent variable, Transportation cost (y7). So, these variables must be considered emphatically while a strategic intervention will be delineated for improving Transportation cost (y7). Model 6.54: Stepwise Regression analysis: Transportation cost (y7) versus 23 Causal variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

29%

Results Model 6.54 presents the stepwise regression analysis, wherein the variables, age (x1), family size (x6), income (on farm & off farm) (x17) and family expenditure (x18), have been retained at the last step to elicit their determining and critical contribution to Transportation cost (y7). The causal variables have explained 29 per cent of variance embedded with the consequent variable.

Important Revelation The causal variables retained at the last step are, age (x1), family size (x6), income (on farm & off farm) (x17) and family expenditure (x18). They have contributed 29 per cent of variance in the consequent variable, Transportation cost (y7). So, these variables must be considered emphatically while a strategic intervention will be delineated for economizing transportation cost (y7). Model 6.55: Stepwise Regression analysis: Transportation cost (y7) versus 23 Causal variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Results and Discussion

147

18%

Results Model 6.55 presents the Stepwise regression analysis, wherein the variables, age (x1), no. of enterprise (x3), year of enterprise (x4), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20), have been retained at the last step to elicit their determining and critical contribution to the dependent variable, Transportation cost (y7). The variables, age (x1), no. of enterprise (x3), year of enterprise (x4), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20), have explained 18 per cent of variance embedded with the consequent variable.

Important Revelation The revelation implies that the Transportation cost (y7) is a major constituent of the economic behavior of a supply chain. The cost of transportation is a polyhedral concept to integrate distance of market, the mode of transportation, the time of transportation and also the road conditions that govern speed and cost of transportation as well. That’s why, a whole lot of system variables have come out as critical causal factors to contribute to Transportation cost (y7).

148

Entrepreneurial Communication in Agriculture

Strategic Importance So, the Transportation cost (y7) is effected by the causal variables like age, enterprise, land owned, yield, income, expenditure and surplus. Transportation cost (y7) mainly depends upon one’s availability of surplus and income. When the surplus will be more, that time only he will have to send bulk amount to the market. So, the causal variables effect the Transportation cost (y7) to a great extent. Model 6.56: Stepwise Regression analysis: Transportation cost (y7) versus 23 Independent Variables (x1 to x23): A comparative delineation: Tripura versus West Bengal

Results Model 6.56 presents the differential variable performance and comparative delineation between Tripura and West Bengal in terms of Transportation cost (y7), through Step wise regression analysis.

Important Revelation The comparative delineation between Tripura and West Bengal shows that, Transportation cost (y7) has been uniquely contributed by 3 variables in Tripura and these are, age (x1), income (on farm & off farm) (x17) and no. of female workers (x23). For the comparing state West Bengal, same dependent variable Transportation cost (y7) has been uniquely contributed by 4 variables and these are, age (x1), family size (x6), income (on farm & off farm) (x17) and family expenditure (x18) and it can be seen that 2 causal variables, namely, age (x1) and income (on farm & off farm) (x17), are found to be common between these two states. So, in terms of strategic implication for both the states, respective functional variables as identified through Step wise regression analysis, should be focused and regressed adequately.

Results and Discussion

149

Model 6.57: Path analysis of Farm enterprise information from cosmopolite sources (y1) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Results Model 6.57 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of cultivable land (x11), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from cosmopolite sources (y1) and the variable, material possessed (x8) has routed the highest indirect individual effect of as many as 11 times, to characterize Farm enterprise information from cosmopolite sources (y1).

Important Revelation Size of cultivable land (x11) has exerted both the highest direct and indirect effect on Farm enterprise information from cosmopolite sources (y1). Higher the size of cultivable land (x11), the more it has an intense information seeking to organize the entrepreneurial management well framed within basic data inventory. The variable, material possessed (x8), has enrouted the highest indirect individual effect of as many as 11 exogenous variables, to characterize the consequent variable, Farm enterprise information from cosmopolite sources (y1). So, the variables, size of cultivable land (x11) and material possessed (x8), have come out for this set of analysis as the most significant determinants on the behavior of Farm enterprise information from cosmopolite sources (y1), which has been put forth by highest

150

Entrepreneurial Communication in Agriculture

direct, indirect and associated properties. So, these are the most important and functional determinants to characterize the consequent variable, Farm enterprise information from cosmopolite sources (y1). Model 6.58: Path analysis of Farm enterprise information from cosmopolite sources (y1) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results Model 6.58 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of cultivable land (x11), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterpriseinformation from cosmopolite sources (y1) and the variable, family size (x6), has routed the highest indirect individual effect of as many as 15 times, to characterize Farm enterprise information from cosmopolite sources (y1).

Important Revelation Size of cultivable land (x11) has exerted both the highest direct and indirect effect on Farm enterprise information from cosmopolite sources (y1). The variable, family size (x6), has enrouted the highest indirect individual effect of as many as 15 exogenous variables to characterize the consequent variable, Farm enterprise information from cosmopolite sources (y1). So, the variables, size of cultivable land (x11) and family size (x6), have come out for this set of analysis as the most significant determinants on

Results and Discussion

151

the behavior of Farm enterprise information from cosmopolite sources (y1), which has been put forth by highest direct, indirect and associated properties. So, these are the most important and functional determinants to characterize the consequent variable, Farm enterprise information from cosmopolite sources (y1). Model 6.59: Path analysis of Farm enterprise information from cosmopolite sources (y1) versus 23 exogenous variables (x1 to x23) of pooled villages of states (Tripura and West Bengal)

Results Model 6.59 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from cosmopolite sources (y1) and the variable, size of holding (x9), has routed the highest indirect individual effect of as many as 13 times, to characterize Farm enterprise information from cosmopolite sources (y1).

Important Revelation Size of homestead land (x10), has exerted both the highest direct and indirect effect on Farm enterprise information from cosmopolite sources (y1). The variable, size of holding (x9), has enrouted the highest indirect individual effect of as many as 13 exogenous variables to characterize the consequent variable, Farm enterprise information from cosmopolite sources (y1), this is because, size of holding (x9) effects

152

Entrepreneurial Communication in Agriculture

the production and quality of information gathered for the farm. So, the variables, size of homestead land (x10) and size of holding (x9), have come out for this set of analysis as the most significant determinants on the behavior of Farm enterprise information from cosmopolite sources (y1), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Farm enterprise information from cosmopolite sources (y1). Model 6.60: Path analysis of Farm enterprise information from localite sources (y2) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Results Model 6.60 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of cultivable land (x11), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from localite sources (y2) and the variable, training exposure (x5), has routed the highest indirect individual effect of as many as 9 times, to characterize Farm enterprise information from localite sources (y2).

Important Revelation Size of cultivable land (x11), has exerted both the highest direct and indirect effect on Farm enterprise information from localite sources (y2). The variable, training exposure (x5), has enrouted the highest indirect individual effect of as many as

Results and Discussion

153

9 exogenous variables to characterize the consequent variable, Farm enterprise information from localite sources (y2), because through training, individual’s behavior changes. So, the variables, size of cultivable land (x11) and training exposure (x5), have come out for this set of analysis as the most significant determinants on the behavior of Farm enterprise information from localite sources (y2), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Farm enterprise information from localite sources (y2). Model 6.61: Path analysis of Farm enterprise information from localite sources (y2) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results Model 6.61 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from localite sources (y2) and the variable, year of enterprise (x4), has routed the highest indirect individual effect of as many as 14 times, to characterize Farm enterprise information from localite sources (y2).

Important Revelation Size of holding (x9), has exerted both the highest direct and indirect effect on Farm enterprise information from localite sources (y2). Higher the size of holding (x9),

154

Entrepreneurial Communication in Agriculture

the more it has an intense information seeking to organize the entrepreneurial management well framed within basic data inventory. The variable, year of enterprise (x4), has enrouted the highest indirect individual effect of as many as 14 exogenous variables to characterize the consequent variable, Farm enterprise information from localite sources (y2). So, the variables, size of holding (x9) and year of enterprise (x4), have come out for this set of analysis as the most significant determinants on the behavior of Farm enterprise information from localite sources (y2), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Farm enterprise information from localite sources (y2). Model 6.62: Path analysis of Farm enterprise information from localite sources (y2) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Results Model 6.62 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from localite sources (y2) and the variable, size of holding (x9), has routed the highest indirect individual effect of as many as 11 times, to characterize Farm enterprise information from localite sources (y2)

Results and Discussion

155

Important Revelation Size of homestead land (x10), has exerted both the highest direct and indirect effect on Farm enterprise information from localite sources (y2). The variable, size of holding (x9), has enrouted the highest indirect individual effect of as many as 11 exogenous variables to characterize the consequent variable, Farm enterprise information from localite sources (y2) because size of holding (x9) is one of the crucial factors for entrepreneurial communication and ventures. So, the variables, size of homestead land (x10) and size of holding (x9), have come out for this set of analysis as the most significant determinants on the behavior of Farm enterprise information from localite sources (y2), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Farm enterprise information from localite sources (y2). Model 6.63: Path analysis of Information seeking and responding behavior (y3) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Results Model 6.63 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of cultivable land(x11), has recorded both the highest direct and indirect effect on the consequent variable, Information seeking and responding behavior (y3). The same variable, size of cultivable land (x11), has routed the highest indirect individual effect of as many as 15 times, to characterize Information seeking and responding behavior (y3).

156

Entrepreneurial Communication in Agriculture

Important Revelation The variable, size of cultivable land (x11), has exerted both the highest direct and indirect effect on Information seeking and responding behavior (y3). The higher the variable, size of cultivable land (x11), the more it has an intense Information seeking and responding behavior (y3). The same variable, size of cultivable land (x11), has enrouted the highest indirect individual effect of as many as 15 exogenous variables to characterize the consequent variable, Information seeking and responding behavior (y3). So, the variable, size of cultivable land (x11), has come out for this set of analysis as the most significant determinant on the characteristic of Information seeking and responding behavior (y3), which has been put forth by highest direct, indirect and associated properties. Therefore, this is the most important and functional determinant to characterize the consequent variable, Information seeking and responding behavior (y3). Model 6.64: Path analysis of Information seeking and responding behavior (y3) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results Model 6.64 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Information seeking and responding behavior (y3) and the variable, no. of fragments (x13), has routed the highest indirect individual effect of as many as 11 times, to characterize Information seeking and responding behavior (y3).

Results and Discussion

157

Important Revelation Size of holding (x9), has exerted both the highest direct and indirect effect on Information seeking and responding behavior (y3). Higher the size of holding (x9), the more it has an intense information seeking behavior to organize the entrepreneurial ventures well within basic data management. The variable, no. of fragments (x13), has enrouted the highest indirect individual effect of as many as 11 exogenous variables to characterize the consequent variable, Information seeking and responding behavior (y3). So, the variables, size of holding (x9) and no. of fragments (x13), have come out for this set of analysis as the most significant determinants on the characteristic of Information seeking and responding behavior (y3), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Information seeking and responding behavior (y3). Model 6.65: Path analysis of Information seeking and responding behavior (y3) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Results Model 6.65 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Information seeking and responding behavior (y3) and the variable, size of holding (x9), has routed the highest indirect individual effect of as many as 10 times, to characterize Information seeking and responding behavior (y3).

158

Entrepreneurial Communication in Agriculture

Important Revelation Size of homestead land (x10), has exerted both the highest direct and indirect effect on Information seeking and responding behavior (y3) because with increasing land holding one will require more information to manage the land properly. The variable, size of holding (x9), has enrouted the highest indirect individual effect of as many as 10 exogenous variables to characterize the consequent variable, Information seeking and responding behavior (y3). So, the variables, size of homestead land (x10) and size of holding (x9), have come out for this set of analysis as the most significant determinants on the characteristic of Information seeking and responding behavior (y3), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Information seeking and responding behavior (y3). Model 6.66: Path analysis of Entrepreneurial communication behavior (y4) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Results Model 6.66 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Entrepreneurial communication behavior (y4) and the variable, marketed surplus (x20), has routed the highest indirect individual effect of as many as 14 times, to characterize Entrepreneurial communication behavior (y4).

Results and Discussion

159

Important Revelation Size of holding (x9), has exerted both the highest direct and indirect effect on Entrepreneurial communication behavior (y4). The variable, marketed surplus (x20), has enrouted the highest indirect individual effect of as many as 14 exogenous variables to characterize the consequent variable, Entrepreneurial communication behavior (y4). So, the variables, size of holding (x9) and marketed surplus (x20), have come out for this set of analysis as the most significant determinants on the characteristic of Entrepreneurial communication behavior (y4), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Entrepreneurial communication behavior (y4). Model 6.67: Path analysis of Entrepreneurial communication behavior (y4) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results Model 6.67 presents the path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Entrepreneurial communication behavior (y4) and the variable, cropping intensity (x16), has routed the highest indirect individual effect of as many as 10 times, to characterize Entrepreneurial communication behavior (y4).

160

Entrepreneurial Communication in Agriculture

Important Revelation Size of holding (x9), has exerted both the highest direct and indirect effect on Entrepreneurial communication behavior (y4). Size of holding (x9), effect both directly and indirectly because with the increasing farm products, information seeking, processing and disseminating behaviour also increase to manage the farm. The variable, cropping intensity (x16), has enrouted the highest indirect individual effect of as many as 10 exogenous variables to characterize the consequent variable, Entrepreneurial communication behavior (y4). So, the variables, size of holding (x9) and cropping intensity (x16), have come out for this set of analysis as the most significant determinants on the characteristic of Entrepreneurial communication behavior (y4), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Entrepreneurial communication behavior (y4). Model 6.68: Path analysis of Entrepreneurial communication behavior (y4) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Results Model 6.68 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Entrepreneurial communication behavior (y4) and the variable size of holding (x9), has routed the highest indirect individual effect of as many as 14 times, to characterize Entrepreneurial communication behavior (y4).

Results and Discussion

161

Important Revelation Size of homestead land (x10), has exerted both the highest direct and indirect effect on Entrepreneurial communication behavior (y4). The variable, size of holding (x9), has enrouted the highest indirect individual effect of as many as 14 exogenous variables to characterize the consequent variable, Entrepreneurial communication behavior (y4). So, the variables, size of homestead land (x10) and size of holding (x9), have come out for this set of analysis as the most significant determinants on the characteristic of Entrepreneurial communication behavior (y4), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Entrepreneurial communication behavior (y4). Model 6.69: Path analysis of Value addition (y5) versus 23 exogenous variables (x1to x23) of villages Bamutia and Kamalghat, Tripura

Results Model 6.69 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded the highest direct effect and the variable, size of cultivable land (x11), has recorded highest indirect effect on the consequent variable, Value addition (y5). The variable, education (x2), has routed the highest indirect individual effect of as many as 10 times, to characterize Value addition (y5).

Important Revelation Size of holding (x9), has exerted the highest direct effect and the variable, size of cultivable land (x11), has exerted the highest indirect effect on Value addition (y5).

162

Entrepreneurial Communication in Agriculture

As long as the land owned is more and the farm produced are more, there will be more demand of value added products. The variable, education (x2), has enrouted the highest indirect individual effect of as many as 10 exogenous variables to characterize the consequent variable, Value addition (y5). So, the variables, size of holding (x9), size of cultivable land (x11) and education (x2), have come out for this set of analysis as the most significant determinants on the behavior of Value addition (y5), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Value addition (y5). Model 6.70: Path analysis of Value addition (y5) versus 23 exogenous variables (x1to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results Model 6.70 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of cultivable land (x11), has recorded the highest direct effect and the variable, size of land under irrigation (x12), has recorded the highest indirect effect on the consequent variable, Value addition (y5) and the variable, income (on farm & off farm) (x17), has routed the highest indirect individual effect of as many as 8 times, to characterize Value addition (y5).

Important Revelation Size of cultivable land (x11), has exerted the highest direct effect and the variable, size of land under irrigation (x12), has exerted the highest indirect effect on Value addition (y5). When irrigation pattern improves, production also increases indirectly, leading to increased Value addition (y5). The variable, income (on farm & off farm) (x17), has

Results and Discussion

163

enrouted the highest indirect individual effect of as many as 8 exogenous variables to characterize the consequent variable, Value addition (y5). So, the variables, size of cultivable land (x11), size of land under irrigation (x12) and income (on farm & off farm) (x17), have come out for this set of analysis as the most significant determinants on the behavior of Value addition (y5), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Value addition (y5). Model 6.71: Path analysis of Value addition (y5) versus 23 exogenous variables (x1to x23) of pooled villages of two states (Tripura and West Bengal)

Results Model 6.71 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of land under irrigation (x12), has recorded both the highest direct and indirect effect on the consequent variable, Value addition (y5) and the variable, size of cultivable land (x11), has routed the highest indirect individual effect of as many as 15 times, to characterize Value addition (y5).

Important Revelation Size of land under irrigation (x12), has exerted both the highest direct and indirect effect on Value addition (y5). Higher the size of land under irrigation (x12), the more will be the Value addition (y5) activities. The variable, size of cultivable land (x11), has enrouted the highest indirect individual effect of as many as 15 exogenous variables to characterize the consequent variable, Value addition (y5). So, the variables, size of land under irrigation (x12) and size of cultivable land (x11), have come out for this set of analysis as the most significant determinants on the behavior of Value

164

Entrepreneurial Communication in Agriculture

addition (y5), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Value addition (y5). Model 6.72: Path analysis of Economical communication (y6) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Results Model 6.72 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Economical communication (y6) and the variable, family expenditure (x18), has routed the highest indirect individual effect of as many as 11 times, to characterize Economical communication (y6).

Important Revelation Size of holding (x9), has exerted both the highest direct and indirect effect on Economical communication (y6). The variable, family expenditure (x18), has enrouted the highest indirect individual effect of as many as 11 exogenous variables to characterize the consequent variable, Economical communication (y6). So, the variables, size of holding (x9) and family expenditure (x18), have come out for this set of analysis as the most significant determinants on the nature of Economical communication (y6), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Economical communication (y6).

Results and Discussion

165

Model 6.73: Path analysis of Economical communication (y6) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results Model 6.73 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Economical communication (y6) and the variable, family education (x7), has routed the highest indirect individual effect of as many as 13 times, to characterize Economical communication (y6).

Important Revelation Size of holding (x9) has exerted both the highest direct and indirect effect on Economical communication (y6).The variable, family education (x7) has enrouted the highest indirect individual effect of as many as 13 exogenous variables to characterize the consequent variable, Economical communication (y6). Education is an important part to understand the financial matters. So, the variables, size of holding (x9) and family education (x7), have come out for this set of analysis as the most significant determinants on the behavior of Economical communication (y6), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Economical communication (y6).

166

Entrepreneurial Communication in Agriculture

Model 6.74: Path analysis of Economical communication (y6) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Results Model 6.74 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of land under irrigation (x12), has recorded both the highest direct and indirect effect on the consequent variable, Economical communication (y6) and the variable, income (on farm & off farm) (x17), has routed the highest indirect individual effect of as many as 9 times, to characterize Economical communication (y6).

Important Revelation Size of land under irrigation (x12), has exerted both the highest direct and indirect effect on Economical communication (y6). The variable, income (on farm & off farm) (x17), has enrouted the highest indirect individual effect of as many as 9 exogenous variables to characterize the consequent variable, Economical communication (y6). So, the variables, size of land under irrigation (x12) and income (on farm & off farm) (x17), have come out for this set of analysis as the most significant determinants on the behavior of Economical communication (y6), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Economical communication (y6).

Results and Discussion

167

Model 6.75: Path analysis of Transportation cost (y7) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Results Model 6.75 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Transportation cost (y7). The same variable, size of holding (x9), has routed the highest indirect individual effect of as many as 12 times to characterize Transportation cost (y7).

Important Revelation Size of holding (x9), has exerted both the highest direct and indirect effect on Transportation cost (y7). The same variable, size of holding (x9), has also enrouted the highest indirect individual effect of as many as 12 exogenous variables to characterize the consequent variable, Transportation cost (y7). So, the variable, size of holding (x9), has come out for this set of analysis as the most significant determinant on the behavior of Transportation cost (y7), which has been put forth by highest direct, indirect and associated properties. Therefore, this is the most important and functional determinant to characterize the consequent variable, Transportation cost (y7).

168

Entrepreneurial Communication in Agriculture

Model 6.76: Path analysis of Transportation cost (y7) versus 23 exogenous variables (x1-x23) of villages Bhawanipore and Ghoragacha, West Bengal

Results Model 6.76 presents the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Transportation cost (y7) and the variable, size of holding (x9), has routed the highest indirect individual effect of as many as 10 times, to characterize Transportation cost (y7).

Important Revelation Size of homestead land (x10), has exerted both the highest direct and indirect effect on Transportation cost (y7). The variable, size of holding (x9), has enrouted the highest indirect individual effect of as many as 10 exogenous variables to characterize the consequent variable, Transportation cost (y7). So, the variables, size of homestead land (x10) and size of holding (x9), have come out for this set of analysis as the most significant determinants on the behavior of Transportation cost (y7), which has been put forth by highest direct, indirect and associated properties. Therefore, these are the most important and functional determinants to characterize the consequent variable, Transportation cost (y7).

Results and Discussion

169

Model 6.77: Path analysis of Transportation cost (y7) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

Results Model 6.77 presents the path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Transportation cost (y7) and the variable, no. of fragments (x13) has routed the highest indirect individual effect of as many as 11 times, to characterize Transportation cost (y7).

Important Revelation Size of homestead land (x10), has exerted both the highest direct and indirect effect on Transportation cost (y7). The variable, no. of fragments (x13), has enrouted the highest indirect individual effect of as many as 11 exogenous variables to characterize the consequent variable, Transportation cost (y7). So, the variables, size of homestead land (x10) and no. of fragments (x13), have come out for this set of analysis as the most significant determinants on the behavior of Transportation cost (y7), which has been put forth by highest direct, indirect and associated properties.Therefore, these are the most important and functional determinants to characterize the consequent variable, Transportation cost (y7).

170

Entrepreneurial Communication in Agriculture

Model 6.78: Conglomeration of 23 exogenous variables (x1to x23) of villages Bamutia and Kamalghat, Tripura, into 12 different factors

Model 6.78 presents the renaming and conglomeration of 23 variables (x1-x23)of villages Bamutia and Kamalghat of Tripura into 12 factors:

It has been found that, Factor 1 has accommodated the following variables, viz., family size (x6), family education (x7), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17) and family expenditure (x18) and has been renamed as Family farming. It has contributed 24.95 per cent to explain the variance.

Results and Discussion

171

Factor 2 has accommodated the following variables, viz., training exposure (x5) and size of holding (x9) and has been renamed as Capacity and competency. It has contributed to 19.81 per cent alone and 44.76 per cent cumulatively to explain the variance. Factor 3 has accommodated the following variables, viz., age (x1) and year of enterprise (x4) and has been renamed as Entrepreneurial chronology. It has contributed to 10.37 per cent alone and 55.14 per cent cumulatively to explain the variance. Factor 4 has accommodated the following variables, viz., material possessed (x8), cropping intensity (x16) and no. of male workers (x22) and has been renamed as Social ecology. It has contributed to 6.89 per cent alone and 62.03 per cent cumulatively to explain the variance. Factor 5 has accommodated the following variable, viz., education (x2) and has not been renamed because it consists of single variable. It has contributed to 5.87 per cent alone and 67.90 per cent cumulatively to explain the variance. Factor 6 has accommodated the following variable, viz., no. of enterprise (x3) and has not been renamed because it consists of single variable. It has contributed to 5.19 per cent alone and 73.09 per cent cumulatively to explain the variance. Factor 7 has accommodated the following variable, viz., family labour(x21) and has not been renamed because it consists of single variable. It has contributed to 4.30 per cent alone and 77.40 per cent cumulatively to explain the variance. Factor 8 has accommodated the following variable, viz., no. of fragments (x13) and has not been renamed because it consists of single variable. It has contributed to 3.92 per cent alone and 81.32 per cent cumulatively to explain the variance. Factor 9 has accommodated the following variables, viz., size of cultivable land (x11) and size of land under irrigation (x12) and has been renamed as Agro-ecology. It has contributed to 3.46 per cent alone and 84.79 per cent cumulatively to explain the variance. Factor 10 has accommodated the following variable, viz., no. of female workers (x23) and has not been renamed because it consists of single variable. It has contributed to 3.41 per cent alone and 88.20 per cent cumulatively to explain the variance. Factor 11 has accommodated the following variables, viz., size of homestead land (x10) and has been renamed because it consist of single variable. It has contributed to 3.07 per cent alone and 91.27 per cent cumulatively to explain the variance. Factor 12 has accommodated the following variables, viz., marketable surplus (x19) and marketed surplus (x20) and has been renamed as Marketability. It has contributed to 2.40 per cent alone and 93.68 per cent cumulatively to explain the variance.

172

Entrepreneurial Communication in Agriculture

While an attempt to be made to improve upon the entrepreneurial behavior, as well as the, communication of the practicing farmers of Tripura, these factors need to be considered in a clandestine manner. The proportion of resources can be allotted based on the proportion of variance, respective factors contributed. Model 6.79: Conglomeration of 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal, into 11 different factors

Model 6.79 presents the renaming and conglomeration of 23 variables (x1 to x23) of villages Bhawanipore and Ghoragacha of West Bengal, into 11 factors: It has been found that, Factor 1 has accommodated the following variables, viz., cropping intensity (x16), income (on farm & off farm) (x17), family expenditure

Results and Discussion

173

(x18), marketable surplus (x19) and marketed surplus (x20) and has been renamed as Family entrepreneurship. It has contributed 22.38 per cent to explain the variance. Factor 2 has accommodated the following variables, viz., size of holding (x9) and size of land under irrigation (x12) and has been renamed as Agro-ecosystem. It has contributed to 17.68 per cent alone and 40.06 per centcumulatively to explain the variance. Factor 3 has accommodated the following variables, viz., age (x1), education (x2), year of enterprise (x4) and training exposure (x5) and has been renamed as Entrepreneurial behaviour. It has contributed to 14.73 per cent alone and 54.79 per cent cumulatively to explain the variance. Factor 4 has accommodated the following variable, viz., no. of enterprise (x3) and has not been renamed because it consists of single variable. It has contributed to 7.35 per cent alone and 62.14 per cent cumulatively to explain the variance. Factor 5 has accommodated the following variables, viz., livestock yield (x15) and Cropping intensity (x16) and has been renamed as Entrepreneurial diversity. It has contributed to 5.70 per cent alone and 67.85 per cent cumulatively to explain the variance. Factor 6 has accommodated the following variables, viz., family education (x7) and material possessed (x8) and has been renamed as Family innovation. It has contributed to 5.55 per cent alone and 73.41 per cent cumulatively to explain the variance. Factor 7 has accommodated the following variables, viz., size of homestead land (x10) and no. of fragments (x13) and has been renamed as Holding distribution. It has contributed to 4.75 per cent alone and 78.16 per cent cumulatively to explain the variance. Factor 8 has accommodated the following variable, viz., size of cultivable land (x11) and has not been renamed because it consists of single variable. It has contributed to 4.21 per cent alone and 82.37 per cent cumulatively to explain the variance. Factor 9 has accommodated the following variables, viz., family labour (x21) and no. of male workers (x22) and has been renamed as Farm human resource. It has contributed to 3.47 per cent alone and 85.85 per cent cumulatively to explain the variance. Factor 10 has accommodated the following variable, viz., no. of female workers (x23) and has not been renamed because it consists of single variable. It has contributed to 3.24 per cent alone and 89.09 per cent cumulatively to explain the variance. Factor 11 has accommodated the following variable, viz., crop yield (x14) and has not been renamed because it consists of single variable. It has contributed to 3.15 per cent alone and 92.24 per cent cumulatively to explain the variance. While an attempt to be made to improve upon the entrepreneurial behavior, as well as the, communication of the practicing farmers of West Bengal, these factors

174

Entrepreneurial Communication in Agriculture

need to be considered in a clandestine manner. The proportion of resources can be allotted based on the proportion of variance, respective factors contributed. Model 6.80: Conglomeration of 30 exogenous variables (x1 to x23 and y1 to y7) of pooled villages of two states (Tripura and West Bengal) into 10 different factors

Model 6.80 presents the renaming and conglomeration of 30 variables (x1 to x23 and y1 - y7) of pooled villages of two states (Tripura and West Bengal) into 10 factors: It has been found that, Factor 1 has accommodated the following variables, viz., family size (x6), family education (x7), livestock yield (x15), cropping intensity (x16), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21) and has been renamed as Family farm ecology. It has contributed 16.4 per cent to explain the variance.

Results and Discussion

175

Factor 2 has accommodated the following variables, viz., size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12) and no. of fragments (x13) and has been renamed as Agro-ecology. It has contributed to 15.71 per cent alone and 32.12 per cent cumulatively to explain the variance. Factor 3 has accommodated the following variables, viz., age (x1), education (x2), year of enterprise (x4) and training exposure (x5) and has been renamed as Capacity building. It has contributed to 9.14 per cent alone and 41.27 per cent cumulatively to explain the variance. Factor 4 has accommodated the following variables, viz., no. of enterprise (x3) and information seeking and responding behavior (y3) and has been renamed as Entrepreneurial communication. It has contributed to 4.78 per cent alone and 46.06 per cent cumulatively to explain the variance. Factor 5 has accommodated the following variables, viz., material possessed (x8) and size of homestead land (x10) and has been renamed as Home innovation. It has contributed to 4.60 per cent alone and 50.66 per cent cumulatively to explain the variance. Factor 6 has accommodated the following variables, viz., no. of female workers (x23), farm enterprise information from localite sources (y2) and economical communication (y6) and has been renamed as Gender communication. It has contributed to 4.35 per cent alone and 55.02 per cent cumulatively to explain the variance. Factor 7 has accommodated the following variables, viz., farm enterprise information from cosmopolite sources (y1), information seeking and responding behaviour (y3) and transportation cost (y7) and has been renamed as Strategic information. It has contributed to 4.24 per cent alone and 59.27 per cent cumulatively to explain the variance. Factor 8 has accommodated the following variable,viz., no. of male workers (x22) and has not been renamed because it consists of single variable. It has contributed to 4.24 per cent alone and 63.51 per cent cumulatively to explain the variance. Factor 9 has accommodated the following variable, viz., crop yield (x14) and has not been renamed because it consists of single variable. It has contributed to 4.16 per cent alone and 67.67 per cent cumulatively to explain the variance. Factor 10 has accommodated the following variables, viz., income (on farm & off farm) (x17) and entrepreneurial communication behaviour (y4) and has been renamed as Communication proficiency. It has contributed to 4.16 per cent alone and 71.83 per cent cumulatively to explain the variance. While an attempt to be made to improve upon the entrepreneurial behavior, as well as the, communication of the practicing farmers of both the states (Tripura and West Bengal), these factors need to be considered in a clandestine manner. The proportion of resources can be allotted based on the proportion of variance, respective factors contributed. 

Chapter

7

SUMMARY AND EPILOGUE 7.1: Summary The present research had been conducted to study the Entrepreneurial communication and their behaviour, process, factors and impact in Agriculture and allied sectors of selected blocks of North eastern state Tripura and West Bengal and in the end their comparison is made. The study had been conducted at villages Bamutia and Kamalghat from blocks Shantipara and Mohanpur respectively, of West Tripura district of Tripura and at villages Bhawanipore and Ghoragacha from blocks Haringhata and Chakdaha respectively, of Nadia district of West Bengal. States, Districts, Blocks and Villages were selected through Purposive sampling method due to the unique nature of the location in terms of subject area of the research and because more number of entrepreneurial farmers areresiding there. A pilot study was conducted to understand the area, its people, institution, communication and extension system of these states. An exhaustive list of respondents was prepared critically with the help of some villagers. From the list, 38 respondents from each of the four villages, and in total 152 respondents were selected for the study through Systematic Random sampling method. The primary data were collected with the help of structured interview schedule by following the personal interview method. The secondary data were collected from our departmental library, internet, Department of Agriculture, Tripura, College of Agriculture, Tripura, Bidhan Chandra krishi Viswavidyalaya, etc. for establishing the conceptual framework of the study. The general objective of the study is to estimate and analyze the “Entrepreneurial communication: The process, factors and impact in Agriculture and allied sectors of selected blocks of Tripura and West Bengal” and the specific objectives are: (i) To conceptualize the premise and perspectives of farm entrepreneurial communication with special reference to Tripura and West Bengal.

Summary and Epilogue

177

(ii) To elucidate the variables characterizing the level of entrepreneurial communication as dependent variable as against a set of exogenous variables, agro-economic and socio-ecological nature. (iii) To estimate the level of interaction between level of entrepreneurial communication and the set of exogenous variables selected for the proposed study. (iv) To organize participatory learning action and analysis on the scope and status of entrepreneurial communication and community level. (v) To generate micro level policy implication for the research locales resultant to the empirical study. 23 Independent variables and 7 Dependent variables were selected for the study respectively and measured with the help of exact scales developed by previous social science researchers or by modifying the developed scale by structured interview schedule for requirement of the study. The Independent variables selected for the study are, Age (x1), Education (x2), No. of enterprise (x3), Year of enterprise (x4), Training exposure (x5), Family size (x6), Family education (x7), Material possessed (x8), Size of holding (x9), Size of homestead land (x10), Size of cultivable land (x11), Size of land under irrigation (x12), No. of fragments (x13), Crop yield (x14), Livestock yield (x15), Cropping intensity (x16), Income (on farm & off farm) (x17), Family expenditure (x18), Marketable surplus (x19), Marketed surplus (x20), Family labour (x21), No. of male workers (x22) and No. of female workers (x23). The Dependent variables selected for the study are, Farm enterprise information from cosmopolite sources (y1), Farm enterprise information from localite sources (y2), Information seeking and responding behavior (y3), Entrepreneurial communication behavior (y4), Value addition (y5), Economical communication (y6) and Transportation cost (y7). The statistical tools viz., Mean, Median, Mode, Standard Deviation, Coefficient of variation, Correlation coefficient, Step wise Regression Analysis, Path analysis and Factor Analysis were used for the purpose of the study. Also Participatory Rural Appraisal is done by Matrix ranking.

7.1.1: Findings from the villages Bamutia and Kamalghat of Tripura are given below: 7.1.1.1: Coefficient of Correlation between Farm enterprise information from cosmopolite sources (y1) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura It has been found that the variables, age (x1), education (x2), year of enterprise (x4), material possessed (x8), size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no.

178

Entrepreneurial Communication in Agriculture

of female workers (x23), have recorded positive and significant correlation with the consequent variable, Farm enterprise information from cosmopolite sources (y1). 7.1.1.2: Coefficient of Correlation between Farm enterprise information from localite sources (y2) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura It has been found that the variables,education (x2), no. of enterprise (x3), family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), crop yield (x14), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21), have recorded positive and significant correlation with the consequent variable, Farm enterprise information from localite sources (y2). 7.1.1.3: Coefficient of Correlation between Information seeking and responding behavior (y3) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura It has been found that the variables,enterprise (x4), training exposure (x5), material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23), have recorded positive and significant correlation with the consequent variable, Information seeking and responding behavior (y3). 7.1.1.4: Coefficient of Correlation between Entrepreneurial communication behavior (y4) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura It has been found that the variables, age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), family education (x7), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21), have recorded positive and significant correlation with the consequent variable, Entrepreneurial communication behavior (y4). 7.1.1.5: Coefficient of Correlation between Value addition (y5) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura It has been found that the variables, age (x1), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23), have recorded positive and significant correlation with the consequent variable, Value addition (y5).

Summary and Epilogue

179

7.1.1.6: Coefficient of Correlation between Economical communication (y6) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura It has been found that the variables, age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), family size (x6), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21), have recorded positive and significant correlation with the consequent variable, Economical communication (y6). 7.1.1.7: Coefficient of Correlation between Transportation cost (y7) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura It has been found that the variables, age (x1), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), livestock yield (x15), cropping intensity (x16), family labour (x21), no. of male workers (x22) and no. of female workers (x23), have recorded positive and significant correlation with the consequent variable, Transportation cost (y7). 7.1.1.8: Stepwise Regression analysis of Farm enterprise information from cosmopolite sources (y1) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Stepwise regression analysis, wherein the variables, training exposure (x5), family size (x6), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), livestock yield (x15) and marketed surplus (x20), have been retained at the last step to elicit their determining and critical contribution to Farm enterprise information from cosmopolite sources (y1). The causal variables have explained 45 per cent variance embedded with the consequent variable. 7.1.1.9: Stepwise Regression analysis of Farm enterprise information from localite sources (y2) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Stepwise regression analysis, wherein the variables, age (x1), year of enterprise (x4), size of homestead land (x10), crop yield (x14) and no. of male workers (x22), have been retained at the last step to elicit their determining and critical contribution to Farm enterprise information from localite sources (y2). The causal variables have explained 37 per cent of variance embedded with the consequent variable. 7.1.1.10: Stepwise Regression analysis of Information seeking and responding behavior (y3) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Stepwise regression analysis, wherein the variables, material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), cropping intensity (x16) and no. of male workers (x22), have been retained at the last step to elicit their determining and critical contribution to Information

180

Entrepreneurial Communication in Agriculture

seeking and responding behavior (y3). The causal variables have explained 43 per cent of variance embedded with the consequent variable. 7.1.1.11: Stepwise Regression analysis of Entrepreneurial communication behavior (y4) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Stepwise regression analysis, wherein the variables, family education (x7), no. of male workers (x22) and no. of female workers (x23), have been retained at the last step to elicit their determining and critical contribution to Entrepreneurial communication behavior (y4). The causal variables have explained 42 per cent of variance embedded with the consequent variable. 7.1.1.12: Stepwise Regression analysis of Value addition (y5) versus 23 Independent variables (x1 to x23) of Bamutia and Kamalghat, Tripura The study reveals the Stepwise regression analysis, wherein the variables, family size (x6) and crop yield (x14), have been retained at the last step to elicit their determining and critical contribution to Value addition (y5). The causal variables have explained 29 per cent of variance embedded with the consequent variable. 7.1.1.13: Stepwise Regression analysis of Economical communication (y6) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Stepwise regression analysis, wherein the variables, income (on farm & off farm) (x17), marketed surplus (x20) and no. of male workers (x22), have been retained at the last step to elicit their determining and critical contribution to Economical communication (y6). The causal variables have explained 32 per cent of variance embedded with the consequent variable. 7.1.1.14: Stepwise Regression analysis of Transportation cost (y7) versus 23 Independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Stepwise regression analysis, wherein the variables, age (x1), income (on farm & off farm) (x17) and no. of female workers (x23), have been retained at the last step to elicit their determining and critical contribution to Transportation cost (y7). The causal variables have explained 47 per cent of variance embedded with the consequent variable. 7.1.1.15: Path analysis of Farm enterprise information from cosmopolite sources (y1) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of cultivable land (x11), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from cosmopolite sources (y1) and the variable, material possessed (x8), has routed the highest indirect individual effect of as many as 11 times, to characterize Farm enterprise information from cosmopolite sources (y1). 7.1.1.16: Path analysis of Farm enterprise information from localite sources (y2) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

Summary and Epilogue

181

The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of cultivable land (x11), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from localite sources (y2) and the variable, training exposure (x5), has routed the highest indirect individual effect of as many as 9 times, to characterize Farm enterprise information from localite sources (y2). 7.1.1.17: Path analysis of Information seeking and responding behavior (y3) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of cultivable land (x11), has recorded both the highest direct and indirect effect on the consequent variable, Information seeking and responding behavior (y3). The same variable, size of cultivable land (x11), has routed the highest indirect individual effect of as many as 15 times, to characterize Information seeking and responding behavior (y3). 7.1.1.18: Path analysis of Entrepreneurial communication behavior (y4) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Entrepreneurial communication behavior (y4) and the variable, marketed surplus (x20), has routed the highest indirect individual effect of as many as 14 times, to characterize Entrepreneurial communication behavior (y4). 7.1.1.19: Path analysis of Value addition (y5) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded the highest direct effect and the variable, size of cultivable land (x11), has recorded highest indirect effect on the consequent variable, Value addition (y5). The variable, education (x2), has routed the highest indirect individual effect of as many as 10 times, to characterize Value addition (y5). 7.1.1.20: Path analysis of Economical communication (y6) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Economical communication (y6) and the variable, family expenditure (x18), has routed the highest indirect individual effect of as many as 11 times, to characterize Economical communication (y6). 7.1.1.21: Path analysis of Transportation cost (y7) versus 23 exogenous variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura

182

Entrepreneurial Communication in Agriculture

The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Transportation cost (y7). The same variable, size of holding (x9), has routed the highest indirect individual effect of as many as 12 times, to characterize Transportation cost (y7). 7.1.1.22: Factor Analysis by conglomeration of 23 independent variables (x1 to x23) of villages Bamutia and Kamalghat, Tripura, into 12 factors, based on factor loading and renaming of all the factors Factor 1 has accommodated the variables, family size (x6), family education (x7), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17) and family expenditure (x18) and has been renamed as Family farming. It has contributed 24.95 per cent to explain the variance. Factor 2 has accommodated the variables, training exposure (x5) and size of holding (x9) and has been renamed as Capacity and competency. It has contributed to 19.81 per cent alone and 44.76 per centcumulatively to explain the variance. Factor 3 has accommodated the variables, age (x1) and year of enterprise (x4) and has been renamed as Entrepreneurial chronology. It has contributed to 10.37 per cent alone and 55.14 per cent cumulatively to explain the variance. Factor 4 has accommodated the variables, material possessed (x8), cropping intensity (x16) and no. of male workers (x22) and has been renamed as Social ecology. It has contributed to 6.89 per cent alone and 62.03 per cent cumulatively to explain the variance. Factor 5 has accommodated the variables, education (x2) and has not been renamed because it consists of single variable. It has contributed to 5.87 per cent alone and 67.90 per cent cumulatively to explain the variance. Factor 6 has accommodated the variables, no. of enterprise (x3) and has not been renamed because it consists of single variable. It has contributed to 5.19 per cent alone and 73.09 per cent cumulatively to explain the variance. Factor 7 has accommodated the variables, family labour (x21) and has not been renamed because it consists of single variable. It has contributed to 4.30 per cent alone and 77.40 per cent cumulatively to explain the variance. Factor 8 has accommodated the variables, no. of fragments (x13) and has not been renamed because it consists of single variable. It has contributed to 3.92 per cent alone and 81.32 per cent cumulatively to explain the variance. Factor 9 has accommodated the variables, size of cultivable land (x11) and size of land under irrigation (x12) and has been renamed as Agro-ecology. It has contributed to 3.46 per cent alone and 84.79 per cent cumulatively to explain the variance. Factor 10 has accommodated the variables, no. of female workers (x23) and has not been renamed because it consists of single variable. It has contributed to 3.41 per cent alone and 88.20 per cent cumulatively to explain the variance.

Summary and Epilogue

183

Factor 11 has accommodated the variables, size of homestead land (x10) and has not been renamed because it consists of single variable. It has contributed to 3.07 per cent alone and 91.27 per cent cumulatively to explain the variance. Factor 12 has accommodated the variables, marketable surplus (x19) and marketed surplus (x20) and has been renamed as Marketability. It has contributed to 2.40 per cent alone and 93.68 per cent cumulatively to explain the variance. 7.1.1.23: At last Matrix Ranking was done, which shows that enterprises like piggery, poultry and fishery are in high demand in Tripura.

7.1.2: Findings from the villages Bhawanipore and Ghoragacha of West Bengal are given below: 7.1.2.1: Coefficient of Correlation between Farm enterprise information from cosmopolite sources (y1) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal It has been found that the variables, cropping intensity (x16), family labour (x21) and no. of female workers (x23), have recorded negative and significant correlation with the consequent variable, Farm enterprise information from cosmopolite sources (y1). 7.1.2.2: Coefficient of Correlation between Farm enterprise information from localite sources (y2) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal It has been found that the variables, size of homestead land (x10) has recorded positive and significant correlation with the consequent variable, Farm enterprise information from localite sources (y2) and the variables, livestock yield (x15), family expenditure (x18), no. of male workers (x22) and no. of female workers (x23), have recorded negative and significant correlation with the consequent variable, Farm enterprise information from localite sources (y2). 7.1.2.3: Coefficient of Correlation between Information seeking and responding behavior (y3) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal It has been found that the variables, material possessed (x8), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20), have recorded positive and significant correlation with the consequent variable, Information seeking and responding behavior (y3) and the variable, family size (x6), has recorded negative and significant correlation with the consequent variable, Information seeking and responding behavior (y3). 7.1.2.4: Coefficient of Correlation between Entrepreneurial communication behavior (y4) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal

184

Entrepreneurial Communication in Agriculture

It has been found that the variables, size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12) and income (on farm & off farm) (x17), have recorded negative and significant correlation with the consequent variable, Entrepreneurial communication behavior (y4). 7.1.2.5: Coefficient of Correlation between Value addition (y5) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal It has been found that the variables, age (x1), year of enterprise (x4), training exposure (x5), cropping intensity (x16), family labour (x21) and no. of female workers (x23), have recorded positive and significant correlation with the consequent variable, Value addition (y5) and the variable, no. of male workers (x22), has recorded negative and significant correlation with the consequent variable, Value addition (y5). 7.1.2.6: Coefficient of Correlation between Economical communication (y6) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal It has been found that the variables, education (x2), no. of enterprise (x3), livestock yield (x15), income (on farm & off farm) (x17), marketable surplus (x19) and marketed surplus (x20), have recorded positive and significant correlation with the consequent variable, Economical communication (y6) and the variables, age (x1), year of enterprise (x4) and training exposure (x5), have recorded negative and significant correlation with the consequent variable, Economical communication (y6). 7.1.2.7: Coefficient of Correlation between Transportation cost (y7) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal It has been found that the variables, size of homestead land (x10), livestock yield (x15), and family labour (x21), have recorded positive and significant correlation with the consequent variable, Transportation cost (y7) and the variables, size of land under irrigation (x12), cropping intensity (x16) and income (on farm & off farm) (x17), have recorded negative and significant correlation with the consequent variable, Transportation cost (y7). 7.1.2.8: Stepwise Regression analysis of Farm enterprise information from cosmopolite sources (y1) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Stepwise regression analysis, wherein the variables, no. of enterprise (x3) and material possessed (x8), have been retained at the last step to elicit their determining and critical contribution to Farm enterprise information from cosmopolite sources (y1). The causal variables have explained 28 per cent of variance embedded with the consequent variable. 7.1.2.9: Stepwise Regression analysis of Farm enterprise information from localite sources (y2) versus 23 independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Stepwise regression analysis, wherein the variable, no. of female workers (x23), has been retained to elicit its determining and critical

Summary and Epilogue

185

contribution to Farm enterprise information from localite sources (y2). The causal variable has explained 22 per cent of variance embedded with the consequent variable. 7.1.2.10: Stepwise Regression analysis of Information seeking and responding behavior (y3) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Stepwise regression analysis, wherein the variables, age (x1) and training exposure (x5), have been retained at the last step to elicit their determining and critical contribution to Information seeking and responding behavior (y3). The causal variables have explained 33 per cent of variance embedded with the consequent variable. 7.1.2.11: Stepwise Regression analysis of Entrepreneurial communication behavior (y4) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Stepwise regression analysis, wherein the variables, size of land under irrigation (x12), no. of fragments (x13) and income (on farm & off farm) (x17), have been retained at the last step to elicit their determining and critical contribution to Entrepreneurial communication behavior (y4). The causal variables have explained 35 per cent of variance embedded with the consequent variable. 7.1.2.12: Stepwise regression analysis of Value addition (y5) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Stepwise regression analysis, wherein the variables, livestock yield (x15) and income (on farm & off farm) (x17), have been retained at the last step to elicit their determining and critical contribution to Value addition (y5). The causal variables have explained 22 per cent of variance embedded with the consequent variable. 7.1.2.13: Stepwise Regression analysis of Economical communication (y6) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Stepwise regression analysis, wherein the variables, age (x1), education (x2), year of enterprise (x4), size of homestead land (x10), livestock yield (x15) and family labour (x21), have been retained to elicit their determining and critical contribution to Economical communication (y6). The causal variables have explained 46 per cent of variance embedded with the consequent variable. 7.1.2.14: Stepwise Regression analysis of Transportation cost (y7) versus 23 Independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Stepwise regression analysis, wherein the variables, age (x1), family size (x6), income (on farm & off farm) (x17) and family expenditure (x18), have been retained to elicit their determining and critical contribution to Transportation cost (y7). The causal variables have explained 29 per cent of variance embedded with the consequent variable.

186

Entrepreneurial Communication in Agriculture

7.1.2.15: Path analysis of Farm enterprise information from cosmopolite sources (y1) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of cultivable land (x11), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from cosmopolite sources (y1) and the variable, family size (x6), has routed the highest indirect individual effect of as many as 15 times, to characterize Farm enterprise information from cosmopolite sources (y1). 7.1.2.16: Path analysis of Farm enterprise information from localite sources (y2) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from localite sources (y2) and the variable, year of enterprise (x4), has routed the highest indirect individual effect of as many as 14 times, to characterize Farm enterprise information from localite sources (y2). 7.1.2.17: Path analysis of Information seeking and responding behavior (y3) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Information seeking and responding behavior (y3) and the variable, no. of fragments (x13), has routed the highest indirect individual effect of as many as 11 times, to characterize Information seeking and responding behavior (y3). 7.1.2.18: Path analysis of Entrepreneurial communication behavior (y4) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Entrepreneurial communication behavior (y4) and the variable, cropping intensity (x16), has routed the highest indirect individual effect of as many as 10 times, to characterize Entrepreneurial communication behavior (y4). 7.1.2.19: Path analysis of Value addition (y5) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of cultivable land (x11), has recorded the highest direct effect and the variable, size of land under irrigation (x12), has recorded the highest indirect effect on the consequent variable, Value addition (y5) and the variable, income (on farm & off farm) (x17), has routed the highest indirect individual effect of as many as 8 times, to characterize Value addition (y5).

Summary and Epilogue

187

7.1.2.20: Path analysis of Economical communication (y6) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of holding (x9), has recorded both the highest direct and indirect effect on the consequent variable, Economical communication (y6) and the variable, family education (x7), has routed the highest indirect individual effect of as many as 13 times, to characterize Economical communication (y6). 7.1.2.21: Path analysis of Transportation cost (y7) versus 23 exogenous variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Transportation cost (y7) and the variable, size of holding (x9), has routed the highest indirect individual effect of as many as 10 times, to characterize Transportation cost (y7). 7.1.2.22: Factor Analysis by Conglomeration of 23 independent variables (x1 to x23) of villages Bhawanipore and Ghoragacha, West Bengal, into 11 factors, based on factor loading and renaming of all the factors Factor 1 has accommodated the variables, cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20) and has been renamed as Family entrepreneurship. It has contributed 22.38 per cent to explain the variance. Factor 2 has accommodated the variables, size of holding (x9) and size of land under irrigation (x12) and has been renamed as Agro-ecosystem. It has contributed to 17.68 per cent alone and 40.06 per cent cumulatively to explain the variance. Factor 3 has accommodated the variables, age (x1), education (x2), year of enterprise (x4) and training exposure (x5) and has been renamed as Entrepreneurial behavior. It has contributed to 14.73 per cent alone and 54.79 per cent cumulatively to explain the variance. Factor 4 has accommodated the variables, no. of enterprise (x3) and has not been renamed because it consists of single variable. It has contributed to 7.35 per cent alone and 62.14 per cent cumulatively to explain the variance. Factor 5 has accommodated the variables, livestock yield (x15) and cropping intensity (x16) and has been renamed as Entrepreneurial diversity. It has contributed to 5.70 per cent alone and 67.85 per cent cumulatively to explain the variance. Factor 6 has accommodated the variables, family education (x7) and material possessed (x8) and has been renamed as Family innovation. It has contributed to 5.55 per cent alone and 73.41 per cent cumulatively to explain the variance.

188

Entrepreneurial Communication in Agriculture

Factor 7 has accommodated the variables, size of homestead land (x 10) no. of fragments (x13) and has been renamed as Holding distribution. It has contributed to 4.75 per cent alone and 78.16 per cent cumulatively to explain the variance. Factor 8 has accommodated the variables, size of cultivable land (x11) and has not been renamed because it consists of single variable. It has contributed to 4.21 per cent alone and 82.37 per cent cumulatively to explain the variance. Factor 9 has accommodated the variables, family labour (x21) and no. of male workers (x22) and has been renamed as Farm human resource. It has contributed to 3.47 per cent alone and 85.85 per cent cumulatively to explain the variance. Factor 10 has accommodated the variables, no. of female workers (x23) and has not been renamed because it consists of single variable. It has contributed to 3.24 per cent alone and 89.09 per cent cumulatively to explain the variance. Factor 11 has accommodated the variables, crop yield (x14) and has not been renamed because it consists of single variable. It has contributed to 3.15 per cent alone and 92.24 per cent cumulatively to explain the variance. 7.1.2.23: At last Matrix Ranking was done, which shows that enterprises like fruits, poultry and vegetables are in high demand in West Bengal.

7.1.3: Findings from the pooled villages of two states, Tripura and West Bengal are given below: 7.1.3.1: Coefficient of Correlation between Farm enterprise information from cosmopolite sources (y1) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) It has been found that the variables, training exposure (x5), material possessed (x8), crop yield (x14) and marketed surplus (x20), have recorded positive and significant correlation with the consequent variable Farm enterprise information from cosmopolite sources (y1). 7.1.3.2: Coefficient of Correlation between Farm enterprise information from localite sources (y2) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) It has been found that the variables, no. of fragments (x13) and livestock yield (x15), have recorded positive and significant correlation with the consequent variable, Farm enterprise information from localite sources (y2) and the variable,no. of female workers (x23), has recorded negative and significant correlation with the consequent variable, Farm enterprise information from localite sources (y2) 7.1.3.3: Coefficient of Correlation between Information seeking and responding behaviour (y3) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) It has been found that the variables, family education (x7), crop yield (x14), income (on farm & off farm) (x17) and no. of male workers (x22), have recorded positive

Summary and Epilogue

189

and significant correlation with the consequent variable, Information seeking and responding behaviour (y3). 7.1.3.4: Coefficient of Correlation between Entrepreneurial communication behaviour (y4) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) It has been found that the variables, size of homestead land (x10), no. of fragments (x13), income (on farm & off farm) (x17), marketable surplus (x19) and marketed surplus (x20), have recorded positive and significant correlation with the consequent variable, Entrepreneurial communication behaviour (y4) and the variables, family size (x6), family education (x7) and no. of female workers (x23), have recorded negative and significant correlation with the consequent variable, Entrepreneurial communication behaviour (y4). 7.1.3.5: Coefficient of Correlation between Value addition (y5) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) It has been found that the variables, age (x1), marketable surplus (x19) and no. of male workers (x22), have recorded positive and significant correlation with the consequent variable, Value addition (y5) and the variable, no. of enterprise (x3) has recorded negative and significant correlation with the consequent variable, Value addition (y5) 7.1.3.6: Coefficient of Correlation between Economical communication (y6) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) It has been found that the variables, education (x2), income (on farm & off farm) (x17) and family labour (x21), have recorded positive and significant correlation with the consequent variable, Economical communication (y6). 7.1.3.7: Coefficient of Correlation between Transportation cost (y7) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) It has been found that the variable, family education (x7), has recorded positive and significant correlation with the consequent variable, Transportation cost (y7). 7.1.3.8: Stepwise Regression analysis of Farm enterprise information from cosmopolite sources (y1) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Stepwise regression analysis, wherein the variable, no. of enterprise (x3), has been retained at the last step to elicit its determining and critical contribution to Farm enterprise information from cosmopolite sources (y1). The variable, no. of enterprise (x3), has explained 5.6 per cent of variance embedded with the consequent variable. 7.1.3.9: Stepwise Regression analysis of Farm enterprise information from localite sources (y2) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

190

Entrepreneurial Communication in Agriculture

The study reveals the Stepwise regression analysis, wherein the variable, no. of female workers (x23), has been retained at the last step to elicit its determining and critical contribution to Farm enterprise information from localite sources (y2). The variable, no. of female workers (x23), has explained 3 per cent of variance embedded with the consequent variable. 7.1.3.10: Stepwise Regression analysis of Information seeking and responding behavior (y3) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Stepwise regression analysis, wherein the variables, family education (x7) and no. of female workers (x23), have been retained at the last step to elicit their determining and critical contribution to Information seeking and responding behavior (y3). The variables, family education (x7) and no. of female workers (x23), have explained 6.5 per cent of variance embedded with the consequent variable. 7.1.3.11: Stepwise Regression analysis of Entrepreneurial communication behavior (y4) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Stepwise regression analysis, wherein the variable, no. of enterprise (x3), has been retained at the last step to elicit its determining and critical contribution to Entrepreneurial communication behavior (y4). The variable, no. of enterprise (x3), has explained 3 per cent of variance embedded with the consequent variable. 7.1.3.12: Stepwise Regression analysis of Value addition (y5) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Stepwise regression analysis, wherein the variables, no. of enterprise (x3), family education (x7), family expenditure (x18) and marketable surplus (x19), have been retained at the last step to elicit their determining and critical contribution to Value addition (y5). The variables, no. of enterprise (x3), family education (x7), family expenditure (x18) and marketable surplus (x19) have explained 4.9 per cent of variance embedded with the consequent variable. 7.1.3.13: Stepwise Regression analysis of Economical communication (y6) versus 23 Independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Stepwise regression analysis, wherein the variables, family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), income (on farm & off farm) (x17), family labour (x21,) and no. of female workers (x23), have been retained at the last step to elicit their determining and critical contribution to Economical communication (y6). The variables, family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), income (on farm & off farm) (x17), family labour (x21) and no. of female workers (x23), have explained 10.8 per cent of variance embedded with the consequent variable.

Summary and Epilogue

191

7.1.3.14: Stepwise Regression analysis of Transportation cost (y7) versus 23 independent variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Stepwise regression analysis, wherein the variables, age (x1), no. of enterprise (x3), year of enterprise (x4), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20), have been retained to elicit their determining and critical contribution to Transportation cost (y7). The variables, age (x1), no. of enterprise (x3), year of enterprise (x4), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20), have explained 18 per cent of variance embedded with the consequent variable. 7.1.3.15: Path analysis of Farm enterprise information from cosmopolite sources (y1) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from cosmopolite sources (y1) and the variable, size of holding (x9), has routed the highest indirect individual effect of as many as 13 times, to characterize Farm enterprise information from cosmopolite sources (y1). 7.1.3.16: Path analysis of Farm enterprise information from localite sources (y2) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Farm enterprise information from localite sources (y2) and the variable, size of holding (x9), has routed the highest indirect individual effect of as many as 11 times, to characterize Farm enterprise information from localite sources (y2) 7.1.3.17: Path analysis of Information seeking and responding behavior (y3) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Information seeking and responding behavior (y3) and the variable, size of holding (x9), has routed the highest indirect individual effect of as many as 10 times, to characterize Information seeking and responding behavior (y3). 7.1.3.18: Path analysis of Entrepreneurial communication behavior (y4) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal)

192

Entrepreneurial Communication in Agriculture

The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Entrepreneurial communication behavior (y4) and the variable, size of holding (x9), has routed the highest indirect individual effect of as many as 14 times, to characterize Entrepreneurial communication behavior (y4). 7.1.3.19: Path analysis of Value addition (y5) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of land under irrigation (x12), has recorded both the highest direct and indirect effect on the consequent variable, Value addition (y5) and the variable, size of cultivable land (x11), has routed the highest indirect individual effect of as many as 15 times, to characterize Value addition (y5). 7.1.3.20: Path analysis of Economical communication (y6) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of land under irrigation (x12), has recorded both the highest direct and indirect effect on the consequent variable, Economical communication (y6) and the variable, income (on farm & off farm) (x17) has routed the highest indirect individual effect of as many as 9 times, to characterize Economical communication (y6). 7.1.3.21: Path analysis of Transportation cost (y7) versus 23 exogenous variables (x1 to x23) of pooled villages of two states (Tripura and West Bengal) The study reveals the Path analysis by decomposing the total effect (r) into direct, indirect and residual effect. The variable, size of homestead land (x10), has recorded both the highest direct and indirect effect on the consequent variable, Transportation cost (y7) and the variable, no. of fragments (x13), has routed the highest indirect individual effect of as many as 11 times, to characterize Transportation cost (y7). 7.1.3.22: Factor Analysis by conglomeration of 30 variables {independent and dependent variables, (x1 to x23) and (y1 to x7)} of pooled villages of two states (Tripura and West Bengal) into 10 factors, based on factor loading and renaming of all the factors Factor 1 has accommodated the variables, family size (x6), family education (x7), livestock yield (x15), cropping intensity (x16), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21) and has been renamed as Family farm ecology. It has contributed 16.41 per cent to explain the variance. Factor 2 has accommodated the variables, size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12) and no. of fragments (x13) and has been renamed as Agro-ecology. It has contributed to 15.71 per cent alone and 32.12 per cent cumulatively to explain the variance.

Summary and Epilogue

193

Factor 3 has accommodated the variables, age (x1), education (x2), year of enterprise (x4) and training exposure (x5) and has been renamed as Capacity building. It has contributed to 9.14 per cent alone and 41.27 per cent cumulatively to explain the variance. Factor 4 has accommodated the variables, no. of enterprise (x3) and information seeking and responding behavior (y3) and has been renamed as Entrepreneurial communication. It has contributed to 4.78 per cent alone and 46.06 per cent cumulatively to explain the variance. Factor 5 has accommodated the variables, material possessed (x8) and size of homestead land (x10) and has been renamed as Home innovation. It has contributed to 4.60 per cent alone and 50.66 per cent cumulatively to explain the variance. Factor 6 has accommodated the variables, no. of female workers (x 23), farm enterprise information from localite sources (y2) and economical communication (y6) and has been renamed as Gender communication. It has contributed to 4.35 per cent alone and 55.02 per cent cumulatively to explain the variance. Factor 7 has accommodated the variables, farm enterprise information from cosmopolite sources (y1), information seeking and responding behavior (y3) and transportation cost (y7) and has been renamed as Strategic information. It has contributed to 4.24 per cent alone and 59.27 per cent cumulatively to explain the variance. Factor 8 has accommodated the variables, no. of male workers (x22) and has not been renamed because it consists of single variable. It has contributed to 4.24 per cent alone and 63.51 per cent cumulatively to explain the variance. Factor 9 has accommodated the variables, crop yield (x14) and has not been renamed because it consists of single variable. It has contributed to 4.16 per cent alone and 67.67 per cent cumulatively to explain the variance. Factor 10 has accommodated the variables, income (on farm & off farm) (x 17) and entrepreneurial communication behavior (y4) and has been renamed as Communication proficiency. It has contributed to 4.16 per cent alone and 71.83 per cent cumulatively to explain the variance.

7.1.4: Findings from the comparative study of two states, Tripura and West Bengal are given below: 7.1.4.1: Coefficient of Correlation (r) between Farm enterprise information from cosmopolite sources (y1) versus 23 Independent variables (x1 to x23): A comparative delineation: Tripura versus West Bengal The joint delineation of ‘r’ value implies that for Tripura, there are 17 positively significant variables and these are, age (x1), education (x2), year of enterprise (x4), material possessed (x8), size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15),

194

Entrepreneurial Communication in Agriculture

income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23) but there is no negatively significant variable and for West Bengal, there is no positively significant variable but there are 3 negatively significant variables and these are, cropping intensity (x16), family labour (x21) and no. of female workers (x23). The common variables between these two states are, family labour (x21) and no. of female workers (x23), when correlated with the dependent variable, Farm enterprise information from cosmopolite sources (y1). 7.1.4.2: Coefficient of Correlation between Farm enterprise information from localite sources (y2) versus 23 Independent variables (x1 to x23): A comparative delineation: Tripura versus West Bengal The joint delineation of ‘r’ value implies that for Tripura, there are 14 positively significant variables and these are, education (x2), no. of enterprise (x3), family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), crop yield (x14), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21) but there is no negatively significant variable and for West Bengal, there is only 1 positively significant variable and this is, size of homestead land (x10) but there are 4 negatively significant variables and these are, livestock yield (x15), family expenditure (x18), no. of male workers (x22) and no. of female workers (x23). The common variables between these two states are, livestock yield (x15) and family expenditure (x18), when correlated with the dependent variable, Farm enterprise information from localite sources (y2). 7.1.4.3: Coefficient of Correlation between Information seeking and responding behavior (y3) versus 23 Independent variables (x1 to x23): A comparative delineation: Tripura versus West Bengal The joint delineation of ‘r’ value implies that for Tripura, there are 20 positively significant variables and these are, age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23) but there is no negatively significant variable and for West Bengal, there are 8 positively significant variables and these are, material possessed (x8), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20), and there is only 1 negatively significant variable and this is, family size (x6). The common variables between these two states are material possessed (x8), no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed

Summary and Epilogue

195

surplus (x20), when correlated with the dependent variable, Information seeking and responding behavior (y3). 7.1.4.4: Coefficient of Correlation between Entrepreneurial communi-cation behavior (y4) versus 23 Independent variables (x1 to x23): A comparative delineation: Tripura versus West Bengal The joint delineation of ‘r’ value implies that for Tripura, there are 18 positively significant variables and these are, age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), crop yield (x14), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21) and there is only 1 negatively significant variable and this is, family education (x7) and for West Bengal, there is no positively significant variable but there are 4 negatively significant variables and these are, size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12) and income (on farm & off farm) (x17). The common variables between these two states are, size of holding (x9), size of cultivable land (x11), size of land under irrigation (x12) and income (on farm & off farm) (x17), when correlated with the dependent variable, Entrepreneurial communication behavior (y4). 7.1.4.5: Coefficient of Correlation between Value addition (y5) versus 23 Independent variables (x1 to x23): A comparative delineation: Tripura versus West Bengal The joint delineation of ‘r’ value implies that for Tripura, there are 18 positively significant variables and these are, age (x1), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20), family labour (x21), no. of male workers (x22) and no. of female workers (x23) but there is no negatively significant variable and for West Bengal, there are 6 positively significant variables and these are, age (x1), year of enterprise (x4), training exposure (x5), cropping intensity (x16), family labour (x21) and no. of female workers (x23) and only 1 negatively significant variable and this is, no. of male workers (x22). The common variables between these two states are, age (x1), year of enterprise (x4), training exposure (x5), family labour (x21), no. of male workers (x22) and no. of female workers (x23), when correlated with the dependent variable, Value addition (y5). 7.1.4.6: Coefficient of Correlation between Economical communication (y6) versus 23 Independent variables (x1 to x23): A comparative delineation: Tripura versus West Bengal The joint delineation of ‘r’ value implies that for Tripura, there are 17 positively significant variables and these are, age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), family size (x6), size of holding (x9), size of homestead land

196

Entrepreneurial Communication in Agriculture

(x10), size of cultivable land (x11), size of land under irrigation (x12), no. of fragments (x13), livestock yield (x15), cropping intensity (x16), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20) and family labour (x21) but there is no negatively significant variable and for West Bengal, there are 6 positively significant variables and these are, education (x2), no. of enterprise (x3), livestock yield (x15), income (on farm & off farm) (x17), marketable surplus (x19) and marketed surplus (x20) and 3 negatively significant variables and these are, age (x1), year of enterprise (x4) and training exposure (x5). The common variables between these two states are, age (x1), education (x2), no. of enterprise (x3), year of enterprise (x4), livestock yield (x15), income (on farm & off farm) (x17), marketable surplus (x19) and marketed surplus (x20), when correlated with the dependent variable, Economical communication (y6). 7.1.4.7: Coefficient of Correlation between Transportation cost (y7) versus 23 Independent variables (x1 to x23): A comparative delineation: Tripura versus West Bengal. The joint delineation of ‘r’ value implies that for Tripura, there are 13 positively significant variables and these are, age (x1), no. of enterprise (x3), year of enterprise (x4), training exposure (x5), family size (x6), family education (x7), material possessed (x8), no. of fragments (x13), livestock yield (x15), cropping intensity (x16), family labour (x21), no. of male workers (x22) and no. of female workers (x23) but there is no negatively significant variable and for West Bengal, there are 3 positively significant variables and these are, size of homestead land (x10), livestock yield (x15) and family labour (x21) and 3 negatively significant variables and these are, size of land under irrigation (x12), cropping intensity (x16) and income (on farm & off farm) (x17). The common variables between these two states are, livestock yield (x15), cropping intensity (x16) and family labour (x21), when correlated with the dependent variable, transportation cost (y7). 7.1.4.8: Stepwise Regression: Differential variable performance in Tripura and West Bengal of Farm enterprise information from cosmopolite sources (y1) versus 23 causal variables (x1 to x23) The comparative delineation between Tripura and West Bengal shows that, Farm enterprise information from cosmopolite sources (y1), has been uniquely contributed by 7 variables in Tripura and these are training exposure (x5), family size (x6), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), livestock yield (x15) and marketed surplus (x20). For the comparing state West Bengal, same dependent variable, Farm enterprise information from cosmopolite sources (y1), has been uniquely contributed by 2 variables and these are no. of enterprise (x3) and material possessed (x8) and it can be seen that none of the causal variables are found to be common between these two states. 7.1.4.9: Stepwise Regression: Differential variable performance in Tripura and West Bengal of Farm enterprise information from localite sources (y2) versus 23 causal variables (x1 to x23)

Summary and Epilogue

197

The comparative delineation between Tripura and West Bengal shows that, Farm enterprise information from localite sources (y2), has been uniquely contributed by 5 variables in Tripura and these are, age (x1), year of enterprise (x4), size of homestead land (x10), crop yield (x14) and no. of male workers (x22). For the comparing state West Bengal, same dependent variable, Farm enterprise information from localite sources (y2), has been uniquely contributed by 1 variable and this is, no. of female workers (x23) and it can be seen that none of the causal variables are found to be common between these two states. 7.1.4.10: Stepwise Regression: Differential variable performance in Tripura and West Bengal of Information seeking and responding behavior (y3) versus 23 causal variables (x1to x23) The comparative delineation between Tripura and West Bengal shows that, Information seeking and responding behavior (y3), has been uniquely contributed by 6 variables in Tripura and these are, material possessed (x8), size of holding (x9), size of homestead land (x10), size of cultivable land (x11), cropping intensity (x16) and no. of male workers (x22). For the comparing state West Bengal, same dependent variable, Information seeking and responding behavior (y3), has been uniquely contributed by 2 variables and these are, age (x1) and training exposure (x5) and it can be seen that none of the causal variables are found to be common between these two states. 7.1.4.11: Stepwise Regression: Differential variable performance in Tripura and West Bengal of Entrepreneurial communication behavior (y4) versus 23 causal variables (x1 to x23) The comparative delineation between Tripura and West Bengal shows that, Entrepreneurial communication behavior (y4), has been uniquely contributed by 3 variables in Tripura and these are, family education (x7), no. of male workers (x22) and no. of female workers (x23). For the comparing state West Bengal, same dependent variable, Entrepreneurial communication behavior (y4), has been uniquely contributed again by 3 variables and these are, size of land under irrigation (x12), no. of fragments (x13) and income (on farm & off farm) (x17) and it can be seen that none of the causal variables are found to be common between these two states. 7.1.4.12: Stepwise Regression: Differential variable performance in Tripura and West Bengal of Value addition (y5) versus 23 causal variables (x1 to x23) The comparative delineation between Tripura and West Bengal shows that, Value addition (y5), has been uniquely contributed by 2 variables in Tripura and these are, family size (x6) and crop yield (x14). For the comparing state West Bengal, same dependent variable, Value addition (y5), has been uniquely contributed again by 2 variables and these are, livestock yield (x15) and income (on farm & off farm) (x17) and it can be seen that none of the causal variables are found to be common between these two states. 7.1.4.13: Stepwise Regression: Differential variable performance in Tripura and West Bengal of Economical communication (y6) versus 23 causal variables (x1to x23)

198

Entrepreneurial Communication in Agriculture

The comparative delineation between Tripura and West Bengal shows that, Economical communication (y6), has been uniquely contributed by 3 variables in Tripura and these are, income (on farm & off farm) (x17), marketed surplus (x20) and no. of male workers (x22). For the comparing state West Bengal, same dependent variable, Economical communication (y6), has been uniquely contributed by 6 variables and these are, age (x1), education (x2), year of enterprise (x4), size of homestead land (x10), livestock yield (x15) and family labour (x21) and it can be seen that none of the causal variables are found to be common between these two states. 7.1.4.14: Stepwise Regression: Differential variable performance in Tripura and West Bengal of Transportation cost (y7) versus 23 causal variables (x1 to x23) The comparative delineation between Tripura and West Bengal shows that, Transportation cost (y7) has been uniquely contributed by 3 variables in Tripura and these are, age (x1), income (on farm & off farm) (x17) and no. of female workers (x23). For the comparing state West Bengal, same dependent variable, Transportation cost (y7), has been uniquely contributed by 4 variables and these are, age (x1), family size (x6), income (on farm & off farm) (x17) and family expenditure (x18) and it can be seen that 2 causal variables, namely age (x1) and income (on farm & off farm) (x17), are found to be common between these two states. 7.1.4.15: Comparative study of interacting variables of Tripura and West Bengal, identifying them into different factors and renaming them The study reveals that, the variables of Tripura are divided into 12 factors, whereas, variables of West Bengal are divided into 11 factors. Among 12 factors of Tripura, 6 factors have been renamed and they are, Family farming [family size (x6), family education (x7), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17) and family expenditure (x18)], Capacity and competency [training exposure (x5) and size of holding (x9)], Entrepreneurial chronology [age (x1) and year of enterprise (x4)], Social ecology [material possessed (x8), cropping intensity (x16) and no. of male workers (x22)], Agro-ecology [size of cultivable land (x11) and size of land under irrigation (x12)], and Marketability [marketable surplus (x19) and marketed surplus (x20)] and 6 factors have not been renamed because they contain only one variable each. Among 11 factors of West Bengal, 7 factors have been renamed and they are, Family entrepreneurship [family size (x6), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20)], Agro-ecosystem [size of holding (x9) and size of land under irrigation (x12)], Entrepreneurial behavior [age (x1), education (x2), year of enterprise (x4) and training exposure (x5)], Entrepreneurial diversity [livestock yield (x15) and cropping intensity (x16)], Family innovation [family education (x7) and material possessed (x8)], Holding distribution [size of homestead land (x10) and no. of fragments (x13)], Farm human resource [family labour (x21) and no. of male workers (x22)] and 4 factors have not been renamed because they contain only one variable each.

Summary and Epilogue

199

7.2: Conclusion A comparative analysis has been carried out to elucidate the level and nature of Entrepreneurial communication in the field of Agriculture and allied enterprises of two states, Tripura and West Bengal. 76 respondents from each of the states have been selected based on the 23 independent and 7 dependent variables as well as determinants. Respondents were selected for first 4 stages, viz., state, district, block and village, purposively and at the grass root stage, Systematic Random sampling procedure was carried out. Out of 23 variables, while comparing the respective social ecologies in operations and in different steps of multivariate analysis, some variables characterize the Entrepreneurial communication. Entrepreneurial communication has got both the structural and functional dimensions. The direction and dictum of Entrepreneurial communication are emanating from a unique Social-ecology in function. While one variable is extremely active in a social-ecology of Tripura, the same may not happen in West Bengal, and at the same time, some variables may act in common, both for Tripura and West Bengal. Some variables were found common, for example, no. of fragments (x13), crop yield (x14), livestock yield (x15), income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19), marketed surplus (x20),etc. for both Tripura and West Bengal as to characterize the entrepreneurial communication respectively. Some variables have been found negatively and significantly correlated to entrepreneurial communication for West Bengal and for other variables, it has been positively and significantly correlated for Tripura. Again, it has been found that the variables, cropping intensity (x16), family labour (x21) and no. of female workers (x23), have acted negatively but significantly in West Bengal, while the same operated positively for Tripura, so far as the character of farm enterprise information from cosmopolite sources (y1), is in concerned. This is simply because, entrepreneurial communication has been closely and organically orchestrated by the level of modernization, the technology socialization process and the market linked interactions. The respective states have had these in unique ways. The commercialization in agriculture runs at higher level in West Bengal than in Tripura. That is why, the home innovation in the form of material possessed (x8), no. of fragments (x13), crop yield (x14), are coming up as important determinants for entrepreneurial communication in Tripura, while, income (on farm & off farm) (x17), family expenditure (x18), marketable surplus (x19) and marketed surplus (x20) have become more discernible in West Bengal. Conclusively, it has been observed that in West Bengal, in the level of entrepreneurial growth in agriculture, after attaining a certain sustainable level, the symptoms of saturation has been developed. For Tripura, the process of entrepreneurial development is at its initial stage, more number of variables have been found positively and significantly correlated to determine the elevation of entrepreneurial communication. However, the study has got tremendous policy implication, a part of which is uniquely suitable for West Bengal, some other components are expected to match Tripura’s social ecology, while some others are suitable for both Tripura and West Bengal. 

Chapter

8

RECOMMENDATIONS AND LIMITATIONS OF THE RESEARCH 8.1: Recommendations Based on the empirical research, following recommendations can be made for the two states:

8.1.1: Tripura (i) In addition to agricultural enterprises, livestock enterprise, especially piggery, can play a pivotal role in Entrepreneurial communication and behavior. Social and cultural inhibitions, may be not that discernible, should be removed through highlighting the higher entrepreneurial possibilities in piggery. (ii) Participation of farm women in commercial agriculture, will give a fillip for ushering of Agricultural entrepreneurship in Tripura. So, gender oriented training and communication interventions will help in creation and building up of neo entrepreneurial behavior. (iii) Ethnic and geo-spatial characters of Tripura need to be considered while participatory enterprise communication will be executed. (iv) Transportation cost, since road communication network is not that much adequate, is high for Tripura in comparison to West Bengal. So, market linked communication can be an important intervention for agriculture in Tripura to grow and flourish. (v) Intensive training program on mobile telephony, community radio, using applications in smart phones, related to agricultural enterprises, can offer a great boost for ushering modern entrepreneurial behavior in enterprises for the domains of agriculture and allied sectors.

8.1.2: West Bengal (i) Land size based planning for business communication can help the growth and success of farm enterprise.

Recommendations and Limitations of the Research

201



(ii) Rice based farming system, supported by irrigation is offering a unique opportunity for capacity building of the farmers of West Bengal.



(iii) Off-farm income is simmering up like anything in West Bengal, so, a complex communication behavior, catering around both on-farm and off-farm entrepreneurship should be focused here in West Bengal.



(iv) Training, focusing on business communication, handling ICT tools and mobile telephony, can go a long way for making communication behavior more adaptive to present social ecology of agriculture and allied sectors of West Bengal.



(v) Social capitals like, Schools, Panchayats, Credit organizations, Market linked institutions, are to be integrated for shaping up a new form of Entrepreneurial communication behavior.

8.2: Limitations of the Research There is no research work in this world, which is without any limitation. This is also true for the present study. The most important limitations which have been observed in this research are as follows:

(i) Bench marking on the status of reigning of ‘Entrepreneurial communication’ has really been a difficult task.



(ii) There were problems of overlapping of some variables that could have been avoided.



(iii) Some new scales could have been better if created. Cardinality in measurements has spared.



(iv) Since, it is a very nascent idea, more of conceptual inputs could have been better, more time could have been devoted to generate crystal information.



(v) Some of the variables have gone bit homophile in nature. So, this has contributed a fair amount of multi-colinearity characters.



(vi) Since the concept is complex, it was very difficult to get qualitative response.



(vii) Nowadays, farmers have become very profession oriented and hesitate to interact and generate information without expectation. That created barriers sometimes to get relevant information unleashed of them. 

Chapter

9

BIBLIOGRAPHY Acharya, S K,L L Somani et al. (2015). Enterprise, Entrepreneurship and Agribusiness Management, Agrotech Publishing Academy, Udaypur, India. Acharya, S K, M M Adhikary (2013). Information Communication Technology in Agriculture: The Changing Global Order and Scale, Agrotech Publishing Academy, Udaypur, India. Agarwal, R. (1997). Innovations in entrepreneurship: major issues in new era of globalisation. Abhigyan. Vol (15), pp. 65-71. Akhouri, M.M. (1996). Conceptual background and rationale for entrepreneurship development training programmes. Paper presented in orientation course on entrepreneurship development in agriculture. December 17-31. IARI, New Delhi. pp.10. Ali, H. (1995). Gateways to market entry. The journal of entrepreneurship. Vol (4), No. (I), pp. 49-69. Atkinson, J.W., and Litwin, G.H. (1960). Achievement motive and test anxiety conceived motive to approach success and pp. 105-motive to avoid failure. Journal of abnormal and social psychology, Vol (60), No. (1), pp. 52-63. Banerjee, M., and Talukdar, R.K. (1997). Variables influencing entrepreneurship of women entrepreneurs. Indian Journal of Extension Education. Vol. (33), No. (1&2). Pp. 25-36. Bankston, C.L., and Zhou, M.Q. (1996). Go fish: The Louisianan Vietnamese and ethnic entrepreneurship in extra active industry. National Journal of Sociology. Vol (10), No (1), pp. 37-55. Barringer, B.R., and Bluedorn, A.C. (1999). The relationship between corporate entrepreneurship and strategic management. Strategic Management Journal, 20(5), 421–444. Basavanna, M. (1971). A study of self-confidence as an attitude of self-concept. Ph.D. Theses (Unpublished). Srivenkateswara University, Tirupati, Andhra Pradesh. Basu, S.K., and Moulik, T.K. (1971). Preference oriented selection criteria for rural entrepreneurs, identification and selection of small scale entrepreneurs. (Ed. Raod, T.V. and Moulik, T.K.). Indian Institute of Management, Ahmadabad, Gujarat.

Bibliography

203

Baul, J.R., Locke, E.A., and Smith, K.G., (2001). A multi-dimensional model of venture growth. Academy of Management Journal 44 (2), 292-303. Bell, T.M., and Pavitt, D.P. (1995). Psychological characteristics associated with performance in entrepreneurial firms and smaller businesses. Journal of Business Venturing 2, 7993. Bhagat, G.R., and Singh, Y.P. (1995). Effectiveness of entrepreneurial development training, on the knowledge level of farm entrepreneurs. Indian Journal of Extension Education. Vol. (31), No. (1-4), pp. 102-104. Bhatt, R.S., (1974). Growth of entrepreneurship in small and medium sectors. The Indian Journal of Public Administration. Vol (20), No. (3), pp. 453-465. Bhattacharjee, S.K., and Akhouri, M.M.P. (1975). Profile of small industry entrepreneurs. SEDME. Vol. (2), No. (1), pp. 73-85. Bhattacharya, S.N. (1983). Entrepreneurship development in India and the South-East Asian countries in agricultural and industrial sectors. Metropolitan book company, New Delhi. Bird, B., (1988). Implementing entrepreneurial ideas: the case for intention. Academy of Management Review 13, 442-453. Bisht, N.S., and Sharma, P.K. (1991). Entrepreneurship expectations and experience. Himalaya publishing house, New Delhi. Pp. 3-4. Bryant, C.R. (1989). Entrepreneurs in the rural environment. J. Rural Stud. 5(4), 337-347. Bull, I., and Willard, G.E. (1993). Towards a theory of entrepreneurship. Journal of Business Venturing. Vol. (8), pp: 183-195. Busenitz, L.L., (1996). Research on entrepreneurial alertness: Sampling measurement and theoretical issues. Journal of Small Business Management. Vol. (34), No. (4), pp. 35-44. Bygrave, W.D. (1994). Portable MBA in Entrepreneurship. John Wiley and Sons, New York. Calder, L.M., and Ross, F. (1976). Group organisation and leadership in rural life. Lucas Bros, Columbia, Missouri. Cantillon, R. (1955). International encyclopaedia of social sciences. Quoted by Cochran, T.C. (1968) under entrepreneurship. Mac Millan, New York. Vol. (5), pp. 88-90. Carland, J.W., (1984). Different entrepreneurs from small business owners. Academy of Management Review. Vol. (9), No. (2), 99. 354-359. Carton, R.B., Hofer, C.W., and Meeks, M.D. (1998). The entrepreneur and entrepre-neurship: operational definitions of their role in society. Singapore: Paper presented at the annual International Council for Small Business Conference. Carrier, C. (1996). Entrepreneurship in small Business: An exploratory study. Entrepreneurship Theory and Practice. Vol. (2), No. (1), pp. 5-20.

204

Entrepreneurial Communication in Agriculture

Cole, A.H. (1949). Entrepreneurship and entrepreneurial history. In change and the entrepreneur. Prepared by the research centre in entrepreneurial history. Harvard University Press, Cambridge. Cole, A.H. (1959). Business enterprise in it social setting. Harvard University Press, Cambridge. Cole, A.H. (1968). Meso-economics: A contribution from entrepreneurial history. Explorations in Entrepreneurial History. Vol. (6), No. (1), 99. 78-86. Collins, J.C., Porras, J.I. (1996). Building your company’s vision. Harvard Business Review, 65 77 (September-October). Covin, J.G., and Slevin, D.P. (1991). A conceptual model of entrepreneurship as firm behaviour. Entrepreneurship Theory and Practice. Vol (16), No. (1), pp. 7-25. Darling, J.R, and Beebe, S.A. (2007). Management in the company. ISSN 1941-899X, Vol. 3, No. 1: E2. David, N.K. (1962). A study of factors associated with low level of adoption of improved agricultural practices. Ph.D. thesis, Division of agricultural extension, IARI, New Delhi. De, D. (1985). Status symbol and innovative entrepreneurship are predictors of far-mers progressiveness. Journal of Extension System. Vol. (1), No. (1), pp. 81-84. De, D. (1986). Factors affecting entrepreneur characteristics of farmers. Indian Journal of Social Work. Vol. (XLVI), No. (4), pp. 541-546. De, D., and Rao, M.S. (2001). Entrepreneurial behaviour of farmers: An Axiomatic theory, Ganga Kaveri Publishing House, D.35/77 Jangamwadimath, Varanasi. De, Kalyan. (1981). Economic Reforms and Resource Management. Chanakya Publications, Delhi, p.102. Diamond, A. (1957). Indian Business Management. Deptt. of Business Management and Industrial Relations, University of Delhi. Pp. 50. Downing, J. (1991). Gender and growth of enterprise. Small Enterprise Development. Vol. (2), No. (1), pp. 4-12. Drucker, F.P. (1985). Innovation and Entrepreneurship – Practice and Principles. Heinemann, London, pp. 31. East West Centre, (1977). Entrepreneurial discovery and development progress of action research. East-West technology and development institute, Honolulu, Hawai, pp. 82-83. Eileen, Fischer., and A, Rebecca, Reuber. (2014). Journal of Business Venturing. Volume 29, Issue 4, July 2014, Pages 565-583. Encyclopaedia Britannica. (1943-1973). Inc. Benton, W. Publishers. Encyclopaedia of social sciences. (1933). Mc Millan Company, New York. Vol. (20), pp. 76-77.

Bibliography

205

English, H.B., and English, A. (1958). A comprehensive dictionary of psychological and psychoanalytical terms. Longmans. Green and Company, New York. Fishbein, M., (1965). Attitude and the prediction of behaviour. In Fishbein, M. (Ed.), Readings in attitude theory and measurement. John Wiley and Sons, New York. Pp. 477-492. Fisher, D.A. (1982). The myopia of learning. Strategic Management Journal 14, 95-112 (Special Issue). Fraser, T.M. (1961). Achievement motivation as a factor in rural development, a report on research in Western Orissa. Haverford College, Haverford, Paris. Freddy, J., and Nager. (2017). Communication Strategies of Women Leaders in Entre-preneurship. Procedia - Social and Behavioral Sciences, Volume 118, Pages 21-28. Gaikwad, V.R. (1978). Entrepreneurship: The concept and social context in developing entrepreneurship. A handbook of Rao, T.V. and Pareek, U. in collaboration with Deshpande, M. V. Mehta, P. and Nadkarni, M.S. Learning Systems, New Delhi. Gartner, W.B., Bird, B.J., and Starr, J.A. (1992). Acting as id Differentiating entrepreneurial from organisation behaviour. Entrepreneurship theory and practice. Vol. 16 (3), pp. 13-31. Ghemawat, P. (1991). Commitment: the Dynamics of Strategy. Free Press, New York. Gopakumar, K. (1995). Entrepreneurship in economic thought: a thematic review. Journal of entrepreneurship, 4 (1), pp. 1-17. Gupta, C.B., and Srinivasan, N.P. (1992). Entrepreneurial development: Second edi-tion. Sultanchand and sons educational publishers, New Delhi. Gupta. C.B., and Khanka, S.S., (2000). Entrepreneurship and small Business manage-ment, Sultanchand and sons, N.Delhi, p.123 and 124. Hamel, G., Prahalad, C.K., (1989). Strategic intent. Harvard Business Review 67 (3), 63-76. Hagen, G.C. (1962). The relevance of psychology to the explanation of social phenomena. Borger, R., Cioffi, F. (Ed.). Explanation in the behavioural sciences. Cambridge University Press, Cambridge, pp. 313-326. Harbison, F.N., and Hyers, C.A. (1964). Education manpower and economic growth. In Nodder, B.W. (Eds.). Economic development in the topics, Methuen, London. Haredero, J.M. (1979). Agricultural entrepreneurship. Identification and selection of small scale entrepreneurs. (Ed. Rao, T.V. and Moulik, T.K.). Indian Institute if Management, Ahmedabad, pp. 151-159. Hari, R., and Mahesh, C. (2014). Credit, risk and market orientations of the rural farming youth of Uttar Pradesh and Rajasthan. International-Research-Journal-of-Agricultural-Economics-andStatistics. 5(2): 262-265.

206

Entrepreneurial Communication in Agriculture

Harper, M., and Vyakaranam, S. (1988). Rural enterprise: Case studies for developing countries. Intermediate technology publications, London. Hegan. (1968). The economics of development. Irwin, RD Inc. Illinois, New York. Himachalam, A. (1990). Developing entrepreneurial industrialist- an alternate approach. Productivity. Vol. 34 (2), pp. 281-287. Hornaday, J.A., and Aboud, J. (1971). Characteristics of successful entrepreneurs. Personal psychology. Vol. (14), No. (6), pp. 66-78. Hoselitz, B.F. (1957). Non-economic factors in economic development in Tandoil, B.C. (Eds.). Environmental and entrepreneur. Cheigh publications, Allahabad, India. Hundal, P.S., and Singh, S. (1975). Structure of personality characteristics and motive pattern of farmers. Indian Journal of Psychology. Vol. (50), No. (1), pp. 33-43. IFAC Proceeding. (2012). Volume 45, Issue 10, Pages 50-55. Ireland, R.D., Hitt, M.A., Camp, L., and Sexton, D.L, (2001). Integrating entre-preneurship and strategic management actions to create firm wealth. Academy of Management Executive 15 (1), 49-63. Javillionar, W., and Peters, D.G. (1973). The Complete Entrepreneur. Entrepreneur-ship Theory and Practice 13, 9-19. Jha, T.M., and Shiyani, G.E., (1995). Entrepreneurship and new firm development: a definitional introduction. Journal of Business Research 36 (1), 1-5. Jhamtani, A. (1996). Dynamics of entrepreneurship. Orientation course on entrepre-neurship development in agriculture. December 17-31, IARI, New Delhi, pp. 5-6. Jones, S. and Cohen, M.B. (1990). The emerging business. Ronald Press, New York. Joshi, S.S., and Kapur, T.R. (1973). Fundamentals of farm business management. Kalyani publishers, New Delhi. Jyothi, V. (1990). Entrepreneurship development among women – study of entrepre-neurs in Guntur district. M. Phil. Dissertation submitted to Nagarjuna University. Guntur, Andhra Pradesh. Jyothi, V., and Prasad, G. (1993). A profile of potential rural women entrepreneurs. Small enterprises development management and extension Journal (SEDME). Vol. (20), No. (1), pp. 23-38. Kanungo, R.N., and Bhatnagar, J. (1978). Achievement orientation and occupational values: A comparative study of young French and English Canadians. Canadian Journal of Behavioural Sciences. Vol. (10), No. (3), pp. 202-213. Kanungo, R.N., and Conger, J.A. (1995). Model orientation in leadership research and their implications for developing countries. New approaches to employee management. Vol (3), pp. 155-170. Kanungo, R.N., and Mendonca, M. (1994). Fundamentals of organisational beha-viour. Kendall Hunt publishing company, Iowa.

Bibliography

207

Keshari, P.K., and Kota, R. (1995). Determinants of the propensity to export: the case of small firms in the diesel engine and chemical industries in Gujarat. The Journal of entrepreneurship. Vol. (4), No. (1), pp. 35-48. Khanka, S.S. (1998). Making the entrepreneurial society. Yojana. Vol. (42), No. (2), pp. 9-11. Kilby, P. (1971). Entrepreneurship and economic development. Free press, New York. Kirzner, I.M. (1973). Competition and Entrepreneurship, University of Chicago Press, Chicago. Kirzner, I.M. (1979). Perception, opportunity and profit: studies in the theory of entrepreneurship. The University Chicago Press, Chicago. Knudson, W., Wysocki, A., Champagne, J., and H. Christopher, Peterson. (2004). Entrepreneurship and innovation in the Agri-food system, Amer. Journal of Agricultural Economics. 86: 1330-1336. Kodithuwakku, S.S., and Rosa, P. (2002). The entrepreneurial process and economic success in a constrained environment. Journal of Business Venturing 17 (2002): 431-465. Kogan, N., and Wallach, M.A. (1964). Risk taking. A study in cognition and personality. Holt, Rinehart and Winston, New York. Koontz, H. (994). Essentials of management. (I edition). Mc Graw Hill publishing company, New York, pp. 39. Kourilsky, M. (1980). Predictors of entrepreneurship in stimulated economy. Journal of creative behaviour: Vol. (14), No. 3, pp. 76-86. Krishnan, and Kumar, K.G. (1998). Management skills for rural enterprises. Entrepre-neurship innovation. Edited by Kanungo, R.N. Sage publications, New Delhi, pp. 338-357. Kumar, E.S. (1998). Theorizing in entrepreneurship: A review, critique and future directions. Entrepreneurship innovation. Edited by Kanungo, R.N., Sage publications, New Delhi, pp. 90-115. Kumar, G.K. (1995). The entrepreneur in economic thought: a thematic overview. The Journal of entrepreneurship. Vol (4), No. (1), pp. 1-15. Kuratko, D.F. (2009). Entrepreneurship, theory, process and practice. (pp. 1–22). Nashville: South Western Publication. Learned, K.E. (1992). What Happened Before the Organisation? A Model of Orga-nisation Formation. Entrepreneurship Theory and Practice 17 39-48. Leeds, C.N., and Stainton, R.S. (1978). Management and business studies (second edition). Macdonald and Evans. Legans, J.P., (1961). The future of entrepreneurial research. Explorations in entrepreneurial history. Second series, Vol (1), pp. 3-9. Lumpkin, G.T., and Dess, G. (1996). Clarifying the entrepreneurial orientation construct and linking it to performance. Academy of Management Review 21 (1), 135-173.

208

Entrepreneurial Communication in Agriculture

Ma, Hao., and Tan, Justin. (2006). Key components and implications of entrepre-neurship: A 4-P framework. Journal of Business Venturing. 21:704-725. Mall, C.P. (1993). Impact of financial incentives on entrepreneurial development in backward regions: A case study of Deoria district of U.P. The Journal of entrepreneurship.Vol. (2), No. (2), pp. 199-207. Manjula, S. (1995). A study of entrepreneurial behaviour of rural women in Ranga Reddy district of Andhra Pradesh. M. Sc. (Home Science). Thesis, ANGRAU, Rajendra Nagar, Hyderabad Manimala, M.J. (1998). Net working for innovation: Anecdotal evidences from a large sample study of innovative enterprises. The Journal of entrepreneurship.Vol. (7), No. (2), pp. 153-169. Manimekalai, N., and Abdullah, M. (1998). Charcoal production and rural entrepre-neurship development. The Indian economic Journal. Vol. (45), No. (2), pp. 159-169. Massie, J.L. (1982). Essentials of Management (Third edition). Prentice Hall of India pvt. Limited, New Delhi. Mc clelland, D.C. (1961). Motivating economic achievement. Free Press, New York. Mc clelland, D.C. (1965). Need achievement and entrepreneurship: a longitudinal study. Journal of personality and social psychology. Vol. (1), pp. 389-392. Mc clelland, D.C. (1969). Motivating economic achievement. Free Press, New York. Mc Grath, RG., and MacMillan, I.C. (2000). The Entrepreneurial Mind-set: Strategies for Continuously Creating Opportunities in the Age of Uncertainty. Harvard Business School Press, Boston, MA. M.C., Gupta. (1987). Entrepreneurships and small scale Industries. Anmol Publica-tions, New Delhi, First Edition. Morky, B.W. (1988). Entrepreneurship and public policy. Quorum books, New York. Morris, M.H., and Lewis, P.S. (1995). The determinants of entrepreneurial activity: implications for marketing. European Journal of Marketing 29 (7), 31-49. Morris, M.H., and Sexton, D.L. (1996). The concept of entrepreneurial intensity: implications for company performance. Journal of Business Research 36 (1), 5-13. Murry, D. (1938). Environment – strategy coevolution and coalignment: a staged model of Chinese SOEs under transition. Strategic Management Journal 26 (2), 141-157. Nandi, A. (1973). Motives, modernity and entrepreneurial competence. Journal of social psychology. Vol. (91), No. (3), pp. 127-136. Narendra, P., and Sharma,V.P. (2007). Enterpreneurial behaviour of the poultry farmers. Journal of Research ANGRAU. 35(3): 45-50. Neill, R.E., and Rogers, E.M. (1963). Measuring achievement motivation among farmers. Department series A.E. 3446. Ohio Agricul. Expt. Stn. Columbus.

Bibliography

209

Newman, Amy., and Scott, Ober. (2013). Business Communication: In Person, In Print, Online, 8e. 8th ed. Mason: South-Western, 2013. 18. Print. Olajide, B.R. (2011). Assessment of farmers' access to agricultural information on selected food crops in Iddo District of Oyo State, Nigeria. Journal-of-Agricultural-and-Food-Information.12(3/4):354-363. Pajarinen, M., Rouvinen, P., and Ylä-Anttila, P. (2006). Uusyrittä jien kasvuha-kuisuus, KTM julkaisuja. Helsinki: Ministry of Employment and the Economy. Palmer, B.I., and Ahiamadu, R.K. (1997). Leadership style and performance of public enterprises. A Nigerian study. Productivity. Vol. (38), No. (1), pp. 54-64. Pareek, U., and Nandkarni, M. (1978). Development of entrepreneurship. A concept-tual model. In Rao, T.V and Pareek, U. (Eds.), Developing entrepreneurship: A hand book, learning systems, New Delhi. Pareek, U., and Rao, T.V. (1995). Counselling and helping entrepreneurs. The Journal of entrepreneurship.Vol. (4), No. (1), pp. 19-34. Parsons, P., and Shills, S.J. (1951). Broadening the concept of marketing. Journal of marketing. Vol. (16), No. (8), pp. 63-64. Patel, D.R. (1995). Entrepreneurship and small business development for women. Kurukshetra, Vol. XLIII, No. (11), pp. 65-68. Patel, M.M., and Sanoria, Y.C. (1997). Correlates of entrepreneurial behaviour of sugarcane growers. Maharashtra J Extn. Edn. Vol. (16), pp. 344-346. Paul, K.C. (1998). A study on entrepreneurial behaviour of vegetable growers in Krishna district of Andhra Pradesh. M.Sc. (Ag.) thesis, ANGRAU, Rajendra Nagar, Hyderabad. Polo, P., and Frias, J. (2010). The relationship between business characteristics and ICT deployment in the rural tourism sector. The case of Spain. International-Journal-of-Tourism-Research. 12(1): 34-48. Pollo, L.V. (1996). On economic theory of entrepreneurship: The strategic role of the entrepreneurial function. International review of sociology. Vol. (6), No. (2), pp 191-213. Prakasam, D.S. (1998). Entrepreneur: An important change agent in every society. Kurukshetra. Vol. (46), No. (10), pp. 51-52. Prasad, R.M. (1983). Comparative analysis of achievement motivation of rice growers in three states in India. Ph.D. thesis (unpublished), U.A.S., Bangalore. Prasad, S.K. (1996). Promoting an entrepreneurship development programme. Laghu Udyog. Vol. (21), No. (2), pp. 3-5. Prashad, Awadesh. (1988). Entrepreneurship development under TRYSEM. Concept Publicity Company, New Delhi. Ramakrishnan, K. (1979). Interview techniques as a method of selection in identification and selection of small entrepreneurs (Eds. Rao, T.V. and Moulik, T.K.). Indian Institute of Management, Ahmadabad.

210

Entrepreneurial Communication in Agriculture

Ramana, A.V. (1999). Entrepreneurship and economic development. Kurukshetra. Vol. (48), No. (2), pp. (8 to 10 & 45). Ramana, A.V., and Papaiah, R. (1998). Nuances of entrepreneurship development. Indian management.Vol. (37), No. (2), pp. 48-53. Rani, C. (1986). Potential women entrepreneurs - A study. SEDME.Vol. (13), No. (3), pp. 13-32. Rao, G.K.V. (1985). A prediction analysis of farming performance of farmers through their entrepreneurial behavior factors. Ph.D. thesis, A.P.A.U. Rajendra Nagar, Hyderabad. Rao, T.V. (1975). Characteristics of entrepreneurs as perceived by entrepreneurial development agents. Paper presented at the work shop on identification and selection for entrepreneur. Indian Institute of Management, Ahmadabad. Rao, T.V., and Mehta, P. (1978). Psychological factors in entrepreneurship. In Rao, T.V. and Pareek, U. (Eds.). Developing entrepreneurship. A hand book of Learning systems, New Delhi. Rao, T.V.S. (1989). A study on entrepreneurial characteristics of vegetable growers in Guntur district of Andhra Pradesh. Unpublished M. Sc. (Ag.) thesis, A.P.A.U., Rajendra Nagar, Hyderabad. Ray, S., and Ramachandran, K. (1996). Towards a frame work for a comprehensive theory of entrepreneurship. The Journal of entrepreneurship.Vol. (5), No. (1), pp. 1-22. Richart, C.B., and Maurer, J.G. (1997). The moderating effect of environmental varia-bles on the entrepreneurial and marketing orientation on entrepreneur led firms. Entrepreneurship Theory and Practice. Vol. (22), No. (1), pp. 47-58. Ricky, W.G. (1992). Essentials of management. Prentice Hall of India Pvt. Ltd., New Delhi, pp. 22-24. Ripsas, S. (1998). Towards an interdisciplinary theory of entrepreneurship. Small business economics. Vol. (10), No. (2), pp. 103-115. Robbins, J.C. (1996). A resource mobilisation theory and the study of social move-ments. Annual review of sociology. Vol. (9), pp. 527-533. Rogers, F.M., and Neill, R.E. (1966). Achievement motivation among Columbian peasants. Michigan state University, East I Lansing, Michigan. Rogers, E.M., and Shoemaker, F.F. (1971). Communications of innovations, A cross cultural approach. The Free Press, A division of Macmillan publication company, Inc. New York. Rogers, E.M., and Svenning, L. (1969). Modernization among peasants: The impact of communication. Hort, Rinehart and Winston, New York. Rousmasset, J.A. (1977). Risk and uncertainty in agricultural development. Seminar report No. 15. Agricultural Development Council, New York. Sara, C. (1998). Portfolio entrepreneurship in the farm sector: Indigenous growth in rural areas. Entrepreneurship and regional development. Vol. (10), No. (1), pp. 17-32.

Bibliography

211

Saylor, M. (1987). Home-based enterprise development and craft marketing. Proceedings of International Rural Entrepreneurship Symposium. Economic Research Service, USDA, Knoxville, Tennessee, pp 57-70. Schumpter, J.A. (1934). The Theory of Economic Development. Harvard University Press, p. 42. Schumpter, J.A. (1961). The theory of economic development: An enquiry into profits, capital, interest and business cycle. Cambridge Harward University Press, Cambridge. Schumpeter, J.A. (1970). The Theory of Economic Development. Harvard University Press, Cambridge, MA. Schumpter, J.A. (1970). The entrepreneur as innovator. Reading in management (second edition). Mc Graw Hill, New York. Schwartz, E.A. (1979). Entrepreneurship: New female frontier. Journal of Contemporary business. winter issue. Vol. (15), pp. 150-163. Scott, M. (1997). Reengineering the rapidly growing entrepreneurial company. Industrial management.Vol. (39), No. (3), pp. 21-23. Senarathna, R.P., and Wickramasuriya, H.V.A (2011). Organizational factors affecting e-commerce adoption in small and medium-sized enterprises. Tropical-Agricultural-Research. 22(2): 204-210. Sexton, D. L., and Bowman, Upton, N. (1991). Entrepreneurship, Creativity and Growth. MacMillan, New York. Shailendra, V. (1990). When the harvest is in developing rural entrepreneurship. Oxford and IBH publishing Co. Pvt. Ltd. New Delhi. Shane, S., and Venkataraman, S., (2006). The promise of entrepreneurship as a field of research. Academy of Management Review 25 (1), 217-226. Schwartz, S.A. (1979). Are champions different from non-champions? Journal of Business Venturing 9, 397-421. Sharma, S.V.S. (1980). Characteristics of entrepreneurs. In developing entrepreneur-rship: Issue and problems. SIET (Small Industry Extension Training). Institute, Hyderabad. Shaver, P., and Scott, M. (1991). Reengineering the rapidly growing entrepreneurial company. Industrial management. Vol. (39), No. (3), pp. 21-23. Singh, D.N. (1970). Developing entrepreneurship for economic development. Vikas Publishing House Pvt. Ltd., New Delhi, pp. 83-92. Singh, K. (1992). Women entrepreneurs. Ashish publishing house, New Delhi. Singh, N.P., and Singh, K. (1971). Motivational components of agricultural and busi-ness entrepreneurs in India. Indian Journal of Industrial relations. Vol. (7), No. (1), pp. 31-52. Singh, P. N. (1986). Factors influencing entrepreneurship. Developing entrepreneur-ship for economic development. Vikas Publishing House Pvt. Ltd., New Delhi, pp. 46-92.

212

Entrepreneurial Communication in Agriculture

Singh, R.N., and Pal, S. (1974). Managerial resourcefulness: A Re-conceptualisation of managerial skills, Human Relations, 45(12), 1311-32. Singh, S. (1970). Motives, Personality characteristics and work values of fast and slow progressing farmers. Behavioural science and rural development. Vol. (2), No. (2), pp. 71-77. Singh, S. (1978). Achievement motivation, decision making orientation and work values of fast and slow progressing farmers in India. The Journal of social psychology. Vol. (106), pp. 153-160. Singh, T.N. (1979). Human factors in entrepreneurship effectiveness. The Journal of entrepreneurship. Vol. (5), No. (1), pp. 23-39. Singh, T.P., and Kumar, K. (1975). Achievement motivation, socio-economic status and green revolution. Indian Journal of Extension Education. Vol. (1.1), No. (10), pp. 1-7. Sinha, E.T. (1996). The Theory of the Growth of the Firm. Oxford: Basil Blackwell. Sinha, Satish., and Mehta, S.L. (1972). Entrepreneurial Development. A New Venture creation. Sisodia, G.S. (1976). A study of the achievement motivation of farmers for mecha-nization. Indian Journal of Extension Education. Vol. (13), No. (3&4), pp. 72-75. Stevenson, H.H., and Jarillo, I.C. (1990). A paradigm of entrepreneurship: entrepre-neurial management. Strategic management Journal, 10th summer special issue. Vol. (11), pp. 17-27. Stoner, D., and Ma, H., (1996). Organisational resilience: extraordinary performance in hostile environments. Paper presented at the 16th Strategic Management Society Conference at Phoenix, Arizona. Sundari, S.S.K. (1995). Entrepreneurship development for rural women. SDEM. Vol. (1). pp. 15-30. Swamy, B.A. (1988). Agricultural entrepreneurship in India. Ph.D. Thesis, Andhra University, Waltair, Andhra Pradesh. Thomas, T.T., and Padmakar, K. (1993). Developing entrepreneurial industrialists. An alternative approach. Productivity. Vol. (34), No. (2), pp. 281-2876. Vasant, Desai. (1999). Entrepreneurship and Technology. Himalaya Publishing House, Mumbai, first edition. Tripathi, D. (1985). An integrated view of entrepreneurship. Economic and political weekly review of management. Vol. (20), No. (48), pp. 62-69. Administrative science. Vol. (31), No. (3), pp. 439-465. Tushman, N., and Anderson, P. (1986). The Five Ages of the Entrepreneur. Venture. 40-42. Venkataraman, S. (2000). The distinctive domain of entrepreneurship research: an editor’s perspective. In: Katz, J., Brockhaus, R. (Eds), Advances in Entrepreneurship, Firm Emergence, and Growth, vol 3. JAI Press, Greenwich, CT, pp. 119-138. Vemze, M.D. (1987). Women entrepreneurs in India. Mittal publications, New Delhi.

Bibliography

213

Vijaya, V., and Kamalanabhan, T.J. (1998). A scale to assess entrepreneurial moti-vation. The journal of entrepreneurship. Vol. (7), No. (2), pp. 183-198. W.C., Kim., and R. Mauborgne. (2005). Blue Ocean Strategy: How to Create Uncontested Market Space and Make Competition Irrelevant. Boston, MA, USA : Harvard Business Press. Weber, M. (1930). Entrepreneurship and economic development. The Free Press, New York. Wharton, J.B. (1966). A catechism on political economy (trans. By Jojn, Richter). New York: Augustus. M. Kelly. Wick, J.H. (1998). Understanding entrepreneurial intentions: The attitudinal determinants. Entrepreneurship and innovation. Edited by Kanungo, R.N. sage publications, New Delhi, pp. 119-138. Yadav, D.S, Chahal, V.P, Arvind, K., and Ummed, S. (2014). Entrepreneurial behaviour and constraints encountered by farm women in dairy enterprise. Indian Journal of Animal Sciences. 84(10): 1127-1132. Zahir, M.A. (1994). Entrepreneurship in Punjab. A case study. Yojana. Vol. (38), No. (8), pp. 24-28. 