Supply Chain Sustainability: Modeling and Innovative Research Frameworks 9783110628593, 9783110625561

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Sachin Kumar Mangla and Mangey Ram (Eds.) Supply Chain Sustainability

De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences

Edited by Mangey Ram

Volume 2

Supply Chain Sustainability Modeling and Innovative Research Frameworks Edited by Sachin Kumar Mangla and Mangey Ram

Editors Sachin Kumar Mangla University of Plymouth Plymouth Business School Mast House Room 102 Sutton Road PL4 8AA Plymouth, United Kingdom [email protected] Mangey Ram Graphic Era Deemed to be University Department of Computer Science and Engineering 566/6 Bell Road 248002 Clement Town, Dehradun, Uttarakhand, India [email protected]

ISBN 978-3-11-062556-1 e-ISBN (PDF) 978-3-11-062859-3 e-ISBN (EPUB) 978-3-11-062568-4 ISSN 2626-5427 Library of Congress Control Number: 2020948009 Bibliographic information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available on the Internet at http://dnb.dnb.de. © 2021 Walter de Gruyter GmbH, Berlin/Boston Cover image: MF3d/E+/Getty Images Typesetting: Integra Software Services Pvt. Ltd. Printing and binding: CPI books GmbH, Leck www.degruyter.com

Acknowledgment The editors acknowledge Walter de Gruyter and the editorial team for their adequate and professional support during the preparation of this book. Also, we would like to acknowledge all the chapter authors and the reviewers for their availability on this book project. Sachin Kumar Mangla University of Plymouth, United Kingdom Mangey Ram Graphic Era Deemed to be University, India

https://doi.org/10.1515/9783110628593-202

Preface Sustainability helps industries to improve their ecological, monetary, and societal performances of their supply chains. The acceptance of sustainability is relatively difficult from the supply chain contexts. In this sense, development of innovative research frameworks and modeling of issues linked to sustainability are significant in supply chains. The topics covered in this book are organized as follows: Chapter 1 deals with the supplier selection problem of a farming machinery manufacturing company in Turkey, and a Mamdani-type fuzzy inference system has been used to solve this problem. Chapter 2 provides a review of green and sustainable freight transport practices and analyzes the scientific mapping of green and sustainable freight transport practices by using bibliometric and network analysis. Chapter 3 discusses the different treatment to reduce the problem of urban expansion and to maintain the urban sustainability of the region. Chapter 4 covers the three sustainable logistics performance key criteria, namely, sustainable procurement, sustainable distribution, and reverse logistics. Fuzzy analytic hierarchy process is used to find the weights of these criteria and the overall operational performance score is found by the weighted scoring method. Chapter 5 discusses the service designing in heritage tourism through fuzzy Kano analysis. This study would be useful for the destination marketing organizations, tourism policymakers, tourism managers to critically analyze the factors responsible for bringing the changes in tourist experiences while visiting a place. Chapter 6 explores the case study of Food and Civil Supplies Department of Uttar Pradesh and suggests what technological solutions are required in implementing green initiatives. Chapter 7 demonstrates an idea of sustainable consumption and how it has been conceptualized and theorized over a period of time. This chapter will be helpful for policy makers in promoting sustainable consumption practice. Chapter 8 explains the sustainability marketing activities in marinas and determines the role of environmental policies in achieving sustainable competitive advantage. The study of this chapter reveals the degree of effectiveness of sustainability marketing activities based on marina certifications and classifications for different types of marinas. Chapter 9 describes the utility of agricultural wastes and proposed that the biomass briquetting plant processes biomass and makes it in cylindrical briquettes which could be a replacement of coal. Chapter 10 explores the use of Internet of Things (IOT) technology in the supply chain management that is specific to perishable food items. This chapter mainly focuses on the implementation of IOT to manufacturing systems.

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The book seeks to explore the contributions made by researchers and practitioners in the domain of sustainability of supply chains for different stakeholder’s perspectives. Also, guide practitioners in developing novel mathematical decision models and original frameworks for effective implementation of supply chain sustainability. This book surely helps industries to understand concepts related to sustainability issues and their implementation in supply chains. Sachin Kumar Mangla University of Plymouth, United Kingdom Mangey Ram Graphic Era Deemed to be University, India

About the editors Dr. Sachin Kumar Mangla is working in the field of green SC/sustainability/Industry 4.0/circular economy/risk management/energy/decision making and modeling. He is committed to do and promote high-quality research. He is working as a senior lecturer of knowledge management and business decision making in University of Plymouth, United Kingdom. Dr. Mangla has more than 5 years of teaching experience in supply chain and operations management and decision making. He has published/presented several papers in reputed international/national journals (RSER, TRE-D, JCP, PPC, IJPR, IJPE, ANOR, ISF, BiJ, RCR, IJLRA, IJQRM, IDMS, IJOR) and conferences (POMS, SOMS, IIIE, CILT – LRN, GLOGIFT). He has h-index 26, i10-index 44, and Google Scholar Citations of more than 2000. He is involved in editing a special issue as a guest editor in production planning and control: The Management of Operations, and Resources, Recycling and Conservation, Annals of Operations Research, Journal of Resource Policy, and Journal of Cleaner Production on various issues of “Industry 4 and Circular Economy,” “Green and Sustainable Supply Chains Performance Improvement,” “Food Supply Chains,” and “Industry 4.0, Cleaner Production, Circular Economy and Ethical Business Development.” Currently, he is also responsible for knowledge-based decision model in “enhancing and implementing knowledge-based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems (RUC-APS),” European Commission RISE scheme, €1.3M. Recently, he has received a grant as a PI from British Council – Newton Fund Research Environment Links Turkey/UK – developing capacity and research network on circular and Industry 4.0-driven sustainable solutions for reducing food waste in supply chains in Turkey. Dr. Mangey Ram received his Ph.D. major in mathematics and minor in computer science from G. B. Pant University of Agriculture and Technology, Pantnagar, India. He has been a faculty member for around 12 years and has taught several core courses in pure and applied mathematics at undergraduate, postgraduate, and doctorate levels. He is currently a professor at Graphic Era (Deemed to be University), Dehradun, India. Before joining the Graphic Era, he was a deputy manager (probationary officer) in Syndicate Bank for a short period. He is editor-in-chief of International Journal of Mathematical, Engineering and Management Sciences and the guest editor and member of the editorial board of various journals. He is a regular reviewer for international journals, including IEEE, Elsevier, Springer, Emerald, John Wiley, Taylor & Francis, and many other publishers. He has published 225 plus research publications in IEEE, Taylor & Francis, Springer, Elsevier, Emerald, World Scientific, and many other national and international journals of repute and also presented his works at national and international conferences. His fields of research are reliability theory and applied mathematics. Dr. Ram is a senior member of the IEEE, life member of Operational Research Society of India, Society for Reliability Engineering, Quality and Operations Management in India, Indian Society of Industrial and Applied Mathematics, member of International Association of Engineers in Hong Kong, and Emerald Literati Network in the UK. He has been a member of the organizing committee of a number of international and national conferences, seminars, and workshops. He has been conferred with Young Scientist Award by the Uttarakhand State Council for Science and Technology, Dehradun, in 2009. He has been awarded the Best Faculty Award in 2011, Research Excellence Award in 2015, and recently Outstanding Researcher Award in 2018 for his significant contribution in academics and research at Graphic Era (Deemed to be University), Dehradun, India.

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Contents Acknowledgment Preface

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About the editors List of contributors

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Nurullah Umarusman, Turgut Hacivelioğullari 1 Fuzzy inference system in sustainable supplier

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Aalok Kumar, Ramesh Anbanandam, Golam Kabir, Yiğit Kazançoğlu 2 Green and sustainable freight logistics for improving supply chain sustainability: a bibliometric analysis 39 Sushobhan Majumdar 3 Sustainability in urban expansion of a metropolitan city: impacts of urban growth towards the outer fringe of Kolkata 59 Muhittin Sagnak 4 Assessment of logistics performance in sustainable supply chain: case from emerging economy 73 Ashutosh Pandey, Rajendra Sahu 5 Service designing through Fuzzy Kano analysis in heritage tourism Somen Dey 6 Developing a framework to provide technological solutions for implementing green supply chain 105 Yatish Joshi, Gaurav Kabra 7 Demand side of the sustainable supply chain (consumers sustainable practices): a conceptual review 119 İpek Kazançoğlu, Can Karaosmanoğlu 8 Can sustainability marketing be implemented as a differentiation strategy? 133

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Jagdeep Singh, Mamta Kumari 9 Agricultural/biomass waste management through “green supply chain way”: Indian “brickfield” perspective 157 Shashikant Rai, Saurabh Mishra, Ram Mohan Mishra 10 Management of quality in perishable food supply chain by using Internet of things (IOT): a novel approach 179 Index

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List of contributors Ramesh Anbanandam Department of Management Studies Indian Institute of Technology Roorkee Uttarakhand, India [email protected] Somen Dey School of Management Studies Motilal Nehru National Institute of Technology Allahabad Prayagraj Uttar Pradesh, India [email protected] Turgut Hacivelioğullari Graduate School of Social Science Aksaray University Aksaray, Turkey [email protected] Yatish Joshi School of Management Studies Motilal Nehru National Institute of Technology Allahabad, India [email protected] Golam Kabir Department of Industrial and System Engineering University of Regina Saskatchewan, Canada [email protected] Gaurav Kabra Operations and Supply Chain Management National Institute of Industrial Engineering Mumbai, India [email protected] Can Karaosmanoğlu Department of Transportation Services Marina and Yacht Management Program Yaşar University, Vocational School Izmir, Turkey [email protected]

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İpek Kazançoğlu Faculty of Economics and Administrative Sciences Department of Business Administration Ege University Izmir, Turkey [email protected] Yiğit Kazançoğlu Department of International Logistics Management Yasar University Izmir, Turkey [email protected] Aalok Kumar Department of Management Studies Indian Institute of Technology Roorkee Uttarakhand, India Department of Industrial and System Engineering, University of Regina Saskatchewan, Canada [email protected] Mamta Kumari Junagadh Agricultural University, Amreli Gujarat, India [email protected] Sushobhan Majumdar Department of Geography Jadavpur University Kolkata, India [email protected] Ram Mohan Mishra Department of Management Studies Indian Institute of Information Technology Allahabad Uttar Pradesh, India [email protected]

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Saurabh Mishra School of Management Studies Motilal Nehru National Institute of Technology Allahabad Uttar Pradesh, India [email protected] Ashutosh Pandey Department of Management ABV – Indian Institute of Information Technology and Management Gwalior Madhya Pradesh, India [email protected] Muhittin Sagnak Department of Information and Document Management Izmir Katip Celebi University Izmir, Turkey [email protected] Rajendra Sahu Department of Management ABV – Indian Institute of Information

Technology and Management Gwalior, Madhya Pradesh [email protected] Shashikant Rai Department of Management Studies Indian Institute of Information Technology Allahabad Uttar Pradesh, India [email protected] Jagdeep Singh PAHER University Udaipur, Rajasthan, India [email protected] Nurullah Umarusman Faculty of Economics and Administrative Sciences, Aksaray University Aksaray, Turkey [email protected]

Nurullah Umarusman and Turgut Hacivelioğullari

1 Fuzzy inference system in sustainable supplier Abstract: Nowadays, businesses focus on sustainable supply chain management to gain economic, environmental, and social benefits. In reference to the criteria determined, selecting sustainable suppliers for the three dimensions of sustainability and for the companies operating in different sectors from these dimensions enables the business to become stronger in the market. In this study, sustainable supplier selection criteria were classified as quantitative and qualitative using the information obtained from the literature research. Later, by comparing Dickson’s criteria with Ghoushchi’s criteria, Dickson’s criteria were classified within the framework of triple bottom line. The solution to the sustainable supplier selection problem of a business that produces sustainable agricultural machines in Turkey using criteria selected from the classification was performed with Mamdani-type fuzzy inference system. Keywords: Mamdani-type fuzzy inference systems, sustainable supply chain management, supplier selection problem

1.1 Sustainable supply chain management The term of sustainability emerged in 1960s as a response to the concerns of environmental degradation and social inequality (McKenzie, 2004). The World Commission on Environment and Development (WCED, 1987) defines sustainability as “the development that meets the needs of the present generation without compromising the ability of future generations to meet their needs.” Since the declaration by WCED in 1987, arguments have been going on in terms of how such a wide and political concept of sustainability can be applied to an economic perspective and made functional, and business world interpreted it as the integration of economic, social, and environmental dimensions, generally known as “triple bottom line” (TBL) (Elkington, 1998). While it is not a universally accepted concept of sustainability, it fundamentally means the integration of economic, social, environmental, and cultural concepts into business applications. The concept of sustainability actually originates from “sustainable development,” which has a much

Nurullah Umarusman, Faculty of Economics & Administrative Sciences, Aksaray University, Aksaray, Turkey Turgut Hacivelioğullari, Graduate School of Social Science, Aksaray University, Aksaray, Turkey https://doi.org/10.1515/9783110628593-001

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wider scope (Caroll and Buchhollz, 2008). The economic line of the TBL points to the effects of business applications by a corporation on the economic system (Elkington, 1998). A corporation needs to supply the needs of its market fully, correctly, and timely; satisfy its customers; and profit economically without compromising its quality in order to continue in a positive direction for a long-term sustainability (Cuthbertson, 2011). For communities, social sustainability is both a condition to strengthen life and a process to achieve it (Mc Kenzie, 2004). Many businesses utilize supplier evaluation tools and partner applications to ensure a higher social responsibility for their supplier chains (Gimenez and Tachizawa, 2012). The social dimension of the TBL represents the necessity of maintaining beneficial and fair applications for labor, human capital, and the community. Applications such as fair wage system and health insurance enrich the society (Alhaddi, 2015). Although the environmental problems that societies face today are widely documented and blamed largely on business world, there is need for developing practical solutions to minimize some of the risks and difficulties rising from such problems. Business world is in the center of these environmental controversies, but it must also locate itself in as the center of solutions (Lamming and Hampson, 1996). The aims of supply chain management (SCM) in terms of sustainability are to optimize manufacturing activities and maximize profitability. However, they should also minimize the use of resources and production of waste material while maximizing the amount of recycled energy in order to ensure environmental sustainability (Zhou et al., 2000). Sustainability is usually associated with corporal social responsibility. The concept of sustainability dictates the fulfillment of current needs without compromising the needs of future generations. Hearing about sustainability for the first time, people think about green products, recycling, global warming, and the protection of rain forests. While these are vital parts of sustainability, costumers also care about their community and the reputation of a business (Heizer et al., 2017). The concept of sustainability created many uses such as “social sustainability,” “environmental sustainability,” “sustainable development,” and “sustainable future” (Kopnina and Blewitt, 2014). Sustainability and sustainable development can be explained as a combination of economic, social, and environmental elements within the problems related to supplier selection. As the concept of sustainability is a key factor in SCM, companies try to incorporate the features of sustainability into their supply chain activities in order to gain competitive advantage (Azadi et al., 2015). Then sustainability leads to competition among institutions, which are focused on innovation (Hansen et al., 2009). Sustainable SCM (SSCM) is the administration of cooperation among companies in addition to the flow of material, information, and capital all along the chain in view of the three fundamental dimensions of sustainable development (Seçkin, 2018). SSCM originated from the way the current generations satisfy their needs and its effects on and the concerns for the capability of future generations to satisfy

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their own needs (Altuntaş, 2015). It is an important discipline that enables the integration of environmental and social applications into commercial activities to reach the target of sustainability (Ashby et al., 2012). Supply chain sustainability is the encouragement of managing environmental, social, and economic effects, and good governance applications along the life span of products and services. The aim of supply chain sustainability is to create long-term environmental, social, and economic values, to protect and improve them for the benefit of all the stakeholders included in the processes until products and services are marketed (Sisco et al., 2010). Sustainable development harbors the pursuit of economic welfare, environmental quality, and social equality. Instead of short-term economic goals, the companies that aim to achieve sustainability need good performance in long-term economic, social, and environmental activities as well (Elkington, 1998). Supply chain members in SSCs are expected to sustain their competitive power by fulfilling needs and economic criteria of their customers while satisfying environmental, ecological, social, and ethic criteria at the same time in order to stay along the chain (Büyüközkan and Çifçi, 2011).

1.1.1 The relationship between SCM and sustainability It is vital for companies in today’s increasingly competitive markets to work with suppliers that can adapt to their policies. When selected correctly, suppliers will increase customer satisfaction and help companies reach their determined targets by ensuring an efficient flow of the supply chain (Uçal Sarı et al., 2017). Previously, only economic criteria were employed in evaluating suppliers; however, social and environmental criteria are considered along with economic criteria today to measure supplier performance (Bektur, 2018). On the other hand, there are deficiencies in terms of sustainability as the research in SSCM mostly focus on economic and environmental dimensions. In order to complete sustainability, the social and human aspect of sustainability may be researched using theories of organizational behavior (Panigrahi and Bahinipati, 2018). It is not an option but a requirement for SSCM to be included in sustainability. Researches show that a long-term success of a company may only be guaranteed as long as the concept of sustainability is integrated into SCM. The companies that aim to maximize the performance of all the three dimensions depict a higher performance compared to those that aim only at economic or social and environmental performance (Carter and Rogers, 2008). Companies will inherit environmental, social, and economic responsibilities, acquire a higher company performance, which would result in a potential advantage to improve competitiveness (Massaroni et al., 2015). Traditional supply chains aim at balancing their benefits for many stakeholders, improving operation efficiency of their factories, and maximizing process and

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activity profits. Nevertheless, essential principles of SSCs are environmental care and social liabilities added to economic profits (Zhang, 2011). Although sustainability has been researched extensively in terms of supply chains, it is seen that diversity and impact on supply chain sustainability performance are lacking sufficient research. Termed as sustainable plans, they improve both supply chain economic performance and also environmental and social performance (Laurin and Fantazy, 2017). Companies that are located in supply chain may be held responsible for the social and environmental activities of the suppliers in their own supply chain (Seuring and Müller, 2008). Businesses have recently found themselves in thin profit margins due to global competition and rapid technological advances. Therefore, they seek commercial partnerships, technological cooperation, and strategic alliances with their partners to increase their competitive power. Basic reasons for such relationships are to cut down investments, acquire sufficient material supply, decrease costs and product delivery durations, acquire core technology, minimize purchase process time, and decrease repeated processes and negotiation costs (Kopnina, 2017).

1.1.2 An insight to the barriers for sustainable SCM The literature on SSCM and SCM processes shows that the factors disturbing supply chains vary based on sectoral differences, company culture, trust between companies, and development levels of companies. According to Uluşkan and Godfrey (2018), previous supply chain researchers tries to determine the barriers for supplier selection criteria and successful supply chain application. Despite different viewpoints in those studies, the common aim is to define the critical elements and criteria in locating global resources. The fundamental aim of supplier selection is to employ sustainability as an integral component of all business activities. Therefore, understanding supplier-specific barriers help in comprehending the capacity, capability, and problems of a supply chain partner (Kumar and Rahman, 2015). In order to internalize SSCM, businesses have to locate the barriers for SSCM and define sustainable supplier selection criteria (Özçelik and Avcı Öztürk, 2014). There are many barriers with different degrees of influence to the successful application of SSCM. That is why it is required to define the dominant factors to adapt the concept of SSCM, which is conducted through the analysis of the barriers and effects of industries (Al Zaabi et al., 2013). Meinlschmidt et al. (2013) analyzed the barriers for sustainability supplier selection and found out that supplier selection focusing on social and ecological factors are not applied on corporate level. In their literature analysis, Ansari and Kant (2017) classified the barriers for sustainable SCM in terms of “application, industry focused, and country.” Walker et al.

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(2008) determined the barriers for environmental SCM are both internal and external based on the knowledge he acquired from seven public and private institutions. Internal barriers include cost and legitimacy while external barriers are regulations, dependency on supplier, and industry-specific barriers. In their literature review, Parmar and Shah (2016) defined 23 basic barriers that could help industrial practitioners and academic experts employ SCM in their manufacturing organizations. They classified these barriers as strategic barriers, cultural barriers, technological barriers, individual barriers, and organizational barriers. Büyüksaatçı Kiriş and Yılmaz Börekçi (2018) analyzed the literature on sustainability for sustainable port management and concluded that drivers focus on issues of environmental sustainability while barriers are amassed in terms of economic sustainability. Barve and Mudili (2013) determined that “poor mining environmental consciousness” is the key barrier at all levels as India lacks proper legislation. Govindan and Hasanagic (2018) concluded in their study that the main barrier is the consumer perception against reproduced products. Additionally, lack of consumer consciousness for circular economy and technological limitations for production are the significant barriers. The uncertainty about demand decreases with coordination and information sharing among the firms in supply chain, and it enables them to invest less in their stocks. Therefore, it would bring easy in planning and decrease in costs. As a result of trust and cooperation forming among firms, sharing risks, minimization of barriers among firms, and increase of flexibility, the time needed to develop and market new products shortens as well (Özdemir, 2004). It is always possible that firms may resist change. Resistance may arise from financial matters, system capacity, geographical location, business type, culture, costs, human resources, information management, and goals. It is important to determine the barriers for sustainable SCM for focal company and/or supplier company. (Ageron et al., 2012). Seuring and Muller (2008) point out that barriers in SSCM are high costs, insufficient coordination, complexities, and insufficiency or lack of communication in SCM. On the other hand, companies’ information on sustainability and/or their lack of it persuade them to keep their current status. Instead of increasing the level of sustainability, it instead acts as a barrier against activating SSCM (Vijfvinkel et al., 2012). Although there are forces persuading companies to increase their sustainability, the factors such as lack of CEO consensus, costs of sustainability and economic states, nonexistence of standards and regulations for sustainability, and conflicts with short- and long-term strategic targets (Giunipero et al., 2012). It is a must to determine criteria for sustainable supplier selection by defining the barriers for SCM to create SSCM. Supplier company culture and financial costs are regarded as barriers for SSCM. Companies have to pay attention to not only the conventional economic factors but also the other dimensions of sustainability (Özçelik and Avcı Öztürk, 2014).

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1.2 A critical perspective on sustainable supplier selection criteria It is a fact that each supplier has obvious superiorities and weaknesses compared to other suppliers based on different criteria. It is because supplier evaluation is conducted in terms of different qualitative or quantitative criteria. For example, a product with short “supply time” may have low “after sale service percentage.” It is also possible that a supplier company may be missing “ISO standards” while having high reputation. Therefore, it must be remembered that “incomparable” and “conflicting” criteria are considered as well in investigating a compromising or satisficing result in supplier selection, which is a multicriteria decision- making process. While supplier selection criteria differ based on sectors, it is also possible to have different criteria in supplier selection for companies in the same sector. Additionally, geographical location, global warming, and such factors force companies to use different criteria in supplier selection. On the other hand, Ravindran and Warsing (2013) compared the relative significances of various supplier selection criteria and concluded that supplier selection criteria may change in time as well. According to Rezaei (2019), supplier selection is a strategical decision in terms of SCM, and the sustainability of SCM also includes supplier selection process. Sustainable supply chain includes managing the flow of material, information, and capital in addition to ensuring cooperation among companies within supply chain, and its goals are chosen as stated by customers and stakeholders from economic, environmental, and social dimensions of sustainable development (Yang et al., 2017). The conventional supplier selection utilizes economic criteria such as cost, quality, and on-time delivery. Although there are many studies about the common criteria in supplier selection process, only few studies include criteria of sustainability (Mohammadi et al., 2018). Nowadays, companies prefer to work with firms that conform with the environmental legislations to increase their sustainability performance and satisfy customer needs. Therefore, they utilize the criteria of sustainability as their basis to select the correct supplier (Gören, 2018). A successful supplier selection may be achieved after analysis and evaluation of compromisebased success criteria in supplier selection decision-making processes in the same or different sectors. When companies apply the concept or sustainability into their businesses, they will benefit from it as well as the country’s economy (Ecemiş and Yaykaşlı, 2018).

1.2.1 Key success factor in supplier selection: criteria Pareto analysis determined the most widely used criteria in conventional supplier selection as the criteria of net price, delivery, quality, production facilities and

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capacity, geographic location, and technical capability (Mukherjee, 2017). It is not possible in today’s competitive business environment to produce high-quality and low-cost products without being a satisficing seller. That is why it is important in purchasing decision to select and keep the sufficient supplier group. The selection of a good cluster of suppliers is vital for the success of a business. Two important phenomena are the criteria to be used in supplier selection and the methods to compare suppliers (Deshmuk and Chaudhari, 2011). Employment of more than one criterion in supplier selection complicates the selection process. Additionally, the determination of the amount of products to be purchased from each supplier based on the criteria given by the business is another significant question. Complexities and ambiguities in real-world problems, sectoral differences, geographical location, a country’s level of humane development, and global economic crises result in the fact that businesses handle supplier selection criteria differently. The significance of SSCM in terms of environmental, economic, and social aspects have increased lately and influenced supplier selection as a consequence. According to Er Kara et al. (2016), businesses have to integrate criteria based on the TBL of sustainability into their supplier evaluation and selection processes as sustainable supplier selection is a significant process in the global and competitive business world. SSCM is the management of materials and information flow as well as the coordination among the firms among the supply chain. All the three dimensions of sustainable development must be handled very attentively along this process. Sustainable supplier selection may be regarded as the process of selecting the suppliers that apply the three dimensions of sustainability in their supply chain in the best possible way. While investigating the criteria to be used to make the selection among the best implementers of sustainability or the question to purchase what amount of products from which supplier, the importance of the sustainable supplier selection criteria becomes manifest.

1.2.1.1 Dickson’s supplier selection criteria Dickson (1966) performed the study on supplier selection criteria in conventional SCM. After his questionnaire with purchasing agencies and managers, Dickson defined 23 different criteria with varying significance levels for supplier selection process. Dempsey (1978), Roa and Kiser (1980), and Bache et al. (1987) identified new criteria for supplier selection with different viewpoints. Later, Weber et al. (1991) classified the information from 74 articles according to Dickson’s 23 selection criteria. Pricing policy, delivery, product quality, and service quality are determined as fundamental criteria among all. Cheraghi et al. (2004) analyzed more than 110 scientific studies published between 1990 and 2001 and investigated supplier selection criteria. A comparison between the studies from 1966 to 1990 and the studies from 1990 to 2001 concluded

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that there are important differences in the relative significance levels of various success factors. Both periods rank price, delivery, and quality as the first three criteria. Ho et al. (2010) analyzed the multicriteria decision-making approaches for supplier evaluation and selection published in international journals between 2000 and 2008. They determined the common approaches; the most popular criteria used in evaluation and the deficiencies in selected approaches. The most popular criterion is quality followed by delivery, price/ cost, manufacturing capability, service, management, technology, research and development, finance, flexibility, reputation, relationship, risk, and safety and environment. Thiruchelvam and Tookey (2011) conducted a comparison between the period from 1966 to 2001 and the period from 2001 to 2010 in terms of the 36 criteria for supplier selection. While price, delivery, and quality are the dominant criteria in their comparison, technical capability poses great significance during the evaluation because the purchasing business is interested in the supplier’s technological capability both in the present and in the future. Nielsen et al. (2014) performed a one-to-one comparative analysis of the literature review from 1966 to 2010. In the supplier selection and supplier evaluation studies since Dickson (1966), there are many different criteria due to different development levels of countries, geographical location, and especially sectoral differences. Nevertheless, price, delivery time, and quality are the most important criteria as seen in the literature results given above. Although economic dimension is highlighted in the conventional supplier selection, the inclusion of environmental and social factors has made sustainable supplier selection vital in the process.

1.2.1.2 Sustainable supplier selection criteria Due to sustainable awareness and pressure from stakeholders, businesses have realized the importance of SSCM applications to achieve economic, environmental, and social benefits (Li et al., 2019). A successful supplier selection may be achieved after analysis and evaluation of compromise-based success criteria in supplier selection decision-making processes in the same or different sectors. When companies apply the concept or sustainability into their businesses, they will benefit from it as well as the country’s economy (Ecemiş and Yaykaşlı, 2018). Supplier selection and purchasing processes include methods to reach the goals not only for the focal company but also for all the supply chain (Alikhania, 2019). Social and environmental criteria are often disregarded in supplier selection. As sustainability became a point of attention in the field of SCM, researchers implemented social and environmental indicators into the conventional supplier selection process. Therefore, social and environmental criteria are to be included as well as the economic criteria in the framework of supplier selection (Song et al., 2017). The three dimensions of

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sustainability and the criteria chosen from them would help make the best decision for sustainable supplier selection (Memaria et al., 2019). Supplier selection criteria ensure continuation of being competitive in market and may also aid in evaluating the most effective supplier to reach sustainability in supply chain (Luthra et al., 2017). In his survey on the present research, Goebel et al. (2012) concluded that sustainable supplier selection mostly focuses on the selective dimension of supplier selection, and the social and environmental dimensions of sustainability are rarely investigated. Wan Mahmood et al., (2014) developed a framework for sustainable supplier selection to demonstrate the interdependency among the subcriteria in supplier selection for the three dimensions of sustainability. Özçelik and Avcı Öztürk (2014) analyzed the supplier selection criteria in three dimensions in their questionnaire with Turkish companies publishing sustainability reports and found out that economic criteria take the first priority followed by environmental and social criteria based on general averages. Govindan et al. (2015) conducted a general literature review and listed the criteria used for green supplier selection and evaluation. In their research based on the criteria used in sustainable supplier selection, Er Kara et al. (2016) grouped them in three dimension and eight subcategories. While cost/price, quality, and delivery performance are used frequently in the economic dimension, production facilities and capacity are used less. Green management strategy and environmental management system are the most frequently used criteria in the environmental dimension whereas environmental cost, resource and energy consumption, and reverse logistic system are less utilized. In the social dimension, corporate social responsibilities and relationship with stakeholders have the high priority while organizational legal responsibilities along with brand image and reputation are inferior. Zimmer et al. (2016) reviewed 143 articles on sustainable supplier selection between 1997 and 2014 and defined the first 10 criteria for each of the economic, social, and environmental dimensions. On the other hand, when the studies that focused only on the economic criteria are disregarded, the environmental dimension is used only in 10,4% of the remaining studies, and the social dimension is used in only one study. The rate of studies that utilized economic and environmental dimensions is 59%. Although two studies used environmental and social dimensions, no study was found utilizing economic and social studies. The rate of studies that utilized all the three dimensions of sustainability is 28%. There are different complexities in sustainable supplier selection and evaluation. If a number of suppliers are evaluated based on increasing and conflicting types of dimensions, problems come up in evaluation and selection. Many analytical tools that were developed to evaluate suppliers rely on conventional supplier selection approaches (Sarkis and Dhavale, 2015). Companies depict different purchasing behaviors in different situations including selection criteria and supplier management. The criteria used especially in supplier selection may be qualitative or quantitative. Therefore, it requires a balance between the conflicting qualitative

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and quantitative factors to select the best supplier (Şen et al., 2008). The selection of the appropriate supplier based on conflicting qualitative and quantitative criteria converts the selection process into a multiple criteria decision-making (MCDM) problem (Govindan et al., 2015). Environmental and social criteria are utilized less compared to economic criteria in supplier evaluation and selection. Criteria in environmental and social dimensions are both qualitative and quantitative (Sarkis and Dhavale, 2015). While the present literature offers some methods to evaluate social sustainability, there are still problems with quantitative features and indicators, which do not have clear definition (Popovic et al., 2017). It is possible to evaluate some criteria as both qualitative and quantitative in supplier selection process. It is because they depend on decision maker’s viewpoint Yang and Chen (2006). Tuczek and Wakolbinger (2018) point out that quantitative criteria must be used to be able to consider a wide cluster of criteria for sustainability. Humphreys et al. (2003) classified environmental criteria as qualitative and quantitative. In their study, “environmental management systems” are the most popular qualitative criterion while “environmental costs” are the most popular quantitative criterion. When the criteria in the literature about the three dimensions of sustainability are considered, it is possible to classify especially environmental and social dimensions as qualitative and quantitative. The criteria that were used in the studies by Özçelik and Avcı Öztürk (2014), Chaharsooghi and Ashrafi (2014), Grover et al. (2016), Ghadimi et al. (2016), Tundys (2016), Zimmer et al. (2016), Rabbani et al. (2017), Luthra et al. (2017), Ghoushchi (2018), Li et al. (2019) and the criteria that were used in the TBL framework based on the results in those studies are given in Table 1.1. Although it is not absolute, it may pose as a guide for future studies.

Table 1.1: Quantitative and qualitative classification for sustainable supplier selection criteria.

Economic

Quantitative criteria

Qualitative criteria

Cost/price

Quality (quality of product)

Total cost of shipments

Innovativeness

Number of shipments

Organization and management

Production facilities and capacity

Reliability

Service

Flexibility Technological and financial capability Delivery time

1 Fuzzy inference system in sustainable supplier

Table 1.1 (continued ) Quantitative criteria

Qualitative criteria

Environmental Environmental costs

Environmental management system

Resource consumption/Energy consumption

Period of obtained ISO standards

Green logistics

Environmental competencies

Renewable energy

Raw material consumption

Recycling

Ozone depleting chemicals Green R&D Green design and purchasing Green manufacturing Waste management and pollution Water consumption Reuse material Environmental product performance Pollution control

Social

Annual number of accidents

The interests and rights of employee

Work safety

Respect for the policies

Safety risk

Work safety and labor health

Employment compensation

Local communities influence

Contractual stakeholders’ influence

Collective bargaining, freedom of association

Equity labor sources

Social code of conduct

Disciplinary and security practices

Health and safety incidents/ practices Local communities’ influence Information disclosure The rights of stakeholders Training Child labor Reputation

Supporting educational institutions Grants and donations

11

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Nurullah Umarusman and Turgut Hacivelioğullari

The classification of the criteria as quantitative or qualitative in terms of the methods used in scientific studies or based on the sector depends on the decision maker’s viewpoint. For example, the criteria of “innovativeness” may be qualitative, or it may be regarded quantitative when seen as a need for investment to ensure “innovativeness”. In terms of fuzzy inference systems (FISs), the criteria of “delivery time” may work as both quantitative and qualitative for fuzzification process when regarded as input. If it is an investment, the criteria of “renewable energy” is quantitative; if it has the criteria already, then it is qualitative. When there is financial support for the criteria of “supporting educational institutions,” it is quantitative; when it is accepted as a task, it is then qualitative. Classifications may similarly be cleared up by providing definition for other criteria. On the other hand, subcriteria may be defined for any criteria and classified as quantitative and/or qualitative to further clear the classification proposed in Table 1.1. Wan Mahmood (2014) proposed the subcriteria for “technology capability” as “technology level, failure mode effect, and critical analysis, capability of research and development, capability of design, and capability of handling pollution”. “Technology level, failure mode effect, and critical analysis” may be taken as quantitative and “capability of design” as qualitative criteria. On the other hand, the subcriteria of “capability of research and development” and “capability of handling pollution” may be classified as both quantitative and qualitative. The contribution of the criteria defined by Dickson (1966) for the supplier selection process is quite significant. The approaches to SCM expanded with the concept of “sustainability” and affected the supplier selection problems. Although economic criteria dominate Dickson’s criteria, it is actually possible to see criteria including the other two dimensions of TBL. According to Weber et al. (1991), Dickson’s criterion of “performance history” may be determined from “delivery” or “quality” performances. Policies of “warranties and claim” may effect a seller’s pricing. To illustrate similar cases, the criteria of the three TBL dimensions defined by Ghoushchi et al. (2018) are compared with Dickson’s criteria and given in Table 1.2. Dickson’s criteria of “management and organization,” “organization and management,” “Local communities’ influence,” “work safety and labor health,” and “environmental management system” include the three dimensions of direct and indirect TBL. A business’s “technical capability” may be explained within the environmental dimension based on the criteria of “green product,” “water consumption,” “renewable energy,” “energy consumption,” and “green R&D.” The criterion of “reliability” may be utilized to explain “performance history,” “impression,” and “repair service” criteria of a business. Another view claims that fundamental criteria to be used in supplier selection for TBL must rely on Dickson’s criteria to increase the efficiency of supplier selection criteria in achieving TBL applications. Then, “subcriteria” must be defined based on information such as sectoral differences, geographical location, and country development index.

1 Fuzzy inference system in sustainable supplier

13

Table 1.2: Dickson’s criteria. Rank Dickson’s criteria

Ghoushchi et al. ()

TBL



Quality

Quality

Economic



Delivery

Delivery time

Economic



Performance history

Reliability

Economic

Delivery time

Economic

Quality

Economic



Warranties and claims policies

Price

Economic



Productivity facilities and capacity

Production facilities and capacity

Economic

Green product

Environmental

Recycling

Environmental

Cost/price

Economic

Total cost of shipments

Economic

Environmental cost

Environmental

Resource consumption

Environmental

Green R&D

Environmental

Green product

Environmental

Water consumption

Environmental

Renewable energy

Environmental

Energy consumption

Environmental

Green R&D

Environmental





Price

Technical capability



Financial position

Financial capability

Economic



Procedural compliance

Respect for the policies

Social



Community system

Information disclosure

Social



Reputation and position in industry Reliability

Economic



Desire for business

Organization and management

Economic



Managenet and organization

Organization and management Local communities’ influence

Economic Social

Work safety and labor health

Social

Environmental management system

Environmental

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Nurullah Umarusman and Turgut Hacivelioğullari

Table 1.2 (continued ) Rank Dickson’s criteria

Ghoushchi et al. ()

TBL



Operating controls



Repair service

Reliability

Economic



Attitude

Reputation

Social

The interests and rights of employees

Social

Ecomomic



Impression

Reliability

Economic



Packing ability

Production facilities and capacity

Economic



Labor relations record

The interests and rights of employees. Social Respect for the policies

Social



Geographical location

Cost

economic



Amounts of past business

Number of shipments

Economic



Training aids

Training

Social



Reciprocal arrangements

Contractual stakeholders’ influence.

Social

Work safety and labor health

Social

1.2.2 Sustainable supplier selection from FIS’s perspective From a general point of view, it is possible to see the different methods used in the solution of supplier selection problems and hybrid models consisting of the integration of these methods. These methods are classified from different perspectives by de Boer et al. (2001), Ding et al., (2003), Pal et al., (2015), Mukherjee et al. (2013) and Mukherjee (2017), Umarusman (2019). In this study, from the first article conducted by Carrera and Mayorga (2008), a literature review including supplier selection problems and sustainable supplier selection problems until 2019 is given. Carrera and Mayorga (2008) proposed FIS as an alternative approach to deal with the ambiguity of supplier selection especially in processes of new product development. Liu and Wang (2009) created an integrated fuzzy approach for supplier selection problems, which makes use of the fuzzy set theory, fuzzy Delphi, FISs, and fuzzy linear assignment. After the literature review, 26 criteria are determined on supplier selection problems. Chen et al. (2009) used FIS for supplier selection in e-production. Yücel and Güneri (2010) proposed a solution of supplier selection problem using adaptive neuro-FIS (ANFIS), which is an approach based on neural network and fuzzy logic. Niraj and Kumar (2011) made use of FIS to solve supplier selection problem with multiple goals by using the criteria of “price,” “quality,”

1 Fuzzy inference system in sustainable supplier

15

and “service.” Güneri et al. (2011) suggested ANFIS model to be used in decisionmaking process for supplier selection. It is made up of two main stages: the selection of inputs by ANFIS and the construction of the final model based on the inputs selected previously. Amindoust et al. (2012) proposed a fuzzy ranking model based on FIS, which evaluates criteria of sustainability for the supplier selection problems. Akgün (2012) developed a FIS to select the best supplier using the criteria of quality, costs, delivery time, and service. Lima Junior et al. (2013) defined a decision method for supplier selection that is built on two kinds of methods: a noncompensatory rule for sorting in qualification stages and a compensatory rule for ranking in the final selection. Abbasi and Asgari (2014) defined the criteria used in supplier selection after a literature review and determined the most important criteria for food industry by using fuzzy Delphi method. Using ANFIS method, they consequently selected the best supplier among a total of 60 suppliers. Tahriri et al. (2014) proposed a new ranking method, which integrated fully deposition modeling (FDM) and FIS methods for supplier selection problems. They used six criteria in their selection such as trust, quality, cost, delivery, management and organization, and finance. Asghari and Abrishami (2014) investigated a method to analyze potential suppliers based on FIS and its impact on gradual covering distance. Asemi et al. (2014) did the supplier selection for a steel company using fuzzy analytic hierarchy process, FISs, and fuzzy TOPSIS. Ghadimi and Heavey (2014) conducted an evaluation on sustainability for suppliers especially in medical device industry using FIS. Bhowmick et al. (2014) used FIS to evaluate the nine suppliers of a business operating in metal industry. Asami et al.,(2014) developed a dynamic fuzzy hybrid MCDM method for evaluation, ranking, and selection. They performed supplier selection for a steel company with their hybrid method including fuzzy analytic hierarchy process, FIS, and fuzzy TOPSIS approaches. Amindoust and Saghafinia (2014) proposed a fuzzy ranking method that uses FIS for supplier selection process in businesses. The applicability of the proposed method was tested with a real-life supplier selection problem. Paul (2015) proposed a rule-based FIS model for supplier selection process, which considers a total of 18 selection criteria (4 quantitative and 14 qualitative) to manage risks in supply chain. The usability of the developed model was tested with an example. Lima Junior et al, (2016) developed a new method, a blend of FISs and some SCOR model indicators, to aid supplier evaluation performance. A pilot application was conducted with 10 suppliers of a company in automotive industry to depict the modeling and application processes. Asgari et al. (2016) made use of ANFIS, fuzzy analytical hierarchy process (FAHP), and fuzzy goal programming (FGP) to evaluate suppliers and select the best. ANFIS method performs better in comparison to FAHP-FGP method as the selected suppliers ranked up higher in all performance scales. Sabaghi et al. (2016) proposed a FIS to evaluate product/process sustainability (SAFT) to evaluate product/process sustainability in different

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Nurullah Umarusman and Turgut Hacivelioğullari

manufacturing industries. They concluded that, as it is independent of fuzzy rule, SAFT is a rather practical and easy method. Amindoust and Saghafinia (2017) developed a framework to evaluate the sustainability of textile suppliers and a model based on FISs to rank a given list of suppliers. Ghadimia et al., (2017) used FIS to evaluate and select the most sustainable suppliers for an automotive spare part manufacturer licensed under a France-based automotive organization. Ashtarinezhad et al. (2018) made use of FISs to evaluate and categorize suppliers in petrol and gas industry. Pourjavad and Shanin (2018) conducted performance evaluation of SSCM using Dematel and Mamdani FIS. Sremac et al., (2019) developed a hybrid method of the artificial intelligence ANFISs to determine the economic order quantity. It is flexible and applicable to a number of goods in supply chains. Mohammadi et al. (2018) proposed an integrated model of fuzzy Shannon entropy and FIS to evaluate and select suppliers according to their sustainability performance. Pourjavad and Shahin (2018) conducted a sustainable SSCM performance assessment using Dematel and Mamdani-type FISs.

1.3 FISs FISs are an important method based on the concept of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. It has a multidisciplinary structure because it can be adapted to many areas as well. The appropriateness of the if-then pattern of FISs to human behavior and a precise assessment of the condition-dependent linguistic outcome in the decision-making process are important in terms of giving a clear result. According to Bede (2013), linguistic variables help to evaluate linguistic expressions in terms of fuzzy mathematical quantities. Fuzzy rules are a set of rules that associate input with output data occasionally in an intuitive manner. In a FIS, approximate reasoning procedure can be modeled by interpolation between the fuzzy rules. Fuzzy inference is such a process that formulates the mapping from a given input to an output with the help of fuzzy logic. With the mapping, decisions can be made, or patterns discerned. The process of FISs involves membership functions, fuzzy logic operators, and if-then rules (Shukla and Tiwari, 2013). FISs express a significant part of fuzzy logic. In many practical applications like control, these systems perform crisp nonlinear mapping specified in the form of fuzzy rules codifying expert or common sense knowledge about the problem (Cherkassky, 1998). FIS operations are rested upon fuzzy logic to map system inputs and outputs. (Li et al., 2018). The basic structure of FIS consist of three conceptual components: a rule base that contains a selection of fuzzy rules; a database that defines the membersip functions is used in the rules; and a reasoning mechanism, which performs the inference procedure (Jang, 1997). Block diagram of a fuzzy rule-based system is shown in Figure 1.1.

1 Fuzzy inference system in sustainable supplier

17

Rule 1 w1

⇀

x is A1

(Crisp or fuzzy) ⇀

X

y is A1

Rule 2 w2

⇀

x is A2

……………..

(Fuzzy) y is B2

Aggregator

Defuzzifier

………...…… Rule r

⇀

x is Ar

wr

y is Br

Figure 1.1: Block diagram of a fuzzy rule-based system (Jang, 1997).

Although there are various FISs in the literature, Mamdani-type FIS and Sugeno-type FIS are the most important ones. Mamdani (1974) was the one who proposed fuzzy rule-based systems dealing with real inputs and outputs for the first time. Afterward, Mamdani type-FIS was introduced by Mamdani and Assilian (1975). The most common rule structure of Mamdani-type FISs includes Zadeh’s (1975) concept of linguistic variables. Sugeno-type FIS is also known as Takagi–Sugeno–Kang (TSK)-type FIS. Sugeno-type FIS was proposed by Sugeno (1985), Takagi and Sugeno (1985) and Sugeno and Kang (1988). Mamdani type-FIS uses fuzzy sets as rule consequent while Sugeno-type FIS utilizes linear functions of input variables as rule consequent (Sivanandam et al. (2007). The differences between them are aggregation and defuzzification procedures, which lie in consequent (Yardımcı and Karpuz, 2017). In today’s world problems, knowledge is frequently stated as a set of “IF premise (antecedent), THEN conclusion (consequent)” type rules. Fuzzy inferencing hinges on the fuzzy representment of “the antecedents and consequents” (Majumdar, 2011). These kinds of FISs are also known as fuzzy rule-based systems with fuzzifier and defuzzifier or, more commonly, as fuzzy logic controllers proposed by Mamdani and Assilian (1975).

1.3.1 Mamdani type-FIS Mamdani-type FIS can supply an extremely intuitive knowledge base that is simple to understand and maintain. Therefore, this type of FIS is more common, especially in decision-making process. (Öztayşi et al., 2013). The basic of a Mamdani-type FIS has four conceptual components: A fuzzy rule base, a fuzzy inference engine, a fuzzification interface and if-need engine, a fuzzification interface, and, if needed, a

18

Nurullah Umarusman and Turgut Hacivelioğullari

defuzzification interface. (Gorzalczany, 2002). Mamdani (1974) and Mamdani and Assilian (1975) developed the Mamdani-type FIS control a steam engine and boiler. A typical fuzzy rule in a Mamdani fuzzy system has the form If x1 is A1 , . . .,and xk is Ak ,THEN y is B. where x = ðx1 , x2 , . . . , xk Þ and y are linguistic variables, A1 , . . ., Ak are fuzzy sets in the antecedent, and B is a fuzzy set in the consequence, respectively. A typical fuzzy reasoning of the Mamdani-type FIS rests on the max–min inference method. (Feng, 2010). These fuzzy IF-THEN rules provides an appropriate framework to include human experts’ knowledge. (Li, 2006). Mamdani-type FIS is commonly accepted to grab expert knowledge. It allows defining the expertise in more intuitive, more human-like way. Nevertheless, Mamdani-type fuzzy inference requires a serious computational burden. With reference to the scientific study of Jang (1997), Cordon et al. (2001), Sivanandam et al. (2007), Öztayşi et al. (2013), Amindoust and Saghafinia (2014), a summary of steps for the Mamdanitype FIS is given as follows: Step 1: (Fuzzification) The membership functions of quantitative and/or qualitative input variables are defined in the fuzzification process. Step 2: (Fuzzy rules) Fuzzy rules are a group of linguistic expressions that describe how the FIS should determine concerning categorizing an input or controlling an output. A fuzzy rule base consists of a collection of fuzzy IFTHEN rules. Step 3: (Fuzzy inference) Fuzzy inference is an inference procedure to draw a conclusion hinging on a set of “If-then” rules. The fuzzy interface engine takes integrations of the identified fuzzy sets consideringly the fuzzy rule and allocates to integrate the related fuzzy field individually. A fuzzification interface that transforms the crisp input data into fuzzy values that function as the input to the fuzzy reasoning process. The Mamdani-type inference system is manually established on the base of expert knowledge, and the final model is not either trained or optimized. The Mamdani-type inference system considers fuzzy inputs and returns fuzzy outputs. The output of the Mamdani inference method is a fuzzy set entailing to be transformed into crisp value through defuzzification. Step 4: (Defuzzification) “Defuzzification” is the last step in fuzzy inference process. Fuzziness provides us evaluating the rules, but the final output of a fuzzy system must be a crisp number. There are different methods in “defuzzification” phase. These are max membership, centroid method, weighted average method, and mean-max membership. An example of a Mamdani-type FIS is shown in Figure 1.2.

19

1 Fuzzy inference system in sustainable supplier

μ

μ

A1

Min

B1

μ

C1 C´1 Z

X μ

Y μ

A2

B2

μ

C2 C´2 Z

Y

X

x

y

μ

Max

C´

Z

ZCOA Figure 1.2: The Mamdani-type FIS.

1.4 Application The company in this application is Tire Ozsan farming mMachinery that specializes in manufacturing farming equipment in Tire county of Izmir, Turkey. It is an SME which started manufacturing machinery in Tire small industrial area in 2007. After meeting domestic demand till 2011, the company moved to Tire organized industrial zone and started exporting. All the regions in Turkey are within its coverage of sales and after-sale support services. The company sells 25% of its products to mostly European countries, Africa, and overseas. It purchases from world renown brands that produce reducers for the sector of farming machinery. The purchased reducers make up approximately 10% of the costs for the machinery being produced and sold. The remaining 90% is supplied from various national firms. The company has so far applied the principle of purchasing based on cost. As both national and international competition became increasingly tougher and its competitors started acting more aggressive using various methods, SSCM presented itself as an important requirement for the company. It aims to create the most suitable model for supplier selection based on its policies.

1.4.1 Defining supplier selection criteria based on sustainability Due to increasing environmental, social, and economic pressure, purchasing process has become even more complex today. To define the criteria for sustainability,

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Nurullah Umarusman and Turgut Hacivelioğullari

the manager of the company was first interviewed to select their criteria to be used in supplier selection based on the dimensions in Table 1.1. To maintain customer satisfaction, the following criteria were selected from an reactive and proactive management viewpoint based on SSCM strategies from both qualitative and quantitative groups of criteria: “cost,” “quality,” “delivery time,” “innovativeness,” “number of ISO standards,” “waste management and pollution,” “renewable energy,” “environmental product performance,” “environmental competencies,” “respect for the policies,” “work safety and labor health,” “training,” “social code of conduct,” “the interests and rights of employees,” and “reputation.” Next, the manager was requested to select the fundamental input criteria to increase the business market share and to be used in FIS from the criteria above. The business manager defined “cost,” “quality,” and “delivery” as the economic criteria; “environmental competencies” and “number of obtained ISO standards” as the environmental criteria; and “work safety and labor health” and “reputation” as the social criteria. “Supplier performance” was chosen as the input for sustainable supplier selection based on the selected criteria above. The input criterion is summarized below. – Cost ($): The sum of all the costs until the purchased product is acquired. – Quality (%): The degree of perfection with an acceptable cost. – Delivery time: The time between the order of a purchased product and its delivery (days). – Environmental competencies (%): Ecological knowledge, sociopolitical knowledge, knowledge on environmental issues, impressive cognitive skills, and percentage of successful environmental friendly behavior (possession of sufficient environmentally harmless facilities and processes during production). – Period of obtained ISO standards (years): The duration of time possessing ISO standards. – Work safety and labor health (%): The success percentage of activities preventing and protecting employees against possible work-related accidents and illnesses. – Reputation (%): The sum of all the views and beliefs held about a company by its contacts. Table 1.3 provides the linguistic information about the criteria above. The delivery criteria and the other criteria in Table 1.3 were defined as trapezoidal fuzzy number and trapezoidal fuzzy number, respectively, based on the information provided by the business manager. The membership functions for cost and delivery time from the criteria are shown in Table 1.3. Ranges for the cost variable are shown in Figure 1.3. Linguistic information for delivery time are defined as “fastest,” “fast,” “acceptable,” and “delayed” in Figure 1.4. In Table 1.4, linguistic information is provided for the output variable. In this study, supplier performance has been used as output.

21

1 Fuzzy inference system in sustainable supplier

Table 1.3: Linguistic variables for inputs. Cost ($)

Cheap

Moderate

Expensive

(;;;)

(;;;)

(;;;)

Quality (%)

Low

Good

Excellent

Qualitative

(;;;)

(;;;)

(;;;)

Delivery (day) Quantitavive

Fastest (;;;)

Fast (;;;)

Acceptable (;;;)

Environmental competencies (%)

Low (;;;)

Average (;;;)

Good (;;;)

Quantitative

Delayed (;;;)

Qualitative ISO standards (Sayı)

Bad

Good

Excellent

Quantitative

(;;;)

(;;;)

(;;;)

Work safety and

Insufficient

Sufficient

Perfect

labor health (%)

(;;;)

(;;;)

(;;;)

Reputation (%)

Low

Moderate

Very good

Qualitative

(;;;)

(;;;)

(;;;)

Qualitative

Cheap

Moderate

Expensive

1

0.5

0 900

950

1000

1050

1100

1150

1200

1250

1300

Figure 1.3: Membership function for cost criteria.

In Table 1.4, linguistic information is provided for the output variable. In this study, supplier performance has been used as output. The Matlab screenshot for the input and output variables as described in Figure 1.6. Six of the rules established using the information in Table 1.3 are given in Table 1.5.

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Nurullah Umarusman and Turgut Hacivelioğullari

Fastest

Acceptable

Fast

Delayed

1

0.5

0 2

3

4

5

6

7

8

9

10

Figure 1.4: Membership funtion of delivery time criteria.

Table 1.4: Linguistic variables for output. Supplier performance (%) Quantitative

Low preference

Moderate preference

Secondary preference

Absolute preference

(;;;)

(;;;)

(;;;)

(;;;)

Low Preference

Moderate Preference

Secondary Preference

Absolute Preference

1

0.5

0 0

10

20

30

40

50

60

70

80

90

100

Figure 1.5: Membership function for supplier performance.

The rule view of the FIS developed to obtain the supplier performance value is shown in Figure 1.7. In Figure 1.7, the performance of the suppliers that the entity wants to evaluate in the supply process can be calculated using the rule view determined according to the defined rules. With the help of the previous period information of the enterprise, the information of the current suppliers for the next period has been

1 Fuzzy inference system in sustainable supplier

23

Figure 1.6: Fuzzification method and defuzzification method and, variables in the FIS editor.

evaluated in the established Mamdani-type FIS model. Table 1.6 presents the quantitative and qualitative information of 13 suppliers and the calculated performance percentages of the suppliers. It is possible to summarize the Supplier’s performances in Table 1.6 as follows: sustainable performance is defined as “moderate preference supplier for Supplier3, Supplier6, Supplier7, and Supplier8”. Suppliers whose sustainable performance is secondary preference are Supplier 11, Supplier12, and Supplier13. Sustainable performance for Supplier1, Supplier2, Supplier4, Supplier 5, Supplier9, and Supplier10 is “Absolute preference”. In addition to this assessment, a sustainable supplier review can be conducted in terms of rules defined using criteria in each dimension.

24

Nurullah Umarusman and Turgut Hacivelioğullari

Table 1.5: Selected among all rules. If Cost

Quality

Delivery

Env. comp.

ISO stand.

W.S. and L.H

Reputation Then Supplier pref.

Cheap

Low

Fastest

Low

Bad

Insufficient Low

Low preference

Cheap

Good

Fastest

Average Bad

Insufficient Low

Secondary preference

Moderate Excellent Delayed

Good

Excellent Perfect

Moderate Excellent Delayed

Low

Good

Insufficient Moderate

Secondary preference

Good

Perfect

Very good

Secondary preference

Sufficient

Low

Low preference

Expensive Excellent Acceptable Good

Expensive Low

Delayed

Average Good

Very good

Abs. preference

In the economic dimension, the performance of the supplier where the quality and cost criteria are input is shown in Figure 1.8. In Figure 1.8, it is preferred that the cost is low when selecting suppliers. When it is examined in terms of cost and delivery time, it is preferred that the cost is low. This relationship is shown in Figure 1.9. If an assessment is made between the quality and delivery time criteria, the company prefers the supplier with quality products with a short delivery time. For this reason, the shorter delivery time is more important. The 3D matrix for quality and delivery time is given in Figure 1.10. When the three economic criteria are compared, the company chooses the supplier according to operating cost, delivery time, and quality criteria. The supplier performance assessment for the “Env. Comp.” and “ISO stand” criteria selected from the environmental dimension is given in Figure 1.11. According to Figure 1.11, the increase in the number of ISO standards causes the X criteria to increase and vice versa. Therefore, it can be concluded that the two criteria are of equal importance within the framework of the defined rules. The relationship between the “work safety and labor health” and “reputation” criteria for supplier performance in terms of social dimension is shown in Figure 1.12. When these two criteria used according to the social dimension are considered, “reputation” has a higher priority in terms of defined rules. In other words, the company attaches more importance to the “reputation” level of the suppliers. A different assessment can be made in terms of the information in Table 1.6: Using the FIS within the TBL framework, there may be a relative order of priority between the criteria (inputs) of each dimension.

1 Fuzzy inference system in sustainable supplier

Figure 1.7: FIS rule view.

25

26

Nurullah Umarusman and Turgut Hacivelioğullari

Table 1.6: 13 Supplier’s calculated performance percentages. Suppliers

Economic

Environmental

Social

Cost Quality Delivery Env. ISO WSLH ($) (%) (day) comp. stand. (%) (%) (sayı)

Sustainbale supplier performance (%)

Reputation (%)















. Absolute

Supplier 















. Absolute

Supplier 















 Moderate

Supplier 















 Absolute

Supplier 

,













. Absolute

Supplier 

,













 Moderate

Supplier 

,













 Moderate

Supplier 

,













 Moderate

Supplier 

,













, Absolute

Supplier  ,













, Absolute

Supplier  ,













. Secondary

Supplier  ,













. Secondary

Supplier  ,













. Secondary

Supplier Performance

Supplier 

90 80 70 60 50 900 1000 1100 Cost

1200 1300

0

20

40

60

Quality

Figure 1.8: Relationship between cost and quality criteria.

80

100

Supplier Performance

1 Fuzzy inference system in sustainable supplier

27

90 80 70 60

900

50 2

1000 1100

4 6

Delivery

1200

8 10

Cost

1300

Supplier Performance

Figure 1.9: Relationship between cost and delivery time criteria.

90 80 70 60 50 2 4 0

6 Delivery

20 40

8

60 10

100

80

Quality

Figure 1.10: The relationship between delivery time and quality criteria.

1.5 Conclusion It is not always possible to have the same level of significance in all dimensions for real-world problems during supplier selection based on TBL. It is

28

Supplier Performance

Nurullah Umarusman and Turgut Hacivelioğullari

90 80 70 60 50 40 60

10 8

Environmental Competencies 80 2

100

6

4

ISO standarts

Figure 1. 11: The relationship between “Env. Comp.” and “ISO stand” criteria.

Supplier Performance

90 80 70 60 50

100 80 60 Reputation 40 20 0

0

20

40

60

80

100

Work Safety and Labor Health Figure 1.12: The relationship between “work safety and labor health” and “reputation” criteria.

actually very difficult to have the same perspective of TBL by businesses in the same sector but located in different countries with different levels of the human development index and economic development index. This makes supplier

1 Fuzzy inference system in sustainable supplier

29

selection difficult especially for businesses with international ties. If such businesses may continue their activities in line with national and international regulations, it will also increase the success of TBL. The criteria in sustainable supplier selection and conventional supplier selection have become very vital because selecting realistic criteria eases supplier selection and helps businesses retain their current positions in long term. Therefore, criteria must be selected based on TBL considering sectoral differences as well. Additionally, supplier selection criteria must be reviewed as each criterion has subcriteria and must be classified as quantitative and/or qualitative. This study evaluates Dickson’s criteria in terms of TBL and determines which criteria may be located in which dimension of TBL. Additionally, a literature review is conducted for the criteria used in sustainable supplier selection, and S-SSC is classified as quantitative and qualitative following the review. As a result of the literature research on the selection of suppliers in the agricultural machinery sector, five scientific studies have been reached. ANP, AHP, TOPSIS methods were used in four of these studies and the global criterion method in one of them. In these articles, Virender and Javant (2014) evaluated the green supplier using ANP in the agricultural-machinery industry. Šimunović et al. (2011) selected suppliers using AHP to purchase a part for the assembly of the agricultural machinery in the model proposed. Umarusman and Hacıvelioğulları (2018) used the global criterion method for supplier selection in the agricultural machinery sector. Calache et al. (2019) proposed a supplier evaluation model for agricultural machinery maintenance using fuzzy TOPSIS. Lu et al. (2019) conducted a study using the TOPSIS method proposed for probabilistic linguistic multiattribute group decisionmaking on supplier selection in new agricultural machinery products. These studies indicate that it should be focused on supplier selection in the agricultural machinery sector. With FISs used in this study, a new window has been opened into the approach to supplier selection problems in the agricultural machinery sector. This study analyzes the supplier selection problem of a farming machinery manufacturing company in Turkey according to TBL and solves it using Mamdanitype FIS. Table 1.1 was used to define the criteria for the problem, and the business manager determined the input variables for the three dimensions of sustainability based on previous supplier information. There are three criteria from economic dimension, two criteria from environmental dimension, and two criteria from social dimension. The criteria from the economic dimension are Dickson’s most popular criteria, which was an expected phenomenon. Additionally, “cost,” “delivery time,” and “number of obtained ISO standards” contain quantitative information while the rest of the total seven criteria have qualitative information. The qualitative data were defined by the business manager as possession percentage for environmental competencies, success percentage of “work safety and labor health” applications, and percentage of “reputation” level. The problem was modeled Mamdani-type inference system based on this information, and “supplier performance” percentages were defined for 13 suppliers. The acquired supplier performance percentages are

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Nurullah Umarusman and Turgut Hacivelioğullari

given in Table 1.6. The developed model is appropriate for the evaluation of current suppliers as well as new ones. Additionally, it is exemplary for a product to be supplied and may be used for other items. Should the company present a sustainable administrative performance by abiding to this study, the weaknesses in supplier selection process will decrease and the company will gain competitive advantages against rival firms in the long run. This application qualifies as a guide for decision makers especially in SMEs. Following the application, the relative priorities among the criteria were defined by comparing the criteria in all dimensions with each other. This comparison obviously does not present universal information but simply results from “the specific rules” defined for the said company in this sector. Izmir is logistically important due to its geopolitical position and having five different ports. Besides, it is one of Turkey’s focal in the agricultural and food industries because it is under the influence of the Mediterranean climate and has fertile soil. In Izmir, where modern agricultural machines are effectively used, many products are above Turkey’s average in terms of yield and quality. Concordantly, modern agricultural machine manufacturing has also developed. In Izmir, where the agriculture-industry-university cooperation network is so strong, this work carried out in the agricultural machinery sector, based on advanced technology, increased its competitiveness and contributed to its pioneering role in sustainably using natural resources.

References Abbasi A. and Asgari M.S. (2014). Supplier selection using adaptive neuro-fuzzy ınference system and fuzzy delphi. International Journal of Operations and Logistics Management, 3(4), 351–371. Ageron B., Gunasekaran A., and Spalanzani A. (2012). Sustainable supply management: An empirical study. International Journal of Production Economics, 140(1), 168–182. Akgün V.Ö. (2012). Tedarikçi Seçiminde Bulanık Çıkarım Sistemi Kurulmasına Yönelik Bir Uygulama. Sosyoteknik Sosyal Ve Teknik Arastirmalar Dergisi, 2(4), 78–96. Alhaddi H. (2015). Triple bottom line and sustainability: a literature review. Business and Management Studies, 2, 6–10. Alikhania R., Torabi S.A., and Altay N. (2019). Strategic supplier selection under sustainability and risk criteria. International Journal of Production Economics, 208, 69–82. Altuntaş C. 11th International strategic management conference 2015: Sustainable demand chain management: An alternative perspective for sustainability in the supply Chain, Procedia – Social and Behavioral Sciences 207: 262–273. Al Zaabi S., Al Dhaher N., and Diabat A. (2013). Analysis of interaction between the barriers for the implementation of sustainable supply chain management. The International Journal, Advanced Manufacturing Technology, 68, 895–905. Amindoust A., Ahmed S., Saghafinia A., and Bahreininejad A. (2012). Sustainable supplier selection: A ranking model based on fuzzy inference system. Applied Soft Computing, 12(6), 1668–1677. Amindoust A. and Saghafinia A. (2014). Supplier evaluation using fuzzy inference systemssupply chain management under fuzziness. In: Kahraman C. and Öztayşi B., editors, Recent developments and techniques. Berlin-Heidelberg: Springer- Verlag, 3–19.

1 Fuzzy inference system in sustainable supplier

31

Amindoust A. and Saghafinia A. (2017). Textile supplier selection in sustainable supply chain using a modular fuzzy inference system model. The Journal of The Textile Institute, 108(7), 1250–1258. Ansari Z.N. and Kant R. (2017). A state-of-art literature review reflecting 15 years of focus on sustainable supply chain management. Journal of Cleaner Production, 142, 2524–2543. Asemi A., Baba M.S., and Asemi A. (2014). Intelligent MCDM method for supplier selection under fuzzy environment. International Journal of Information Science and Management, 12, 33–40. Asghari M. and Abrishami S.J. Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management Bali, Indonesia, January 7–9, 2014:2437–2444. Asgari M.S., Abbasi A., and Alimohamadlou A. (2016). Comparison of ANFIS and FAHP-FGP methods for supplier selection. Kybernetes, 45, 474–489. Ashby A., Leat M., and Hudson-Smith M. (2012). Making connections: a review of supply chain management and sustainability literature. Supply Chain Management: An International Journal, 17(5), 497–516. Ashtarinezhad S.E., Arfaraz A.H., and Navabakhsh M. (2018). Supplier evaluation and categorize with combine fuzzy dematel and fuzzy ınference system. Data in Brief, 18, 1149–1156. Azadi M., Jafarian M., Saen R.F., and Mirhedayatian M.S. (2015). A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Computers & Operations Research, 54, 274–285. Azadnia A.H., Saman M.Z.M., and Wong K.Y. (2015). Sustainable supplier selection and order lotsizing: an ıntegrated multi-objective decision-making process. International Journal of Production Research, 53(2), 383–408. Doi:10.1080/00207543.2014.935827 Bache J.C., Parnaby J.R., and Tobias A.M. (1987). Supplier development systems. International Journal of Technology Management, 2(2), 219–228. Barve A. and Muduli K. (2013). Modelling the challenges of green supply chain management practices in Indian mining industries. Journal of Manufacturing Technology Management, 24(8), 1102–1122. Bede B. (2013). Fuzzy inference. In: Mathematics of fuzzy sets and fuzzy logic. Studies in fuzziness and soft computing. Berlin: Springer. Bektur G. (2018). A combined approach for sustainable supplier selection: a case study for a manufacturing firm. International Journal of Engineering Technologies-IJET, 4(3), 129–135. Bhowmick T., Md TR H., and Mondal P.K. A case study of appropriate supplier selection of RFL industry by using Fuzzy Inference System (FIS), International Conference on Mechanical, Industrial and Energy Engineering 2014;25–26: 1–5. Büyüksaatçı Kiriş S. and Yılmaz Börekçi D. (2018). Sürdürülebilir Liman İşletmeciliğini Yönlendirici ve Engelleyici Faktörler: Bir Üçlü Bilanço Yaklaşımı. Istanbul Gelisim Üniversitesi Sosyal Bilimler Dergisi, 5(1), 192–220. Büyüközkan G. and Çifçi G. (2011). A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Computers in Industry, 62(2), 164–174. Calache L.D.D.R., Pedroso C.B., Lima Júnior F.R., and Carpinetti L.C.R. (2019). Supplier selection and evaluation model proposal for industrial maintenance based on Fuzzy-TOPSIS. Gestão & Produção, 26(2), e3565. https://doi.org/10.1590/0104-530X-3565-19 Chaharsooghi S.K. and Ashrafi M. (2014). Sustainable supplier performance evaluation and selection with neofuzzy topsıs method. International Scholarly Research Notices, 2014, Article ID 434168, 1–10. Cherkassky V. (1998). Fuzzy inference systems: A critical review. In: Kayak O., Zadeh L.A., et al Eds., Computational intelligence: Soft computing and fuzzy-neuro integration with applications. Springer, 177–197. Caroll A.B. and Buchhollz A.K. (2008). Business and society: Ethics and stakeholder management (7th ed.). Mason, Ohio: Thomson/South-Western.

32

Nurullah Umarusman and Turgut Hacivelioğullari

Carrera D.A. and Mayorga R.W. (2008). Supply chain management: a modular Fuzzy Inference System approach in supplier selection for new product development. Journal of Intelligent Manufacturing, 19(1), 1–12. Carter C.R. and Rogers D.S. (2008). Framework of sustainable supply chain management: moving toward new theor. International Journal of Physical Distribution & Logistics Management, 38(5), 360–387. Chen J., Wu M.H., Jiang W.R., Wang A.B., and Yan J.H. (2009). Study a fuzzy ınference system on the supplier evaluation in e-manufacturing. Applied Mechanics and Materials, 16(19), 189–192. Cheraghi S.H., Dadashzadeh M., and Subramanian M. (2004). Critical success factors for supplier selection: an update. Journal of Applied Business Research, 20(2), 91–108. Cordon O., Herrera F., Hoffmann F., and Magdalena L. (2001). Genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. Singapore: World Scientific Publishing. Cuthbertson R. (2011). The need for sustainable supply chain management. In: Cetinkaya B., Cuthbertson R., Ewer G., Klaas-Wissing T., Piotrowicz W., and Tyssen C., editors, Sustainable chain management, practical ıdeas for moving towards best practice. Berlin: Springer-Verlag, 3–13. de Boer L., Labro E., and Morlacchi P. (2001). A review of methods supporting supplier selection. European Journal of Purchasing and Supply Management, 7(2), 75–89. https://doi.org/ 10.1016/S0969-7012(00)00028-9 Dempsey W.A. (1978). Vendor selection and the buying process. Industrial Marketing Management, 7, 257–267. Deshmuk A.J. and Chaudhari A.A. A review for supplier selection criteria and methods, technology systems and management, First International Conference 2011, ICTSM Mumbai, India: 25–27. Dickson G.W. (1966). An analysis of vendor selection systems and decisions. Journal of Purchasing, 1, 5–17. Ding H., Benyoucef L., and Xie X. A simulation-optimization approach using genetic search for supplier selection, in: Chick S., Sanchez P.J., Ferrin D., and Murrice D.J. (Eds.), Proceedings of the 2003 Winter Simulation Conference. Ecemiş O. and Yaykaşlı M. (2018). An application on sustainable supplier selectıon by multi-criteria decision making methods. Akademik Sosyal Arastirmalar Dergisi, 6(83), 382–399. Elkington J. (1998). Cannibals with forks: the triple bottom line of twenty-first century business. Stony Creek, CT: New Society Publishers. Er Kara M., Ö Y., Ümit S., and Fırat O. (2016). Sustainable supplier evaluation and selection criteria. In: Erdoğdu M., Yüksel Mermod A., and Aşkun Yıldırım O.B., editors, Social and economic perspectives on sustainability. London: IJOPEC Publication, 159–167. Feng G. (2010). Analysis and synthesis of fuzzy control systems a model-based approach. Boca Raton: CRC Press. Ghadimi P., Azadnia A.H., Heavey C., Dolgui A., and Can B. (2016). A review on the buyer–supplier dyad relationships in sustainable procurement context: past, present and future. International Journal of Production Research, 54(5), 1443–1462. Ghadimi P., Dargib A., and Heavey C. (2017). Sustainable supplier performance scoring using audition check-listbased fuzzy inference system: A case application in automotive sparepart industry. Computers & Industrial Engineering, 105, 12–27. Ghoushchi S.J., Milan M.D., and Rezaee M.J. (2018). Evaluation and selection of sustainable suppliers in supply chain using new GP-DEA model with imprecise data. Journal of Industrial Engineering International, 14, 613–625. Gimenez C. and Tachizawa E.M. (2012). Extending sustainability to suppliers: a systematic literaturere view. Supply Chain Management: An International Journal, 17(5), 531–543.

1 Fuzzy inference system in sustainable supplier

33

Giunipero L.C., Hooker E.R., and Denslow D. (2012). urchasing and supply management sustainability: Drivers and barriers. Journal of Purchasing and Supply Management, 18(4), 258–26. Goebel P., Reuter C., Pibernik R., and Sichtmann C. (2012). The influence of ethical culture on supplier selection in the context of sustainable sourcing. International Journal of Production Economics, 140(1), 7–17. Gorzalczany M.B. (2002). Computational intelligence systems and applications neuro-fuzzy and fuzzy neural synergisms. Heidelberg: Springer-Verlag. Govindan K. and Hasanagic M. (2018). A systematic review on drivers, barriers, and practices towards circular economy: a supply chain perspective. International Journal of Production Research, 56(1–2), 278–311. Govindan K., Rajendran S., Sarkis J., and Murugesan P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of Cleaner Production, 98(1), 66–83. Gören H.C. (2018). A decision framework for sustainable supplier selection and order allocation with lost sales. The Journal of Cleaner Production, 183, 1156–1169. Grover R., Grover R., Rao V.B., and Kejriwal K. (2016). Supplier selection using sustainable criteria in sustainable supply chain management. The International Journal of Economics and Management Engineering, 10(5), 1775–1779. Güneri A.F., Ertay T., and Yucel A. (2011). An approach based on ANFIS input selection and modeling for supplier selection problem. Expert Systems with Applications, 38(12), 14907–14917. Hansen E.G., Große-Dunker F., and Reichwald R. (2009). Sustainability ınnovation cube: a framework to evaluate sustainability-oriented ınnovations. International Journal of Innovation Management, 13(4), 683–713. Heizer J., Render B., and Munson C. (2017). Principles of operations management sustainability and supply chain management (10th ed.). Boston: Pearson Education Limited. Ho W., Xu X., and Dey P.K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. European Journal of Operational Research, 202(1), 16–24. Humphreys P., McIvor R., and Chan F. (2003). Using case-based reasoning to evaluate supplier environmental management performance. Expert Systems with Applications, 25, 141–153. Jang J.-S.R. (1997). Neuro-fuzzy and soft computing: A computational approach to learning and machine intelligence. Upper Saddle River: Prentice Hall. Kopnina H. (2017). Sustainability: New Strategic Thinking for Business. Environment Development and Sustainability, 19, 27–43. Kopnina H. and Blewitt J. (2014). Sustainable business: Key issues. New York: Routledge. Kumara D. and Rahman Z. (2015). Sustainability adoption through buyer supplier relationship across supply chain: A literature review and conceptual framework. International Strategic Management Review, 3, 110–127. Lamming R. and Hampson J. (1996). The environment as a supply chain management issue. British Journal of Management, 7, Special Issue, 45–56. Laurin F. and Fantazy K. (2017). Sustainable supply chain management: a case study at IKEA. Transnational Corporations Review, 9(4), 309–318. VOL. 9, NO. 4, 309–318 Li J., Yang L., Qu Y., and Sexton G. (2018). An extended Takagi–Sugeno–Kang inference system (TSK+) with fuzzy interpolation and its rule base generation. Soft Comput, 22, 3155–3170. Li J., Fang H., and Song W. (2019). Sustainable supplier selection based on SSCM practices: A rough cloud TOPSIS approach. Journal of Cleaner Production, 222(10), 606–621. Lima Junior F.R., Osiro L., and Carpinetti L.C.R. (2013). A fuzzy inference and categorization approach for supplier selection using compensatory and non-compensatory decision rules. Applied Soft Computing, 13, 4133–4147.

34

Nurullah Umarusman and Turgut Hacivelioğullari

Liu H.T. and Wang W.K. (2009). An integrated fuzzy approach for provider evaluation and selection in third-party logistics. Expert Systems with Applications, 36(3), 4387–4398. Lu J., Wei C., Wu J., and Wei G. (2019). Topsis method for probabilistic linguistic MAGDM with entropy weight and its application to supplier selection of new agricultural machinery products. Entropy, 21, 953. Luthra S., Govindan K., Kannan D., Kumar S., Chandra M., and Garg P. (2017). An integrated framework for sustainable supplier selection and evaluation in supply chains. Journal of Cleaner Production, 140(3), 1686–1698. Majumdar A. (2011). In: Majumdar A., Soft computing in textile engineering. New Delhi: Woodhead Publishing Limited. 159–177. Mamdani E.H. (1974). Application of fuzzy algorithms for simple dynamic plant. Proceedings of the IEEE, 121, 1585–1588. Mamdani E.H. and Assilian S. (1975). An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7(1), 1–13. Massaroni E., Cozzolino A., and Wankowicz E. (2015). Sustainability in supply chain management – a literature review. Sinergie Italian Journal of Management, 33(98), 331–355. Mc Kenzie S. (2004). Social sustainability: Towards some definitions. Hawke Research Institute Working Paper Series No:27. Magill: Hawke REsearch Institute. Meinlschmidt J., Schaltenbrand B., Busse C., and Förstl K. (2013). Environmental and sustanable performance from a Supply Chain Management. In: Clausen U., Hompel M., and Klumpp M., editors, Efficiency and Logistics. Berlin: Springer-Verlag, 175–184. Memaria A., Dargib A., Jokara M.R.A., Ahmad R., and Abdul Rahim A.R. (2019). Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. Journal of Manufacturing Systems, 50, 9–24. Mohammadi E.K., Talaie H.R., Safari H., and Salehzadeh R. (2018). Supplier evaluation and selection for sustainable supply chain management under uncertainty conditions. International Journal Of Sustainable Engineering, 11(6), 382–396. Mukherjee K. (2017). Supplier selection an mcda-based approach. India: Springer (India) Pvt. Ltd. Mukherjee K., Sarkar B., and Bhattacharyya A. (2013). Supplier selection by f-compromise method: A case study of cement industry of NE India. International Journal of Computational Systems Engineering, 1(3), 162–174. Nielsen I.E., Banaeian N., Golinska P., Mobli H., and Omid M. (2014). Green Supplier Selection Criteria: From a Literature Review to a Flexible Framework for Determination of Suitable Criteria. In: Golinska P., editör, Logistics operations, supply chain management and sustainability. Switzerland: Springer International Publishing, 79–100. Niraj M. and Kumar S. (2011). Modeling for supplier selection through fuzzy logic. International Journal of Scientific & Engineering Research, 2(8), 1–5. Özçelik F. and Avcı Öztürk B. (2014). A research on barriers to sustainable supply chain management and sustainable supplier selection crıteria. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 16(2), 259–279. Özdemir A.İ. (2004). Tedarik zinciri yönetiminin gelişimi, süreçleri ve yararları. Erciyes Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi, 23, 87–96. Öztayşi B., Behret H., Ö K., Uçal Sarı İ., and Kahraman C. (2013). Fuzzy inference systems for disaster response. In: Vitoriano B., Montero J., and Ruan D., editors, Decision aid models for disaster management and emergencies. Paris: Atlantis Press, 75–94. Panigrahi S.S., Bahinipati B., and Jain V. (2018). Sustainable supply chain management: A review of literature and implications for future research. Management of Environmental Quality: An International Journal, https://doi.org/10.1108/MEQ-01-2018-0003

1 Fuzzy inference system in sustainable supplier

35

Pal O., Gupta A.K., and Garg R.K. (2013). Supplier selection criteria and methods in supply chains: A review. International Journal of Social, Education, Economics and Management Engineering, 7(10), 1395–1401. Parmar V. and Shah H.G. (2016). A literature review on supply chain management barriers in manufacturing organization. The International Journal of Engineering Development and Research, 4(1), 26–42. Paul S.K. (2015). Supplier selection for managing supply risks in supply chain: a fuzzy approach. The International Journal of Advanced Manufacturing Technology, 79(1–49), 657–664. Popovic T., Kraslawski A., Barbosa-Póvoa A., and Carvalho A. (2017). Quantitative indicators for social sustainability assessment of society and product responsibility aspects in supply chains. Journal of International Studies, 10(1), 9–36. Pourjavad E. and Shahin A. (2018). Hybrid performance evaluation of sustainable service and manufacturing supply chain management: An integrated approach of fuzzy dematel and fuzzy inference system. International System in Accounting, Finance and Management, 25, 134–147. Rabbani M., Foroozesh N., Mousavi S.M., and Farrokhi-Asl H. (2017). Sustainable supplier selection by a new decision model based on interval-valued fuzzysets and possibilistic statistical reference point systems under uncertainty. International Journal of Systems Science Operations & Logistics, 6(2), 162–178. Ravindran A.R. and Warsing D.P. (2013). Supply chain engineering models and applications. Boca Raton: CRC Press Taylor & Francis Group. Rezaei J. (2019). Sustainable supplier selection: A process view. In: Sarkis J. and Elgar E., editors, Handbook on the sustainable supply chain, handbook on the sustainable supply chain. Cheltenham: Edward Elgar Publishing, 136–147. Roa C.P. and Kiser G.E. (1980). Educational buyer‟s perception of vendor attributes. Journal of Purchasing and Materials Management., 16, 25–30. Sabaghi M., Mascle C., Baptiste P., and Rostamzadeh R. (2016). Sustainability assessment using fuzzy-inference technique (SAFT): A methodology toward green products. Expert Systems With Applications, 56, 69–79. Sarkis J. and Dhavale D.G. (2015). Supplier selection for sustainable operations: A triple-bottomline approach using a Bayesian framework. The International Journal of Production Economics, 166, 177–191. Seçkin F. (2018). The development of sustainability concept on supply chain management and supplier selection. Aurum Journal of Engineering Systems and Architecture, 2(2), 45–64. Seuring S. and Müller M. (2008). From a literature review to a conceptual framework for fustainable supply chain management. Journal of Cleaner Production, 16, 1699–1710. Shukla K.K. and Tiwari A.K. (2013). Efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems. London: Springer. Sisco C., Chorn B., Pruzan-Jorgensen P.M., and Compact G. (2010). Supply chain sustainability: A practical guide for continuous improvement. Norway: United Nations Global Compact. Sivanandam S.N., Sumathi S., and Deepa S.N. (2007). Introduction to fuzzy logic using MATLAB. Berlin Heidelberg: Springer-Verlag. Song W., Xu Z., and Liu H.-C. (2017). Developing sustainable supplier selection criteria for solar airconditionermanufacturer: An integrated approach. Renewable and Sustainable Energy Reviews, 79, 1461–1471. Sremac S., Zavadskas E.K., Matic B., Kopic M., and Stevic Z. (2019). Neuro-fuzzy inference systems approach to decision support system for economic order quantity. Economic ResearchEkonomsk Istrazivanja, 32(1), 1114–1137. Sugeno M. (1985). Industrial applications of fuzzy control. Amsterdam: Elsevier.

36

Nurullah Umarusman and Turgut Hacivelioğullari

Sugeno M. and Kang G.T. (1988). Structure identification of fuzzy model. Fuzzy Sets System, 28(1), 15–33. Šimunović K., Draganjac T., and Lujić R. (2011). Supplier selection using a multiple criteria decision making method. Strojarstvo, 53(4), 293–300. Şen S., Başligil H., Şen C.G., and Baraçli H. (2008). A framework for defining both qualitative and quantitative supplier selection criteria considering the buyer–supplier integration strategies. International Journal of Production Research, 46(7), 1825–1845. Tahriri F., Mousavi M., Hozhabri Haghighi S., and Zawiah Md Dawal S. (2014). The application of fuzzy Delphi and fuzzy inference system in supplier ranking and selection. Journal of Industrial Engineering International, 10(3), 1–16. Takagi T. and Sugeno M. (1985). Fuzzy identification of systems and its application to modeling and control. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 15, 116–132. Thiruchelvam S. and Tookey J.E. (2011). Evolving trends of supplier selection criteria and methods. International Journal of Automotive and Mechanical Engineering, 4, 437–454. Tuczek F. and Wakolbinger T. (2018). A meta-analysis of sustainable supplier selection approaches. In: Qudrat-Ullah H., editor, Innovative Solutions for Sustainable Supply Chains Switzerland. Springer International Publishing AG. 55–80. Tundys B. Sustainable supplier selection criteria in the context of developing of green supply chain, 2016 5th IEEE Int. Conf. on Advanced Logistics & Transport (ICALT),147–153. Uçal Sarı İ., Çayır Ervural B., and Bozat S. (2017). Analyzing criteria used in supplier evaluation by dematel method in sustainable supply chain management and an application to health sector. Pamukkale University Journal of Engineering Sciences, 23(4), 477–485. Uluskan M. and Godfrey A.B. (2018). Business environment-supply chain framework and benchmarking supply chain structures: Haiti versus China. Benchmarking: An International Journal, 8(5), 3021–3044. Umarusman N. (2019). Multiple objective decision-making methods in supplier selection. In: Mangla S.K., Luthra S., Jakhar S.K., Kumar A., and Rana N.P., editors, Sustainable Procurement in Supply Chain Operations. Boca Raton: CRC Press, 177–212. Umarusman N. and Hacıvelioğulları T. (2018). Slution proposal for supplier selection problem: An application in agricultural machinery sector with global criterion method. Dokuz Eylul University Faculty of Economics and Administrative Sciences Journal, 33(1), 353–368. Vijfvinkel S., Bouman N., and Hessels J. (2012). Environmental sustainability and financial performance of SMEs. This research has been partly financed by SCALES. Scientific Analysis of Entrepreneurship and SMEs, 1–47. Virender P. and Jayant A. (2014). A green supplier selection model for agricultural-machinery ındustry. International Journal of Applied Engineering Research, 9(5), 597–605. Walker H., Di Sisto L., and McBain D. (2008). Drivers and barriers to environmental supply chain management practices: Lessons from the public and private sectors. Journal of Purchasing and Supply Management, 14(1), 69–85. Wan Mahmood W.H., Tukimin R., Muhamad M.R., and Yusup M.Z. Sustaınable Criteria In A Supplier Selection: A Pre-Revıew, International Symposium on Research in Innovation and Sustainability 2014 (ISoRIS ’14) 15–16 October 2014, Malacca, Malaysia, 1841–1844. Weber C.A., Current J.R., and Benton W.C. (1991). Vendor selection criteria and methods. European Journal Of Operational Research, 50, 1–17. World Commission on Environment and Development (WCED). (1987). Report of the world commission on environment and development: our common future. New York: United Nations. Yang -C.-C. and Chen B.-S. (2006). Supplier selection using combined analytical hierarchy process and grey relational analysis. Journal of Manufacturing Technology Management, 17(7), 926–941.

1 Fuzzy inference system in sustainable supplier

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Yang M., Movahedipour M., Zeng J., Xiaoguang Z., and Wang L. (2017). Analysis of success factors to implement sustainable supply chain management using interpretive structural modeling technique: a real case perspective. Mathematical Problems in Engineering, 1(14), https://doi. org/10.1155/2017/7274565 Yardımcı A.G. and Karpuz C. (2017). Fuzzy rock mass rating: soft-computing-aided preliminary stability analysis of weak rock slopes. In: Ceryan N., Editor, Handbook of research on trends and digital advances in engineering geology IGI Press. 97–131. Yücel A. and Güneri A.F. (2010). Application of adaptive neuro fuzzy inference system to supplier selection problem. Sigma Journal of Engineering and Natural Sciences, 28, 224–234. Zadeh L.A. (1975). The concept of a linguistic variable and its applications to approximate reasoning–I. Information Sciences, 8(3), 199–249. Zhang Z.H. Designing sustainable supply chain networks. A thesis in the department of Concordia Institute for Information Systems Engineering 2011: 1–129. Zhou Z., Cheng S., and Hua B. (2000). Supply chain optimization of continuous process ındustries with sustainability considerations. Computers and Chemical Engineering, 24(2–7), 1151–1158. Zimmer K., Fröhling M., and Schultmann F. (2016). Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development. International Journal of Production Research, 54(5), 1412–1442.

Aalok Kumar, Ramesh Anbanandam, Golam Kabir, Yiğit Kazançoğlu

2 Green and sustainable freight logistics for improving supply chain sustainability: a bibliometric analysis Abstract: The concept of green and sustainable freight transport practices is evolving rapidly and attracted the attention of academic researchers and transport practitioners. This chapter provides a review of green and sustainable freight transport practices measure for providing a better understanding of evolving research fields. The literature review considered 20 years of research data for analyzing the research pattern. This chapter uses bibliometric and network analysis for analyzing the scientific mapping of green and sustainable freight transport practices. The chapter also analyzes the most influencing research articles of the field, top contributing authors, organizations, and key research areas related to the field. The most explored research clusters are presented along with future research directions. Keywords: bibliometric literature review, green freight transport, sustainable development, sustainability

2.1 Introduction In the last two decades, environmental management has become an emerging topic of various management disciplines. The environmental and social sustainability practices significantly contributing to improve the sustainability performance of freight transport business (Behrends, 2011; Kiani Mavi et al., 2019; Kumar and Anbanandam, 2019; Sanchez-Rodrigues et al., 2010; Shankar et al., 2019). The term green and sustainable development are most commonly used in supply chain research (McKinnon et al., 2015; The World Bank, 2012). Nevertheless, the green and sustainability issues in the freight transport industry remains very complex (Lai et al., 2011). The road freight Aalok Kumar, Department of Management Studies, Indian Institute of Technology Roorkee, UK, India; Department of Industrial & System Engineering, University of Regina, Saskatchewan, Canada Ramesh Anbanandam, Department of Management Studies, Indian Institute of Technology Roorkee, UK, India Golam Kabir, Department of Industrial & System Engineering, University of Regina, Saskatchewan, Canada Yiğit Kazançoğlu, Department of International Logistics Management, Yasar University, Izmir, Turkey https://doi.org/10.1515/9783110628593-002

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Aalok Kumar, Ramesh Anbanandam, Golam Kabir, Yiğit Kazançoğlu

transport industry is regarded as the most environmentally degraded mode of transport (Engström, 2016), and need to discuss its improvement by proposing green and sustainable freight mobility practices (Sureeyatanapas et al., 2018). Freight transport companies facing many problems to integrate green freight transport practices for improving the sustainability performance of the freight transport industry (Shankar et al., 2018). The global freight movement is not only viable for economic prosperity but also has to manage the environmental and social welfare of the society (Kumar and Anbanandam, 2019). The freight transportation industry uses multiple modes of transport such as airways, roadways, railways, and waterways (Steadieseifi et al., 2014), but their environmental sustainability measurement is mostly ignored. The freight transport system causes the multiple environmental externalities. These externalities are related to greenhouse gases (GHG) emission, air pollution, noise, land use, and safety hazards (Bask and Rajahonka, 2017). The freight transportation system is highly dependent on fossil fuels (Kelle et al., 2019). The developing nations face many challenges to promote the social sustainability of the freight transport industry (Kumar and Anbanandam, 2019), and promotion of intermodal freight transport system would help to improve the environmental sustainability of freight transport industry (Kumar and Ramesh, 2018). Nevertheless, the relevant literature rarely considers the involvement of green and sustainable freight transport (GSFT) practices for improving supply chain sustainability performance (Solomon et al., 2019). The social and environmental sustainability practices measurement can also support the decision makers for formulating green policies for the logistics industry (Dou et al., 2014). This chapter highlights the research articles that discuss the GSFT practices of the freight logistics industry. This chapter presented a detailed bibliometric analysis-based review of green freight transport research. This chapter is based on the following research objectives: – To present the snapshot of the GSFT practices for improving supply chain sustainability performance. – To highlight the influence of research articles, researchers, and research domains based on bibliometric analysis. – To present the future research direction in the field of GSFT discipline. The answer to the above objectives is addressed in the following way. First, a detailed literature search is conducted with a time span of 20 years. Second, a bibliometric analysis tool (Vos Viewer) is used to plot the scientific mapping of the selected field. Third, the proposed research scope is presented. The remainder of the chapter is arranged in the following manner. The methodology of the literature survey is presented in Section 2.2. Section 2.3 highlights the result analysis of various dimensions. The literature discussion is presented in Section 2.4. The conclusion of the literature review is given in the last section.

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2.2 Literature review procedure The aim of a literature review is to identify, classify, and assess the body of knowledge in an organized, objective, and perspective manner (Tranfield et al., 2003). The purpose of structural literature review is to handle the huge amount of scientific literature and also analyze the used methods, which provide deeper analysis and the relationship of research fields (Raghuram et al., 2010). This chapter is presenting the bibliometric analysis of GSFT practices in three ways; first, compare to other text mining procedures such as content analysis, bibliometric analysis can handle several hundred articles with less computational complexity (Feng et al., 2017). Second, the bibliometric based literature review provides an in-depth analysis of the relationship among various research disciplines, authors, citations, and cocitations. Third, the visualization of computational results is clear to researchers for reading and to identify research gaps in the selected field.

2.2.1 Literature data screening and analysis After the literature review topic is finalized, three freight logistics researchers were consulted for the most suitable search keywords. The keywords “freight transportation,” “freight logistics,” “green freight transport*,” “sustainable freight,” “low carbon freight transport,” and “freight supply chain” are finalized for identifying GSFT practices. The focus of this measure is to identify GSFT practices from the prespective of sustainable development. Based on the keywords mentioned, four different search combinations are generated with Boolean operators: (1) freight transport AND green AND supply chain, (2) freight logistics AND green AND supply chain, (3) sustainable AND freight transport OR logistics, and (4) green practices OR sustain* practices AND freight transport. The above combination of literature is searched with the Scopus database. Fahimnia et al. (2015) recommended that the Scopus database is more robust than the Web of Science database because it contains more than 21,000 titles from 5,000 publishers. Chicksand et al. (2012) suggested that the Scopus database is best for analyzing supply chain and logistics management research. The search results are limited to the English language and for the period of 2001–November 2019. The search string used is the comprehensive search of criteria in title, abstract, keywords search in the Scopus database. The second stage is to limit the search to the business, management and accounting and decision science area. The other freight transport practices are also considered as urban freight, city logistics, multimodal transport, synchormodal transport, low emission transport, sustainable freight mobility, and green road transport for assessing the sustainability performance of freight transportation. The initial data search found 1,321 articles with a combination of search keywords. After careful consideration and removal of not relevant studies, 171 (127 articles, 27 book chapters,

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13 literature reviews, 2 books) papers are found relevant and included for the final bibliometric analysis. The bibliometric research analysis consists of four steps proposed by (Hurter, 2015). These four steps are as follows: (a) formation of search keywords with multiple combinations, (b) data filtration and its formatting, (c) primary analysis, and (d) detailed data analysis of search results. The scientific mapping of searched literature is performed with the VOS viewer (https://www.vosviewer.com/). The database of searched literature is formatted in a .csv format and all relevant papers are reviewed and validated. The research field analysis and scientific mapping of research topics are presented in form of publication over the years, annual citation value, co-citation analysis, co-citation network of cited sources, co-citation network of authors, and keywords analysis. The distribution of the research field is visualized is performed with the VOS viewer (Noyons et al., 1999). The VOS viewer software is a graphic-interface and mapping visualization software for text mining (van Eck and Waltman, 2010). The GSFT literature review analysis and science mapping are presented in the next section.

2.3 Results 2.3.1 Publication and citation structure The research on GSFT for improving logistics business sustainability is having an increasing trend. Figure 2.1 shows the increasing trend of published papers in the last 20 years.

30

26 23

No. of articles

25

22

21

20

15

15

15

15

9

10 5

3 1

3

5

4 2

3 1

1

2

0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Publication year

Figure 2.1: Publication statistics of GSFT research from 2001–2019.

The publication on GSFT topic declined in the year 2016 but again showed an increasing trend of the scientific publication. The green and sustainable freight transportation research increased in the last 5 years and published 67.5% of the total research articles in the last 5 years. Similarly, Figure 2.2 representing the area-wise distribution of GSFT

2 Green and sustainable freight logistics for improving supply chain sustainability

43

6% 7% 34%

8%

Business, management and accounting Engineering Decision sciences

10%

Social sciences Economics, econometrics, and finance Environmental science Computer science

16% 19%

Figure 2.2: Distribution of GSFT research over the disciplines.

articles and found that most of the articles (34%) fell under business, management, and accounting areas.

2.3.2 Influential nation/region and authors In this section, we analyze the countries with more publications in the field of the GSFT field. Table 2.1 reveals that the top ten countries are contributing significantly in the field of green and sustainable freight logistics practices. Table 2.1 also highlights the contribution in citation and total link strength of a country. In developing nations studies, India and Brazil are significantly focused on green and sustainable freight transportation practices, whereas the UK and European countries significantly consider the importance of GSFT practices in their supply chain processes. Figure 2.3 highlights the visual map of countries considering the importance of GSFT in their supply chain processes. Table 2.2 highlights the top studies discussing the importance of green and Table 2.1: Top 10 countries contribution to GSFT practices research. #

Country

         

United Kingdom Sweden United states Italy Germany India Netherlands Brazil Spain Belgium

No. of papers

Citation

Total link strength

         

         

         

Serbia

India

United states

Belgium

Norway

Italy

United kingdom

Turkey Kazakhstan

Thailand

Germany

Figure 2.3: Top countries network in publication of GSFT research.

Nigeria

Brazil

Finland

Sweden

Netherlands

Denmark Austia

Morocco

Singapore

Canada

44 Aalok Kumar, Ramesh Anbanandam, Golam Kabir, Yiğit Kazançoğlu

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Table 2.2: Most influential research work focusing on GSFT practices. #

Authors

Title

Source title



Steadieseifi et al. () Goldman and Gorham () Limbourg and Jourquin () Limbourg and Jourquin () Meyer and Winebrake ()

Multimodal freight transportation planning: a literature review Sustainable urban transport: four innovative directions

European Journal of Operational Research Technology in Society

Optimal rail-road container terminal locations on the European network

Transportation Research Part E: Logistics and Transportation Review Journal of Cleaner Production

















Building environmental sustainability: empirical evidence from logistics service Ppoviders Modeling technology diffusion of complementary goods: the case of hydrogen vehicles and refueling infrastructure Iannone The private and social cost efficiency of () port hinterland container distribution through a regional logistics system Demir et al. A selected review on the negative () externalities of freight transportation: modeling and pricing Schliwa et al. Sustainable city logistics – making cargo () cycles viable for urban freight transport Nuzzolo and Comi ()

 Ülkü ()

 Lam and Lai ()  SanchezRodrigues et al. ()  Reis ()

Urban freight demand forecasting: a mixed quantity/delivery/vehicle-based model Dare to care: shipment consolidation reduces not only costs but also environmental damage Developing environmental sustainability by ANP-QFD approach: the case of shipping operations The impact of logistics uncertainty on sustainable transport operations

Analysis of mode choice variables in short-distance intermodal freight transport using an agent-based model  Marchet et al. Environmental sustainability in logistics () and freight transportation: a literature review and research agenda  Davies et al. Assessing the impact of ICT on UK () general haulage companies

Citation  





Technovation



Transportation Research Part A: Policy and Practice



Transportation Research Part E: Logistics and Transportation Review Research in Transportation Business and Management Transportation Research Part E: Logistics and Transportation Review International Journal of Production Economics









Journal of Cleaner Production



International Journal of Physical Distribution and Logistics Management Transportation Research Part A: Policy and Practice



Journal of Manufacturing Technology Management



International Journal of Production Economics





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Aalok Kumar, Ramesh Anbanandam, Golam Kabir, Yiğit Kazançoğlu

sustainable practices in global supply chain management. Steadieseifi et al. (2014) discussed the importance of multimodal freight transport network design for improving the sustainability performance of freight distribution. The work of (Goldman and Gorham, 2006) highlights the sustainability practices of urban freight distribution. The scientific relation map of top-cited work in presented in Figure 2.4.

2.3.3 Bibliometric mapping analysis In this section, the authors analyze the co-citation of GSFT articles that cited references, researchers, and cited sources. The analysis used to find the pattern in the emerging field of research and discuss the future research path.

2.3.3.1 Citation analysis Citations are used as a measurement of influence in the research area. If an article having a high number of citations, the publication is regarded as the most influential research. A co‐citation is defined as a link between a pair of research articles cited by a third (Eto, 2016). The co-citation method helps to identify the pattern of a research domain, and to identify the relationship among the research fields (Pierce, 1990). If a paper cited two papers, then it might be that two cited papers have a close relationship (White and Griffith, 1981). The advantage of doing co-citation analysis is to find a cluster of research fields and graphically visualize the distribution of networks. VOS viewer software provides three types of co-citation analysis. The co-citation from references represents the number of nodes linked to other sources. The reference co-citation network of selected articles is shown in Figure 2.5. 2.3.3.1.1 Co-citation network analysis The co-citation analysis of the journal provides information regarding the influence of the journal. Table 2.3 shows the top journal with a number of articles, citation strength, and link strength. The co-citation network of the journal is displayed in Figure 2.6. The journal of cleaner production is the most influential journal for publishing GSFT practices research followed by the transportation research part A: policy and practices. The studies with the above journal are further explored and found that most of the paper presents certain policy instruments for improving the sustainability performance of the freight transport industry. The author co-citation measurement is widely used to identify the intellectual level and researchers’ activities in a given field (Backhaus et al., 2011). When an author cites other authors’ research works, and when the author’s work is cited by

Figure 2.4: Map of most influential researchers of the field.

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Aalok Kumar, Ramesh Anbanandam, Golam Kabir, Yiğit Kazançoğlu

Figure 2.5: Co-citation analysis from references.

48

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Table 2.3: Most influential journal for GSFT practices research. Journal name Journal of Cleaner Production Transportation Research Part A: Policy and Practice International Journal of Production Research Transportation Research Part E: Logistics and Transportation Review Research in Transportation Business and Research International Journal of Physical Distribution and Logistics Management International Journal of Production Economics International Series of Operations Research and Management European Journal of Operational Research Benchmarking: An International Journal

No. of citations articles

total link strength

   

   

   

 

 

 

 

 

 

 

 

 

other researchers, then co-citation analysis represents the intellectual relationship of similar work. It can be agreed that when two authors cited at least one common document in the same reference list are co-cited when at least one document in the same reference list (Backhaus et al., 2011). Table 2.4 presents the cocitation analysis of the top ten authors and the graphical relationship is given in Figure 2.7.

2.3.3.2 Keyword mapping and analysis Research keywords is the basic unit to represent the field of study, which can provide a trend of knowledge and research trends. The keyword co-occurrence network analysis can highlight the link among various keywords through nodes. Table 2.5 shows the most commonly used keywords in GSFT research. Figure 2.8 plots the graphical relation of GSFT keywords. The more commonly used keywords in the literature are freight transportation, sustainable development, sustainability, freight transport, and decision-making. The above literature analysis clearly shows that most of the freight transportation research evolves around sustainable development. The second most frequently used combination of sustainable freight transportation is observed. Based on the bibliometric analysis result, the following five clusters are observed and given in Table 2.6. Table 2.6 shows that cluster 5 has a smaller number of nodes and mostly focused on the intermodal or multimodal freight transport sustainability. Based on the cluster analysis of keywords, Table 2.7 presents the research scope for developing GSFT practices.

Evaluation and Program Plannin

Journal of Cleaner Production

Figure 2.6: Co-citation analysis of top journals.

International Journal of Shipp

International Journal of Produ Business Strategy and the Envi

Research in Transportation Bus

International Journal of Produ Transportation Research Part E

European Journal of Operationa

Central European Journal of Op

50 Aalok Kumar, Ramesh Anbanandam, Golam Kabir, Yiğit Kazançoğlu

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Table 2.4: Top ten authors co-citation analysis. #

Author

         

Sarkis, J. Browne, M. Macharis, C. Holguin-veras, J. Taniguchi,E. Mckinnon, A.C. Ballot, E. Allen, J. Crainic, T.G. Montreuil, B.

Citation

Total link strength

         

, , , , ,  , , , ,

2.4 Discussion This chapter presents a bibliometric analysis in order to highlight the importance of GSFT practices for promoting sustainable freight transportation system. The analysis of selected peer-reviewed articles claims that an increasing trend of GSFT practices. The last 5 years have a high number of research articles discussing the sustainability issues of freight transportation. However, the above result analysis must be taken by the academic researchers’ community with care. The presentation of highly cited articles as an indicator of research assessments because of the growing interest to develop scientific policies (Van Raan, 2000). Tijssen et al. (2002) recommended that the presentation of the most-cited articles is to represent world class research. Moreover, most of the studies consider the policy implications for developing sustainable freight transportation. The developing nations like India and Brazil are significantly contributing to the policy formulation for improving the environmental and social sustainability of freight transportation (Kumar and Anbanandam, 2019; Kumar and Ramesh, 2018; Shankar et al., 2019). The adoption of green freight transportation practices are helping to develop environmental friendly transport practices (Evangelista et al., 2017). In the selected literature review sample, fuzzy-based method is used to a considerable level, including regional case studies, survey-based model, optimization model, and simulation-based studies (Alshubiri et al., 2014; Iannone, 2012; Sureeyatanapas et al., 2018; Tacken et al., 2014). The second type of study is based on the conceptual framework for improving freight transport sustainability (Behrends, 2011; Kiani Mavi et al., 2019; Kumar and Anbanandam, 2019; Shankar et al., 2019).

Aalok Kumar, Ramesh Anbanandam, Golam Kabir, Yiğit Kazançoğlu

Figure 2.7: Top authors co-citation network.

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Table 2.5: Most cited keywords with respective link strength. #

Keywords

         

Freight transportation Sustainable development Sustainability Freight transport Decision making Logistics Supply chain Transportation Environmental impact Roads and street

Occurrence

Total link strength

         

         

2.5 Conclusions and limitation of the study This chapter highlights the relationship between GSFT practices for a sustainable supply chain by conducting a bibliometric analysis. The bibliometric mapping of the considered research field considers the growth of the number of publications, top-cited papers, productivity of the papers in terms of citation analysis, authors contribution to sustainability research, productivity by the country, co-citation analysis, and cluster analysis. This chapter considers a review for a period from the year 2001 to November 2019. A total of 171 articles are selected suitable for data analysis. With the sources retrieved in the bibliometric analysis, it is possible to draw some conclusions. The number of publications in GSFT practices has been increasing, especially in the last 5 years. Also, most of the articles are focused on the policy concern, that is, green freight distribution, intermodal, multimodal, and transport network design. The cluster distribution of keywords clearly shows that the intermodal and multimodal freight transportation is less explored. The synchromodal based transport system is the most sustainable way of freight transportation (Steadieseifi et al., 2014). The developing nation such as India and Brazil are significantly contributing to the development of a sustainable freight transport system. The United Kingdom is a top-performing country to promote sustainable freight transport practices. Journal of cleaner production and transportation research part A: policy and practice are the most preferred journals for publishing green and sustainable development of the freight transport industry. This chapter tries to develop a roadmap of GSFT practices with a comprehensive approach of literature review: (a) the nature of growing attention of researchers and practitioners in the last 20 years, (b) most of the studies propose policies and conceptual framework for analyzing GSFT practices; (c) various newer transport technologies such as intermodal, synchromodal, and multimodal are less explored;

Aalok Kumar, Ramesh Anbanandam, Golam Kabir, Yiğit Kazançoğlu

Figure 2.8: Network of most used keywords for GSFT practices.

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Table 2.6: Keywords for the five clusters of GSFT. Cluster 

Cluster 

Cluster 

City logistics Freight transport Sales Supply chain management Sustainability Sustainable transportation Transport Transport policy Urban freight transport

Decision making Design/methodology/approach Environmental management Environmental performance Environmental sustainability Green logistics Literature reviews Logistics Road freight transport Supply chains

Competition Costs Freight transportation Investments Marketing Public policy Sustainable development Transportation mode

Cluster 

Cluster 

Carbon Carbon dioxide Container Environmental impact Greenhouse gases Roads and streets Sustainable transport

Intermodal transport Intermodal transportation Shipping Transportation planning Multimodal transport

Table 2.7: Research focus of GSFT clusters. Cluster # Nodes Research focuses  

 





 

 

Sustainable freight transport policy and practices Focuses on the development of models, methods, and approaches to measure sustainable logistics performance Focuses on the optimization, simulation, and cost-competitive model for sustainable freight transport system Green and environmentally responsible freight transport system This cluster discusses the intermodal and multimodal freight transport systems and their sustainability issues

(d) various countries contribution in GSFT practices development; and (e) finally presented a mapping of various GSFT practices. This literature review is a guideline for freight logistics researchers to develop a more sustainable solution for the freight transport industry. The cluster analysis clearly shows that intermodal or multimodal based freight transport sustainability measures are less explored. In this way, this chapter is an important contribution to improve the knowledge of the relationship between GSFT practices. This study has certain limitations such as search criteria and keyword combinations that are limited. The further research can

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be explored that more keywords combination and do a separate analysis for each search result. To present more concise result, a separate study for developing and developed nations GSFT practices are required. Acknowledgments: The Ministry of Human Resources Development, Government of India, financially supports this work, through IIT Roorkee Ph.D. grant number: MHRD/IITR/DoMS/16918015. The work was also supported by Queen Elizabeth Golden Jubilee Visiting Researchers Fellowship through the University of Regina, Saskatchewan, Canada.

References Alshubiri F., Allaoui H., Goncalves G., Hazen B.T., Beškovnik B., and Jakomin L. (2014). Green logistics: Improving the environmental sustainability of logistics. Journal of Industrial Engineering and Management, 53, 147–155. https://doi.org/10.3926/jiem.2173 Backhaus K., Lügger K., and Koch M. (2011). The structure and evolution of business-to-business marketing: A citation and co-citation analysis. Industrial Marketing Management, 40, 940–951. https://doi.org/10.1016/j.indmarman.2011.06.024 Bask A. and Rajahonka M. (2017). The role of environmental sustainability in the freight transport mode choice: A systematic literature review with focus on the EU. International Journal of Physical Distribution & Logistics Managemen, 47, 560–602. https://doi.org/10.1108/IJPDLM-03-2017-0127 Behrends S. (2011). Urban freight transport sustainability. Framework. Chicksand D., Watson G., Walker H., Radnor Z., and Johnston R. (2012). Theoretical perspectives in purchasing and supply chain management: An analysis of the literature. Supply Chain Management. https://doi.org/10.1108/13598541211246611 Davies I., Mason R., and Lalwani C. (2007). Assessing the impact of ICT on UK general haulage companies. International Journal of Production Economics, 106, 12–27. https://doi.org/10.1016/j. ijpe.2006.04.007 Demir E., Huang Y., Scholts S., and Van Woensel T. (2015). A selected review on the negative externalities of the freight transportation: Modeling and pricing. Transportation Research. Part E, Logistics and Transportation Review, 77, 95–114. https://doi.org/10.1016/j.tre.2015.02.020 Dou Y., Zhu Q., and Sarkis J. (2014). Evaluating green supplier development programs with a greyanalytical network process-based methodology. European Journal of Operational Research, 233, 420–431. https://doi.org/10.1016/j.ejor.2013.03.004 Engström R. 2016. The Roads’ Role in the Freight Transport System, in: Transportation Research Procedia. pp. 1443–1452. https://doi.org/10.1016/j.trpro.2016.05.217 Eto M. (2016). Rough co-citation as a measure of relationship to expand co-citation networks for scientific paper searches. Processing Association for Information Science and Technology, 53, 1–4. https://doi.org/10.1002/pra2.2016.14505301131 Evangelista P., Colicchia C., and Creazza A. (2017). Is environmental sustainability a strategic priority for logistics service providers?. Journal of environmental management, 198, 353–362. https://doi.org/10.1016/j.jenvman.2017.04.096 Fahimnia B., Tang C.S., Davarzani H., and Sarkis J. (2015). Quantitative models for managing supply chain risks: A review. European Journal of Operational Research. https://doi.org/10.1016/j. ejor.2015.04.034

2 Green and sustainable freight logistics for improving supply chain sustainability

57

Feng Y., Zhu Q., and Lai K.H. (2017). Corporate social responsibility for supply chain management: A literature review and bibliometric analysis. Journal of Cleaner Production. https://doi.org/ 10.1016/j.jclepro.2017.05.018 Goldman T. and Gorham R. (2006). Sustainable urban transport: Four innovative directions. Technology and Society, 28, 261–273. https://doi.org/10.1016/j.techsoc.2005.10.007 Hurter C. (2015). Analysis and visualization of citation networks. Synthetic Lecture Vision, 3, 1–127. https://doi.org/10.2200/s00688ed1v01y201512vis006 Iannone F. (2012). The private and social cost efficiency of port hinterland container distribution through a regional logistics system. Transportation Research Part A Policy and Practice, 46, 1424–1448. https://doi.org/10.1016/j.tra.2012.05.019 Kelle P., Song J., Jin M., Schneider H., and Claypool C. (2019). Evaluation of operational and environmental sustainability tradeoffs in multimodal freight transportation planning. International Journal of Production Economics, 209, 411–420. https://doi.org/10.1016/j.ijpe.2018.08.011 Kiani Mavi R., Fathi A., Farzipoor Saen R., and Kiani Mavi N. (2019). Eco-innovation in transportation industry: A double frontier common weights analysis with ideal point method for Malmquist productivity index. Resources, Conservation and Recycling, 39–48. https://doi. org/10.1016/j.resconrec.2019.04.017 Kumar A. and Anbanandam R. (2019). Development of social sustainability index for freight transportation system. Journal of Cleaner Production, 210, 77–92. https://doi.org/10.1016/j. jclepro.2018.10.353 Kumar A. and Ramesh A. (2018). Modelling intermodal freight transportation promotion for sustainable supply chain in india. Springer Singapore, 115–137. https://doi.org/10.1007/978-981-10-8010-4_7 Lai K.H., Lun V.Y.H., Wong C.W.Y., and Cheng T.C.E. (2011). Green shipping practices in the shipping industry: Conceptualization, adoption, and implications. Resources, Conservation and Recycling. https://doi.org/10.1016/j.resconrec.2010.12.004 Lam J.S.L. and Lai K.H. (2015). Developing environmental sustainability by ANP-QFD approach: The case of shipping operations. Journal of Cleaner Production, 105, 275–284. https://doi.org/ 10.1016/j.jclepro.2014.09.070 Limbourg S. and Jourquin B. (2009). Optimal rail-road container terminal locations on the European network. Transportation Research. Part E, Logistics and Transportation Review, 45, 551–563. https://doi.org/10.1016/j.tre.2008.12.003 Marchet G., Melacini M., and Perotti S. (2014). Environmental sustainability in logistics and freight transportation: A literature review and research agenda. Journal of Manufacturing Technology and Management. https://doi.org/10.1108/JMTM-06-2012-0065 McKinnon A., Browne M., Piecyk M., and Whiteing A. (2015). Green logistics: Improving the environmental sustainability of logistics. Transport Reviews. https://doi.org/10.1007/s13398-0140173-7.2 Meyer P.E. and Winebrake J.J. (2009). Modeling technology diffusion of complementary goods: The case of hydrogen vehicles and refueling infrastructure. Technovation, 29, 77–91. https://doi. org/10.1016/j.technovation.2008.05.004 Noyons E.C.M., Moed H.F., and Luwel M. (1999). Combining mapping and citation analysis for evaluative bibliometric purposes: A bibliometric study. Journal American Society for Information Science, 50, 115–131. https://doi.org/10.1002/(SICI)1097-4571(1999)50:23.0.CO;2-J Nuzzolo A. and Comi A. (2014). Urban freight demand forecasting: A mixed quantity/delivery/ vehicle-based model. Transportation Research. Part E, Logistics and Transportation Review, 65, 84–98. https://doi.org/10.1016/j.tre.2013.12.014 Pierce S.J., 1990. Disciplinary work and interdisciplinary areas: {Sociology} and {Bibliometrics}, in: Scholarly {Communication} and {Bibliometrics}. pp. 46–58.

58

Aalok Kumar, Ramesh Anbanandam, Golam Kabir, Yiğit Kazançoğlu

Raghuram S., Tuertscher P., and Garud R. (2010). Mapping the field of virtual work: A cocitation analysis. Information Systems Research. https://doi.org/10.1287/isre.1080.0227 Reis V. (2014). Analysis of mode choice variables in short-distance intermodal freight transport using an agent-based model. Transportation Research Part A Policy and Practice, 61, 100–120. https://doi.org/10.1016/j.tra.2014.01.002 Sanchez-Rodrigues V., Potter A., and Naim M.M. (2010). The impact of logistics uncertainty on sustainable transport operations. International Journal of Physical Distribution & Logistics Managemen, 40, 61–83. https://doi.org/10.1108/09600031011018046 Schliwa G., Armitage R., Aziz S., Evans J., and Rhoades J. (2015). Sustainable city logistics – Making cargo cycles viable for urban freight transport. Research in Transportation Business & Management, 15, 50–57. https://doi.org/10.1016/j.rtbm.2015.02.001 Shankar R., Choudhary D., and Jharkharia S. (2018). An integrated risk assessment model: A case of sustainable freight transportation systems. Transportation Research Part D: Transport and Environment, 63, 662–676. https://doi.org/10.1016/j.trd.2018.07.003 Shankar R., Pathak D.K., and Choudhary D. (2019). Decarbonizing freight transportation: An integrated EFA-TISM approach to model enablers of dedicated freight corridors. Technological Forecasting and Social Change, 143, 85–100. https://doi.org/10.1016/j.techfore.2019.03.010 Solomon A., Ketikidis P., and Koh S.C.L. (2019). Including social performance as a measure for resilient and green freight transportation. Transportation Research. Part D, Transport and Environment. https://doi.org/10.1016/j.trd.2019.01.023 Steadieseifi M., Dellaert N.P., Nuijten W., Van Woensel T., and Raoufi R. (2014). Multimodal freight transportation planning: A literature review. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2013.06.055 Sureeyatanapas P., Poophiukhok P., and Pathumnakul S. (2018). Green initiatives for logistics service providers: An investigation of antecedent factors and the contributions to corporate goals. Journal of Cleaner Production, 191, 1–14. https://doi.org/10.1016/j.jclepro.2018.04.206 Tacken J., Rodrigues V.S., and Mason R. (2014). Examining CO2e reduction within the German logistics sector. International Journal of Logistics Management. https://doi.org/10.1108/IJLM09-2011-0073 Tijssen R.J.W., Visser M.S., and Van Leeuwen T.N. (2002). Benchmarking international scientific excellence: Are highly cited research papers an appropriate frame of reference?. Scientometrics, 54, 381–397. https://doi.org/10.1023/A:1016082432660 Tranfield D., Denyer D., and Smart P. (2003). Towards a methodology for developing evidenceinformed management knowledge by means of systematic review. British Journal of Management. https://doi.org/10.1111/1467-8551.00375 Ülkü M.A. (2012). Dare to care: Shipment consolidation reduces not only costs, but also environmental damage. International Journal of Production Economics, 139, 438–446. https://doi.org/10.1016/j. ijpe.2011.09.015 van Eck N.J. and Waltman L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84, 523–538. https://doi.org/10.1007/s11192-009-0146-3 Van Raan A.F.J. (2000). The pandora’s box of citation analysis: Measuring scientific excellence – The last evil?. Asist Monographs Series, 301–319. White H.D. and Griffith B.C. (1981). Author cocitation: A literature measure of intellectual structure. Journal American Society for Information Science, 32, 163–171. https://doi.org/10.1002/ asi.4630320302 The World Bank, 2012. Inclusive Green Growth: the pathway to sustainable development, The World Bank. https://doi.org/10.1205/psep.05009

Sushobhan Majumdar

3 Sustainability in urban expansion of a metropolitan city: impacts of urban growth towards the outer fringe of Kolkata Abstract: Urban expansion is basically the expansion of land toward the outskirt areas of the city. The rate of urban expansion in the countries like India is very high than the first world countries. In India, agricultural tract, forest area, wetland has been transformed into the built-up area near the fringe area. Most of the development of this area is unplanned, which influences negative externalities. For the future modeling and planning of this area, these negative externalities should be minimized. To measure the rate of urban expansion satellite images of four years have been used. This study reveals that because of the growth of the built-up areas most of the semi urban or villages have been transformed into the urban land area, which is mainly unplanned. For the sustainable development of the area, these unplanned growth should be minimized. The land use and land cover maps used in this study will be helpful for future modeling and planning of this area. This type of study will be helpful to take immediate measures to reduce the problem of urban expansion and to maintain the urban sustainability of the region. Keywords: urban fringe, sustainable planning, negative externalities, urban expansion, urban sustainability

3.1 Introduction Urbanization is the process of an area to be urbanized and is one of the major phases of globalization (He et al., 2006; Song et al., 2012; Shahbaz et al., 2014). Forecast of population according to the United Nations regarding demographic growth and forecast of the United Nations (2012), urban population is projected to be increased by 67.2 percent in 2050. Problems related with population growth are now a worldwide phenomenon that is mainly because of the impact of expansion of the city’s physical boundary (Marshall, 2007; Shlomo et al., 2011). Urban growth of an area has both the positive effect and negative impact. Positive effect of urban growth is related with the increase in facilities (infrastructural, health, etc.) whereas negative impact of urban growth leads to negative externalities of the city. Recently, it is one of the major thrust areas of academic research because it is related with the sociopolitical issues and economic issues as well (Bourne, 1996; Sushobhan Majumdar, Department of Geography, Jadavpur University, Kolkata, India https://doi.org/10.1515/9783110628593-003

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Fischel, 1982; Peiser, 1989). Change in land use pattern and land cover is mainly because of the activities of the human beings, which is further modified because of the change in the human needs that affect various physical and nonphysical resources (Vink, 1975). Nowaday, most of the urban or peri-urban researchers suggest the compact city model for a urban form in a sustainable way. Agarwal et al., 2002; Chen et al., 2008; Jenks and Burgess, 2000; Eastman et al. 2005; Koomen et al., 2007; Thomas and Cousins, 1996 have categorized change in land use as an criteria of change analysis. Land use is a series of activities occurring on land due to the human interference for the proper use of land (Nayak, 2014). The spatial patterns of land use expansion in the developed countries have been used in many areas of research like ecology of human beings, spatial econometrics, and sociopolitical issues (Liu et al., 2001). Recently, remote sensing is a valuable tool to scrutinize the urban growth in the fringe area. Remote-sensing data are now one of the useful tools for mapping the transformation of change in land use and land cover (LULC) of an area (El-Kawy et al., 2011). In most of the research, remotely sensed data have been used for monitoring LULC changes in the urban area with various environments (Dewan and Yamaguchi, 2009; Stefanov et al., 2001; Yang and Lo, 2002). Remote sensing and geographic information system (GIS) are the most common and useful data sources for detecting the change in land use, quantification of change in land use, and mapping the uses of land and land cover pattern because of its cost-effective methods (Chen et al., 2005; Lu et al., 2004). Methodology used in this article is innovative compared to other articles, in the sense that in this article, simple methodology has been followed to find out the urban sustainability in this area. For this reason, it is very easy to understand the policy makers or decision makers to take major policies in future. The main objectives of this study are to find out growth in urban areas of Kolkata city from 1990 to 2015 and also to find out the consequences of urban expansion on the fringe areas. For the sustainable growth and development of the area, these negative consequences should be reduced.

3.2 Database and methodology 3.2.1 Areas of study Kolkata and its outer areas are known as Kolkata metropolitan area (KMA). Kolkata city (Figure 3.1) is one of the major metropolitan cities located in the eastern side of the country. KMA is under the regulations of Kolkata metropolitan development authority (KMDA), that is, former Calcutta metropolitan planning organization (CMPO). It was formed by an act of land control in 1965. After its development, a perspective plan was developed in 1966. According to the perspective plan of the former CMPO, which was

3 Sustainability in urban expansion of a metropolitan city

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Figure 3.1: Areas of study.

then the area of Calcutta metropolitan district (CMD) was 1380 sq. km. Later the boundary of the KMA was modified by KMDA by the implications of various gazettes. At present, the area of KMA is nearly 1841.47 sq. km, which covers the entire Kolkata district and parts of surrounding districts such as 24 Parganas (South), 24 Parganas (North), Nadia, Hooghly, and Howrah district. The administrative boundary of KMA is bounded by the KMDA and all types of perspective planning in KMA are formulated by KMDA. Table 3.1 showing different constituent units of KMA.

3.2.2 Methodology Landsat images from 1990 to 2015 have been used for the study. Following table describes the detailed information of those images (Table 3.2).

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Table 3.1: Different constituent units of KMA. Constituent units

Units in Numbers

Total area (in sq. km.)

Total population (in lakhs)



.

.

Municipalities (M)



.

.

Census towns (CT)



.

.

Out growths (OGs)



.

.

Rural areas (Mouzas)



.

.

Total area of KMA



.

.

Municipal corporations (MC)

Table 3.2: Information regarding the remote sensing imagery. Satellite

Acquisition Date

Sensor

Spatial Resolution

Projection

Landsat OLI 

--

OLI–

m

Landsat  Series

--

TM

m

WGS  UTM

Landsat  Series

--

ETM+

m

 N

Landsat  Series

--

TM

m

Four sets of remote-sensing images have been collected from the United States Global Survey (USGS). Landsat thematic mapper sensor (TM) and landsat enhanced thematic mapper series of (L7) (ETM+) images and landsat OLI 8 (L8) images (with a path and row of 138 and 45) have been used for the purpose of this study. During the stacking of different image, file layer thermal band has been excluded because of the chances of misclassification. Maps published from various sources like KMDA, Kolkata Municipal Corporation (KMC) have been used. At the time of georeferencing, topographic maps have been used. For some ground truth verification, field verification has been done over the areas of study.

3.2.2.1 Processing of satellite images The satellite images that were obtained from the USGS have been corrected and regeo-referenced with the universe projection system (UTM) from the topographic

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sheets, which was previously geocorrected. After that, randomly 475 ground control points have been selected geocorrection. Resampling techniques have been used using nearest neighbor algorithm technique.

3.2.2.2 Enhancement of images and interpretation by visual techniques Enhancement of images basically used mainly for the clarification of the satellite images through its modification using digital image processing techniques. Supervised classification techniques have been used as the percentage of error that will be increased by the visual classification techniques (Lillesand and Kiefer, 1994). By the process of supervised classification process, five uses of land and land cover maps have been produced properly.

3.2.2.3 Image classification Uses of land and cover of land types are calculated from satellite images through the process of supervised classification algorithm of the images (Campbell, 1987). Objective of the classification of images has been done mainly to classify all the digital number (DN) values of the pixels of the satellite image to the land cover classes under the same category (Lillesand and Kiefer, 1994). Maximum likelihood algorithm (MLA) has been used as it examines all the statistical tools when classifying the neighboring pixel. So, it has been considered here as a most accurate classifier algorithm techniques.

3.2.2.4 Supervised classification techniques using MLA Researcher used Erdas imagine V 14.0 software for digital classification of the satellite images. During the classification training, samples have been collected all over the area through random sampling strategy using feature space tool. For the classification, training samples have been collected from the all categories. All confusions were avoided at the time of sample selection. After collection of samples, maximum likelihood classification has been used for classification. Among the algorithm techniques, maximum livelihood (ML) is one of the parametric classification algorithms that is mainly used for the supervised classifications. This algorithm is based on likelihood and unknown measurement vector. Di = In ðAc Þ − ½0.55 Inðjcovc jÞ − ½0.55ðX − Mc Þ Tðcove − 1ÞðX − Me Þ

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3.2.2.5 Classification improvement Some LULC classes were spectrally confused with the other classes because of the mixing of various colors and textures of pixels. Because of the mixing of same tones of pixels, it is very difficult to separate them, for example, misconception between ponds, wet land, etc. In few areas, the percentage of visual error may be increased because of urban vegetation mix up with the aquatic plants of the water bodies. To minimize the error during classification, the old LULC maps have been compiled with the new maps by the help of visual interpretation techniques. The compilation of the initial LULC maps with the new maps reduces the error during classification.

3.2.2.6 Accuracy assessment of the satellite images Assessment of accuracy is a most fruitful method for classifying the satellite images at the time of change analysis (Owojori and Xie, 2005). For the assessment of accuracy, random sampling techniques have been used. For the accuracy assessment, Erdas imagine V 14.0 software has been used. Overall accuracy of those images has been obtained from the confusion matrix by dividing the total number of the data that makes major diagonal by the sum of calculated pixels of those images. Khat statistics has been calculated by using following equations. ^= K

M

r P i=j=1

nij −

M2 −

r P i=j=1

r P

i=j=1

ni nj

ni nj

Where: r = Sum number of calculated rows in the confusion matrix nij = Sum of row i, column j ni = Sum of row i nj = Sum of column j M = Sum of error matrix

3.3 Discussion and analysis Growth and expansion mainly occurred to the southeastern side i.e., toward the Rajpur– Sonarpur areas, toward the southwestern part i.e., toward the Maheshtala municipality area, Budge Budge municipality and Pujali municipality areas and

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also in the northeast direction i.e., Barasat, Madhyamgram areas because it has been found during supervised classification of the satellite images. Easy accessibility through the major road, railway and availability of vacant flat land at low price are the probable causes behind the urban expansion of the city.

3.3.1 Pattern of LULC in 1990 Five LULC types Table 3.3 have been found in the year 1990 after the classification of image in 1990 Figure 3.2. From the supervised classification, highest category was vegetation (i.e., 52.25% of the total areas of study) followed by built-up area that comprises 16.55% of the total areas of study, barren land (i.e., 13.90% of the total areas of study), water bodies (i.e., 9.32% of the total areas of study), and cultivated land (i.e., 7.89% of the total areas of study) as shown in Table 3.4. Expansion of urban area in this time period mainly occurred toward the northeastern part, northwestern part, and southeastern direction from the city centre areas. During this period, availability of the cultivated land and wetland are relatively high in the city fringe areas. Vegetables and fishes from the peripheral areas used to come to the Kolkata city to meet the needs of the city people, and those regions acted as a storehouse of fresh and perishable vegetables, inland fishes, and dairy milk for city. Table 3.3: Major land use types. No. Land use classes

Description



Areas under urban area

Lands for residential purposes, areas for commercial purposes, areas for industrial purposes, metalled roads, railway lines



Areas under forest cover

Areas under vegetation, areas under forest



Land under agriculture

Areas under agriculture, cultivated area



Water bodies or wet land area

Perennial river, nonperennial river pond, man-made canals, artificial reservoir



Land presently barren

Waste land area, land area which are currently fallow

3.4 Patterns of land use in the year 2000 In the year 2000 (Figure 3.3), urban area was covered by 25.04% of the total study area. Forest or vegetation area conceded 38.40% of the total study area, 5.58% of the total area of study was under the cultivated area, 5.26% was under the water bodies, and 23.70% of the total land was under the barren land (Table 3.4). In this

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88°30'0''E

22°30'0''N

22°30'0''N

88°0'0''E

23°0'0''N

Sushobhan Majumdar

Land use categories Built-up area Vegetation Cultivated land Water bodies Barren land 88°0'0''E

0

5

10

20 Kilometers 88°30'0''E

Figure 3.2: Patterns of uses of land and land cover types of KMA in 1990. Source: Computed from the Landsat TM images, Dated-14.11.1990.

time period, expansion was mainly toward the northwestern side (i.e., Bally, Uttarpara area), northeastern side (Barasat, Madhyamgram area) and also toward the southeastern side (i.e., Rajpur Sonarpur, Garia area). Accessibility from the city core areas by road and extension of Kolkata metro railway to the southern part of Kolkata were the probable causes behind the urban expansion of Kolkata city. Probable reason behind the decline in the percent of water bodies is because of the expansion of built-up area to the city fringe area due to the real estate developers who used the water bodies or wetland for the construction of new real estate development projects. For example, in the roadside of the Belgharia-Barrackpore expressway, a very good amount of land has been transformed into urban area.

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Table 3.4: Trends of uses of land and land cover types (percent) in Kolkata and its surroundings. 









Urban area or built-up area

.

.

.

.

.

Vegetation

.

.

.

.

.

Cultivated land

.

.

.

.

.

Water bodies

.

.

.

.

.

.

.

.

.

.

88°0'0''E

88°30'0''E

22°30'0''N

BALLY, UTTARPARA AREA

BARASAT, MADHYAMGRAM AREA

GARIA, RAJPUR SONARPUR AREA

Land use categories Built-up area Vegetation Cultivated land Water bodies Barren land 88°0'0''E

0

5

10

20 Kilometers 88°30'0''E

Figure 3.3: Land use pattern and land cover types of KMA in 2000.

22°30'0''N

Barren land

23°0'0''N

Year

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3.4.1 Patterns of LULC in 2010 and 2015

22°30'0''N

22°30'0''N

23°0'0''N

88°30'0''E

23°0'0''N

In the year 2010 (Figure 3.4), Forest area or vegetation area accounted for 37.17% out of the total area whereas built-up area covers only 31.17% of the total study areas of KMA. Only 4.78 % of the total areas of study were under the water bodies, 3.89% was under the cultivated area or agricultural land area, and 23.07% out of the total KMA was under the barren land. In 2015 (Figure 3.5), 33.60% of the total areas of KMA was under urban area, and it was preceded by forest tracts (i.e., 38.11% out of the total areas) and barren or waste land (i.e., 232.23% out of the total areas of study), wetland and water bodies (i.e., 3.80 % of the total study area), and agricultural land or cultivated land (i.e., 2.26% of the total study area) (Table 3.4). By 2010 and 2015, expansion occurred toward northeastern side, southeastern and mainly toward the southwestern side (i.e.

Land use categories Built-up area Vegetation Cultivated land Water bodies Barren land

0

5

10

20 Kilometers 88°30'0''E

Figure 3.4: Pattern of land use and land use of KMA in the year 2010.

88°30'0''E

22°45'0''N

22°45'0''N

23°0'0''N

88°15'0''E

69

23°0'0''N

3 Sustainability in urban expansion of a metropolitan city

MAHESHTALA, BUDGE BUDGE AND PUJALI AREA GARIA, RAJPUR SONARPUR AREA

Land use categories Built-up area Vegetation Cultivated land Water bodies Barren land New growth 88°15'0''E

0

5

10

22°30'0''N

22°30'0''N

BARASAT, MADHYAMGRAM AREA

20 Kilometers 88°30'0''E

Figure 3.5: Patterns of land use types and land cover of KMA in the year 2015.

Maheshtala municipality area, Budge Budge municipality area and Pujali municipality area) from Kolkata city. Because of the expansion of the urban areas from the city core to peripheral areas, forest or vegetation area, cultivated tract, wetland, and water bodies have been rapidly decreased. Transformation of land is very high in Halisahar, Soanrpur, Garia areas as it has been seen from the classification of satellite images. One of the major characteristics of Kolkata city is that a maximum number of the villages in 2001 census has been changed into census towns in 2011 census. In recent decades, Kolkata city has grown in a linear way toward the southeastern part and southwestern part besides the eastern part of the Hooghly River as it has been found after the supervised classification of the remotely sensed imageries. Minutely, it has been found that the Kolkata city has grown through the major roads, for example, toward Sonarpur (through N.S.C. Bose Road), Maheshtala (by B.B.T. Road), Halisahar, Kanchrapara (beside the railway lines or where accessibility is high).

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3.5 Consequences of urban growth Kolkata city are facing a lot of problems due to the huge urban growth toward the outer areas of the city. Because of real estate development by the real estate developers, most of the nonurban land has been converted into the urban area within the few years span of time. Agricultural land, wetland, vegetation areas are declining tremendously because of the huge urban growth. Decrease in the vegetation area and agricultural area shows adverse effect on the local natural ecosystems. The price of land is increasing rapidly near the city area. Because of the increase in the price of land, people have to move outside the city area for their residential purposes. The major problem is that there are no strict laws for preventing the unplanned urban growth. Due to this reason, the farmers or small households have to sell their land to the promoters unwillingly. Lack of recognition of the land area is also another problem. In addition, there is no coordination among the authorities responsible for the planning of this area.

3.6 Recommendations The development in the fringe area are mainly governed by village panchayats, nagar panchayats, district administration, district planning committees of Kolkata (DPC), metropolitan planning committees (MPC) of Kolkata, development authorities regarding the development of Kolkata etc. Due to the poor resource and less expertise, rural local bodies are unable to control the development in such areas. There is lack of legislation to control such areas through the town and country planning acts. The functions of various agencies are also overlapping and uncoordinated, so there is a need of control area development plan to control the haphazard growth of the area. As there is no master plan for the development of this area, it should be developed for the future modeling and sustainable development. Population pressure in Kolkata is another problem in this area. Population increase in this area is mainly because of the two reasons, one is natural increase and another is increase due to huge migration. Compared to the first reason, second reason affects the most as it increases the population within a short time period.

3.7 Conclusion Kolkata city is located in the eastern part of Indian subcontinent with 15.89 million populations. After mid-90s, total population of Kolkata has been rapidly increased mainly because of the immigration from East Pakistan or Bangladesh, which creates tremendous pressure on the existing land resources. For this reason, this increasing

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71

population demands more open space for the residential uses that are fixed in supply. To meet the demands of land, most of the agricultural land, vegetation area, water bodies, or wetland has been converted into the residential area. For the sustainable development of this area or to reach urban sustainability, different plans and policies should be developed to reduce this unhealthy transformation of land. Due to the reduction of water bodies and agricultural land, negative externalities of the city is increasing day by day. So, to meet or to attain urban sustainability in Kolkata, these negative externalities or negative consequences should be minimized. With the economic growth and physical development of the area, the economic structure has been shifted from nonagricultural-based economy to service-oriented economy because of the impact of urbanization. Because of the unhealthy transformations of the land from the agricultural land to urban area, there is a negative impacts on the local existing land resources. The methodology used in this article is innovative in the sense that this methodology is relatively new than the other traditional methodologies. The images that have been used here is extremely innovative in the sense that the images clearly depict the negative consequences of urban growth in a precise manner, which are quiet easy for the readers and researchers of all levels to understand. For the sustainable development of the area, Government officials and policy makers should take various planning strategies for the development of the area to reduce the negative externalities of the city and to protect the agricultural lands from the building promoters or from the real estate developers. The change in uses of land and land cover pattern produced in Kolkata area will not only help the periurban, urban developers, urban researchers, etc., to take decisions regarding the future planning and development of plans and policies but also the decision makers to take the right decisions for the sustainable planning and development of the city.

References Agarwal C., Green G., Grove J., Evans T.P., and Schweik C. (2002). A review and assessment of landuse models: dynamics of space, time, and human choice. Gen.Tech. Rep. NE-297. US Department of Agriculture, Forest Service, Northeastern Research Station, Newton Square. Bourne L.S. (1996). Reurbanization, uneven urban development and the debate on new urban forms. Urban Geography, 7(8), 690–713. Campbell J.B. (1987). Introduction to remote sensing. The Guilford Press. New York. Chen H., Jia B., and Lau S. (2008). Sustainable urban form for Chinese compact cities: Challenges of a rapid urbanized economy. Habitat International, 32, 28–40. Chen X., Vierling L., and Deering D. (2005). A simple and effective radiometric correction method to improve landscape change detection across sensors and across time. Remote Sensing of Environment, 98(1), 63–79. Dewan A.M. and Yamaguchi Y. (2009). Land use and land cover change in Greater Dhaka, Bangladesh: using remote sensing to promote sustainable urbanization. Applied Geography, 29(3), 390–401.

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Eastman J.R., McKendry J., and Fulk M.A. (2005). Change and time series analysis. In: Explorations in geographic informations systems technology. Geneva: United Nations Institute for Training and Research (UNITAR). El-Kawy O.A., Rød J., Ismail H., and Suliman A. (2011). Land use and land coverchange detection in the western Nile delta of Egypt using remote sensing data. Applied Geography, 31, 483–494. Fischel W.A. (1982). The urbanization of Agricultural Land: A review of the National Agricultural Lands Study. Land Economics, 5(8), 236–259. He C.Y., Okada N., Zhang Q.F., Shi P.J., and Zhang J.S. (2006). Modeling urban Expansion scenarios by coupling cellular automata model and system dynamic model in Beijing, China. Applied Geography, 26, 323–345. Jenks M. and Burgess R. (2000). Compact cities: Sustainable urban forms for developing countries. London: E & FN Spon. Koomen E., Stillwell J., Balkema A., and Scholten H.J. (2007). Modelling land-use change progress and applications. Dordrecht: Springer. Lillesand T.M. and Kiefer R.W. (1994). Remote sensing and image interpretation (4th ed.). New York: Wiley. Liu S., Wu C., and Chen T. (2001). A critical review on the progress of urban land use theories in the west. Geographical Research, 20(1), 111–119. Lu D., Mausel P., Brondizio E., and Moran E. (2004). Change detection techniques. International Journal of Remote Sensing, 25(12), 2365–2407. Marshall J.D. (2007). Urban land area and population growth: A new scaling relation-ship for metropolitan expansion. Urban studies (Edinburgh, Scotland), 44, 1889–1904. Nayak L.T. (2014). Trend of land use and land cover change in Bellary district, Karnataka using geospatial technique. Geographical Review of India, 76, 236–257. Owojori A. and Xie H. (2005). Landsat image-based LULC changes of San Antonio, Texas using Advanced atmospheric correction and Object-oriented image analysis Approaches. Paper presented at the 5th International Symposium on Remote Sensing of Urban Areas, Tempe, AZ. Peiser R. (1989). Density and Urban Sprawl. Land Economics, 65, 193–194. Shahbaz M., Sbia R., Hamdi H., and Ozturk I. (2014). Economic growth, electricity con-sumption, urbanization and environmental degradation relationship in UnitedArab Emirates. Ecological Indicators, 45, 622–631. Shlomo A., Parent J., Civco D.L., Blei A., and Potere D. (2011). The dimensions of globalurban expansion: estimates and projections for all countries, 2000–2050. Progressive Plan, 75, 53–107. Song W., Chen B.M., Zhang Y., and Wu J.Z. (2012). Establishment of rural housing land standard in China. Chinese Geographical Science, 22, 483–495. Stefanov W.L., Ramsey M.S., and Christensen P.R. (2001). Monitoring urban land cover change: an expert system approach to land cover classification of semi-arid to arid urban centers. Remote Sensing of Environment, 77, 173–185. Thomas L. and Cousins W. (1996) The compact city: A successful, desirable and achiev-able urban form. In: Jenks M., Burton E., and Williams K., (Eds.) The compact city: A sustainable urban form. London: E & FN Spon, 53–65. United Nations. (2012). World urbanization prospects the 2011 revision. New York: United Nations. Vink A.P.A. (1975). Land use in advancing agriculture. Springer-Verlag. Berlin, Germany. Yang X. and Lo C.P. (2002). Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area. International Journal of Remote Sensing, 23(9), 1775–1798.

Muhittin Sagnak

4 Assessment of logistics performance in sustainable supply chain: case from emerging economy Abstract: Nowadays, environmentally friendly operations became more critical; therefore, the sustainability concept has been evolved as new ways of thinking in supply chain operations. In that sense, the performance assessment of the sustainable supply chains needs a holistic structure covering the entire supply chain. Given the need to ensure supply chain sustainability, the performance assessment of logistics activities is critical. This chapter aims to measure the logistics performance of a furniture manufacturing company. The framework consists of three sustainable logistics performance key criteria; namely, sustainable procurement, sustainable distribution, and reverse logistics. First, the weights of the criteria were calculated by the fuzzy analytic hierarchy process. Weighted scoring method is used to compute the whole logistics performance. “Remanufacturing of materials,” “On-time delivery,” and “Using eco-labeled materials” were found as the most important factors for determining the logistics performance. Keywords: logistics performance, sustainable supply chain, performance assessment, sustainability, fuzzy AHP, weighted scoring method

4.1 Introduction Supply chains provide the simultaneous operation of many organizations to meet the needs of customers (Beske and Seuring, 2014). In addition, the World Commission on Environment and Development (WCED), 1987, recommends organizations to point out environmental and social aspects to ensure economic growth. Moreover, decision makers at the domestic level have begun to pressurize institutions to seriously consider integrating sustainable supply chain practices into organizations’ supply chain processes (Govindan et al., 2019; Sharma and Kearins, 2011). Sustainability concept has become necessary in determining the strategies of organizations due to the rapid decline of resources and the increasing necessity of social responsibility (Luthra and Mangla, 2018; Mangla et al., 2013). This creates a need to include sustainability concept in the supply chain. Sustainable supply chain management is therefore defined as the interaction between organizations to get Muhittin Sagnak, Izmir Katip Celebi University, Department of Information and Document Management, Izmir, Turkey https://doi.org/10.1515/9783110628593-004

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economic, environmental, and social gains through the chain (Seuring and Müller, 2008; Taylor and Vachon, 2018). Sustainable supply chain management aims to manage capital, information, and material flow within the supply chain while managing and implementing the economic, environmental, and social practices based on the triple bottom line approach (Carter and Rogers, 2008). Sustainable supply chains aim to minimize negative environmental consequences, reduce resource use, and eliminate waste in production and consumption (Dong et al., 2016; Genovese et al., 2017; Sarkis et al., 2011; Srivastava, 2007) Prior studies indicate that activities from production to consumption have undergone an ethical transformation. In demand-related studies, sustainable behavior and attitudes of consumers (Fisher et al., 2012), ethical consumerism (Newholm and Shaw, 2007), and sustainability issue for consumers (Moisander and Pesonen, 2002) are revealed. In supply-related studies, organizations have been found to focus more on the various sustainability issues that arise in the development of sustainable goods and services (Heikkurinen and Mäkinen, 2018). The assessment of sustainable supply chain performance involves establishing a holistic structure through the supply chain. The level of performance for the sustainable supply chain can be appraised using both quantitative and qualitative metrics. It represents the long-term competitive advantage of organizations in terms of their economic returns, taking into account their effect on the society and environment without compromising the needs of stakeholders (Kleindorfer et al., 2005; Paulraj, 2011). Triple bottom line approach, which combines economic, environmental, and social practices, is commonly used to utilize sustainability performance (Elkington, 1998; Margolis and Walsh, 2003). In terms of economic performance, organizations deal with the productivity rate and financial returns; and use some financial indicators such as return on asset, return on investment, market share, and profit (Flynn et al., 2010). Concerning environmental performance, prior studies revealed that reduction in energy consumption, hazardous material use, and waste management are used (Glavas and Mish, 2015; Zhu and Sarkis, 2004). From the point of social performance, organizations are engaged in corporate social responsibility issues to contribute to society (Carroll, 1999; Dahlsrud, 2008; Turban and Greening, 1997). Since one of the important issues in terms of sustainable supply chain operations is logistics activities, creating a sustainable environment in logistics activities is very crucial. Sustainable logistics performance is the ability to improve efficiency on transportation modes considering economic, environmental, and social issues in coordination with manufacturing, marketing, and organizational activities. In addition, decreasing the CO2 emission and reducing water, soil, and air pollution facilitate environmentally friendly transportation (Green et al., 2008; Kazancoglu et al., 2018; Lau, 2011) Sustainable logistics contain various activities such as sustainable procurement, sustainable distribution, and reverse logistics (Hervani et al., 2005). Given the need to ensure supply chain sustainability, this chapter aims (1) to propose a framework for the measurement of performance of logistics practices in

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the sustainable supply chain and (2) to calculate the performance of logistics in the sustainable supply chain. The application was conducted in a furniture manufacturing company. In this context, a conceptual framework has been developed by taking into account the factors affecting logistics performance. The conceptual framework includes both quantitative and qualitative factors. To evaluate the logistics performance of the sustainable supply chain of the organization in a meaningful way, the relative importance levels of all factors were analyzed, and the total performance level was determined by considering the performance levels based on each factor. Fuzzy analytic hierarchy process (AHP) technique was used to calculate the relative importance weights of the factors. The total performance level was determined by the weighted scoring method. Following the introduction, Section 4.2 represents the past studies concerning logistics performance. Section 4.3 highlights the proposed framework, Section 4.4 describes the methodology, and Section 4.5 highlights the application and shows the results. Section 4.6 includes the concluding remarks, limitations, and directions for future research.

4.2 Literature review In order to collect data from prior research, the systematic state-of-the-art literature review has been done as proposed by Yadav and Desai (Yadav and Desai, 2016). Logistics with a sustainability focus is the ability to increase efficiency on transportation modes while decreasing CO2 emission and reducing water, soil, and air pollution (Kazancoglu et al., 2018). In addition, it should also be in coordination with manufacturing, marketing, and other supply chain activities. Hervani et al. (Hervani et al., 2005) stated that sustainable logistics activities should cover sustainable procurement, sustainable distribution, and reverse logistics. Since the logistics activities create pollution, the adoption of sustainable or green logistics creates great benefits (Guide, 2000). The efficient management of sustainable logistics activities affects the operational and economic performance of the organizations positively; therefore, it increases the long run competitiveness (Lau, 2011). As part of logistics activities, green procurement reduces waste and liability cost (Karpak et al., 2001); green packaging decreases solid waste and packaging cost and increases environmental benefits (Lau, 2011); green transportation reduces the fuel consumption and therefore cuts operating costs while minimizing noise and pollution (Vannieuwenhuyse et al., 2003). Wisner (Wisner, 2003) found a positive relationship between logistics activities and organizational performance. Rao and Holt (Rao and Holt, 2005) discovered that logistics activities have a positive impact on the organizations’ competitiveness regarding productivity and efficiency. Green et al. (Green et al., 2008) proposed a

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logistics performance model to incorporate logistics performance as the main focus. They indicated that logistics performance is positively affecting the marketing performance; and thereby, financial performance. Lau (Lau, 2011) investigated and developed a performance index regarding logistics activities to compare the performance levels of China and Japan. Bjorklund et al. (Bjorklund et al., 2012) developed a framework investigating the relationship between environmentally friendly logistics management and performance measurements of the organizations. El-Berishy et al. (ElBerishy et al., 2013) focused on the green logistics concept to demonstrate the interrelation between green logistics and sustainability issues considering economic, environmental, and social benefits.

4.3 Proposed framework Logistics performance assessment requires a holistic approach through the sustainable supply chain. The conceptual framework, which has been formed by considering all factors that may affect logistics performance, includes qualitative and quantitative criteria required for sustainable logistics performance measurement. Table 4.1 represents the proposed framework for the performance of logistics activities within the sustainable supply chain. The conceptual framework consisting of these factors was established at the end of the detailed literature review. Table 4.1: The main and subcriteria for the logistics performance. Sustainable procurement

Sustainable distribution

Reverse logistics

Using eco-labeled materials

On-time delivery

Purchasing environmentally-friendly materials Supplier education

Eco-driving

Supplier support

Order cycle time

Audit of suppliers

Environmentally friendly transportation Delivery dependability Utilization of vehicles

Remanufacturing of materials Reusing and recycling of materials Reduction of time for recycling Inclusion of third party logistics Design for reverse logistics

Certification Pressure to suppliers for environmental actions Specifications for green design

Order fulfillment

Efficient use of fuel Optimization of routes Decrease in empty running Use of green vehicles

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Table 4.2 shows the related literature for the performance of logistics activities within the sustainable supply chain.

Table 4.2: Related literature for the performance of logistics activities. Main criteria

Sub-criteria

References (Green et al., , Lau, , Kazancoglu et al., , Diabat et al., , Wu et al., , Govindan et al., , Uygun and Dede, , Jabbour and Jabbour, , Younis et al., , Vanalle et al., )

Sustainable procurement

Using eco-labeled materials

(Green et al., , Kazancoglu et al., , Diabat et al., , Zhu et al., , Zhu et al., , Zhu et al., , Bhattacharya et al., )

Purchasing environmentally friendly materials

(Kazancoglu et al., )

Supplier education

(Kazancoglu et al., )

Supplier support

(Kazancoglu et al., , Diabat et al., )

Audit of suppliers

(Kazancoglu et al., , Diabat et al., , Zhu et al., , Zhu et al., , Zhu et al., , Tseng et al., , Chaudharya and Chanda, )

Certification

(Green et al., , Kazancoglu et al., , Diabat et al., , Zhu et al., , Zhu et al., , Bhattacharya et al., , Zhu et al., , Tseng et al., , Shang et al., )

Pressure to suppliers for environmental actions

(Kazancoglu et al., , Shang et al., )

Specifications for green design

(Green et al., , Kazancoglu et al., , Diabat et al., , Zhu et al., , Bhattacharya et al., , Zhu et al., ) (Kazancoglu et al., , Uygun and Dede, , Malviya and Kant, )

Sustainable distribution On-time delivery

(Kazancoglu et al., , Diabat et al., , Zhu et al., , Rostamzadeh et al., )

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Table 4.2 (continued ) Main criteria

Sub-criteria

References

Eco-driving

(Kazancoglu et al., , Rostamzadeh et al., )

Order fulfillment

(Green et al., , Kazancoglu et al., )

Order cycle time

(Kazancoglu et al., , Duarte et al., )

Environmentally friendly transportation

(Kazancoglu et al., , Rostamzadeh et al., , Tyagi et al., )

Delivery dependability

(Green et al., , Kazancoglu et al., , Diabat et al., )

Utilization of vehicles

(Kazancoglu et al., , McKinnon et al., )

Efficient use of fuel

(Kazancoglu et al., , McKinnon et al., )

Optimization of routes

(Kazancoglu et al., , McKinnon et al., )

Decrease in empty running

(Kazancoglu et al., , McKinnon et al., )

Use of green vehicles

(McKinnon et al., ) (Lau, , Kazancoglu et al., , Govindan et al., , Uygun and Dede, , Jabbour and Jabbour, , Geng et al., , Sharma et al., )

Reverse logistics

Remanufacturing of materials

(McKinnon et al., )

Reusing and recycling of materials

(Kazancoglu et al., , Rao and Holt, , Vachon and Klassen, , Paulraj, )

Reduction of time for recycling

(Kazancoglu et al., , Bhattacharya et al., )

Inclusion of third party logistics

(Zhu et al., )

Design for reverse logistics

(Kazancoglu et al., , Bhattacharya et al., )

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4.4 Methodology In this chapter, the weights of the main and subcriteria were calculated by the fuzzy AHP. Weighted scoring method is used to compute the whole logistics performance. The reason to integrate fuzzy logic is its capability to deal with the subjective judgment of human beings.

4.4.1 Fuzzy AHP AHP was proposed by Saaty (Saaty, 1980), and it is one of the most commonly used multiple-criteria decision-making (MCDM) techniques. It is known for its capacity to manage the qualitative and quantitative criteria (Chung et al., 2005). Using crisp values in AHP has some disadvantages (Onut et al., 2009). The fuzzy set theory introduced by Zadeh (Zadeh, 1965) suggested the use of linguistic terms in pairwise comparisons to overcome the subjective judgment of human beings. A tilde (~) is placed above when a fuzzy set is represented (Zadeh, 1965). In this chapter, triangular fuzzy numbers that are indicated as (lij, mij, rij) were used (Kahraman et al., 2003; Onut et al., 2009). A fuzzy version of AHP methodology is different from Saaty’s (Saaty, 1980) approach (Duran and Aguilo, 2008; Kilincci and Onal, 2011). The fuzzy judgment vector is attained for each criterion using pairwise comparisons. The consistency ratio has to be computed to check whether the results of any AHP analysis are consistent.

4.4.2 Weighted scoring method Weighted scoring method is used to prioritize the results and find the total score. The ease of use of weighted scoring method makes it common in current literature. The performance score of logistics activities is found by the multiplication of the main and subcriteria weights and individual performance scores. The score is evaluated as follows: Si =

n X

Sij wj

j=1

where Si indicates the logistics performance score.

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4.5 Application The application was made in a company operating in the furniture industry in Turkey. The reasons to implement this study in the furniture manufacturing company are some shortcomings in their supply chain. These shortcomings are listed as an insufficient green emphasis on their logistics activities and insufficient attention to reverse logistics activities. Fifteen authorities whose main responsibility is sustainable logistics activities responded pairwise comparisons. Table 4.3 shows the linguistic terms for pairwise comparisons. Table 4.3: Linguistic variables for fuzzy AHP. Linguistic terms

Fuzzy numbers (, , ) (, , ) (, , ) (, , ) (, , )

Equal importance level Moderately importance level Strong importance level Very strong importance level Absolute importance level

Linguistic terms for individual performance levels are shown in Table 4.4.

Table 4.4: Fuzzy linguistic scale for performance scores. Linguistic terms

Fuzzy numbers

Extremely good (EG) Good (G) Fair (F) Poor (P) Extremely poor (EP)

(., , ) (., ., ) (., ., .) (, ., .) (, , .)

Table 4.5 shows the relative weights of the main criteria. Table 4.5: Weights of the main criteria. Criteria

Weights of criteria

Sustainable procurement

.

Sustainable distribution

.

Reverse logistics

.

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This result shows that the most important criterion for sustainable logistics activities is a sustainable distribution with a weight of 0.403, followed by sustainable procurement and reverse logistics with weights of 0.320 and 0.277, respectively. Table 4.6 shows the results of calculation for weights and performance scores. Within the “sustainable procurement” main criterion, “using eco-labeled materials” was found as the most important criterion with a weight of 0.069, followed by “certification” and “purchasing environmentally friendly materials” criteria with weights of 0.06 and 0.047, respectively. “On-time delivery” was found as the most important criterion with a weight of 0.074, followed by “environmentally friendly transportation,” and “order fulfillment” criteria with weights of 0.048, and 0.047, respectively within the “sustainable distribution” main criterion. Within “reverse logistics” main criterion, “remanufacturing of materials” was found as the most crucial criterion with a weight of 0.092, followed by “design for reverse logistics” and “reusing and recycling of materials” criteria with weights of 0.065, and 0.048, respectively. Performance scores column contains data in which experts determine the performance of logistics for each criterion. The collective scores column was obtained by multiplying the weight of each subcriterion by the corresponding performance score according to the weighted scoring method. Accordingly, the total sustainable logistics performance of the organization was found to be 0.581 or 58.1%. This is an indication that the logistics score is 58.1% to achieve sustainable supply chain.

4.6 Conclusion Nowadays, there is a need for organizations to consider environmental circumstances as well as social and economic one. In order to minimize waste and protect natural resources, organizations have attempts to become greener. Within this context, decision makers at the domestic level have started to force organizations to take into consideration integrating sustainable supply chain practices into organizations’ supply chain processes (Govindan et al., 2019). The assessment of sustainable supply chain performance requires a holistic view using both quantitative and qualitative criteria. In this regard, since one of the important issues in terms of sustainable supply chain operations is logistics activities, creating a sustainable environment in logistics activities is very crucial. In this chapter, given the need to ensure supply chain sustainability, a framework is proposed to calculate the logistics performance in the sustainable supply chain. A conceptual framework has been developed by taking into account the factors affecting sustainable procurement, sustainable distribution, and reverse logistics.

.

.

Sustainable distribution

Criteria weights

Sustainable Procurement

Criteria

On-time delivery Eco-driving Order fulfillment Order cycle time Environmentally friendly transportation Delivery dependability Utilization of vehicles Efficient use of fuel Optimization of routes Decrease in empty running Use of green vehicles

Using eco-labeled materials Purchasing environmentally friendly materials Supplier education Supplier support Audit of suppliers Certification Pressure to suppliers for environmental actions Specifications for green design

Subcriteria

Table 4.6: Weights of criteria and subcriteria, and performance scores.

. . . . . . . . . . .

.

. . . . . . . . . . . .

. . . . . . .

Individual weights

. . . . . . .

Subcriteria weights

. . . . . . . . . . .

.

. . . . . . .

Individual scores

. . . . . . . . . . .

.

. . . . . . .

Scores

.

.

Total scores

82 Muhittin Sagnak

Reverse logistics

. Remanufacturing of materials Reusing and recycling of materials Reduction of time for recycling Inclusion of third party logistics Design for reverse logistics

. . . . .

. . . . .

. . . . .

. . . . . .

.

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The relative importance levels of all criteria were analyzed using fuzzy AHP and the total performance level was determined by weighted scoring method. The most important criterion for sustainable logistics activities is sustainable distribution followed by sustainable procurement and reverse logistics activities. Considering the subcriteria, “remanufacturing of materials,” “on-time delivery,” and “using eco-labeled materials” were found as the most important subcriteria. This work has some limitations. As in all MCDM problems, the acquisition of data is based on subjective judgments during pairwise comparisons; therefore, the results cannot be definitive. Future research may focus on the implementation of performance assessment of logistics activities with a different set of criteria. Furthermore, the proposed framework can be used to assess the performance level in a different emerging economy.

References Beske P. and Seuring S. (2014). Putting sustainability into supply chain management. Supply Chain Management: An International Journal, 19(3), 322–331. Bhattacharya A., Mohapatra P., Kumar V., Dey P.K., Brady M., Tiwari M.K., and Nudurupati S.S. (2014). Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach. Production Planning and Control, 25(8), 698–714. Bjorklund M., Martinsen U., and Abrahamsson M. (2012). Performance measurements in the greening of supply chains. Supply Chain Management: An International Journal, 17(1), 29–39. Carroll A.B. (1999). Corporate social responsibility: evolution of a definitional construct. Business and Society, 38(3), 268–295. Carter C.R. and Rogers D.S. (2008). A framework of sustainable supply chain management: Moving toward new theory. International Journal of Physical Distribution & Logistics Management, 38(5), 360–387. Chaudharya T. and Chanda A.K. (2015). Evaluation and measurement of performance, practice and pressure of green supply chain in Indian manufacturing industries. Uncertain Supply Chain Management, 3, 363–374. Chung S.H., Lee A.H., and Pearn W.L. (2005). Product mix optimization for semiconductor manufacturing based on AHP and ANP analysis. International Journal of Advanced Manufacturing Technology, 25, 1144–1156. Dahlsrud A. (2008). How corporate social responsibility is defined: An analysis of 37 definitions. Corporate Social Responsibility and Environmental Management, 15(1), 1–13. Diabat A., Khodaverdi R., and Olfat L. (2013). An exploration of green supply chain practices and performances in an automotive industry. International Journal of Advanced Manufacturing Technology, 68, 949–961. Dong C., Shen B., Chow P.S., Yang L., and Ng C.T. (2016). Sustainability investment under cap-andtrade regulation. Annals of Operations Research, 240(2), 509–531. Duarte S., Cabrita R., and Machado V.C. Exploring lean and green supply chain performance using balanced scorecard perspective. Proceedings of the 2011 International Conference on Industrial Engineering and Operations Management Kuala Lumpur, Malaysia, 2011. Duran O. and Aguilo J. (2008). Computer-aided machine-tool selection based on a Fuzzy-AHP approach. Expert Systems with Applications, 34, 1787–1794.

4 Assessment of logistics performance in sustainable supply chain

85

El-Berishy N., Rügge I., and Scholz-Reiter B. (2013). The Interrelation between Sustainability and Green Logistics. IFAC Proceedings Volumes, 46(24), 527–531. Elkington J. (1998). Partnerships from cannibals with forks: The triple bottom line of 21st-century business. Environmental Quality Management, 8(1), 37–51. Fisher C., Bashyal S., and Bachman B. (2012). Demographic impacts on environmentally friendly purchase behaviors. Journal of Targeting Measurement and Analysis for Marketing, 20(3–4), 172–184. Flynn B.B., Huo B., and Zhao X. (2010). The impact of supply chain integration on performance: A contingency and configuration approach. Journal of Operations Management, 28(1), 58–71. Geng R., Mansouri S.A., and Aktas E. (2017). The relationship between green supply chain management and performance: A meta-analysis of empirical evidences in Asian emerging economies. International Journal of Production Economics, 183, 245–258. Genovese A., Acquaye A.A., Figueroa A., and Koh S.L. (2017). Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications. Omega, 66, 344–357. Glavas A. and Mish J. (2015). Resources and capabilities of triple bottom line firms: going over old or breaking new ground?. Journal of Business Ethics, 127(3), 623–642. Govindan K., Jha P.C., Agarwal V., and Darbari J.D. (2019). Environmental management partner selection for reverse supply chain collaboration: A sustainable approach. Journal of Environmental Management, 236, 784–797. Govindan K., Khodaverdi R., and Vafadarnikjoo A. (2015). Intuitionistic fuzzy based DEMATEL method for developing green practices and performances in a green supply chain. Expert Systems with Applications, 42, 7207–7220. Green K.W. Jr., Whitten D., and Inman R.A. (2008). The impact of logistics performance on organizational performance in a supply chain context. Supply Chain Management: An International Journal, 13(4), 317–327. Guide V. (2000). Production planning & control for remanufacturing: industry practice and research needs. Journal of Operations Management, 18(4), 467–483. Heikkurinen P. and Mäkinen J. (2018). Synthesising corporate responsibility on organizational and societal levels of analysis: An integrative perspective. Journal of Business Ethics, 49(3), 589–607. Hervani A.A., Helms M.M., and Sarkis J. (2005). Performance measurement for green supply chain management. Benchmarking: An International Journal, 12(4), 330–353. Jabbour C.J.C. and Jabbour A.B.L. (2016). Green human resource management and green supply chain management: Linking two emerging agendas. Journal of Cleaner Production, 112, 1824–1833. Kahraman C., Ruan D., and Dogan I. (2003). Fuzzy group decision making for facility location selection. Information Sciences, 157, 135–153. Karpak B., Kumcu E., and Kasuganti R.R. (2001). Purchasing materials in the supply chain: managing a multi-objective task. European Journal of Purchasing & Supply Management, 7(3), 209–216. Kazancoglu Y., Kazancoglu I., and Sagnak M. (2018). A new holistic conceptual framework for green supply chain management performance assessment based on circular economy. Journal of Cleaner Production, 195, 1282–1299. Kilincci O. and Onal S.A. (2011). Fuzzy AHP approach for supplier selection in a washing machine company. Expert Systems with Applications, 38, 9656–9664. Kleindorfer P.R., Singhal K., and Wassenhove L.N. (2005). Sustainable operations management. Production and Operations Management, 14(4), 482–492. Lau K.H. (2011). Benchmarking green logistics performance with a composite index. Benchmarking: An International Journal, 18(6), 873–896.

86

Muhittin Sagnak

Luthra S. and Mangla S.K. (2018). When strategies matter: Adoption of sustainable supply chain management practices in an emerging economy’s context. Resources, Conservation and Recycling, 138, 194–206. Malviya R.K. and Kant R. (2015). Green supply chain management (GSCM): A structured literature review and research implications. Benchmarking: An International Journal, 22(7), 1360–1394. Mangla S., Madaan J., and Chan F.T. (2013). Analysis of flexible decision strategies for sustainability-focused green product recovery system. International Journal of Production Research, 51(11), 3428–3442. Margolis J.D. and Walsh J.P. (2003). Misery loves companies: Rethinking social initiatives by business. Administrative Science Quarterly, 48(2), 268–305. McKinnon A., Browne M., Piecyk M., and Whiteing A. (2015). Green logistics: Improving the environmental sustainability of logistics (Third ed.). Kogan Page. Londres, Philadelfia, USA. Moisander J. and Pesonen S. (2002). Narratives of sustainable ways of living: Constructing the self and the other as a green consumer. Management Decision, 40(4), 329–342. Newholm T. and Shaw D. (2007). Studying the ethical consumer: A review of research. Journal of Consumer Behavior, 6(5), 253–270. Onut S., Kara S.S., and Isik E. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Systems with Applications, 36, 3887–3895. Paulraj A. (2009). Environmental motivations: A classification scheme and its impact on environmental strategies and practices. Business Strategy and the Environment, 18(7), 453–468. Paulraj A. (2011). Understanding the relationships between internal resources and capabilities, sustainable supply management and organizational sustainability. Journal of Supply Chain Management, 47(1), 19–37. Rao P. and Holt D. (2005). Do green supply chains lead to competitiveness and economic performance?. International Journal of Operations and Production Management, 25(9), 898–916. Rostamzadeh R., Govindan K., Esmaeili A., and Sabaghi M. (2015). Application of fuzzy VIKOR for evaluation of green supply chain management practices. Ecological Indicators, 49, 188–203. Saaty T.L. (1980). The analytic hierarchy process. New York: McGraw-Hill. Sarkis J., Zhu Q., and Lai K.H. (2011). An organizational theoretic review of green supply chain management literature. International Journal of Production Economics, 130(1), 1–15. Seuring S. and Müller M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699–1710. Shang K.C., Lu C.S., and Li S. (2010). A taxonomy of green supply chain management capability among electronics-related manufacturing firms in Taiwan. Journal of Environmental Management, 91(5), 1218–1226. Sharma A. and Kearins K. (2011). Interorganizational collaboration for regional sustainability: What happens when organizational representatives come together?. The Journal of Applied Behavioral Science, 47(2), 168–203. Sharma V.K., Chandna P., and Bhardwaj A. (2017). Green supply chain management related performance indicators in agro industry: A review. Journal of Cleaner Production, 141. 1194–1208. Srivastava S.K. (2007). Green supply chain management: A state-of-the-art literature review. International Journal of Management Reviews, 9(1), 53–80. Taylor K.M. and Vachon S. (2018). Empirical research on sustainable supply chains: IJPR’s contribution and research avenues. International Journal of Production Research, 56(1–2), 950–959. Tseng M.L., Lin Y.H., Tan K., Chen R.H., and Chen Y.H. (2014). Using TODIM to evaluate green supply chain practices under uncertainty. Applied Mathematical Modelling, 38, 2983–2995. Turban D.B. and Greening D.W. (1997). Corporate social performance and organizational attractiveness to prospective employees. The Academy of Management Journal, 40(3), 658–672.

4 Assessment of logistics performance in sustainable supply chain

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Tyagi M., Kumar P., and Kumar D. (2015). Parametric selection of alternatives to improve performance of green supply chain management system. Procedia – Social and Behavioral Sciences, 189. 449–457. Uygun O. and Dede A. (2016). Performance evaluation of green supply chain management using integrated fuzzy multi-criteria decision making techniques. Computers and Industrial Engineering, 102, 502–511. Vachon S. and Klassen R.D. (2007). Supply chain management and environmental technologies: the role of integration. International Journal of Production Research, 45(2), 401–423. Vanalle R.M., Ganga G.M.D., Godinho Filho M., and Lucato W.C. (2017). Green supply chain management: An investigation of pressures, practices, and performance within the Brazilian automotive supply chain. Journal of Cleaner Production, 151. 250–259. Vannieuwenhuyse B., Gelders L., and Pintelon L. (2003). An online support system for transportation mode choice. Logistics Information Management, 16(2), 125–133. Wisner J.D. (2003). A structural equation model of supply chain management strategies and firm performance. Journal of Business Logistics, 24(1), 1–26. World Commission on Environment and Development (WCED). (1987). Our Common Future. Oxford, England: Oxford University Press. Wu K.J., Liao C.J., Tseng M.L., and Chiu A.S. (2015). Exploring decisive factors in green supply chain practices under uncertainty. International Journal of Production Economics, 159, 147–157. Yadav G. and Desai T.N. (2016). Lean Six Sigma: a categorized review of the literature. International Journal of Lean Six Sigma, 7(1), 2–24. Younis H., Sundarakani B., and Vel P. (2016). The impact of implementing green supply chain management practices on corporate performance. Competitiveness Review, 26(3), 216–245. Zadeh L.A. (1965). Fuzzy sets. Information Control, 8, 338–353. Zhu Q. and Sarkis J. (2004). Relationships between operational practices and performance among early adopters of green supply chain management practices in chinese manufacturing enterprises. Journal of Operations Management, 22(3), 265–289. Zhu Q., Sarkis J., and Geng Y. (2005). Green supply chain management in China: pressures, practices and performance. International Journal of Operations and Production Management, 25(5), 449–468. Zhu Q., Sarkis J., and Lai K.H. (2007). Green supply chain management: pressures, practices and performance within the Chinese automobile industry. Journal of Cleaner Production, 15, 1041–1052. Zhu Q., Sarkis J., and Lai K.H. (2008). Confirmation of a measurement model for green supply chain management practices implementation. International Journal of Production Economics, 111, 261–273. Zhu Q., Sarkis J., and Lai K.H. (2013). Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. Journal of Purchasing and Supply Management, 19(2), 106–117.

Ashutosh Pandey, Rajendra Sahu

5 Service designing through Fuzzy Kano analysis in heritage tourism Abstract: Service quality management is one of the vital roles to be managed during the process of supply chain management in an organization. The objective of this chapter is to prioritize the service process design in heritage tourism, where a dearth of such study was noticed during a systematic literature review. The prioritization was done using fuzzy multicriteria decision-making with Kano analysis. The data have been collected from overall 263 inbound tourists visiting the five famous heritage sites located in the golden triangle circuit in India through fuzzy Kano questionnaire. It resulted in a classification of 24 service attributes into four fuzzy Kano factors, namely, must-be quality, one-dimensional quality, attractive quality, and indifferent quality. Service blueprint was utilized to visualize the prioritization done through fuzzy Kano analysis. It resulted in the identification of seven service blueprint stages, namely, vehicle parking, ticket purchase, entry gate, heritage site tour, shopping souvenir, resting at the park, and depart. The given study would be useful for the destination marketing organizations, tourism policymakers, tourism managers to critically analyze the factors responsible for bringing the changes in tourist experiences while visiting a place. It can help to build a robust service delivery process, an essential aspect of supply chain management and further can help increase inbound tourists’ satisfaction and inflow at the place. Keywords: fuzzy Kano, heritage tourism, inbound tourist, service blueprint, service designing, service quality

5.1 Introduction The building blocks of supply chain management (SCM) such as supply, distribution, and production have been borrowed conceptually from economics. SCM has been criticized in the past due to its much focus on tangibility (Prakash, 2011; Vargo and Lusch, 2004). The tangibility concept having service – dominance perspective has been identified as a need of an hour by many researchers for building a robust SCM system through a value-creation network. It enhances the role of ser-

Ashutosh Pandey, Rajendra Sahu, Department of Management, ABV – Indian Institute of Information Technology and Management, Gwalior, Madhya Pradesh, India https://doi.org/10.1515/9783110628593-005

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vice as a value coproduction on partner involving the people, technology, other internal and external services, and sources of information (Lusch and Vargo, 2006; Spohrer et al., 2007). This study looked into the field of heritage tourism for the scope of improvisation of the service delivery process, which is an essential aspect of SCM. The tourism industry is one of the fastest-growing service industry in the world (Bouzahzah and El Menyari, 2013; Daniel et al., 2017). With the advent of new technologies, changes in tastes and preferences and the dynamic nature of tourism, tourists are demanding better experience by having a memorable and engaging travel experience rather than the conventional sun and sand tours (Mkono, 2012). Seeing the changing needs of tourists, the demand for heritage tourism has grown, and policymakers of different countries are taking this as an integral part of their service economy (Timothy, 2014). If we look into India’s tourism sector, despite its rich cultural heritage aspect and a favorable world cultural ranking, the foreign tourist arrivals are comparatively low as compared to its Western and Asian counterparts (Table 5.1). Table 5.1: List of top cultural ranking countries and inbound tourist arrivals. Sl. No.

Country

. . . . . . .

China Spain France Japan Italy Germany India

International tourist arrival

World cultural ranking

,, ,, ,, ,, ,, ,, ,,

      

Sources: United Nation World Tourism Organization (2017) and World Economic Forum, The travel and tourism competitiveness report 2017.

Geary (2013) criticized that the majority of resources spent on creating a brand image through financial investment rather than focusing on the creation of tourists’ experiences at the place. This led us to introspect on service quality issue in the heritage tourism of India and defined the research gaps. Past studies show that that much of the service quality studies in heritage tourism were derived by the linearity concept, which says satisfying the particular service attribute would lead to customer satisfaction. Many researchers criticized this linearity concept of service quality and advocated the non-linearity concept of service quality (Harrington et al., 2017; Kano et al., 1984; Lin et al., 2018; Pawitra and Tan, 2003). The first objective focuses on the prioritization of service quality attributes in heritage tourism through fuzzy Kano analysis. The second objective focuses on designing the service blueprint by identifying the various failure points during service-delivery process.

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5.2 Theoretical framework 5.2.1 SCM and service quality The concept of SCM has been evolved from a product focus approach to further including the services approach. Chopra and Meindl (2010) mentioned, “A supply chain consists of all stages involved, directly or indirectly, in fulfilling a customer request. The supply chain includes not only the manufacturer and suppliers, but also transporters, warehouses, retailers, and customers themselves.” Baltacioglu et al. (2007) mentioned the importance of service delivery in their definition as “a network of suppliers, service providers, consumers, and other supporting units that performs the functions of transactions of resources required to produce services; transformation of these resources into supporting and core services and the delivery of these services to customers.” Prior research says that service quality developed along with supply chain enhances the business performance of an organization along with developing a loyal customer base (Sachdeva and Gandhi, 2019). The SCM of an organization achieves a differential advantage by delivering superior value to its customers (Prakash, 2014). Therefore, service quality can act as a catalyst for SCM and can enhance overall business productivity.

5.2.2 The Kano model Kano model, which was proposed by Professor Noriaki Kano, highlights the nonlinear dimension of customer satisfaction and prioritizes their needs as per effect on their satisfaction. It categorizes the customer requirements into five categories, namely, “must-be,” “one-dimensional,” “attractive,” “indifferent” and “reverse requirements.” Table 5.2 describes, in brief, the five categories, as mentioned by Kano et al. (1984). Figure 5.1 presents the Kano model, as suggested by Robinson (2009). As Kano analysis presents the nonlinear dimensions of service attributes, it would be helpful to prioritize the service quality attributes in the heritage tourism and to enhance the overall tourist experiences while visiting the heritage sites.

5.2.3 The fuzzy theory Professor Zadeh (1965) introduced the fuzzy concept, which helps to remove the vagueness or uncertainty in real-life using the mathematical methodology. It is based on membership function that assigns the elements involved with a value of 0 to 1. It helps to deal with vagueness, ambiguity, and uncertainty in the data.

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Table 5.2: List of top cultural ranking countries and inbound tourist arrivals. Quality factors

Meaning

Must- be factor

It results in “dissatisfaction” if not fulfilled and “taken for granted” when fulfilled. It results in “dissatisfaction” if not fulfilled and “satisfaction” if fulfilled. It does not result in “dissatisfaction” if not fulfilled and results in “satisfaction” if fulfilled. It does not have any effect with its presence or absence on customer satisfaction or dissatisfaction. Assuming that all people are not alike, it results in “dissatisfaction” when fulfilled and “satisfaction” when not fulfilled.

One-dimensional factor Attractive factor Indifference factor Reverse factor

Source: Kano et al. (1984).

Customer satisfaction Very satisfied

Attractive One dimensional

Indifferent Fully

Not at all

Degree of achievement

Must be

Very dissatisfied

Reverse

Figure 5.1: Kano model (Robinson, 2009).

5.2.4 The fuzzy Kano model It is the combination of two concepts, that is, Fuzzy, a multicriteria decisionmaking tool and Kano model as proposed by Kano et al. (1984). The Kano model based on traditional functional and dysfunctional questions faces the problem of providing the option of single response and uncertainty due to unclear views of respondents (Table 5.3). Therefore, Fuzzy theory is connected with the Kano model to strengthen the model and to remove the vagueness and uncertainty arising while

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Table 5.3: The traditional Kano questionnaire. Services

Like

Functional Dysfunctional

✓

Must-be

Neutral

Live-with

Dislike

✓

answering the questionnaire. It provides the flexibility to the respondents to give multiple responses for a given question (Shahin et al., 2017). The respondents under fuzzy Kano model are asked two sets of questionnaires with an option of marking multiple responses for the single question (Table 5.4). The first set of functional questions are positively framed questions such as “If the visitors are made to feel welcome, how do you feel?” The second set of dysfunctional questions are negatively framed questions such as “If the visitors are not made to feel welcome, how do you feel?”

Table 5.4: The fuzzy Kano’s questionnaire. Services Functional Dysfunctional

Like

Must-be

Neutral

.

.

.

Live-with

Dislike

.

.

The responses of fuzzy Kano questionnaire are collected and summarized into two matrixes named F and D for each set of questions. F = ½0.2 0.7 0.1 0 0 D = ½0 0 0 0.4 0.6 In the next stage, fuzzy matrix is created by multiplying the functional and dysfunctional responses. It results into creation of 5 × 5 Kano’s two-dimensional fuzzy matrix combination S as given in eq. (5.1). 2 3 0 0 0 0.08 0.12 6 0 0 0 0.28 0.42 7 6 7 6 7 7 0 0 0 0.04 0.06 S=6 (5:1) 6 7 6 7 4 5 00000 00000 After creating the 5 × 5 fuzzy matrix, the result is matched with the Kano evaluation table given in Table 5.5 as proposed by Matzler and Hinterhuber (1998) to prioritize the responses under five Kano categories as given in eq. (5.2).

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Table 5.5: Kano evaluation table. Dysfunctional questions Functional questions

. Like . Must be . Neutral . Live with . Dislike

 T=

. Like

. Must-be

. Neutral

. Live-with

. Dislike

Q R R R R

A I I I R

A I I I R

A I I I R

O M M M Q

M O I A R Q , , , , , 0.42 0.12 0.28 0.08 0 0

 (5:2)

Next, as per the common consensus and standard α cut is applied on the identified value of T (eq. 5.2). The threshold value of α cut is taken as α ≥ 0.4. Large α cut (α > 0.4) results into less coverage representation of samples. Low α cut (α < 0.4) results into formation of happy threshold and lower sample subordination (Chai et al., 2015; Meng et al., 2015). Therefore, α ≥ 0.4 is considered to evaluate the Kano categorization and the fuzzy Kano category that was found to be equal or more than the α ≥ 0.4, which was given the attribute value = 1, and others as 0. Hence, the final result obtained was T = (1, 0, 0, 0, 0, and 0). If more than one Kano category was found to be having attribute value as 1, then the priority level was set as per the Kano prioritization of quality attributes (M > O > A > I > R).

5.2.5 Service blueprint Service blueprint recognizes the complex nature of service between human, product, and process (Lee et al., 2015). It helps to design the robust business process by improving the service model of operation by formulating the concern duties of an individual in the service system (Shostack, 1982). Service blueprint helps to avoid conflicts while delivering the services by visualizing the service delivery process. It helps to identify the failure points and weaknesses in the delivery process through visualization of the service delivery process. Service failure may occur if the service delivery process is not managed at different stages. The intangible nature of services is required it to be adequately managed, and hence Shostack (1987) created service blueprint for efficiently managing the service delivery process through designing the services. Prior studies reveal that the service blueprint has been designed in various fields such as historic houses (Laws, 1998), hotel services (Milton and Johnson, 2012), and nature-based tourism (Albrecht, 2014). The systematic literature review revealed that no such study had been carried out in improvising the service delivery process through service blueprint in the

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Physical evidence Customer actions Contact person

Onstage Backstage

Support processes

Line of interaction Line of visibility Line of internal interaction

Figure 5.2: Model of service blueprint as suggested by Zeithaml and Bitner (2003).

heritage setting in India. Service designing was done by adopting the service blueprint proposed by Zeithaml and Bitner (2003), as shown in Figure 5.2.

5.3 Empirical case study Fuzzy Kano analysis was performed in a heritage setting in India. Six top locations as per the inbound tourists’ footfalls were chosen from the golden triangle tourist circuit comprising Jaipur–Delhi–Agra route in India. After prioritizing the heritage service attributes through fuzzy Kano analysis, service blueprint was designed by adopting Zeithaml and Bitner (2003) service blueprint model as given in Figure 5.2. The details of the empirical case study are mentioned in the following sections.

5.3.1 Questionnaire design and data collection The questionnaire had two parts: the first part asked the demographic information and the second part collected functional and dysfunctional responses through fuzzy Kano analysis. For collecting the responses of the second part of the questionnaire, Histoqual scale proposed by (Frochot and Hughes, 2000) containing 24 service quality attributes. The data were collected from the golden triangle circuit namely, Amber Fort and Hawa Mahal from Jaipur, Red fort and Qutub Minar from Delhi, Agra Fort and Taj Mahal from Agra. A Cochran formula with 5% margin error was used to calculate the minimum sample size required to be collected for data analysis. The Cochran formula revealed that at least a sample size of 377 samples are required to be collected. Using a cross-sectional study design and a proportionate quota sampling, 100 samples were collected from the six locations. Mall interception method was used to collect the overall data from each location through the help of 24 graduate students from the field of management and tourism. Proper

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training and instructions were provided to the graduates for collecting the data from the given locations. The data was collected from January to March 2019. Sampling units were male and female inbound tourists above 18 years of age. A total of 487 sample data were received, and after careful analysis, 82 data were removed due to inaccuracy, missing information, and redundancy. Therefore, a total of 405 data were found suitable for the given study. Demographic information collected from the respondents revealed that majority of tourist were male (68.64%) with maximum visitors falling in the age group of 26–32 (48.88%). The majority of the inbound tourists were having average income under $1,000–$2,000 (55.30%). Majority of them were found to be married (58.27%) and most of them had bachelor’s degree (58.51%). The tourists were found to be mostly from the USA (28.64%), followed by Europe (26.66%), the UK (21.97%), Asia (11.85%), Australia (7.16%), and Africa (3.70%).

5.3.2 Fuzzy Kano prioritization The second part of the questionnaire containing functional and dysfunctional set of questions was evaluated and prioritized using fuzzy Kano analysis. Using the α cut ≥ 0.4, the service attributes were classified into four categories namely, must-be quality, one-dimensional quality, indifferent quality, and attractive quality. Table 5.6 presents the service attributes prioritization based on fuzzy Kano analysis. The result revealed five service attributes classified under must-be attributes, seven service attributes classified under one-dimensional quality attributes, three service attributes were classified under attractive quality attributes, and nine service attributes were classified under indifferent quality attributes.

Table 5.6: Fuzzy Kano prioritization and customer satisfaction indices. Service Attributes Courteous and helpful staff Staffs willingness to take time with visitors Visitors welcome greetings Tolerable crowding level Well-informed staffs to answer the tourists’ query Easy accessibility around the site Convenient opening hours at property Easy availability of staff Well-kept and restored property

A         

O

M

I Category

   O    O    I    O    I    A    A    O    M

SII

DDI

. . . . . . . . .

−. −. −. −. −. −. −. −. −.

97

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Table 5.6 (continued ) Service Attributes

A

Cleanliness and upkeep of the property is satisfying Attractive grounds Authentic sites Clear and helpful direction signs Large variety of plants in garden and park Interesting interiors of the house Enough information provided by leaflet Detailed information mentioned on the property and ground Visitors are well-informed about different facilities and attraction available at the site Helpful foreign language leaflets Wide variety of dishes and refreshment offered by restaurants Large variety of goods offered by shops Efficient services provided by restaurant staffs Need of less able visitors are taken care by the place Facility for children are provided

       

O

M

 

I Category  M

   I    M    I    I    A    M    M

SII

DDI

. −. . . . . . . .

−. −. −. −. −. −. −.

 



 O

. −.

   

  I   O

. −. . −.

     

  I   O   I

. −. . −. . −.



  I

. −.



5.3.3 Customer satisfaction indices It is used to analyze, how strong the customer sentiments are regarding satisfaction and dissatisfaction of Kano categorized service attributes (Hu and Hsiao, 2016). Satisfaction indices are of two types namely, satisfaction increment index (SII) and dissatisfaction decrement index (DDI). The formulae for calculating both the indices are given in eqs. (5.3 and 5.4). The SII equation explains greater the satisfaction level if the value is found to be close to 1. Similarly, DDI equation explains the greater the dissatisfaction level if the value is found to be close to −1. The SII and DDI equations for the fuzzy Kano service attributes are shown in Table 5.6. SII =

DDI =

A+O A+O+M+I

(5:3)

− ðO + M Þ ðA + O + M + I Þ

(5:4)

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5.3.4 Designing customer satisfaction matrix Customer satisfaction quadrant matrix quantifies the sentiments of the customers through the help of satisfaction indices (SII and DDI). It has four quadrants. The first quadrant explains about the attractive quality attributes and known as “increased satisfaction area.” The second quadrant explains about indifferent quality attributes and known as “indifference area.” The third quadrant explains about the must-be quality attributes and known as “eliminate dissatisfaction area.” The fourth quadrant represents one-dimensional quality attributes and known as “improvement area.” Figure 5.3 shows the customer satisfaction matrix visualizing the various fuzzy Kano service attributes.

−20

Quadrant 2 (Indifference area)

Quadrant 1 (Increased satisfaction area)

I

−40

I II I I I I I

A AA

DDI

Quadrant 3 (Dissatisfaction area)

Quadrant 4 (improvement area)

−60

O

O

O M M −80

M

M O

M

O O 20

40

60

O 80

SII Figure 5.3: Customer Satisfaction Matrix. A = Attractive Quality, I = Indifferent Quality, M = Must Be Quality, O = One Dimensional Quality. SII = Satisfaction Increment Index, DDI = Dissatisfaction Decrement Index.

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The details of service attributes identified under each quadrant are as follows:

5.3.4.1 Quadrant 1 It includes the attractive quality elements such as easy accessibility around the site, convenient opening hours of the property, and interesting interiors of the house. This service attributes to enhance customer delight if fulfilled. Hence, it can be taken care of increasing the satisfaction level of customers.

5.3.4.2 Quadrant 2 It includes the indifference quality attributes such as visitors welcome, well-informed staffs, attractive grounds, clear and helpful signs, a large variety of plants in the garden, helpful foreign language leaflets, a large variety of goods in shops, efficient services by restaurant staffs, need for less-abled visitors, and facilities for children. These service attributes do not affect the satisfaction or dissatisfaction of customer, and, hence, the resources can be optimized for all these service attributes by shifting the requirement for other critical service attributes.

5.3.4.3 Quadrant 3 It includes the must-be quality service attributes such as well-kept property, cleanliness, and upkeep of the property, authenticity of sites, leaflet information and detailed information mentioned on property and grounds. These service attributes result in both high dissatisfaction if not fulfilled, and satisfaction if fulfilled; hence, these attributes cannot be avoided. The organizsations must take care of these attributes, which may bring changes in customers’ satisfaction if not fulfilled.

5.3.4.4 Quadrant 4 These service attributes include one-dimensional quality attributes such as courteous and helpful staff, staff willingness to take time with customers, tolerable to crowd, easy availability of staff, visitors being well informed about the facilities and attraction available at the site, availability of a variety of dishes at restaurant and efficient service provided by restaurant staff. These elements result in dissatisfaction if not fulfilled, and hence they are seen as an improvement area, which is required to be maintained by the organization for delivering customer satisfaction.

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5.4 Designing service blueprint Service blueprinting helps to visualize the overall interaction between the customer and service provider sequentially. It helps to identify the different fall points, which could be the reason for changes in customer satisfaction and overall experiences. It consists of a line of interaction that draws a line between customer action and service provider actions. Next, it contains a line of internal interaction that draws a line between the back office and support process. Service blueprint was designed using the model adopted from Zeithaml and Bitner (2003). The stages of service blueprint were validated through qualitative study and means of actions. It included observational study while collecting the data from inbound tourists. The general activities of tourists while visiting the place were monitored, and various steps were noted down. This systematic literature review conducted in the field of service blueprinting also helped to chalk out the stages. Next, the identified stages went through an expert opinion. Overall, eight experts were included in the panel having two subject experts, two professional guides, two tour managers, and two research scholars in the field of tourism and management. The expert opinion went through confirmation and reconfirmation stages, and finally, the refined stage containing seven steps were finalized for designing service blueprint. Further, a pilot study was conducted where the finalized stages were shown to the group of five inbound tourists for the feedback. Majority of the tourists supported the stages finalized during the past process. Finally, the fuzzy Kano prioritized service quality attributes that were mapped using the service blueprint while designing each stage. Fuzzy Kano prioritization helped to identify the critical service attributes, which could bring changes in the overall experiences of the tourist while visiting the heritage sites. Figure 5.4 in Appendix 1 represents the service blueprint designed for the heritage sites. The blueprint is divided into seven stages in chronological order, namely, vehicle parking, ticket purchasing, entry gate, heritage site tour, shopping souvenir, resting at the ground/park, and departure.

5.5 Conclusion and implications This research was carried on to design a robust service delivery process in heritage setting depicting the fuzzy Kano prioritized service attributes as per the experiences shared by the inbound tourists in India. The novelty of this research is that it explored the nonlinear dimension of service quality in heritage tourism. No such research has been carried on in Indian context for exploring the nonlinear dimensions of service quality attributes of heritage tourism in India. Based in line with past studies done in the context of historic houses (Laws, 1998) and naturebased tourism (Albrecht, 2014), this study presented the similar concept of service

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blueprint in heritage tourism. First, this study would be useful to destination marketing organizations, tourism managers, and operation management and staff to identify the various critical fall points and plan the service delivery process accordingly leading to avoidance of service failure, increase in customer satisfaction, and increase in overall efficiency. There are certain limitations to the study that has been carried on in Heritage setting of tourism, and future studies can be carried on in other fields of tourism such as adventure tourism, religious tourism, medical tourism, and many more. Second, it has been carried on in the Indian context; and future studies can be replicated in other countries to validate the study further. Third, this study is based on Histoqual scale for deriving service attributes in heritage settings. There are certain limitations of Histoqual, such as its broad applicability to the entire heritage setting apart from historic houses and its limited service attributes. Future studies can be done, including more service attributes in the context of heritage tourism in a broader way.

References Albrecht J.N. (2014). Micro-mobility patterns and service blueprints as foundations for visitor management planning. Journal of Sustainable Tourism, 22(7), 1052–1070. Baltacioglu T., Ada E., Kaplan M.D., Yurt O., and Kaplan Y.C. (2007). A new framework for service supply chains. Service Industries Journal, 27(2), 105–124. Bouzahzah M. and El Menyari Y. (2013). International tourism and economic growth: the case of Morocco and Tunisia. Journal of North African Studies, 18(4), 592–607. Chai C., Bao D., Sun L., and Cao Y. (2015). The relative effects of different dimensions of traditional cultural elements on customer product satisfaction. International Journal of Industrial Ergonomics, 48, 77–88. Chopra S. and Meindl P. (2010). Supply chain management. Prentice-Hall: Pearson Education. Daniel A.D., Costa R.A., Pita M., and Costa C. (2017). Tourism Education: What about entrepreneurial skills?. Journal of Hospitality and Tourism Management, 30, 65–72. Frochot I. and Hughes H. (2000). HISTOQUAL: The development of a historic houses assessment scale. Tourism Management, 21(2), 157–167. Geary D. (2013). Incredible India in a global age: The cultural politics of image branding in tourism. Tourist Studies, 13(1), 36–61. Harrington R.J., von Freyberg B., Ottenbacher M.C., and Schmidt L. (2017). The different effects of dis-satisfier, satisfier and delighter attributes: Implications for Oktoberfest and beer festivals. Tourism Management Perspectives, 24, 166–176. Hu K.C. and Hsiao M.W. (2016). Quality risk assessment model for airline services concerning Taiwanese airlines. Journal of Air Transport Management, 53, 177–185. Kano N., Seraku N., Takahashi F., and Tsuji S. (1984). Attractive quality and must-be quality. Journal of the Japanese Society for Quality Control, 41, 39–48. Laws E. (1998). Conceptualizing visitor satisfaction management in heritage settings: An exploratory blueprinting analysis of Leeds Castle, Kent. Tourism Management, 19(6), 545–554. Lee C.H., Wang Y.H., and Trappey A.J.C. (2015). Service design for intelligent parking based on theory of inventive problem solving and service blueprint. Advanced Engineering Informatics, 29(3), 295–306.

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Lin C.F., Fu C.S., and Li C.C. (2018). Integrating means-end chains and the Kano model to understand tourists’ cognitive structure toward leisure and recreational resources of suburban-mountains. Asia Pacific Journal of Tourism Research, 23(2), 183–199. Lusch R.F. and Vargo S.L. (2006). Service-dominant logic: reactions, reflections and refinements. Marketing Theory, 6(3), 281–288. Matzler K. and Hinterhuber H.H. (1998). How to make product development projects more successful by integrating Kano’s model of customer satisfaction into quality function deployment. Technovation, 18(1), 25–38. Meng Q., Jiang X., He L., and Guo X. (2015). Integrating fuzzy theory into Kano model for classification of service quality elements: A case study of machinery industry in China. Journal of Industrial Engineering and Management, 8(5), 1661–1675. Milton S.K. and Johnson L.W. (2012). Service blueprinting and BPMN: A comparison. Managing Service Quality, 22(6), 606–621. Mkono M. (2012). Cultural heritage and tourism: an introduction, by Dallen J. Timothy. Journal of Heritage Tourism, 7(3), 277–278. Pawitra T.A. and Tan K.C. (2003). Tourist satisfaction in Singapore – a perspective from Indonesian tourists. Managing Service Quality: An International Journal, 13(5), 399–411. Prakash G. (2011). Service quality in supply chain: Empirical evidence from Indian automotive industry. Supply Chain Management, 16(5), 362–378. Prakash G. (2014). QoS in the internal supply chain: The next lever of competitive advantage and organisational performance. Production Planning and Control, 25(7), 572–591. Robinson C. (2009). How is Kano survey prepared and analyzed. The Journal for Quality and Participation, 32(2), 1–3. Sachdeva A. and Gandhi S.K. (2019). Operationalization and Measurement of Service Quality in Manufacturing Supply Chains: A Conceptual Framework. Shahin A., Barati A., and Geramian A. (2017). Determining the Critical Factors of Radical Innovation Using an Integrated Model of Fuzzy Analytic Hierarchy Process-Fuzzy Kano With a Case Study in Mobarakeh Steel Company. EMJ – Engineering Management Journal, 29(2), 74–86. Shostack G.L. (1982). How to Design a Service. European Journal of Marketing, 16(1), 49–63. Shostack G.L. (1987). Service Positioning through Structural Change. Journal of Marketing, 51(1), 34. Spohrer J., Maglio P.P., Bailey J., and Gruhl D. (2007). Steps toward a science of service systems. Computer, 40(1), 71–77. Timothy D.J. (2014). Contemporary cultural heritage and tourism: Development issues and emerging trends. Public Archaeology, 13(1–3), 30–47. United Nations World Tourism Organization (UNWTO) (2017), UNWTO Tourism Highlights 2017, UNWTO, Madrid, Spain available at: https://www.e-unwto.org/doi/pdf/10.18111/ 9789284419029 (accessed 8th June 2019). Vargo S.L. and Lusch R.F. (2004). The Four Service Marketing Myths: Remnants of a Goods-Based, Manufacturing Model. Journal of Service Research, 6(4), 324–335. World Economic Forum. (2017). The travel & tourism competitiveness report 2017. Geneva: World Economic Forum. Zadeh L.A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. Zeithaml V.A. and Bitner M.J. (2003). Services marketing: Integrating customer focus across the firm (3rd ed.). New York, NY: McGraw-Hill Irwin.

Ticket purchase

Vehicle parking

Line of internal interaction

Line of visibility

Supporting system

F

Operation managers and staff

Availability of large variety of goods and souvenir.

Shopping souvenir

F5

Fail point

Convenient opening hours of property Attractive ground Availability of large variety of plants

Resting at the ground/park

F6

Crowd management Visitors informed about the facilities Visitors welcome

Entry gate

F3

Customer activities

Maintenance staff

Depart

F7

Figure 5.4: Service Blueprint of Heritage Site. Notes: M = must-be, O = one-dimensional, A = attractive, I = indifferent; the numbers in parentheses indicate the satisfaction coefficient and dissatisfaction coefficient.

Back office

Easy accessibility at the heritage site Maintaining authenticity of site Up keeping of the site Maintenance of Cleanliness at the site Proper display of historical information at monuments Staffs willingness to take time with tourists Staffs availability when needed Interesting interior of the site Helpful foreign language leaflets

Heritage site tour

F4

Maintenance of ticket counters Helpful and courteous staff Informative leaflets

F2

F1

Line of interaction

Front office

Proper signage direction at site Well informed staffs for tourists query

Appendix 1

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6 Developing a framework to provide technological solutions for implementing green supply chain Abstract: Issues on environmental sustainability in every developmental activities of human civilization are the prime concern for all the stakeholders associated with the events. The idea of implementing green initiatives is an effort to attain longterm sustainability results to maintain environmental and ecological balance. The aim of the present research is to review the literature on current state of technological issues, problems, and various other aspects of green supply chain and the need of implementing technological solutions for the same. Based on the literature review, suitable gaps have been found out and outlined in future research directions. Further, the study also consider a case of Food and Civil Supplies Department of Uttar Pradesh and suggest what technological solutions are required for the same. Keywords: environmental sustainability, green supply chain, technological solutions

6.1 Introduction Sustainability issues become a critical consideration in the design of all the operational activities of a supply chain. The different activities and functions are (a) procurement of raw materials from suppliers, (b) processing of the product within the core facility, and (c) its distribution through selective channels to finally reach its end user requires assessment in the wake of environmental concerns. The term sustainable supply chain and green supply chain (Mardani et al., 2019; Zaid et al., 2018; Gautam et al., 2019; Luthra et al., 2016a; Luthra et al., 2016b; Chin et al., 2015; Ahi and Searcy, 2013) adheres to the concept and implies adapting different strategies, policies, and frameworks into the design aspects of any supply chain to make it more efficient, sustainable, and environment friendly in achieving long-term results in terms of operational efficiency and economic viability. The various constituents and functional activities of this green supply chain framework include green suppliers, green material sourcing, green procurement, green management, green marketing, green logistics, and application of associated green technologies. This chapter presents an exhaustive literature

Somen Dey, School of Management Studies, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, Uttar Pradesh, India https://doi.org/10.1515/9783110628593-006

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review to understand the principles underlying the integration of green initiatives in the design of a supply chain for the achievement of sustainable growth oriented results with an objective to develop a sustainable green framework for the supply chain of a public food supplies department.

6.2 Literature review on green supply chain solutions The last couple of decades have witnessed an increasing rate of environmental issues worldwide, which poses a severe threat to climatic changes and global warming (Joshi et al., 2019; Khan, 2018). The effects are scarcity and degradation of natural resources, air and water pollution, adverse effects on flora and fauna, and increasing rate of diseases, which is a threat to human lives (Joshi & Rahman 2019). The application of green framework with the supply chain aims to minimize or eliminate environmental degradation levels, controls the rising pollution in air, land, and water through the adoption of sustainable green practices. This results an increase in economic growth and creates competitive advantage in terms of customer satisfaction, enhanced environmental sustainability, creating positive image and reputation (Khan et al., 2018). The term green supply chain management or solutions (GSCS) refers to an idea of combining sustainable environmental practices into conventional supply chain operations (Handfield et al. 1997; Srivastava, 2007; Sarkis et al., 2011; Khan et al., 2017; Khan et al., 2018). This includes all related activities such as green supplier selection, green material purchasing or procurement, product designing, manufacturing and continuing through all phases of production, distribution, and waste management or recycle post completion of product’s life. GSCS along with green logistics (GL) is an essential element for attaining longterm sustainable results (El-Berishy et al., 2013; Chen et al., 2018). GL is a multifaceted and multidimensional discipline consisting of upstream and downstream flows of products, services, and information governed by economic, social, and environmental factors. It aims at reducing different kinds of wastes and focus on actions to eliminate the adverse effects on the environment (Mintcheva, 2005). GL is an essential driver for incorporating sustainability in GSCS. The objective of GSCS is achieving a balance or trade-off between profitability and issues concerning environmental sustainability (Cucchiella et al., 2012; Dubey et al., 2017; Genovese et al., 2017; Govindan et al., 2015a; Govindan et al., 2015b; Mangla et al., 2014; Sarkis et al., 2011; Zhu et al., 2008; Zhu and Sarkis, 2004). The green effort is required in different supply chain activities, that is, product or service design, supplier selection, raw materials procurement, manufacturing, packaging, as well as distribution (Barari et al., 2012, Mangla et al., 2013). Figure 6.1 depicts a model of green supply chain practices.

6 Developing a framework to provide technological solutions

Green purchasing

Green manufacturing

107

Green distribution

Reuse/recycle

Customer

Production

Supplier

Recovery

Green reverse logistics Keys:

Materials

Products

Inventory

Figure 6.1: Model of the green supply chain (Khan, 2018).

The list of essential green practices to be adopted for the effective ad successful implementation of GSCS is as follows: a. Green material sourcing: This encompasses all the activities, that is from (1) collaborating with green suppliers for the supply of raw materials. The collaboration is based on prioritizing the various sustainable green indices through application of various quantitative techniques, such as fuzzy logic and set theory (Wang et al., 2019; Liu et al., 2012), identifying the barriers and risks involved using multicriteria decision-making (Kumar et al., 2019; Haeri and Rezaei, 2019; Watrobski et al., 2019), assessing the environmental issue and its impact on performance (Mishra et al., 2019). (2) Procurement of raw materials/components that are eco-friendly, sustainable, reusable, and recyclable (Eltayeb et al., 2011; Govindan et al., 2015a; Govindan et al., 2015b; Handfield et al., 1997; Min and Galle, 2001; Carter and Rogers, 2008). Some researchers also utilized case study based research to understand the green sourcing (Pagell and Wu, 2009). b. Green manufacturing: It refers to approach of redesigning the production processes to integrate eco-friendly operations within the manufacturing field (Luthra et al., 2016a; Luthra et al., 2016b; Govindan et al., 2015a; Govindan et al., 2015b; Eltayeb et al., 2011; Baines et al., 2012; Prajogo and Olhager 2012). It includes several green efforts that consist of sustainable and judicial use of natural resources to eliminate wastages, reduce pollution, such as carbon emissions and adopting a recycling strategy. The Bureau of Labor Statistics details about the specific green technologies developed or initiated are as follows:

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(i)

Utilization of energy from renewable sources, which includes solar, wind, biomass, geothermal, hydropower, ocean and solid waste. (ii) Achieving energy efficiency through sustainable measures and practices. (iii) Pollution reduction, greenhouse gas emissions reduction, and recycling. c.

Green marketing: It includes a broad range of activities (i.e., planning, production, process, pricing strategies, promotional strategies, and after-sales service) designed to sell the products in the market based on their environmental benefits (Groening et al., 2018; Bhaskaran et al., 2006). Organizations adopting green marketing practices, which are committed to sustainable development, social responsibility, are keen in implementation of sustainable business practices and reduction of expenses (production, packaging, transportation). d. Green management: Green management practices enhance an organization’s ability to implement the green practices effectively within the culture of organization by focusing on environmental compliance objectives, increased efficiency, reductions in cost, sustainable results targeted toward the greater welfare of society, and significant reductions in carbon footprint (Lee et al., 2012; Luthra et al., 2016b; Kang et al., 2012). e. Green transportation and reverse logistics: The transportation industry is experiencing significant rapid growth worldwide owing to emergence of new technologies, introduction of new business models, and increased customer expectations. The transportation industry is expected to expand at a compound annual growth rate (CAGR) of 7.5% between 2015 and 2024 (Transparency International Report, 2016). In particular, the Asia Pacific region is one of the largest markets in the world for the transportation industry, with India as one of its promising stakeholders. India’s logistics performance index ranking is improving gradually and is in 36th position in 2016, according to the World Bank. The transportation industry is further expected to grow at a CAGR of 15–20% between 2016 and 2020 with an annual turnover of INR 13,000 crores. Green transportation or green logistics includes activities such as green packaging and warehousing (Baines et al., 2012; Prajogo and Olhager 2012; Khan et al., 2017). GL targets to achieve significant reduction in transportation costs, reduced carbon emissions, opportunity for enhancing efficiency of the transportation systems, increased customer satisfaction, increased profitability, and implementation of green and sustainable technologies in logistics (Luthra at al., 2016b; Govindan et al., 2015a; Govindan et al., 2015b; Brandenburg, M., and Rebs, T., 2015). The integration of reverse logistics (Prajapati et al., 2019a; Agarwal and Singh, 2019; Dev et al., 2019; Bottani et al., 2019; Prajapati et al., 2019b) with green initiatives in a supply chain promotes reusability, recycling, and remanufacturing for the products and materials that can be again used by customers.

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Soda et al. (2016) highlighted the barriers and remedies for the implementing the green supply chain management (GSCM) framework in Indian settings in a coal-based thermal power plant. Kang and Hwang (2017) studied the importance of collaborations and interorganizational interactions for the successful implementation of green initiatives with supply chain operations. The different factors, which directly contribute to the greening effort in supply chains as identified in literature, include reverse logistics, industrial symbiosis, eco-innovation practices, green IT technologies, green design of operations, carbon management, customer environmental collaboration, ISO 14001 certifications, green purchasing, green manufacturing, green packaging, green logistics, green warehousing, green outsourcing policies (Tseng et al., 2019; Maditati et al., 2018; De Oliveira et al., 2018). Rajabion et al. (2019) developed a research model for examining the impact of urban transportation systems, farmer’s awareness regarding green principles on the successful implementation of GSCM for urban distribution of agricultural products. Wang et al. (2018) examined the effects of customer preferences and cost component on GSCM practices. Sharma et al. (2017) identified the key performance indicators for GSCM in an agro-based industry within Indian settings. GL has received considerable attention from both the academic and industrial communities as a result of significant increase in greenhouse gas emission levels from the various transportation operations (El-Berishy and Scholz-Reiter, 2016). Zhang and Zhao (2012) defines GL as a systematic approach in designing and managing different services related to green transportation, storage, packaging, processing, distribution, and green information management to reduce environmental damages and minimize the economic and environmental impacts of these logistics activities. In this direction, Vasiliauskas et al. (2013) developed a framework (Figure 6.2) for the implementation of GL for road transport. Zhu et al. (2008) described the steps for the effective implementation of GL and emphasized that a coordination between the various stakeholders (i.e., business, society, and government agencies) is necessary for the successful realization of GL. The steps consist of (1) taking decisions in the wake of environmental assessment, (2) continuous deployment of advanced eco-friendly technologies, (3) investment and integration, and (4) organizational policies and

Ecologic level

– Optimal routes. – Security of the necessary service level. – Savings of energy resources.

Economic level

Green Logistics concept implementation

– Decrease in pollution. – Use of renewable energy sources. – Savings of fossil fuel.

Social level

Figure 6.2: Key goals for implementing GL (Vasiliauskas et al., 2013).

– Decrease in the number of accidents. – Decrease in congestion. – Security of favorable working conditions.

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management based on green principles. Murphy and Poist (2003) highlighted the necessary actions that need to be undertaken at an enterprise level for the successful implementation GL. These actions included are as follows: a. Reengineering and designing the components of logistics systems by taking environmental and social factors into consideration. b. Encouraging innovations and promoting green logistics for – Inbound logistics. – Intrafacility logistics. – Outbound logistics. c.

Training of staff for creating awareness about green initiatives and green technologies. d. Collaborating with institutions that specialize in green initiatives. e. Audit of environmental control. f. Application of IT tools and technologies supports the successful implementation of GL by ensuring efficient and sustainable consumption of resources, reduces the negative impact of transportation on the environment, increases safety, and decreases possibility of road accidents (Batarliene and Jarasuniene, 2016). Some of the most promising IT applications include tracking systems, distribution systems, reservation systems, fuel consumption control systems, real-time monitoring systems for drivers, control systems for toll collection, safety management, and process control. Further, Vasiliauskas et al. (2013) listed the factors that constitute the internal and external environment influencing the implementation of GL in any organization. The internal environment consists of human (1) resource factors, (2) institutional factors, (3) technical factors, and (4) micro-economic factors. Subsequently, the external environment includes (1) political and legal considerations (such as government support, transparent and flexible subsidy, and grants), (2) social factors (such as living standards, education level, working conditions requirement), (3) ecological factors (such as increasing pollution levels, limited availability of fossil fuels, and expensiveness of energy) and (4) scientific-technical factors (such as IT application levels, modern transport infrastructure, application of information and communication systems i.e., ICTs). Zhang and Zhao (2012) highlighted the importance and management strategy of green packaging of logistics enterprises, which includes use of green packaging materials that are recyclable and do not contribute to environmental degradation. Zhang et al. (2014) identified the prominent drivers for adopting green logistics practices by conducting a case study of road freight industry in China. The designated drivers were further classified according to environment i.e., internal and external. The external drivers included environmental management of logistics, lowcarbon levels in transportation, storage, packaging, fleet management, usage of alternative energy, and logistics innovation. The internal drivers included scale of

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road freight companies, assets and ownership attribute logistics resources, logistics capabilities, and assessment of environmental impacts. Golroudbary et al. (2019) designed and studied sustainable and hybrid logistics models using simulation and suggested framework for decision-making in delivery management. Mesjasz-Lech (2016) highlighted the influence and contribution of GL in reducing the negative environmental impacts such as air pollution. Seroka-Stolka (2016) developed a research framework, which investigated the factors governing logistics, organization’s commitment, and willingness to adopt green initiatives. The factors included in the frame were environmental and purchasing policy, competence building through training and education, effective communication, the implementation of ISO 14001 environmental management systems (EMS), and ecological awareness and responsibility. Watrobski (2016) outlined the applications of multicriteria decision-making (MCDM) tools to the field of GL. Seroka-Stolka and Ociepa-Kubicka (2019) described the relationship between GL and circular economy. Centobelli et al. (2017) developed taxonomy of green initiatives and technological tools (Table 6.1) and investigated their process of diffusion among logistics service providers (LSP). Chhabra et al. (2017) analyzed the performance of different sustainable green practices in Indian automobile industry using analytical hierarchy process (AHP) tool. The various alternatives were evaluated based on three criteria that is, green efficiency, factor of safety, and ease of operation. In addition, many researchers investigated the proponents, antecedents, performance assessment, environmental practices, and critical success factors for the implementation of GL (Lai and Wong, 2012; Sallnas and HugeBrodin, 2018; Aldakhil et al., 2018; Arslan and Sar, 2018). Subramanian et al. (2014) studied and tested a conceptual model that attempts to integrate small and mediumsized logistics providers (SMSLPs) with cloud service providers in China to derive the green and cost-benefits of cloud computing technology.

Table 6.1: A taxonomy of technological tools (derived from Centobelli et al. (2017)). Sl No.

Phase of service

Technological tool



Transportation Global positioning system applications

Emission control systems



Warehousing Warehouse management systems

Real time locating systems



Logistics service Material management systems

Logistics management systems



Management Environmental management systems Enterprise resource planning systems Expert systems Learning management systems

Environmental database systems

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6.3 Implications and future research directions The present research reviews the current state of the art for implementing green framework in supply chain operations. Based on this, various technological solutions such as various matrices, app-based monitoring, and integration to properly manage the green supply chain are proposed to design a green sustainable framework for the Food and Civil Supplies Department of the state of Uttar Pradesh.

6.4 A case study of food supplies department of the state of Uttar Pradesh The Indian state of Uttar Pradesh is the country’s fourth largest state and ranks third in terms of economy. The state ranks second among the top manufacturing states in India, housing a large number of micro, small and medium enterprises in both organized and unorganized sectors with a consumer base of over 200 million population (Transparency International Report (2016)). The exports recorded a CAGR of about 13.26% in the last five years. The Uttar Pradesh government with a vision to support “Make in India” initiative of Government of India, launched the Industrial Investment and Employment Promotion Policy 2017 (IIEPP) and the Food Processing Industry Policy 2017 (FPIP) for enhancing investments in related industries and necessary support infrastructure. Besides, the Uttar Pradesh Warehousing and Logistics Policy 2018 (UPWLP) aims to support IIEPP 2017, by strengthening the logistics sector in particular. The state government envisions building and developing sustainable and eco-friendly logistics and transportation systems in the state. Green logistics is a sustainable framework that aims at reducing the negative ecological impacts as a result of different logistics operations through the implementation of eco-friendly transportation, reduction of carbon emissions, application of scientific disposal techniques, waste management practices, use of bio-degradable items, use of renewable energy sources and adoption of efficient recyclable methods. Hence, the concept of green logistics is promoted under the above policies. There is a need to study and investigate the different supply chain activities and logistics solutions provided by the Food and Civil Supplies Department of Uttar Pradesh for districts of eastern UP and to develop a framework for the implementation of GL and GSCM practices (in terms of achieving long-term sustainability results). The supply chain management systems (Food and Civil Supplies Department, Uttar Pradesh) is responsible for the successful and productive purchase, storage, selling and distribution of necessary items, food grains (i.e., wheat and rice), oils, kerosene, coal, and other petroleum products, seeds and other agricultural products to consumers at reasonable prices. There is growing need to redesign the entire chain operations

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to achieve long-term sustainable results taking into consideration its impact on environment and society. Following are some of the concerns in this direction. a. There is a need to study the current state of the art in existing practices and investigate the different barriers inhibiting the successful adoption of sustainable green technologies and green practices. b. To propose technological solutions in real-time logistics, supply chain management, and process improvement. c. To promote green and innovative practices to develop a competitive logistics infrastructure and reduce the carbon footprint in existing operations of AAPURTI (Food and Civil Supplies Department, Government of Uttar Pradesh). d. To study and identify the factors that govern the top-level management willingness to adopt green initiatives. e. To conduct a feasibility study to forecast the practicality, implementation, and future success of these green technologies.

6.5 Conclusion The integration of a green and sustainable framework into the design consideration of various operational activities in a supply chain is a challenging task. It requires multiple collaborative efforts from various stakeholders of the value chain. Proper design, coordination, and implementation of green framework will ultimately lead to the successful realization of sustainable objectives.

References Agrawal S. and Singh R.K. (2019). Analyzing disposition decisions for sustainable reverse logistics: Triple Bottom Line approach. Resources, Conservation and Recycling, 150, 104448. Aldakhil A.M., Nassani A.A., Awan U., Abro M.M.Q., and Zaman K. (2018). Determinants of green logistics in BRICS countries: An integrated supply chain model for green business. Journal of Cleaner Production, 195, 861–868. Arslan M. and Şar S. (2018). Examination of environmentally friendly “green” logistics behavior of managers in the pharmaceutical sector using the Theory of Planned Behavior. Research in Social and Administrative Pharmacy, 14(11), 1007–1014. Ahi P. and Searcy C. (2013). A comparative literature analysis of definitions for green and sustainable supply chain management. Journal of Cleaner Production, 52, 329–341. Baines T., Brown S., Benedettini O., and Ball P. (2012). Examining green production and its role within the competitive strategy of manufacturers. Journal of Industrial Engineering and Management (JIEM), 5(1), 53–87. Barari S., Agarwal G., Zhang W.C., Mahanty B., and Tiwari M.K. (2012). A decision framework for the analysis of green supply chain contracts: An evolutionary game approach. Expert Systems with Applications, 39(3), 2965–2976.

114

Somen Dey

Batarlienė N. and Jarašūnienė A. (2016). Development of Advanced Technologies (AT) in green transport corridors. Procedia Engineering, 134, 481–489. Bhaskaran S., Polonsky M., Cary J., and Fernandez S. (2006). Environmentally sustainable food production and marketing: opportunity or hype?. British Food Journal, 108(8), 677–690. Bottani E., Vignali G., Mosna D., and Montanari R. (2019). Economic and environmental assessment of different reverse logistics scenarios for food waste recovery. Sustainable Production and Consumption, 20, 289–303. Brandenburg M. and Rebs T. (2015). Sustainable supply chain management: A modeling perspective. Annals of Operations Research, 229(1), 213–252. Carter C. and Rogers D. (2008). A framework of sustainable supply chain management: moving toward new theory. International Journal of Physical Distribution & Logistics Management, 38(5), 360–387. https://doi.org/10.1108/09600030810882816 Centobelli P., Cerchione R., and Esposito E. (2017). Developing the WH2 framework for environmental sustainability in logistics service providers: A taxonomy of green initiatives. Journal of Cleaner Production, 165, 1063–1077. Chin T.A., Tat H.H., and Sulaiman Z. (2015). Green supply chain management, environmental collaboration and sustainability performance. Procedia Cirp, 26, 695–699. Chen D., Ignatius J., Sun D., Zhan S., Zhou C., Marra M., and Demirbag M. (2018). Reverse logistics pricing strategy for a green supply chain: A view of customers’ environmental awareness. International Journal of Production Economics, 217, 197–210. Chhabra D., Garg S.K., and Singh R.K. (2017). Analyzing alternatives for green logistics in an Indian automotive organization: A case study. Journal of Cleaner Production, 167, 962–969. Cucchiella F., Koh L., Walker H., and Jones N. (2012). Sustainable supply chain management across the UK private sector. Supply Chain Management: An International Journal, 17(1), 15–28. De Oliveira U.R., Espindola L.S., da Silva I.R., da Silva I.N., and Rocha H.M. (2018). A systematic literature review on green supply chain management: Research implications and future perspectives. Journal of Cleaner Production, 187, 537–561. Dubey R., Gunasekaran A., and Papadopoulos T. (2017). Green supply chain management: Theoretical framework and further research directions. Benchmarking: An International Journal, 24(1), 184–218. Dev N.K., Shankar R., and Swami S. (2019). Diffusion of green products in Industry 4.0: Reverse logistics issues during design of inventory and production planning system. International Journal of Production Economics, 107519. Diffusion of green products in Industry 4.0: Reverse logistics issues during design of inventory and production planning system. International Journal of Production Economics, 223, 107519. https://doi.org/10.1016/j.ijpe.2019.107519. El-Berishy N.M. and Scholz-Reiter B. (2016). Development and implementation of a green logisticsoriented framework for batch process industries: two case studies. Logistics Research, 9(1), 9. El-Berishy N., Rügge I., and Scholz-Reiter B. (2013). The interrelation between sustainability and green logistics. IFAC Proceedings Volumes, 46(24), 527–531. Eltayeb T.K., Zailani S., and Ramayah T. (2011). Green supply chain initiatives among certified companies in Malaysia and environmental sustainability: Investigating the outcomes. Resources, Conservation and Recycling, 55(5), 495–506. Gautam P., Kishore A., Khanna A., and Jaggi C.K. (2019). Strategic defect management for a sustainable green supply chain. Journal of Cleaner Production, 233(1), 226–241. Genovese A., Acquaye A.A., Figueroa A., and Koh S.L. (2017). Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications. Omega, 66, 344–357.

6 Developing a framework to provide technological solutions

115

Golroudbary S., Zahraee S., Awan U., and Kraslawski A. (2019). Sustainable operations management in logistics using simulations and modelling: A framework for decision making in delivery management. Procedia Manufacturing, 30, 627–634. Govindan K., Soleimani H., and Kannan D. (2015a). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European journal of operational research, 240(3), 603–626. Govindan K., Khodaverdi R., and Vafadarnikjoo A. (2015b). Intuitionistic fuzzy based DEMATEL method for developing green practices and performances in a green supply chain. Expert Systems with Applications, 42(20), 7207–7220. Groening C., Sarkis J., and Zhu Q. (2018). Green marketing consumer-level theory review: A compendium of applied theories and further research directions. Journal of Cleaner Production, 172, 1848–1866. Haeri S.A.S. and Rezaei J. (2019). A grey-based green supplier selection model for uncertain environments. Journal of Cleaner Production, 221, 768–784. Handfield R.B., Walton S.V., Seegers L.K., and Melnyk S.A. (1997). ‘Green’value chain practices in the furniture industry. Journal of Operations Management, 15(4), 293–315. Industrial Investment and Employment Promotion Policy (IIEPP) of Uttar Pradesh (2017) Government of Uttar Pradesh Joshi Y., Sangroya D., Srivastava A.P., and Yadav M. (2019). Modelling the predictors of young consumers’ sustainable consumption intention. International Journal of Non-Profit and Voluntary Sector Marketing, 159, 235–243. Joshi Y. and Rahman Z. (2019). Consumers’ sustainable purchase behaviour: Modeling the impact of psychological factors. Ecological Economics, 159, 235–243. Kang M.J. and Hwang J. (2017). Interactions among inter-organizational measures for green supply chain management. Procedia Manufacturing, 8, 691–698. Kang K.H., Stein L., Heo C.Y., and Lee S. (2012). Consumers’ willingness to pay for green initiatives of the hotel industry. International Journal of Hospitality Management, 31(2), 564–572. Khan S.A.R., Zhang Y., Anees M., Golpîra H., Lahmar A., and Qianli D. (2018). Green supply chain management, economic growth and environment: A GMM based evidence. Journal of Cleaner Production, 185, 588–599. Khan, S. A. R. (2018). Introductory chapter: introduction of green supply chain management. In Green Practices and Strategies in Supply Chain Management. IntechOpen. DOI: 10.5772/ intechopen.81088. Khan S.A.R., Dong Q., Zhang Y., and Khan S.S. (2017). The impact of green supply chain on enterprise performance: In the perspective of China. Journal of Advanced Manufacturing Systems, 16(03), 263–273. Kumar A., Zavadskas E.K., Mangla S.K., Agrawal V., Sharma K., and Gupta D. (2019). When risks need attention: adoption of green supply chain initiatives in the pharmaceutical industry. International Journal of Production Research, 57(11), 3554–3576. Lai K.H. and Wong C.W. (2012). Green logistics management and performance: Some empirical evidence from Chinese manufacturing exporters. Omega, 40(3), 267–282. Lee S.M., Tae Kim S., and Choi D. (2012). Green supply chain management and organizational performance. Industrial Management & Data Systems, 112(8), 1148–1180. Liu X., Yang J., Qu S., Wang L., Shishime T., and Bao C. (2012). Sustainable production: practices and determinant factors of green supply chain management of Chinese companies. Business Strategy and the Environment, 21(1), 1–16. Luthra S., Mangla S.K., Xu L., and Diabat A. (2016a). Using AHP to evaluate barriers in adopting sustainable consumption and production initiatives in a supply chain. International Journal of Production Economics, 181, 342–349.

116

Somen Dey

Luthra S., Garg D., and Haleem A. (2016b). The impacts of critical success factors for implementing green supply chain management towards sustainability: an empirical investigation of Indian automobile industry. Journal of Cleaner Production, 121, 142–158. Maditati D.R., Munim Z.H., Schramm H.J., and Kummer S. (2018). A review of green supply chain management: From bibliometric analysis to a conceptual framework and future research directions. Resources, Conservation and Recycling, 139, 150–162. Mangla S., Madaan J., Sarma P.R.S., and Gupta M.P. (2014). Multi-objective decision modelling using interpretive structural modelling for green supply chains. International Journal of Logistics Systems and Management, 17(2), 125–142. Mangla S., Madaan J., and Chan F.T. (2013). Analysis of flexible decision strategies for sustainability-focused green product recovery system. International Journal of Production Research, 51(11), 3428–3442. Mesjasz-Lech A. (2016). Urban air pollution challenge for green logistics. Transportation Research Procedia, 16, 355–365. Mintcheva V. (2005). Indicators for environmental policy integration in the food supply chain (the case of the tomato ketchup supply chain and the integrated product policy). Journal of Cleaner Production, 13(7), 717–731. Mardani A., Kannan D., Hooker R.E., Ozkul S., Alrasheedi M., and Tirkolaee E.B. (2019). Evaluating of Green and Sustainable Supply Chain Management Using Application of Structural Equation Modelling: A systematic review of the state of the art literature and recommendations for future research. Journal of Cleaner Production, 249, 119383. Min H. and Galle W.P. (2001). Green purchasing practices of US firms. International Journal of Operations & Production Management, 21(9), 1222–1238. Mishra M.K., Choudhury D., and Rao K.V.G. (2019). Impact of SMEs green supply chain practice adoption on SMEs firm and environmental performance. Theoretical Economics Letters, 9(6), 1901–1919. Murphy P.R. and Poist R.F. (2003). Green perspectives and practices: a “comparative logistics” study. Supply Chain Management: An International Journal, 8(2), 122–131. Pagell M. and Wu Z. (2009). Building a more complete theory of sustainable supply chain management using case studies of 10 exemplars. Journal of Supply Chain Management, 45(2), 37–56. Prajapati H., Kant R., and Shankar R. (2019a). Prioritizing the solutions of reverse logistics implementation to mitigate its barriers: A hybrid modified SWARA and WASPAS approach. Journal of Cleaner Production, 240, 118219. Prajapati H., Kant R., and Shankar R. (2019b). Bequeath life to death: State-of-art review on reverse logistics. Journal of Cleaner Production, 211, 503–520. Prajogo D. and Olhager J. (2012). Supply chain integration and performance: The effects of longterm relationships, information technology and sharing, and logistics integration. International Journal of Production Economics, 135(1), 514–522. Rajabion L., Khorraminia M., Andjomshoaa A., Ghafouri-Azar M., and Molavi H. (2019). A new model for assessing the impact of the urban intelligent transportation system, farmers’ knowledge and business processes on the success of green supply chain management system for urban distribution of agricultural products. Journal of Retailing and Consumer Services, 50, 154–162. Sarkis J., Zhu Q., and Lai K.H. (2011). An organizational theoretic review of green supply chain management literature. International Journal of Production Economics, 130(1), 1–15. Sallnäs U. and Huge-Brodin M. (2018). De-greening of logistics?–Why environmental practices flourish and fade in provider-shipper relationships and networks. Industrial Marketing Management, 74, 276–287. Seroka-Stolka O. and Ociepa-Kubicka A. (2019). Green logistics and circular economy. Transportation Research Procedia, 39, 471–479.

6 Developing a framework to provide technological solutions

117

Seroka-Stolka O. (2016). Green initiatives in environmental management of logistics companies. Transportation Research Procedia, 16, 483–489. https://doi.org/10.1016/j.trpro.2016.11.045 Sharma V.K., Chandna P., and Bhardwaj A. (2017). Green supply chain management related performance indicators in agro industry: A review. Journal of Cleaner Production, 141, 1194–1208. Soda S., Sachdeva A., and Garg R.K. (2016). Implementation of green supply chain management in India: Bottlenecks and remedies. The Electricity Journal, 29(4), 43–50. Srivastava S.K. (2007). Green supply‐chain management: a state‐of‐the‐art literature review. International Journal Of Management Reviews, 9(1), 53–80. Subramanian N., Abdulrahman M.D., and Zhou X. (2014). Integration of logistics and cloud computing service providers: Cost and green benefits in the Chinese context. Transportation Research Part E: Logistics and Transportation Review, 70, 86–98. The Uttar Pradesh Food Processing Industry Policy (FPIP). (2017). Government of Uttar Pradesh The Uttar Pradesh Warehousing and Logistics Policy (UPWLP) (2018) Government of Uttar Pradesh Transparency International Report (2016) www.transparency.org Tseng M.-L., Islam M.S., Karia N., Fauzi F.A., and Afrin S. (2019). A literature review on green supply chain management: Trends and future challenges. Resources, Conservation and Recycling, 141, 145–162. Vasiliauskas A.V., Zinkevičiūtė V., and Šimonytė E. (2013). Implementation of the concept of green logistics reffering to it applications for road freight transport enterprises. Business: Theory and Practice, 14(1), 43–50. Wang J., Gao H., Wei G., and Wei Y. (2019). Methods for multiple-attribute group decision making with q-rung interval-valued orthopair fuzzy information and their applications to the selection of green suppliers. Symmetry, 11(1), 56. Wang Z., Wang Q., Zhang S., and Zhao X. (2018). Effects of customer and cost drivers on green supply chain management practices and environmental performance. Journal of Cleaner Production, 189, 673–682. Wątróbski J., Jankowski J., Ziemba P., Karczmarczyk A., and Zioło M. (2019). Generalised framework for multi-criteria method selection. Omega, 86, 107–124. Wątróbski J. (2016). Outline of multicriteria decision-making in green logistics. Transportation Research Procedia, 16, 537–552. Zhang Y., Thompson R.G., Bao X., and Jiang Y. (2014). Analyzing the promoting factors for adopting green logistics practices: a case study of road freight industry in Nanjing, China. ProcediaSocial and Behavioral Sciences, 125, 432–444. Zhang G. and Zhao Z. (2012). Green packaging management of logistics enterprises. Physics Procedia, 24, 900–905. Zhu Q., Sarkis J., and Lai K.H. (2008). Confirmation of a measurement model for green supply chain management practices implementation. International Journal of Production Economics, 111(2), 261–273. Zhu Q. and Sarkis J. (2004). Relationships between operational practices and performance among early adopters of green supply chain management practices in Chinese manufacturing enterprises. Journal of Operations Management, 22(3), 265–289. Zaid A.A., Jaaron A.A., and Bon A.T. (2018). The impact of green human resource management and green supply chain management practices on sustainable performance: An empirical study. Journal of Cleaner Production, 204, 965–979.

Yatish Joshi, Gaurav Kabra

7 Demand side of the sustainable supply chain (consumers sustainable practices): a conceptual review Abstract: The widespread development efforts have been associated with negative effect on the nature and society. The deteriorating environmental condition has emphasized the need of promoting efforts for sustainability; and in the last two decades, increasing consideration has been given to the concept of sustainable development. Sustainable consumption, which emphasizes on motivating the responsible form of consumer behavior, represents the demand side of the supply chain. Sustainable consumption is about responsible consumption practices that also focuses on protecting the nature and using natural resources sensibly, while protecting the lives of future generations. However, industries, government, and most of the consumers struggle to comprehend sustainable consumption. With the realization of the consequences, the number of persons willing to adopt sustainable consumption has been improved in the last few years, but they are failing to convert it into actual practices. This area has been discussed, and literature has given few definitions of the term sustainable consumption with a wide range of associated terms like ethical consumption, fair consumption, and green consumption. This chapter aims at comprehending the notion of sustainable consumption, and how it has been conceptualized and theorized over a period of time. The finding of this chapter will be useful for policy makers in promoting sustainable consumption practice. Keywords: sustainable supply chain, sustainable consumption, ethical consumption, green consumption, attitude- behavior gap

7.1 Introduction Nowadays, a large part of the population in today’s life is living in a materialist world and have adopted a hectic lifestyle. In these conditions, individuals frequently do not ponder the natural or social outcomes of their activities and purchasing conduct. Sustainable consumption represents the demand side of the supply chain, and

Yatish Joshi, School of Management Studies, Motilal Nehru National Institute of Technology, Allahabad, Uttar Pradesh, India Gaurav Kabra, Operations and Supply Chain Management, National Institute of Industrial Engineering, Mumbai, India https://doi.org/10.1515/9783110628593-007

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consumer demands drive the other ends of production and distribution. Researchers are likewise worried about the results of unmonitored sustainable consumption, which can prompt “ecological, social and financial degeneration” (Hume, 2010). So as to deal with the issue, endeavours are progressively made to create responsible consumption practices and typify them in every day customers’ conduct. This research likewise contributes fundamentally by inspecting different consumption practices, inspirations driving them, and their results.

7.1.1 Sustainable development The idea of sustainable development is described as the advancement that considers the concerns of the present-day without trading the capability of coming ages to tackle their very own problems. Sustainable development works for accomplishing “monetary (benefit), social (individuals) and ecological (planet) objectives” (Hume, 2010; Vermeir and Verbeke, 2008). The financial part identifies with ensuring reasonable costs for the organizations as well as the shoppers. The ecological or biological viewpoint includes caution for the indigenous habitat and safeguarding biological reserves. At last, the social component alludes to focus on developments in the concern and desires of the general public (Vermeir and Verbeke, 2008). Accordingly, sustainability views from natural, social, and financial angles.

7.1.2 Demand side of the sustainable supply chain (consumers sustainable practices) While supply chain deals with the demand side of the sustainable supply chain, sustainable consumption is portrayed as “the effects of gathering and purchasing material possessions to increase happiness and social position” (Yadav et al., 2019). Sustainable consumption originated with a basic thought that “considers the customer’s social responsibility, aside individual needs and wants” (Vermeir and Verbeke, 2008). Birtwistle and Moore (2007) characterized it as “Sustainable consumption is consumption that supports the ability of current and future generations to meet their material and other needs, without causing irreversible damage to the environment or loss of function in natural systems.” Belz and Bilharz (2005) recognizes sustainable consumption in macro as well as micro perspective. In micro sense, it alludes to consumption designs that can be summed up inside and among various ages. In macro perspective, SC alludes to consumption exercises that support in diminish the environmental and societal issues related with manufacturing and consumption – that may not remain common among ages. It enhances business with respect to moderating natural and social pressure from consumption.

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7.1.2.1 Environment-friendly consumption Environment-friendly consumption is concerned with purchasers displaying ecologically responsible consumption, for example, having contemplations on the natural outcomes of the buy, use, and recycle behavior. (Yadav and Pathak, 2016). Green consumption is likewise portrayed as a type of societal purchasing conduct, described as a difficult moral concern, and the customer, being a cognizant customer “takes into account the public consequences of his or her private consumption and attempts to use his or her purchasing power to bring about social change” (Moisander, 2007). According to a few authors, the “green customers” was extended to “ethical purchasers” so as to represent people’s ethical concerns (Newholm and Shaw, 2007).

7.1.2.2 Ethical consumption Ethical consumption, is described as “the purchase of a product that concerns a certain ethical issue which may benefit the environment, society, or the legal issues” (De Pelsmacker et al., 2005). The moral customer, comparable to the green purchaser, is considered responsible toward the general public and communicating these sentiments through their buying preferences (Vermeir and Verbeke, 2008). In this manner, it can be accepted that moral consumers show some types of sustainable consumption practices that mull over the ecological as well as social outcomes of consumption.

7.1.2.3 Evolution of the concept of sustainable consumption Sustainable consumption has gained a significant prominence all through the previous ages. It has been examined and explored in cultural, sociopolitical, and managerial point of view. The evolution and development of the concept has been provided in the table 7.1.

7.2 Important theories and framework Prior research has investigated the demand side of the sustainable supply chain by examining buyer conduct by keeping similar variables that influence purchasers’ conduct in different settings. These viewpoints go from models of rational decision to characteristic based model. Here, we discuss models/theoretical frameworks used for studying the sustainable consumer behavior.

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Table 7.1: Evolution of the concept of sustainable consumption. Year and source

Explanation/statements

 “An Essay on the Principle of Population” By Thomas Malthus

It concluded with the remark “The power of population is indefinitely greater than the power of the earth to Produce subsistence for man.”

 UN Conference on the Human Environment:

It concluded with the remark “In our time, man’s capability to transform his surroundings, if used wisely, can bring to all peoples the benefit of development and the opportunity to enhance the quality of life. Wrongly or heedlessly applied, the same power can do incalculable harm to human beings and human environment.”

 Report “Limits to Growth” By Club of Rome.

It recommended that to achieve a sustainable civilization, the people should “moderate not only their demand for children, but also their material lifestyles. To achieve this change would mean that the globe’s people establish their status, derive satisfaction, and challenge themselves with goals other than the ever-increasing production and ever-accumulating material wealth.”

 United Nations WCED

“Perceived needs are socially and culturally determined, and sustainable development requires the promotion of Values that encourage consumption standards that are within the bounds of the ecologically possible and to which all can reasonably aspire.”

 United Nations Conference on Environment and Development

“The major cause of the continued deterioration of the global environment is the unsustainable pattern of consumption and production, particularly in industrialized countries, which is a matter of grave concern, aggravating poverty and imbalances.”

Rio Earth Summit in 

The word was presented as a worldwide policy concern with an objective to change consumption pattern.

 United Nations Commission on Sustainable Development (UNCSD)

Need for sustainable consumption has been established.

Oslo Symposium in .

There is a need to focus on the: “The use of goods and services that respond to basic needs and bring a better quality of life, while minimizing the use of natural resources, toxic materials and emissions of waste and pollutants over the lifecycle, so as not to jeopardize the needs of future generations” (Ofstad, ).

 United Nations Economic and Social Council (UNECOSOC)

SC was assimilated in the UN Guidelines on Consumer Protection.

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Table 7.1 (continued ) Year and source

Explanation/statements

 United Nations Environment Programme (UNEP)

UNEP SC program originates and dialog of SC in the Human Development Report of the UN Development Program (UNDP)

 UNEP

It describes that “SC engages, economically and socially, from the bottom up, using the actions and perspective of consumers and citizens as its starting point, rather than the big-picture assessments of the global environment of sustainable development discourse.”

 World Summit on Sustainable Development (WSSD) in Johannesburg

The appeal has been made to the countries across the world to “Encourage and promote the development of a framework in support of regional and national initiatives to accelerate the shift towards Sustainable consumption and production to promote social and economic development within the carrying capacity of ecosystems.” A ten-year program has been designed to execute sustainable consumption and production practices.

 Launch of the Marrakech Process “A coalition of willing countries has can work to promote on Sustainable Consumption and sustainable consumption and production, especially Production (in Marrakech, Morocco) through policy guidelines and in emerging economies.”  Iris Vermeira and Wim Verbekeb

Consumption need to “takes the consumer’s social responsibility into account in addition to individual needs and wants”

 G. Birtwistle and C.M. Moore

Consumption need to “supports the ability of current and future generations to meet their material and other needs, without causing irreversible damage to the environment or loss of function in natural systems.”

 United Nations Conference (Rio ).

Marrakech Process -year framework (YFP) was formally adopted on managing the various ends of sustainable supply chain (consumption and production).

7.2.1 Means-end theory “Means-end theory” elucidates customers’ cognitive process of product categorization (Gutman, 1982). It says that customer perceived value is formed by appraising presentation of items characteristics in relation to buyer’s expectation (Petrick and Backman, 2002). A review of prior research and well-known philosophies in the broad field of marketing, sustainability, and related areas highlights the importance of perceived value. Anderson and Narus (2009) and Sirdeshmukh et al. (2002) stated value as the foundation of business association. Comprehending consumer

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apparent value has been one of the key areas of marketing research (ArslanagicKalajdzic and Zabkar, 2015). Value research draws mainly from the theory of market choice behavior and means-end theory (Chi and Kilduff, 2011). The means-end theory has been used to comprehend the perceived value in demand side of the sustainable supply chain.

7.2.2 The theory of market choice behavior The theorey of market choice behavior (TMCB) was offered by Sheth et al. (1991), which emphasizes exclusively on consumption value, for example, functional, social, emotional, conditional, and epistemic value. It states that “market choice is a function of multi-dimensional consumption values which affect consumer consumption behavior differently in various circumstances, and these values are independent of one another” (Chi and Kilduff, 2011). It provides a strong theoretic base for the growth of the several perceived value measurement scales in the B2B context (Fiol et al., 2011; Sweeney and Soutar, 2001).

7.2.3 The theory of planned behavior The theorey of planned behavior (TPB) depends on the supposition that individuals ordinarily behave in a reasonable, objective way and intentionally think about the results of alternative practices also, picking the one that is most favorable. TPB posits that: “a person’s intention to perform (or not to perform) a behaviour is the most important immediate determinant of that action.” (Ajzen, 2005; Ajzen and Fishbein, 2002). Intention is an outcome of three elements − attitude, subjective norm, and perceived behavioural control (PBC). TPB tries to consider customer choice-creation procedure and purchasing conduct concerning green consumption (Gupta and Ogden, 2009; Magnusson et al., 2001; Shaw et al., 2000), ecofriendly transport (Lane and Potter, 2007), and recycle behavior (Davies et al., 2002) though TPB does not think about moral issues, with regard to the studied literature. TPB has been explored, and a few alterations have been anticipated so as to make it increasingly appropriate to shopper practices not altogether coordinated by rational, comprehension, and dispositions. Vermeir and Verbeke (2006) built up the structure for sustainable consumption conduct that it consolidates the predictors of goal from the TPB, The framework suggests three fundamental elements of intention: individual values, needs, and personal motives, which influence the degree of shoppers’ association in the buy or decision choice; data and information, deciding customers’ degree of conviction in the product traits; and social control, applied here by the items’ accessibility and perceived buyer viability. TPB has been extensively utilized in various studies to

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understand the sustainable consumption behavior (Chen and Tung, 2014; Liobikienė et al., 2016; Yadav and Pathak, 2017).

7.2.4 Value–beliefs–norms Value–beliefs–norms (VBN) theory is a known theory of environmentally significant behavior and incorporates Schwartz’s (1973) the moral norm activation framework, the theory of personal values, and the new environmental paradigm (NEP). VBN’s focal reason is that pro-social convictions and individual moral standards are vital indicators of pro-ecological conduct (Stern, 1999; Stern et al., 1999), which focuses on importance of holding deep altruistic and biospheric values, are bound to acknowledge the convictions of the NEP perspective. The NEP comprises values that offer appreciation to ordinary limit and the significance of protecting the equilibrium of environment (Dunlap and van Liere, 1978). As indicated by VBN, the more grounded purchasers’ self-absorbed worth direction, the more uncertain they are to acknowledge the NEP. Prior studies have demonstrated that acknowledgment of the NEP relates emphatically to the consciousness of the (natural) results of one’s activities, which thus drives people to get mindful of their duty to decrease those outcomes (Jackson, 2005). These convictions incorporate convictions about the results of various practices, the two ramifications for nature and for oneself. So also, customers’ qualities may prompt dismissal of the NEP and, in this way, adds to convictions that are counter to feasible utilization, for example, when buyers see economical items as mediocre compared to conventional ones. Research has indicated a potential disgrace around ecologically benevolent or reused/restored items being seen as less viable contrasted with customary item options (Luchs et al., 2010). Further, as per the VBN, buyers create individual standards dependent on their convictions about who is answerable for outcomes of earth noteworthy practices. This standard could involve an individual feeling of commitment to make expert natural move (Stern, 2000) or a conviction that others rather need to adjust their practices. Standards can both encourage or hinder sustainable consumption practices.

7.2.5 Motivation–abilities–opportunity Motivation–ability–opportunity (MAO) framework expands on the direction of VBN to incorporate the job of propensities and errand information (ability) and environments (opportunity) to recognize limitations and empowering influence of sustainable practices (Olander and Thogersen’s, 1995). Ability includes both a propensity and information component. The opportunity construct includes structural restraints. When sustainable choices are accessible in nature, they can be costly or hard to find

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contrasted with conventional items, in this manner, diminishing economical utilization (Tanner and Kast, 2003). However, one of the prior studies has found that lessening the time and exertion requested to devour reasonably and changing natural conditions might be a higher priority than pricing (Thogersen, 2005). Other outside factor, for example, activities (or inaction) by the administration, organizations, and the way of life can restrict a customer’s opportunity to pick sustainable alternatives in certain product categories (e.g., accessibility of quality electric vehicles etc.). Concerning other social elements, the absence of strong data about the ecological effect of items via marking can compel sustainable utilization practices (Borin et al., 2011). Message validity are additionally vital issues since buyers experience problems, observing what claims are real (Manget et al., 2009).

7.2.6 Theory of reciprocal determinism Phipps et al. (2013) introduced the theory of reciprocal determinism and suggested that “past behaviour is not only an outcome of its antecedents, but also a determining variable that can affect future sustainable behaviour.” They recommended that other than individual and social elements, past sustainable conduct can impact shoppers’ sustainable conduct. Seeing previous sustainable activities as a determinant of future sustainable practices would deliver a better insight into the consumption behavior, which may, in turn, aid in inspiring and strengthening sustainable consumption behavior among consumers. Such an insight will also throw light on how earlier conduct along with other social, cultural, and personal variables, impacts customers’ future sustainable consumption practices. Some of the previous studies have successfully applied the concept of reciprocal determinism and established various forms of past conduct as a predictors of consumer present sustainable conduct (Koklic et al., 2019; Lee, 2014).

7.3 Factor affecting demand side of the sustainable supply chain (sustainable consumption practices) Demand part of the sustainable supply chain that represents the consumption of sustainable goods has been addressed by many researchers along various dimensions; the researches focused on demand of sustainable product and also the gap between customers’ attitude and behavior toward the same.

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While exploring the ethical consumption, it has been found that ecological issues affect the ethical consumption (Wheale and Hinton, 2007). Ecological issues and sense of accountability were observed to have a favorable effect on green awareness, buying intention, and real purchasing (Makatouni, 2002; Wang et al., 2014). Consumers’ social concern was observed to positively affect the buying of fair trade goods (De Ferran et al., 2007; Ozcaglar-Toulouse et al., 2006). The lack of access to ethical clothing (outlets range, fashionable clothing), prices, and dearth of information are the major hurdles in buying ethical fashion clothing (Shaw et al., 2006). Knowledge is a crucial variable, and it has been found that information of ecological matters favorably influenced consumers’ green purchase conduct (e.g., Eze and Ndubisi 2013). Social responsibility criteria were observed to have a favorable effect on consumers’ fair trade buying behavior (Aertsens et al., 2011; Bang et al., 2000; Shen et al., 2012). Lack of information was observed to negatively influence green buying conduct (Ozcaglar‐Toulouse et al., 2006; Padel and Foster, 2005). While exploring the consumer behavior toward organic food, it has been found that customers generally show favorable attitudes, but low level of actual buying. Moral attitude, health consciousness, perceived behavioral control and attitude are the main motives of purchase (Yadav and Pathak, 2016). Moral obligation, self-identity, attitude toward fair trade product and trust are drivers of consumer demand for fair trade products (Beldad and Hegner, 2018; Yadav and Pathak, 2016). Also shoppers are eager to give extra payment for fair trade labeled coffee (Loureiro and Lotade, 2005). Personal values (such as universalism values, benevolence values) were found to affect consumers fair trade consumptions (Doran, 2009) while exploring the consumer green purchasing behavior Tanner and Kast (2003) that identified the individual attitudes and beliefs. Knowledge, perceived time barrier, and store characteristics are the significant factors affecting green food purchase. Further, some of the studies found that exploring the social influence and peer pressure affect green buyer as green buyers that affiliate themselves with certain groups (Tarkiainen and Sundqvist, 2005) Some of the studies reported that attitude is the most vital determinant of green buying (Young et al., 2010; Zhao et al., 2014). Retailer and peers can influence consumer environmentally responsible behavior (Yelena et al., 2013). Vermeir and Verbeke (2008) explore sustainable food consumption and found that sustainable products are considered hard to obtain. High involvement, social norms, individual values, perceived consumer effectiveness, and perceived social influences have impact on buying decision. Leary et al. (2014) further identified that perceived marketplace influence affects customers’ sustainable purchasing. Further exploring, it has been found that customers are also eager to consume less once they realized negative consequences. However, materialism intensifies the degree to which a wealthy customer or society limit consumption. It has been found that ecological information, ecological values and sensitivity, response efficiency, contextual factors, and behavioral intention affect sustainable consumption behavior.

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7.4 Implications The present study reviews the concept, evolution, and important theories of sustainable consumption and identifies the different elements affecting consumers’ sustainable consumption practices. It additionally offers reasons behind the consumer sustainable or unsustainable consumption practices on the basis of recognized variables. Future researchers are encouraged to explore these factors. The present study also informs policy makers and marketing managers about the various factors of sustainable consumption practices. Such understanding would help managers to encourage sustainable consumption practices.

7.5 Conclusion and future research direction Over time and with the growing emphasis on sustainable consumption, several studies addressed the concept of sustainable consumption practices and observed inconsistency between customers’ favorable attitudes toward ethical concerns and their real engagements. However, no complete and united clarification of the issue is provided. Not only there is a disagreement about the definition of sustainable consumption, but also there has been some debate about the term itself. Sustainable consumption still remains a complex and understood concept that includes a range of ideas and practices. Future research might emphasis on the determination of additional impelling variables and explanations for the inconsistency in sustainable consumption conduct. The research on sustainable consumption is typically founded on self- stated customer attitudes; there is also a need of dealing with actual observation of behavior. There is a need to develop a sustainable consumption framework to explain the demand side (i.e., sustainable consumer behavior). Future research may also investigate the effects of sustainable marketing strategies toward promoting sustainable consumption.

References Aertsens J., Mondelaers K., Verbeke W., Buysse J., and Van Huylenbroeck G. (2011). The influence of subjective and objective knowledge on attitude, motivations and consumption of organic food. British Food Journal, 113(11), 1353–1378. Ajzen I. (2005). Attitudes, personality, and behavior (2nd ed.). Milton-Keynes, England: Open University Press / McGraw-Hill. Ajzen I. and Fishbein M. (2002). Understanding attitudes and predicting social behaviour. New Jersey: Prentice Hall. Anderson J.C., Narus J.A., and Narayandas D. (2009). Business market management: Understanding, creating, and delivering value. Pearson Prentice Hall.

7 Demand side of the sustainable supply chain

129

Arslanagic-Kalajdzic M. and Zabkar V. (2015). The external effect of marketing accountability in business relationships: Exploring the role of customer perceived value. Industrial Marketing Management, 46, 83–97. Bang H.K., Ellinger A.E., Hadjimarcou J., and Traichal P.A. (2000). Consumer concern, knowledge, belief, and attitude toward renewable energy: An application of the reasoned action theory. Psychology & Marketing, 17(6), 449–468. Beldad A. and Hegner S. (2018). Determinants of fair trade product purchase intention of Dutch consumers according to the extended theory of planned behaviour. Journal of Consumer Policy, 41(3), 191–210. Belz F.M. and Bilharz M. (2005) Nachhaltiger Konsum: Zentrale Herausforderungen für moderne Verbraucherpolitik. Consumer Science Diskussionsbeitrag 1. [WWW document]. URL http://www.alexandria.unisg.ch/EXPORT/DL/41721.pdf Chen M.F. and Tung P.J. (2014). Developing an extended theory of planned behavior model to predict consumers’ intention to visit green hotels. International Journal Of Hospitality Management, 36, 221–230. Chi T. and Kilduff P.P. (2011). Understanding consumer perceived value of casual sportswear: An empirical study. Journal of Retailing and Consumer Services, 18(5), 422–429. Giampietri E., Verneau F., Del Giudice T., Carfora V., and Finco A. (2018). A Theory of Planned behaviour perspective for investigating the role of trust in consumer purchasing decision related to short food supply chains. Food Quality And Preference, 64, 160–166. De Ferran, Florence, and Klaus G. Grunert. “French fair trade coffee buyers’ purchasing motives: An exploratory study using means-end chains analysis.” Food Quality and Preference 18.2 (2007): 218–229. Birtwistle G. and Moore C.M. (2007). Fashion clothing – where does it all end up?. International Journal of Retail and Distribution Management, 35(3), 210–216. Borin N., Cerf D.C., and Krishnan R. (2011). Consumer effects of environmental impact in product labeling. Journal of Consumer Marketing, 28(1), 76–86. Davies J., Foxall G.R., and Pallister J. (2002). Beyond the intention–behaviour mythology: An integrated model of recycling. Marketing Theory, 2(1), 29–113. De Pelsmacker P., Driesen L., and Rayp G. (2005). Do consumers care about ethics? Willingness to pay for fair-trade coffee. Journal of Consumer Affairs, 39(2), 363–385. Doran C.J. (2009). The role of personal values in fair trade consumption. Journal of Business Ethics, 84(4), 549–563. Dunlap R. and van Liere K. (1978). The new environmental paradigm — A proposed measuring instrument and preliminary results. The Journal of Environmental Education, 9(4), 10–19. Eze U.C. and Ndubisi N.O. (2013). Green buyer Behavior: Evidence from Asia consumers. Journal of Asian and African Studies, 48(4), 413–426. Fiol L.J.C., Moliner Tena M.A., and Sánchez García J. (2011). Multidimensional perspective of perceived value in industrial clusters. Journal of Business & Industrial Marketing, 26(2), 132–145. Gupta S. and Ogden D.T. (2009). To buy or not to buy? A social dilemma perspective on green buying. Journal of Consumer Marketing, 26(6), 376–391. Gutman, J. (1982). “A Means-End Chain Model Based on Consumer Categorization Processes.” Journal of Marketing, 46: 60–72. Hume M. (2010). Compassion without action: Examining the young consumer’s consumption and attitude to sustainable consumption. Journal of World Business, 45(4), 385–394.

130

Yatish Joshi, Gaurav Kabra

Jackson T. (2005). Motivating sustainable consumption: A review of evidence on Consumer behavior and behavioural change. A report to the Sustainable Development Research Network. Surrey (UK): University of Surrey. Koklic M.K., Golob U., Podnar K., and Zabkar V. (2019). The interplay of past consumption, attitudes and personal norms in organic food buying. Appetite, 137, 27–34. Koos S. (2011). Varieties of environmental labelling, market structures and sustainable consumption across Europe: A comparative analysis of organizational and market supply determinants of environmental labelled goods. Journal of Consumer Policy, 34(1), 127–151. Lane B. and Potter S. (2007). The adoption of cleaner vehicles in the UK: Exploring the consumer attitude-action gap. Journal of Cleaner Production, 15, 1085–1092. Leary, R. B., Vann, R. J., Mittelstaedt, J. D., Murphy, P. E., & Sherry Jr, J. F. (2014). Changing the marketplace one behavior at a time: Perceived marketplace influence and sustainable consumption. Journal of Business Research, 67(9), 1953–1958. Lee K. (2014). Predictors of sustainable consumption among young educated consumers in Hong Kong. Journal of International Consumer Marketing, 26(3), 217–238. Liobikienė G., Mandravickaitė J., and Bernatonienė J. (2016). Theory of planned behavior approach to understand the green purchasing behavior in the EU: A cross-cultural study. Ecological Economics, 125, 38–46. Loureiro M.L. and Lotade J. (2005). Do fair trade and eco-labels in coffee wake up the consumer conscience? Ecological Economics. 53, 129–138. Luchs M.G., Naylor R.W., Irwin J.R., and Raghunathan R. (2010). The sustainability: Potential negative effects of ethicality on product preference. Journal of Marketing, 74(5), 18–31. Manget J., Roche C., and Munnich F. (2009). Capturing the green advantage for consumer companies. http://www.bcg.com/expertise_impact/publications/PublicationDetails.aspx?id= tcm:12-15409 accessed Feb 2, 2014. Magnusson M.K., Arvola A., Hursti U.K., Aberg L., and Sjoden P. (2001). Attitudes towards organic foods among Swedish consumers. British Food Journal, 103(3), 209–226. Makatouni A. (2002). What motivates consumers to buy organic food in the UK? Results from a qualitative study. British Food Journal, 104(3/4/5), 345–352. Moisander J. (2007). Motivational complexity of green consumerism. International Journal of Consumer Studies, 31, 404–409. Newholm T. and Shaw D. (2007). Studying the ethical consumer: A review of research. Journal of Consumer Behaviour, 6, 253–270. Ofstad, S. (publisher) “Symposium: Sustainable Consumption”, Oslo. Ministry of Environment (1994) Olander F. and Thogersen J. (1995). Understanding consumer behaviour as prerequisite for environmental protection. Journal of Consumer Policy, 18(4), 345–385. Ozcaglar‐Toulouse N., Shiu E., and Shaw D. (2006). In search of fair trade: Ethical consumer decision making in France. International Journal Of Consumer Studies, 30(5), 502–514. Padel S. and Foster C. (2005). Exploring the gap between attitudes and behaviour: Understanding why consumers buy or do not buy organic food. British Food Journal, 107(8), 606–625. Petrick J.F. and Backman S.J. (2002). An examination of the construct of perceived value for the prediction of golf travelers’ intentions to revisit. Journal of Travel Research, 41(1), 38–45. Phipps M., Ozanne L.K., Luchs M.G., Subrahmanyan S., Kapitan S., Catlin J.R., . . . Weaver T. (2013). Understanding the inherent complexity of sustainable consumption: A social cognitive framework. Journal of Business Research, 66(8), 1227–1234.

7 Demand side of the sustainable supply chain

131

Press M. and Arnould E.J. (2009). Constraints on sustainable energy consumption: Market system and public policy challenges and opportunities. Journal of Public Policy & Marketing, 28(1), 102–113. Schwartz S. (1973). Normative explanations of helping behavior: A critique, proposal, empirical test. Journal of Environmental Psychology, 9(4), 349–364. Shaw D. and Clarke I. (1999). Belief formation in ethical consumer groups: An Exploratory study. Marketing Intelligence and Planning, 17(2), 109–119. Shaw D., Hogg G., Wilson E., Shui E., and Hassan L. (2006). Fashion victim: The impact of fair trade concerns on clothing choice. Journal of Strategic Marketing, 14, 427–440. Shaw D., Shiu E., and Clarke I. (2000). The contribution of ethical obligation and self- identity to the theory of planned behaviour: An exploration of ethical consumers. Journal of Marketing Management, 16(8), 879–894. Shen B., Wang Y., Lo C.K., and Shum M. (2012). The impact of ethical fashion on consumer purchase behavior. Journal of Fashion Marketing and Management, 16(2), 234–245. Sheth J., Newman B., and Gross B. (1991). Consumption values and market choices: theory and applications. Cincinnati: South-Western Publishing Company. Sirdeshmukh D., Singh J., and Sabol B. (2002). Consumer trust, value, and loyalty in relational exchanges. Journal of Marketing, 66(1), 15–37. Stern P.C. (1999). Information, incentives, and proenvironmental consumer behavior. Journal of Consumer Policy, 22(4), 461–478. Stern P.C. (2000). New environmental theories: Toward a coherent theory of environmentally significant behavior. Journal of Social Issues, 56(3), 407–424. Stern P.C., Dietz T., Abel T., Guagnano G.A., and Kalof L. (1999). A Value–Belief–Norm theory of support for social movements: The case of environmental concern. Human Ecology Review, 50(2), 81–97. Sweeney J.C. and Soutar G.N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203–220. Tanner C. and Kast S.W. (2003). Promoting sustainable consumption: Determinants of green purchases by Swiss consumers. Psychology and Marketing, 20(10), 883–902. Tarkiainen A. and Sundqvist S. (2005). Subjective norms, attitudes and intentions of Finnish consumers in buying organic food. British Food Journal, 107(11), 808–822. Thogersen J. (2005). How may consumer policy empower consumers for sustainable Lifestyles?. Journal of Consumer Policy, 28(2), 143–178. UNEP. (2001). Consumption opportunities - strategies for change. A report for decision makers. Geneva: UNEP. Vermeir I. and Verbeke W. (2008). Sustainable food consumption among young adults in Belgium: Theory of planned behaviour and the role of confidence and values. Ecological Economics, 64, 542–553. Vermeir, I., & Verbeke, W. (2006). Sustainable food consumption: Exploring the consumer “attitude–behavioral intention” gap. Journal of Agricultural and Environmental ethics, 19(2), 169–194. Wang P., Liu Q., and Qi Y. (2014). Factors influencing sustainable consumption behaviors: a survey of the rural residents in China. Journal of Cleaner Production, 63, 152–165. Wheale P. and Hinton D. (2007). Ethical consumers in search of markets. Business Strategy and the Environment, 16, 302–315. Yadav R., Singh P.K., Srivastava A., and Ahmad A. (2019). Motivators and barriers to sustainable food consumption: Qualitative inquiry about organic food consumers in a developing nation. International Journal of Nonprofit and Voluntary Sector Marketing, 24(4), e1650.

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Yadav R. and Pathak G.S. (2017). Determinants of consumers’ green purchase behavior in a developing nation: Applying and extending the theory of planned behavior. Ecological Economics, 134, 114–122. Yadav R. and Pathak G.S. (2016). Intention to purchase organic food among young consumers: Evidences from a developing nation. Appetite, 96, 122–128. Yelena, et al. (2013). Environmentally conscious consumption: The role of retailers and peers as external influences. Journal of Retailing and Consumer Services, 20(3), 251–372. Young W., Hwang K., McDonald S., and Oates C.J. (2010). Sustainable consumption: Green consumer behaviour when purchasing products. Sustainable Development, 18, 20–31. Zhao H.H., Gao Q., Wu Y.P., Wang Y., and Zhu X.D. (2014). What affects green consumer behavior in China? A case study from Qingdao. Journal of Cleaner Production, 63, 143–151.

İpek Kazançoğlu, Can Karaosmanoğlu

8 Can sustainability marketing be implemented as a differentiation strategy? A case study on marinas in the Aegean Region of Turkey Abstract: Over the last few decades, there has been growing emphasis on environmental protection, as well as implementation of principles regarding sustainable developments in tourism. Environmental sustainability is far more vital for marina management as marinas are, by definition, located next to a body of water. In literature review, there is limited research related to sustainability marketing activities in marinas. This study aims to understand sustainability marketing activities in marinas and to determine the role of environmental policies in achieving sustainable competitive advantage. The research method consists of semistructured indepth interviews with selected marina managers from the Aegean region of Turkey, which is home to the majority of marinas in the country. Each marina is unique by nature; therefore, every marina has to apply various strategies to achieve sustainable competitive advantage. The findings reveal the degree of effectiveness of sustainability marketing activities based on marina certifications and classifications for different types of marinas. Consequently, as much as marina managements appreciate the importance of environmental sustainability and ways of marketing it, complementary strategies are also needed to gain competitive advantage in the short run. However, in the long run, sustainability marketing is essential for marinas to keep their competitive edge. Keywords: sustainability marketing, sustainable competitive advantage, marina management, marinas, yachting

8.1 Introduction While most traditional resources prove to be finite, the world population is ever growing, with no end in the foreseeable future. Therefore, sustainability is currently one of the key themes in all areas of business. Although it is essential to various types of business, few are as reliant on sustainability as marina management. In terms of the three levels of a product in marketing literature, sustainability affects İpek Kazançoğlu, Faculty of Economics and Administrative Sciences, Department of Business Administration, Ege University, Izmir, Turkey Can Karaosmanoğlu, Department of Transportation Services, Marina and Yacht Management Program, Yaşar University, Vocational School, Izmir, Turkey https://doi.org/10.1515/9783110628593-008

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both the core product, as well as the actual product. In order for a marina to be regarded as sustainable, it should maintain the balance between “economic development, social equity, and environmental protection” in the long run (Lam and Yap, 2019). The development of a marina in a location with a sustainable coastal zone development plan is a rate that contributes to natural biodiversity, ecosystem functioning, and the ability to provide ecosystem services, both for current and future generations. This plan incorporating all interrelations between economic, environmental, and social values constituting and affecting the ecosystem is the complex way in which a marina can prove to be truly sustainable (De Boer, 2016). Marinas are located on coastal regions, which – by their very nature – are typically sensitive and vulnerable environments. These areas are exposed to risks such as the global effects of climate change, particularly the rise in sea levels or local urbanization developments. Still, they are sought after for recreational and tourism purposes (Biondi, 2014). As part of the marine tourism industry, marinas’ main purpose is to provide shelter for seagoing vessels. Additionally, a plethora of services is available for berth holders and occasionally to non-berth holder customers. In accordance with their raison d’être, marinas must be located in environmentally desirable places. The environment inside the marina, as well as its surroundings, are the main factors in determining the attractiveness of a certain marina for boat owners, such as potential customers. Disregard for the environment will eventually affect the demand for a marina. On the other hand, adopting a truly environmentally conscious approach will support a marina’s long-term survival, enhancing its reputation over generations. A marina’s main operations may involve boat docking (berthing), cleaning, building, and maintenance facilities, fueling, waste management, while they may offer numerous additional supportive operations/services. According to the Marina 2020 Industry Report, active communication between policy makers and the marina sector is important to ensure environmentally sensitive marina design, in line with measures that set new targets for 2020 and beyond in terms of a greener and more competitive economy, energy efficiency, and so on. Having a reputation for environmentally friendly practices has become an essential part of marinas’ competitive edge (Hales et al., 2016). However, investing in environmentally conscious business practices comes with a considerable price tag (Woo et al., 2018). All marinas offer similar services, however, in order to remain competitive within their industry; they need to sustain environmentally conscious practices, as well as supportive services (Dragovic et al., 2015). As an important tourism subsector generating relatively high revenues, ensuring product differentiation, and providing sustainable development opportunities, marina tourism may be evaluated as a strategic option for Turkish tourism. Turkey has great potential in yacht tourism, due to its long coastline (8333 km), natural beauty, and high-quality accommodation facilities. There are currently 83 marinas

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that operate in Turkey (Maritime Chamber of Commerce). A study on Turkish marinas by the Maritime Chamber of Commerce in 2019 revealed that there were 20 marinas in the Aegean region of Turkey alone. According to the literature review on environmental policy and sustainability of marinas, existing studies are focused on environmental management systems (EMS) (Lavery, 2010, Tselentis, 2008, Tselentis et al., 2016); developing sustainability (Biondi, 2014, Tselentis et al., 2016, Lam and Van de Voorde, 2012, Heron and Juju, 2012, Heron, 2015, Biondi and Lara, 2015, Tselentis et al., 2015); their environmental impacts (El Gohary and Hassan, 2012); and certifications (Blue Flag) (Heron, 2015, Dijk, 2009, Eser and Sumer, 2013). The ways that marinas adopt sustainability practices are waste/water management, energy conservation, health and safety regulations, environmental management and training, emission and residual management, and integration of natural life with ports and urban areas (Dragovic et al., 2015). According to Akaltan & Isik (Akaltan and Işık, 2018), environmental practices of the marinas in Turkey include waste water management, recycling and waste management, power management, training of yachtsmen, waste management of dry-dock areas, rainwater management, compliance with waste management regulations of the Ministry of Environment, and volunteer-based environmental management. Environmental sustainability approaches of all marina enterprises and users have been gaining importance in order to ensure environmental sustainability in marinas. In this respect, not only the management of the marina, but every person who visits the marina must have environmental awareness and contribute to sustainability. Environmental sustainability in marinas; efficient use of resources, reuse, recovery and disposal; efficient use of energy and natural resources; minimizing the use of hazardous chemicals are all measures of how minimized their impacts are on the environment. Marinas provide licensed waste reception facilities or receive services from environmental consultancy firms to collect waste oil and bilge oil formed by yachts and boats to protect the environment. In the literature review section, it is shown that there has been a serious neglect of the understanding of sustainability marketing activities in marinas, which determines the role of environmental policies in achieving competitiveness. The contribution of this chapter is to investigate the role of marinas’ sustainability marketing activities in achieving competitiveness through sustainable growth and development. The study consists of two parts: the first part includes the theoretical framework for sustainability marketing activities and their implications for marinas (Blue Flag, Blue Star, Blue Card, Gold Anchor Awards, ISO 9001 & 14001), while the second part consists of in-depth interviews with managers of selected marinas regarding sustainability marketing activities. Implications and suggestions are revealed based on the findings. In this context, there is an analysis of the extent to which sustainability marketing activities have an effect on sustainable competitive advantage.

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8.2 Literature review 8.2.1 Sustainability marketing According to the literature, the 1975 study titled “sustainability marketing” organized by American Marketing Association (AMA) is the first on the issue of green marketing. Green marketing is defined as an organization’s attempt at designing, promoting, pricing, and distributing products to satisfy human needs and wants in ways that minimize environmental harm (Stanton and Futrell, 1987, Pride and Ferrell, 1993, Polonsky, 1995). Green marketing is a holistic strategic management concept that integrates environmental issues into corporate strategies, so that production and marketing of products and services are conducted in ways that are less harmful to the environment. To that end, corporations have been developing strategies that target society to increase awareness of global warming, nonbiodegradable solid waste, harmful impacts of pollutants, and so on, ever since (Charter, 1992, Fuller, 2000, Chandran and Robinson, 2016). Sustainability marketing focuses on environmental issues and is related to environmental marketing, ecological marketing, social marketing, and sustainability marketing (Zhu and Sarkis, 2016). Green marketing as a concept went under a three-phase evolution between 1975 and 2000. In the first phase, coined as ecological green marketing, all marketing activities were concerned with understanding and finding solutions for environmental problems. The second phase was called sustainability marketing. This phase focused on designing new environmentally friendly products, by implementing cleaner technologies. The period from late 1980s to late 1990s was indubitably marked by the effects of green marketing. Although the concept was formally accepted by firms and companies, its practical applications proved to be hard. Despite the difficulties in applying the concept as a whole, the post 90s period saw a rise in terms of acceptance of green concepts into marketing. During this stage, marketing principles were further influenced by sustainable development (Katrandjiev, 2016). The last phase was focused on the sustainability of green marketing (Shrikanth and Raju, 2012). This phase proposed that environmental issues should be considered through a holistic management process for suppliers and retailers, community members, regulators, and NGOs. Fuller, in 2000, gives one of the earliest definitions of sustainability marketing as “a process of planning, implementing and controlling the development, price-formation and distribution of a product in a way that guarantees adherence to the following three criteria: (1) satisfying consumer needs; (2) guaranteeing the achievement of the organization’s goals; (3) the whole process being in harmony with the ecosystem” (Fuller, 2000). Responsible production, as well as consumption, to create a sustainable economy through recycling and reusing, fair trade, product-service swaps, reduction of sources, composting, energy efficiency was the main theme of this phase (Peattie, 2001, Peattie and Charter, 2003).

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By definition, sustainable marinas are in tune with their “natural, social, and economic environments” (De Boer, 2016). The aim of sustainability marketing is not only to identify and satisfy customers but also to create value for society through providing sustainable developments and encouraging the consumption of ecofriendly products (Peattie and Crane, 2005, Osman et al., 2016, Lam and Li, 2019). Examples of sustainability marketing activities include efficient energy operations, developing pollution control systems, recyclable and biodegradable packaging, and ecologically safe production – all of which allow transformative change (Choudhary and Gokarn, 2013). Although several definitions of sustainability marketing are discussed, products that are considered green have one or more of the following common qualities: efficient in energy and/or water consumption, decreased hazardous emissions, recyclable, renewable, made of reused materials, certified organic, environmentally safe and/or healthy, and biodegradable (Thakur and Aurora, 2015). Sustainability marketing strategies should be implemented in different markets, depending on the degree of consumers’ environmental concerns (Ginsberg and Bloom, 2004). Sustainability marketing can help corporations gain a competitive advantage, and a strong consumer base. The AMA lists three definitions of sustainability marketing from three different perspectives: retailing, social marketing, and environmentally oriented. As per the retailing perspective, sustainability marketing focuses on marketing environmentally safe products. The social marketing perspective refers to products designed to minimize harmful effects on environment. The environmental perspective defines the efforts of organizations to change production processes to reuse or recycle products in a manner that it is sensitive or responsive to ecological concerns (Bruer, 2009).

8.2.2 Sustainability marketing strategies for marinas Marinas, which are essentially yacht harbors, can be defined in a variety of ways. A basic definition in the Merriam-Webster Dictionary suggests that a marina is a dock or basin providing secure moorings for pleasure boats and often offering supply, repair, and other facilities (Merriam-Webster Dictionary, 2018). The International Council of Marine Industry Associations (ICOMIA), a major international trade association representing the global marine industry, defines marina as follows: A public, private or commercially provided facility, ordinarily located at the waterside, that primarily supplies wet (e.g., slips, moorings, anchorage) and/or dry (e.g., drystack, on-land) storage for recreational boats for a rental fee or for purchase and generally offers/sells one or more boating-related services and/or products such as fuel, restrooms and showers, maintenance and repairs, sewage pumpout, boat sales, and/or ship store. (ICOMIA. Recreational Boating Definitions, 2006)

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Marinas may cause pollution by a number of activities such as “boating, fueling, hull repair, engine maintenance”; however, it is possible to manage these facilities in ways as to minimize the negative effects on the environment and preserve water quality (Koc and Mermer, 2016). If not supervised, yachts may release sewage water that can cause sickness in humans and pollute shellfish resources (Massachusetts Clean Marina Guide, 2001). Although the basic function of a marina is to provide secure moorings for recreational boats, customers are unlikely to spend their recreational time or berth their boat in an environmentally displeasing marina. By definition, the environment would be in a more natural and pristine state without human intervention, that is, without manmade structures or waste. All by-products of human civilization can be viewed as a disease on the otherwise untouched environment. Therefore, the visionary goal of a marina should be to help improve or at least avoid harming the environment. This can be realized and is achieved by marinas all over the globe, and there are abundant instances of marinas designed and built without a major impact on the local environment, for example, those built inside national parks or on protected coastlines (Heron and Juju, 2012). Nowadays, marinas are playing a leading role in sustainable business initiatives, by utilizing green technologies and integrating environmental issues into all organizational activities. Many marinas have adopted environmentally friendly policies and implemented regulations to protect and prevent environmental damage. Attention to environmental issues extends to building “green” marinas, a new standard in the United States, which requires a high-level of eco-friendliness from both developers and owners. Leadership in Energy and Environmental Design (LEED) is the USA’s nationally accepted benchmark for the design, construction, and operation of high-performance green marina buildings. It is a rating system devised by the United States Green Building Council to evaluate the environmental performance of a building and encourage market transformation toward sustainable design. The system is credit-based, allowing projects to earn points for environmentally friendly actions taken during construction and use of a building. The standard is now spreading outside the USA, with Dubai being one of the first areas to strive toward achieving it (Heron and Juju, 2012). According to the standards and initiatives of the European Union (EU), green concepts and sustainable development should be implemented in all aspects of marina operations (Tselentis et al., 2016). A marina’s raison d’être is to primarily provide services for recreational boats, as well as their guests and crew. Rahbar and Abdul Wahid’s study (Rahbar and Abdul Wahid, 2011) indicates that sustainability marketing strategies should be applied on different markets, according to the degree of consumer environmental concern. Such sustainability marketing concepts include low-energy solutions, sustainable products, biodegradable, nontoxic ingredients, low waste (or emissions), chemical-free recycled materials, and

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clean marina (Seltzer, 2013). These activities promote health and safety issues as part of an environmentally friendly strategy (Tselentis et al., 2015). To be able to achieve these goals, dedicated staff is needed to focus on environmental and social issues. There is no single international standard in the marina sector in terms of environmental/safety-related classifications; instead, there are a few programs for assessing these aspects with various degrees of complexity (Heron and Juju, 2012). Major classifications that act as direct or indirect marketing tools for marinas are as follows: criteria for assessing environmental care (the Gold Anchor Award, the Blue Star Award), certifications (the Blue Flag, ISO 9001 & 14001, Blue Card), and Clean Marina Programs. These eco-labels comprise an important issue as well as a motivation to continually improve the services to consumers, especially in developing countries for supporting the sustainability. Gold Anchor Award. Since 2013, the Yacht Harbour Association (TYHA) and the Marina Industries Association (MIA) have jointly conducted the global Gold Anchor accreditation (classification). The ratings range from one to five Gold Anchors, covering an environmental audit, waste management plan, fire and safety plans, and areas of the ISO 14001 and OHSAS 18001 marina standards. There are 130 participating marinas throughout the world, operating in 23 countries. Fourteen marinas in Turkey are classified as having Five Gold Anchors (TYHA, 2018). Environmental policies and procedures, ambience, planning, customer service, on water and on shore facilities, and infrastructure are the basis for the evaluation criteria to obtain a Gold Anchor accreditation. Gold Anchor is a prestigious marketing tool that enables marinas to be recognized as a brand. This accreditation assures customers of the quality of services, and thus is an attraction for existing and potential customers in a competitive market. It also helps individual marinas to differentiate themselves from competitors, by endowing them with a tangible measure, reward, and recognition for their efforts. For instance, to receive this award, the environmental facilities should be capable of containing oil spills using a combination of retaining booms and absorbent spillage mats, as well as environmentally friendly hull wash. They should also be able to effectively manage paint particles during antifouling and hull painting, as defined by procedures. Blue Star. Blue Star Marina Certification is a comprehensive quality assessment tool to indicate the quality level of marinas through third party assessment by the International Marine Certification Institute (IMCI). This marina classification program awards a star rating of one to five to indicate the quality of certified marinas. The criteria used to determine the level of quality for marinas are external presentation, safety, sanitary installation and hygiene, service, food supply and leisure, management, environmental protection, and disposal. This certification offers the following benefits for boat and marina operators: marinas can easily be compared across country borders; marina operators receive a low cost, internationally standardized certification that displays marina quality, and finally, is alerted to areas for improvement, thus, increasing customer satisfaction, as well as overall revenue

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(Marina Network Association). In Turkey, only Teos Marina and Palmarina have the Blue Star classification (IMCI, Blue Star Marina, 2020). Blue Flag. The Blue Flag program is an environmental eco-label for beaches, marinas, and yachts that requires them to attain the 24 criteria concerning high standards of water quality, environmental education and information, environmental management, safety, and services. Some criteria are designated as obligatory, others as guidelines to promote sustainable development according to specific circumstances (Dijk, 2009). Blue Flag certification is a symbol of quality in terms of marketing, as well as an indicator of achieved sustainability of development (Radchenko and Aleyev, 2011). In total, 22 Turkish marinas qualify for the Blue Flag certification (Go Turkey Tourism, 2018). ISO 9001 & 14001. ISO 9001 quality management standard was first introduced in 1987, leading to higher levels of performance and customer satisfaction. The standards were updated in 1994, 1997, 2000 and 2008, and are being reviewed in 2015. Marinas meeting the criteria for this standard are assessed annually to ensure progress is being maintained, providing customers with world standard procedures and demonstrating a commitment to quality. The four main elements of the standard are environmental policy planning; implementation and operation; checking and corrective action; and on-going management review. ISO 14001 is intended to provide environmental management standards to enable organizations to become environmentally friendly, reduce waste output, measure consumption, and evaluate their environmental performance. This certification ensures marinas are less susceptible to safety risks, have improved safety processes, are able to prevent pollution, and continually progress in conformity with legal and other requirements by an external auditor (Heron, 2015). ISO 14001 assessment covers the areas of strategic environmental management, leadership, and environmental protection through approaches such as using sustainable resources, offsetting climate change, and ensuring the protection of ecosystems and encouraging biodiversity. These quality management standards enable marinas to measure their degree of success, improve efficiency, decrease operating costs, resolve environmental problems, increase profits, and make advances in health and safety. Clean Marinas program. The Clean Marinas program is a regional voluntary program that ensures the use of environmentally friendly facilities resulting in sustainable management practices and the protection of marinas from pollution. This eco-label program, managed and accredited by the Marina Industry Association (MIA), is an easy-to-follow system for developing valuable environmental management practices and leads to accredited operators gaining substantial business benefits. This program represents a valuable eco-friendly recommendation that can be used to attract customers in marketing efforts (Seltzer, 2013). In order to apply, marinas must meet standards and demonstrate emergency plans in the event of pollution or fire. A compulsory inspection is required at least every three years. These criteria cover areas including separation of waste, determining the location of

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waste containers, waste management plan, staff training, regulated boat washing and maintenance areas, and informing customers and boat owners about environmental practices (Heron and Juju, 2012). Blue Card. The Blue Card is a legal electronic card system in Turkey. This card helps prevent marine pollution and illegal discharges by providing procedures for gathering data on the location and timing of disposal, as well as the levels of a vessel’s waste tank (gray, black, etc.) before and after disposal. This card enables local authorities to use an online system to monitor waste discharges from motor vehicles, such as yachts, recreational crafts, and tour boats (Noyan, 2016). The system provides data on frequency of wastes disposed and improves control over inspection. The Blue Card system, overseen by the Ministry of Environment and Urbanization, Coast Guard Commandership, and Port Authorities, is established at 55 marinas in Turkey, and has been applied to approximately 20,000 vessels (Noyan, 2016).

8.3 Methodology The aim of the study is to understand the sustainability marketing activities in marinas, to determine the role of environmental policies in achieving competitiveness, and to identify and evaluate the environmental practices, and consequently reveal the beneficial management practices currently utilized. Since the topic of sustainability marketing in marinas is mainly an untapped area of the literature, a qualitative methodology was preferred – as recommended by various authors in cases where the context and the phenomenon need clarification (Rojo, 2009).

8.3.1 Research questions – What are the environmental management practices of marinas in terms of sustainability marketing practices? – Overall, are customers conscious about the importance of environmental sustainability? Do the preferences of local and foreign tourists differ? – Which eco-label classifications/certifications are held by marinas, and do these provide a sustainable competitive advantage by means of differentiation?

8.3.2 Procedure The research method of this study consists of semistructured in-depth interviews with seven managers from selected marinas across the Aegean region of Turkey, home to the majority of marinas in the country. This method was chosen as the

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most suitable approach for understanding the motivational factors involved in decision-making. The study was carried out between June 15 and August 20 in 2019. Seven marinas in the vicinity of Izmir (in the Aegean region (i.e., West and Southwest Turkey) were selected, based on classifications and/or certifications received by the marinas, and their significance in terms of berthing capacity and traffic, as well as proximity to Izmir, for ease of travel. Based on the aforementioned criteria, the selected marinas were: 1. IC Cesme Marina (Cesme, Izmir) 2. Setur Cesme Marina (Cesme, Izmir) 3. Port Alacati (Cesme, Izmir) 4. Teos Marina (Seferihisar, Izmir) 5. Milta Bodrum Marina (Bodrum, Mugla) 6. D-Marin Turgutreis (Turgutreis, Mugla) 7. Palmarina (Yalikavak, Mugla) All respondents gave permission to audio-recorded interviews, which lasted about one hour on average. The interviews were transcribed verbatim. Following this, an analysis of relevant documents, including but not limited to written environmental policy statements, was undertaken to validate the accuracy of the interview data. The analysis is supported by related images illustrating environmental measures taken by marinas. The literature review on the topic provided the theoretical basis for identifying and/or developing the major themes as follows: environmental practices of marinas, saving water and electricity, sensitivity of marinas’ customers regarding environmental sustainability, monitoring strength of marinas regarding environmental regulation, sustainability marketing certifications and classifications (Blue Flag, Gold Anchor Award, ISO 9001 & 14001), and influence of sustainability marketing activities over customer preferences.

8.3.3 Findings Table 8.1 gathers the data regarding the marinas’ certifications and classifications based on the interviews with marina managers, posts documents in corresponding marinas’ front offices, and information available on their website.

8.3.3.1 Environmental practices In terms of sustainability marketing, numerous environmental practices are adopted by marinas. Some try to differentiate themselves by unique environmental practices, while others only adopt the minimum requirements.

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Table 8.1: An overview of the marinas analyzed. Marina Total # of managers berths M M

 

M M

 

M



M



M



Blue flag

Gold anchor award Blue star

ISO 

ISO 

N Every year since  N Every year since  Every year since  Every year since  Every year since 

N N

N N

Y Y

N N

N  anchors since   anchors since   anchors since   anchors

N  stars

N N

N N

N

N

N

N

N

N

N

Y

Y

In the interviews, waste collection and sorting emerged as the key practices. The strong emphasis placed on these practices by marina managements suggest that these are the main pillars of marina environmental management and are the basis for all other practices. Different types of wastes are collected in separate facilities. Solid waste management involves separate collection in specific containers, minimization at the source, reuse, and recycling alternatives. After being collected and sorted, waste is generally managed by the local municipality. Hazardous waste, which is mainly a by-product of maintenance and repair, is collected in designated bins and areas. For wastewater management, practices differ among marinas. Some marinas provide separate collection facilities for wastewater from land and from water. We have a mobile waste water collection facility, as well as a stationary one.

(M5)

We have a waste collection facility. We have both a fixed waste collection facility, and a floating barge servicing the marina. Boats up to 30m dock at the fixed facility and dispose of waste, while we pick up the waste from boats over 30m. Larger vessels prefer us over the other marinas. We are able to service 120m-vessels inside the marina. (M7)

Marina managers underlined that two of the most essential environmental measures are designating specific spaces for waste collection and sorting the collected garbage into separate bins/areas, for example, batteries and paper. An example of a designated waste collection & sorting area can be seen in Figure 8.1. As for the environmental arrangements in a marina, the space for waste collection should be large enough, so that battery and paper wastes are separated. The sea must not be polluted. (M3)

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Figure 8.1: The designated area in one of the marinas has separate bins for various types of waste, in accordance with MARPOL.

In all marinas analyzed, paper, glass, metal, and plastic wastes are separated, and recycling programs are implemented. The berth holders are obliged to participate in the recycling program. One of the more creative recycling programs came up with pieces of art made from repurposed materials. A portrait of Sadun Boro can be seen in Figure 8.2. Waste sorting is carried out regularly. There is a designated area to dispose of the products that cannot be sorted. There are bins for kitchen oil (frying oil). Waste oil from engines is also collected. There is a facility where we keep the bilge water we take away from vessels. (M6) Art is made out of the garbage that comes from the sea. There is a statue made out of junk metals. There is the statue of Sadun Boro made out of bottles. (M6)

As for recycling water, marina managements show innovative approaches. We provide fresh water that is desalinized. We have a capacity of desalinizing 780 tons of salt water per day. (M7)

In another approach employed by one marina, the water used to clean underwater hulls is filtered and reused. This marina also uses water circulation canals that make fishing possible inside the marina. The marina houses circulation canals, a bilge-water and engine oil collection facility, a household waste collection facility, and a waste sorting facility. (M6) The same water is used over and over again on the underwater hull wash area. There is a sanitation plan for that purpose. (M2)

As another environmental practice, M2 has been collecting and filtering rainwater as a source of fresh water – the only example of such a system in Turkey.

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Figure 8.2: An artwork tribute to the legendary seaman, Sadun Boro, made from glass and plastic bottles retrieved from the sea. Rain gutters as well as a facility to collect water in drainage and filter it – not seen anyplace else in Turkey. . . (M2)

One of the marinas has launched an initiative named the “Mussel Project.” It is a brilliantly organic application to keep the water inside the marina clean and fresh. According to their own scientific research, a mussel can filter about 150 liters of water per day. Furthermore, the marina management has planted 75 olive trees, 51 pomegranate trees, 31 orange trees, 16 lemon trees, and 2 gumwood trees, which are regularly harvested for their fruit. Every year, the olives are harvested by the marina employees and their family members in a festive ceremony. Then, the olives are pressed into premium olive oil (Figure 8.3), which is gifted to distinguished guests of the marina. M1 stated that their marina has been awarded the Green Apple Environment Awards, and thus proudly displays the Green World Ambassador logo on their website as well as their front office. This logo on the website is accompanied by an environmental policy statement: –

We will meet the environmental legislation that relates to the operation of the marina (No: 2872), and where possible identify opportunities to adopt best practice over and above the minimum requirements by receiving monthly legislative updates.

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Figure 8.3: Premium olive oil made from olives grown on the marina premises.

–

– – – – – – – – – –

We will ensure that marina boats are fuelled safely and responsibly to avoid spillages and pollution. All boats will have a spill kit ready when refuelling. Boat drivers will be trained in refuelling good practice and the use of spill kits. We will minimise the use of electricity in all of our activities. For example; turning off lights, replacing old light bulbs with energy efficient models. We will minimise the use of water in all of our activities. For example; fitting hoses with automatic trigger nozzles and turning off taps when not in use. We will minimise the creation of waste. For example; we will only print and photocopy if absolutely essential and then print double-sided. Where possible, we will use email rather than printed materials to communicate and promote our activities. We will provide suitable containers for the disposal of hazardous waste streams. We will encourage members to apply best management practises in dockyard area. We will endeavour to take a sustainable approach to our operations. We will publicise our environmental commitment and promote sustainability amongst our members and visitors on our website and marina notice boards. We will measure our progress and review this policy on an annual basis. (IC Çeşme Marina) Any marina that does not take environmental measures seriously and follow up on the latest advancements on environmental sustainability will inevitably fall back in terms of competitive advantage. (M1)

8.3.3.2 Saving water and electricity A recurring theme in the interviews was the vital role of saving water and electricity for the environment and for all parties involved. There are many ways in which a marina can achieve a reduction in the amount of water and electricity consumed by both berth holders and personnel. A widely common practice among the analyzed

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marinas is to offer pre-paid water and electricity to its berth holders – as the only way to receive those services, too. We have switched to LED lamps and hose guns. Water and electricity is provided through a pre-paid system. (M4) We have adopted a system of pre-paid electricity and water for all yachts – all through a single key. [. . .] Every Setur Marina (Koc Group) has it now. The water and electricity consumption fell by 50% within three months. (M2)

Due to the advancements in energy-efficient technology, as is currently available, solar-powered restrooms and/or showers have become a viable option. Three out of the seven marinas analyzed utilized their exposure to the sun by employing technology, resulting in sizeable cuts in their overall electricity consumption. While some marinas use solar power for hot water for restrooms and showers, others do so for storing and regenerating electricity. Green energy – especially solar panel technology – is heavily used. That is how we provide hot water for our customers. (M7) We will be generating electricity via solar power in the near future.

(M6)

We are seriously considering using solar power for our restrooms and showers.

(M5)

Moreover, switching to LED lamps -wherever possible- vastly reduces the electricity consumption in an average marina, where various light sources are needed. Considering these major marinas offer a wide array of facilities/services from bars to yacht maintenance/repair, LED lamps make a significant difference. All of the lighting in the marina is provided by LED lamps, which save energy.

(M2)

8.3.3.3 Sensitivity of marina customers regarding environmental sustainability As much as marina managements may try to protect the environment, this goal cannot be achieved without cooperation from berth holders. To begin with, all marina managers agree that biodegradable soap is essential – as regular soap is destructive to the marine environment. As one marina manager puts it: “it is not enough if only marina managements and personnel are environmentally conscious; customers should be, too.” In order to establish a certain degree of consciousness regarding the environment, we constantly send out e-mails to both vessel crews and other clients reminding them of the marina rules. (M7)

In an attempt to determine the environmental awareness of customers, the degree to which they comply with the environmental regulations of their respective marinas was investigated. To that end, most of the marina managers interviewed stated

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that use of regular foaming soap agents is strictly prohibited, and biodegradable ones are used instead. If a customer is caught violating this regulation, some marinas notify the Coast Guard, as any direct action by the marina would risk losing the customer. However, an ethical as well as a managerial dilemma is posed by customers that damage the environment, and on purpose rather than through ignorance. Are such customers worth the pursuit at the expense of a long-term sustainability of their immediate environment? Other marina managers stated they have been able to establish a self-monitoring mechanism among clients, which relies on whistle-blowing, such as by documenting such actions via photographs. Anybody may turn in anybody else. Our regulations are based on self-inspection of the clients. We have a “right/wrong board”, where pictures of wrongful actions are posted. (M6)

8.3.3.4 Enforcement capabilities of marinas regarding environmental regulation Marinas have no authority to issue fines regarding environmental issues. For instance, in case of a waste/oil leakage inside the marina, the client responsible may be billed under cleaning charges; however, no official fine can be issued in such cases. The common view among the marina managers interviewed is that marinas lack adequate enforcement capabilities. On the grounds it is the Coast Guard that has to fine malpractices upon inspection, we cannot perform inspections of our own. (M1)

8.3.3.5 Sustainability marketing certifications and classifications Blue Flag. Among all the certifications and classifications, the Blue Flag certification is by far the most popular; nevertheless, two opposite views are put forth by the marina managers. It enhances the marina’s image by showing how environmentally friendly the marina is. (M7) Although, supposedly, the Blue Flag makes a marina more prestigious, we yet have to experience a positive effect on our marketing efforts. (M6)

Some marina managers argued that not every customer perceives a significant value for the Blue Flag award. It is seldom asked for during reservation processes (M5).

It is particularly uncommon for Turkish berth holders to assign this certification any significance. However, for potential berth holders who are environmentally conscious, it is seen as a prerequisite for a marina.

8 Can sustainability marketing be implemented as a differentiation strategy?

It is more sought after by foreign customers [than local ones].

149

(M2)

Gold Anchor Award. Two marina managers believed the Gold Anchor Award was not worth the effort. One stated it was impossible for their marina to attain five Gold Anchors even if they wanted to – due to physical restrictions. The remaining four managers said it was particularly sought after by foreign customers. According to an analysis of the questionnaires we hand out to our berth holders, having five Gold Anchors matters more for the foreign customers. (M5) Foreigners are more selective. Having the Blue Flag Award coupled with five Gold Anchors means a lot to them. (M4) In order to attain the 5 Gold Anchor level, we have to have amenities like spas, etc. Since we are physically restrained, we would be stuck at the 4 Gold Anchors level, no matter what. (M2)

ISO 9001 & 14001. Most managers interviewed stated that obtaining ISO certifications is excessively costly, and for most, irrelevant to them – which is why they never even considered applying. Out of the seven marinas, only one already had the most recent ISO 14001 certification, and another was just considering obtaining it. Blue Card. All marina managers acknowledged that the Blue Card is mandatory for all yachts, regardless of their origins. It was also noted that berth holders seem to behave in a more environmentally sensitive manner while berthing in Blue Flag marinas.

8.3.3.6 Influence of sustainability marketing activities over customer preferences Most managers agreed that even though sustainability marketing activities might have a positive effect on the image of a marina, they had no real influence in convincing a berth holder to choose a certain marina. “Although the concept of ‘green’ makes the overall concept positive, it does not change the basis for preference. At the end of the day, the location is what counts the most. Since it is not the basis for preference, it should be added that a customer brings in a new customer only if he/she leaves here satisfied. Service quality is the next biggest factor.” (M6)

8.4 Conclusion To conclude, while being environmentally conscious is clearly essential for marinas, it certainly comes with many challenges. Environmental sustainability is of great importance for marinas, which are an important part of marine tourism. The most significant theme regarding environmental sustainability in marinas is waste management. Sustainable marina environment, protection of marine resources including flora/

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fauna, contribution to regional development and national economy, reuse/recycling, waste recovery and disposal are not only environmental, but also economic and social sustainability measures of a marina. On the other hand, effective environmental management and monitoring sustainable development are the common difficulties faced by a marina. In this study, the sustainability marketing activities of seven marinas were analyzed in terms of environmental practices, and the certifications and/or classifications held by them. It was investigated how far these practices/certifications/ classifications consequently affected berth holders’ preferences. Since the literature on marina management and sustainability marketing activities is limited, in general, this study aims to form the basis for further quantitative research. As far as certifications are concerned, the Blue Flag award enjoys worldwide recognition and is regarded as a valid eco-label by at least a proportion of berth holders. It is by far the most common certification for marinas, as well as having the greatest general level of awareness. However, while some marina managers attribute great significance to it from a berth holder’s point of view, other opinions range from “moderately important” to “not at all important.” Marinas that are part of a corporate structure often comply with the ISO 9001 standards, which contributes to the image of a professionally run enterprise. ISO 14001, which is by far more appropriate for marinas, is relatively new, and therefore less known. As awareness of ISO 14001 grows, compliance will become more meaningful for marinas. As for classifications, the Gold Anchor Award Scheme – especially at the level of five gold anchors – creates the impression of a high-quality and environmentally friendly marina in the minds of green consumers, while the Blue Star award has narrower recognition and appeal and is yet to become widespread. In addition to certifications and classifications, marinas also have their own unique mixture of environmental practices to increase attractiveness, and further expand their customer base by enhancing their reputation as an environmentally conscious marina. The Blue Card, mandatory for every boat navigating Turkish waters regardless of its homeport or flag, allows marinas some degree of monitoring over how, where, and when wastewater is discharged. Despite the numerous certifications and classifications analyzed in this study, there is a noticeable lack of a comprehensive management approach to sustainability. This owes a lot to the common managerial understanding that location is the main factor in the attractiveness of a marina. Thus, at any stage in a marina’s existence, the marketing strategy is mainly reliant upon its location. Since the location cannot be changed, some of the managements feel powerless to increase or decrease the demand. However, all acknowledge that the marina itself will not be sustainable, unless the environment is sustainable as well. The existence of a sustainability marketing strategy displays top management’s commitment to environmental sustainability. Such ports utilize sustainability marketing as a differentiation strategy; it is indeed a good thing, for it sets the direction for

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the port industry toward sustainability. This sustainability marketing strategy aspect shows that the top management of a port is committed to environmental sustainability. These marinas use sustainability marketing strategies to differentiate themselves from competitors. These are good practices that set the direction for the marinas toward sustainable development (Lam and Li, 2019). Environmental sustainability is crucial to a marina, yet presents many challenges. Environmental sustainability refers to a perpetual process, rather than a state of being. In the case of marinas, their attitude toward acting environmentally may mean the difference between their continued existence and their demise. Hence, sustainable activities are important not only for their marketing implications but also for a marina’s long-term existence.

8.5 Managerial implications Careful planning of the physical media in marinas is crucial for customers’ experience design, and social sustainability. It is essential for a marina to have international quality certificates regarding sustainability, and these certificates may cover some safety-related and environmental standards as well. Marina managements should understand and appreciate the value of international quality certificates in order to have sustainable and green marinas. Moreover, these certificates also cover some crucial safety-related and environmental standards. Physical planning of marinas is essential in providing a high-level guest experience and social sustainability. Successful marinas are those that have already embraced the relevant certifications and/or classifications for their businesses, as it helps them obtain new customers while retaining existing ones in a critically competitive environment. The most critical factor in a marina’s success is its ability to provide a level of customer service that will differentiate it from the competition. Ultimately, sustainability marketing activities should be considered as the quintessence of a long-term sustainability for a marina, rather than a means to an end. For a marina facility to be regarded as sustainable, its management needs to institute safe and environmentally friendly working conditions. Routine training sessions, including but not limited to, first aid practices, fire drills, handling of hazardous materials, emergency response, and safety at sea, and pump out safety may help employees understand the critical processes in a marina. It would also be supportive to encourage sustainable developments within the marina to improve water quality and the surrounding environment, in general, to assess the noise level in the facility, and to define the policy for sustainable use and protection of the marina’s coastal environment. Even though every marina is unique in terms of its “expectations, rights and responsibilities with regard to sustainable marina development,” still the same pattern for sustainability needs to be followed, and regulatory, economic, and planning tools must be utilized to pursue social, economic, and environmental issues. The performance

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of sustainability in marina development depends on the successful implementation of practices such as “cost saving and improved management control, compliance with legislation, fair competition, meeting customer expectations, improved environmental performance, raising awareness and motivating personnel, integrating the elements of an EMS and monitoring the quality of management and environmental performance.” To achieve sustainability, these practices should all be considered by marina management: – Implementation of environmental policy and EMS – Determining standards for water quality – Defining and pursuing standards for environmental management – Improving environmental education and safety – Improving water management – Improving waste management – Analysis of energy consumption alongside docks and berths – Promoting health and safety issues in regard to environmentally friendly strategies – Compliance with the highest standards of the Gold Anchor Scheme – Getting accreditation to provide sustainable development concepts in marina – Compliance with the Blue Flag award Stakeholders are essential to the development of sustainable marinas. Achieving a certain level of satisfaction among yachtsmen and marina personnel will help encourage local stakeholders to further develop and promote sustainable practices in the area (Tselentis et al., 2016). As customers – especially yachtsmen – are the main source of income for a marina, their concerns regarding the natural as well as the social environment should be taken into account while forming strategies and carrying out operations (Lam and Dai, 2015). Integrating environmental practices into their business strategy, and then conveying these strategies via a suitable corporate image achieved through appropriate marketing activities would greatly benefit marina managements. This integration could also take place in the corporate vision or values level. Then, it would emphasize the management’s commitment to environmental sustainability as a whole. To complement the corporate image, sustainable development could be supported by social responsibility and economic benefit models over the long term (Dragovic et al., 2015). The continuous investment necessary to maintain these awards and certifications will keep a marina on the path to a long-term profitability. Moreover, marinas need to integrate sustainability marketing activities into their strategic plans, and then communicate their image to their surroundings (Rojo, 2009). Furthermore, marinas’ websites could provide details of sustainability programs developed and administered by their managements (Lam and Li, 2019).

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8.6 Limitations and future research Quite possibly, this qualitative study will pave the way for a poll study regarding sustainability marketing in marinas, which will provide insight into the customers’ perception of awards and certifications. Likewise, a quantitative study will help measure the awareness and satisfaction levels of berth holders, and act as a tool to boost demand, improve satisfactions levels, and assure customer loyalty.

References Akaltan C. and Işık N.G. (2018). Marinalarda Çevre Yönetimi Uygulamaları: Türkiye Marinaları Üzerine Bir Çalışma. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 11, 73–92. Biondi E.L. (2014). Planning sustainable marinas-the social dimension of sustainability. USA: In PIANC World Congress San Francisco. Biondi E.L. and Lara A.L. (2015). Sustainable marinas–institutional framework of sustainability. “Smart Rivers 2015” Buenos Aires, Argentina, URL: http://www.pianc.org.ar/_stage/pdf/pa pers_sr2015/68_paper_Biondi_USA_10.pdf, (Accessed on 25. 12.2018). Bruer R. Posts tagged ‘American Marketing Association’. (n.d.). (2009), URL: http://www.rbruer. com/tag/american-marketing-association/, (Accessed on 03. 04.2019). Chandran K. and Robinson M. (2016). Consumer belief and purchase intention towards the green marketing: Literature review. International Journal, 2, 200–203. Charter M. (1992). Greener marketing: A responsible approach to business. Greenleaf Publishing. Choudhary A. and Gokarn S. (2013). Green marketing: A means for sustainable development. Journal of Arts, Science and Commerce, 4(1), 26–32. De Boer G.G. (2016). Developing a framework for an ecosystem-based approach to sustainable marina development: Including a framework application case study for a marina on the island of Mauritius, Indian Ocean. Dijk J. (2009). Implementation of the blue flag program key issues and concerns. Graduate thesis, Blue Flag Program St. Maarten, URL: http://epicislands.org/46%20-%20Implementation%20of%20the %20Blue%20Flag%20Program_Jenna%20van%20Dijk%202009.pdf, (Accessed on 15.01. 2017). Dragovic B., Tselentis B.S., Papadimitriou S., Šerović D., Škurić M., Meštrović R., and Mikijeljević M. (2015). A study approach of marina sustainable development framework. Proceedings of 14th International Conference RaDMI 2014, Topola (Serbia), Bar and Kotor (Montenegro), Vol. 3: 1031–1038. El Gohary R. and Hassan N.A.A. (2012). Environmental Impact Assessment (EIA) of marine structures – A case study. KSCE Journal of Civil Engineering, 16(5), 689–698. http://doi.org/ 10.1007/s12205-012-1347-5 Eser Z. and Sumer S.I. (2013). Managers’ concerns to use blue flag as a marketing tool in tourism industry in Turkey. ASBBS Proceedings, 20(1), 448. Fuller D.A. (2000). Sustainable marketing: managerial-ecological issues. United States of America: Sage Publications. Ginsberg J.M. and Bloom P.N. (2004). Choosing the right green marketing strategy. MIT Sloan Management Review, 46(1), 79–84. Go Turkey Tourism, Blue Flag Marinas in Turkey, URL: http://www.goturkeytourism.com/things-todo/blue-flag-marinas-in-turkey.html, (Accessed on 05.01. 2018).

154

İpek Kazançoğlu, Can Karaosmanoğlu

Hales D.N., Lam J.S.L., and Chang Y.T. (2016). The balanced theory of port competitiveness. Transportation Journal, 55(2), 168–189. Heron R. (2015). The marina vol. II, your guide to certification and classification. Marina Publications. Heron R. and Juju W. (2012). The marina: Sustainable solutions for a profitable business. Marina Publications. IC Çeşme Marina, Environmental Policy, URL: https://cesmemarina.com.tr/en/environmentalpolicy/, (Accessed on 12.12.2019). ICOMIA. Recreational Boating Definitions. (n.d.). (2006). URL: http://www.icomia.com/library/ Document.ashx?DocumentDataId=2299. (Accessed on 03.03. 2017). IMCI, Blue Star Marina, URL: http://www.bluestarmarina.org/en/certification/operator-info, (Accessed on 03.01.2020). Katrandjiev H. (2016). Ecological marketing, green marketing, sustainable marketing: Synonyms or аn evolution of ideas. Economic Alternatives, 1(7), 71–82. Koc E. and Mermer D. (2016). Environmental and safety-related aspects in marina operations: A case study. The Second Global Conference on Innovation in Marine Technology and the Future of Maritime Transportation, Conference Proceedings Book, Bodrum, Muğla, Turkey, 740. Lam J.S.L. and Dai J. (2015). Environmental sustainability of logistics service provider: An ANP-QFD approach. The International Journal of Logistics Management, 26(2), 313–333. Lam J.S.L. and Li K.X. (2019). Green port marketing for sustainable growth and development. Transport Policy, 84, 73–81. Lam J.S.L. and Van de Voorde E. (2012). Green port strategy for sustainable growth and development. In: Transport logistics for sustainable growth at a new level. International Forum on Shipping, Ports and Airports (IFSPA), 27–30. Lam J.S.L. and Yap W.Y. (2019). A Stakeholder perspective of port city sustainable development. Sustainability, 11, 447. Lavery H. (2010). The relationship of boat movements to environmental management at some queensland marinas. Queensland Environmental Practice Reporter, 16(72), 40–65. Maritime Chamber of Commerce. Türkiye’de Deniz Turizmi, URL: https://www.denizticaretodasi.org.tr/ Media/SharedDocuments/DenizTicaretiDergisi/agustos_ek_2019.pdf, (Accessed on 05.09. 2019). Massachusetts Clean Marina Guide. (2001). Strategies to reduce environmental impacts, A Coastal Zone Management/EOEA publication, Prepared by Epsilon Associates, Inc. or the Massachusetts Office of Coastal Zone Management. Merriam-Webster Dictionary. Definition of marina. (n.d.). URL: https://www.merriam-webster.com/ dictionary/marina (Accessed on 02.03. 2018). Noyan K. (2016). The Blue Card system experience – Prevention of yacht-sourced illegal discharges and collection of waste. URL: http://web.unep.org/unea/side-events/blue-card-systemexperience-prevention-yacht-sourced-illegal-discharges-and-collection-waste-0, (Accessed on 12. 12.2018). Osman A., Othman Y.H., Salahudin S.N., and Abdullah M.S. (2016). The awareness and implementation of green concepts in marketing mix: A case of Malaysia. Procedia Economics and Finance, 35, 428–433. Peattie K. and Charter M. (2003). Green marketing. The marketing book, 5, 726–755. Peattie K. and Crane A. (2005). Green marketing: Legend, myth, farce or prophesy?. Qualitative Market Research: An International Journal, 8(4), 357–370. Peattie K.J. (2001). Towards sustainability: The third age of green marketing. The Marketing Review, 2(2), 129–146.

8 Can sustainability marketing be implemented as a differentiation strategy?

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Polonsky M.J. (1995). A stakeholder theory of approach to designing environmental marketing strategy. Journal of Business & Industrial Marketing, 10(3), 29–46. Pride W.M. and Ferrell O.C. (1993). Marketing (8th ed.). Boston, MA: Houghton Mifflin. Radchenko V. and Aleyev M. (2011). Blue flag program implementation prospective in Ukraine. Journal of Coastal Research, 52–59. Rahbar E. and Abdul Wahid N. (2011). Investigation of green marketing tools’ effect on consumers’ purchase behavior. Business Strategy Series, 12(2), 73–83. Rojo I.M. (2009). Economic development versus environmental sustainability: The case of tourist marinas in Andalusia. European Journal of Tourism Research, 2(2), 162–177. Seltzer D. (2013). Green marketing ideas and strategies for boating businesses. URL: http://marine marketingtools.com/green-marketing-ideas-and-strategies-for-boating-businesses/336, (Accessed on 03.04. 2019). Shrikanth R. and Raju D.S.N. (2012). Contemporary green marketing–brief reference to Indian scenario. International Journal of Social Sciences & Interdisciplinary Research, 1(1), 26–39. Stanton W.J. and Futrell C. (1987). Fundamentals of marketing (8th ed.). New York: McGraw-Hill Book Company. Thakur S. and Aurora R. (2015). Consumer preferences change when it comes to green marketing. Marketing, 245–255. Tselentis V., Dragovic B., Nikitakos N., Skuric M., and Coric A. (2015). Integrative model of sustainable development for marinas and nautical ports. In Proceedings of European Conference on Shipping, Intermodalism & Ports–ECONSHIP, 1–10. Tselentis V., Papadimitriou S., and Tzannatos E. (2016). Environmental management and monitoring for sustainable development in marinas. FME Transactions, 44(3), 304–312. Tselentis V.S. (2008). Marina environmental review system: A methodology to assess environmental management in recreational ports. European Research Studies, 11(1/2), 47. Woo J.K., Moon D.S.H., and Lam J.S.L. (2018). The impact of environmental policy on ports and the associated economic opportunities. Transportation Research Part A: Policy and Practice A, 110, 234–242. The Yacht Harbour Association. Gold Anchor, URL: http://www.which-marina.com/ GoldAnchorSearch.asp?SLS=2&GA=5&MappingOption=, (Accessed on 16.12.2018). Zhu Q. and Sarkis J. (2016). Green marketing and consumerism in China: Analyzing the literature. International Journal of Production Economics, 181, Part B, 289–302.

Jagdeep Singh, Mamta Kumari

9 Agricultural/biomass waste management through “green supply chain way”: Indian “brickfield” perspective Abstract: Agricultural/biomass waste is available everywhere, and the waste biomass is a harmful for the environment; hence, it should be processed and used for mankind purposes. Increasing logistical needs attracting more vehicles on road, which result in more production progressively, and increasing needs of industrialization globally, pollution is increasing day by day. The discharge of chemical compounds containing gaseous chlorine or bromine from industries, vehicles, and other human activities such as burning the biomass/agricultural wastes impacts and depletes the ozone layer gradually, which is harmful for all kind of lives. Various harmful gases and particles like CO, CO2, SO2, and black carbon are also emitted into the atmosphere, resulting in melting of glaciers, causing acid rain and various kinds of diseases like skin diseases, respiratory diseases, breathing problems, cancer etc. To reduce such pollution, biomass wastes must be processed through proper channels so as to use it to create wealth and protect environment at a microlevel for sustainability. This research found that the waste can become an economic haste through green supply chain way, which provides the opportunity to become an entrepreneur through waste management and protecting environment from harmful gases and smoke that causes various diseases and greenhouse effect. Research proposed the biomass briquetting plant, which processes biomass to make it in cylindrical briquettes that could be a replacement of coal. These briquettes are very useful in various industries, brickfields, and hotels/restaurants. These briquettes are renewable source of energy, environment friendly, easy accessibility and available, cheaper, pollution-free and have a good calorific value, and hygienic to manage. It is also free from toxic gases and produces less ash content as compared to black coal. This is the original research that was carried out along with a new plant start-up in the district of Farrukhabad, Uttar Pradesh, India, on biomass/agricultural waste management and utilizing the output in brickfields (brick kilns – ईंट भट्ठा) and industries. This study has focused much on agricultural wastes; however, it provides the roadmap for future studies on wastes management irrespective of the geography. Keywords: biomass, waste management, agricultural waste, environment, green supply chain, waste to wealth, brickfield, brick kilns, atmosphere, ozone layer depletion, acid rain, harmful gases

Jagdeep Singh, PAHER University, Udaipur, Rajasthan, India Mamta Kumari, Junagadh Agricultural University, Amreli, Gujarat, India https://doi.org/10.1515/9783110628593-009

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9.1 Introduction While everyone is talking about environment protection, waste management plays an important role in it. It is well known that due to greenhouse effect, glaciers are melting day by day and the overall temperature is also increasing. Because of industrialization and farmers burning the agricultural wastes, various harmful gases and smoke is released in the environment and depleting ozone layer & making environment polluted. As a result, we could see acid rain, various kinds of diseases like skin diseases, respiratory diseases, breathing problems, cancer etc. Now, to overcome on these issues, wastes must be processed through proper channels and processes for further use to create wealth, protect environment at a micro-level for sustainability.

9.1.1 What is waste? Waste may be defined as “anything that does not create value.” Wastes are available everywhere, and only we need to understand and make it useful. We are describing here the category wise wastes availability in India as follows:

9.1.2 Categorization of various wastes There are different types of wastes that could be categorized as below: – Various kind of solid wastes – Electronic wastes – Various kinds of liquid wastes – Various kinds of plastic wastes – Various kinds of metal wastes – Many other wastes such as nuclear wastes and so on. Above wastes could be further categorized as wet wastes and dry wastes. Wet waste

Dry waste

Flowers, fruits waste, juice peels, and house trees waste

Waste from packaging material of any kinds

All kind of kitchen wastes related to and from eatable items

Cardboard and cartons, paper and plastic etc.

Sanitary wastes

Waste from glass and metals

Waste from fruit and vegetable shops

Rags, ashes, and rubber etc.

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(continued ) Wet waste

Dry waste

Waste from restaurants and food companies

Pouches, tetra packs, and sachets etc.

All kinds of dry leaves or waste plants etc.

Medicinal wastes

All kinds of biomass wastes that are recyclable

Rejected and useless electronic items, clothing, furniture and equipment

9.1.3 Waste management As name suggests, managing the waste, that is, waste should be managed in such a way that it protects the environment and creates wealth for sustainability. Solid waste management (SWM) is a generally defined as the application of techniques to make sure a systematic implementation of a range of functions such as accumulating, handling, transporting, processing, and treatment and disposal of solid waste. Waste management system (WMS) must be environment friendly, cost-effectively sustainable and recognition in human society.

9.1.4 Disposal of waste Various practices have been adopted to dispose waste from the population; however, these practices are not good and not certified. Removal and dumping of waste is a severe problem and should be taken care very seriously to protect human society across the world. Removal of waste from its generation site and disposing it out of sight away is a general practice; however, it does not solve the problem. This process of waste disposal increases the problems when it goes beyond the control of everyone. This could result in various types of pollutions such as soil, water, and air pollution etc. along with other concerns like health hazards, unpleasant surroundings etc. Hence waste must be handled properly to avoid various kinds of pollution.

9.2 Literature review The majority of businesses define waste as “anything that does not create value” (BSR, 2010). The burning and digesting the agricultural wastes aerobically in the land itself, leads to air pollution and also releases unbearable and greenhouse gases. Chemicals used in fertilizers are harmful for soil and health and these fertilizers are not only expensive but also continue accumulating in crops, soil, which undergo

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biomagnification leading to various health problems (Lokeshwari and Swamy, 2010). Waste is unavoidable aspect everywhere. We waste our time in some form or others; similarly, there is different kind of wastes out of which there is an agricultural waste. Plastic wastes are also one of the challenges that create opportunities to the societies for innovation and research apart from of their sustainability awareness and technological advances. This paper reviewed the recent progress in the recycling and recovery of the plastic solid wastes. An exceptional importance is given on waste generated from polyolefin sources, which make up a great proportion of our daily life consisting of recycled plastic products. It was concluded from this paper that lots of plastic solid waste of tertiary and quaternary treatment schemes come into view to be robust and worthy of additional investigation (Al-Salem et al., 2009). To dispose the agriculture waste, farmers started burning it and digest it aerobically in the land itself, which leads to air pollution, release of unbearable and greenhouse gases. This study conducted on agricultural waste management through vermin-composting. This study provides bioremedial recycling technology for agricultural waste, which meets a part of agricultural input and also conserves the environment (Lokeshwari and Swamy, 2010). (Agarwal et al., 2015) studied the existing practices related to a various kinds of waste management initiatives that are conducted for the welfare of human society in India. This paper found and proposed the possibility of advancement in the area of various waste management techniques. Key roles of formal sector are also discussed that is engaged in waste management. Increased population and superior lifestyle of individuals result in amplified creation of various kinds of wet and solid wastes in urban areas. It is nowhere different in rural areas, that is, similar kind of wastes created in rural areas as well. There is a visible dissimilarity between the solid waste from rural and urban areas, but due to rising urbanization and fast adoption of “one-time use” concept, express exchanges and communication, the gap between the rural and urban is diminishing (Agarwal et al., 2015). (Bhattacharya et al., 2018) concluded that the plastic consumption is constantly increasing due to urbanization and the global demand is also growing day by day. Although the increasing rates of plastic production project positively for Indian businesses and the economy, irrational waste management practices are leading adverse environment effects. A systematic, scientific, and efficient planning is required for a better enduse application that could take the plastic waste management with sustainable solutions and alternatives. (Nguyen et al., 2019) analyzed the techniques and the grounding steps for establishment of rice husk ash which is most widely used and applied agro waste in engineering fields. Use of agro waste ashes has been considered by many researchers in different engineering fields. Various applications are considered including wastewater treatment, additive for cement industry, and alkaliactivated materials, as an additive for production of glass, silicate, pure silica, silicon carbide, refractory materials, as filler in thermoplastics and rubbers, reinforcing agent, and adsorbent in polymer composites and epoxy thermos table polymers, for producing advanced materials such as silicon nitrite (Si3N4) and magnesium silicide (Mg2Si),

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and many more. (Upadhyay and Harshwardhan, 2017) studied conversion of biomass and agricultural wastes. Agricultural substances are those substances that are produced on earth with the change of seasons. The wastes generated from crops have good potential to transform into energy in related energy sector. The wastes produced from animal waste or from crop residues called biomass has an interdependent relationship with ecosystem from production to disposal and has physicochemical properties. This research agreed to enhance the economic values of the agricultural waste into useful products. (Agarwal et al., 2015) Suggested to achieve socioeconomic and environmental objectives along with financial sustainability in the area of waste management whether it is solid or wet waste management. It also carefully evaluated the strengths and weaknesses of the municipal corporation and the community so that an efficient system for waste management could be evolved. (Veeresh et al., 2011) Studied to conclude the extent of agricultural biowaste generation and utilization technologies and also the status of vermin technology practised in Tamil-Nadu. Majority of the farmers were found practicing conventional biowaste management but were aware of vermin technology. Waste management is one of the critical emerging issues not only in India but across the world. The reason is that a large amount of waste that is being generated every day, and the impact of such waste is hazardous for the environment and human beings as well as other living beings. For the speedy increasing volume of the vehicles, there is a parallel need to increase waste management initiatives by governments as well as private corporate players across the world. There is a need of modern facilities to reuse and recycle waste materials like solvents, metal, batteries, plastics, and so on. This article reveals the solid waste (generated from end-of-life vehicles) management strategies adopted by automobile industry to minimize waste (Sharma et al., 2016). Vehicle recycling, component reuse, and metal recovery are important aspects of vehicle manufacturers, suppliers, governments, material recyclers, dismantlers, and shredders. The highly efficient car recycling infrastructure serves to divert materials from landfill and recycle metals to a high-volume consumer product and serves as an alternative source of low-cost components for repair of vehicles that might otherwise be taken out of service (Paul, 2009).

9.3 Methodology for research and project (plant) setup The methodology used was very simple – defining the importance of the study, setting up the objectives, defining the approach used for the research as well as project (Plant) setup

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(a.) Importance of the study and the project This study and the project are very important as the study helps to find the problems in deep and the project (Plant) provides the solution to the problems. During the study, it was found that 1. Technology is not available or accessible to common farmers. This results in delay in crop harvesting, and hence loss of some percentage of crops, for example, wheat, mustard, etc. 2. Farmers are burning the agricultural wastes (stalk) or putting wastes aside in a field to use as compost after decomposition. Farmers burn their crop residues/ wastes to clear the field easily and quickly at cheaper cost, but it kills weeds and pests that leads to loss of soil nutrients and increases air pollution. It affects human health as various harmful gases produced during burning process. If farmers use this decomposed waste as fertilizer, it is not much effective, and hence farmers still need to use chemical fertilizers such as urea, potash, nitrogen, etc. If farmers sell it, they hardly get Rs 3.5–5/sq feet, which is Rs 400–600 per trolley (~ 120 sq feet). If farmers sell agricultural wastes (stalk) to briquette manufacturer, they get Rs 100–170 per quintal (100 kg) which is about 3–5 times more. 3. Brickfields (brick kilns) use black coal that generates huge pollution due to smoke, which emits harmful gases such as CO, CO2, SO2, black carbon, which adversely affect soil, plants, animals, and people in its surroundings. In addition, coal is very expensive (Rs 10 K–13 K per metric ton) in comparison to biomass/agricultural briquettes (Rs 5 K–5.5 K per metric ton). The above problems attracted to start a project of briquette manufacturing plant to empower rural economy by way of “waste to economic haste”. This plant uses bagasse, press mud, mustard stalk, maize stalk, maize waste, leaf/branch, coffee husk, saw dust, cotton stalk, soybeans husk, groundnut shells, paddy straw, jute waste, tea waste, caster seed shells, betel nut shells, coir pith, bamboo waste, cotton stalks, cattle straw, mustard husk, coconut wastes, and so on, to make briquettes. It was decided to work for farmers and rural people to strengthen their economic state by processing their agricultural waste, and hence this waste management project was started. Vision was set as below: To empower the rural economy through Agricultural waste management and technology and create value to all stake holders. (b.) Objectives Objectives of the research project were defined as below: 1. Learning the current practices connected to SWM (What is the framework?) 2. Processing biomass wastes in such a way to protect environment – green supply chain way (What is green supply chain framework in biomass waste management?) 3. To start a briquette manufacturing plant (How to start a briquetting plant?).

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4. Waste to economic haste: to create wealth from the agricultural/biomass waste and protect environment (results and financials). 5. Identify the future challenges in waste management (briquetting plant) setup (c.) Approach for project (plant) setup There were five phases in the study until successful implementation of the project. Phase-1: research phase Phase-2: resources management phase Phase-3: project implementation and go-live phase Phase-4: mass production and on-job training phase Phase-5: marketing and sales and financials Phase-1: research phase In this phase, concept discussion and brainstorming was done and based on the brainstorming sessions and discussions, questionnaire was prepared to collect the data. Data analysis was carried out in the MS excel, graphs, and charts were created based on the data and finally framework of SWM prepared. This study tried to explore the green supply chain management and its definition. Based on the literature reviews and the outcome of the analysis of the collected data, a green supply chain framework was also prepared, which is very important for this chapter. The things discussed in this phase are methodology, data collection, scope of the research, Gantt chart, briquette plant suppliers, data analysis, frameworks of SWM, and green supply chain framework for agricultural waste management. Scope of the research: Though the project implemented in district Farrukhabad, Uttar Pradesh, India, however it could be implemented anywhere whether it is India or any other country where similar kind of wastes available. The scope and focus of this study is agricultural/biomass waste. Hence, the study will be focusing on agricultural/ biomass waste management only.

9.3.1 Data collection Project can be started by anyone and it does not require much technical knowledge; however, person should be careful and learn each and every aspect of the project. First and foremost, it is required to know the market whether output will be sold or not and who will be the buyers/customers. Based on the literature reviews, it was clear that there are buyers who use these briquettes such as industries, brick kilns, and hotels/restaurants, and it was decided to consider only two types of customer’s brick kilns and hotels/restaurants. Industries are far from the focal point where the study was conducted. After questionnaire prepared, data collection was done through questionnaire via F2F interviews from hotels and brickfields (kilns) owners. The radius was covered 30 km from

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the place where the project to be installed. Total customers covered were 60 as follows: Sample size: a.) Hotels – 20 b.) Brickfields (brick kilns) – 40 Project plan (Gantt chart): This was a systematic and step-by-step planning and execution of various activities of the project taken for project finalization (discussion) until order delivery through various other activities as shown in the Gantt chart.

9.3.2 Major briquette machine (plant) suppliers in India There are many briquette making plant suppliers in India. Discussion with some of them are as follows: – Ecostant India Private Limited, Ludhiana, Punjab – Radhe Engineering, Rajkot, Gujarat – Ronak Engineering, Rajkot, Gujarat Based on the quote evaluation and the feasibility study, Ecostan India was finalized.

9.3.3 Analysis The study was conducted at Kanasi of Farrukhabad district, Uttar Pradesh, India. Framework of SWM: Supply chain flows are clear (see Figure 9.5) from the framework of the raw material to the delivery, to the final customer through waste collection, processing, storing/packing/dispatch. This framework has shown various kinds of sources of wastes such as agricultural, sugar factory, farming, forest and so on. Also, the framework shows the automotive waste, engineering waste, and heavy machinery waste. There are various kinds of mechanism to process these wastes to make it useful to reuse it. There are other processes associated with the framework such as information and communication flow, financial flow, and material flow.

9.3.4 Define Green supply chain management The green supply chain management (GSCM) may be defined as integrating environmental thinking into supply-chain management, including product design, material sourcing and selection, manufacturing processes, delivery of the final product as well as end-of-life management of the product after its useful life.

Activity

Figure 9.1: Project plan (Gantt chart).

Order delivery started to the customers

On job training to all available people - labour and staff

Go-live and 1st production

82.5 kVA generator installation

Machine delivery and installation

Press mud supply started from our own contract from kaimganj sugar mill

Mastard plant stalk (Biomass) supply started

Electricity connection and other legal formalities

MSME registration online

Called raw material/ biomass waste suppliers and farmers and discussed & negotiated/fixed the prices

Construction of the base area as per specified by the bruquette plant supplier (As per documents received)

Construction of the plant started

Quotation negotiation, supplier finalisation and releases PO for plant supply

Quotation from the briquette machine (plant) suppliers

Market research (visit to the int bhattas & hotels)

Visit of existing briquette plants

Site/location decision

Idea (Concept) discussion

1/18 1/19 1/20 1/21 1/22 1/23 1/24 1/25 1/26 1/27 1/28 1/29 3/25 3/26 3/27 3/28 3/29 3/30 3/31 4/1 4/2 4/3 4/4 4/5 4/6 4/7 4/8

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Table 9.1: The fuel preferences in the brick kilns. Fuel used in brick kilns Pure coal

Pure biomass briquettes (coal is used only to ignite first time)

Wood directly with coal







Coal and biomass briquettes combination

Mustard plant stalk, wood and coal combined

All things based on availability







Fuel used in Int Bhattas: Pure coal 23%

Fuel used in Int Bhattas: Pure biomass briquettes (coal is used only to ignite 1st time)

26%

Fuel used in Int Bhattas: Wood directly with coal 6%

Fuel used in Int Bhattas: Coal and biomass briquettes combination

0% 10%

Fuel used in Int Bhattas: Mustard plant stalk, wood & coal combined Fuel used in Int Bhattas: All things based on availability

35%

Figure 9.2: Type of fuel used in brick kilns (int bhattas).

Table 9.2: The Preferences of briquettes type in brick kilns.

Briquette type preferred in brickfields (brick kilns): Pure Mustard Plant Stalk

Pure bagasse (sugarcane stalk after crushing to extract cane juice)

Pure press mud (Ladhoi)

Bagasse/mustard plant stalk/saw dust and press mud combination

Briquettes are not preferred/ used at all











In this chapter, a complete activity chart (Gantt Chart) is provided so that the reader could digest it easily. For the details, please refer Figure 9.1. The data of various types of fuels, used in brick kilns, is mentioned in the table 9.1. During the data analysis, it was found that maximum number of brick kilns (~35%) prefer to use the combination of black coal and biomass briquettes as

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0% Briquette type preferred in Int Bhattas: Pure mustard plant stalk 19% Briquette type preferred in Int Bhattas: Pure bagasse (Sugar Cane stalk after crushing to extract cane juice)

35% 10%

Briquette type preferred in Int Bhattas: Pure press mud (Ladhoi) Briquette type preferred in Int Bhattas: Bagasse/ mastard plant stalk/saw dust and press mud combination

36%

Briquette type preferred in Int Bhattas: Briquettes are not preffered/used at all

Figure 9.3: Briquette-type preference.

14

Fuel type

6 3

2 1

No of briquette suppliers

No of coal suppliers

Wood suppliers

Mastard plant stalk suppliers (local farmers)

Mastard plant stalk purchased directly from farmers

Figure 9.4: Average number of suppliers per int bhatta “fuel type wise”.

mentioned in figure 9.2. There is a huge scope to improve further so that burning of black coal or direct biomass waste/wood could be reduced to protect environment. It is clearly defined as shown in Figure 9.6 that how green supply chain framework is useful for creating wealth and protecting the environment. It helps to create wealth from waste and protects the environment by reducing toxic gases in the atmosphere. Real examples are taken from current plant, which helps farmers and brickfields and chemical/ceramic industries. It helps to reduce the cost for brickfield’s owners, and hence produce good bricks at cheaper price and avoids usage of coal by 90%. Similarly, it uses for running boilers in the ceramic and chemical industries. This research shows that briquettes could be made from any agricultural wastes however all are not preferred by the brick kilns. The preferences of the briquettes type is given in the Figure 9.3 as above in district Farrukhabad, UP however it depends on region to region. In last few years, the use of biomass briquettes has

Retailer

Packing & dispatch

Retailer

Finance flow

Customer -6

Customer -5

Customer -4

Customer -3

Customer -2

Customer -1

Finance flow

Output (Finish product)

Whole seller

Compost / vermicompost

Briquettes packing & dispatch

Information / Communication

Process (Raw material)

Scrap dealer/vendor

Dry solid waste processing plant

Wet solid waste processing plant

Bio/agri. waste processing plant

Waste processing plants-small or big

Information / Communication

Input (Raw material flow)

Any others

Heavy machinery

Engineering

Automotive

Solid waste (Not Easy Recyclable)

Solid waste which cannot be briquetted

Forest

Farming wastes

Sugar factory

Agricultural waste

Solid waste ( Easy Recyclable)

Figure 9.5: Framework of solid waste management.

SOURCES OF WASTE SUPPLY

168 Jagdeep Singh, Mamta Kumari

Cash flow

Waste flow

Win-win situation between farmer and briquettes making plant as waste gets paid

Cash Flow

Briquette making plant

Cash flow

Dealer having agricultural waste

Cash flow Waste Waste flow flow

Farmer having agricultural waste

Win-win situation between brick field owner and briquette making plant as coal price is more than double of briquettes

Cash Flow

Biomass briquettes & pellets

Figure 9.6: Green supply chain framework for biomass/agricultural waste management.

Farmers could be able to increase the produce

Farmers could harvest on time to reduce wastes & costs

A group of farmers could buy agricultural equipments

Economically enriched farmer

Steam boiler

Steam

Bricks

Use of 100% coal (black) as fuel - more smoke & More Ash (~20% – 30%), Harmful gases like Co, CO2, SO2, and Black Carbon emission

Brick field (Int Bhatta)

Use of biomass briquettes with coal as fuel - less smoke emission - no or very less harmful gases, less ash (5% – 7%), No carbon back emission

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increased and hence the increment in the briquettes suppliers which is shown in figure 9.4 as above. Phase-2: Resource management phase a) Resources management phase In this phase, it was needed to arrange all the resources related to a complete supply chain, and hence brainstorming session was conducted again and jotted down all possible requirements that were finalized as below: – Machine: Briquette making plant and 82.5 kVA generator – It was discussed with three suppliers based on preliminary research for both items. Received quotation over email, studied/evaluated, analyzed and negotiated for finalization. Both items confirmed by the suppliers at the final desired and negotiated price, and hence PO was issued to the respective suppliers. As per agreement, machine to be delivered after 30 days from the final PO and the generator within 15 days as and when required. Price for briquette making plant for 70 mm briquette output – Rs 14,000,00 includes four months consumable supply. If you purchase 90 mm machine, it costs Rs 17,00, 000–Rs 21,50,000 depending upon company and model etc. Price for 82.5 kVA and 125 kVA silent (closed body) generator are Rs 6,00,000 and Rs 7,50,000, respectively. – Material: Raw material, that is, waste materials which were mustard plant stalk, sugarcane bagasse and press mud. Press mud and bagasse were arranged through a contract with Kaimganj sugar mill. For mustard plant stalk, it was discussed and arranged from local farmers and suppliers/dealers and finalized the rates. Cash on delivery – Rs. 140/Quintal (100 kg) and payment after 1–2 months – Rs. 170 /quintal – People (Worker/Labor):. Casual worker – Daily wage – Rs 300 per 10 hours Supervisor – Rs 12,000 per month Total people required – 6 people per 10 hours shift (Casual labour – 5, Supervisor – 1) – Factory’s building Construction and other required arrangements as per briquette plant supplier – Factory includes warehouse to keep the produced material. Construction cost comes about Rs 10 Lakh (1 million INR) including all facilities such as machine hall, output and storage hall, waste material process hall, water tank for cooling the machine, boring and motor tap, hand pump for water, security room, and generator room etc. – Legal requirements were completed such as micro, small and medium enterprise (MSME) registration and conversion of infertile land into commercial land and application for electricity connection.

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– GST registration was required and hence it was also done – Finish product upon selling should collect 5% GST. Regular GST filing to be done to avoid penalty charges. b.) How to start a briquette manufacturing project/plant? This project can be started by anyone and does not require much technical knowledge; however, person should be careful and learn each and every aspect of the project. There are few things that are important for sustainability: 1. Market/customer: whether product will be sold easily or not. 2. Raw material (biomass) availability in your area: Identify the biomass wastes in your area and its continuous availability. 3. Facility/plant location: Plant should be near the market/customers to minimize the transportation cost and enhance the service level. 4. Electricity (commercial connection)/DGSET availability 5. Labor availability

9.3.5 Biomass waste management technique Biomass waste management technique could be anything that process wastes into usable forms. This study focuses on briquettes manufacturing plant. It is an ecofriendly technology that converts miscellaneous residues like industrial (press mud, bagasse, etc.) or agriculture waste (stalk, maize stalk, maize waste, leaf/ branch, coffee husk, saw dust, cotton stalk etc.) into solid cylindrical blocks, which is generally referred as biofuel. These cylindrical briquettes are made with high mechanical pressure as shown in Figure 9.7. This technology does not require any binding material or chemical to bind the waste to convert into briquettes, and hence this technology may be called as binder less technology. Biomass briquettes are substitute to nonrenewable vestige fuels and can be used in several manufacturing industries like boilers, brickfields (kilns), furnaces, and so on. The basic function of this briquetting machine is to reduce the size of bulk density raw material into compact form to increase its calorific value. The size and shape of the briquetting machine depends on its output size. Usually, the size of the briquettes varies from 40 mm to 100 mm based on the usage and production. For brickfields (kilns), maximum size used is 70 mm and for furnaces and boilers, any size could be used as specified above. Production capacity of any briquetting machine depends on feed stalks (raw material) and the shape and size of the output. Normally, the production capacity varies from 200 kg/h to 2,500 kg/h as it depends on various raw materials used.

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Sawdust briquette

MDF briquette

Wood shavings / Sawdust mixture

Pine briquette

Shredded straw briquette

Mahogany briquette

Shredded paper briquette

Cardboard briquette

Figure 9.7: Biomass waste management plant and products (a) plant, (b) burning briquettes, and (c) products.

9.3.6 Types of briquette machines Normally, the type of briquetting machine depends on the input material and the size of output. There are various types of briquetting machines as discussed below: Pellet making machine – The size of pellet is normally 10 mm–20 mm Briquette making machine – The size of briquette is normally 40 mm–100 mm. Biomass/agriculture waste briquetting machine is shown in Figure 9.7. It also shows various types of samples of briquettes with a burning sample. Benefits: Benefits are explained as follows: (i)ߓMore efficient – Its heating value (calorific value, Please refer Table 9.3 of calorific values of various biomass wastes) is around 3000–4500. – Briquettes produce relatively more intense. – Briquettes have a higher practical thermal. – Briquettes have much lower ash content (2–10% compare to 20–40% in coal).

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– Briquettes are 40% more efficient and hotter and longer lasting than firewood. (ii)ߓSmokeless or very much low smoke to protect the environment – Briquettes create no smoke or negligible smoke, soot, or carbon deposits. – Briquettes produce no or very little fly ash after burn – depends on raw material used. – Briquettes do not emit gases or any toxic chemicals such as sulphur etc. (iii)ߓEasy to transport – Biomass/agricultural wastes are bulkier in volume as compacted to briquettes. – Briquettes volume could be upto 10 times lower than raw material (biomass waste), which makes it easy to store and handle. (iv)ߓRenewable – Briquettes make use of organic materials that are common and renewable. Hence, this project supports “Go Green” initiative and “Green Supply Chain Management (GSCM).” (v)ߓEasy availability of biomass (agricultural waste) – Agricultural wastes are available everywhere at cheaper or no costs. Examples of agricultural wastes are plant wastes, trees’ waste wood, sawdust, wood shavings, shredded straw, shredded papers, MDF, pine, bagasse, sugar mill’s mill mud, and so on. (vi)ߓCheaper – Cheaper raw material, and hence cheaper total production cost. Also, the cost of project is not very high as compared to the other industries, and it is easy to install and run efficiently and profitably. Use (application) of briquettes: Usually briquettes are known as white coal and used in many industries such as follows: .

Brick kilns

.

Rubber industry

.

Food processing units

.

Ceramic units

.

Textile mills

.

Vegetables plant

.

Paper manufacturing Plants

.

Dairy and milk plants

.

Chemical factory

Major advantages to set up a briquetting plant as follows: – Create wealth out of agricultural waste – Its cost-effectiveness as compared to black coal and hence highly demanded – Easy availability of raw material/waste material – No marketing is required after 1 year of plant setup due to high demand

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Table 9.3: Calorific value of raw material and fuel material. Calorific value of raw materials

Calorific value of fuel materials

Raw materials Approx

Raw materials Approx

K Cal / Kg

K Cal / Kg

Bark (wood)



Sugar mill waste



Bagasse (sugarcane)



Sugarcane trash



Bamboo dust



Wheat straw



Cotton stalk



Arhar (toor) stalk



Coir pitch



Saw dust



Maize stalks



Heavy furnace oil



Pine niddles



Kerosene



Rice husk



Diesel



Rice straw



LPG



Sar khanda grass



Coal Grade ‘b’



Coffee husk



Coal Grade ‘c’



Groundnut shell



Firewood



Castor seed shell



Charcoal



Jute waste



Calorific value of briquette “white coal”



Mustard husk



Source: Radhe Engineering

– Breakeven is very less as it is one of the good project in terms of return on investment (ROI) – Job creation and social work by protecting environment – Tax benefits – income tax is free for first five years Phase-3: Project implementation and go-live All arrangements were done, building was almost constructed during March 2018 and machine base was ready; therefore, machine was called and installed. It took 7–10 days to cure. Meanwhile machine fitting was done by the technician sent by Ecostan India. After everything was set, machine testing was done on April 7, 2018. It was OK tested for go-live. Trail production was carried out and finally got nod from supplier’s technician for mass production.

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Phase-4: Mass production and on-job training Project was set and ready for mass production. Mass production started along with the training of all the staffs/labors. Customers (brickfield owners) were called for inauguration and to see the sample of the output briquettes. Sample checked and OKAYED by all the customers available. First delivery was done on April 8, 2018, and in full swing production (2-shift operation – 10 hours each shift) started from April 11, 2018. That is how this waste management project (plant) started.

9.4 Results and financials discussion: wealth from waste The results of the research were found as below: i.) The demand of briquettes by hotels is very less as compared to brickfield, and hence hotels were ignored at initial level only. ii.) Only 31 responses were received out of 40. iii.) 26% brickfields found using pure coal; however, remaining 74% were using either briquettes or wood or agricultural waste stalk directly along with black coal. (Ref: Graphs-1). iv.) The research found a huge scope in waste management area. The above results were confirmed by the actual project’s financial situation as follows: The analysis of the ROI and other financials was done after plant closed during the June end 2018. The current financial situation is explained as shown in Figure 9.8 in the conclusion section, which shows that it is one of the good project and economically viable. It creates extra revenue for farmers, protects environment, help brickfield owners to produces bricks at lower cost. Moreover, It helps society by creating jobs, getting good quality bricks at cheaper price from brick Kilns and the key is environment protection through green supply chain way.

9.5 Recommendation This study clearly shows that this kind of waste management projects must be started and supported by individuals, corporate as well as Central and State Governments so that we could create a good environment and help to boost rural economy by waste management through a green supply chain way.

10,00,000 30,58,000

Building construction cost

Grand total cost of plant establishment

Figure 9.8: Current financial situation of the project.

Total turnover per day (In INR) Turnover per month (In INR) - 22 Days working

525

Sale rate (EXW)

15,01,500

68,250

130

2

No of shifts - 2

Total production per day (in Kuntal)

65

*Production per shift (10 hours) in Kuntal (1 Kuntal

Production & operation

14,08,000 6,50,000

70,000 38,000

13,00,000

Price (INR)

Total Generator - 82.5 KVA (Cummins)

3 Months consumables Plant transportation, unloading and installation

Complete plant cost

Particular

Plant establishment costs (INR)

Energy costs and other over heads (By electricity) Total cost of production per Kuntal

Annual turnover (7 months) - In INR Annual revenue (7 months) - In INR

Annual production costs (7 months) - In INR

Annual productive months (Plant works only 7 month) - Due to rain and also depends on Int Bhattas (Normally, brick fields (Int Bhattas) function from Nov to Jun (Note:Plant can run 12

Annual costs, turnover and revenue

Hence total working capital per month-

1,05,10,500 48,76,410

56,34,090

7

3,68,225

2,94,580

0 78 103

Energy costs and other over heads (By Genset)

Total production cost per month 22 days 2 Shifts (In Rs.)

21

Labour cost per Kuntal (1 Supervisor+5 L)

2,860

82

Average raw material cost per month (Including 8% wastage & dry)-In INR

Total production per month per 2 shift for 22 days (In Kuntal)

150

Raw material per Kuntal-In INR (payments after 30–60 days)

Input costs (INR) (Note: 1 Kuntal = 100KG)

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9.6 Conclusion This study gives a new dimension of thinking and creating wealth out of waste. This study also offers deeper understanding about the various kinds of wastes and way of its management. This study has given a complete project plan so that anyone could start the project without any problems. Start a project and contribute to collect and process the agricultural wastes (making biomass coal/briquettes used as an option of black coal) to make it economic haste for farmers and to provide it to brickfields (Brick Kilns) who use it instead of coal (For Brick baking – ईंट पकाना / ईंट सेंकना). It is very cheap in comparison to black coal and hence bricks produced are of good quality at a cheaper rate and also protects the environment from various harmful gases that are emitted while burning coal. It is clear from the entire episode that there was a major demand from brickfield side and very less demand of briquettes from hotel side. Since, brick kilns are major pollution creators in rural India, and hence this study recommends that brickfields (brick kilns) must use white coal (briquettes) for two major reasons: 1. It avoids pollution. 2. It is cheaper. This is not limited to brickfields only, white coal (briquettes) must be used by all industries, wherever feasible to use, for many reasons as explained during the study in the benefit section. Someone rightly said – Where is a will, there is a way.

Bibliography Agarwal R., Chaudhary M., and Singh J. (2015). Waste management initiatives in india for human well being. European Scientific Journal, June 2015 /SPECIAL/ edition, 105–127. Al-Salem S.M., Lettieri P., and Baeyens J. (2009). Recycling and recovery routes of plastic solid waste (PSW): A review. Waste Management (Elsevier), 29, 2625–2643. Bhattacharya R.R., Chandrasekhar K., Deepthi M.V., and Roy P. (2018). Challenges and opportunities: Plastic waste management in India. New Delhi: The Energy and Resources Institute (TERI). BSR. (2010). Business for Social Responsibility. “The New Frontier in Sustainability”, The Business Opportunity in Tackling Sustainable Consumption. Effective Utilization of Agricultural Waste – Review Paper. (2017). International Journal of Engineering Research & Technology (IJERT), 6(9), 52–59. Foundation W.R. (1996). So what is integrated waste management? Journal of the World Resource Foundation, 49. Lokeshwari M. and Swamy C.N. (2010). Waste to wealth – agriculture solid waste management study. Pollution Research (EM International), 29(3), 129–133. Nguyen H., Moghadam M.J., and Moayedi H. (May 2019). Agricultural wastes preparation, management, and applications in civil engineering: a review. Journal of Material Cycles and Waste Management.

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Paul R. (2009). End-of-life management of waste automotive materials and efforts to improve sustainability in North America. Sustainable Development and Planning, 4(2), 853–861. Sharma S., Sharma A., Sharma A., and Srivastava P. (2016). Automobile Waste and Its Management – Review Article. Research Journal of Chemical and Environmental Sciences 4(2), 01–07. Upadhyay K. and Harshwardhan K. (2017). Effective utilization of agricultural waste – review paper. International Journal of Engineering Research & Technology (IJERT), 6(9), 52–59. Veeresh S.J., Narayana J., and Teixeira da Silva J.A. (2011). Agricultural bio-waste management in the bhadrawathi taluk of karnataka state. India: Global Science Books.

Shashikant Rai, Saurabh Mishra, Ram Mohan Mishra

10 Management of quality in perishable food supply chain by using Internet of things (IOT): a novel approach Abstract: This chapter explores the use of Internet of things (IOT) technology in the supply chain management specific to perishable food items. The chapter explores the effect of IOT technology to solve the inefficiency problems of supply chain. The past and present literature mainly focuses on the use of IOT technology to limited analytical models and empirical studies. The studies reviewed mainly focuses on the implementation of IOT to manufacturing systems. The further chapter also focuses on the use of IOT tech to the perishable supply chain with few identified areas. Keywords: Internet of things (IOT), supply chain management, perishable food, virtualization

10.1 Introduction The report published by General Administration of Quality Supervision, Inspection and Quarantine (AQSIQ) Statistics Report, in the year 2013, indicates an increase in demand for Salmon (kind of fish) from 74 million in 2003 to 238.8 million. The advent of urbanization had also greatly affected the eating habits of the people residing in these urban centers. Now there is more concern for better food quality with minimum loss of nutrition in the transit. In China, the demand for Salmon (kind of fish) has increased from 74 million to 238.8 million between 2003 and 2013 as indicated by AQSIQ. The great interest in nourishment has increased the ventures in the development, preparation, and transportation of these perishable foods. Mostly these activities regarding perishable food supply chain are handled through supply chain for perishable food. To meet the demand for present consumers across the world, business ventures are inclined to radically reevaluate the associations, individuals, exercises, and large data involved in transitory of these items. Supply chain management is a powerful tool for business relation and its effectiveness and efficiencies can affect the revenue to a large extent. This is developing more interest

Shashikant Rai, Ram Mohan Mishra, Department of Management Studies, Indian Institute of Information Technology Allahabad, Uttar Pradesh, India Saurabh Mishra, School of Management Studies, Motilal Nehru National Institute of Technology Allahabad, Uttar Pradesh, India https://doi.org/10.1515/9783110628593-010

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in SCPF, which is known as farm to fork successor. Such an efficient supply chain will not only meet-manage the gigantic demand and market share, respectively, but will further affect every activity involved that will affect the process, inspection, packaging, warehousing, transportation, distribution, marketing, and farming techniques. The challenges put forth as discussed above is forcing toward smarter supply chain methods. These smart methods will help in dealing with the unpredictable nature of the supply chain with a minimum loss of nutrition at the end of perishable supply chains.

10.1.1 Internet of things Internet of things (IOT) was introduced in 1999 as a system of production and living smarter. Essentially, it is the idea of connecting any device (given that it has an on/ off switch) to the Internet and to other connected devices. It is a gargantuan network of connected things and people – all of which collect and share data about the way they are used and about the environment around them. There are three different tiers to the IOT pyramid: the perception layer, the network layer, and the application layer. The perception layer consists of temperature and humidity sensors (among others), radio frequency identification (RFID) readers and tags, GPS, camera and other sensing terminals. Moving on, the elements that comprise the network layer are the Internet, network management systems and cloud computing platforms and wide networks. It is the centre of things, the hub, responsible for processing and transferring information obtained by the previous layer. Finally, the IOT application layer is the interface between the user and the IOT. It combines with the industry needs to realize the smart application of IOT.

10.1.2 Different layers in IOT architecture and how they work – Create: Sensor – Sensors attached to the system takes the data from the real-world information. However, in some systems, they collect the data and also formulate automated solutions accordingly. – Communicate: Network – Uses various networking devices to communicate the data collected from the sensors and putting it on the internet. – Aggregate: Integration – It is the most important functioning step as it aggregates and analysis all kinds of data collected from the sensors and some additional data so that the decision can be taken accordingly.

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– Analyze: Augmented intelligence – Under this section, raw data collected from downstream is analyzed so as to predict actionable insights from it. – Act: Augmented behavior – It uses the insight derived from IOT data to automatically make changes in human or machine behavior act.

10.1.3 Supply chain management Supply chain management (SCM) can be defined as the active management of supply chain activities to maximize customer value and achieve a sustainable competitive advantage. Supply chain firms have made conscious efforts to develop and run supply chains in the most effective and efficient method possible, and this is reflected in SCM practices. Supply chain activities cover everything from product development, sourcing, production, and logistics, as well as the information systems needed to coordinate these activities. The concept of SCM is based on two core ideas: 1. The combined effort of multiple organizations is represented in every product that reaches the user. This collection of organization is called the supply chain. 2. The view of the majority of supply chains has been very restricted in the past, with the organizations only paying attention to the going-ons within their “four walls.” Many businesses failed to comprehend, much less manage, said supply chains. The result was disjointed and often was ineffective supply chains.

10.1.4 Food wastage: India versus the world Around 14.5% of India’s populace do not have adequate nourishment and different substances for good wellbeing and condition – an incredible 194.4 million individuals. The reasons are fluctuating; however, the most noticeable of them and the one important to this exploration paper is nourishment wastage/lack. As per one’s estimation out of the all out nourishment created far and wide around 33% of the all out is squandered and its vast majority incorporates transitory nourishment things. In spite of the fact that a huge measure of this happens at the underlying phases of the production network (e.g., during harvest or postcollect periods), one of the significant guilty parties in this wonder is simply the store network. A large portion of the nourishment wastage happens during the stock and the utilization of the nourishment. Some the nourishment things are additionally

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squandered on the racks and in the storage facilities and cold stockpiling; this is basically because of the extremely high perishability of the things and exceptionally high creation of the items when contrasted with the interest in the market. Around 67 million tons of nourishment is squandered in India every year, adding up to a sum of 92,000 crore INR. Approximately, 21 million tons of wheat decays yearly in India, alongside different types of vegetable and natural product squander. As indicated by the Food Sustainability Index 2018, India positions second in the middle-income nations as far as maintainability of nourishment and gaining ground toward meeting ecological, cultural, and financial key performance indicators (KPIs). A KPI is a sort of execution estimating pointer. It fundamentally assesses the achievement of an association in different fields it is engaged with. This bears a great news and is proof that we are making positive strides toward enhancing our present production network, so as to avoid the wastage of transitory nourishment things. In any case, the procedures received so far can just accomplish such a great deal, and the need of great importance is to fuse IOT so as to plan a framework that can be remotely checked and is simpler to get to, while likewise being financially feasible and essentially implementable.

10.1.5 Food wastage and the food corporation of India Nowhere else is the rising and palpable trouble of excess food supplies and the lack of a proper supply chain management system felt than in the recent statistics released by the Food Corporation of India (FCI) and the economical cesspool it is in now. FCI procures rice and wheat through the public distribution system, and in the financial year 2019–20, their reserves have been running record high. In this situation, it has become increasingly difficult for the FCI to sell said stocks, causing them to pile up even more and eventually resulting in food wastage. Let us examine the reason behind this. Wheat stocks stood at 435.9 lakh metric tonnes as on August 1, 2019, while rice stocks stood at 328.9 lakh metric tonnes on the same date, according to data included in the Handbook of Statistics on the Indian Economy, released by the Reserve Bank of India last week. Taken together, stocks are coming close to FCI’s stated storage capacity. According to a Press Information Bureau statement in February, the total storage capacity available with FCI, Central Warehousing Corporation and state agencies stood at 851.54 lakh metric tonnes as of December 2018, which included 724.79 lakh metric tonnes in covered capacity. The more readily apparent conclusion to be drawn from this data is that the FCI simply needs more space in order to store the increasingly large amount of food here. However, that would be incorrect. Simply giving more storage space will not reduce food wastage.

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10.2 Problem statement The principle issue that this examination paper endeavors to handle is the perishability of nourishment things, and how it enhances the present production network with the assistance of the IOT, and how it can help us in this undertaking. In any case, we will endeavor to quickly give an expansive diagram of the current issue. Every year, around 40% of all nourishment delivered in India is squandered. This number sums up to associate with 21 million tons of nourishment. The purposes for this stunning number differ from lacking appropriation channels to unchecked stockpile request holes, to the monetary powerlessness of a huge scholarly people to buy nourishment, lastly to the short-lived nature of said nourishment items. Transitory nourishment if not refrigerated at the temperature of (4.4 °C) 40 F° or below or solidified at −17.8 °C (0 F°) or below, tend to go waste and may turn hazardous. Processed meat, fish, poultry, every single cooked food remains are certain products whose nourishment could be prolonged only with the help of the maintenance of preserving temperature. Refrigeration process helps to halt the bacterial growth, while solidification almost completely halts it. If not processed properly, two different groups of microscopic organisms, first one being pathogenic microbes that causes food borne diseases and second one being decay microorganisms that causes nourishment decay and resulting in a bad smell, taste and change in the appearance of food. Discussing the inventory network, usually these nourishment things land at our doorstep through the accompanying procedure: As definite in the above inventory network graph, the nourishment things need to go from the rancher, on to the ranchers’ affiliation, following which it is conveyed to promoting organizations, at that point onto the market/hypermarket/grocery store and lastly to the shoppers. This four-advance inventory network gives a lot of chances to the nourishment things to die in the manner. Our goal is to limit every single imaginable misfortune in this production network and to make it more savvy just as quicker. Therefore, we are expecting to enhance the production network for short-lived nourishment things. So as to carry out this responsibility, we will take the assistance of the IOT, considering the idea engaged with it referenced over the presentation. Before perceiving how we can utilize IOT in this perspective, we should initially comprehend the accurate extension and impacts of nourishment perishability.

10.2.1 What problems arise to the surface when we study the SCM of perishable food items? – Different geographical areas with different logistics have different agricultural needs. It has dispersed consumption.

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– The time and distance involved in transportation process increases the perishability of agriculture products. Since often products need to be carried over long distances, it greatly increases the risk of perishing in the way. – The equipment, infrastructure, and technology involved in agricultural SCM are still quite backward and not up to the standards of today’s market needs/ demands. Due to this very less development, other subsidiary or ancillary processes such as the mechanism involved in the processing and packaging of the products are also affected for not meeting the conditions for the transportation, processing, packaging, and storage of agricultural products. – It proves to be more complex than usual to fully grasp the market information, given the volatility and uncertainty associated with it, thanks to the dispersed consumer base and nonstandard supply chain operations. Additionally, these same factors often cause farmers to produce crops or food items blindly without an acute realization of the supply-demand gap. – The capital investment involved in producing perishable food items is also high. In order to ensure that the products meet the quality requirements of consumers, strengthening the asset specificity is crucial. These problems were linked directly or semi-directly with the supplier at the head of the supply chain. Now, let us examine some more areas wherein the supply chain could use optimization.

10.2.2 What sort of biological parameters in the supply chain may accelerate the perishability of said food products? – Transient nourishments are normally appropriated in temperature‐controlled supply chains, to be specific, cold chains. In the dispersion procedure from crude material providers to customers’ fridges, nourishment items crumble continuously because of the development and movement of microorganisms. The microorganisms can be presented during nourishment preparation or be available in the nourishment fixings, and they may develop gradually if the natural parameters (for example temperature) are leveled out or quickly if not. – The nourishment is protected if the fridge is still at 5 °C. Nourishments held above 5 °C for over two hours ought not to be devored and should be disposed of. – The temperature-necessity changes with the kind of nourishment and different things. The solidified nourishment or profoundly short-lived nourishment things are kept best in the cooler at − 20 to − 10 °C. Other staple requires a temperature somewhere in the range of 1 and 5 °C. Another misinterpretation is that hot nourishment cannot be set legitimately in the icebox. Hence, individuals keep hot nourishments at room temperature for long to bring down their

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temperature, therefore making the ideal condition for microorganisms to support and develop. – Numerous perilous refrigeration rehearses are followed in India at staple shops, stores, and Edible Enterprises. Business administrators once in a while give any significance to the cleaning and support of iceboxes. Regularly, because of space imperatives, these are kept in direct daylight and furthermore to pull in clients or publicize the nourishment brands. – Inconvenient deterioration microorganisms incorporate vigorous psychrotrophic Gram-negative microbes, yeasts, molds, heterofermentative lactobacilli, and spore-shaping microscopic organisms. Psychrotrophic microscopic organisms can deliver a lot of extracellular hydrolytic catalysts, and the degree of recontamination of purified liquid milk items with these microbes is a significant determinant of their time frame of realistic usability. Contagious decay of dairy nourishments is shown by the nearness of a wide assortment of metabolic results, causing off-smells and flavors, notwithstanding noticeable changes in shading or surface.

10.3 Literature review Production network is steadily meeting the trend setting innovations. Marlino et al. referenced that the here and now’s inventory network has seen a great amount of change when contrasted with the past few years. As of late, the production network is not just influenced by expanded reality in material handlings and numerous different parts, yet in addition reinforced by the more up-to-date, better and further developed advancements basically involving AI, man-made consciousness, mechanical technology, and huge information. These headways are set under the crate of IOT, which depends on the commutative procedure, creation choices, overseeing computerized gadgets, and data innovation. IOT may assist us with filling the hole that is left gaping between the two significant gatherings in the task. These exist at the extraordinary parts of the bargains condition range, that is, between the person who produces, and the person who buys. IOT may help the representatives working in the business to be refreshed with ongoing information with unimaginably exact qualities that may assist the administrators with making productive choices and have a generally better grasp on the general task. The IOT utilizes different propelled sensor-based gadgets that are associated with one another through a system, which cooperate and share information to give answers for the issue, for example, transportation, material following, planned refreshing, staffing, stock administration, and asset distribution and a lot progressively different things. This entire arrangement may require a few exact and modern gadgets, for example, global positioning system (GPS), RFID, bluetooth innovations,

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wireless frameworks, and high-spec cameras so as to keep up the information social affair and ongoing data imparting to incredible exactness. A few audits of the past effective instances of IOT’s innovative applications in SCMare referenced as pursues: – Mechanical autonomy is reforming every one of the fields, which are operational in giving new jobs to give supply chains to conveyance organizations, for example, Ali Baba express or Amazon just as materials dealing with. – By making speculations just as placing various resources and tries in SCM, organizations like Wal-Mart and Dell have seen a general diminishing in stock and coordination’s use, development at the pace at which they complete their customer’s solicitations, and furthermore expanded the general sentiment of authoritative intensity.

10.3.1 Status of SCM in India Proficient SCM adds to the upper hands to the associations. Here, we have passed on SCM and logistics alongside its significance devices and advancements as to improve the general execution of SCM and Logistics in India. To accomplish this, associations and organizations should concentrate on executing the systems and techniques that make a vital open door for organizations to watch an expansion in income. This is just conceivable by refocusing on incorporating Information Technology with SCM and Logistics. The ideal innovation stage can gather information at the undertaking level and convey this data so as to help the particular requests of their prime assembling or circulation. Associations ought to likewise utilize its intensity and the different developing system advances to build their business and limit their misfortune.

10.3.2 Usage of internet in supply chain optimization (management) The foremost objective of the SCM is not single-dimensional, and it targets limiting the cost, expanding the gauges of administrations, and furthermore improving the correspondence between different production network organizations; and it likewise builds the adaptability as far as conveyance and reaction time as it gathers information dependent on continuously. On mixing the IOT with the inventory network, it can give much better advantage to the business as far as cost-sparing chances and improvement of the present store network are concerned; for example, conventional coordinations rehearses were moderate and this has been streamlined to a huge degree by presenting the web and it likewise has decreased the cost-adequacy.

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Lencioni et al. demonstrated that depending on the positioning, the most prominent utilization of the Internet for store network, the board is in transportation, trailed by handling, overseeing merchant relations, buying and obtainment, and client assistance.

10.3.3 Digital supply chains At the hours of the wide and well-associated worldwide economy, the computerized store network is turning into the most inquired-about pattern and it is additionally on the way of progress and achievement. Advanced innovation is occurring over the customary tasks and now every business has become or will turn into a computerized business and its outcome on inventory network and the executives will be heavenly. As per Yan et al., just relying on the conventional method for SCM technique cannot prompt increasing far-reaching focal points in the market rivalry. In this way, numerous organizations/ventures have comprehended the most significant factor of these progressions and they have just begun attempting to bring advanced innovation into their activities; nonetheless, simply including advances into the business is not the response to everything. There are a few distinctive computerized advances, which could be checked under the IOT and could effectively qualify as a fate of the production network. The computerized advances are as follows: 1. Production network and augmented reality (AR) 2. Production network, IOT and Big Data 3. Production network and RFID.

10.3.4 Smart supply chain with AR According to the study by Cirulis et al., the target of AR being used to process the real-time data, which help in decision-making in enhancing human senses and capacity. AR innovation helps to interface virtual data with the real world. This can help in development of smart supply chain network for better optimization. The innovation of IOT is exceptionally utilized in the continuous information assortment and for different condition-related components. Most businesses are utilizing this innovation to contend in the market, and this innovation is likewise utilized in SCM. AR will give advantages to the recorded inventory network as follows: Picking optimization: By utilizing AR, any expert can see an “advanced picking list” on a heads-up show. Experts can choose a structure material and the computerized presentation will ascertain and control them through the briefest and most effective way through the distribution center for the bundle to be gotten. This data

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can likewise be spared in the Warehouse Management System at the same time with the assistance of distributed computing. Cargo/container loading: The presentations have bit by bit directions with the best system to stack the holder as per the size, measurement, and weight of the structure material stacked into the vehicle. The data and information through AR can guarantee ideal stacking and accordingly help lessen cargo cycles of the inventory from the distribution center to the building site. Dynamic traffic support: Most transportation vehicles (e.g., trucks) are furnished with GPS route, yet AR frameworks are the characteristic successors. Headsup and windshield’s showcases would enable the driver to recourse shipments continuously without diverting the driver fundamentally. For instance, a truck is stacked with solid packs, and AR can show the driver the basic data including the heaviness of the solid sacks, fuel effectiveness, the course to reach the goal. Office planning: AR can assist the experts with visualizing their next office in full-scale even before the development begins. The AR model can also help to upgrade work process with the help of websites and can gauge the crude material expected to do number of exercises. The AR framework can likewise assists the organizers with selecting potential providers for different structure materials while keeping up an online database at the same time.

10.4 Proposed solutions Looking over, we find that some of the food items’ demands depend on the season, and there is no linear demand for the items. As a result of this, these items perish easily because of their high production and low demand. To overcome this, IOT can help us a lot as it deals with the real-time data and information. Hence, we can study a lot about the current production and demand ratios. Using the IOT and obtaining the statistical data about the present demand of the consumer, we can easily predict the demand of the consumer in the upcoming time; hence, we can optimize the supply chain and minimize the waste of perishable food items and focus on the production according to it. By properly arranging the complete construction of the IOT including the arrangement of the sensors, radiofrequency technology and Internet together, we can accurately understand the manufacturing, demand, handling, storage, transportation, sales, and distribution of the products. The application of IOT can increase the efficiency of the transport of agricultural products greatly. It can be used to manage the transporting system in order to avoid any invalid transport. In addition, it can be used to dynamically monitor temperature and quality so as to prevent the temperature prone food items to perish. Moreover, IOT can be used to obtain all cold storage related data and all the current transport related data to get a proper data to solve the circulation-related issues. Using IOT, we can

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GPS tracking Distance minimization Advanced work distribution

Web portal Reducing food storage time

Instant response

Storage facilities

Figure 10.1: The different aspects of using IOT and the advantages of having a computerized web portal.

read the information of the products through embedded tags, and hence monitor the quantity and inventory quantity of goods, add goods, and deals with expired products timely, and also using it to improve the efficiency of the customer’s purchase and checkout. Another easily implementable and effective strategy to optimize the supply chain would be to install GPS trackers in all the storage containers, which contain the said perishable food items. This would allow those involved directly with the supply chain process to constantly be updated about where the food items currently are, and this would further allow them to control the transportation element of the supply chain to a greater extent than before. For instance, if they receive an update saying that a certain food item has been delivered successfully at a given warehouse, they can immediately direct the delivery persons at the next warehouse or shop to come and pick up the food. Additionally, we can make use of the constantly developing GPS technology in this field. Furthermore, we could customize the entire experience for the consumers as well. For example, if a person wants to buy a certain vegetable in bulk, he would only need to sign into the website of the supply chain and the moment the relevant food item arrives at the nearest warehouse/godown/shop, he would be notified about it.

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Figure 10.2: The optimized supply chain. At every stage of the chain, the location is updated via GPS, which informs the people involved at the next stage as well as the consumer.

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As the figure 10.1 shows, IoT helps in coordination among the various stakeholders with relative data to synergise the whole supply chain. The above figure shows the optimisation of supply chain linking farmer to consumer with the help of technology and thus improving the efficiency of the chain.

10.5 Conclusion This paper focuses and investigates the problems in the agriculture supply chain and various issues in the current system and how it can be optimized. However, it also discusses the IOT principles in the optimization of the supply chain, basically of the agricultural products. It deals with the various principles in agricultural production, processing, transportation, and sales process. It mainly promotes the use of modern technological approach in the agricultural field in order to optimize the complete agricultural supply chain. Thus, it mainly focuses on how to optimize the complete supply chain and to minimize the wastage of perishable food items using the principles of the modern IOT. The virtualization of supply chain on the above lines may help in reducing the unpredictable nature of such supply chain networks, which may increase the shelf life of perishable food products while maintaining the food safety norms and meeting the sustainability requirements. The virtualization will address the areas such as network control, processes and object and, so IOT can be a powerful tool to manage this complexity as it enables us to make the decision related to the supply chain on a real-time basis. In addition, it enables us to remotely control, monitor, plan, and optimize business accordingly using the internet-based on virtual objects. Implementation of virtualization of food supply chains requires infrastructures that support the food supply companies, including SMEs to easily connect to virtual objects in a secure and trusted way, while managing the integrity between different views. The main contribution of this paper lies in introducing the IOT in the field of optimization of the supply chain of perishable food items to minimize the wastage and increase the efficiency to manage and control the complete system of production, distribution, supply, and marketing. Hence, it deals with the real-time data collected from the current market status, weather and forecasting the results based on them so as to optimize the complete supply chain. Lastly, the virtualization model proposed is just an early thought toward the automation of supply chain. Such automation will also help toward more smart supply chain, which will help in self- learning supply chain based on dynamic optimization, real-time simulation and quick decision support, which will lead toward development of smart SCM system that can operate, decide, and learn with minimum human intervention.

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FCI’s open market sales see little success Rice/wheat sold as % of amount offered in open market sales 100 90

90.6

93.7

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70 60 50 41 40 30 20

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10 0 RICE

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Figure 10.3: Year-wise open market sales of rice/wheat. Source: FCI,201.

Moreover, addressing the issue highlighted earlier in this paper about the FCI not having enough storage space, we posit that adding more space to their previously commissioned lands will not automatically solve food wastage. This is because giving more storage space will not actually help boost the sales of wheat and rice. FCI has only managed to sell 15% of the wheat and 40% of the rice in its stocks in the first quarter of the financial year 2019–20. What is needed here is, again, a highly optimized supply chain, which can result in faster, more efficient sales of said stocks and which can thus help prevent food wastage. Using IOT in this regard is the most sensible option available, and by incorporating all the elements highlighted in our proposed solution, we can greatly reduce the food wastage as well as dispose of the remaining stocks in an efficient, quick, and easily impenetrable manner.

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Bibliography Alfian G., Ijaz M.F., Muhammad Syafrudin M., Syaekhoni A., Fitriyani N.L., and Rhee J. Customer behavior analysis using real time data processing: A case study of digital signage-based online stores, emerald, 14 January 2019. Ali S.M., Moktadir A. Md., Kabir G., Chakma J., Rumi J.U. Md., and Islam T. Md. Framework for evaluating risks in food supply chain: Implications in food wastage reduction, sciencedirect, 24 April 2019. Aryal A., Liao Y., Nattuthurai P., and Bo L. The emerging big data analytics and IOT in supply chain management: a systematic review, emerald, 24 December 2018. Badia-Melis R. and Ruiz-Garcia L. Real time tracking and remote monitoring in food traceability., emerald, 24 june 2016. Calatayud A., Mangan J., and Christopher M. The self thinking supply chain, emerald, 14 January 2017. Chande A., Dhekane S., Hemachandra N., and Rangaraj N. “Perishable inventory management and dynamic pricing using RFID technology”, Springer, June 2005. Chaudhuri A., Dukovsks-Popovska I., Subramanian N., Chan H.K., and Bai R. Decision-making in cold chain logistics using data analytics: a literature review. emerald, 13 August 2018. Fonseca L. and Cane C. Monitoring perishable food, science direct, 15 November 2019. Gunpinar S. Supply Chain optimization of blood products, semanticscholar, January 2013. Haddud A., DeSouza A., Khare A., and Lee H. Examining potential benefits and challenges associated with the Internet of Things integration in supply chains, emerald, 2 October 2017. Kumar A. A review of IOT Applications in supply chain optimization of the construction materials., researchgate, July 2018. Lifang W., Yue X., Jin A., and Yen D.C. Smart supply chain management: a review and implications for future research, emerald, 8 August 2016. Luthra S., Mangla S.K., Garg D., and Kuamar A. Internet of things in agriculture supply chain management: a developing country perspective, researchgate, February 2018. Manavalan E. and Jayakrishna K., A review of internet of things embedded sustainable supply chain for industry 4.0 requirements, sciencedirect, 16 November 2018. Munuzuri J., Onieva L., Cortes P., and Guadix J. Using IOT data and applications to improve the port-based intermodal supply chains, sciencedirect, 23 January 2019. Pundir A., Jadhav D., and Ganapathy L. Improving supply chain visibility using internet of things, researchgate, January 2019. Shamsuddoha M. Integrated supply chain model for sustainable manufacturing: A system dynamics approach, emerald, 20 October 2015. Shi J., Zhang F., and Xiuli Q. Optimization distribution strategy for perishable foods using RFiD and sensor technology, emerald, 12 October 2010. Shih C.-W. and Wang C.-H. Integrating wireless sensor networks with statistical quality control to develop a cold chain system in food industries, science direct, 17 December 2015. Sinha A.K. and Anand A. Optimizing supply chain network for perishable products using improved bacteria foraging algorithm, science direct, 3 November 2019. Stefan Seuring. A review of modeling approaches for sustainable supply chain management, Sciencedirect, March 2013. Tanner D. Applications of RFID technologies in food supply chain, sciencedirect, 30 November 2015. Verdouw C.N., Wolfert J., Beulens A.J.M., and Rialland A. Virtualization of food supply chains with the internet of things, sciencedirect, 10 November 2015.

194

Shashikant Rai, Saurabh Mishra, Ram Mohan Mishra

Verdouw C., Sundmaeker H., Tekinerdogan B., Conzon D., and Montanaro T. Architecture framework of IOT-based food and farm systems: A multiple case study, sciencedirect, 4 August 2019. Verdouw C., Sundmaeker H., Tekinerdogan B., Conzon D., and Montanaro T. Architecture framework of IOT-based food and farm systems, science direct, 4 August 2019. Wang Y., Yang C., and Hou H. Risk management in perishable food distribution operations: A distribution route selection model and whale optimization model, emerald, 5 October 2019. Yang Y., Chi H., Tang O., Zhou W., and Fan T. Cross perishable effect on optimal inventory preservation control. sciencedirect, 28 January 2019. Zhong R., Xun X., and Wang L. Food supply chain management: systems, implementations, and future research. emerald, 16 October 2017.

Index acid rain 158 agricultural waste 158–161 atmosphere 157, 167 attitude-behavior gap 126–127 bibliometric analysis 41, 51–53 biomass waste management technique 171 biomass waste management 162–163 biomass 157 brick kilns 157, 162–164, 166, 173, 175 brickfield 157, 162–164, 166–167, 171–175 briquette machine suppliers 164–165 briquette making machine 172 citation analysis 46 co-citation network analysis 46 defining supplier selection criteria 19 defuzzification 17–18, 23 Dickson’s supplier selection criteria 7 digital supply chains 187 dissatisfaction decrement index 97–98 environmental sustainability 40, 105–106, 135, 147–149 environment-friendly consumption 121 ethical consumption 120–121, 127 FISs 12, 14–17, 29 food supply chain 179 freight logistics 39–41 freight supply chain 41 freight transportation 40–45, 49, 51, 53 fuzzification 12, 17–18, 23 fuzzy AHP 79–80 fuzzy inference systems 1, 12 fuzzy inference 16–18 fuzzy Kano model 92–93 fuzzy Kano prioritization 96 fuzzy Kano 89, 93 green consumption 119–121, 124 green freight transport 40–41, 51 green management 9, 105, 108 green manufacturing 11, 107, 109

https://doi.org/10.1515/9783110628593-011

green marketing 105, 108, 136 green material sourcing 107 green supply chain management 106, 109, 163–164 green supply chain 105, 106 green transportation 75, 108–109 heritage tourism 89–91, 100–101 inbound tourist 89–90, 92, 95–96, 100 internet of things 179–180 Kano model 91–92 keyword analysis 49 linguistic variables 16–18, 21–22 logistics performance 55, 73–76, 79, 81, 108 low carbon freight transport 41 Mamdani-type fuzzy inference systems 1, 16–17 marina management 132, 143–145, 147, 150–152 market choice behavior 124 means-end theory 123–124 membership function 16, 18, 20–22, 91 methodology 60–61 motivation–abilities–opportunity 125 ozone layer depletion 158 pellet making machine 172 perishable food 180, 184, 188–189, 191 planned behavior 124 qualitative criteria 10–12, 76, 79, 81 quantitative criteria 10–12, 76, 79, 81 reverse logistics 73–76, 78, 80–81, 107–109 satellite images 59, 62–65, 69 satisfaction increment index 97–98 sensitivity 142, 147 service blueprint 89–90, 94–95, 100, 103 service designing 89, 95

196

Index

service quality 89–91, 95, 100, 149 solid waste management 143, 159, 168 supplier selection problem 1, 12, 14–15, 29 supply chain management 1–2, 46, 55, 73–74, 89, 112–113, 179–181 supply chain sustainability 3–4, 40, 73–74, 81 sustainability marketing strategies 137–138 sustainability marketing 136–137 sustainability 3, 19, 39, 133, 136, 147–149 sustainable competitive advantage 133, 135, 141, 181 sustainable consumption 110, 119–128 sustainable development 1–3, 6–7, 39–40, 49, 53, 55, 59, 70–71, 108, 119–123, 133–134, 136–138, 140, 150–152 sustainable freight transport 39–40, 42–43, 49, 51, 53, 55 sustainable supplier selection criteria 1, 4, 7, 8, 10 sustainable supplier 1, 4–5, 7–9, 14, 16, 20, 23, 29

sustainable supply chain management 1, 73–74 sustainable supply chain 6, 53, 73–77, 81, 105, 119–121, 123–124, 126 theorey of market choice behavior 124 theory of planned behavior 124 theory of reciprocal determinism 126 urban expansion 59–60, 65–66 urban fringe 59 urban sustainability 59–60, 71 value–beliefs–norms 125 waste management system 159 waste management 20, 74, 106, 112, 134–135, 139, 141, 143, 149, 152, 157–158, 160–163, 175 waste 158–159 weighted scoring method 73, 75, 79, 81, 84 yachting 133

De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences

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