Innovation and Behavioral Strategy 9798887300603

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Innovation and Behavioral Strategy

A volume in Research in Behavioral Strategy T. K. Das, Series Editor

Research in Behavioral Strategy T. K. Das, Series Editor Published Innovation and Behavioral Strategy (2022) Edited by T. K. Das Entrepreneurship and Behavioral Strategy (2020) Edited by T. K. Das Behavioral Strategy for Competitive Advantage (2018) Edited by T. K. Das Culture and Behavioral Strategy (2017) Edited by T. K. Das Decision Making in Behavioral Strategy (2016) Edited by T. K. Das The Practice of Behavioral Strategy (2015) Edited by T. K. Das Behavioral Strategy: Emerging Perspectives (2014) Edited by T. K. Das In Development Behavioral Strategy in International Management

Innovation and Behavioral Strategy

edited by

T. K. Das City University of New York

INFORMATION AGE PUBLISHING, INC. Charlotte, NC • www.infoagepub.com

Library of Congress Cataloging-in-Publication Data   A CIP record for this book is available from the Library of Congress   http://www.loc.gov ISBN: 979-8-88730-060-3 (Paperback) 979-8-88730-061-0 (Hardcover) 979-8-88730-062-7 (E-Book)

Copyright © 2022 Information Age Publishing Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the publisher. Printed in the United States of America

CONTENTS

About the Book Series.......................................................................... vii T. K. Das 1 Inspired Teams: Building a Holding Environment to Catalyze Innovation........................................................................... 1 Steven B. Wolff, Michele Norton, Dave Silberman, and Brian Moran 2 Strategic Behaviors of Leaders in Open Innovation: The Role of Ambidextrous Leadership and Entrepreneurial Behaviors.......... 29 Parisa Haim Faridian and Kathryn E. Weaver 3 Behavioral Strategy, Innovation, and Environmental Disruptions..... 53 Mzamo P. Mangaliso, Leah Z. B. Ndanga, and David L. Major 4 Open Innovation Through a Collaborative Community of Firms: An Emerging Organization Design.................................... 85 Charles C. Snow and Refik Culpan 5 Towards a More Comprehensive Capital-Based Framework for Explaining Performance of Small-Scale Entrepreneurs: Illustrations From the Ghanaian Marketplace................................. 109 Joseph Ofori-Dankwa, Micah DelVecchio, and Akosua K. Darkwah



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vi  ⏹ Contents

6 New Product Performance Through Channeling in Supply Chain Innovation Alliances: The Nexus of Collaboration Intensity, Divergent Communication Schemes, and Alliance Duration....................................................................... 133 Ricarda B. Bouncken and Robin Pesch 7 Innovation and New Partner Selection: Theory and Exploratory Evidence From the Information and Communications Technology Sector in the Netherlands............... 161 Gjalt de Jong 8 Coopetition in Networks and Its Implications for Innovation........ 187 Xiaotian Yang and Fen Zhang 9 Public–Private Innovation Strategic Alliances for SMEs: An Emerging Model........................................................................... 209 George Tsekouras and Costis Kompis About the Contributors...................................................................... 267 Index................................................................................................... 275

ABOUT THE BOOK SERIES

Behavioral strategy continues to attract increasing research interest within the broader field of strategic management. Research in behavioral strategy has clear scope for development in tandem with such traditional streams of strategy research that involve economics, markets, resources, and technology. The key roles of psychology, organizational behavior, and behavioral decision making in the theory and practice of strategy have yet to be comprehensively grasped. Given that strategic thinking and strategic decision making are importantly concerned with human cognition, human decisions, and human behavior, it makes eminent sense to bring some balance in the strategy field by complementing the extant emphasis on the “objective” economics-based view with substantive attention to the “subjective” individual-oriented perspective. This calls for more focused inquiries into the role and nature of the individual strategy actors, and their cognitions and behaviors, in the strategy research enterprise. For the purposes of this book series, behavioral strategy would be broadly construed as covering all aspects of the role of the strategy maker in the entire strategy field. The scholarship relating to behavioral strategy is widely believed to be dispersed in diverse literatures. These existing contributions that relate to behavioral strategy within the overall field of strategy have been known and perhaps valued by most scholars all along, but were not adequately appreciated or brought together as a coherent sub-field or as a distinct perspective of strategy. This book series on Research in Behavioral Strategy will cover the essential progress made thus far in this admittedly fragmented literature and elaborate upon fruitful streams of scholarship. More importantly, the book series Innovation and Behavioral Strategy, pages vii–viii Copyright © 2022 by Information Age Publishing www.infoagepub.com All rights of reproduction in any form reserved.

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viii  ⏹ About the Book Series

will focus on providing a robust and comprehensive forum for the growing scholarship in behavioral strategy. In particular, the volumes in the series will cover new views of interdisciplinary theoretical frameworks and models (dealing with all behavioral aspects), significant practical problems of strategy formulation, implementation, and evaluation, and emerging areas of inquiry. The series will also include comprehensive empirical studies of selected segments of business, economic, industrial, government, and nonprofit activities with potential for wider application of behavioral strategy. Through the ongoing release of focused topical titles, this book series will seek to disseminate theoretical insights and practical management information that will enable interested professionals to gain a rigorous and comprehensive understanding of the subject of behavioral strategy. —T. K. Das City University of New York Series Editor Research in Behavioral Strategy

CHAPTER 1

INSPIRED TEAMS Building a Holding Environment to Catalyze Innovation Steven B. Wolff Michele Norton Dave Silberman Brian Moran

ABSTRACT To fully realize the power of innovation, organizations must harness individuals’ and team’s cognitive and emotional capacities to unlock their collective strength. This chapter explores the emotional climate teams need to create breakthrough innovation. While much of the innovation literature has traditionally focused on organizational innovation and organizational practice, we focus on teams and how their culture supports innovation. We explore how teams can emotionally (feeling), cognitively (knowing), and socially (doing) unleash the power of strategic, breakthrough innovation. We enter the conceptual framework through concepts of holding environments, social capital, and human factors. The team’s holding environment—a complex, nonlinear web of social interactions guided by the values and norms of the team—builds social capital that serves dual purposes: (a) supporting productive emotional Innovation and Behavioral Strategy, pages 1–28 Copyright © 2022 by Information Age Publishing www.infoagepub.com All rights of reproduction in any form reserved.

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2  ⏹  S. B. WOLFF et al. and human dynamics as the team goes about its work (being) and (b) supporting the accomplishment of the team’s task (doing). We then organize a discussion of the values into four primary outcomes that support innovation and which emerge from the interaction guided by the values and norms: (a) energy—to energize members, (b) learning—to foster continuous learning and improvement, (c) execution—to support the team’s task accomplishment, and (d) transparency—to support the generation of undistorted information and make it readily available. We end with discussions of practical implications and future research.

INTRODUCTION In the book, Making the Impossible Possible, the authors tell the story of the Rocky Flats Nuclear Weapons Plant (Lavine & Cameron, 2006). In 1951, the Rocky Flats mission produced detonators for nuclear weapons and helped keep the world safe for democracy during the Cold War. The workforce was seen as patriotic heroes, but in 1989 this would all change. The plant shut down and environmental crime investigations began. Protests would escalate over the next 6 years, and environmental investigations would culminate in a shutdown of the plant and an Environmental Protection Agency (EPA) lawsuit that detailed egregious and dangerous conditions. During this time, due to the environmental damage caused by management incompetence, executive employees were branded as environmental criminals, and employees came to work solely to fulfill contractual requirements. The plant needed innovative behaviors to turn the situation around. Instead, the plant employees were lethargic and embodied behaviors that stifled innovation. As a result, 900 employee grievances were submitted concerning unsafe working conditions. This was double the national average of safety incidents. Experts claimed cleaning up the environment and addressing the widespread and deeply rooted issues would take over $36 billion and 70 years to complete. In contrast to the despair and elongated expectations of the internal Rocky Flats teams, a privately held company, hired to manage the cleanup, showed up differently. This company moved with a different beat and completed the project nearly 60 years ahead of the estimates and 30 billion dollars under budget. Further, their team was able to do it 13 times cleaner than required, turned adversaries into supporters, created labor relations described as “the best they had seen in their careers” (Lavine & Cameron, 2006, p. 23), had a safety record twice the national average, and generated 200 technological innovations. Where one management team failed miserably, another was able to come in and create an environment filled with positive energy, transparency, exploration, and the execution needed to innovate effectively towards an unimaginable outcome. This story should

Inspired Teams  ⏹  3

leave you wondering: “How did they do that, what was the magic recipe, and could my team do that?” This chapter answers those questions as it explores why some teams innovate and others do not. The strategic management of any organization is composed of behavioral strategies that “merge cognitive and social psychology with strategic management theory and practice” (Powell, Lovallo, & Fox, 2011, p. 1369) and are based on the assumption that strategic management must be grounded in the realities of human cognition, emotion, and social interaction (Powell et al., 2011). The difference between the management team that illustrated innovative behaviors at Rocky Flats Nuclear Plant compared to the team that did not, was the embodiment of different values. This chapter highlights those values that support innovation. We do this by illuminating the behavioral strategies that teams can develop to unleash the power of strategic, breakthrough innovation and create the inspiration members need to innovate within their organizations. CONCEPTUAL FRAMEWORK This chapter leads to an understanding of how to build teams that are a catalyst for innovation in an organization; we call these teams inspired teams. We discuss a network of linked concepts by which the team environment leads to innovative outcomes (see Figure 1.1). We define innovative outcomes as the number of innovations in product, service, or process, the radicalness and novelty of the innovation, and the degree to which the team can get those innovations accepted (West & Anderson, 1996). Holding Environment We enter the model through the concept of a holding environment. Winnicott (1965), a British psychologist, explored the concept that healthy Holding Environment

Social Capital

Values

Relational SC

Innovation Process

Outcomes

Cognitive SC Norms Interaction

Structural SC

Human Factors

Figure 1.1  Model of the connection between a team’s holding environment and outcomes.

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child development occurs in an environment created by their parents; the extent to which the environment meets the child’s needs and provides a sense of security has consequences for the long-term psychological health of a child. A context that supports individual needs has been called a holding environment and has been extended to organizational environments (e.g., Kahn, 2001). We apply this concept to the environment created by team member interaction. It is essential because it affects team members’ emotional and psychological state, which, in turn, affects their behavior and performance (e.g., Argyris, 1957; Basseches, 1986) and ultimately, the team’s ability to innovate. We conceptualize the team’s holding environment as a complex, nonlinear web of social interaction that is guided by the values and norms of the team and affects social capital, which Nahapiet and Ghoshal (1998) argue “constitute(s) some aspect of the social structure, and . . . facilitate(s) the actions of individuals” (p. 244). As a complex system, many feedback loops exist that allow the system to adapt, even when some elements fail (Meadows, 2008); influencing the system demands attention to the entire operating environment rather than any particular element. For example, when a transgression occurs between two team members, it does not mean that the relationship will suffer; this is linear, cause-and-effect thinking. Research finds that other aspects of the holding environment, such as concern for each other’s perspective, can help mitigate this potential outcome (Okimoto & Wenzel, 2014). Values that guide interaction in the holding environment reside in individuals and are a general sense of right and wrong (Frese, 2015). Norms are specific social expectations of behavior that embody the values, and when shared, lead to routines and practices (Frese, 2015). Values can be brought into the team by individuals. Still, team members must share the values to create norms, that is, specific social expectations of behavior that individuals conform to. On the other hand, norms can be agreed to by the team, and over time, if the resulting practices benefit the team, those norms become valued by team members and turn into shared values (Frese, 2015). However they emerge, values and norms are vital elements that shape interaction in the team, which, in turn, create or destroy the team’s social capital. Social Capital Nahapiet and Ghoshal (1998) explain that social capital is a social asset that facilitates collective action; they identify three forms of social capital: relational, cognitive, and structural. All three forms are essential to team functioning and are created by the shared values and norms of the holding environment. Relational social capital facilitates interaction and moderates

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the effect of emotions generated when team members interact. Relational social capital, thus, promotes sharing and processing information, an essential task of innovation (Nijstad, Bechtoldt, & Choi, 2019). Cognitive social capital facilitates interaction by creating shared understanding. One way shared understanding supports innovation is by building emotional capability (Huy, 1999). Emotional capability reduces the perceived emotional threat of a challenge by focusing on possibilities. This makes the team more likely to accurately assess the situation and explore new ideas rather than take a defensive posture. Finally, structural social capital represents the benefits from relationships that occur beyond the team’s boundaries; these relationships are a source of new insights and innovative ventures (van Woerkom & Croon, 2009) as well as aiding dissemination of an innovation. Structural social capital has also been considered to include roles, rules, precedents, and procedures that the team uses in the process of performing its task (Claridge, 2018). Social capital generated by team interaction facilitates collective action in three ways. First, it facilitates task accomplishment through a shared understanding of what is required to accomplish the task, such as how much risk we take, how much we need to engage key stakeholders, what information is essential, and so forth. Second, it moderates the effect of team member interaction on human factors such as the emotion generated by failure or the biases created through experience, and so forth. Third, it facilitates collaborative action by affecting human factors such as the emotion we feel when sharing unpopular perspectives, the degree of awareness of bias we may have when making decisions, and the threat we may feel when implementing new and innovative ideas, and so forth. Human Factors Although we often think we are rational beings who make informed decisions based on facts, this is not how humans work. Our bodies provide information to our brain, which in turn drives our behavior (Blake, 2018). However, in Western culture, we tend to think it is the other way around; the predominant focus is on intelligence and rational thinking. This focus has obscured the role that our body, particularly emotion and cognition, plays in just about everything we do and every decision we make (Blake, 2018; Finkelstein, Whitehead, & Campbell, 2009). The term human factors has been historically used to understand the role human error plays in adverse events such as medical accidents, plane crashes, and so forth (Reason, 1995). The intent of understanding human factors in this context is to eliminate the fallibility of humans and prevent adverse events. In recent years, researchers have recognized that humans are not entirely rational beings

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and that emotion, cognition, and social interaction underlie human behavior and decision making (Powell et al., 2011). For example, work from cognitive and social psychology has been used to better understand fields such as economics and strategy. We use the term human factors to represent the emotion, perceptual filters, motivation, mindset, and so forth, that affect human behavior in the innovation process. Teams can use identical task processes (the doing) but produce very different results depending on human factors (the being). For example, if people are afraid to make a mistake, the team will not take risks; if people don’t value customer input, they will not connect to their market; if emotional capability is low, the team may look at a challenge through rose-colored glasses and dismiss the need to change course. Innovation Innovation is universally considered a critical strategic imperative for organizational success (Anderson, Potočnik, & Zhou, 2014) and is vital to the survival of today’s organizations (Naranjo-Valencia, Jiménez-Jiménez, & Sanz-Valle, 2011). Innovation is seen across all the functions of an organization, from solving client problems, creating new marketing campaigns, designing new software or technologies, and the list could go on (Hogan & Coote, 2014). As a result of the predominant belief that we are rational beings, research on innovation has historically focused on rational models that include areas of study such as antecedents to innovation (Kirsch, Ko, & Haney, 2010), innovation processes such as brainstorming (Paulus, Kohn, & Arditti, 2011), the systemic nature of innovation (Edquist, 2010), and the affect of innovation on performance (Cantwell, 2005). Other research focuses on organizational innovation and organizational practices, for example, human resource development (Seeck & Diehl, 2017). Innovation is inherently a collective process (Büschgens, Bausch, & Balkin, 2013) that involves human factors. Ideas must be shared, combined, selected, and implemented to become an innovation that benefits the organization. The need to understand innovation as a collective process has led, more recently, to a greater focus on the human side of innovation. For example, To and Fisher (2019) studied how human factors affect the creative process and the first edition of The Oxford Handbook of Group Creativity and Innovation was published in 2019 (Paulus & Nijstad, 2019). While research on innovation in teams has recently expanded, many of the studies narrowly focus on specific aspects of the team’s process and culture. For example, Mueller and Cronin (2009) examined how team relational support facilitates creative processes; Nijstad et al. (2019) discuss creativity in teams

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from an information processing perspective; and Nemeth and O’Connor (2019) discuss the role of dissent in team creativity. Paradoxically, the current research on human factors and teams is often rationally oriented. By this we mean that human factors such as emotion, perceptual filters, motivation, mindset, and so forth, are treated as independent variables that have an antecedent relationship to innovation processes and outcomes. For example, moods have been associated with individual inputs into the innovative process, such as cognitive flexibility (Isen, 2001). While this is valuable insight, it is descriptive of what is happening; it does not help us understand the generative forces that create the moods and emotions being studied. It inherently operates from the assumption that if we know what human factors are associated with desired innovative behaviors and mental states, such as cognitive flexibility, they can be managed externally, presumably by “leaders.” There is truth to the argument that leaders influence human factors that, in turn, shape innovative behavior; however, we argue that the environment is a generative force that is created by team member interaction and must be considered holistically. Through its effect on social capital, the environment affects human factors such as emotion, perceptual filters, motivation, and mindset, which, in turn, affect a team’s innovation outcomes. The innovation research discussed above provides essential insight into innovation on teams, but from a usefulness perspective, the narrow, linear focus of academic research makes practical guidance somewhat tricky for practitioners. Our focus is on teams and how their holding environment holistically supports or inhibits innovation. We know that as teams become more prevalent within organizations, a pressing problem is how to ensure that team members act collaboratively to achieve specific goals (Child & McGrath, 2001; Towry, 2003) such as innovation. Human Factors and Innovation Many human factors influence innovation outcomes; we provide a sampling (see Table 1.1), not an exhaustive list. This discussion aims to show that human factors exist and must be considered when creating a holding environment that supports innovation in a team. One human factor that affects innovation is emotion. There is relative agreement that fear affects innovation (Edmondson & Mogelof, 2006). Innovation suffers when people do not feel safe sharing ideas, taking risks, and enduring inevitable failure. Fear can be moderated by the environment in which team members act. For example, a failure is an ambiguous event that means different things in different environments. Some teams create a blame culture where people are afraid to fail and look for someone to blame their failure on.

Affects the effort people will put into finding new ideas and creating breakthroughs. Affects the ability to learn and “see” new possibilities.

Lack of identification with work of the team.

Lack of focus on reflection, discussing errors is dangerous.

Mindset/Beliefs

Prevents sharing, limits perseverance to create breakthroughs.

Lack of energy and commitment to teamwork.

Motivation

Prevents team from using critical information, distorts information.

Closes down possibility. Change goals rather than create breakthroughs.

Anxiety, stress when facing challenge

Devaluing certain information, “Come with solutions not problems.”

Inhibits sharing of perspectives and ideas.

Fear of rejection

Perceptual Filters

Inhibits experimentation and taking risks.

Fear of failure

Emotion

Connection to Innovation

Examples

Human Factor

TABLE 1.1  Sample of Human Factors in Innovation

Create rituals of reflection and learning, explore errors as learning opportunities.

Create a compelling purpose, craft roles to fit individuals and use full capability.

Create connection, emotional capability to endure challenge.

Create connection within team to open minds, build networks of external relations.

Build emotional capability. Create a compelling purpose. Create catalysts to support new habits.

Create psychological safety and a sense of belonging.

Create positive meaning around failure.

Mitigation

Value reflection, learning, making information visible.

Value compelling purpose, creating roles that people love.

Value understanding, mutual support, optimism.

Value external relations, candid expression, understanding, caring.

Value compelling purpose, optimism, integrity, catalysts, proactivity.

Value understanding, caring, acceptance, reflection, candor.

Value failure, curiosity, experimentation

Associated Values

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Other teams celebrate failure with rituals where people share their failures and discuss what was learned. This ritual creates cognitive social capital— a shared understanding that failure is not something to fear but rather is something from which to learn. The meaning attached to failure, consequently, helps reduce that prospective fear. Innovation requires that team members share their perspectives and ideas candidly (Nahapiet & Ghoshal, 1998). The quality of relationships, supported by relational social capital, determines the degree to which people feel part of the team, that they won’t be rejected, and thus, feel safe to contribute new and creative ideas candidly (Edmondson & Mogelof, 2006). When team members do not feel safe and fear rejection, they will be less likely to contribute to the creative process. Another emotional component of innovation is the emotion triggered by challenges and “bad news,” for example, a product is no longer viable in the market, requiring a change in direction. The ability of a team to handle such events and information without distorting the reality of the situation, for example, a belief that “the challenge is not so bad,” or, “we don’t have to worry about it,” is called emotional capability (Huy, 1999). The ability of the team to stay committed to its goal and deal with the breakdown (defined as a challenge that prevents the team from achieving its goal) directly determines its ability to create breakthrough innovation (Scherr, 1989). One way the environment can address building emotional capability is by creating a shared understanding of the significance of remaining committed to a goal in the face of a breakdown (Scherr, 1989), such as a belief that “we don’t move the goalposts (i.e., our commitments) when the going gets tough.” Another is by maintaining an air of hope and optimism that the team can find a solution to the challenge it faces (Huy, 1999). Having a strong sense of purpose that team members identify with helps build commitment and hope, which are needed to make breakthroughs in the face of breakdowns (Henderson, 2021). Another human factor that affects innovation is the ability to sense important information and process it objectively (Nijstad et al., 2019). Several things can interfere with this process. First, the data the team deems essential, and thus allows in, is determined by a shared understanding of what is required to do the work. For example, many teams do not value information from the external world, for example, customers, and do not seek such information. Entire products are designed based on an internal conception of what is needed, without validation from the market. Many of these products may be innovations that are accepted in the market, but many of them will fail. The team needs to tune its filters by building a shared understanding of which information it deems necessary and will actively seek. Important information is often unclear, and people may only have a vague sense about a particular idea or concept but are unable to fully and

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coherently articulate that sense. The team may filter out this information by a shared belief that people need to express their ideas clearly and come to the team with “solutions, not problems.” This ill-advised approach filters out information that cannot be readily understood and processed. Conversely, the team can create cognitive social capital that validates and explores vague feelings and hunches as potentially valid and vital information. Another human factor is the extent to which team members are energized and motivated by the team’s purpose and work (Amabile, 2001; Seeck & Diehl, 2017). Intrinsic motivation is essential for people to put energy into the team’s work and share their thinking and ideas. When people have high levels of psychological availability they can engage in the work to a greater extent and are more motivated to contribute ideas (Kahn, 1990). A final human factor that we will discuss is team members’ mindsets and beliefs. One belief that affects innovation is the extent to which team members identify with the team (Haslam, Adarves-Yorno, Steffens, & Postmes, 2019); in other words, the extent to which the values, purpose, and work of the team represents the team members’ sense of identity and what is important to them. A team’s environment can create an enhanced sense of meaning and purpose to their work through cognitive social capital. This then leads to creating routines and rituals, a form of structural social capital, that keeps the purpose front-and-center and central to decision making. So far, we have argued that the team environment is a complex web of interactions that produce social capital, which, in turn, shapes behavior in a team through its effect on the human factors associated with interaction. These human factors affect the quality and character with which the team carries out its task of innovation, which ultimately affects the outcomes it produces. Therefore, one key to fostering innovation within a team is understanding the environment that shapes team member interaction to support innovation (Mueller & Cronin, 2009). What exactly is this environment, and how do you create a holding environment for innovation? CREATING HOLDING ENVIRONMENTS FOR INNOVATION Although the concept of a holding environment has been primarily conceived of as an environment that supports the emotional needs of individuals, we expand the concept to include an environment that supports the work that individuals do. As team members go about their work, the human and behavioral aspects of the work will naturally be supported by the traditional conception of a holding environment, that is, one that meets the emotional needs of team members. However, the environment can also support task accomplishment (Schein, 2010). For this reason, we conceive of the holding environment as serving a dual purpose: (a) supporting

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productive emotional and human dynamics as the team goes about its work (being) and (b) supporting the accomplishment of the team’s task (doing). For example, let’s consider an engineering team in the early stages of product development. The team must develop something innovative that will sell in the market. This involves exploring, learning, synthesizing various perspectives, and selecting an option. The environment of the team must engender curiosity and encourage people to learn by trying new things, some of which may fail. The environment must also hold its members when they do fail; their need to belong must be met so they maintain their sense of worth and belonging in the team (Fonseca, Lukosch, & Brazier, 2019). Once the innovation is in the dissemination phase, the environment must hold members when there is a breakdown, that is, when there is an unforeseen obstacle in the path of accomplishing their goal (Scherr, 1989). The environment must not only help members through the anxiety and stress of having to find a way to create a breakthrough, but it must also help them mobilize around the task to find possibilities in the situation, call in external favors, and energize them to rally in the face of being challenged. We organize the following discussion of a holding environment for an innovation team into four primary outcomes the environment needs to produce to support the team: (a) energy—the environment needs to create energized members, (b) learning—the environment needs to foster continuous learning and improvement, (c) execution—the environment needs to support the team’s task accomplishment, and (d) transparency— the environment needs to support the generation of undistorted information and make it readily available. These outcomes roughly parallel the four forms of control that Büschgens et al. (2013) identify as organizational cultures within which innovation can occur (group, developmental, rational, and hierarchical). Group control is concerned with relationships, as is the energy outcome in our model. Developmental control is about learning, and rational control is essentially about the mechanics of task accomplishment, as is the execution outcome in our model. The hierarchical culture is concerned with controlling information. The transparency outcome in our model is related to information, but it is about producing and managing information rather than controlling it. Nevertheless, we find these four main categories a valuable way to think about the primary outcomes a holding environment must produce for a team to be effective. Conceptually, there is a big difference in the cultures discussed by Büschgens et al. (2013) and the outcomes of a holding environment for innovation. Büschgens et al. (2013) identify organizational cultures within which innovation teams operate. They conceive of culture, generated by a dominant set of values, as a form of control that shapes the team’s innovative behavior within the organization. They use the framework to organize a metaanalysis of the innovation literature. We argue that, although an innovation

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team exists within the organizational context, it generates its own culture and needs all four sets of values to produce a holding environment that supports innovation and team effectiveness. The model discussed by Büschgens et al. (2013) was derived from the work of Quinn and McGrath (1982), who also argue that all sets of values are essential to effectiveness. Within each outcome area, the values must create an environment that holds both the task work needed for innovation and the human factors associated with performing the task. Although the values do not prescribe task processes, they guide behavior around the task in a general way. This builds cognitive social capital, that is, a shared understanding of behaviors that facilitate the team’s work. Similarly, the values around the human factors associated with innovation do not prescribe behaviors; they guide interaction such that the team holds the needs, concerns, and emotions of team members, that is, member needs are met through the interactions among team members. As a result, the team builds social capital, which facilitates collaboration. The values we discuss are not intended to be an exhaustive set of values that affect innovation; as we said above, the effects of these values cannot be thought of in linear, causal terms. The values interact with each other to produce the holding environment. Although the validity of the connection between any particular value and innovation is supported by literature, our experience is that this set of values is much more powerful when taken together. We group the values into the four primary outcomes for the purposes of threading together our conceptual model; however, the values may influence other outcomes beyond the one in which it is categorized. For example, although we categorize integrity as primarily affecting the execution outcome, it also has an effect on energy; people will be more energized when integrity is high. The holding environment created by the set of values, not only facilitates innovation, but also builds a high-performing team that is resilient, passionate, agile, and joyful. Yes, they will create breakthrough innovation, but they are more likely to experience flow (Csikszentmihalyi, 2004) and continually build social capital that supports breakthrough innovation and collaboration to accomplish its work. We will enter each outcome through story, literature, reflection, and discussion and then conclude by bringing all the outcomes together from a more holistic perspective. Energy Good Jane, Bad Jane We all have had bosses that energize us and ones that make us dread showing up to work each day. Bad Jane regularly chided her team for not having organizational awareness and missing the politics happening around

Inspired Teams  ⏹  13

the office. Her nagging and expressed frustration caused her team to disengage. One of the team members even discussed how they would usually do reading for work on the train to the office, but it stopped because they became de-energized by Bad Jane’s lack of support and caring. When Good Jane took over, she understood the need for organizational awareness and realized she could support her teammate, help fill in the gaps, and set her team up for success. For example, in a meeting, when she or someone mentioned the name of a vital stakeholder, she would be sure to mention that person’s position because she knew her teammate needed that critical information. For that one team member, that slight difference motivated them to start reading on the train once again and rejuvenated their energy. Many forces can shift the energy of a team, some big and some small. In the Rocky Flats story, the employees went from feeling like heroes to having no purpose and feeling like criminals who did something wrong. The excitement turned to complaints, distrust, and mistakes. It felt just as impossible to turn around the morale as it did to clean up the site. Any team needs energized team members to perform at its highest potential. In Good Jane, Bad Jane, we see how team members must be accepted and not diminished based on perceived shortcomings. The Rocky Flats story takes away the employees’ purpose and meaning. As the investigations unfolded, the new contractors found themselves living a new plot line based on a different set of values, which induced a whole new set of emotions, motivation, and energy. Through those two stories, it becomes evident that energy is more than just motivation (Seeck & Diehl, 2017). Energy emerges from the team members’ connection to the purpose and through the relationships on the team. Team members need to be committed to and aligned around the team’s purpose (West & Anderson, 1996). Members will be more energized and aligned around the purpose if they interpret it as compelling (Kahn & Fellows, 2013). Thus, the holding environment needs to create cognitive social capital that shapes members’ understanding of the team and how they fit into the overall purpose (Hamel & Breen, 2007). Compelling, however, is in the eye of the beholder. Thus, to affect team members’ commitment to the team’s work, the holding environment must encourage framing the team’s purpose so that it connects to people’s emotions; it must also keep that purpose front and center (Henderson, 2021). For example, Steve Jobs, when Apple was building the early personal computers, framed the task not as building a computer but instead as changing the world. He also had each engineer’s name inscribed inside the case of the early Macintosh computers. This created cognitive social capital that helped employees interpret their work as highly meaningful. Another aspect of the environment that affects energy is how it shapes the meaning members attribute to their role on the team; can a member

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maintain their true identity as a member of the team (Kahn, 1990). When team members must hide part of their identity and cannot be their whole selves on the team, they are less energized and committed to their work. The team’s holding environment is instrumental in creating a context where team members do not have to sacrifice part of themselves; they can maintain their full identity. Thus, a value that the team crafts roles such that people are accepted and allowed to utilize their full range of talent will increase member commitment to that role. Energy is also affected by the character of relationships in the team, which involves the creation of relational social capital such as psychological safety and trust (Edmondson & Mogelof, 2006). When the environment generates these types of relational social capital, members feel connected and safe to be their authentic selves in the team (Edmondson, 2018). This is extremely important for innovation, which requires sharing and synthesizing different perspectives. If members do not feel safe, they will be reluctant to contribute their ideas. Safety is created when people feel understood, supported, and cared for (Kahn, 1990). A value that encourages inquiry into teammates’ needs, concerns, and perspectives helps team members feel known and understood. This directly affects their sense of belonging, a basic social need (Fiske, 2018). When people are not concerned about being rejected by the team, they focus their energy on the team’s work and away from, often disruptive, behavior designed to boost their sense of belonging (Clark, 2020). This is critically important to innovation because people are more willing to share ideas and put forth thinking the team may not initially accept. Finally, when people feel a sense of support, they are driven to reciprocate and are more psychologically available (Kahn, 1993). This channels energy into the team’s work and creates pro-social and citizenship behaviors that facilitate task accomplishment. Learning Don’t Break the Unbroken This is a common value among teams that feel like they are working well together, everyone is getting along, and their performance is viewed as good. One team we observed was operating on that value, and when a member of the team began to voice concerns, that team member was viewed as dysfunctional. The team squashed that team member’s concerns to force her back into the “don’t break what is not broken” space. They wanted that comfortable space back regardless of the unintended consequences that might result from trying to maintain their comfort. The leader asked the member to “stop disrupting” team meetings. After squashing the team member’s speaking up behaviors, new behaviors emerged, such as tapping

Inspired Teams  ⏹  15

their leg whenever the leader spoke, which later turned into pacing the room. Nothing on the team felt like it had before, the team’s usual way of operating could no longer exist, but they fought hard to try to get their “don’t break what is not broken” feeling back. They avoided trying new things or acknowledging the potential of failure, and never once were curious about the concerns being raised. They limited their success without realizing what they were doing. The environment accepted avoiding discussion of failures or potential areas of growth instead of accepting the difficult conversations needed to deal with potential failures or concerns head-on. In the Rocky Flats story, we can imagine that somewhere between 1951 and the beginning of the investigation and shutdown in 1989, some employees noticed problems; but the feelings of being patriotic heroes and interacting with the unspoken value of don’t break what is not broken could have led to an environment where curiosity and exploration were diminished and actions that needed to be taken were avoided. Innovation largely depends on an environment that encourages learning and exploration (West & Anderson, 1996), something so visibly missing from the stories shared above. The holding environment facilitates these characteristics by encouraging curiosity, experimentation, and risk-taking. “Curiosity is the desire to know, to see, or to experience that motivates exploratory behavior, information seeking, and learning” (Lievens, Harrison, Mussel, & Litman, 2022, p. 179), which are key behaviors that promote innovation. These behaviors, however, have an emotional consequence; taking a risk to experiment with something new is bound to lead to attempts that fail (Edmondson, 2018; Edmondson & Mogelof, 2006). Similarly, when trying something new, unforeseen challenges are bound to arise. How the team deals with these failures and challenges directly affects their resilience and ability to create breakthrough innovation (Scherr, 1989). Teams need an environment that encourages what Duckworth, Peterson, Matthews, and Kelly (2007) call grit, that is, passion and perseverance. The holding environment must generate cognitive social capital that attaches meaning to the inevitable challenges and failures that arise when taking a risk to try new things. When people do not fear failing and making mistakes, they are more resilient and more able to maintain their effort to find new ways to achieve their goals (Wang, Jones, & Wang, 2019). Execution Creating Value or Creating Individual Accomplishments A science and technology team was expected to innovate new solutions for active shooter threats. It was a team of brilliant science and technology experts, who each independently were exceptional at solving problems based

16  ⏹  S. B. WOLFF et al.

on their knowledge and expertise. They were trusted and highly regarded, so no financial or significant time constraints were given to the team. Each team member tackled the problem relatively independently and with little input from potential end-users or external stakeholders. Still, when they were expected to come together as a team and collectively use their creations in a simulated active shooter experience, their innovations failed miserably. The team created no ways of working across the team, which resulted in individual innovations, but together, they were impractical for the end-user. It was easier to execute the task individually than as a team, and it was easier to do it without input from the end-users, but it significantly affected the team’s ability to create value. The team failed to execute. In contrast, in the Rocky Flats Story, we saw how the team that was hired, intentionally took purposeful action by continually finding ways to create value and gain support from external stakeholders. As a result, they made over 200 technological innovations that dramatically improved their outcomes. Accomplishing the team’s task, especially innovation, requires more than energy and learning; the holding environment must facilitate the team’s work. In a holding environment, this means creating cognitive social capital that focuses the team on value-adding activity (Modig & Åhlström, 2012) and builds internal and external support for the team; it is not about prescribing task processes. In the Rocky Flats story, if they tried to use prescribed task processes, they would have limited their ability to be resilient, innovate, and accomplish the task. The Active Shooter Innovation Team never focused on collectively creating value-add, but each member assumed that their innovations would be a value add. By operating without internal and external support, they limited their ability to execute the mission. Teams often do not prioritize work by the value it creates for the organization. In a study of organizational resilience and responsiveness, Gartner found that workplace “friction,” that is, employees’ effort that does not add value, accounts for up to 66% of lost responsiveness (Gartner, 2020, p. 13). Unfortunately, the holding environment that most teams operate in does not encourage them to proactively identify and eliminate nonvalue-added work. This is de-energizing and frustrating because effort is spent with little return to the organization. A holding environment can be created to build cognitive social capital that creates a shared understanding of the importance of prioritizing work by the value it adds; as the Agile principle says, “The art of maximizing the amount of work not done—is essential” (Beck et al., 2022, n.p.). Connections to stakeholders outside the team, a form of structural social capital, are instrumental for innovation in a team (Hülsheger, Anderson, & Salgado, 2009). These connections serve multiple purposes; they expose team members to new ideas and they create relationships that support value creation by helping to gain acceptance for the innovation.

Inspired Teams  ⏹  17

Even if the work is sufficiently prioritized to add maximum value and the team is supported by its stakeholders, team members must create trust among themselves, a form of relational social capital. Trust supports execution by freeing up resources that might otherwise go into checking up on one another. One way trust is created is by demonstrating the integrity to make and keep promises (Brothers & Kumar, 2015). For the team to execute at the highest levels, team members must have confidence that their teammates will keep their commitments, ask for help when needed, and proactively address any commitments they may be unable to meet. Paralleling the need for individuals to demonstrate integrity and follow through on their commitments, the team needs to follow through on its intentions and agreements. As the team learns, and agrees on how it can improve, it must turn intentions into behavior. For example, a team may intend to operate with certain values and agree on norms to enact those values. This, however, is not as easy as it sounds; it often requires changing habits, and, as we know, old habits die hard. To help catalyze the development of new habits that improve execution, the team can create rituals and tools (structural social capital), as well as language and distinctions (cognitive social capital), that help it follow through on its agreements. For example, one process often used in innovation is brainstorming. This process requires that team members do not shoot down ideas. IDEO, an industrial design firm, created a tool whereby they gave each team member a nerf blaster. If someone noticed a teammate shooting down an idea, another team member would shoot them with the nerf blaster (Druskat & Wolff, 2001), which served to remind them of the team’s agreement. This is a fun tool that catalyzes development of the agreed-to habit of not shooting down ideas during brainstorming. This is just one example of a tool that a team can create to safely remind them of, and reinforce, the norms they agreed to. Transparency Full Transparency or Selective Information Sharing A Silicon Valley start-up team won a contract they had bid on. Each team member was known for their expertise and for “getting the job done.” The team members knew each other, but they had never officially worked together as a team. They never set norms for sharing information or working together, so a trail of miscommunication ensued that led the team to failure. Each team member shared what they were working on in emails, but no one could be confident that the information they were sharing was what team members needed. They were sharing what they wanted to share, and often, the information was intended to make them “look good.” Many times teammates ignored the emails and kept doing their tasks. When they

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would come together with their client, they would argue in front of them. When team members left the meeting, they did not argue about fixing the negative impact they were having on each other’s parts; but instead, they expressed their anger about undermining each other’s expertise in front of the client. The team members would double down that their approach was right, and to protect their status, they continually shared less and less information. They shared what would make them “look good” to their client but failed to share what the team actually needed to accomplish the task. The only candid conversations played out in front of their client. The project ultimately failed with a loss of 56 million dollars; the start-up lost future contracts with the company, and team members started having a negative influence on other work teams. In the Rocky Flats story, we see how information was not shared across the organization. Each silo understood a piece of their environmental impact, but they withheld information that would allow them to take more purposeful action. They didn’t value authentic conversation but rather valued maintaining their patriotic heroes status. The needed level of openness required psychological safety that did not exist within that project, which ultimately led to a complete failure. Innovation has been conceived of as information processing (Nijstad et al., 2019), whereby individual resources are combined to create a collective product. You might say information is the lifeblood of innovation; without accurate and diverse sources of information, there can be no meaningful information processing. In both stories shared above, the flow of information, or lack thereof, led to epic failures. There are virtually infinite sources of information available to a team, most irrelevant to its task. The holding environment creates cognitive social capital that helps the team pay attention to relevant information and can ease emotional distress the information may cause, allowing the team to make sense of it without distortion (Huy, 1999). Information resides at three levels within a team. Individuals possess knowledge and expertise, but they also contain an array of physical and emotional information, which they may not consider relevant to the team. For example, we have all heard of the term “gut feeling,” but different cultures value this information to a greater or lesser extent. Gut feeling, however, has a neurological basis and provides valid information about what is happening in our environment (Blake, 2018). This is crucial information for the idea generation phase of innovation. The holding environment must create cognitive social capital that helps team members frame their emotions and “gut feel” as valid information and encourages them to be candid about their thoughts and feelings. When team members do not share what they are sensing, it deprives the team of information necessary for both the task of innovation and illuminating how the team can perform and interact more effectively.

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To function at high levels, team members must not only value essential sources of information, they must candidly share information, especially their felt sense and perspective. Candor requires relational social capital, especially psychological safety, so people will be willing to share their thinking and question the status quo (Edmondson & Mogelof, 2006). The values of Transparency create cognitive social capital that encourages candor; the relational social capital needed to facilitate candor is built mainly with the energy set of values. The second level of information is the team level. At this level, the team needs to create a shared sense of itself, its processes, team member performance, and its work product to learn and continually improve. In a study by Drach-Zahavy and Somech (2001) studying antecedents to innovation, they found that team learning was highly correlated to innovation. To facilitate learning, the holding environment must create cognitive social capital that creates a shared belief that team reflection is important and structural social capital that makes reflection a standard way of operating. A well-known example of this occurs in military teams, especially the Navy Seals, where they review each operation after action (Willink & Babin, 2017). This helps the team learn, which leads to process innovation as they discover new ways of operating. The third level of information is the external level. To create new products and services that are accepted in the market, the team needs to be connected to its customers and the environment; this makes customer needs visible, but it also brings in new perspectives that can help the team see possibilities it was previously blind to. By valuing external connections, the holding environment facilitates building structural social capital, that is, the network of external relations that connects the team and its members to the external world. Information that is not shared or available to the team becomes a barrier to both innovation and overall team effectiveness. For example, when information about where a team stands in relation to performance goals is made visible, it serves as an early warning system that creates awareness of when the team is off course. The holding environment can generate cognitive social capital that creates a mindset that making information visible is valuable. In fact, some organizations do this to such an extent that typically private information, such as salaries, is made visible to all, and errors, often kept hidden, are publicly discussed (Edmondson, 2018). Holistic Look at Inspired Team Values and Social Capital The team hired to turn around the Rocky Flats Mission was constantly learning, sharing information, building energy as they progressed towards

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their goals, and effectively taking purposeful action, enabling them to surpass their intended outcomes. Being an inspired team, they made the impossible, possible. Creating the right environment increases the possibility of team innovation. Creating the wrong environment induces fear of mistakes, fear of being authentic, a lack of commitment or engagement, limiting the team’s innovation capabilities. Creating the conditions for innovation requires a deliberate focus on building a holding environment where team members can learn, be transparent, build energy, and execute effectively. Table 1.2 depicts the values discussed above and shows their influence on the three types of social capital. Operating in an environment guided by these values will lead to interaction that unleashes the power of your team. TABLE 1.2  Inspired Teams Values and Associated Social Capital They Create RELATIONAL (Nature & Quality of Relationships)

COGNITIVE (Shared Understandings)

Example from Claridge (2018)

• Trust and trustworthiness • Psychological safety • Obligations and expectations • Identity and identification

• Shared language, codes, and narrative • Shared attitudes, values, and beliefs

• Network ties and configuration • Roles, rules, precedents, and procedures

Energy

• Understanding (knowing your teammates well enough to work effectively together) • Caring (support, validation, acknowledgment) • Acceptance (accepting teammate’s whole self)

• Purpose (shared understanding and commitment to the team’s work)

• Acceptance (crafting roles to fit the person)

Learning

• Failure (forgiveness when something goes wrong or there has been a transgression)

• Failure (shared meaning placed on failure) • Optimism (mindset of possibility when facing challenges) • Curiosity (a shared value that drives experimentation)

• Experimentation (process used to learn and deal with “not knowing” and uncertainty)

STRUCTURAL (Social Structure)

(continued)

Inspired Teams  ⏹  21 TABLE 1.2  Inspired Teams Values and Associated Social Capital They Create (continued) RELATIONAL (Nature & Quality of Relationships)

COGNITIVE (Shared Understandings)

STRUCTURAL (Social Structure)

Execution

• Integrity (expectation about how promises are managed) • Proactivity (expectation to identify and eliminate low-value work and anticipate and address challenges)

• Catalysts (language • Catalysts (rituals and and distinctions to tools to help team support discussion follow through on and expression) intentions) • Stakeholders (mindset • Stakeholders that connection (relationships to stakeholders is for support and important) resources) • Proactivity (system to prioritize work)

Transparency

• Candor (expectation that team members will be authentic and candid)

• Reflection (shared belief that team should reflect on individual and team performance) • Visibility (shared belief that information should be visible and available)

• Reflection (rituals to foster reflection) • External (creating ties to customers and gathering external/market information)

Note: Some values are shown in more than one column. This is because the relation is not linear or causal. Some aspects of operating with a particular value can have effects on different aspects of social capital.

Living these values to create a holding environment requires experimentation, but ultimately your team can have a mood of possibility, ambition, and excitement as they push towards their goals. Living the values creates the foundation for generating a team that can make the impossible possible. PRACTICAL IMPLICATIONS Because a holding environment is a gestalt, it cannot be created by focusing, singly, on the parts. The path to creating a holding environment is nonlinear. You cannot say, A → B → C, so to get to C, I will start by focusing on A. The holding environment is created by the being—what is valued, what is paid attention to, what is believed—of those who interact to create the environment, not by their doing (Deci, Connell, & Ryan, 1989). When being is not aligned with action, people sense it; this is the body’s intelligence. They may not articulate what they feel, but it drives their behavior. People perceive the disconnect and lack of genuineness even though intentions

22  ⏹  S. B. WOLFF et al.

may be good. Well-meaning leaders, trying to do the right thing, but operating from a misaligned being can do more harm than they do good. On the other hand, people are forgiving. When leaders can be vulnerable, admit they are trying to change how they lead, that they will make mistakes, and they are looking to those they lead to help them on their journey, people will join them, forgive them, and support them because they are being genuine (Lencioni, 2003). This means that leaders must be self-aware and honest about who they are; they must be in touch with their being before they can shape the holding environment for the team. Although this may sound difficult to some leaders, the good news is that because a holding environment is a gestalt, leaders can begin where they are comfortable; the values can be implemented in small steps, one or two values at a time. As leaders progress to building different aspects of the holding environment, they may come to inspired team values they are less comfortable with. Even this can be approached in a way that minimizes discomfort. Because the holding environment is the product of everyone’s interaction, the responsibility to build it falls on everyone, not just the leader. If the leader can be a bit vulnerable and let the team know of their discomfort, they can suggest an experiment (an inspired team value in itself) to test a set of norms that embody the value. If the experiment does not work well, the experiment ends and the team can try something else. Not committing to the experimental norms eases the potential anxiety of trying something new and not knowing if it will succeed. When leaders express their concern about implementing a particular value, they build trust; by enlisting the team’s help to enact the values, the team will own the development of its holding environment. Every team will create a unique set of norms to enact a particular value that is right for its particular combination of personalities. Some practical tips for creating this holding environment include: 1. Be intentional and consistent. Your team’s environment will develop whether you pay attention or not; don’t allow your team’s environment to develop by chance. One way to ensure consistency is to take 5 minutes to focus on one of the values at each meeting; significant change happens in small steps (Fogg, 2019). 2. Use a question to start a discussion around the chosen value. The discussion will help create a shared understanding and agreement about expected behavior. These conversations turn the values into norms that guide interaction. For example, a question that might help the team agree on norms to embody the value of caring is: “How do we want to support each other to be our whole and best selves?” 3. Every interaction reinforces or diminishes the values by which the team operates. Enlist the team to help build the holding environment. To do this, the team needs to understand the inspired teams

Inspired Teams  ⏹  23

framework of values and, through discussion, agree on those values, or modify them to better suit the team. Then they need to agree on the behavioral norms to enact those values. Team members must then be empowered to share when they sense the team is, or is not, operating under the agreed to values. For example, suppose the team has agreed to support each other’s success. In that case, a team member who notices another team member is not contributing to a brainstorming session might make the observation, “I notice Joe has been quiet, and we have not asked for his perspective. Is that OK?” This helps the team reflect on its supportive behaviors and raises awareness about how it is interacting. The ensuing discussion helps reinforce the value, assuming the team still wants to be guided by it. 4. Because the values of the holding environment work together and lead to emergent patterns of behavior, when problems arise, it is often easier and more productive to focus on the values that comprise the holding environment than to address the behaviors directly. For example, we have observed that conflict often results from problems in the values of understanding and caring. When people don’t understand each other, they make up stories, leading to passing judgment. When people are judged and not supported, it leads to resentment and conflict. Once the values of understanding and caring become a vital part of the holding environment and guide interaction, many conflicts simply disappear. Another implication of the inspired teams framework is that teams may have more control over their performance than typically considered in the literature. As we mentioned above, the innovation literature focuses on organizational conditions for innovation. While the organization’s environment plays an important role, teams in the same environment have different performance levels. There are many possible reasons for this; however, in our experience, a significant factor is the holding environment the team has created. For example, we have observed that high-performing teams have greater external support; however, underlying that support is proactivity. It is not that high-performing teams somehow manage to get more support from leadership; instead, they go out and get it. Their holding environment values doing what it takes to get the job done, that is, proactivity. Average teams are passive and play the victim; they wait for support and complain when it is not forthcoming. The inspired teams holding environment is an environment that creates resilience and commitment to the team’s purpose. When something gets in their way, they take action to overcome it. This is not to suggest that the organizational environment is not essential, just that its effect on team innovation can be magnified (or

24  ⏹  S. B. WOLFF et al.

mitigated if unhelpful) by helping teams learn to intentionally take responsibility to create a holding environment that supports their purpose. FUTURE RESEARCH To fully capture the implications of this framework, more integrative research on the human and cognitive side of innovation within the organizational context is needed, especially at the team level. There is a balance of skills, expertise, and experiences that will help speed up the path to innovation in teams. Still, there will never just be one path to innovation, so maybe the focus should not be on one thing in isolation but rather on the paths that create more possibilities for innovation. Using the inspired teams framework as a lens to observing and researching teams can support more integrative research. As more interdisciplinary research teams explore innovation in organizations, we will create the space for understanding the parts and the whole to gain insights yet to be discovered. More practically, this framework needs to be researched across teams in organizations to determine the validity and reliability of its intended purpose to support teams in setting values and norms that create the space where innovation thrives. CONCLUSION We started this chapter wondering how teams that express innovative behavior strategies like those in the Rocky Flats story are created. Throughout the rest of the chapter, we connected literature, research, and experience to argue that innovation occurs at the team level and that innovation outcomes are enhanced when the team creates a holding environment that builds social capital. This is accomplished by injecting key values that guide team member interactions to enhance innovation. Although the innovation literature recognizes the effect of team culture on innovation, there is no comprehensive framework of values that helps teams influence the human factors that affect innovation. Widmann and Mulder (2018) posit we need a deeper understanding of affective team behavior processes in innovative work behavior. This chapter presented the inspired teams framework as a guiding reference for creating a holding environment in support of that call and to further enable innovative behavior in teams. Embedded in any team is the possibility of innovation, but whether that possibility becomes realized is dependent upon the behavioral strategies enacted. Any team that seeks to embody behavioral strategies to facilitate innovation would be well informed by utilizing the four sets of values—energy,

Inspired Teams  ⏹  25

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CHAPTER 2

STRATEGIC BEHAVIORS OF LEADERS IN OPEN INNOVATION The Role of Ambidextrous Leadership and Entrepreneurial Behaviors Parisa Haim Faridian Kathryn E. Weaver

ABSTRACT Current leadership theories rarely provide integrative frameworks that explain complexities associated with leading both exploration and exploitation activities from an open system perspective. To address this research gap, this study examines leadership emergence and effectiveness in the context of open innovation (OI). Thus, we investigate how technical and social contributions of emergent leaders result in leadership styles that support effectiveness in achieving both entrepreneurial and innovational outcomes in OI? By discussing how OI leaders emerge and achieve outstanding outcomes, despite significant challenges associated with this context, this study evokes leadership research in better understanding the complexities and impact of straInnovation and Behavioral Strategy, pages 29–51 Copyright © 2022 by Information Age Publishing www.infoagepub.com All rights of reproduction in any form reserved.

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30  ⏹  P. HAIM FARIDIAN and K. E. WEAVER tegic approaches of leaders in regulating behaviors of diverse actors in OI. Further, this study offers insights into managing nuances of cultivating an environment conducive to innovation by adopting different styles of leadership. Lastly, by incorporating strategic entrepreneurial behaviors, such as opportunity recognition, in addition to ambidextrous leadership style, this study sheds new light on managing the challenges associated with aligning different strategic foci associated with innovation.

INTRODUCTION The digital age has witnessed the prevalence of novel approaches to collaborative innovation (Chesbrough, Vanhaverbeke, & West, 2006; Gassman, Enkel, & Chesbrough, 2010; West & Bogers, 2014). This shift in knowledge-asset creation is evident in the increasing popularity of new forms of innovation networks and ecosystems consolidated under the construct of open innovation (OI; Birkinshaw, Hamel, & Mol, 2008; Chesbrough, 2004; Yoo, Boland, Lyytinen, & Marjchrzak, 2012). Open innovation represents the dual focus on accelerating the development of innovation and expanding markets for external use of innovation (Chesbrough, et al., 2006). Open innovation relies on systematic internal and external exchange of knowledge; namely, inbound and outbound OI. However, current leadership theories rarely provide integrative frameworks that explain complexities associated with leading both exploration and exploitation activities from an open system perspective. To address this research gap, this study examines leadership emergence and effectiveness in the context of OI. Thus, we investigate: “How do technical and social contributions of emergent leaders result in leadership styles that support effectiveness in achieving both entrepreneurial and innovational outcomes in OI?” By discussing how OI leaders emerge and achieve outstanding outcomes, despite significant challenges associated with this context, this study evokes leadership research in better understanding the complexities and impact of strategic approaches of leaders in regulating behaviors of diverse actors in OI (e.g., volunteer innovators, unaffiliated actors, and organizational members; Fleming & Waguespack, 2007; Garud & Karnoe, 2003). Further, this study offers insights into managing nuances of cultivating an environment conducive to innovation by adopting different styles of leadership. Lastly, by incorporating strategic entrepreneurial behaviors, such as opportunity recognition, in addition to ambidextrous leadership style, this study sheds new light on managing the challenges associated with aligning different strategic foci associated with innovation. This study is structured in six sections. The first section describes what we know about leadership in OI. More specifically, this section discusses how innovation networks have increased globalization and how understanding leaders’ roles in such a context is valuable. The second section

Strategic Behaviors of Leaders in Open Innovation  ⏹  31

provides an in depth look at the current state of research on OI strategic leadership, including an exploration of research gaps and deficiencies in the literature. The third section provides an integrative model of leadership in OI focusing on the emergence of ambidextrous leadership and the effectiveness of entrepreneurial behaviors as related to OI. The fourth section then discusses implications for theory and methodology, specifically focusing on implications for leadership and innovation literature as well as potential methodological challenges of related research. The fifth section explores the future of leadership research in OI and makes several suggestions for emerging research questions. We end with a conclusion on how our study cross-pollinates the three fields of leadership, innovation, and entrepreneurship to offer a comprehensive view of complexities of leadership behavior in the age of globalization and information. LEADERSHIP IN OPEN INNOVATION Innovation Networks and Globalization The technological advancements of the information age have exacerbated the complexity of the organizations’ practice and theory by expanding the horizon to include novel aspects to organizational studies ranging from organizations as instruments of globalization and information capitalism and inequality, to ambassadors of socio-technical change and virtual co-creation of value (Haim Faridian, 2015). In specific, proliferation of IT has led organizations to embrace the open-system model that advocates a network theory of organizational ecosystems, thriving and collaborating on a global scale (Ahuja & Carley, 1998; Pickering & King, 1995). As a result, novel approaches to developing and appropriating innovation across organizational boundaries have gained prominence (Gassman et al., 2010; West & Bogers, 2014; West & Gallagher, 2006). This shift in knowledge-asset creation is evident in the increasing popularity of new forms of innovation networks and ecosystems, including open source communities and crowdsourcing innovation platforms (Birkinshaw et al., 2008; Chesbrough, 2004; Yoo et al., 2012). Linux, Ubuntu, Firefox, WordPress, and Elon Musk’s SpaceX are a few examples of OIs developed in networks that allow an open transfer of knowledge across network boundaries. The most basic form of OI, found in open source communities, features a network of programmers that voluntarily contribute to development of software without expectations of monetary rewards. These communities are commonly organically formed and thus adopt informal and fluent structures that lack hierarchical authority (Fleming & Waguespack, 2007; O’Mahony & Ferraro, 2007). The global pandemic has fueled the

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prevalence of open source, to the extent that open source project creation on GitHub, the most popular social coding and project hosting service, jumped by up to 40% year over year in 2020 (Forsgren, 2020). Leaders in Knowledge Economies As the global business landscape changes, organizational roles have evolved accordingly, in order to correspond to the new demands imposed by the complexity of new environments and contexts. Amongst organizational roles, leadership is central in adapting to new changes and ensuring viability of organizations. In addition to the traditional operational roles, in interorganizational networks, leaders are expected to build information capital through interactions and collaboration of organizations. Effectiveness of leaders in managing this ongoing exchange of organizational knowledge and resources improves economic performance by fostering collaborative innovation inside the network (Haim Faridian & Neubaum, 2021). In that sense, leading OI has evolved to include strategic and entrepreneurial, as well as innovational, foci. However, OI presents unique challenges and opportunities to (a) leadership associated with managing transient members and (b) unaffiliated innovators with varying motivational incentives attempting to lead through unorganized formal structures and bureaucratic functions.. The meritocratic nature of governance in OI means that innovation leaders emerge by virtue of their technical and social capabilities (Fleming & Waguespack, 2007). However, successful emergence of leaders does not guarantee their effectiveness in appropriation and commercialization of innovation, which is contingent upon entrepreneurial and business expertise. This paradox has forced open source leaders to adopt new roles, which requires expertise that diverge from the traditional scope of their role, such as acting as the keystone in communities (Chesbrough & Crowther, 2006; Enkel, Gassman, & Chesbrough, 2009; Jansen, Vera, & Crossan, 2009; Von Hippel, 2001; Von Krogh, Spaeth, & Lakhani, 2003). CURRENT STATE OF RESEARCH ON OPEN INNOVATION LEADERSHIP Leadership Literature and Innovation Embracing the new trends in innovation practice, the interest in research on OI has increased considerably in the past 2 decades. This increased interest is evident in the exponential increase of the number of citations over the past years. Figure 2.1 illustrates the number of times that publications

Strategic Behaviors of Leaders in Open Innovation  ⏹  33

relevant to OI1 have been cited by other publications in the Dimensions database between 2002 and 2021. In contrast, despite the significance of leadership in OI context, this emerging area of inquiry is at its infancy stages. As Figure 2.2 illustrates, while research in this area has gained more interest in the past 2 decades, the relevant record of publications2 remain 1,000

Publications in Each Year

900 800

Criteria: Text—“open innovation” in title and abstract

700 600 500 400 300 200 100 0

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Year

Figure 2.1  Publications in open innovation. Source: 2022 Digital Science and Research Solutions Inc. Dimensions at www.dimensions.ai 30 28

Publications in Each Year

26 24

Criteria: Text—“‘open innovation’ leader” in title and abstract

22 20 18 16 14 12 10 8 6 4 2 0

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Year

Figure 2.2  Publications in open innovation leadership. Source: 2022 Digital Science and Research Solutions Inc. Dimensions at www.dimensions.ai

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considerably limited. Despite the stark contrast, both areas of inquiry have witnessed the highest rate of increase in the past few years. Because of the meritocratic nature of power in OI governance, the literature in this area is more concerned with the emergence of leaders than their effectiveness. Overall, leadership emergence is defined as the processes that result in perceiving an individual as being leader-like (Ilies, Gerhardt, & Le, 2004), and leadership effectiveness as performance of emerged leader that impacts achievement of organizational goals (Judge, Bono, & Ilies, 2002). Open innovation literature attributes emergence of leadership to two general categories of contributions; namely, technical and social contributions. Technical contributions in OIs are highly dependent on individuals’ technical skills and their desire and motivation to contribute to the organic development of innovation. Social contributions constitute two strategic behaviors of boundary spanning and brokering. Fleming and Waguespack (2007) define brokers as individuals who connect actors and exploit structural holes in their favor. Conversely, boundary spanners are defined as individuals who contribute to dispersion of information within and across initiatives. In that sense, brokers are considered politically savvy actors, and boundary spanners as guardians of information flow and dispersion (Fleming & Waguespack, 2007). However, more recent studies on leading GitHub blockchain open source projects show that technical contributions of leadership have little influence on open, collaborative innovation success. In contrast, internal and external social capital contributions were found to be impactful. Ultimately, the joint effect of technical and internal social capital, in addition to a commitment to the community’s openness orientation, had the most significant impact on OI success (Mu & Wang, 2020). The effectiveness of leaders in innovation context in general has been studies in terms of their styles of leadership. The literature on leadership in context of innovation has long advocated transformational style of leadership as the driver for motivating individuals to step outside their job tasks and engage in innovative activities (Bass, 1999; Keller, 2006). However, in the context of OI where tasks are commonly vaguely defined and ordinary job-related tasks outside innovation requirements may not exist, transformational leadership by itself may not result in leadership effectiveness in market and institutional domains. Further, geographically dispersed and informal structures common in OI contexts warrant leadership styles that compensate for the lack of face-to-face interaction by creating an environment that is supportive of motivational needs such as need for relatedness. Acknowledging the need for different styles of leadership in innovations has gained more weight in recent years. A strong stream of literature investigates the importance of ambidextrous leaders in innovative organizations (Mumford, Hunter, & Byrne, 2009; Rosing, Frese, & Bausch, 2011).

Strategic Behaviors of Leaders in Open Innovation  ⏹  35

Ambidextrous leaders in the context of innovation are defined as leaders that balance operational related tasks with innovational related ones (Mumford, Hunter, & Byrne, 2009). Rosing et al. (2011) discuss heterogeneity of leadership styles in innovation context through a meta-analysis that shows different styles are not always negatively or positively correlated with innovation. The extant of research on the effect of transformational leadership on innovation shows that in order for transformational style to be effective it needs to be practiced in an environment that is supportive (Eisenbeiss, van Knippenberg, & Boerner, 2008; Jung, Wu, & Chow, 2008). Supportive environment is defined as one that advocates goal attainment and high level of performance standards, which are associated with transactional style of leadership. Research findings on the impact of transactional leadership styles in managing innovation have also led to contradictory results (Dayan, Di Benedetto, & Colak, 2009; Jansen et al., 2009; Lee, Park, Park, & Yoon, 2010). Based on their meta-analysis, Lowe, Kroeck, and Sivasubramaniam (1996) explain this contradiction by suggesting that the effect of transformational style on explorative objectives and transactional styles on exploitative objectives is contingent upon moderating factors. This assertion is supported by empirical studies. For instance, Jansen et al. (2009) showed that while under conditions of highly dynamic environments, transactional leadership and exploratory objectives are shown to correlate negatively; in a stable environment the correlation is positive. The predominant theoretical approach in this area links transactional and transformational styles to exploitive or explorative objectives, respectively. However, more relevant studies to OIs context investigate additional outcome measures that reflect leadership emergent and effectiveness performance more clearly (e.g., quality and quantity of innovation, monetization, and expansion of initiative). Dayan et al. (2009) examines the correlation between transactional and transformational leadership and two criteria of product success and speed-to-market. In the context of OIs, quantity and quality of innovation represents product success, while monetization strategies influence speed-to-market. Dayan et al. (2009) suggests a positive association between transactional leadership style and product success, and a non-significant relation with speed-to-market. Conversely, transformational leadership style is positively associated with speed-to-market. Keller (2006) also reports a positive relationship between transformational leadership style and speed-to-market. An adjacent area of research on a hub-based innovation ecosystem focuses on the assumption of leadership by a single firm that influences strategies of others in the ecosystem. An example is Apple’s iPhone ecosystem. Organizations in hub-based ecosystems must manage conflicts between goals and objectives of the ecosystem and those of their own.

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More recent research has investigated the impact of sub-types of transformational style on OI. For instance, Mu, Bian, and Zhao (2019) found taskoriented leadership behaviors have minute influence on open collaborative innovation success, while relation-oriented leadership behaviors contribute significantly to open collaborative innovation. Naqshbandi, Tabche, and Choudhary (2019) found that empowering leadership supports exploration, integration, and diffusion of knowledge in OI through the mediating effect of an employee involvement climate. Knowledge-oriented leadership has been found to positively influence OI outcome through the mediating effect of knowledge management (Naqshbandi & Jasimuddin, 2018). Research Gaps and Deficiencies The current leadership theories rarely provide integrative frameworks that explain complexities associated with leading both exploration and exploitation in OI. Further, while literature on OI focuses on factors for the emergence of leaders; namely, technical and social contributions commonly described as value creation, it fails to recognize leadership effectiveness in capitalizing on innovation; namely, value capturing. As a result, OI literature in general fails to adequately identify the link between leadership emergence and effectiveness that explains how innovational factors related to emergence lead to entrepreneurial factors related to effectiveness of leaders in this context. Some of the most recent research findings question the traditional view of criteria for emergence of leaders in OI (Mu et al., 2019). More importantly, recent research contradicts the general understanding of the positive effect of both transactional and transformational styles of leadership on innovation. For instance, Jia, Chen, Mei, and Wu (2018) found a negative effect on transactional leadership on organizational innovation performance, while breadth and depth of openness mediate this relationship. Lastly, studies that investigate various attributes and dimensions of transformational and transactional styles of leadership on OI are also scarce (Naqshbandi et al., 2019). INTEGRATIVE MODEL OF LEADERSHIP IN OPEN INNOVATION The integrated framework of OI leadership proposed in this study is postulated in two phases of emergence and effectiveness that, although distinct, are linked and using concepts of ambidextrous and entrepreneurial leadership. In this study rather than utilizing the common approach in linking transactional and transformational styles to exploitive or explorative

Strategic Behaviors of Leaders in Open Innovation  ⏹  37

Contributions

Technical

Social Boundary-Spanning

Social Brokering

Emergence of Ambidextrous Leadership Transactional Leadership Contingent reward Management by exception— active Management by exception— passive

Transformational Leadership Inspirational motivation Challenging expectations Intellectual stimulation Individualized consideration Idealized influence

Effectiveness of Entrepreneurial Behaviors Opportunity Exploitation Behaviors Monetization Quality and Quantity of Innovation

Opportunity Exploration Behaviors Expansion of the Initiative

Figure 2.3  Integrative model of open innovation leadership.

objectives, respectively, we use three outcome measures that are more relevant to OI contexts; namely, quality and quantity of innovation, monetization, and expansion of initiative. The leadership styles that support both innovational and entrepreneurial outcomes, transactional and transformational, respectively, emerge as a result of social and technical contributions (see Figure 2.3). Emergence of Ambidextrous Leadership Central to the framework in this study are leadership styles and behaviors that ensure three contributions for emergence of leaders: technical, boundary spanning, and brokering contributions. We generalize the array of strategic leadership behaviors under two generic styles of transformation and transactional. Transformational Leadership Transformational leadership is viewed as a process that involves empowering followers to change and pursue predetermined objectives (Bass, 1999; Burns, 1978). Five distinct behaviors are commonly associated with transformational leadership including: an idealized influence of the leader acting as a role-model, considerations for individual development, inspirational motivation, intellectual stimulation of the follower, and performance beyond what is expected (Wang & Rode, 2010).

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Idealized influence dimension of transformational leadership refers to leaders behaving in admirable ways to encourage followers to identify with them. Such leaders provide an appropriate model for followers by showing conviction and appealing to them on an emotional level. Inspirational motivation demands leaders to articulate ideas in a manner that are appealing and persuading. Challenging expectations refers to leaders attempting to challenge followers and holding them to high standards, while communicating optimism about future goals, and providing meaning for the task at hand. In short, the three dimensions of idealized influence, inspirational motivation, and challenging expectations require leaders to establish their power and social influence in OI contexts (House & Aditya, 1997; House, Howard, & Walker, 1991). Social brokerage activities, on the other hand, aim to facilitate control networks and oneself position by connecting actors and exploiting structural holes for self-serving purposes (Fleming & Waguespack, 2007). By conducting social brokerage activities, candidates obtain techniques for socially influencing members to join the initiative that expands innovation in the institutional domain. Consequently, social brokerage activities are conducive to emergence of tendencies and behaviors associated with three dimensions of the transformational style of leadership—idealized influence, inspirational motivation, and challenging expectations—through improving the power position and influence of emergent leaders in OI. Proposition 1: Social brokerage behaviors influence the emergence of transformational leadership behaviors by strengthening their idealized influence, inspirational motivation, and challenging expectations of members in OI. The intellectual stimulation dimension of transformational leadership refers to leaders’ actions in challenging follower’s assumptions and encouraging them to take risks. Leaders possessing this behavior stimulate and encourage creativity in their followers. Conversely, individualized consideration reflects a leader’s concern about followers’ needs and acting as a “life coach” by listening to their “personal” concerns and needs. Such leaders provide individual support that best fit the specific needs of their followers. These two dimensions of transformational leadership require leaders to connect with the followers while pushing innovation objectives forward. In the context of OI, social boundary spanning activities provide the opportunity to interact with others while dispersing information across boundaries (Fleming & Waguespack, 2007). As interactions in OIs are commonly limited to impersonal computer mediated communications (CMC), social boundary spanning is perhaps one, if not the only, means of satisfying need for relatedness. Consequently, in OIs, membership and participation are often motivated by desire to gain knowledge and information, as these are the commodities commonly restricted by

Strategic Behaviors of Leaders in Open Innovation  ⏹  39

boundaries. By dispersing information across boundaries, leadership candidates establish relationships with others. Thus, boundary-spanning activities are conducive to emergence of tendencies and behaviors associated with two dimensions of a transformational style of leadership—intellectual stimulation and individualized consideration—by means of creating opportunities to interact with others while acquiring and dispersing knowledge. Proposition 2: Social boundary spanning behaviors influence the emergence of transformational leadership behaviors by intellectual stimulation and individualized consideration of members in OI. Transactional Leadership Transactional leadership was first introduced as the opposite end of transformational leadership (Burns, 1978). While transformational leaders offer a purpose that transcends short-term goals and focuses on higher order intrinsic needs—for example, personal and career development— transactional leaders focus on a simple exchange of resources related to basic extrinsic needs—for example, advice about how to improve the application of technical contributions (Kuhnert & Lewis, 1987). Further, while transformational leadership focuses on establishing a personal relationship, transactional leadership is mainly concerned with performing the basic tasks. Contrasting the early conceptualizations, more recent studies suggest that the relationship between transformational and transactional leadership may indeed follow an augmented effect. In that sense, transformational leadership builds on the simple exchange-oriented premises of transactional style and suggests that in addition to meeting basic extrinsic needs, leaders inspire followers towards fulfilling intrinsic needs and altruistic ends (Avolio, Walumbwa, & Weber, 2009; Judge & Piccolo, 2004). Three distinct behaviors are commonly associated with transactional leadership including: contingent reward, active management by exception, and passive management by exception. Contingent reward refers to leaders’ behavior related to setting up constructive exchanges with followers. The bases of these behaviors are rooted in clarifying expectations. Active management by exception refers to the proactivity of the leader in taking necessary actions in order to manage their interactions with followers. Active leaders monitor followers’ performance—anticipating and/or identifying problems. Subsequently, they take corrective actions before serious difficulties arise. Passive management by exception refers to leaders’ tendencies to wait until serious difficulties arise before taking actions, if any. Overall, exhibiting the three behaviors associated with contingent reward, active management by exception, and passive management by exception require leaders to first and foremost understand the nature of tasks and goals (Avolio, Walumbwa, & Weber, 2009; Judge & Piccolo, 2004).

40  ⏹  P. HAIM FARIDIAN and K. E. WEAVER

In the context of OIs, as it was discussed earlier, due to the poorly determined extrinsic rewards, and informal structure, technical contributions of volunteer developers are contingent upon their motivation and choice. By exercising autonomy in producing technical contributions, leadership candidates gain an understanding of how tasks can be designed and structured and goals can be set in order to best utilize available skills and achieve objectives despite the informal structure of initiative (Gange & Deci, 2005). As a result of focusing on structuring tasks and motivating available human resources to achieve innovation goals, leadership style that emerges as a result of technical contributions is expected to develop transactional leadership behaviors related to clarifying goals, and supporting the followers in achieving through passive and active management (Bass, 1999). In short, technical contributions are conducive to emergence of tendencies and behaviors associated with three dimensions of transactional style of leadership—contingent reward, active management by exception, and passive management by exception—through improving the knowledge of innovation dynamics, tasks, and goals of emergent leaders in OI. Proposition 3: Technical contributions influence the emergence of transactional leadership behaviors by providing an understanding of the innovation dynamics surrounding contingent reward, active management by exception, and passive management by exception of members in OI. Effectiveness of Entrepreneurial Behaviors In the second phase of the model, meaning leadership effectiveness, we discuss the impact of strategic entrepreneurial opportunity exploration and exploitation behaviors on achieving innovation outcomes. Critical challenges for network and ecosystem entrepreneurs have been discussed in terms of managing multiple and contradicting goals and recognizing innovation and growth opportunities (Nambisan & Baron, 2013). Addressing these challenges demands metacognition awareness and persistence on long-term goals including: performance/success goals, technology development goals, and relational goals (Nambisan & Baron, 2013). In this study, we investigate the link between entrepreneurial opportunity exploration and exploitation and three different forms of innovation outcomes: innovation monetization, quality and quantity of innovation, and expansion of OI initiative. Entrepreneurial Opportunity-Exploration Behavior The primary behaviors in achieving entrepreneurial goals and intentions involve opportunity search and exploration followed by opportunity exploitation (Shook, Priem, & McGee, 2003). Entrepreneurial exploration

Strategic Behaviors of Leaders in Open Innovation  ⏹  41

entails individual alertness to new opportunities. The behaviors in discovering opportunities are driven by individuals’ past knowledge about markets and how to serve markets and address customer needs (Shane & Venkataraman, 2000). Social boundary spanning activities provide an opportunity to increase interaction in OIs, as discussed earlier. Interactions across boundaries allow leaders to explore opportunities for new in-bound and out-bound innovations. Further, in the context of OI, where interactions are limited to computer-mediated communications, social boundary spanning improves relational job design and motivation for prosocial behavior through increased interaction amongst members on the basis of information exchange. Thus, by dispersing information to outside existing boundaries, leaders can actively explore opportunities for new collaborations, and subsequently expand OI initiatives. In short, transformational leadership behaviors in the form of engaging individuals across boundaries through information exchange mediated by opportunity exploration behaviors are expected to expand OI initiatives. Proposition 4: Social boundary spanning behaviors have an indirect effect on expanding OI initiatives in terms of exploring opportunities for cross-boundary collaborations through the practice of transformational leadership behavior. Similar to boundary spanning behaviors, social brokerage behaviors provide an opportunity to increase interaction in OIs, as discussed earlier. Social brokerage behaviors entail connecting individuals and filling structural holes in OI. While brokering new relationships, transformational leaders explore opportunities embedded in OI networks (Conger & Kanungo, 1987), reshaping the networks by connecting and moving members in a manner that improves network density. A number of studies have also reported a positive correlation between transformational leadership style and speed-to-market (Dayan et al., 2009; Keller, 2006). Thus, by connecting contributors in the network, leaders can actively explore opportunities for enriching human and social capital central to innovation processes and expanding OI initiatives. In short, transformational leadership behaviors in the form of brokering relationships among contributors in the OI mediated by opportunity exploration behaviors are expected to expand OI initiatives. Proposition 5: Social brokering behaviors have an indirect effect on expanding OI initiatives in terms of exploring opportunities for intra-network collaborations through the practice of transformational leadership behavior. Entrepreneurial Opportunity Exploitation Behavior Exploitation of entrepreneurial opportunities entails monetization of existing products and services (Shane & Venkataraman, 2000). Technical

42  ⏹  P. HAIM FARIDIAN and K. E. WEAVER

contributions help establish the social status of emergent leaders as experts in OIs (Podsakoff & Schriesheim, 1985). Such expertise assists leaders to set and clarify innovation goals, which are crucial in effectiveness of transactional leadership styles. However, in order to motivate OI members in achieving these goals, practicing the transactional style of leadership must involve creating a supportive environment that offers contingent rewards such as positive feedback and recognition and validation of contributors in the community. As OI leaders motivate members to achieve goals, the quality and quantity of innovation is expected to improve. Further, technical knowledge and expertise responsible for technical contributions of leaders can assist in setting higher standards for goals and objectives of OI, which in turn improves quality of innovation. Lastly, by managing technical contributions, leaders exploit resources central to monetization of innovation. In short, transactional leadership behaviors in the form of managing technical contributions in the OI mediated by opportunity exploitation behaviors improve quality and quantity of innovation and eventual monetization. Proposition 6: Managing technical contributions have an indirect effect on exploiting opportunities to improve quality, quantity, and monetization of innovation through the practice of transactional leadership behaviors in OI. IMPLICATIONS FOR THEORY AND METHODOLOGY Implications for Leadership Literature and Innovation The proposed model in this manuscript advances our understanding of how leaders emerge and achieve exceptional innovation performance in face of contextual challenges associated with the OI context discussed earlier. This manuscript aims to contribute to research and practice of leadership in general by offering a pragmatic and holistic view of leadership as a function of both transactional and transformational approaches and entrepreneurial strategic behaviors. By introducing integrative approaches that best represent complexities of contemporary contexts such as OI, the theoretical arguments in this paper incite leadership literature to embrace complexities of strategic leadership behaviors that deviate from traditional theories of leadership. Implications of this research for the field of innovation in general, and OI in specific are more significant. The research on leading OI initiatives remains disjointed and limited, as discussed earlier. Thus, the integrative approach offered in this study offers a direction for unifying this field of inquiry that holds great promise. The unifying approach offered in this study is twofold: first, aligning the strategic leadership behaviors at both stages of

Strategic Behaviors of Leaders in Open Innovation  ⏹  43

emergence and effectiveness, and second, strategizing value creation and capturing that represent the dual foci of OI. Methodological Challenges As existing research suggests, emergence and effectiveness of leadership styles in achieving innovation outcomes are commonly contingent upon underlying context-dependent processes. Consequently, in operationalization of propositions, such as those offered in this study, caution should be taken in consideration for contextual factors that can influence the results. For instance, environmental dynamism is commonly viewed as a moderating variable influencing innovation processes. Consequently, these methodological challenges might result in inconsistencies across findings in studies using samples from highly dynamic industries such as software, than from less dynamic ones such as hardware technologies. FUTURE OF LEADERSHIP IN OPEN INNOVATION Emerging Research Future research should further investigate the moderating effect of contextual and environment-based factors. To better understand how the environment can become supportive in OIs with respect to motivation, it is imperative to gain a general understanding of the contextual factors involved in OI, which differ from a traditional organizational context in a number of ways that are perhaps best explained by socio-technical theory. For instance, de-individuation that is caused by lack of face-to-face interactions may affect innovation outcomes suggested in this research in terms of motivation. Sociotechnical theories argue that reliance on CMC over a long period, isolates members and deteriorates group cohesion and members’ ability to identify with collective culture (Ma & Agarwal, 2007). De-individuation can impact the motivation to participate and contribute to OI initiatives, presenting an implication that should be addressed in future research. As discussed earlier, the scholarly interest in OIs has increased exponentially in the past 2 decades. As Figure 2.1 illustrates, the number of published articles with “open innovation” in the title and abstract has increased from zero in 2002, to a little more than 500 in 2012, and to more than 870 in 2021. However, the number of published articles with “open innovation” and “leader” in the title or abstract has not been as significant. As shown in Figure 2.2, there were only two articles in 2005 that focused on OI leadership. Since then, the research emphasis on leaders within OI contexts has been on a slight positive trend, yet still

44  ⏹  P. HAIM FARIDIAN and K. E. WEAVER

minimal. The largest increase was seen most recently from 2020 to 2021, where the number of publications jumped from 15 to 27. From this we can appreciate the field’s realization of the importance of understanding OI leaders. Similar trends are shown in Figures 2.4 and 2.5 on the academic impact of citations. Figure 2.4 reveals the increase in citations for those articles 25,000 22,500

Citations in Each Year

20,000

Criteria: Text—“open innovation” in title and abstract

17,500 15,000 12,500 10,000 7,500 5,000 2,500 0

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Year

Figure 2.4  Citations in open innovation. Source: 2022 Digital Science and Research Solutions Inc. Dimensions at www.dimensions.ai 400

Citations in Each Year

350

Criteria: Text—“open innovation” “Leader” in title and abstract

300 250 200 150 100 50 0

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Year

Figure 2.5  Citations in open innovation leadership research. Source: 2022 Digital Science and Research Solutions Inc. Dimensions at www.dimensions.ai

Strategic Behaviors of Leaders in Open Innovation  ⏹  45

with “open innovation” in the title and abstract. The exponentially increasing positive slope shows zero citations in 2002, a little over 2,500 citations in 2012, to more than 22,500 citations in 2021. Figure 2.5 reveals the increase in citations for those articles with “open innovation” and “leader” in their abstract and title. As shown, there were zero citations in 2002, 59 in 2012, and 380 in 2021. Figures 2.6 and 2.7 illustrate the number of publications in various research categories. As expected, publications in both areas of OI and OI leadership were published mostly in journals in the main category related to business scholarship; namely, commerce, management, tourism, and services. For publications on OI, information and computing sciences makes up the second largest research category of research. This pattern can be attributed to the strength of research on open source projects and high technology ecosystems and networks. The third largest research category in this area belongs to studies in human society. Open innovation presents a rich context 15 Commerce, Management, Tourism, an…

4,129

08 Information and Computing Sciences

1,118

16 Studies in Human Society

615

14 Economics

430

09 Engineering

226

10 Technology

193

11 Medical and Health Services

181

12 Built Environment and Design

160

18 Law and Studies

110

13 Education

94

17 Psychology and Cognitive Sciences

88

20 Language, Communication, and Culture

69

06 Biological Sciences

63

03 Chemical Sciences

40

01 Mathematical Sciences

36

07 Agricultural and Veterinary Sciences

29

21 History and Archaeology 22 05 Environmental Sciences 21 02 Physical Sciences 18 04 Earth Sciences 6

Criteria: Text—“open innovation” in title and abstract

22 Philosophy and Religious Studies 5 19 Studies in Creative Arts and Writing 4

Figure 2.6  Categories of research in open innovation. Source: 2022 Digital Science and Research Solutions Inc. Dimensions at www.dimensions.ai

46  ⏹  P. HAIM FARIDIAN and K. E. WEAVER 15 Commerce, Management, Tourism, an…

113

16 Studies in Human Society

20

08 Information and Computing Sciences

17

14 Economics

17

11 Medical and Health Services

5

20 Language, Communication, and Culture

3

09 Engineering

2

17 Psychology and Cognitive Sciences

2

06 Biological Sciences

1

07 Agricultural and Veterinary Sciences

1

10 Technology

1

12 Built Environment and Design

1

19 Studies in Creative Arts and Writing

1

21 History and Archaeology

1

Criteria: Text—“‘open innovation‘” leader in title and abstract

Figure 2.7  Categories of research in open innovation leadership. Source: 2022 Digital Science and Research Solutions Inc. Dimensions at www.dimensions.ai

for studying human collaborations and interactions in collectives such as communities, networks, and ecosystems, which offer a prime context for social studies. In contrast, for publications related to OI leadership the second largest research category belongs to studies in human society, while information and computing sciences makes up the third largest category. Studying leadership in this context offers valuable insights on emergence of leaders in meritocracies and through democratic processes, which appeals more to studies in human society than the area of information and computing science. Analysis of the co-authorship networks, as illustrated in Figures 2.8 and 2.9 demonstrate a decentralized pattern for both research areas of OI and OI leadership, with the most density of research taking place in Europe. Reinventing Strategic Role of Leaders While the trends discussed earlier demonstrate a strong potential for advancing research in this area, literature on leadership in OI are yet to be fully recognized for its significant implications in the mainstream management field. Although the contextual factors in OI differ from a traditional organizational context in a number of ways, this context reflects challenges and complexities associated with value-creation and capture in the knowledge economy. Thus, an OI context can lend valuable lessons to

Strategic Behaviors of Leaders in Open Innovation  ⏹  47

Figure 2.8  Network of co-authorship in open innovation.

Figure 2.9  Network of co-authorship in open innovation leadership.

48  ⏹  P. HAIM FARIDIAN and K. E. WEAVER

organizational research, specifically with respect to the role and behaviors of leaders. For instance, the subject of motivation warrants specific attention in the context of OI as these initiatives are representative of weak situations due to informal structure and uncertain and ambiguous tasks and roles (House & Aditya, 1997). Under complex and uncertain conditions, namely weak situations, individuals’ traits and dispositions, such as motivation, have a stronger influence on behaviors. Consequently, the emergence and effectiveness of individuals in open initiatives as leaders can be determined, to an extent, by individuals’ motivational dispositions. In short, the complexity of OIs that entails both social and technical aspects warrants considerations for different types of motivation for leadership roles. CONCLUSION This study aimed to address the gap in strategic leadership literature in terms of scarcity of application of open system perspective in offering integrative frameworks that explain complexities of leading both exploration and exploitation activities. To address this research gap, this study examined leadership emergence and effectiveness in the context of OI. More specifically, we investigated how technical and social contributions of emergent leaders in OI result in leadership styles that support their effectiveness in achieving both entrepreneurial and innovational outcomes. In doing so, this study evoked literature on leadership, innovation, and entrepreneurship, while cross-pollinating the three fields to offer a comprehensive view of complexities of leadership behavior in the age of globalization and information. NOTES 1. The sample represents publications with the keyword “open innovation” mentioned in the title and/or abstract. 2. The sample represents publications with the keywords “open innovation” and “leader” mentioned in the title and/or abstract.

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50  ⏹  P. HAIM FARIDIAN and K. E. WEAVER Ilies, R., Gerhardt, M. W., & Le, H. (2004). Individual differences in leadership emergence: Integrating meta-analytic findings and behavioral genetics estimates. International Journal of Selection and Assessment, 12(3), 207–219. Jansen, J. J. P., Vera, D., & Crossan, M. (2009). Strategic leadership for exploration and exploitation: The moderating role of environmental dynamism. Leadership Quarterly, 20(1), 5–18. Jia, X., Chen, J., Mei, L., & Wu, Q. (2018). How leadership matters in organizational innovation: A perspective of openness. Management Decision, 56(1), 6–25. Judge, T.A., Bono, K.E., Ilies, R. (2002). Personality and leadership: A qualitative and quantitative review. Journal of Applied Psychology, 87, 765–780. Judge, T. A., & Piccolo, R. F. (2004). Transformational and transactional leadership: A meta-analytic test of their relative validity. Journal of Applied Psychology, 89(5), 755–768. Jung, D. I., Wu, A., & Chow, C. W. (2008). Towards understanding the direct and indirect effects of CEOs’ transformational leadership on firm innovation. Leadership Quarterly, 19(5), 582–594. Keller, R. T. (2006). Transformational leadership, initiating structure, and substitutes for leadership: A longitudinal study of research and development project team performance. Journal of Applied Psychology, 91(1), 202–210. Kuhnert, K. W., & Lewis, P. (1987). Transactional and transformational leadership: A constructive/developmental analysis. Academy of Management Review, 12(4), 648–657. Lee, S., Park, J., Park, G., & Yoon, B. (2010). Open innovation in SMEs—An intermediated network model. Research Policy, 39(2), 290–300. Lowe, K. B., Kroeck, K. G., & Sivasubramaniam, N. (1996). Effectiveness correlates of transformational and transactional leadership: A meta-analytic review of the MLQ literature. Leadership Quarterly, 7(3), 385–425. Ma, M., & Agarwal, R. (2007). Through a glass darkly: Information technology design, identity verification, and knowledge contribution in online communities. Information Systems Research, 18(1), 42–67. Mu, R., & Wang, H. (2020). A systematic literature review of open innovation in the public sector: Comparing barriers and governance strategies of digital and non-digital open innovation. Public Management Review, 24(4), 1–23. Mu, W., Bian, Y., & Zhao, J. L. (2019). The role of online leadership in open collaborative innovation: Evidence from blockchain open source projects. Industrial Management & Data Systems, 119(9), 1969–1987. Mumford, M. D., Hunter, S. T., & Byrne, C. L. (2009). What is the fundamental? The role of cognition in creativity and innovation. Industrial and Organizational Psychology, 2(3), 353–356. Nambisan, S., & Baron, R. A. (2013). Entrepreneurship in innovation ecosystems: entrepreneurs’ self-regulatory processes and their implications for new venture success. Entrepreneurship Theory and Practice, 37(5), 1071–1097. Naqshbandi, M. M., & Jasimuddin, S. M. (2018). Knowledge-oriented leadership and open innovation: Role of knowledge management capability in Francebased multinationals. International Business Review, 27(3), 701–713.

Strategic Behaviors of Leaders in Open Innovation  ⏹  51 Naqshbandi, M., Tabche, I., & Choudhary, N. (2019). Managing open innovation: The roles of empowering leadership and employee involvement climate. Management Decision, 57(3), 703–723. O’Mahony, S., & Ferraro, F. (2007). The emergence of governance in an open source community. Academy of Management Journal, 50(5), 1079–1106. Pickering, J. M., & King, J. L. (1995). Hardwiring weak ties: Interorganizational computer-mediated communication, occupational communities, and organizational change. Organization Science, 6(4), 479–486. Podsakoff, P. M., & Schriesheim, C. A. (1985). Field studies of French and Raven’s bases of power: Critique, reanalysis, and suggestions for future research. Psychological Bulletin, 97(3), 387–411. Rosing, K., Frese, M., & Bausch, A. (2011). Explaining the heterogeneity of the leadership-innovation relationship: Ambidextrous leadership.  Leadership Quarterly, 22(5), 956–974 Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217–226. Shook, C., Priem, R., & McGee, J. (2003). Venture creation and the enterprising individual: A review and synthesis. Journal of Management, 29, 379–399. Von Hippel, E. (2001). User toolkits for innovation. Journal of Product Innovation Management, 18(4), 247–257. Von Krogh, G., Spaeth, S., & Lakhani, K. R. (2003). Community, joining, and specialization in open source software innovation: A case study. Research Policy, 32(7), 1217–1241. Wang, P., & Rode, J. C. (2010). Transformational leadership and follower creativity: The moderating effects of identification with leader and organizational climate. Human Relations, 63(8), 1105–1128. West, J., & Bogers, M. (2014). Leveraging external sources of innovation: A review of research on open innovation. Journal of Product Innovation Management, 31(4), 814–831. West, J., & Gallagher, S. (2006). Challenges of open innovation: The paradox of firm investment in open-source software. R&D Management, 36(3), 319–331. Yoo, Y., Boland Jr, R. J., Lyytinen, K., & Majchrzak, A. (2012). Organizing for innovation in the digitized world. Organization Science, 23(5), 1398–1408.

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CHAPTER 3

BEHAVIORAL STRATEGY, INNOVATION, AND ENVIRONMENTAL DISRUPTIONS Mzamo P. Mangaliso Leah Z. B. Ndanga David L. Major

ABSTRACT Innovation has been found to be a key determinant of the firm’s long-term survival. The assumption is that in contemporary times characterized by uncertainty, complexity, and disruptive environments, firms that do not innovate eventually fail. This assumption brings up the contradictory perspectives of strategic choice versus environmental determinism. The former asserts that firm executives can determine the fate of their organizations by making strategic choices that can lead to the firm’s success. Several writings in the resource-based view tradition support the notion that the sustainability of competitive advantage is possible if the firm can develop resources that are valuable, rare, inimitable, and non-substitutable. The environmental determinism school asserts that organizations must adapt to prevailing environmental conditions or they will fail. Innovation and Behavioral Strategy, pages 53–84 Copyright © 2022 by Information Age Publishing www.infoagepub.com All rights of reproduction in any form reserved.

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54  ⏹  M. P. MANGALISO, L. Z. B. NDANGA, and D. L. MAJOR This is exemplified in Porter’s five forces framework, which describes the five competitive forces in the firm’s environment to which firms must adapt or risk failure. Bearing these two perspectives in mind, this chapter centers the discussion on disruptive environments and the central role that innovation plays in mitigating them. Specifically, the chapter will discuss the unique insights that behavioral strategy offers to making the appropriate choice of innovations in the face of environmental jolts. It argues that innovation choices, made from the broad consultative processes integral to behavioral strategy, lead to more sustainable organizational performance. A number of propositions are developed at the nexus of behavioral strategy, innovation, and the performance of organizations when they confront disruptive events. The chapter concludes with a discussion of implications for future research.

INTRODUCTION Over the years, the strategy literature has increasingly been recognizing environmental turbulence as having an important moderating influence in the relationship between planning and performance (Ansoff, 1991; Goodstein & Boeker, 1991; Miller & Friesen, 1983; Mintzberg, 1994b; Spender, 2014; Theobald, 1994). It has been mentioned with increasing frequency as researchers have grappled with how organizations should cope with rapid changes in the environment. Moreover, some research has begun to focus on more intense manifestations of turbulence in the form of hypercompetition (D’Aveni, 1994), “black swan” events (Taleb, 2007), and environmental jolts (Venkataraman & Van de Ven, 1998). Despite general consensus on these realities in the literature, there still appears to be a paucity of research about strategic approaches that can be utilized in order to mitigate and traverse the disruptive environmental events when they occur. The chapter is an attempt to fill that lacuna focusing on the intersection of strategy, environment, and innovation. We aver that behavioral strategy offers a more realistic portrayal of strategic choice by acknowledging the essential role of both executives’ cognitive and affective considerations, as well as their mutual interactions among one another through multilevel communication systems in the process of their decision. We suggest that under these environmental conditions, greater reliance on behavioral strategy processes will engender more appropriate innovation and hence yield more sustainable performance. The chapter is arranged as follows. The next section provides a conceptual scaffolding upon which each of the main themes of the chapter; namely, environmental turbulence, innovation, and behavioral strategy, are based. This is followed by a number of propositions that contextualize and relate these variables to one another. The chapter ends with a discussion and some concluding comments.

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CONCEPTUAL BACKGROUND One of the shared and enduring canons in the management orthodoxy is that organizations must have congruence with the demands and vicissitudes of their external environments or else they will fail (Miles & Snow, 1984; Miller, 1992; Morosini, Shane, & Singh, 1998; Zajac, Kraatz, & Bresser, 2000). The upper echelons literature suggests that the manner whereby organizations achieve this environmental fit is largely determined through the subjective choices made by their top management team or TMT (Das, 1986; Hambrick & Mason, 1984; Hrebiniak & Joyce, 1985). Since its formal emergence as a field, strategic management has mostly focused on rationality and cognitive processes as the main considerations in the choices executives make. However, there has been growing evidence showing that strategic choices are also influenced by emotional (feeling) processes, and that greater strategic alignment can be accomplished when both cognitive and emotional frames are harmonized (Raffaelli, Glynn, & Tushman, 2019). Developments that began in behavioral economics (Thaler, 2015, 2016; Tomer, 2007), spurred the emergence of the subfield of behavioral strategy into advancing the idea that a more realistic conception of strategy combines both cognitive and affective aspects of decision-making (Bromiley, 2004; Lovallo & Sibony, 2018; Mangaliso & Ndanga, 2017; Powell, Lovallo, & Fox, 2011). Notably, the affective aspects of decision-making are influenced by the executive’s background, personality, values, and beliefs (Das & Teng, 2001; Gupta, 1984; Kets de Vries & Miller, 1984). Behavioral strategy thus asserts that it is the confluence of their cognitive and affective considerations that feed into the collective decisions that the firm’s TMT makes. Environmental Uncertainty According to scholars in the field of management, one of the challenges that organizations face is overcoming the challenge of uncertainty (Samsami, Hosseini, Kordnaeij, & Azar, 2015). The construct of uncertainty seems to have infiltrated the management discourse in the late 19th century through the activities of the newly emerging corps of professional engineers who had taken on a more visible management role in the running of post-industrial revolution organizations (Samsami et al., 2015). Subsequently, coping with uncertainty became identified not just as the major challenge that organizations faced, but also as the essence of the administrative process (Miles, Snow, & Pfeffer, 1974; Starbuck, 1976; Thompson 1967). Indeed, the success of organizations rests squarely on the efficacy of its administrative process in eliminating uncertainty and being able to regulate the organization’s input–throughput–output process (Miles & Snow, 1978; Thompson, 1967;

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Williamson 1985). It is perhaps in this regard that strategic management evolved as a field with one of the goals being to help the firm overcome the challenge of uncertainty by shaping its competitive landscape, hence the coming into being of the various generic strategies and strategic types in the 1970s and 1980s (Miles & Snow, 1978; Porter, 1980). The role of uncertainty in organizational politics is clearly seen when some subgroups are able to obtain power over others depending on the amount of uncertainty they control and the success they have in controlling it (Hickson, Hinings, Lee, Schneck, & Pennings, 1971). Although there have been many writings on the subject of uncertainty, little is known about the processes whereby managers respond to uncertainty in formulating their corporate strategies (Parnell, Lester, & Menefee, 2000). A number of writers have suggested various ways of overcoming uncertainty, which include designing organizations in the appropriate mix of organic and mechanistic structures or providing the appropriate kind of information in terms of its scope, timeliness, and level of aggregation (Burns & Stalker, 1961; Chenhall & Morris, 1986; Lawrence & Lorsch, 1967; Mangaliso, 1995). In his classic work, Thompson (1967) suggests that under norms of rationality organizations respond to uncertainty by using any of five strategies. They seek to either (a) seal off their core technologies from environmental influences (e.g., through patents); (b) buffer environmental influences (e.g., by stockpiling); (c) smooth out input and output transactions (e.g., by offering special prices); (d) anticipate and adapt to environmental changes (e.g., through forecasting); or (e) ration their resources (e.g., furloughs, reduced workweek). But uncertainty is a multidimensional phenomenon especially if viewed both from the perspective of who affects it and who experiences it. Managers respond to what they perceive, and perception of uncertainty is an individual psychological trait rather than an environmental attribute (Hambrick & Mason, 1984; Miles et al., 1974). It is with this in mind that the subfield of behavioral strategy developed. In some of the writings on environmental uncertainty there is an implicit linearity when it is categorized as dynamic, complex, or hostile (Dess & Beard, 1984). However, some behavioral theorists suggest that the relationship should be considered as nonlinear, making a distinction between uncertainty and risk (March & Simon, 1958). In situations of risk, the probability of occurrence of events can be quantified. With uncertainty, such quantification is impossible—the unknowns remain unknown (Teece & Leigh, 2016). The implications of this nonlinear relationship are well known in economics through the law of diminishing returns to scale, which posits that beyond a certain point linearity converts to an exponential relationship. The implication of this law is that the utility value of additional information will not always increase but, instead, it reaches a point beyond which it will decrease. Further, due to their limited cognitive information

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processing abilities, managers will use bounded rationality and other heuristics and biases that limit their ability to make optimal decisions (March & Simon, 1958; Tversky & Kahneman, 1974). Research in the economics of information has also shown the intricacies of information and the environment. For example, Stiglitz (2000) observed that while information is imperfect, it has asymmetries that are shaped by the behaviors of managers and firms. In short, as the rate of complexity and change begins to outpace the content of available information, the usefulness of additional information will depend on other information properties as well. The ability of organizations to thrive under adverse periods created by environmental jolts can be attributed to their possession of dynamic capabilities, that is, capabilities that firms possess to adapt their resource base to fit the emerging environmental vicissitudes (Teece, Pisano, & Shuen, 1997). Furthermore, since cognition plays such a key role in interpreting external environments, the firm’s dynamic capability is enhanced when executive cognition allows them to shape a firm’s adaptive resource base in sync with changes in the environment (Adner & Helfat, 2003). Environmental Turbulence The contemporary post-industrial information age characterized by rapid technological changes, globalization, and the uncertainty and unpredictability of the environment has escalated to the point of being labeled as turbulent. This has put pressure on firms to embark upon planning processes infused with greater innovative and creative “out-of-the-box” thinking. They are forced to introduce innovative processes, products, and organizational forms in quick succession to avoid obsolescence and keep up with the rapid changes that pervade the environment. The notion of environmental turbulence emerged in the late 1980s from the writings of Igor Ansoff, which unleashed a series of debates in the strategy field (Ansoff, 1991; Mintzberg, 1991, 1994a). Environmental turbulence has been defined as the complex interconnectedness of environmental elements that exhibit rapid, unpredictable, and discontinuous change that makes the future hard to predict (Mangaliso, Mir, & Knipes, 1998). It is a phenomenon that has been mentioned with increasing frequency as researchers have grappled with how organizations should cope with rapid changes in the environment. Environmental turbulence is associated with a wide variety of literatures as shown in Table 3.1. Environmental turbulence is recognized as having an important moderating influence in the relationship between strategic planning and performance outcomes (Ansoff, 1991; Goodstein & Boeker, 1991; Mintzberg, 1994a; Theobald, 1994). For instance, environmental turbulence is said

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Authors

Premise

Resource Dependency

Aldrich & Pfeffer (1976); Pfeffer & Salancik (1978); Thompson (1967)

Environment is a system-like context of resources and social structures. Organizations use their resources to actively shape their environments or protect their core by buffering.

Decline

Cameron, Kim, & Whetten (1987); D’Aveni (1989); Zammuto & Cameron (1985)

Diminishing resources in organizations’ task environments lead to adverse effects such as layoffs and mutual blame. Typically felt at lower levels of the organization. Turbulence is felt at higher levels.

Crisis

Meyer (1982); Mitroff & Pauchant (1990); Shrivastava & Mitroff (1987)

Events inside and outside organizations represent threats to organizations’ survival. Organizations must anticipate, manage, and prevent corporate crises.

Volatility

Bourgeois (1985); Smart & Vertinsky (1977); Snyder (1987)

Problem with volatility is that change in the rate of change in the environment leads to unpredictability. Unlike turbulence, volatility is of finite duration.

Uncertainty

Bourgeois & Eisenhardt (1988); Duncan (1972); Starbuck (1976); Thompson (1967)

Exists when knowledge about activity is incomplete, probability of outcome not known, a set of stimuli that lack meaning until perceived by individuals. Uncertainty is a state of mind, turbulence is the state of the world.

Chaos Theory

Baumol & Benhabib (1989); Levy (1994); Stacey (1991); Thietart & Forgues (1995)

Organizations viewed as complex, nonlinear, dynamic systems that exhibit characteristics of both chaos and stability. High levels of turbulence lead to chaos that makes long-term forecasting practically impossible. Short-term planning enhanced by simulation.

Postmodernism

Harland (1987); Lotringer & Baudrillard (1986); Rosenau (1992)

Truth is unknowable. Attempts at longrange planning like “navel-gazing.” Only stifle organizational innovation and creativity.

to have been responsible for revolutionizing the managerial roles that led to the global dominance of Japanese corporations (Johnston, 1995), the reconstruction of management in post-communist Eastern Europe (Johnson & Loveman, 1995), the “greening” of organizational studies (Shrivastava, 1987), and the organizational reengineering revolution (Hammer & Champy, 1993). This may have been the reason why some scholars in

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the field warned that environmental turbulence will continue to challenge organizations (Ansoff, 1991). Environmental turbulence has dramatic deleterious effects when initiated by environmental jolts, which are transient perturbations whose low probability of occurrence makes them difficult to anticipate, but whose impact on the organization is great and inimical (Meyer, 1982; Venkataraman & Van de Ven, 1998). Some researchers suggest that turbulence makes strategic planning seem nearly impossible to execute (Emery & Trist, 1985; McCann & Selsky, 1984). Yet, as empirical evidence from a study of the oil majors industry has shown, it can be executed (Grant, 2003). Traditionally, strategic planning and management discourse considers information as the element that enables managers across various levels of the organizational hierarchy to remain on the same page. This is particularly important with respect to decision-making since it is axiomatic that at each stage of the strategic management process—from environmental scanning to strategic choice—information constitutes the basis of all decision-making. The extant strategic management literature indicates that the usefulness of management information varies as a function of the context of decision-making (Samsami et al., 2015). Prior research suggests that strategic decision-making accounts for two types of contextual factors: those related with the external organizational environment and those related to internal firm characteristics (Child, 1972; Hickson et al., 1971; Papadakis, Lioukas, & Chambers, 1998). These two factors are aligned with previous research (Chenhall & Morris, 1986; Mangaliso, 1995), which suggests that contextual variables in decision-making are conceptualized through environmental uncertainty and organizational decentralization. Environmental turbulence is escalated by sporadic events that occur and jolt the environment into a tailspin, producing calamitous aftereffects on organizations and human life in general. In recent years such events include the explosion of the Space Shuttle Challenger in 1985 (Preble, 1997; Schwartz, 1987); the Union Carbide disaster in Bhopal, India (Shrivastava, 1987); the 9/11 attacks on the Twin Towers of New York; and a series of financial accounting scandals that were subsequently revealed at major U.S. corporations (Boin, 2009). Other examples include the collapse of the U.S. housing bubble of the mid-2000s that resulted in record foreclosures, and the 2007–2008 financial crisis that threw markets worldwide into a tailspin. It was around that time that Nassim Taleb (2007) introduced the term “black swan” into the mainstream organizational lexicon. Following Taleb (2007), the general consensus among researchers is that there are three criteria that characterize a black swan event (Antipova, 2021; Higgins, 2013; Murphy, Jones, & Conner, 2020; Nafday, 2009). First, is its outlier status, that is, being outside the realm of regular expectations because of the impossibility of predicting it a priori. Second, is the extreme impact it

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leaves behind in its aftermath. Third, is the tendency of people to concoct explanations for its occurrence ex posteriori, making it seem explainable and predictable. The most recent example of such an event is the outbreak of the COVID-19 pandemic with its unprecedentedly high and devastating impact on a whole range of global activity. Because of the subjectivity involved in the interpretations under the categories opinions differ on the classification of events as black swans, and questions have been raised about whether the COVID-19 pandemic is truly a “black swan” event. Researchers with experience in dealing with low-frequency high-impact scenarios have argued that COVID-19 cannot be viewed as a “black swan” event since there were multiple warnings issued by experts in epidemiology and related public health fields that a major pandemic was not a question of if, but only of when (Murphy et al., 2020). But several others believe that it qualifies in view of its devastating impact on social, economic, and technological activity and systems worldwide (Antipova, 2021; Higgins, 2013). Strategic Choice Strategic choices are a central tenet of strategic management and the strategic choice versus environmental determinism debate (Hrebiniak & Joyce, 1985). Research from the population ecology perspective relegates strategic managers to a lesser role positing that firms have little choice since organizational change is viewed as a response dictated by external environmental dependencies (Aldrich, 1979) in their work on population ecology (an example of environmental determinism) posit that firms have little or no strategic choice as the external environment compels firm structure and is the most influential determiner of performance. DiMaggio and Powell (1991) in their seminal work on institutional theory assert that structure and operation of firms are affected by industry and economy-wide opposite or isomorphic forces, such as regulation, professionalization, and trade associations that constrain strategic choice. However, the upper echelons literature avers that organizations and their actions and outcomes are influenced by, and are, a reflection of their top managers (Hambrick & Mason, 1984). An accepted tenet of upper echelons research is that strategic choices are made by the organization’s TMT after consideration of the totality of the organization’s resource capabilities and the opportunities and threats in the dynamic external environment (Hambrick & Mason, 1984). In that sense it has been noted that strategic choice extends from the firm’s internal assessment to the environment within which it operates, and back to the standards of performance against which the pressure of economic constraints has to be evaluated (Child, 1997). A number of factors are mentioned in the

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literature that differentiate strategic choices from other administrative or operational choices, including the following three: (a) they are choices made by those in power—the firm’s TMT, (b) their projections tend to be over a fairly long time horizon, and (c) their nature is entrepreneurial in the sense that a considerable amount of the firm’s resources are put at risk, which makes failure quite costly (Chandler, 1962; Miles & Snow, 1978; Penrose, 1959). Following from the above, in this chapter we define strategic choice as the conscious choice of entrepreneurial, large-scale, and difficult to reverse courses of action made by the firm’s TMT in pursuit of the firm’s long-term goals. From the behavioral strategy perspective, the superiority of TMT agency arises from the diversity of member perspectives that get taken into consideration before making the strategic choice. The behavioral component of strategic choice forces executives (dominant coalition) to use their own cognitive bases and values to direct their attention, select, and interpret the stimuli (environmental and organizational) that are out there. This process forms the basis of their perceptions which, in turn, affect strategic choices (Hambrick & Mason,1984). Executives’ disposition, biases, and background characteristics serve to filter and shape the stimuli that the executives confront, and thus can also be used to predict those executives’ strategic choices. As a caveat, it is worth noting that more recent literature has observed that strategic choices are not necessarily made exclusively by the TMT. The middle management literature challenges the notion of the strategy making process as a top–down analytical and linear process, where top managers formulated and middle managers implemented strategies (Mangaliso, 1995). Instead, this research has identified several ways in which middle managers contribute to the strategy process, including improvement of strategic decision quality; promotion of upward, downward, and outward change; identification of capabilities; and creation of organizational knowledge. However, for the purposes of this chapter we will focus on the upper-level strategic choices involving innovation. The foregoing discussion of strategic choice at firm-level conjures up the Miles and Snow (1978) strategic choice typology in which firm classification and hence their nimbleness to respond to environmental events can be anticipated. The Miles and Snow (1978) typology has been widely embraced in the management field because of its innate parsimony and applicability in a variety of industries (Moore, 2005). In the typology, businesses are classified according to their competitive stances into four strategic types; namely, prospectors, analyzers, defenders, and reactors. Prospectors are innovative firms whose strategic stance is to seek out new markets. Analyzer firms are not first-movers, but adopt innovations introduced by other firms and improve them. Defenders are firms that are content with their product

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market position and will invest in defending their niche rather than in new product markets. Reactors are firms that lack a specific strategic stance but simply respond to environmental events as they occur (see DeSarbo, Di Benedetto, Song, & Sinha, 1993). As we will show in our propositions and discussion sections, firms can adopt any of the four strategic types depending on the perceptions and information available to the dominant coalition, usually the top management team. Behavioral Strategy From its conception as a field, strategic management has mostly focused on rationality as the main consideration for the choices made. Its underlying epistemology has been based on the positivist neoclassical conceptions of reality that assume human behavior to remain constant at all times and across cultures. Behavioral strategy differs from conventional strategy because it assumes that humans possess limited cognitive informationprocessing capabilities and are prone to making biased judgments based on heuristics and shortcuts (March & Simon, 1958; Tversky & Kahneman, 1974). It acknowledges that strategic decisions are the result of behavioral factors and not only the result of techno-economic rational optimization (see Bromiley, 2004; Lovallo & Sibony, 2018; Mangaliso & Ndanga, 2017; Powell et al., 2011; Yang & Lester, 1995). Strategic decisions made exclusively through rationality become amplified under intense pressure and in the face of turbulence, often leading to less than optimal strategic choices and unintended outcomes (Murphy & Cotteleer, 2015; Payne, Bettman, & Johnson, 1993). These assertions are especially valid in unexpected disruptive events, that is, events with a low expected probability of occurrence but a high expected impact on organizations, such as the fateful attacks on the Twin Towers of the World Trade Center in 2001, the market crash of 2007 following the collapse of the housing market, and the outbreak of the COVID-19 pandemic in 2020. Behavioral strategy developments were stimulated by parallel developments that emerged out of behavioral economics research. These developments advanced the idea that a more realistic conception of human behavior combines both cognitive and affective aspects of decision-making (Thaler, 2015; 2016; Tomer, 2007). Behavioral strategy considers both cognitive and affective aspects of decision-making as well as other human characteristics that greatly influence the executive’s behavior, such as their personality, values, and beliefs (Das & Teng, 2001; Gupta,1984; Kets de Vries & Miller, 1984). It asserts that the confluence of these factors constitutes the collective decisions that the firm’s executives make. Powell (2017) goes further to introduce the notion of “diligence-based” strategy, which

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is particularly helpful in businesses that operate in markets dominated by human relationships. However, as Dereli (2015) notes, for a firm’s survival to be sustainable in the new and changing environment, proper innovation management is needed that involves creative, management, and production processes. The management of these functions require strategies and structure focused on human behavior. In the chapter we focus on the role played by managerial behavior in making strategic decisions in response to disruptive events. Foss (2020) argues that the emerging behavioral strategy view offers unique insight into decision-making in a situation of “disruption,” which is “a situation in which a low-probability or even entirely unanticipated event emerges that has drastic impact and consequences at a systemic level, not just upsetting relations between firms and their stakeholders within a single industry but hitting at the level of the entire economy.” The psychological and behavioral lenses through which managers’ decision-making is analyzed in behavioral strategy provides unique insight in extreme environmental conditions. Innovation Innovation is defined as the invention, development, and implementation of new ideas. Schumpeter (1934) described innovation as any new combination of existing and new elements, while Van de Ven (1986) later referred to innovation as the inception, development, and implementation of new ideas. In either case, innovation has long been at the core of business activity. The new combinations or new ideas manifest as new products, new services, or new organizational processes and routines in an organization’s quest for survival within changing competitive landscapes (D’Aveni, Dagnino, & Smith, 2010; Major, Maggitti, Smith, Grim, & Derfus, 2016). No shortage of academic thought and research have pursued the broad innovation topic since early Schumpeterian conception, with a focus on products as goods and services and organizational processes. These forms of innovation have long been conceived of as a means of survival and as drivers of business development or as a result of necessity, as suggested by the old adage affirming that necessity is the mother of innovation (Bolton, 1993; Grant & Berry, 2011). While innovation may be traced back to the earliest incarnations of business enterprise, only in more recent thinking have notions of new combinations and new ideas begun to explicitly account for social cognitive antecedents and consequences. Indeed, early study conceived of innovation as the result of processes and procedures that tended to be generally linear, programmatic in nature, and confined to the deliberate processes embedded within traditional R&D functions of organizations. More recent

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theorizing accounts for innovation processes that are nonlinear, sporadic, and originate across business functions. The bipartite concept of exploration and exploitation in the foundational March (1991) article have been fundamental to academic research in innovation, as well as organizational learning and strategic decision-making. Innovation as a new combination is also closely linked to uncertainty and environmental dynamics as important catalyzing and attenuating forces. Fierce competitive pressures of hyper competition (D’Aveni, 1994) and fast-moving technological changes (Eisenhardt,1989; Katila & Shane, 2005; Shane, 2000) now are taken into account in more recent innovation research. These studies importantly theorize and test moderating conditions within turbulent and uncertain environments (Bicen & Johnson, 2015; Candi, Van Den Ende, & Gemser, 2013; Maula, Keil, & Zahra, 2013). The findings provide rich guidance for how organizations might navigate in not just technological uncertainty, but in wholly unexpected events and within environmental turbulence. In terms of uncertainty, Candi et al. (2013) hypothesizes that flexibility has alternating moderate effects—flexible project specifications vs. flexible project planning. Bicen and Johnson (2015) suggest that constant iterating and market feedback testing, in a process referred to as lean innovation capability, positively impact innovation outcomes. Also, in an interesting extension of the attention-based view of the firm, Maula et al. (2013) suggest that managerial attention drivers, such as social connectivity, serve an important moderating role in uncertain, highvelocity environments. Firms are shown to be especially vulnerable to industry-altering innovations or technological discontinuities given limits to managerial sensemaking and attention. How managers attend to environmental shifts has a consequential impact on organizational processes and the long-term persistence of the organization. In general, the innovation literature tends to suggest that firms may mitigate adversity presented by unexpected events and environmental turbulence through the integration of proper flexibility, recursive cycles of constant iterating and managerial attention, and sensemaking. The propositions that follow combine innovation literature with behavioral strategy to guide firms through uncertain, turbulent environments and disruptive events. PROPOSITIONS Our starting point is the unexpected disruptive events. These environmental jolts differ somewhat from the uncertainty that is inherent in the strategic management process. In layman’s terms, uncertainty is a state of unpredictability or a situation where there is not enough information to formulate an opinion or make a decision. In the management literature,

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uncertainty is usually related to a lack of knowledge about the organization’s environment. As Carpenter and Frederickson (2001) observe, uncertainty is a consequence of environmental factors that generally result in a lack of information needed to assess means-ends relationships, make decisions, and confidently assign probabilities to their outcomes. It follows therefore, that better information about the environment reduces uncertainty and leads to better strategic choices. Helmer (2003) draws a distinction between conditions of certainty, uncertainty, and risk, noting that these three are usually presented as three mutually exclusive dispositions concerning any given outcome. Certainty occurs when the relevant dimensions of the outcome are completely known. Uncertainty exists when the relevant dimensions are not known and where it is impossible to attribute a meaningful probability function to the outcomes. Risk exists where the relevant dimensions of the outcome are not known, but it is possible to meaningfully attribute a known probability function to the outcomes. Some researchers prefer to fold the terms uncertainty and risk into the term ambiguity defined as “uncertainty about probability, created by missing information that is relevant and could be known” (Camerer & Weber, 1992, p. 330). Following from the above, we define uncertainty as a dynamic state that occurs when a decision-maker is unable to meaningfully attribute probabilities from which to accurately predict the outcome of an event or action. This is especially so in these unexpected disruptive events. The latter are situations “in which a low-probability or even entirely unanticipated event emerges that has drastic impact and consequences at a systemic level, not just upsetting relations between firms and their stakeholders within a single industry but hitting at the level of the entire economy” (Foss, 2020, p. 1323). The decision makers are unable to ascertain the probability of these events, and hence are somewhat unprepared and are forced to make decisions without extensive information. Previous behavioral strategy scholars have shown how decision-making in firms relies on simplification by the decision makers based on prior experiences and personality traits. Our question becomes: “What determines success, or survival, when there is an unexpected disruptive event?” Innovation has been found to be a key determinant of the firm’s sustainable long-term survival. The assumption is that in contemporary environments characterized by uncertainty, complexity, and disruption, firms that do not innovate eventually fail. This assumption brings up the old debate of strategic choice versus environmental determinism (Hrebiniak & Joyce, 1985). The environmental determinism school of thought argues that organizations must fit the demands of the environment or risk failure (Miller, 1992). A good example that comes from this school is Michael Porter’s (1980) five forces framework, which suggests that firms which do not adjust

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their strategies according to the vicissitudes of the market become increasingly vulnerable to powerful industry forces. The alternative school asserts that firm executives can determine the fate of their organizations by making choices that can lead to the firm’s success or failure. An example of this school of thought is the resource-based view, which claims that sustainable competitive advantage is possible if the firm can acquire or develop resources with the requisite characteristics of being valuable, rare, inimitable, and nonsubstitutable (Barney, 1991; Foss, 1997; Penrose, 1959). Another aspect to consider is that of the strategy frameworks and theories. None are dedicated to the understanding of the strategic implications of disruptions, that is, radical and at least partially unforeseen changes that are exogenous to a set of interacting firms, such as industries or ecosystems. The strategy theories discussed above deal with the more general aspects of strategy. There are theories that deal with parts of strategy, such as networks, alliances, or power; some theories deal with internal changes, such as Schumpeterian competition theories; and some, like the dynamic capabilities view, may offer insight into change but are at too high a level of abstraction. In light of these shortcomings, Foss (2020) argues that behavioral strategy is uniquely situated in terms of providing a psychologically based interpretive lens that could lend great insight into decision-making in extreme conditions, such as the COVID-19 disruptions. Risk Propensity In the categorization of environments as dynamic, complex, or hostile there seems to be an implicit assumption of linearity of the dimensions on the part of scholars (Dess & Beard, 1984). However, research by behavioral theorists suggests that the relationship should be considered as nonlinear (March & Simon, 1958). Also notable are the differences between uncertainty and risk. In situations of risk, the probabilities of occurrence of events can be quantified but with uncertainty, such quantification is impossible— the unknowns remain unknown (Teece & Leigh, 2016). The implications of this nonlinear relationship are well known in economics through the law of diminishing returns to scale, which posits that beyond a certain point, linearity converts to an exponential relationship. In the economics literature, the foundational theory for explaining how decision-makers make choices under uncertainty is the subjective expected utility (SEU) theory (Bonoma & Johnston, 1979; Currim & Sarin, 1983, 1984). Even though the SEU is a robust theory, some inadequacies have been identified in its ability to serve as a descriptive model for decision-making under risk and ambiguity since the exact probabilities cannot always be assigned to event, in effect rendering the uncertainty itself to be uncertain (Kahn & Sarin, 1988). An

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alternative explanation comes from the prospect theory, the fundamental tenet of which is that people overweight outcomes that are considered certain relative to outcomes that are merely probable (Kahneman & Tversky, 1979). The tendency to deal with ambiguous situations in this way, called the certainty effect, contributes to risk aversion in choices involving sure gains and to risk seeking in choices involving sure losses. Proposition 1A: Since they are generally risk averse, defender firms will attempt to weigh the risks against the probabilities of the negative outcome, but in the case of disruptions characterized by ambiguity and where no exact probabilities can be calculated, the defender strategy will be rendered ineffectual. Proposition 1B: Prospector firms will consider the potential gains from taking action and take quick actions to avoid the potential negative actions. Intellectual Curiosity While most business organizations may not have anticipated their onset, some environmental disturbances, or jolts, such as the onset of the COVID-19 pandemic may not have been entirely improbable in the epidemiological community (Maxmen, 2020). Organizations that combine both cognitive and affective components of decision-making in the process of sense-making about the environment would have had some inkling about the imminence of the virus before it reached continental America. Based on that information, they could have developed innovative strategies to mitigate the impact of the pandemic. Proposition 2: Firms that rely on the broader sense-making of behavioral strategy are to a greater extent better equipped to anticipate the onset of highimpact events such as COVID-19 and make appropriate innovative choices to mitigate their impact for better performance. Progressiveness Progressive firms, otherwise known in Miles and Snow’s (1978) typology as prospector firms often thought of as “innovators” are known to advocate for innovative processes and ideas. Such firms use projections ahead of their rivals and implement the necessary changes before the rest of the competition does. Evidence of this can be seen in firms that already had flexible working hours and remote working before the pandemic made it necessary.

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Proposition 3A: Since prospector firms already have innovative structures and processes in place that only need tweaking and expanding, they are better situated to respond to the onset of disruptive events. Proposition 3B: Prospector firms are quick to read the signs and make strategic adjustments in their routines and procedures (e.g., working remote, social distancing, and mask wearing in the case of COVID-19) before they are required by law. International Experience Globalization has become ubiquitous in the marketplace making the competitive landscape more heterogeneous, diverse, and uncertain. This makes acquiring a global mindset to develop the dynamic capabilities necessary to compete in the international market place a sine qua non (Luo, 2000; Mangaliso & Ndanga, 2017). A global mindset combines “an openness to and awareness of diversity across cultures and markets with a propensity and ability to synthesize across this diversity” (Gupta & Govindarajan, 2002, p. 117). It allows firms to deploy the capabilities acquired from the innovations culled in their various operations around the world wherever appropriate, and systematically upgrade and adapt them to the new situations they encounter (Lessard, Lucea, & Vives, 2013). That makes firms with prior experience in disruptive environments, such as war-torn regions and areas previously hit by pandemics such as the SARS virus, more prepared when similar unexpected events occur in their environments. Foss (2020) gives the example of how Taiwanese firms were able to quickly and successfully innovate by basing the interpretation on their prior experience with the SARS virus. Proposition 4: The global mindset that firms gain from international experiences gives them capabilities to embark upon innovative strategies, that can quickly be deployed when they encounter environmental disruptions. Technical Expertise The strategic management literature shows plenty of evidence about the importance of technical expertise in decision-making. This becomes amplified when unexpected disruptions result in intensified complexity, turbulence, and chaos in the environment. During these disruptions, the media is rife with conflicting information. Therefore, firms that lack

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technical expertise in their decision-making ranks to understand or decipher what the facts are may be victims of misinformation and make the wrong decisions. Proposition 3B: Firms with technical expertise are more likely to make innovative decisions that benefit the firm in the long term. Proposition 3B: Firms that lack technical expertise are more likely to be victims of misinformation and make rash innovations that potentially harm the firm. Network Connections Lechner, Frankenberger, and Floyd (2010) argue that social network embeddedness has both positive (access to information, power, etc.) and negative (costs of redundant information coordination, tie upkeeping, etc.) effects. Negative consequences of “strong ties” and centrality are more pronounced in exploratory initiatives than in “exploitive” initiatives. Although exploratory groups appear to benefit less from increases in shared vision, shared vision is a positive influence on performance for both types of initiatives. Proposition 6A: Under disruptive environmental conditions, executives of firms embedded in networks with prevalent pack mentality, are less likely to independently investigate phenomena, and subsequently fall victim to groupthink, and lack innovativeness. Proposition 6B: Under disruptive environmental conditions, executives of firms embedded in open minded, progressive networks with intellectually curious peers with technical expertise, are more likely to come up with innovative ways of dealing with the disruptions. The next set of propositions describe how the causal factors of environmental jolts, behavioral strategy, and innovation interact to influence performance. This is depicted in Figure 3.1. Environmental jolts have been defined as sudden and unprecedented events whose probability of occurrence is difficult to foresee and whose impact on organizations are disruptive and often destructive to the organization (Meyer, 1982; Venkataraman & Van de Ven, 1998). In other words, environmental jolts are low probability–high impact events that can adversely affect the economic opportunities for the population of firms in the environment. Gersick (1991) conceptualizes environmental changes as not occurring in a linear continuous way but, rather, in a pattern of alternation between long periods of relative

70  ⏹  M. P. MANGALISO, L. Z. B. NDANGA, and D. L. MAJOR P7

Environmental Disruption

P8

Innovation

P9

Performance

P10

Behavioral Strategy P1A

Risk Propensity

P6B

P1B

P6A P2

P5B

Network Connectedness

P5A

Intellectual Curiosity

P3A

P3B

Progressiveness

Technical Expertise

P4

International Experience

Figure 3.1  Relationship of causal factors on performance.

stability and brief periods of revolutionary upheavals or jolts. This is what she calls the “punctuated equilibrium paradigm.” Period P1 in Table 3.2, represents the pre-environmental jolt environment that occurs over long periods of stability (Gersick, 1991). During P1 the environment is in a stable state and only minor disturbances occur from time to time during this period. Under these relatively stable environmental conditions firms can succeed by following their normal routines and based on standard procedures and top–down decision-making. Firms can make strategic choices based on extending trends from the past and projecting them into the future with little risk of failure. Minor innovations are sufficient to accomplish and maintain planned performance goals. Since there is less chance of a major stumble in the environment, any disturbances that occur can be mitigated through logically incremental adaptations (Quinn, 1991). The role that cognition and affect play may be less critical during this phase. In this environment, firms may follow either the effectuation-based or the causation-based logistics and still be able to achieve satisfactory performance outcomes (Shirokova, Osiyevskyy, Laskovaia, & MahdaviMazdeh, 2020). Effectuation-based logistics leverage existing organizational resources and control the environmental uncertainty to create new markets, products, processes, and opportunities. In the Miles

Behavioral Strategy, Innovation, and Environmental Disruptions  ⏹  71 TABLE 3.2  Strategic Choice, Turbulent Environments, Performance Period Parameter

P1: PreEnvironmental Jolt

P2: During Environmental Jolt

P3: PostEnvironmental Jolt

State of Environment

Relatively stable; in equilibrium; minor disturbances, e.g., pre-9/11

Turbulent, tailspin (Gaba & Meyer, 2021); in disequilibrium; even the ground is in motion (McCann & Selsky, 1984), for example, during COVID

Relatively settled; new equilibrium; for example, post 9/11, post-COVID

Strategic Choice

Decision-making mostly top–down; TMT mostly rational; TMT, cognition, affect influences

Combined bottom– up, and top–down decision-making; tempered rationality; increased TMT cognitive-affective inputs

Increasingly top– down; combo of rationality and affective decisionmaking

Innovation

Prospectors— successful innovations based reliance on effectuation logistics

Prospectors—effective performance outcomes

Prospectors—higher performance levels than pre-jolt

Defenders—less successful due to reliance on causation logistics Analyzers—reliance on a combination of both effective

Defenders—ineffective Defenders—may performance return to pre-jolt levels outcomes Create of vestibule Analyzers—moderately units for innovation effective performance outcomes

and Snow (1978) typology, prospector firms continue to innovate by relying on effectuation logistics. Causation-based behavioral logistics use rigorous, forward-looking analysis, relying on well-prepared plans, pre-defined goals, and require resources to continue to focus on lowering their cost structures as a way to improve efficiency. This is the strategic posture that Miles and Snow’s (1978) defenders use. Analyzers strike a balance between the prospectors and defenders. In this period the differential in performance outcomes between these strategic types will be minor and only vary according to firm-specific prevailing conditions. The setting in period P2 occurs after the onset of an environmental jolt. Here the environment is in a tailspin and disequilibrium, and even the “ground is in motion” (McCann & Selsky, 1984). During this phase the rules of the game are radically altered, and strategic decisions that follow the book are a sure path to failure. Firm executives may find sporadic success

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through decision-making based on consultation with tempered rationality and increased cognitive and affective inputs. A combination of bottom–up and top–down decision processes become the preferred modus operandi. The causation-based logistics of defender firms become highly unreliable in the turbulence caused by environmental jolts. On the other hand, even though the effectuation-based logistics of prospector firms involve higher costs and unreliable strategy, they lead to reliable performance outcomes in turbulent environments. They are able to establish brighter future prospects for themselves by stepping up their investment in R&D to find innovative processes and products since environmental jolts are seen as opportunities for exploration and exploitation (Gersick, 1991; March, 1991). By comparison, analyzer firms will engage in less R&D investment in process and product improvements. Defenders will invest the least in R&D and most of the investment will be in process improvements. The third period, P3, is when the environment has reached equilibrium under the new normal. During this, firms will adjust their innovative activities and elevate them to higher levels than their pre-disturbance levels. To bolster their innovation efforts, prospector firms might ramp up activities such as bootlegging and introduce new ways such as off-site innovation vestibules—a term borrowed from the HR practice of setting up a work environment in an off-site setting to train workers under the guidance of an expert (Lefkowitz, 1970). Defenders will revert to seeking new ways of cost cutting and analyzers will be wedged between the two strategic types as suggested by Miles and Snow (1978). Environmental Disruption and Innovation When an environmental jolt occurs, as in Period P2 in Table 3.2, it destabilizes the system’s infrastructure, leaving it in a state of disarray. The resultant revolution causes disruptions in the system’s deep structure, rendering the environment in a state of disarray and organizations left scrambling to find their bearings. The immediate response of organizations following a disruptive event is to ensure the organization’s long-term survival. To forestall organizational deterioration in disruptive environments, firms will increase their activities in process and product innovations. Among the process innovations are improvements involved in the value chain activities that include input, operational, output, and warehousing processes. The goal in process improvement is to minimize production cost so as to protect the firm’s margins. The activity that firms adopt to mitigate the effects of environmental disruptions can be captured in the following proposition: Proposition 7: When environmental disruptions occur, firms will step up their innovation activities in order to maintain their economic viability.

Behavioral Strategy, Innovation, and Environmental Disruptions  ⏹  73

Innovation and Performance It has been established in the extant research that R&D stimulates innovation and technological improvements which, in turn, can lead to improvements in productivity and hence performance (Chan, Lakonishok, & Sougiannis, 2001; Cohen, Diether, & Malloy, 2013; Hirshleifer, Hsu, & Li, 2013; Huergo & Moreno, 2011). Yet, the task of making these connections is made difficult by the fact that R&D investment is such a highly uncertain activity. Moreover, in cases where a firm has had a consistent record of R&D investment, and therefore an increased capacity for innovation, the stock market largely ignores or misvalues that information (Cohen et al., 2013). The following proposition captures this situation: Proposition 8: The amount of R&D investment will drive innovations. Firms with greater investment in R&D will exhibit greater process product innovations in the period following environmental disruptions. Behavioral Strategy, Environmental Disruption, and Innovation The extant research shows that when confronted with changes in the environment, firms respond in one of two ways. One way is to adopt strategic stasis, escalation of commitment (Staw, 1981) and embarking upon strategic persistence (Jansen, 2004), or what some have dubbed the “sticking to their knitting” strategy (Peters & Waterman, 1982). Here, information processing is likely to be approached in a top–down or theory-driven approach guided by the executives’ past experiences in pre-disruption times. An alternative response is to embark upon strategic change to align the organizational product and processes with the emerging realities. It is here that we believe that behavioral strategy plays a key role in enhancing the executives’ abilities to perceive the radical changes in the environment, discard the organization’s traditional routines and processes rendered obsolete by the changes, and adopt innovative processes and procedures (Akgün, Lynn, & Byrne, 2003; Sabahi & Parast, 2020). Proposition 9: Behavioral strategy mediates the relationship of environment and innovation. Firms that follow the tenets of behavioral strategy are more likely to engage in innovation in the period following disruptive events. Behavioral Strategy, Innovation, and Performance The orthodoxy in the extant literature has been to attribute successful innovations primarily to the individual agency of the entrepreneur in

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isolation from social interaction. But research shows that successful entrepreneurial activities occur in a social environment in which the entrepreneur is embedded. The developments in behavioral strategy showing the centrality of social cognition challenge the orthodoxy of the enterprising individual suggesting that it is through the web of interactions with others that more effective product and process innovations are brought about in rapidly changing environments (Fiske & Taylor, 2021; Walsh, 1995). In fact, researchers in social cognition generally assume that it is the shared and interactive cognitive representations of actors that mediate the behavioral responses of the collective to social phenomena (Strack & Förster, 2009). We suggest that two firms with the same amount of R&D investment can follow divergent innovation paths depending on the strategies they follow. It is in that sense that behavioral strategy mediates innovation and performance. Hence the following proposition: Proposition 10: Behavioral strategy mediates the relationship of innovation and performance such that innovations of firms that follow the canons of behavioral strategy are more likely to lead to higher performance. DISCUSSION In this chapter we reviewed the streams of literature on organizational environments, strategy, and innovation, and the extent to which they affect organizational performance. Historically, the main question that strategic management answers has been why some firms succeed and why others fail. The evidence from the field pointed to environmental vicissitudes or the strategic choices that organizations make or both as the determinant of success or failure (Hrebiniak & Joyce, 1985). Strategic responses to these questions have typically been predicated on relatively stable environments in which incremental changes sufficed. Under such conditions, organizations could afford to use rational decision-making in their planning and reach their performance goals without much deviation between the projected and actual performance. When environmental disruptions occur, they cause radical alterations in the institutional infrastructure of the environment in which organizations operate. In reference to the punctuated paradigm theory we noted earlier, paradigm shifting events seem to occur in greater frequencies and within decreasing time intervals. This requires organizations to be fleet-footed in adjusting to these changes. Our point is that the key to fleet-footedness is the ability to innovate, and that the culture of innovation must be embedded in the organization’s DNA. The literature points to the generative causal link between innovative use of resources and performance noting that mere possession of dynamic capabilities does not

Behavioral Strategy, Innovation, and Environmental Disruptions  ⏹  75

contribute to the firm’s sustainable competitive advantage—it’s their effective deployment and innovative use that does (Luo, 2000; Mahoney, 1995; Penrose, 1959). Most research points to the culture of innovation and exploration as an important enabler and difference maker for survival in disruptive environments (Osiyevskyy, Shirokova, & Ritala, 2020; Sabahi & Parast, 2020). However, a question that is still of interest to research concerns the processes involved in creating a culture that supports innovation. Our propositions suggest several ways whereby organizations can create the culture of innovation. In the first six propositions we attempt to show the qualities that innovative firms should nurture in order to create and sustain a culture of innovation. We looked at prospect theory (Kahneman & Tversky, 1979) as an explanation of success and failure of risk-taking, risk-averse behavior. Under conditions of environmental disruption, we predict that risk-taking and innovative firms—or prospectors in the Miles and Snow (1978) typology—will tend to overweight gains and implement innovative strategies. By definition, defender firms are risk-averse, and we therefore predict that they will tend to overemphasize losses and hence be rendered ineffectual under disruptive environmental changes. Other propositions related such factors such as the intellectual breadth of sense-making deriving from the processes of behavioral strategy that enable a firm to have greater ability for anticipating major disruptions, such as COVID-19. In this regard, as noted earlier, signs of COVID-19 had been detected by experts in epidemiology (Murphy et al., 2020). Had the information been more widely available, it would have been possible for organizations to take steps to mitigate the severity of its impact. The last four propositions suggest that behavioral strategy plays an important mediating role between environment, innovation, and performance. On one hand, when disruptive events occur in the environment, behavioral strategy can be more effective in the formulation of the appropriate innovative strategies. Similarly, when it comes to implementation, behavioral strategy once again plays a pivotal role in determining the most appropriate of innovative strategies to adopt. Turning to the implications of behavioral strategy for the firm’s ability to innovate, a few advantages can be identified. Firms develop resilience in their operations and supply chains as a result of the dynamic capabilities deriving from prior investment in R&D (De Carvalho, Ribeiro, Cirani, & Cintra, 2016; Sabahi & Parast, 2020). A study conducted in Brazil in the years following the 2008–2009 global financial crisis, demonstrated that firms that committed greater resources to innovative activities were more resilient in sustaining higher financial performance than their non-innovative counterparts (De Carvalho et al., 2016). In the study, resilience was defined as the ability and capacity of an organization to withstand unexpected environmental changes, discontinuities, and risks. Another recent study

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conducted in Russia on strategic management approaches under economic crises and related turbulence showed that when a crisis situation poses an existential threat to organizations, firms can respond by adopting the risktaking, innovation-focused exploitative strategy, or the production oriented efficiency-focused explorative strategy (Osiyevskyy et al., 2020). Of the two strategies, the results of the study demonstrated that the best approach is the exploitative strategy rather than explorative strategy. Thus, a firm committed to innovation can cope with declining performance during crisis periods through exploitation of new opportunities until the broader crisis situation is resolved. An important bridging factor that connects innovation, resilience, and sustained performance is the information sharing that is an integral defining characteristic of behavioral strategy. Through communication and greater capacity for tolerance of activities off the beaten track, firms foster a climate and culture of innovation among their employees. For instance, they encourage activities such as the bootlegging seen in organizations such the Minneapolis Mining and Manufacturing Company—3M (Peters & Waterman, 1982). It should be noted, by contrast, that while bootlegging has many advantages, red flags have been raised concerning the risks involved when bootlegging behavior becomes widespread in organizations (Globocnik, 2019). There may be risk involved with the salience of opportunities and the threats inherent in employees “going underground” with their innovative breakthroughs. This effect becomes weaker when managers provide more support in the form of resources and feedback, whereas encouragement to innovate strengthens the relationship. CONCLUSION We began the chapter by noting how strategic management gradually evolved from the assumptions of a predictable environment to the current environments characterized by disruptions, hypercompetition, turbulence, jolts, and “black swan” events (Ansoff, 1991; D’Aveni, 1994; Miller & Friesen, 1983; Mintzberg, 1994b; Spender, 2014; Taleb, 2007; Theobald, 1994; Venkataraman & Van de Ven, 1998). Over the years, the strategy literature has increasingly been recognizing environmental turbulence as having an important moderating influence in the relationship between planning and performance, which are at the higher end of environmental turbulence. Under such circumstances, resorting to normative corporate response typologies such as the generic competitive strategies is sure to lead to failure. We note that more recent empirical research has shown that the relevance and utility of deliberate/normative strategy (Mintzberg & Waters, 1985) diminishes and gets eclipsed by “emergent” strategy approaches as environments become more turbulent (Kopmann, Kock, Killen, &

Behavioral Strategy, Innovation, and Environmental Disruptions  ⏹  77

Gemünden, 2017). That is why some researchers have moved away from the neo-classical assumptions of decision-makers as strictly rational, utility maximizing agents. To find ways to improve decision-making, behavioral strategy has increasingly shifted attention to employing concepts from cognitive psychology and behavioral economics. This increases the probability to anticipate environmental disruptions, and fosters the ability to join the dots in making strategic choices in the interface of rapidly changing environments, innovation, and performance goals. Although research abounds on each of these factors either singly or in two at a time, to date there is a paucity of research located on their combined intersectionality to suggest approaches that organizations can use to withstand disruptive environmental events when they occur. The chapter was an initial attempt to fill that lacuna. We presented propositions that might assist future researchers in finding the appropriate alignments among the factors that will hopefully pave the way to innovative ways for mitigating the impact of turbulent and disruptive environments. REFERENCES Adner, R., & Helfat, C. E. (2003). Corporate effects and dynamic managerial capabilities. Strategic Management Journal, 24(10), 1011–1025. https://doi.org/10 .1002/smj.331 Akgün, A. E., Lynn, G. S., & Byrne, J. C. (2003). Organizational learning: A sociocognitive framework. Human Relations, 56(7), 839–868. https://doi.org/10 .1177/00187267030567004 Aldrich, H. E. (1979). Environments and organizations. New York, NY: Prentice-Hall. Aldrich, H. E., & Pfeffer, J. (1976). Environments of organizations. Annual Review of Sociology, 2(1), 79–105. https://doi.org/10.1146/annurev.so.02.080176.000455 Ansoff, H. I. (1991). Critique of Henry Mintzberg’s “The design school: Reconsidering the basic premises of strategic management.” Strategic Management Journal, 12(6), 449–461. Antipova, T. (2021). Coronavirus pandemic as black swan event. In T. Antipova (Ed.), Integrated Science in Digital Age 2020. ICIS 2020. Lecture Notes in Networks and Systems (Vol. 136, pp. 356–366). Cham, Switzerland: Springer. Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. Baumol, W. J., & Benhabib, J. (1989). Chaos: Significance, mechanism, and economic applications. Journal of Economic Perspectives, 3(1), 77–105. Bicen, P., & Johnson, W. H. (2015). Radical innovation with limited resources in high-turbulent markets: The role of lean innovation capability. Creativity and Innovation Management, 24(2), 278–299. Boin, A. (2009). The new world of crises and crisis management: Implications for policymaking and research. Review of Policy Research, 26(4), 367–377.

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CHAPTER 4

OPEN INNOVATION THROUGH A COLLABORATIVE COMMUNITY OF FIRMS An Emerging Organization Design Charles C. Snow Refik Culpan

ABSTRACT We develop a model of the multi-firm collaborative innovation process using data on Blade.org—a collaborative community of more than 200 firms in the computer server industry. We argue that a collaborative community is a new way of organizing for open innovation, following the three established approaches of alliances, static networks, and outsourcing. A collaborative community of firms is a powerful organizational form for firms wanting to pursue product/service and market opportunities in environments where knowledge is complex and widely distributed. We expect this organizational form to be used increasingly in knowledge-intensive industries where continuous innovation is a strategic objective.

Innovation and Behavioral Strategy, pages 85–107 Copyright © 2022 by Information Age Publishing www.infoagepub.com All rights of reproduction in any form reserved.

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INTRODUCTION Firms today understand that they cannot be continuously innovative by going it alone. Increasingly, firms are involving their customers, suppliers, and other external parties in product and technological innovation—a phenomenon referred to as “open innovation” (Chesbrough, 2003, 2006; Chesbrough & Appleyard, 2007). An open innovation philosophy and process can help firms innovate by reducing the cost of product development and process improvement—accelerating time to market for new products; improving product quality; and accessing customer, supplier, and other external knowledge and expertise. Until recently, the open innovation process has taken three main forms: alliances, static networks, and outsourcing. For example, firms in a particular industry may form a consortium or other type of alliance in order to pool their R&D resources (Culpan, 2002). Alternatively, a firm may construct a fixed network of outside specialists that they can rely on to enhance the innovation process. Procter & Gamble’s Connect and Develop program (Huston & Sakkab, 2006) is one such effort. Last, firms may turn to outside resources for help when their own internal innovation initiatives become stalled. For example, many firms have outsourced their intractable problems to Innocentive, a company that provides a market in which independent scientists and hobbyists act as external problem solvers for those companies. A new form of open innovation is emerging, and given its initial success, it may grow rapidly in the coming years. We call this form a collaborative community of firms (Miles, Miles, & Snow, 2005; Snow, Fjeldstad, Lettl, & Miles, 2011; Snow, Strauss, & Culpan, 2009a; Snow, Strauss, & Lettl, 2009b). A collaborative community innovates differently from an alliance, external network, or outsourcing partner. Essentially, this organizational approach assembles a group of complementary firms (Stieglitz & Heine, 2007) in which community values and collaborative capabilities and processes enable firms to work with one another temporarily on innovation projects. Based on data on Blade.org, a prominent example of a collaborative community of firms in the computer server industry, we develop and support empirically a model of the multi-firm collaborative innovation process and assess the ability of the collaborative community of firms organizational model to create value for those firms that adopt it. Our chapter is structured as follows. First, we describe the new strategic orientation of large-scale multi-firm collaboration and its associated community values and organizational structures by identifying and describing the factors that have led to this emerging organizational form. Second, we describe our method and data which involve an in-depth, longitudinal study of Blade.org, including the collection of online survey data from Blade.org’s member firms. Third, we build a model of collaborative strategy, structure,

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and process. Last, we make an overall assessment of multi-firm collaborative innovation. We denote innovation outcomes by pointing out the benefits that accrue to community members in the form of new products, access to collaboration partners, and capability development. Our chapter contributes to the innovation management literature in two main ways. First, we identify a new and growing form of open innovation, a collaborative community of firms, by describing its properties, strengths, and limitations. Second, based on the Blade.org case, we build a model of the multi-firm collaborative innovation process that both researchers and managers can benefit from as an important new way of pursuing continuous innovation. COLLABORATIVE STRATEGY AND A COMMUNITY OF FIRMS In order for firms to compete effectively in a complex, dynamic, and highly interconnected global business environment, they have to innovate continuously. Traditionally, firms have relied on their own resources and capabilities to do so. Today, however, in many fields relevant knowledge for innovation is dispersed across firms, industries, and countries. Few firms possess all of the required knowledge and capabilities to single-handedly develop new products and apply new technologies. Moreover, in knowledge-intensive industries the ability to both create and apply knowledge is of vital importance for firm competitiveness and sustainable advantage. According to Chesbrough (2003), In many industries today, the logic supporting an internally oriented, centralized approach to R&D has become obsolete. Useful knowledge is widespread in many industries, and ideas must be used with alacrity if they are not to be lost. These factors create the new logic of Open Innovation, which embraces external ideas and knowledge in conjunction with internal R&D. (p. 177)

Drawing on the logic of open innovation, we develop a conceptual model of the multi-firm collaborative innovation process. Two streams of theoretical thought underlie our model. The first is the knowledge-based view of the firm (Grant, 1996; Nickerson & Zenger, 2004; Nonaka & Takeuchi, 1995; Nonaka, Toyama, & Hirata, 2008). This view says that a firm is a learning knowledge-creating entity, and it argues that knowledge and the capability to create and utilize knowledge are the most important sources of a firm’s sustainable competitive advantage. The second research stream is strategic alliances between and among firms suggesting that firms can create value in the form of new products and technologies by sharing knowledge and other resources (Culpan, 2009; Dyer & Hatch, 2006; Grant & Baden-Fuller, 2004; Inkpen, 1996; Inkpen & Tsang, 2005; Mesquita, Anand,

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& Brush, 2008). Building on these two theoretical streams, we argue that in knowledge-intensive industries, firms are moving beyond the traditional open innovation approaches of alliances, external networks, and outsourcing. The emerging collaborative community of firms organizational model has received research attention because it has demonstrated its ability to create value in the form of innovative products and technologies that is both faster and more effective than alliances, static networks, and outsourcing. Pisano and Verganti (2008) call this approach an “innovation community,” referring to a dynamic network where anybody can propose problems, offer solutions, and decide which solutions to use. They further argue that “it is no longer just a matter of hiring the most talented and creative people or establishing the right internal environment for innovation. The new leaders in innovation will be those who can understand how to design collaborative networks and how to tap their potential” (Pisano & Verganti, 2008, pp. 80). This signifies a major strategic change from a sole-player approach—or even a small number of players in an alliance—to large sets of multiple players working together dynamically and collaboratively. It also signifies a change in the managerial mind-set, moving from “closed” business model to a “collaborative” business model with “multiple partners.” Of course, not every organization is ready for or capable of handling such a paradigm shift. Organizations can undertake such ventures only when they realize their own capabilities and limitations but also foresee the benefits of collaborating with others. Shifting from firm-based innovation to community-based innovation, Lee and Cole (2003) built a model of knowledge creation in purposeful, loosely coordinated, distributed systems as an alternative to a firm-based approach. Specifically, by citing the case of the Linux kernel development project, they demonstrated an evolutionary knowledge creation process in which thousands of talented volunteers, dispersed across organizational and geographical boundaries, collaborate via the Internet to produce an innovative product of high quality. Their community-based model suggests that the product development process can be effectively organized as an evolutionary process of learning driven by criticism and error correction. Along the same lines, but focusing on commercial organizations, Snow et al. (2009b) view a community of firms as a form of organizing in which independent member firms network temporarily with one another and also commit to a set of shared values and norms, and where there are mechanisms to exert moral suasion and to extract compliance from members. Further, Snow et al. (2011) argue that the broad emergence of community-like structures across strategy types, industries, and geographies leads to the proposition that the community model of organizing is a strong complement to the network model of organizing. In order to understand how firms that form and/ or participate in communities achieve long-term competitive success, one

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needs to know (a) the various forms communities may assume and (b) the different ways firms can use communities to leverage their innovation efforts. Last, Miles, Snow, Fjeldstad, Miles, and Lettl (2010) assert that collaborative communities are a powerful means for firms to pursue opportunities in the global marketplace, and collaborative values and capabilities offer a promising approach for addressing the many challenges that the global economy poses. They describe two types of situations in which large-scale multi-party collaboration is required in order to successfully pursue global opportunities or to resolve global problems: (a) situations in which a large number of actors depend on and contribute to a resource commons and (b) situations in which a large number of actors share a common goal, and each actor provides its complementary contribution to the larger system in a coordinated manner. In the next section, we develop a community-based model for innovation based on data from Blade.org where a large group of complementary firms work collaboratively and share common goals and values. METHOD AND DATA Blades, the fastest-growing segment of the computer server market, reached sales of more than $1 billion in 2007 (Miller, 2007). As firms look to grow their data centers or replace aging infrastructures, many are employing Blades to save space, increase density, and decrease power consumption while lowering total cost and improving infrastructure flexibility. Blade.org was established in 2006 by IBM, Intel, and six other founding firms to promote the development and innovation of blade technology to help customers meet the growing demands on their information technology (IT) systems. We and our colleagues have been studying Blade.org since 2007. Members of the research team have conducted multiple interviews with leaders in Blade.org’s principal office and with various executives and technical specialists in five member firms, including two of the founding firms and one international member firm. We have also attended, and gathered data at, two all-member meetings of Blade.org which are held three times a year. In May 2008, we conducted an online survey of Blade.org member firms that focused specifically on community-of-firms organizational issues and processes, and these data are reported here. We remain in contact with the executives in Blade.org’s principal office in order to monitor and analyze developments as they occur. Origin and Purpose of Blade.org The origin of Blade.org can be traced to August 2004 when IBM announced that it was opening the specifications to its BladeCenter server

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chassis (Clabby Analytics, 2007). IBM stated that its goal was to build a developer community that would focus on expanding the number of solutions that could be made available from its promising blade architecture. IBM also noted that it could not drive all innovation on blade applications itself; it expected its partners to play a major role in creating future blade-based solutions. In February 2006, IBM announced the formation of an independent organization (Blade.org) that would serve as the facilitator for a community of blade developers, and it invited relevant vendor and user firms to provide feedback and develop solutions (products) specifically for BladeCenter. The economic purpose of Blade.org is to foster and accelerate the growth of solutions based on the blade processor technology. The specific purposes for which Blade.org is organized include: enabling the ongoing development of blade-based solutions, helping to bring solutions to the market in a timely fashion, increasing the adoption and number of solutions in both existing and new markets, and increasing customer confidence in blade-based solutions. The Blade.org community undertakes a wide variety of activities to achieve these purposes, including the provision of guidelines to member firms for designing their solutions, developing independent compliance testing procedures that member firms may use, hosting industry-wide SolutionFests and other marketing events, educating the marketplace on blade platform solutions, and incorporating member concerns and preferences into strategic initiatives that expand and improve the community. Membership and Governance Structure Blade.org has three membership categories: governing members, sponsoring members, and general members. Governing member firms, each of whom has a representative who sits on Blade.org’s board of directors, are limited by the organization’s bylaws to 11 in number and include the original eight founding firms (Brocade, Citrix, IBM, Intel, Network Appliance, Nortel, Novell, and VMWare). Governing member firms pay annual membership dues (as do all member firms except customers), entitling them to certain rights (see www.Blade.org Membership Benefits, 2008; Bylaws of Blade.org, 2006): • Opportunities to collaborate with other Blade.org solution providers • Influence the direction of the blade server market • Networking opportunities with industry leaders at trade shows and other industry events • Increased visibility within the marketplace • Ability to leverage Blade.org’s marketing activities including use of the Blade.org logo in promotional literature

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• Use of independent compliance testing arranged by Blade.org • Increased media coverage through access to Blade.org’s public relations firm • Speaking opportunities at Blade.org events • Free banner advertising on the Blade.org website and various discounts • Ability to appoint a member of the board of directors • Eligibility for their employees to serve as cair of a technical committee or subcommittee and to participate in the activities of any committee or subcommittee • Influence the agenda of all-member meetings. Of these various rights, the core rights that accrue from membership in Blade. org are opportunities to collaborate with other member firms and eligibility for participation in the work of technical committees and subcommittees. Sponsoring member firms are of three types: 1. They are currently distributing or developing hardware, software, or services offerings for the blade platform. 2. They provide consulting or distribution support for blade-based solutions or products. 3. They currently use blade platform solutions. Sponsoring members have the same rights as governing members except for the right to appoint a representative to the board of directors. Last, a firm can become a general member of Blade.org if it has a legitimate business interest in participating in the community and is willing to publicly support Blade.org and its mission by being listed on the organization’s website and in press releases. A general member must be approved by a majority vote of the board of directors. In early 2008, Blade.org began to offer free membership to its corporate customers (called end users). End user membership benefits include invitations to participate in a variety of technical and marketing activities, an opportunity to join any Blade.org committee or subcommittee, access to a forum where they can voice concerns and suggestions directly to Blade. org vendors, and an opportunity to network with other firms which allows customers to share best practices within the blade community. Overall, such benefits allow customers to influence the overall direction of the blade market as well as solution development. Blade.org operates as a “program” under the auspices of the Industry Standards and Technology Organization (ISTO). ISTO, whose parent organization is the long-established Institute of Electrical and Electronics Engineers (IEEE), was started in 1999 as a not-for-profit corporation that offers

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industry groups (e.g., consortia, special interest groups, alliances, forums, working groups) support for technology and standards development. The IEEE-ISTO serves as an umbrella organization to provide a legal forum for industry groups to operate without the need to incorporate. Programs of the IEEE-ISTO enjoy the legal protections and insurance benefits of operating within an incorporated, fully insured, nonprofit organization. The IEEE-ISTO provides a complete menu of administrative and operational support, leaving Blade.org’s member firms free to focus on the community’s mission and activities. Blade.org has a principal office located in Research Triangle Park, North Carolina (contiguous to the cities of Raleigh, Durham, and Chapel Hill). The principal office houses the strategic leadership of Blade.org, and its executives plan and organize strategic initiatives designed to expand and enrich the community. Initiatives are developed using feedback from Blade. org’s member firms. In addition, Blade.org has nine technical committees staffed by volunteers from the member firms. These committees are organized by function and include committees on technology, solutions architecture, hosted client work group, power and cooling, compliance and interoperability, marketing, small and medium businesses, membership benefits, and bylaws and membership. The Blade.org volunteer committees perform a dual function for the community of firms: They do work that is useful to the community as a whole, and they serve as a repository of knowledge that member firms can tap into when needed. Thus, the committees are keepers and developers of the community’s knowledge commons. Collaborative Innovation Processes The key to understanding Blade.org’s organization design is to focus on the strategic role it is playing. IBM is the inventor of the blade technology, and it holds a number of patents related to that technology. Given IBM’s size and capabilities, creating one or more dedicated blade business units which, in turn, would partner with select suppliers and lead users would be the taken-for-granted approach to developing commercial applications for the blade technology. However, rather than attempting to exploit the blade IP through its own business units or through specific technology alliances with other firms, IBM, along with its fellow founding firms, chose to form a collaborative community of firms focused on accelerating the development and adoption of blade server solutions. Thus, the founding firms created an organizational system (or “platform”) that enables the member firms to develop their own solutions. Solutions are developed through inter-firm collaborations which can take one of four main forms: (a) bilateral collaboration (a Blade.org

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member firm collaborates with its customer on a new solution, perhaps using consulting advice from IBM as the inventor of the blade technology); (b) direct collaboration (a small temporary network of member firms work together on the development of a new solution); (c) pooled collaboration (Blade.org member firms supply ideas, information, and experiences to a central database called Bladeuser.org that is accessible by member firms wanting to pursue innovation projects); and (d) external collaboration (a Blade.org member firm works with a non-Blade.org firm on a one-off bladebased innovation project). Findings From the Online Survey In 2007, an online survey was conducted with the member firms of Blade.org to determine their motives for joining the community as well as their attitudes and opinions regarding Blade.org’s processes and benefits. A total of 50 of the 61 member firms at the time replied to the survey, resulting in a response rate of 82%. The membership types of responding firms are 27% governing members, 22% sponsoring members, and 51% general members. The types of firms are shown in Figure 4.1. As the data show, most Blade.org participants are hardware providers followed by end users (customers), software providers, developers, distribution partners, and resellers. (Currently, end users outnumber all other types as customers were offered free membership beginning in January 2008.)

Figure 4.1  Types of member firms.

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Figure 4.2  Reasons for joining.

The members of Blade.org are highly motivated to be involved in the community as the data in Figure 4.2 indicate. The primary motivation for joining is to keep up with technical and market developments, and this is closely followed by the perceived opportunity to collaborate with the founding firms and with other member firms. Member firms perceive the community as an ecosystem of collaborative learning and innovation. By joining the community, member firms seek primarily the benefits of identifying potential collaboration partners and obtaining new knowledge (see Figure 4.3). Regarding collaborative relationships, member firms expressed favorable opinions (agree and strongly agree) in the following areas: identify and evaluate new collaboration partners, access to collaboration partners, willingness to collaborate with other member firms, improve ability to innovate, acquire new technical capabilities, and improve existing technical capabilities (see Figure 4.4). In terms of community identity and inter-firm trust, both of which are considered to be essential for the success of collaborative innovation, the data show that the majority of member firms agree or strongly agree with the following factors: identifying with Blade.org values (openness, sharing, voluntarism, etc.), expecting that other firms in the community will carry out the activities that they have agreed to, believing that the firms in the

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Figure 4.3  Perceived benefits of membership.

Figure 4.4  Collaborative relationships.

community have the abilities to do what they say they will do, considering Blade.org membership to be important to their identity, believing in the importance of supporting the Blade.org community by contributing ideas and knowledge even if they do not directly benefit, and perceiving that firms in the community act in mutually beneficial ways. All of these perceptions and beliefs reflect a strong sense of community identity and the existence of trust among the member firms (see Figure 4.5.

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Figure 4.5  Community identity and inter-firm trust.

The responses of the member firms regarding community leadership are shown in Figure 4.6. The data indicate that in all areas (albeit less in helping form linkages among member firms and recruiting new members) member firms think that Blade.org leaders play an effective facilitating role. These areas include: helping members and prospective members understand the benefits of collaboration within the community; being effective in planning and organizing strategic initiatives that help the community as a whole; contributing to the formation of social relationships among the members; acting in the interests of the community as a whole; supporting member firms in the creation and pursuit of common goals; motivating member firms to participate and openly share valuable knowledge; creating an atmosphere of trust within the community; being active in identifying roles, capabilities, and goals of individual member firms; and balancing differences in goals and interests among member firms. Overall, the data indicate that the leadership of Blade.org is largely effective in the eyes of member firms. The data displayed in Figure 4.7 delineate the types of investments made by the member firms. Investments in the community include the

Figure 4.6  Community leadership.

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Figure 4.7  Investments in the community made by member firms.

provision of collaborative software, testing equipment, and conference facilities. These resources were largely provided by the founding firms, and member firms’ investments in these areas are small. The major investment made by member firms is time—time to learn about the blade processor technology, the products and business practices of other member firms, how to transfer knowledge to other firms, and how to collaborate. Overall, member firm time investments are significant while capital and financial investments are small. At bottom, every business strategy and organization design is judged by its outcomes and performance. The survey results in this regard are shown in Figure 4.8. Member firms agree or strongly agree that the Blade.org community is achieving the following results: lowering the costs of bringing innovations to market, reducing the time required to bring innovations to market, creating innovations that are effective in the marketplace, increasing end user satisfaction with products and services, strengthening relationships with existing customers, developing new customer relationships, working with customers who are on the leading edge of market or technological trends, strengthening relationships with existing suppliers, developing new supplier relationships, working with suppliers that are on the leading edge of market or technological trends, developing innovations that could not have been done alone, developing novel or “non-obvious” solutions (as opposed to incremental solutions), ensuring that products and services

Figure 4.8  Community outcomes and member firm benefits.

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Figure 4.9  Overall satisfaction of member firms.

are compatible with industry standards, increasing the ability to create new products and services on a continuous basis, and increasing the ability to act entrepreneurially (i.e., to identify and develop business opportunities beyond a member firm’s current domain). Thus, the data show that the Blade.org organizational model is producing numerous benefits for member firms and that these benefits far outweigh costs and investments. Lastly, the survey asked member firms to assess their overall satisfaction with their experiences in Blade.org. They answered that they were satisfied as follows: 37% strongly agree, 41% agree, 18% neutral, 4% disagree, and 0% strongly disagree (see Figure 4.9). These responses, along with those shown in Figure 4.8, suggest that the member firms have generally benefited from their involvement in Blade.org and are satisfied with their experiences to date. Coupled with the fact that Blade.org member firms developed more than 60 solutions (new products) during the first 18 months of the community’s existence, it appears that the community of firms organizational model is effective both in generating innovations and in facilitating member firms’ collaborative efforts. CONCEPTUAL MODEL OF COLLABORATIVE INNOVATION IN A COMMUNITY OF FIRMS Based on the online survey data, as well as contextual data obtained through interviews, we develop a conceptual model consisting of three main components: collaborative strategy, a community of firms as an organization design, and the innovation outcomes of such an arrangement (see Figure 4.10). The model is summarized below.

Collaborative Strategy

Ability to influence development of blade processor market

Business networks of the founding firms used to invite complementary firms into the community

Mission and vision statements that describe the community’s technical and economic purpose

Opportunities to collaborate with founding firms and other member firms Obtain new knowledge and ideas

IBM’s reputation used to attract relevant firms

Community Creation

Access to new business opportunities

Perceived Benefits

Maintenance and development of the knowledge commons by the technical committees

Belief that member firms care about each other’s welfare

Belief that fellow member firms will act in mutually beneficial ways

Belief that fellow member firms are competent and dependable

Administrative services provided by IEEE-ISTO Infrastructure and strategic initiatives provided by the Principal Office

Member firms identify with collaborative values of Blade.org

Identity and Trust

Legally binding bylaws support the governance system

Community Development

Organization Design: Community of Firms

Figure 4.10  A model of collaborative innovation in a community of firms.

In environments where knowledge is complex, growing, and widely distributed, firms seek alliances with others, and the locus of innovation is a community of firms

Multifirm Collaboration

Time to learn how to collaborate with other member firms

Time to learn about products and business practices of other member firms

Intangible Assets: Time to learn about blade technology

Capital Assets: Collaboration software, testing equipment and facilities

Investment

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Perceived Benefits From a management perspective, each member firm is driven by incentives, expectations, and perceived rewards. As shown in Figure 4.10, the members of a well-designed community of firms perceive the main benefits to be the opportunity to work collaboratively and to identify potential collaboration partners. Community Creation A key characteristic of an effective community of firms is how it was created. Of foremost importance is the reputation of the founding firms. Also, the process can be enhanced by (a) developing mission and vision statements that describe the community’s technical and economic purposes and (b) using the business networks of the founding firms and effective communication (e.g., a well-designed website) to attract desirable firms into the community. Last, it is important to invite “relevant” firms to join the community. In the case of Blade.org, this meant inviting complementors—firms whose complementary knowledge and skill sets are required to develop the computer server industry in a systematic and effective manner. Community Development A community of firms cannot grow and develop without an appropriate organization structure. In the case of Blade.org, the structure involved legally binding bylaws, administrative services provided by IEEE-ISTO, a facilitator (principal office) that provides infrastructure and strategic initiatives, and knowledge commons maintained and developed by technical committees staffed with representatives from member firms. Identity and Trust An important ingredient of collaborative communities is the member firms’ identification with community values and their trust of fellow members. It is important for members to identify themselves with Blade.org and to value their membership. It is also vital for members to support the organization in an open and voluntary manner and to make commitments to it. Equally important is the degree of trust the members have in the deeds and abilities of other members as well as the belief that member firms care about the welfare of their collaboration partners.

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Investments A community of firms requires initial investments to be made by both the founding firms and the member firms. In the case of Blade.org, the founding firms (primarily IBM) invested in physical assets such as collaboration software and testing equipment as well as the executive staff in the principal office. Investments made by the member firms primarily involved time—time to learn about the blade processor technology, the products and business practices of other community members, and how to transfer knowledge to other firms via collaboration on innovation projects. Outcomes and Benefits Collaborative innovation among the member firms of a community yields numerous outcomes and benefits. In the case of Blade.org, the primary outcome is the ability to conduct open and continuous innovation. At the level of the individual firm, there are numerous benefits including increased capacity to innovate, lower costs of innovation, faster innovation times, and the opportunity to learn and grow. ORGANIZATIONAL AND MANAGERIAL ASSESSMENT OF COLLABORATIVE INNOVATION Based on the case of Blade.org and the related online survey findings, we believe that the collaborative community of firms organizational model appears to be a valuable means of conducting continuous innovation. Nevertheless, there are many important questions that can be raised about this evolving approach. For example, why did a capable and powerful company such as IBM (and its fellow founding firms) choose to form a collaborative community of firms instead of competing in the computer server market by itself? Can other firms form communities that are equally successful? Will the collaborative community of firms model work in other industries and contexts? We believe that most firms would struggle to form a collaborative community of firms, certainly more than IBM and its fellow founding firms did. IBM had participated in the open source software movement in the 1990s and had been a generous financial supporter of the worldwide Linux community in its early years. IBM had built up a large stock of goodwill and experience in community-based organizations. It had also developed an early version of a collaborative community in a large project called Eclipse, and it learned from that experience that a community of firms was a better vehicle for developing products and markets than going it alone (or via a

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series of alliances). When IBM, Intel, and the other founding firms invited relevant and complementary firms in the computer server industry to join a collaborative community, virtually all of them readily accepted the invitation. Without the capabilities and reputation of IBM as a solid collaboration partner, other large firms probably would not be able to form a collaborative community of firms as quickly or as effectively. When the next large collaborative community appears, it is likely to be in a knowledge-intensive industry such as computers or nanotechnology, and we expect it to be formed by a capable, reputable firm whose business philosophy embraces community values and principles. The creation of a community of firms for collaborative innovation means a new strategic orientation and organizational arrangement for firms. It is a result of the dispersion of knowledge across companies and countries and the direct interdependency of collaborating firms to develop product, market, and technological innovations (Powell, Koput, & Smith-Doerr, 1996). Multi-firm collaboration entails some strategic and organizational requirements that may contradict the traditional managerial philosophies and approaches of hierarchical and centralized organizations. Thus, companies interested in this new breed of organization will need to make changes in two major areas. First, as noted above, strategists and managers of such organizations will need to change their mind-set of self-reliance and the soledeveloper of innovation as well as the appropriation of excessive returns from innovation. They must be willing to work with numerous other capable parties to develop new ideas and products/services. The idea of collective generation of innovation lays the foundation for large-scale, multi-party collaboration. Second, in addition to having diverse skills and knowledge, firms wishing to form and participate in collaborative communities must be willing and able to play a facilitator role. From an organizational perspective, the purpose of Blade.org—heavily manifested in the activities of its principal office—is to enable the member firms to identify, connect with, and collaborate with other member firms. Blade.org is not a hierarchical organization; it is a community in which the member firms self-organize using the protocols and infrastructures provided by a facilitator (Bøllingtoft, Müller, Ulhøi, & Snow, 2012). Despite the advantages of achieving innovations through a collaborative community of firms as opposed to hierarchical organization structures, collaborative designs present challenges as well. IBM, for example, believed that it would be better off by sharing its blade technology with others and by inviting them to develop product applications and to contribute to the technology’s further development. According to Culpan (2002), the starting point in strategic alliance decisions to increase innovation capacity is resource and competence sharing as the means of building competitive advantage. This can be accomplished by exploiting symmetrical competencies,

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deploying asymmetrical competencies, or creating new competencies. IBM and the other founding firms, as well as the member firms of Blade.org, have openly shared valuable resources within a commercial framework that permits each firm to pursue both its individual and collective interests. In their study, Ozcan and Eisenhardt (2009) found that executives are more likely to assemble high-performing portfolios when they visualize those portfolios in the context of the entire industry as opposed to a series of single ties. As the number of members increases, the governance mechanism of a community of firms must accommodate. There is a need for a well-defined governance mechanism in defining the roles of members, the rules of governance, and in facilitating the activities of members and resolving conflicts if they arise. In alliance governance, especially with a multi-party alliance, the large number of contractual and relational interactions and transactions make governance complex. Recognizing this fact, Fjeldstad, Snow, Miles, and Lettl (2012) have offered a governance framework for multiparty collaboration that is scalable and allows the actors to self-organize. The framework is built on (a) commons where the actors accumulate and share resources and (b) protocols, processes, and infrastructures that enable peer-to-peer collaboration. Leaders of communities of firms need to support member firms in the creation and pursuit of common goals by designing an incentive system such that member firms commit their assets, resources, and time to learn and share knowledge created as a result of their collaborative interactions. When a firm joins a community of firms, it has certain expectations and goals. It is vital for a community of firms to meet member expectations and objectives by providing a trusting and collaborative environment that is conducive to innovation. The main incentives for accomplishing this are opportunities to collaborate with other firms to create value in the form of new products, markets, and knowledge, and to appropriate that value based on recognized contributions. CONCLUSION A collaborative community of firms such as Blade.org has emerged as a result of circumstances where knowledge is complex, growing, and widely distributed, thus stimulating the need for multi-party collaboration. Such circumstances cause the locus of innovation to shift from within a single firm to groups and communities of firms. We do not suggest that open innovation conducted by means of alliances, static networks, and outsourcing will decline but rather that innovation conducted according to a collaborative community of firms model offers a valuable alternative in certain situations. Open innovation strategy implemented through a collaborative community

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of firms marks a reversal of the traditional philosophy and approach that has dominated organization theory and practice for many years. ACKNOWLEDGMENT This chapter, save some minor changes, was earlier published as Snow, C. C., & Culpan, R. (2012). Open innovation through a collaborative community of firms: An emerging organization design. In T. K. Das (Ed.), Strategic alliances for value creation (pp. 279–300). Charlotte, NC: Information Age. REFERENCES Bøllingtoft, A., Müller, S., Ulhøi, J. P, & Snow, C. C. (2012). Collaborative innovation communities: Role of the central services provider. In A. Bøllingtoft, L. Donaldson, G. Huber, D. D. Håkonsson, & C. C. Snow (Eds.), Collaborative communities of firms: Purpose, process, and design (pp. 89–104). New York, NY: Springer Science+Business Media. Chesbrough, H. W. (2003). Open innovation: The new imperative for creating and profiting from technology, Boston, MA: Harvard Business School Press. Chesbrough, H. W. (2006). Open business models: How to thrive in the new innovative landscape, Boston, MA: Harvard Business School Press. Chesbrough, H. W., & Appleyard, M. M. (2007). Open innovation and strategy. California Management Review, 50(1), 57–76. Clabby Analytics. (2007). Blade.org: The snowball effect. Retrieved from http://clabby analytics.com/uploads/Blade.org_-_The_Snowball_Effect_Final_Final.pdf Culpan, R. (2002). Global business alliances: Theory and practice. Westport, CT: Quorum Books. Culpan, R. (2009). A fresh look at strategic alliances: Research issues and future directions. International Journal of Strategic Business Alliances, 1(1), 4–23. Dyer, J. H., & Hatch, N. W. (2006). Relation-specific capabilities and barriers to knowledge transfers: Creating advantage through network relationships. Strategic Management Journal, 27, 701–719. Fjeldstad, Ø. D., Snow, C. C., Miles, R. E., & Lettl, C. (2012). The architecture of collaboration: Organizing resources among large sets of actors. Strategic Management Journal. 33(6), 734–750. Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17, 109–122. Grant, R. M., & Baden-Fuller, C. (2004). A knowledge accessing theory of strategic alliances. Journal of Management Studies, 41, 61–84. Huston, L., & Sakkab, N. (2006). Connect and develop: Inside Procter & Gamble’s new model for innovation. Harvard Business Review, 84(3), 58–66. Inkpen, A. C. (1996). Creating knowledge through collaboration. California Management Review, 39(1), 123–140.

Open Innovation Through a Collaborative Community of Firms  ⏹  107 Inkpen, A. C., & Tsang, E. (2005). Social capital, networks, and knowledge transfer. Academy of Management Review, 30, 146–165. Lee, G. K., & Cole, R. E. (2003). From a firm-based to a community-based model of knowledge creation: The case of the Linux kernel development. Organization Science, 14, 633–649. Mesquita, L. F., Anand, J., & Brush, T. E. (2008). Comparing the resource-based and relational views: Knowledge transfer and spillover in vertical alliances. Strategic Management Journal, 29(9), 913–941. Miles, R. E., Snow, C. C., Fjeldstad, Ø. D., Miles, G., & Lettl, C. (2010). Designing organizations to meet 21st-century opportunities and challenges. Organizational Dynamics, 39(2), 93–103. Miles, R. E., Miles, G., & Snow, C. C. (2005). Collaborative entrepreneurship: How communities of networked firms use continuous innovation to create economic wealth. Stanford, CA: Stanford University Press. Miller, R. (2007, December 4). IDC: Sales of blades hit $1 billion in 3Q07. DataCenter Knowledge. http://www.datacenterknowledge.com/archives/2007/12/04/idc -sales-of-blades-hit-1-billion-in-3q07 Nickerson, J. A., & Zenger, T. R. (2004). A knowledge-based theory of the firm: The problem-solving perspective. Organization Science, 15, 617–632. Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. Oxford, UK: Oxford University Press. Nonaka, I., Toyama, R., & Hirata, T. (2008). Managing flow: A process theory of the knowledge-based firm. London, England: Palgrave Macmillan. Ozcan, P., & Eisenhardt, K. M. (2009). Origin of alliance portfolios: Entrepreneurs, network strategies, and firm performance. Academy of Management Journal, 52, 246–279. Pisano, G. P., & Verganti, R. (2008). Which kind of collaboration is right for you? Harvard Business Review, 86(12), 78–86. Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996). Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly, 41, 116–145. Snow, C. C., Fjeldstad, Ø. D., Lettl, C., & Miles, R. E. (2011). Organizing continuous product development and commercialization: The collaborative community of firms model. Journal of Product Innovation Management, 28(1), 3–16. Snow, C. C., Strauss, D. R., & Culpan, R. (2009a). Community of firms: A new paradigm for open innovation and an analysis of Blade.org. International Journal of Strategic Business Alliances, 1, 53–72. Snow, C. C., Strauss, D. R., & Lettl, C. (2009b). Blade.org: A collaborative community of firms. In A. Bøllingtoft, D. D. Håkonsson, J. F. Nielsen, C. C. Snow, & J. Ulhoi (Eds.), New approaches to organization design (pp. 3–21). New York, NY: Springer. Stieglitz, N., & Heine, K. (2007). Innovations and the role of complementarities in a strategic theory of the firm. Strategic Management Journal, 28, 1–15.

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CHAPTER 5

TOWARDS A MORE COMPREHENSIVE CAPITALBASED FRAMEWORK FOR EXPLAINING PERFORMANCE OF SMALL-SCALE ENTREPRENEURS Illustrations From the Ghanaian Marketplace Joseph Ofori-Dankwa Micah DelVecchio Akosua K. Darkwah

ABSTRACT Traditionally, several studies have used financial capital, human capital, and social capital constructs to explain the success of entrepreneurs who operate small-scale enterprises in emerging economies. Entrepreneurial market-traders Innovation and Behavioral Strategy, pages 109–132 Copyright © 2022 by Information Age Publishing www.infoagepub.com All rights of reproduction in any form reserved.

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110  ⏹  J. OFORI-DANKWA, M. DELVECCHIO, and A. K. DARKWAH in Ghana, West Africa, operate within political and economic institutions which have created turbulent environments with few financial safety nets. These market traders also work in highly adverse physical conditions (e.g., fires, floods, hot weather, and unhygienic conditions). When market traders operate in such “double-void” contexts, we argue that financial, human, and social capital are not enough for them to succeed. Such traders need to be highly innovative and have creative decision-making skills. They also need a high level of optimism, determination, and resilience. Consequently, the more currently referenced capital sources (cognitive capital, psychological capital) are particularly relevant in predicting the performance of their enterprises. We use published studies and extensive information about the marketplace in Ghana to develop vignettes that highlight the need for cognitive and psychological capital. We examine the implications of emphasizing cognitive and psychological capital for theory, research, and practice associated with small scale enterprises, particularly those situated in emerging economies.

INTRODUCTION Scholars have long examined the different capital factors which help entrepreneurs operating small-scale enterprises to succeed (Kiggundu, 2002). Traditionally, management scholars have focused on financial capital (Orser, Riding, & Manley, 2006; Van den Brink & Chavas, 1997), human capital (Bates, 1990; Unger, Rauch, Frese, & Rosenbusch, 2011), and social capital (Lyon, 2000; Stam, Arzlanian, & Elfring, 2014) as determinants of productivity and entrepreneurial performance. The effects of these traditional forms of capital (financial, human, and social) have also been well-studied in explaining the performance of small enterprises in emerging economies including West Africa (e.g., Acquaah, 2007; Cleaver, 2005; Honig, 1998; Omri & Ayadi-Frikha, 2014; Robson, Haugh, & Obeng, 2009). Some scholars have been critical of primarily emphasizing such traditional capital sources and have begun to advocate for researchers to focus on alternative capital sources (e.g., Gilbert, 2010; Luthans, Luthans, & Luthans, 2004; Mitchell et al., 2002). We term these alternative capital sources as emerging as a contrast to the more referenced and traditional sources. For example, some scholars have sought to emphasize the cognitive capital aspects associated with entrepreneurship (Boso, Story, & Cadogan, 2013; Grégoire, Corbett, & McMullen, 2011; Mitchell et al., 2002; Mitchell, Randolph-Seng, & Mitchell, 2011). These studies emphasize the importance of cognitive capital characteristics such as having creative and innovative thinking to make good decisions quickly and effectively (Mitchell et al., 2011). Other researchers have advocated a focus on psychological capital (Luthans, Avey, Avolio, Norman, & Combs, 2006; Luthans et al., 2004; Rauch & Frese, 2007). Psychological capital emphasizes the importance of the

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individual entrepreneur’s levels of optimism, determination, and persistence for success (Rauch & Frese, 2007). Building on institutional theory and its underlying institutional theory difference hypothesis (Garcia & Orsato, 2020; Julian & Ofori-Dankwa, 2013; Khanna & Palepu, 1997; Li et al., 2018; Ofori-Dankwa & Julian, 2013), we argue that the benefits of cognitive and psychological capital will be more pronounced in emerging economies. Further, heeding calls for more indigenous theory building for indigenous entrepreneurs (Nkomo, 2015; Peredo, Anderson, Galbraith, Honig, & Dana, 2004), we use Ghanaian marketplaces and the entrepreneurial traders who operate in these markets as the context for this study (Fafchamps, McKenzie, Quinn, & Woodruff, 2014). Ghanaian markets are characterized by double void and highly resourceconstrained environments (Agbeko, Blok, Omta, & Velde, 2016; Shantz, Kistruck, & Zietsma, 2018). We build on extensive direct information about the Ghanaian institutional context (Darkwah, 2001, 2002, 2016; OforiDankwa & Julian, 2013) and use several relevant research studies about the Ghanaian marketplace to develop vignettes that illustrate the very dynamic and highly adverse environments of the Ghanaian marketplace. These vignettes also point to the advantages of creativity and innovation decision-making associated with cognitive capital (Mitchell et al., 2011), and the benefits of determination and persistence associated with psychological capital (Rauch & Frese, 2007). Specifically, the vignettes illustrate the use of cognitive capital and psychological capital by different market women during the government endorsed bulldozed destruction of several marketplaces in Ghana between 1979–1981 (Campbell, 1985; Robertson, 1983); frequent marketplace fires (Oteng-Ababio & Sarpong, 2015; TwumBarima, 2014); flooding of marketplaces, particularly during the annual rainy season (Das & Majumdar, 2019); and the difficulties market women experienced dealing with the national lockdown in Ghana in 2020 during the COVID-19 pandemic (Adebisi, Rabe, & Lucero-Prisno III, 2021; Asante & Mills, 2020). The vignettes also reflect some of the health issues that the market women deal with (Kudzawu, Agbokey, & Ahorlu, 2016; Quaidoo, Ohemeng, & Amankwah-Poku, 2018) and the dangers and difficulties that women hawkers face (Beek & Thiel, 2017; Steel, Ujoranyi, & Owusu, 2014). This chapter is structured in the following way. First, we describe the traditional sources of capital and the newly referenced sources of capital that researchers have been using to explain the performance of small-scale entrepreneurs. Second, we highlight institutional theory and its underlying institutional differences hypothesis and provide six research grounded vignettes to suggest that the cognitive capital and the psychological capital frameworks approaches are particularly relevant in contexts such as marketplaces in Ghana, West Africa. Finally, we examine the implications of emphasizing cognitive and psychological capital for theory, research, and

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practice associated with small scale enterprises, particularly those situated in emerging economies. EXPLAINING PERFORMANCE OF SMALL-SCALE ENTREPRENEURS: TRADITIONAL AND EMERGING CAPITAL-BASED FRAMEWORKS Traditionally, scholars have focused on financial capital (Orser, Riding & Manley, 2006; Van den Brink & Chavas, 1997), human capital (Bates, 1990; Unger et al., 2011), and social capital (Lyon, 2000; Stam et al., 2014) as determinants of productivity and entrepreneurial performance. Several of the above studies have looked at how these different forms of capital are integrated and interact to determine the success of entrepreneurs (e.g., Carter, Brush, Greene, Gatewood & Hart, 2003; Cooper, Gimeno-Gascon, & Woo, 1994; Davidsson & Honig, 2003; Honig, 1998). For example, some researchers (e.g., Carter et al., 2003; Honig, 1998) used all three traditional capital sources (finance, human, & social) to predict the success of small-scale enterprises, while some researchers focused on the financial and human dimensions (e.g., Berge, Bjorvatn, & Tungodden, 2014; Coleman, 2007; Cooper et al., 1994), and yet others focused on human and social capital (Anderson & Moller, 2003). Traditional Capital-Based Models Financial Capital The importance of financial capital in firm performance and in an entrepreneurial startup has been well established (Coleman, 2007; Cooper et al., 1994; Davidsson & Honig, 2003). The extent of capitalization cannot only predict the successful startup of businesses (Cooper et al., 1994) but also the growth (Coleman, 2007) and the long-term viability of small businesses (Bates, 1990; Honig, 1998). In the Ghanaian marketplace specifically, traders seek funding through a variety of formal and informal sources. Formally, traders seek financing for physical capital from financial institutions such as banks and credit unions who provide either cash or in-kind grants (Fafchamps et al., 2014). Over the last few decades, there has been the growth of microfinance institutions (Madichie & Nkamnebe, 2010). Particularly in the Ghanaian context, the importance of financial capital is heightened because of lending uncertainty, higher risk premiums, and therefore a highly constrained market for credit (Fafchamps et al., 2014). A major funding problem that traders face is not only the difficulty of acquiring needed financial assistance but the fact that interest

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rates on loans are exorbitant, including those from the microfinance sector. Consequently, the potential profitability gains could be large if only these prohibitive costs did not exist (Grimm, Krüger, & Lay, 2011). As the ability to raise financial capital is such an essential part of doing business, we anticipate that such an ability will be positively related to performance indicators such as revenues and profits. A relatively well-established and traditional means of finance in West Africa is the susu. A susu is an informal rotating savings and credit association (ROSCA) typically made up of traders who have known each other for a long time and can therefore vouch for the honesty and integrity of the members, thus overcoming the risk premiums associated with asymmetric information (Stiglitz & Weiss, 1981). Members of a susu club will meet on a regular basis to contribute an agreed upon amount which is then given to one member, on a rotating basis. The amounts, however, are not as substantial as what can be acquired in the formal banking system (Bortei-Doku Aryeetey & Aryeetey, 1995; Van den Brink & Chavas, 1997). Human Capital The importance of human capital to the success of small businesses has been well established (Grossman, 2000). For example, the nature of human capital has been associated with the success of entrepreneurial startups (Davidsson & Honig, 2003; Unger et al., 2011) and sustained success of small businesses (Castrogiovanni, 2011). Human capital has been measured and conceptualized in several different ways. A conventional abstraction is to view human capital from an educational perspective and to refer to the formal education that has been received (Becker, 2009). It can also be viewed from a vocational training perspective (Honig, 1998). Human capital is also conceptualized with respect to the current knowledge bundles that an individual has, and which can be effectively utilized in their workplace (Blundell, Dearden, Meghir, & Sianesi, 1999). Therefore, human capital in the form of education for example, enables Ghanaian traders to be more aware of existing and changing market conditions. Further, human capital enables market traders to more easily acquire good financial management knowledge. For example, knowledge of profit-loss statements and inventory management systems, would help a marketplace trader be successful. The lack of human capital, and particularly, the lack of financial information makes it difficult for the small business firms to succeed. Another important conceptualization of human capital comes from a gender perspective (Orser et al., 2006). This conceptualization is particularly important in the Ghanaian context because of the historical, traditional, and systemic disadvantages that women have experienced (Dzapasi & Machingambi, 2014; Lindvert, Yazdanfar, & Boter, 2015; Shabaya & Konadu-Agyemang, 2004). Given that Ghanaian women’s participation in trade

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goes back almost 2 centuries (Cruickshank, 1853; Daniell, 1856; Denzer, 1994), it is important to further explore the implications of gender as a determinant of access to human capital. Social Capital The utility of social capital has long been recognized for business success in general (Davidsson & Honig, 2003) and for traders in emerging economies, in particular (Fafchamps & Minten, 2002; Honig, 1998). In the African context, social capital has been posited as a potentially competitive advantage that businesses can have (Mangaliso, 2001) and has also been linked to trader success especially if channeled into the development of personalized economic relationships (Lyon, 2000; Trager, 1981). For example, Ubuntu, the southern African principle of togetherness, can be seen as a type of social capital which provides competitive advantages to individuals and businesses through a stronger desire to maintain a large relational network (Mangaliso, 2001). To further illustrate, the financial success of some immigrant communities who settle in Africa (e.g., the Lebanese in Ghana) has been attributed to the strong social capital and the associated networks that these community members have (Ramachandran & Shah, 1999). Particularly in the marketplace, social capital provides an advantage in different ways. From a family perspective, if a family has been in business for a long time, they will have a well established and dependable network of suppliers and creditors that become very valuable, in times of market turmoil. Additionally, from a customer base perspective, the level of social capital and the ability to network and establish strong relationships would determine the number of consistent customer bases (Lyon, 2000; Trager, 1981). Emerging Capital-Based Models Cognitive Capital Researchers have long recognized the individual performance implications of cognitive processes in general (Au, Chan, Wang, & Vertinsky 2003; Lipe, 1998) and its impact on the specific performance of entrepreneurs (Fenton-O’Creevy, Soane, Nicholson, & Willman, 2011; Mitchell, Busenitz, et al., 2002; Mitchell, Smith, et al., 2002). While the importance of cognitive capital for entrepreneurs has been recognized (e.g., Mitchell et al., 2011; Randolph-Seng et al., 2015), its full implications, specifically for traders in Ghana, have not been researched. The Ghanaian marketplace is very dynamic with consistently changing marketplace conditions. There is, therefore, a consistent need for market traders to scan the environment, determine the emerging market trends, and make appropriate “buy” decisions. Further, the relatively low market

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entry barriers result in large numbers of new entrants and consequently results in a highly competitive environment. Under such conditions, there are several advantages of a trader having cognitive capital. It will be very advantageous for a market trader to have highly creative and effective decision-making skills (Mitchell et al., 2011). A trader who suffers from paralysis by analysis would be heavily disadvantaged. Further, the market trader is typically self-employed with very few people working for him or her. Consequently, the market traders wear several hats including correctly reading the market to identify what products to purchase and bring to the market and how to creatively attract customers to successfully sell. Under such conditions, it will be very advantageous for Ghanaian market traders to be highly creative and innovative (Mitchell et al., 2011). Psychological Capital As noted above, a substantial amount of research has looked at human, financial, and social capital and the advantages that accrue when these are used in the Ghanaian market context. The amount of research focusing on psychological capital and its performance implications for Ghanaian traders has been relatively less (Rauch & Frese, 2007). Psychological capital is based on the relatively consistent aspects of a market trader’s personality. Luthans et al. (2004) use the term psychological capital to encompass the traits of confidence, hope, optimism, and also resilience. Given the harsh physical conditions (hot weather, unhygienic surroundings, lack of comfortable selling facilities), we posit that it is likely that individuals with higher levels of psychological capital will do better. For example, Frese, Brantjes, and Hoorn (2002) suggest that traders with high levels of psychological capital will be highly motivated, have a high need for achievement, and be more resilient in the face of adversity in the marketplace. These traits are likely to be especially important in how the entrepreneur addresses the difficulties of the Ghanaian marketplace. We, therefore, posit that market traders who do not have a high level of motivation, persistence, determination, and resilience are less likely to be able to survive, let alone thrive in the market. INSTITUTIONAL DIFFERENCE HYPOTHESIS: ILLUSTRATIONS FROM THE MARKETPLACE IN GHANA Institutional Difference Hypothesis Institutional difference hypothesis (IDH) is the theoretical undergirding for this chapter. IDH suggests that there are substantial institutional differences between developed and underdeveloped economies and these differences consequently determine what business strategies will be successful in

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these different contexts (Khanna & Palepu, 1997; Khanna & Rivkin, 2006). Consequently, several studies have sought to illustrate the efficacy of IDH (e.g., Garcia & Orsato, 2020; Julian & Ofori-Dankwa, 2013; Li et al., 2018; Ofori-Dankwa & Julian, 2013). Building on institutional theory difference hypothesis, in the section below, we use Ghana as our study context. We highlight Ghana’s several important institutional differences as compared to more developed economies. We also use research grounded vignettes to further illustrate the substantial institutional differences between developed economies and developing economies such as Ghana. We specifically argue that given the relatively adverse institutional and business environments that women traders in Ghana operate in, the benefits of cognitive and psychological capital will be more pronounced in such emerging economies. Ghana, West Africa’s Resource Scarce and Turbulent Marketplace Context Marketplaces in Ghana are typically and traditionally large spaces with many clusters of traders, most of whom operate out of small stalls and kiosks or sell in the open (Darkwah, 2001). Slowly, there has been an increasing trend of market women trading globally (Darkwah, 2002, 2016, 2021). While the market traders are predominantly women, there are specific items such as construction and automotive items that are mostly sold by males. To get a good understanding of the difficult conditions in which Ghanaian marketplace traders operate, we need to first consider the national resourceconstrained environment in which the markets are embedded. Markets in Africa are characterized by both the substantive lack of efficient economic institutions and a lack of the physical factors of production. The marketplace traders have consequently been described as operating in a “double void” context (Ofori-Dankwa & Julian, 2011). There are high levels of credit constraints with annual interest rates typically well over 30%, low levels of infrastructure development, and substantial tension between traditional and modern socio-cultural practices (Ofori-Dankwa & Julian, 2013). The difficulty of operating small-scaled enterprises in such a context is further compounded by market related factors. Some of the segments in the market, such as those associated with petty trading and reselling, have relatively low entry barriers. The low costs of entry cause a large influx of traders into the marketplace, including rural-urban migrants, thereby increasing levels of competition (Fafchamps et al., 2014). Other segments of the market, such as those trading in construction and technological equipment have high entry barriers primarily because of their capital-intense nature. The difficulties associated with the importation of these goods are further compounded by the substantial difficulty in acquiring capital

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funding and the cost of financing (Fafchamps et al., 2014). The lack of basic marketplace infrastructure and unclear tax regimes make these difficult conditions even more strenuous (Clark, 1994, 2010; Darkwah, 2001; Skinner, 2010). For example, traders often have to sell in adverse conditions (e.g., very hot and unhygienic surroundings, without adequate building facilities). Market traders in Ghana often operate their small business out of necessity (Kuada, 2015). The necessity-oriented entrepreneur is especially prevalent given that most of the Ghanaian markets are female-dominated marketplaces (Calderon, Iacovone, & Juarez, 2017). In such a context and consistent with previous literature, we argue that having the traditionally referenced financial, human, and social capital sources are clearly advantageous for Ghanaian traders. We, however, argue that the highly adverse physical, infrastructural, and financial conditions under which the traders operate requires additional forms of capital. More specifically, this context requires the creativity and innovation of cognitive capital and the determination and persistence of psychological capital to keep the marketplace trader abreast with the exigencies of the market. SIX RESEARCH GROUNDED VIGNETTES We provide six vignettes showing the type of business challenges in the marketplaces of developing economies such as Ghana. These vignettes strongly emphasize why cognitive capital and psychological capital matter in these contexts. Cognitive capital reflects innovation, the ability to be adaptive and use creative problem-solving skills. Psychological capital has its focus on attitudes and traits such as persistence, determination, and resilience. These vignettes, which draw on scholarly accounts of the marketplace, reflect the reality of the marketplace. Specifically, the vignettes illustrate the use of cognitive capital and psychological capital by different marketplace women in several historical instances. We examine the following cases: 1. The government-endorsed bulldozing and destruction of several marketplaces in Ghana between 1979–1981 (Campbell, 1985; Robertson, 1983) 2. The frequent marketplace fires (Oteng-Ababio & Sarpong, 2015; Twum-Barima, 2014) 3. The flooding of the marketplaces, particularly during the annual rainy season (Das & Majumdar, 2019) 4. The difficulties marketplace women experienced in dealing with the national lockdown in Ghana during the COVID-19 pandemic (Adebisi et al., 2021; Asante & Mills, 2020)

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5. The healthcare challenges that marketplace women face (Kudzawu et al., 2016; Quaidoo et al., 2018) 6. The dangers and difficulties that women hawkers face (Beek & Thiel, 2017; Steel et al., 2014) These 6 cases have been chosen to illustrate how the above forms of capital would be necessary to survive and succeed in both rare instances (e.g., the government’s destruction of the marketplace), along with more predictable and frequently occurring adverse events. DESTRUCTION OF THE MAKOLA AND OTHER GHANAIAN MARKETS, 1979–1981 Akosua owns a small business in Makola Market, selling beads and trinkets. She has been a trader for several years. In meetings with her fellow traders during and after work, their discussion centered on the consistent government propaganda suggesting that the traders were hoarding goods like sardines and milk, and price gouging—making it difficult for the average Ghanaian to afford these goods. They also noted that top government officials consistently characterized them as “enemies of the revolution,” a revolution that all of the women knew was little more than a coup d’état. Very early one day, they saw several military helicopters flying very low over the open-air marketplace. Everybody was afraid. No one knew what to expect. Akosua, always a proactive quick thinker, systematically packed up all her beads and trinkets and safely transported them to the safety of her home. The next morning, she went back to the marketplace and without warning, the soldiers came! They came with bulldozers and looted the market stalls as they bulldozed the stalls. Market women who protested were stripped of their clothing and publicly caned. Akosua rushed home immediately and returned cautiously two days later. To her utter dismay, she saw that the marketplace had been totally bulldozed. She also learned that one of her trading colleagues had tried to fight the soldiers who were destroying her outdoor stall. She had been stripped naked and caned in public as a form of humiliation intended to deter anyone else from resisting. Several months later, the government now more aware that the marketplace entrepreneurs were not the cause of the economic ailments of the country, bowed to public pressure and allowed the marketplace to reopen. Because of her quick thinking, Akosua still had most of her beads and wares. However, when the government reopened the marketplace, she had to make the tough decision to return. She felt very guilty that when she was taking her wares home, she had not warned her friend to do likewise. She felt traumatized and was very afraid that the razing of the marketplace could happen again. In the end, with great determination, and after developing her own ways of coping, she decided to return. To this day, even as she continues to

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make a living trading at the market, she still has nightmares that she must constantly overcome on her own.

THE FIRE IN THE MARKETPLACE Adwoa sells clothing out of her open-air shop in the Makola Market. It is the harmattan season and the dry winds have been blowing all day. In the afternoon, she is drinking some cold water and taking a much needed break. She begins to smell smoke and sees people running and dashing towards the main exit. Immediately Adwoa thinks back to a few years ago, when members of the Ghana Fire Service in Accra had done a short training program in Accra and had handed out pamphlets and discussed the need to plan fire escape routes well in advance. The fire service crew had strongly advocated the need to be extra cautious and the need to evacuate even when it seemed that the fire had gone out. Suddenly there was a strong gust of wind and Adwoa saw a huge blaze shoot up in the sky from behind her neighbor’s stalls. The heat was intense, and the crowd of shoppers and traders rushed toward the main market entrance, the quickest way out. People were falling and being trampled. Adwoa though, years ago, had proactively taken time to survey her location and she realized that the quickest way out was not the safest way out. Though she was afraid, she calmed herself, she took her most valued items, and quickly took a long narrow alley right by the blaze, but away from the crowd. Adwoa did escape eventually, meeting her children at the front door of her home. They had seen the smoke at the marketplace and were very worried that their mom might not return. That night, Adwoa had a dream about a glowing ember jumping up and catching her blouse on fire. She woke, still sweating in fear. But after she calmed down, she envisioned a blouse which blended shapes of sparks with more traditional geometric patterns. The next day, she returned to the marketplace which had been reduced to embers. The fire service crew had run out of water and was unable to save what had been left in her booth. There was one thing left though: a sewing machine that she used to make quick repairs for her customers who needed it . . . a sort of informal warranty program. She brought the sewing machine home and began to sew together the pattern of sparks and shapes she had seen the night before. When the market finally reopened, she marketed the new cloth pattern and blouses. She indicated that this cloth pattern was a sign of resilience of the Makola traders to fire and whatever adversity they faced in their lives. After just one week, to her utter surprise, her new cloth pattern was a big hit and her inventory was quickly depleted. Adwoa took her receipts and bought one more sewing machine, asking her sister to join her in the new

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line of fire-inspired clothing. Given limited access to finance, they slowly but steadily expanded and were able to eventually hire 20 employees who produced for the West African market. Adwoa realized she had a creative gift. Eventually she and her sister transitioned from a small-scale retail of clothing and into dress design, outsourcing the sewing and textile manufacturing to specialist firms across Africa.

FLOODING DUE TO RAIN AND BLOCKED DRAINAGE As far back as her childhood, Abena looked forward to going to the marketplace to help her mother sell her wares. As soon as school was over, and over the weekends, she would go to help her mother sell in the marketplace. Abena truly loved selling. There was only one period when she absolutely hated being in the market. This was when the rains came. The rains would come fast and furious. Soon the entire marketplace was flooded. The floods destroyed people’s property and left a foul stench in its wake. Surprisingly, despite it occurring over and over again, everyone consistently complained, blamed the government and local authorities, and did nothing. Abena’s mother’s death was sudden and totally unexpected. With no one to rely on financially, Abena stopped school, took over the shop and became a full-time market woman. She was determined to do something about the recurring floods. She carefully analyzed and saw that the major problem stemmed from the gutters and drains that were clogged with waste. Abena decided to put in place an action plan to help deal with the clogged drains and gutters. First, she decided to call a meeting of all the stall owners on her entire block. Abena set the meeting for one early Monday morning. The first meeting was a total disaster. Very few of the stall owners turned up, as on Monday morning, all were too busy getting their stalls set up to open. Undeterred, Abena decided to call a second meeting. This time, she solicited the help of one of the leaders in the marketplace, referred to as market queens. She also brought in a well-known pastor to pray for all the women. She provided lunch, locally nicknamed Agenda Item 13, at her own cost. Finally, she held the meeting on a Sunday afternoon, when traditionally, there is a bit of a lull in a marketplace that literally never sleeps. At the meeting, Abena proposed several innovative suggestions to help mitigate flooding when the next rains came. Having the support of the market queen and pastor, most of her suggestions were adopted and overall, the meeting was very successful. All the stall owners agreed to chip in some money. This was used to get laborers to clean out the gutters. Next, she purchased large empty barrels and plastered big signs on the large barrels urging all to put their waste and garbage into the barrels. Next, Abena contracted a garbage removal organization that would come to pick up the garbage on a weekly basis. Finally, she hired a building contractor, who laid a

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large set of pipes that ensured that, if the rains came, the water drained away from their section of the market. The rains came the following year with a vengeance. As usual, most of the marketplace was flooded with several traders losing their goods. However, in Abena’s section of the market, for the first time in memory, the rains came without floods.

IMPLEMENTING COVID-19 REGULATIONS AT THE MARKETPLACE Akua had a well set up restaurant right in the middle of the market. While Akua took pride in being one of the most knowledgeable market women, the occurrence of COVID-19 and the total lockdown of the market that followed took all, including Akua, by total surprise. One late March evening in 2020, the President of Ghana took to the airwaves and announced that because of COVID-19, Ghana was immediately undergoing a total lockdown for weeks. It meant that the market was totally shut down and all traders had to stay home. This was a totally unprecedented occurrence. Akua, with no substantial savings on hand, and totally dependent on the restaurant for income, was in distress; this situation could lead to financial ruin. In Ghana, a nationwide system of unemployment benefits for self-employed people has not yet been set up. Self-employed people like Akua would be hard pressed under such circumstances to support a family. Food distribution by the government and some charitable organizations were also few and far between. Akua immediately thought of several new ideas and quickly implemented them. First, she decided to move her cooking from the restaurant to her home. However, unlike in the United States and other high-income economies, small Ghanaian restaurateurs do not have their own website. Fortunately, there is widespread access to cell phones. Akua had always been well organized and had the telephone numbers of several of her regular clients. She called each of them individually to inform them that she will be able to cook all the old favorites from her menu out of her home but for pick-up only. This got her started. She did not have to work outside the home and was able to cover her costs and take care of herself and her small family. While she did not know how to design her own website, Akua knew a young man who was very good with web designing. She immediately hired this young man from the university and quickly had an app developed that enabled her clients to inform her of foods needed. Next, she entered into an agreement with a delivery service. Clients that needed food contacted her and she sent the food to them. Fortunately, the total lockdown period was relatively short, but the closing of restaurants persisted for a while. Setting up the on-line food distribution process enabled Akua to survive the lockdown and the restrictions on eateries that persisted for a while after that period.

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UNADDRESSED HEALTH ISSUES IN THE MARKETPLACE Yaa was taking a shower when she noticed a small lump on her right breast. She thought nothing of it until she could see that it had gotten bigger. She clearly needed to go to the Korle-Bu hospital. This was the major teaching hospital in Ghana. However, it was always busy. She knew that going would mean a whole day’s worth of sales would be lost. Yaa, a trader at the Kaneshie market, pondered what to do. She decided to wait for a few weeks to see if it got even bigger. Yaa went to church on Sunday and after church, told the pastor of her problem. The pastor prayed for 20 minutes without ceasing and gave her a small bottle of olive oil. The pastor assured her that the olive oil had powerful spiritual and healing qualities and that it would cure Yaa of her breast ailment. To Yaa’s absolute dismay though, the lump seemed to get bigger and bigger. She could no longer ignore it. She needed to do something about her health but she could not afford to lose a day’s worth of sales. Caught in this dilemma, Yaa decided to join her colleagues at the Wednesday prayer meeting, organized by the women’s fellowship of her Methodist church, to put her mind at ease. At that meeting, the leader of the women’s fellowship broached the subject of organizing a health screening exercise on the last Sunday of each month when there were 5 Sundays in a month. In discussing what kind of health screening to organize first, the team settled on breast cancer screening. As soon as that decision was made, Yaa’s mind went into overdrive. This screening could be the answer to her dilemma; she could get her health status checked on a weekend and manage to go to work during the week. Resolved to make sure this screening was held the very next month, which coincidentally had 5 Sundays, she volunteered to join the planning committee. Over the next 2 weeks, she worked closely with the doctors in her church to find volunteer breast cancer specialists who could come to the church with a mobile X-ray and lab facility. Despite the short notice, they got lots of support from the healthcare specialists they approached and organized a very successful event. Yaa also got to have her breast examined. Thankfully, the lump was benign. Yaa resolved afterwards to ensure that her colleagues at the market did not have to endure the stress she felt when she had to choose between her health and her livelihood. She has continued to serve as a volunteer on the health team in her church and she has extended that service to her market as well. She organizes a quarterly health screening service at the market where a volunteer health team arrives to screen for a range of diseases like diabetes, hypertension, and breast cancer.

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DANGERS FOR FEMALE HAWKERS Efua had very little growing up. Her family was homeless for a while, but eventually her mother was able to find a way to pay rent on a tiny apartment. Poor, but physically gifted, Efua was strong and she had the ability to carry goods in the traditional manner by balancing her wares on her head. In the late summer and early fall, oranges are plentiful near Accra, Ghana. Producers will sell extra bushels of oranges to roadside vendors like Efua. She learned the usual methods of walking down a lane of cars parked at a red light, and then walking back up the road before the light turned green and the cars drove away. Sometimes the road became crowded with vendors like herself, so Efua would move to find a new spot. But this year, there were so many women of all ages trying to sell everything from oranges to chilies that Efua was left with unsold oranges and little cash. One Friday she left to go back home. She had been able to afford monthto-month rent on a small cinder-block studio but had missed paying for several weeks and her door locks had been changed. She recalled some abandoned cement buildings that some of the other women who could not afford rent would sleep in. She got there before it was dark and fell asleep in a corner. Efua abruptly woke up to find someone’s hands groping her. Efua rolled over to find an old man standing over her. He then quickly knelt down and laid on top of Efua, pinning her to the ground. Efua was not just strong, but a quick thinker too. She brought her knee up into the man’s groin. As he writhed in pain, she rolled him off of her. She ran out into the night. Efua returned to find that all of her oranges had been stolen. Efua was devastated and depressed. She was, however, determined not to give up. The next morning, Efua came up with the idea to ask if someone wanted help in selling oranges or anything. She asked her friend Amma if she could help and Amma agreed to share her wares for her to sell. Efua then told her what happened and Amma said, “You know what? That same man also assaulted me several months ago.” Efua suddenly had an idea and said, “Amma, you know what we need to do? We should stick together and form a team. We can’t be there alone at night.” Then, throughout the day, as Efua and Amma sold oranges, they spoke to more and more women traders who agreed to form teams to watch over each other and help each other. Slowly, the Women’s Protection Association (WPA) was formed. This was a women’s advocacy association, providing advice and resources for women in need. Weeks went by and the WPA name spread among the female vendors. Everyone knew Efua and Amma. Eventually the women were able to perfect the coordinated effort. Things were so successful that she was able to travel to other parts of Accra and then eventually Tema to share their ideas for women’s advocacy. Efua had become an accomplished labor organizer without even knowing it.

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One day, a university professor came to visit her. The professor had been researching solutions for the protection of women vendors on the city streets. The government of Ghana had been providing grants to the university for this. The professor had heard about the work that Efua was doing and had tracked her down. She hired Efua as a research assistant. Efua learned as she went from place to place, helping to administer the surveys that would become part of a research project. Eventually, Efua herself would finish her schooling and go on to college with a scholarship she was able to obtain given her work history as a research assistant. While earning her degree, Efua learned about advocacy strategies. Upon graduation, she helped to set up the Women’s Advocacy Institute.

RESEARCH AND POLICY IMPLICATIONS Research Implications Some important research implications flow from the ideas associated with this chapter. First, while the traditional capital theories (human, financial, and social) have been well researched (e.g., Carter et al., 2003; Coleman, 2007; Cooper et al., 1994; Davidsson & Honig, 2003), with some of the studies done in an emerging economy context (Honig, 1998), there have been relatively few studies that have utilized the traditional capital theories in the Ghanaian context. A notable example is the study by Acquaah (2007) that looked at the performance implications of social capital in Ghana. Despite the substantive similarities of the Ghanaian economies and those of emerging economies, there may also exist important cultural differences which warrant further study (Ofori-Dankwa & Ricks, 2000). Second, the research grounded vignettes we developed describe government endorsed destruction of marketplaces in Ghana between 1979–1981 (Campbell, 1985; Robertson, 1983); frequent marketplace fires that destroy the property of market traders, several of whom do not have insurance (Oteng-Ababio & Sarpong, 2015; Twum-Barima, 2014); marketplace flooding after the rains (Das & Majumdar, 2019); and the difficulties marketplace women experienced in response to the COVID-19 national lockdown in Ghana (Adebisi et al., 2021; Asante & Mills, 2020). These vignettes confirm and highlight substantial institutional differences between developed economies and developing economies, such as Ghana (Ofori-Dankwa & Omane-Antwi, 2015). Third, given the resource-scarce and turbulent environment that market traders in West Africa operate under, success in such a resource-constrained, hyper-dynamic environment requires strong levels of capitalization in a

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multiplicity of areas. The traditional capital models that have emphasized financial, human, and social capital sources have been effectively used in emerging economies, such as Jamaica, to explain and predict the performance of small-scale traders (Honig, 1998). Given that generally, countries in West Africa can be characterized as being “emerging economies,” traditional models will be useful in helping to understand the factors that will help Ghanaian market traders to be successful. However, as we argue, there is substantial merit in the utilization of additional capital sources. The adverse physical conditions and lack of basic hygiene facilities require persistence, determination, and motivation that is reflected in the psychological capital model. Further, the competition resulting from the low entry requirements and the need for traders to effectively wear multiple hats as they operate, result in a fast-paced hustle and bustle marketplace requiring a high level of creativity, innovation, and entrepreneurial decision-making that is reflected in the cognitive capital models. Fourth, our chapter raises an intriguing research question. We have categorized three well referenced capital theories (financial, human, and social) as traditional, then contrasted them with the more recently referenced cognitive capital and psychological capital theories that we have termed emerging. Specifically, our chapter suggests the utility of a comprehensive and integrated capital-based model utilizing five different theoretical capital-based sources—the traditional models of financial capital, human capital, and social capital merged with the recent scholarly focus on cognitive capital and psychological capital. Furthermore, and intriguingly, we do not know whether the three traditional capital theories have greater predictive efficacy than the two emerging capital theories. We posit that within the Ghanaian marketplace, a comprehensive capital-based model that integrates the traditional capital sources with the more recently referenced capital sources will have a higher level of predictive efficacy than a model based solely on traditional capital sources. Research is needed to test, clarify, and resolve this research question. Finally, while we highlight the utility of focusing on cognitive and psychological capital-based approaches, there may be other equally relevant and useful approaches that we do not focus on in this chapter. For example, the implications of technological capital have been well recognized by researchers. At the global level, the technological capital differential has been one of the important explanations of the global north and south trade imbalance (Dollar, 1986; Eaton & Kortum, 2002; Kumar & Russell, 2002). At the national and country levels, technological capital provides nations with competitive advantages and has been associated with increasing levels of innovation and its resultant economic growth (Barrell & Pain, 1997). Within countries, technological capital differences in communities have resulted in digital divides between the technological haves and have nots

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(Gilbert, 2010; Ofori-Dankwa & Ofori-Dankwa, 2009). Within Ghanaian markets as well, technological capital is fast becoming a competitive advantage (Gilbert, 2010; Kwami, 2016; Ofori-Dankwa & Ofori-Dankwa, 2009). A good example of technological capital is cell phones. Cell phones in Africa are ubiquitous in the marketplace and are management tools that market traders in West Africa can use for several tasks such as keeping in touch with customers, identifying price differentials, and substantially enhancing flow of information in the marketplace (Kwami, 2016). Further, cell phone technology enables identification of potential suppliers and accounting approaches. The cost associated with cell phones and applications is dropping in the same way as the cost of laptop computers and internet technologies (Ofori-Dankwa & Ofori-Dankwa, 2009). With costs going down, technology is becoming more affordable and the premium of technology as capital is fast rising in the Ghanaian markets. The limited scholarship on traders’ use of technology, specifically cell phones, suggests that indeed it can be harnessed to improve business success (Kwami, 2016). Policy and Practical Implications Two important policy and practical implications flow from our chapter. First, market traders in West Africa have been researched primarily from a more anthropological (e.g., Clark, 1994, 2010), sociological (e.g, Darkwah, 2001, 2002, 2016, 2021), and economic (e.g., Fafchamps et al., 2014; Fafchamps & Minten, 2002) perspective. The more management-oriented research has tended to focus on managers and less on market traders (e.g., Acquaah, 2007). Undoubtedly, market traders play a significant role in the economies of nations in West Africa. They also use all the different managerial functions as they operate. Given the very dynamic environment in which they operate, market traders, just as their managerial counterparts, have to consistently scan the environment, plan, implement, motivate, and evaluate the effectiveness of their decisions. Consequently, more management-oriented scholarly work on market traders in West Africa is warranted (Darley & Luethge, 2016). Secondly, as far back as the 1980s (Safavi, 1981) and even more recently (Nkomo, 2015; Peredo et al., 2004), business schools in West Africa have been criticized for not having more indigenously relevant programs. For example, the business schools on the continent tend to emphasize the traditional management education curricula, similar to business schools in more developed economies. However, responding to advocations for more indigenously relevant teaching curricula (e.g., Nkomo, 2015; Peredo et al., 2004; Safavi, 1981), we propose more trader-centric and, by extension, more indigenously relevant business school programs.

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CHAPTER 6

NEW PRODUCT PERFORMANCE THROUGH CHANNELING IN SUPPLY CHAIN INNOVATION ALLIANCES The Nexus of Collaboration Intensity, Divergent Communication Schemes, and Alliance Duration Ricarda B. Bouncken Robin Pesch

ABSTRACT The study analyzes how new product development in strategic alliances is affected by collaboration intensity considering the moderating effects of divergent communication schemes and alliance duration. As indicated by proponents of embedded ties, strong collaboration intensity allows a fast exchange

Innovation and Behavioral Strategy, pages 133–160 Copyright © 2022 by Information Age Publishing www.infoagepub.com All rights of reproduction in any form reserved.

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134  ⏹  R. B. BOUNCKEN and R. PESCH of knowledge and further development of ideas and new insights about technologies and markets. The merits of intensified collaboration will increase speed to market and superiority of newly developed products in strategic alliances for innovation. However, we know little so far on the effects of divergent communication schemes between alliance partners. Communication as a process of transferring and encoding messages is not likely to result in the transfer of identical information if the communicating persons have different conceptualizations and different interpretation systems. We assume that divergent communication schemes between alliance partners cause misunderstandings and reduce the benefits of collaboration intensity on new product superiority and speed to market. We also hypothesize that the negative effect of divergent communication schemes is compensated by greater alliance duration because alliance partners develop a better understanding of each other over time. Results are derived from a survey study of 253 supply chain innovation alliances in the engineering industry using structural equation modeling. Our findings indicate that greater collaboration intensity advances both new product superiority and speed to market. Yet, divergent communication schemes turn the positive effects into negative effects. If firms persevere with the alliance, greater alliance duration can offset the negative effects.

INTRODUCTION New product development set up to pursue innovation is one pillar of a firm’s competitive advantage (Balachandra & Friar, 1997; Griffin, 1997b; Olson, Walker, & Ruekert, 1995). One avenue to improve the quality and speed of new product development (NPD) are innovation alliances within the supply chain environment. A prominent example is the strategic alliance between the South Korean electric supplier LG and the car manufacturer GM for the development of electric cars. Research on alliances stresses that strategic alliances are a means for the extension of firms’ resource base and the access of new technologies (Das & Kumar, 2007; Grant & Baden-Fuller, 2004). Supply chain innovation alliances draw on such enveloped potentials of complementary and extended resources and utilize information transfer up and down the supply chain. In this vein, several empirical studies have shown that the involvement of suppliers in NPD enhances productivity, speed, and quality (Clark, 1989; Primo & Amundson, 2002; Ragatz, Handfield, & Petersen, 2002). Roy, Sivakumar, and Wilkinson (2004) evaluate innovations in supply chains as tools for cost reductions and efficiency increases. Supply chain innovation alliances can help to overcome the challenges associated with technological complexity of NPD processes and barriers of foreign market entry (Littler, Leverick, & Bruce, 1995).

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However, prior research has only rudimentarily investigated conditions and success of innovation in supply chain alliances allowing greater interaction, collaboration, and information exchange across vertically aligned firms. We argue that communication processes and joint work allow the detection of new technological advances on the upstream side and consumer needs and new business models on the downstream side. Yet, the joint work and communication is based upon a social structure of participants who have to share and process information, coordinate activities, and work coherently if they want to use the potentials of the supply chain alliance. Intensified collaboration by frequent meetings, intensified relationships, and informal interactions across the supply chain stages allows to process information more deeply and to expand the development of new ideas. This can improve the speed of NPD and the superiority of innovations. At the same time, supply chain innovation alliances have to cope with different targets, behaviors, and beliefs across firms, which are associated with different routines and different role models of the supply chain allies (Chen & Paulraj, 2004; Fawcett, Magnan, & McCarter, 2008; Lajara & Lillo, 2004; Roy et al., 2004). These divergences can hamper communication thereby reducing the advantages of supply chain innovation alliances. Specifically, divergent communication schemes of partners often rooted in the mental sets of managers in different supply chain stages and embedded in different firm cultures can reduce the quality of new products and speed to market by delaying and restricting understanding. Still, different viewpoints within alliances will help to develop novel ideas and further challenge, upgrade, and refine new product concepts. Intense transfers of knowledge and of technologies across firms through frequent meetings and co-work inspires development processes, but also is disturbed by communication and coordination problems. Firms can overcome this dilemma by a concept that we refer to as channeling. Channeling describes the transfer, merging, and changing of ideas across persons occurring across supply chain stages in innovation alliances. This chapter investigates the fundamentals around channeling in supply chain innovation alliances by the study of how collaboration intensity influences NPD performance and how it is affected by partners’ divergent communication schemes. As firms can learn to cope with others’ differences over time, we further investigate if greater alliance duration facilitates interaction and improves new product superiority and speed to market. We structure the chapter as follows: We start with the development of our conceptual model and the corresponding hypotheses. Herein, we first explain supply chain innovation alliances and then develop our concept of channeling. A description of methodology and of empirical results follows. The last sections contain a discussion and conclusion.

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THEORY AND HYPOTHESES Supply Chain Innovation Alliances Innovations are new products or services, new production process technologies, new structures or administrative systems, or new plans affecting organizational members usually pursued by structured NPD processes (Damanpour, 1991). Trott (2008) evaluates NPD processes leading to innovation as “the management of all activities involved in the process of idea generation, technology development, manufacturing, and marketing of a new (or improved) product or manufacturing process or equipment” (p. 15). Common understanding is that innovation is a highly structured, knowledge intensive activity (Wang, Yeung, & Zhang, 2011). It requires information about their environmental and endowment conditions, resource deployments, market knowledge, and technological know-how (Gemünden, Heydebreck, & Herden, 1992; Utterback, 1974). Consequently, firms have extended their routine work by NPD activities using the potentials of greater information exchange up and down the supply chain (Azadegan, 2011). Das and Teng (2000) describe strategic alliances as “voluntary cooperative interfirm agreements aimed at achieving competitive advantage for the partners” (p. 33). In analogy, we define supply chain innovation alliances as interfirm agreements between two or more firms along the supply chain set up for NPD using information exchange and complementary resources, coordination of joint marketing, or shared production facilities. Strategic alliances can take many forms ranging from informal agreements about joint activities to formalized structures of equity-based joint ventures (Das & Kumar, 2007). Similarly, supply chain innovation alliances can range from arm’s-length contracts to equity-based joint ventures. In the past 2 decades, firms have achieved best practice by using supply chain alliances to reduce costs and increase quality across participating firms while improving coordination and information transfer (Barratt, 2004; Fawcett et al., 2008). Typically, the objective of supply chain management is to create and coordinate manufacturing processes seamlessly across the supply chain while being better than competing supply chains (Anderson & Katz, 1998). Firms within supply chains have started to exchange information across partners, establish idea workshops with different firms in the supply chain, test components, change modules and components, use modular designs, and experiment with numerous forms of alliances to improve innovation and to speed up NPD processes. Alliance research emphasizes that strategic alliances create value through integration of specialized (Grant & Baden-Fuller, 2004), complementary, and supplementary knowledge (Buckley, Glaister, Klijn, & Tan, 2009). Thus, a fundamental mechanism behind the advantages of supply

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chain alliances for product innovation is the use of suppliers’ specialization advantages and their associated complementarities. A second fundamental mechanism is the use of increased upstream and downstream information transfer and coordination advantages that improve NPD. A third fundamental mechanism is the enlarged resource portfolio at hand, since alliances offer access to other firms’ resources for creating competitive advantages (Das & Teng, 2000). The inclusion of partners across the supply chain permits additional adaptations to tangible and intangible resources or appropriate and timely feedback regarding the product design that increase speed and market success. In the environment of short product life-cycles, speed to market is highly relevant (Eisenhardt & Tabrizi, 1995; Griffin, 1997a), which defines the time elapsed between the development of an initial product idea and its market launch (McNally, Akdeniz, & Calantone, 2011). Further, NPD performance is reflected by the benefits it creates for customers, especially in relation to competing products (Lee & Colarelli O’Connor, 2003). Therefore, both new product superiority and speed to market are important targets in supply chain innovation alliances. Channeling Supply chain innovation alliances formed to generate and commercialize novel products, services, or technologies (Gulati, 1998) use all three fundamental mechanisms. Yet, information transfer or exchange regarding market opportunities, technological advancements, and new business or technology models across organizational boundaries is influenced by different work styles, targets, and behavioral patterns (Hult, Ketchen, & Slater, 2004; Makhija & Ganesh, 1997). These complicate the definition and selection of a product that is to be implemented in the market. They can hamper development, production, supply, and customer services. At the same time, different ideas, targets, limitations, and potentials need to be considered for the selection of a new product that requires actions, operations, and allows financial returns. Thus, different viewpoints of various partners have positive and negative effects. We develop channeling as a new concept for the mechanism associated with the sharing of information, the stimulation of new ideas, new technology concepts, and business models covering all supply chain allies across supply chain stages and organizational boundaries. Channeling envelops the discussion of ideas, the rejection or change of concepts, the overhaul of concepts, and the reflection on the implementation across allies that aim to use their specific knowledge and competences for the development of new products. Channeling appears directly and indirectly via communication

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and joint work in the NPD process. It requires understanding and consensus, but also covers disagreement, creativity, and constructive discussions. Channeling is based upon relationships across persons and firms. It is a specific outlet of relationships across firms associated with information processing, disagreement, reflections, and the development of new concepts that can stimulate NPD within supply chain alliances. Prior research has analyzed diverse factors that can be interpreted as antecedents or performance categories of channeling. These are knowledge exchange (Easterby-Smith, Lyles, & Tsang, 2008), resource combination (Grant & Baden-Fuller, 2004), or joint sensemaking within strategic alliances (Cheung, Myers, & Mentzer, 2011). We acknowledge close collaboration and high communication quality as important conditions of channeling (Cheung et al., 2011; Lawson, Petersen, Cousins, & Handfield, 2009). However, little is known about the role of divergent communication schemes between supply chain allies which influence how channeling develops over time. To close this research gap, we examine interrelation intensity, communication divergence, and alliance duration as components of channeling in supply chain innovation alliances. Figure 6.1 shows our conceptual model indicating all the hypotheses. Interrelation Intensity High interrelation intensity as “the magnitude of ongoing interactions between partners” shapes relationships, their atmospheres, and, in consequence, determines performance of partnerships (Lin & Germain, 1998, p. 6). Sacco and Vanin (2000) refer to interrelation intensity as “the specific Divergence of Communication Schemes H3a – H1 +

New Product Superiority

H3b –

Collaboration Intensity

H5a + H2 + H4a + H4b +

Alliance Duration

Figure 6.1  Conceptual model.

Speed to Market H5b +

Controls: • Innovation Orientation • Research Intensity • Size

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channel through which interaction (and specifically cooperation) takes place[,] [. . .] caus[ing] the emergence of stable social patterns of cooperation through the reinforcement of the interaction between players who [successfully] aspire to the cooperative outcome” (p. 235). Interrelation intensity is often linked to commitment (De Clercq, Sapienza, & Crijns, 2005; Heide & Miner, 1992). Within collaboration across organizational borders, we specify interrelation intensity as collaboration intensity. Consistent with the understanding of collaboration intensity as the level of mutual communication and joint engagement (Schleimer & Shulman, 2011), we define collaboration intensity as the strength and frequency of alliance interaction by personal meetings, cultivation of close relationships, and informal communication that can include knowledge and technical transfers. Firms need to identify and deploy complementary resources in supply chain innovation alliances based upon understanding, comprehension, and coordination of NPD processes and potentials across partners. This can take advantage of high collaboration intensity in different aspects. Strong interpersonal ties are a channel through which allies learn about each other’s competencies (Kale, Singh, & Perlmutter, 2000). Greater collaboration improves firms’ capabilities of identifying and evaluating complementary resources which is critical for achieving relational rents (Dyer & Singh, 1998). The greater discussion and understanding across firms allow a better use of the resource portfolio which advances the development of superior new products (Wang et al., 2011). Close and intensive interaction between alliance partners strengthens the understanding of the value and complementarities of alliance partners’ resources while improving information exchanges about alliances partners’ resources (Lawson et al., 2009). With closer personal interaction of greater collaboration intensity, firms are able to transfer richer information and knowledge than by indirect communication. Interorganizational teams, regular meetings and conferences, or social events drive the combination and exchange of resources and knowledge (Autry & Golicic, 2010; Cousins & Menguc, 2006; Lawson et al., 2009; Sobrero & Roberts, 2002; Tether, 2002; Tomlinson, 2010). The importance of collaboration intensity is emphasized for the exchange of implicit knowledge embodied in individual cognition and expertise (Polanyi, 1969) which is a key driver of innovation (Goffin & Koners, 2011; Senker, 1995). The specific characteristics of tacit knowledge require practical experience or personal interaction to be acquired and developed (Nielsen & Nielsen, 2009). Both are rooted in intensified collaboration between alliance partners. Greater collaboration intensity facilitates channeling that additionally shapes a climate of trust (Kale et al., 2000), an important driver of channeling. Lane, Salk, and Lyles (2001) argue that trust improves the ability to understand partners’ knowledge. The greater the trust, the more all parties are willing to exchange knowledge and to help each other to understand

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alliance partners’ knowledge. More frequently exchanged information in greater detail and with greater scope from trustful partners can reduce the inherent uncertainty of NPD and thereby improve the quality of product innovation. In essence, the intensified collaboration stimulates trust and commitment, reduces personal barriers, and provokes openness as persons get to know each other better. Increased trust, commitment, cohesion, and personal understanding further reduce individuals’ fear of articulating imprudent ideas and making fools of themselves. It stimulates the free flow of insights, ideas, connotations, meanings, and helps to experiment with new concepts. Greater collaboration intensity as such is a fundament of channeling improving the superiority of product innovation. Hypothesis 1: Collaboration intensity between supply chain innovation allies is associated with increased new product superiority. Arguments stated above also apply for the improvement of speed to market within alliances across the supply chain. Also referred to as development cycle time, speed to market is defined as the time elapsed between development of the initial product idea and ultimate commercialization (McNally et al., 2011). Yet, further arguments specify the effect of collaboration intensity on speed to market. Ragatz, Handfield, and Scannell (1997) argue that close collaborative NPD offers a faster execution of tasks because differences leading to future problems, such as contradictory requirements, can be identified and solved before problems occur by using an extended resource base. In a similar vein, Zahra, Ireland, and Hitt (2000) postulate that knowledge diversity reduces product development cycles. The improvement of relational capital through close and intensive interaction leads to a development and improvement of interorganizational processes and thereby to the acceleration of NPD (Cousins, Handfield, Lawson, & Petersen, 2006; Nielsen & Nielsen, 2009). By quickening and easing information transfers, collaboration intensity can improve speed to market (Cyril, 2001). Frequent interactions in the form of interorganizational teams, or regular meetings, and conferences reduce the probability of undesirable developments. A larger body of information, including explicit and tacit knowledge is shared. Frequent interactions improve the speed of information transfers, comprehension, and feedback. They also lead to greater personal attainments that in turn allow a better and faster prediction of a partner’s behavior. On the downside, high collaboration intensity is time demanding, requires coordination efforts, and on top of this might include cognitive lock-ins (Johnston, McCutcheon, Stuart, & Kerwood, 2004; Littler et al., 1995). The time and efforts of frequent meetings might also distract from the actual work in NPD. Further, the greater

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information exchange and openness associated with high collaboration intensity opens up windows for opportunism. Still, the speed of the NPD process requires high collaboration intensity to prevent misunderstandings and to use complementary resources and knowledge efficiently. Hypothesis 2: Collaboration intensity between supply chain innovation allies is associated with increased speed to market. Divergent Communication Schemes As described before, communication between allies is vital to the success of strategic alliances (Doz & Hamel, 1998) since it helps to ensure understanding and delivers several informational benefits (Butler, 2010). George (2012) emphasizes that communication is needed to coordinate learning processes, to send and acquire knowledge, and to promote interpersonal creativity for creating innovation within alliances. However, firms within supply chain innovation alliances have to cope with divergent communication schemes that relate to dissimilar behavioral patterns, modes of interpretation (Daft & Weick, 1984), and ways of information expression (Lavie, Haunschild, & Khanna, 2012). A communication scheme is an implicit understanding of how to codify, transfer, and interpret information, which also develops in organization and reduces coordination efforts. Differences of interpretation and articulation can root in various factors such as the organizational environment (Daft & Weick, 1984) or the organizational (Lavie et al., 2012) and national culture (Das & Kumar, 2010). Divergent communication schemes become visible in different degrees of directness, formality (Haghirian, 2011; Lavie et al., 2012), and context-orientation of communication (Hall & Hall, 1990). Low context orientation describes a communication process in which the meaning of a message is rooted in the coded, explicit, transmitted information, whereas in high context communication processes the meaning of a message is strongly embedded in the context that surrounds the information (Hall & Hall, 1990). Divergent communication schemes can induce misunderstanding and frustration, since sender and receiver have different mindsets and expectations on the communication process. Yet, resolving these misunderstandings might stimulate a constructive dialogue, an interchange of different viewpoints, and as such stimulate the development of novel ideas. These can offset cognitive lock-ins and advance product innovation. However, divergent communication schemes impede channeling by the limitation of the participating firms’ capability to assimilate knowledge exchanged in alliances. If individuals misunderstand their alliance partners’

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knowledge, the organization cannot effectively absorb and apply the obtained knowledge for developing superior products (Lane & Lubatkin, 1998; Malhorta, Gosain, & El Sawy, 2005). A firm’s capability to value, assimilate, and apply new knowledge from a particular alliance partner is referred to as partner-specific absorptive capacity (Dyer & Singh, 1998; Lane & Lubatkin, 1998; Malhorta et al., 2005), based on Cohen and Levinthal’s (1990) concept of absolute absorptive capacity. Partner-specific absorptive capacity is a critical determinant of knowledge sharing and thereby of achieving relational rents (Dyer & Singh, 1998). We argue that divergent communication schemes in sum impede the positive effects of collaboration intensity on new product superiority. Hypothesis 3a: The positive relationship between collaboration intensity and new product superiority is weaker when firms have greater divergent communication schemes. In other words, divergent communications schemes between supply chain innovation allies negatively moderate the relationship between collaboration intensity and new product superiority. Similar argumentation holds for the effects on speed to market. Low usage of partner-specific absorptive capacity caused by divergent communication schemes impede channeling and as such the effective combination and exchange of complementary knowledge for new products and optimized interorganizational routines. Divergent communication schemes hamper the positive benefits of close collaboration on speed to market. Misunderstandings caused by dissimilar expectations regarding communication processes are a barrier for the resolution of contradictory requirements, unexpected tasks, and problems. They require additional effort and time. Thus, the positive effect of collaboration intensity on speed to market is reduced by increasingly divergent communication schemes. Hypothesis 3b: The positive relationship between collaboration intensity and speed to market is weaker when firms have greater divergent communication schemes. In other words, divergent communication schemes between supply chain innovation allies negatively moderate the relationship between collaboration intensity and speed to market. Alliance Duration Since, alliance conditions are dynamic in nature (Ariño & de la Torre, 1998) and evolve over time (Doz, 1996), we specify our hypotheses by considering the moderating effect of alliance duration also known as link (Kotabe, Martin, & Domoto, 2003) or relationship duration (Squire, Cousins,

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& Brown, 2009). In the context of supply chain alliances, alliance duration captures the amount of experiences that supply chain allies have in dealing with each other (Kotabe et al., 2003). The development of innovative products can take advantage of greater experiences of all partners across supply chain stages about their environmental and endowment conditions, resource deployments, market knowledge, technological know-how, and customers. Greater partner-specific experiences through longer alliance duration will augment advantages from greater collaboration intensity improving NPD processes via enhanced knowledge transfer (Squire et al., 2009) and coordination. Firms achieve a sounder understanding of the value and complementarities of each other’s resources over time (Kotabe et al., 2003). We argue that alliance duration influences the relationship between collaboration intensity and NPD performance. As alliance partners operate jointly over an extended period of time, they develop an understanding of peculiarities and barriers that otherwise would inhibit NPD (Cousins et al., 2006). Over time, interorganizational routines emerge and speed up the NPD process (Grunwald & Kieser, 2007). The development and improvement of interorganizational routines is also driven by the development of partner-specific absorptive capacity which enhances the effective combination and exchange of technological and innovation process knowledge between alliance partners. Hypothesis 4a: The relationship between collaboration intensity and new product superiority is greater when firms have longer alliance experience. In other words, alliance duration positively moderates the relationship between collaboration intensity and new product superiority in supply chain innovation alliances. Hypothesis 4b: The relationship between collaboration intensity and speed to market is greater when firms have longer alliance experience. In other words, alliance duration positively moderates the relationship between collaboration intensity and speed to market in supply chain innovation alliances. Divergent communication schemes that are fraught with misunderstanding foster disagreements and the fear that the other party is acting opportunistically. If firms are unsure about alliance partners’ behavior, they will obstruct their partners’ access to their resources to impede opportunistic behavior, such as learning races (Khanna, Gulati, & Nohria, 1998). A reduced fear of opportunistic behavior through longer interaction instead decreases the protectiveness of alliance partners and facilitates the combination, exchange, and joint creation of knowledge (Lane et al., 2001; Squire et al., 2009). Ongoing interaction across partners develops relational capital which refers to the level of trust, respect, and friendship between alliance partners

144  ⏹  R. B. BOUNCKEN and R. PESCH

(Cousins et al., 2006; Kale et al., 2000; Lawson et al., 2009). It can shape a personal attachment across partners that can help to reduce negative effects due to communicational misunderstanding (Handfield & Bechtel, 2002). Moreover, modes of interpretations and communication schemes develop over time. They do not only emerge through internal stimuli in the firm. They are also contingent on external factors and communication across organizational borders. As such, supply chain partners can mutually develop more compatible communication schemes or develop tolerance for the divergent communication scheme that they experience in the supply chain alliances. Thus, the development of partner-specific absorptive capacity requires time, since trust and a shared understanding of each other are time demanding determinants of partner-specific absorptive capacity. We argue that alliance partners learn how to cope with divergent communication schemes or develop joint schemes in the course of the alliance work. Thus, the moderating effect of divergent communication schemes on the relationship between collaboration intensity and new product superiority is influenced by alliance duration. Negative effects through divergent communication schemes that reduce the superiority of new products and the speed to market diminish or can be compensated by longer alliance duration. Hypothesis 5a: Negative effects of divergent communication schemes on the relationship between collaboration intensity and new product superiority are positively moderated by alliance duration: greater alliance duration mitigates the negative effects. Hypothesis 5b: Negative effects of divergent communication schemes on the relationship between collaboration intensity and speed to market are positively moderated by alliance duration: greater alliance duration mitigates the negative effects. EMPIRICAL STUDY Questionnaire Design and Sample The engineering industry is an interesting industry for the analysis of supply chain innovation alliances. This industry has to cope with strong innovative pressures driven by fast technological development across national borders. The engineering industry is mainly characterized by small and medium firms which have limited technological, financial, and personnel resources for innovation activities (Dilk, 2009). Supply chain innovation alliances help to overcome firms’ scarcity of resources. Prior to the survey, we carried out two interviews with two executives of the VDMA—Europe’s largest engineering

Channeling in Supply Chain Innovation Alliances  ⏹  145

association. Both executives stated that the German engineering and technology industry is mainly characterized by small and medium firms which have limited technological, financial, and personnel resources for innovation activities and that supply chain innovation partnerships are widely used to overcome this scarcity of resources. Therefore, we assume that the engineering and technology industry is appropriate for the purpose of our study. For the survey, we contacted 1,200 executives of firms operating in the engineering industry through a standardized questionnaire in Spring 2011. This approach corresponds to the selection of key informants knowledgeable about innovation and alliance matters (Lechner, Dowling, & Welpe, 2006). We received 253 completed questionnaires at a response rate of about 21.08%. Our sample consists of 59 suppliers and 194 manufacturers. To reduce common method bias, we collected data on performance from secondary sources on the firms’ research intensity and financial performance. The average sales of the firms in 2010 were approximately 241 million Euros while the average number of workers employed by these organizations amounted to 1,207. The firms’ average R&D intensity, defined as the share of R&D expenses to sales, was over 11%. Scales Collaboration intensity indicates the strength and frequency of alliance interaction. We measured collaboration intensity by using three items of the scale for technical exchange across units and firms from Kotabe et al. (2003). For new product superiority we adapted the scale of Lee and Colarelli O’Connor (2003). We operationalized speed to market as the time elapsed between development of the initial product idea and commercialization (McNally et al., 2011) by applying three items taken from Rindfleisch and Moorman (2001) as well as from Liao, Fei, and Chen (2007). As communication can be described by the amount of context surrounding information and the degree of directness (Haghirian, 2011; Hall & Hall, 1990), we measured the divergence of communication schemes by asking respondents to compare their (a) context orientation and (b) directness of communication with the context orientation and directness of alliance partner’s communication. To measure alliance duration, we asked respondents for how many months the firm has been collaborating with its partner. We further included the following control variables: innovation orientation, research intensity, and firm size. Innovation orientation is a dynamic capability that assists a firm’s proclivity, openness, and inclination to generate and distribute novel ideas within alliances (Bouncken, Teichert, & Koch, 2007). It strongly influences the innovation output of firms and therefore should be controlled. We used the following items from Hurley and Hult (1998): the firm’s engagement towards

146  ⏹  R. B. BOUNCKEN and R. PESCH

(a) creativity in their firm, (b) the constant search for new product ideas, and (c) the participation of personnel in developing novel ideas. Research intensity is defined as research and development investments divided by a firm’s sales volume (Cohen & Levinthal, 1990; Hoskisson & Hitt, 1988). This key figure is widely acknowledged as an influential factor on new product superiority and speed to market (Grabowski & Vernon, 1990; Hoskisson & Hitt, 1988; Kamin & Schwartz, 1982). Prior research has shown that the size of a firm affects its adaptability and responsiveness (Hannan & Freeman, 1984) which are of fundamental importance for the fast development of superior new products. In order to control for the impact of firm size, we included each firm’s total number of employees in our study. To avoid common method bias, we applied several procedural steps (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). First, we reduced the item social desirability effect and evaluation apprehension by assuring all respondents complete confidentiality and anonymity during data collection and analysis. Second, to reduce item ambiguity we avoided vague concepts as well as double barreled questions and kept questions simple (Tourangeou, Rips, & Rasinski, 2000). Besides these procedural controls, we also tested for the presence of common method bias via Harmon’s single-factor test, by conducting an un-rotated principal component factor analysis on all the variables measured. Five factors with eigenvalues above 1 were identified. The largest did not account for a majority of the variance (37.6%). Therefore, we conclude that the presence of common method bias is unlikely in our study. Method To test our hypotheses, we applied structural equation modeling using the Mplus 5.0 software (Muthén & Muthén, 2009). The derived structural equation model reflects the relationships between the latent dependent and independent constructs. Before testing our hypotheses, we applied confirmatory factor analysis (CFA) to validate the measurement model. The goodness-of-fit indices testing the correspondence of the predicted from the proposed model all indicate a very good model fit with CFI = .972, RMSEA = .054, and SRMR = .040 (Schermelleh-Engel, Moosbrugger, & Müller, 2003). In addition, we carefully examined convergent and discriminant validity. All indicators show good fit (see Table 6.1). Results Table 6.2 presents the results of our structural models. The first model investigates control variables while the second model tests hypotheses 1

Note: All factor loadings are significant (t > 3.1 respectively p < 0.001)

Constructs and Items Collaboration Intensity: We regularly meet with our partner. We cultivate a close relationship to our partner. There is informal communication with our partner. New Product Superiority: In the collaboration our innovations . . .    incorporate technology that was new to customers.   offer benefits that were new to customers.   introduce many completely new features to the market. Speed to Market: In the collaboration our innovations . . .   are developed and launched faster than our typical product development speed.  are developed and launched faster than our major competitor’s new products.   are developed and launched faster than the industry norm. Divergence of Communication Schemes: Compared to us, the collaboration partner has . . .   different context use in communication (more task-oriented or associated with more context information).  different communication directness (things are either addressed more directly or more indirect/paraphrased). Innovation Orientation: We strongly encourage creativity in our firm. We constantly search for new product ideas. We encourage all personnel in developing novel (product) ideas.

TABLE 6.1  Construct Measurement

0.74 0.80 0.69 0.66 0.72 0.76 0.75 0.71 0.60

0.81 0.45

0.50 0.49 0.54

0.86 0.89 0.83 0.81 0.85 0.87 0.86 0.84 0.77

0.90 0.67

0.707 0.703 0.734

Standard factor Indicator loadings reliability

0.76

0.75

0.86

0.88

α 0.90

0.76

0.77

0.86

0.88

Composite reliability 0.92

0.51

0.63

0.68

0.71

AVE 0.74

0.81

0.21

0.96

0.92

Fornell– Larcker ratio 0.24

Channeling in Supply Chain Innovation Alliances  ⏹  147

Speed to Market New Product Superiority Speed to Market

→ → →

  R&D Intensity

  Innovation Orientation

  Innovation Orientation

***

New Product Superiority

→

  R&D Intensity

Speed to Market

→

  Log(Alliance Duration)

→ → →

  Collaboration Intensity × Divergent Communication

  Collaboration Intensity × Log(Alliance Duration)

  Collaboration Intensity × Log(Alliance Duration)

*

**

Standardized path coefficient significant at p < 0.1, p < 0.05;

→

  Collaboration Intensity × Divergent Communication

p < 0.01

Speed to Market

New Product Superiority

Speed to Market

New Product Superiority

New Product Superiority

→

  Log(Alliance Duration)

Interaction Effects

New Product Superiority Speed to Market

→ →

  Divergent Communication

Speed to Market

→

  Collaboration Intensity

  Divergent Communication

New Product Superiority

→

  Collaboration Intensity

Direct Effects

New Product Superiority Speed to Market

→ →

  Log(Number of Employees)

  Log(Number of Employees)

Controls

Paths

TABLE 6.2  Structural Parameters

0.556 ***

0.450***

0.102

0.061

–0.025

0.022

Model 1

0.111

*

0.292***

–0.245***

–0.187**

–0.037

–0.074

–0.078

0.025

0.046

0.421

0.036 0.142

0.636*

0.547*** 0.203***

***

0.602 ***

0.526

0.011*

0.009

0.496***

0.011* *

0.040 –0.004

0.010 0.546***

*

0.028 –0.011

Model 4

β-coefficients Model 3

0.381***

0.114

0.098

–0.028

0.068

Model 2

Standardized β-coefficients

148  ⏹  R. B. BOUNCKEN and R. PESCH

Channeling in Supply Chain Innovation Alliances  ⏹  149

and 2, both supported by the results. The association between collaboration intensity and new product superiority as well as speed to market is positive and significant (β = .292, p