Crossing boundaries: Involving external parties in innovation

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Tilburg University

Crossing boundaries

Slot, J.H.

Publication date: 2013 Document Version

Publisher's PDF, also known as Version of record

Link to publication in Tilburg University Research Portal

Citation for published version (APA):

Slot, J. H. (2013). Crossing boundaries: Involving external parties in innovation. CentER, Center for Economic Research.

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Crossing Boundaries:

Involving External Parties in Innovation

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Crossing Boundaries:

Involving External Parties in Innovation

PROEFSCHRIFT

ter verkrijging van de graad van doctor aan Tilburg University op gezag van rector magnificus, prof. dr. Ph. Eijlander,

in het openbaar te verdedigen

ten overstaan van een door het college voor promoties aangewezen commissie in de aula van de Universiteit op woensdag 18 december 2013 om 16.15 uur

door

Johanna Hendrika Slot

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Committee

Prof. dr. Barbara Deleersnyder, Associate Professor of Marketing, Department of Marketing, Tilburg School for Economics and Management, Tilburg University, The Netherlands.

Prof. dr. Inge Geyskens, Professor of Marketing and CentER Fellow, Department of Marketing, Tilburg School for Economics and Management, Tilburg University, The Netherlands.

Prof. dr. Katrijn Gielens, Associate Professor of Marketing, Department of Marketing, Kenan-Flagler Business School, University of North Carolina at Chapel Hill, USA.

Prof. dr. Lisa Scheer, Professor of Marketing, Department of Marketing, College of Business, University of Missouri, USA.

Prof. dr. Raji Srinivasan, Professor of Marketing, Department of Marketing, McCombs School of Business, University of Texas at Austin, USA.

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And ever, as the story drained The wells of fancy dry, And faintly strove that weary one To put the subject by, "The rest next time -" "It is next time!" The happy voices cry. Thus grew the tale of Wonderland: Thus slowly, one by one, Its quaint events were hammered out – And now the tale is done, And home we steer, a merry crew, Beneath the setting sun.

Lewis Carroll, Alice’s Adventures in Wonderland, “All in the Golden Afternoon,” stanza 5 and 6

Acknowledgments

Following a career in business, my first steps in the world of academia made me feel like Lewis Carroll’s Alice when she started her Adventures in Wonderland. My first courses in Tilburg, Marnik Dekimpe’s “Marketing Models” and Xavier Martin’s “Advanced Strategy in Business”, seduced me with a combination of theoretical challenge, methodological rigor, and managerial relevance. As if research were a cake, with the words “EAT ME” beautifully printed on it in large letters. After one bite, I already shrank, and shrank, and shrank some more – and I instantly felt very small, finding myself in the midst of the great (and sometimes puzzling!) minds of the Tilburg Marketing faculty. I was attracted to the new challenge that faced me immediately. And that is how the Adventures of Johanna in Wonderland commenced.

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First and foremost, I am greatly indebted to my advisors, Inge Geyskens and Stefan Wuyts. Inge, meeting you was the very reason for me to come to Tilburg. You were the one who expressed faith in my research capabilities at a very early stage. You sowed the seed of my ambition overseas, a career path I had never envisioned myself taking. You have been a great source of inspiration – your incredible precision, perseverance, and personal attention have helped me enormously. Stefan, you have taught me to translate my business experience into research ideas and testable hypotheses. Your everlasting stream of comments, changes, and critical questions helped me to develop my skills in developing theory. Even though you are at Koç University most of the time, your responsiveness to my many, many emails made the distance between Tilburg and Istanbul disappear. Inge and Stefan, thank you for believing in me (also in moments that I did not), and for pushing me to higher levels. This dissertation would not be here without you.

Second, I am equally indebted to Raji Srinivasan. You have helped me a lot in becoming a better researcher. After taking your online class, you invited me to spend a semester at McCombs Business School, in Austin, Texas, an amazing opportunity. By working with me, you taught me lessons I will remember forever. Our research projects are a true inspiration. On a personal level, you always keep an eye out for me. Thanks for being my friend. You have changed my life, and I am incredibly grateful for it.

Third, I also would like to thank the members of my doctoral committee: Barbara Deleersnyder, Katrijn Gielens, Lisa Scheer, and Raji Srinivasan. I feel very privileged to have such distinguished academics in my committee. I appreciate your comments, questions, and suggestions; they have certainly improved the essays in this dissertation. Special thanks go to Barbara Deleersnyder. You have helped me greatly as I developed my teaching skills. Moreover, you were always available to discuss my career opportunities, for which I am truly thankful.

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initiated my collaboration with NLR. Furthermore, I want to thank Maxim Schram and Eveline van Eekelen of CMNTY, who were so kind to share the data of the Redesignme community with me. In addition, at ASML, I thank Bert Koek and the many other managers I met, who sparked my fascination for high-tech industries.

Thanks also to CentER and the Marketing Department of Tilburg for the coordination of the doctoral program and the financial support that enabled me to go abroad and to visit conferences. A special word of gratitude goes to the Institute for the Study of Business Markets. Receiving the Doctoral Support Award facilitated my research greatly.

My paranimphs have been particularly important to me in the last years. First, Arjen, my great office mate - I enjoyed discussing papers, issues in retail marketing (your work), innovation (my work), and our job market adventures. I wish you the best in Amsterdam. For every one of your many future accomplishments, I will decorate my office in your name, like in the ‘old days’. Second, Anne, my academic sister – you are always available for me being next door, both literally in Tilburg and in Leuven. You have been – and continue to be – an inspiring example to me. Thank you for our many win-win conversations, for your encouragements, and for your personal advice. Arjen and Anne, I will never ever forget you. It is an honor to have you by my side.

Being a PhD student at the Tilburg Marketing Department was a great pleasure. Not in the least, my other fellow PhD students have been very important to me. Millie and Didi brightened up the day with many ‘hallway’ conversations. Néomie shared my interest in strategic issues. Jonne sharpened my econometric skills. Mark, Jaione, Femke, Yufeng, Soulimane, Max, and Kristopher, among other things, thank you for your passionate participation during our annual Sinterklaas events.

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Robert, I would like to thank you for sharing your view on the world with me. Anick, Bart S., Carlos, George, Hans, Michel, Natasja, Rutger, and Vincent, your stories livened up lunch and coffee breaks. Scarlett, Heidi, Nancy, Angelique, and Nienke – you were always ready to help out when needed. Furthermore, thanks to my friends around the world. Dear Emine, you cheered up the office during your time in Tilburg and welcomed me in Istanbul. Dear Leah, you will be my Austin friend forever. Lastly, I would like to thank my new colleagues at The Smeal College of Business at The Penn State University for giving me the opportunity to continue my academic career.

Importantly, I have always felt the unconditional support of my loving family and friends. Pa en ma, voor jullie was het geen verrassing dat ik me zo thuis voelde op de universiteit. Dank voor jullie onbegrensde liefde en voor jullie hartverwarmende steun op de moeilijke momenten. Jullie hebben mij altijd gestimuleerd. Albertine, Klaas, en Hendrieke, ik ben er trots op dat ik jullie ‘grote zus’ mag zijn. Ik kan me geen betere broer en zussen wensen! Roelant, Linda, Robin, en natuurlijk ook Anne-Marie en Floris, het is fijn om jullie erbij te hebben. Loek, Afra, Diana, en Luke, dank voor jullie warme belangstelling (en welkom Fenna! Hoe klein je ook bent, je bent het bewijs dat alles slechts relatief is). Mijn vrienden van De Keet: hoewel ik weet dat ik soms een rare eend in de bijt kan zijn, kan ik altijd op jullie rekenen.

Last but not least, my loved one. Lieve Michiel, als jij niet aan mijn zijde had gestaan in de afgelopen jaren, was me dit niet gelukt. Je kent me door en door, voelt me precies aan. Je hebt me onvoorwaardelijk gesteund in mijn carrièreswitch aan het begin van dit traject. Gedurende de afgelopen jaren heb jij ervoor gezorgd dat ik mijn doel voor ogen hield. En nu gaan we weer verder… Dank je voor je vertrouwen in onze toekomst. Ons leven gaat verder in Amerika. De volgende stap wordt een hele grote. Maar samen kunnen we het aan. Ik hou van je, zielsveel, wanneer en waar dan ook.

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Chapter 1

Introduction

To improve the return on investments in innovation, firms increasingly open up

their new product development (NPD) processes by applying open innovation tactics. A prevalent phenomenon is the involvement of external parties in innovation, which forms the central topic of this dissertation. Before going over to the empirical core of the thesis, this chapter will first introduce the topic of open innovation. Next, we describe the gaps in extant research this thesis aims to address. Finally, we will provide an outline of the dissertation in which the empirical studies are briefly introduced.

1.1 FROM CLOSED TO OPEN INNOVATION

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Yet, the development of new products is tough, for multiple reasons. First, NPD is a risky activity. Many NPD initiatives fail before reaching the market. According to a benchmarking study of 416 firms executed by Barczak, Griffin, and Kahn (2009), seven ideas are needed for every single NDP project initiated. Unsure technological developments make that only one out of eleven of the NPD projects started leads to a market introduction of a new product. Once on the market, only about half of the new products are successful commercially. Comparing the benchmarking study’s survey results over time (Page 1993; Griffin 1997, 2002), NPD success rates are remarkably stable, indicating the difficulty firms experience in improving the return on NPD investments. Second, NPD is expensive, requiring large investments in the development of new knowledge, skills, and technologies (Schmidt and Calantone 2002) that have limited ability to increase short-term cash flows (Srinivasan, Lilien, and Sridhar 2011). Over the last decades, the costs of technology development have increased dramatically, a trend that is reported in a wide variety of industries, including computer and semiconductors, pharmaceuticals, and even consumer products (Chesbrough 2007). Third, completing the NPD process takes times: the development of new products takes three years to complete, on average (Barczak, Griffin, and Kahn 2009). Reducing NPD cycle time such that new products are introduced to the market earlier is imperative for new product success (Cooper and Kleinschmidt 1994), especially in a business environment characterized by shrinking product life cycles (Chesbrough 2007).

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Nowadays, the NPD process has changed. In an attempt to increase the efficiency and effectiveness of the NPD process, firms increasingly apply open innovation practices (Chesbrough 2003). Open innovation describes a new paradigm based on the premise that valuable ideas can come from inside or outside a firm and can go to market from inside or outside the firm as well (Chesbrough 2003). By crossing firm boundaries, firms do not need to rely solely on internal research and development as sources for innovation. Examples include buying externally developed technology on the market or licensing internally developed technology (Chesbrough 2003; Von Hippel 2005), and forming joint ventures or alliances for innovation (Rothaermel and Deeds 2004).

This dissertation focuses on the practice of involving external parties in the formerly internally organized NDP process. The benefits of inviting external parties to participate in NPD include access to external resources including knowledge and skills (Fang 2008; Handfield et al. 1999; Jeppesen and Lakhani 2010). Involving external parties may be the source of new product ideas (Afuah and Tucci 2012; Stump, Athaide, and Joshi 2002). Depending on their role, external parties could also share materials, equipment, and machinery, for use in the developing firm’s NPD process.

Gaining access to external party resources may increase the developing firm’s technological and market knowledge, which may reduce the risk associated with developing (Walter et al. 2003) and marketing a new product (Chen, Li, and Evans 2012). Furthermore, access to external parties’ resources may reduce the time to market (Campbell and Cooper 1999), although the additional activities necessary for managing the external party involvement might also lengthen the NPD process (Bajaj, Kekre, and Srinivasan 2004). Similarly, external party involvement can affect the cost efficiency of NPD processes both positively and negatively (Bensaou 1997; Koufteros, Vonderembse, and Jayaram 2005).

This dissertation focuses on the participation of three types of external parties in

NPD: suppliers, customers, and the “crowd”.1

1_{A firm can also involve other types of external parties in its NPD projects, such as research institutes and}

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1.2 RESEARCH GAPS AND CONTRIBUTIONS

The overarching objective of this dissertation is to shed light on how to successfully

manage the participation of external parties in NPD. Organized per type of external party

involved, we formulate gaps in extant research that form the basis for the contributions of this dissertation.

Supplier Involvement

Developments in supply chain management in the 1980s initiated opening up the innovation process by letting suppliers participate in car manufacturers’ NPD processes (e.g., Clark 1989; Kotabe, Martin, and Domoto 2003; Takeishi 2001), a practice that was rapidly adopted in other industries. Supplier involvement ranges from minor participation to close collaboration with the developing firm. For example, involved suppliers may provide suggestions during the product’s design phase or share their technological knowledge with the firm’s engineers during the development phase. Alternatively, suppliers may co-locate their employees on-site. Suppliers may also take over design, development, engineering, and testing tasks (Handfield et al. 1999; Wasti and Liker 1997; Wynstra and Ten Pierick 2000).

The growth in relevant research has paralleled the growth of supplier involvement in practice. Yet, an integrative review that consolidates prior findings on the role of supplier involvement in NPD is still lacking. The first contribution of this dissertation is to take stock of the extant literature on supplier involvement in NPD by analyzing the antecedents and consequences.

Customer Involvement

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technological knowledge and skills to the NPD process (Fang, Palmatier, and Evans 2008), whereas in consumer markets, their contribution may come in the form of co-development (Chan, Yim, and Lam 2010; Franke, Schreier, and Kaiser 2010).

The growing popularity of customer participation is reflected in the academic literature. Now that a substantial body of research on customer involvement in NPD has accumulated, an integrative review that consolidates prior findings is opportune. This dissertation will contribute to the literature by systematically analyzing the antecedents and the consequences of customer involvement in NPD, in a similar fashion to our analysis of supplier involvement in NPD. In addition, this dissertation will contribute to the extant literature by comparing the involvement of suppliers and customers in terms of their antecedents and consequences.

Although the academic attention for customer involvement in NPD is growing, extant research on customer involvement focuses on the traditional ‘markets of many.’ In contrast, the role of the involved customer in ‘markets of one,’ in which only one customer purchases the product developed, is not studied. These interactions are common in business-to-business markets, where a single customer firm outsources the development of technology or a product to an external supplier firm. The question rises whether the outsourcing customer should be involved in the developing firm’s NPD process. A complicating feature of these industrial relationships is their multiplex nature: these relationships often include more than one role: the customer may also be a partner of, a competitor against, or even a supplier to the developing firm (Tuli, Bharadwaj, and Kohli 2010). We contribute to the literature by empirically investigating the effects of customer involvement in outsourced NPD in these multiplex relationships.

Crowd Involvement

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and submit ideas in response to a firm’s open call for ideas. Many firms, including Heineken, Frito-Lay, Unilever, and Samsung, organize these contests to gather input to be used in the idea generation phase of the NPD process.

Despite the growing importance of the crowd as an external resource for the NPD process, motivating the crowd to expend effort in such contests is a key challenge (McKinsey 2009, p. 53). This dissertation aims to add to the emerging literature on the involvement of the crowd in NPD by empirically investigating how to motivate the crowd to contribute to the idea generation phase of the NPD process.

1.3 OUTLINE

This dissertation consists of three essays that focus on the involvement of external parties in an NPD context. An overview of the chapters’ content, research approach, and sample is depicted in Table 1.1. Despite their common focus on external party involvement in NPD, each chapter is self-contained and can be read independently. Each chapter starts with its own introduction and ends with a discussion of the major findings. The next sections will outline the three chapters that form the core of this dissertation.

We start our analysis in Chapter 2 – The Role of Supplier and Customer Involvement

in New Product Development: A Meta-Analysis – by taking stock of the extant empirical

work on supplier and customer involvement in NPD. In the last decades, the participation of suppliers and customers in a firm’s internal NPD process have become increasingly important in business. Following practitioners’ interests, researchers in marketing, strategic management, operations management, and other academic domains studied the role of supplier and customer involvement in NPD, contributing to a fragmented literature base on the topic. Using meta-analytic techniques, which are indispensible for integrating and expanding a field’s knowledge base (Hunter and Schmidt 1990), we bring sharper focus to these seemingly distinct streams of research.

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We propose and test a framework including both antecedents and consequences of supplier and customer involvement in NPD. Regarding the antecedents, we focus on (i) a firm’s resources (in technology and marketing) and (ii) the environmental uncertainty a firm faces (with respect to technology and the market) as predictors of supplier and customer involvement in NPD. In terms of the consequences, we focus on (i) product innovativeness, (ii) speed to market, and (iii) cost performance as outcomes of supplier and customer involvement. We find that supplier involvement improves speed to market and cost performance, but lowers product innovativeness. In contrast, customer involvement improves product innovativeness while lowering speed to market.

TABLE 1.1: Chapter Overview

Chapter 2 Chapter 3 Chapter 4

Research Question

What are the antecedents and consequences of supplier and customer involvement in NPD?

How does customer participation in outsourced NPD affect supplier task performance for multiplex relationships?

How does the prize structure of an online idea generation contest affect idea creativity? External Party Studied Supplier Customer Customer

(in partner, competitor, and reversed supplier roles)

Crowd

(undefined group of individuals)

Context NPD projects NPD projects Idea generation

contests Performance Measure Innovativeness Speed to market Cost performance

Supplier task performance (customer and supplier perspective)

Creativity Research

Approach Meta-analysis Primary study Primary study

Data Sources

Empirical work in marketing, strategic management, operations management, and supply chain management

Project administration data Evaluation reports

Strategic cooperation plans Procurement records Surveys

Contest data Submissions Panel of judges

Sample 119 samples from 140

studies 140 NPD projects

106 idea generation contests

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Chapter 3 – The Effect of Customer Participation in Outsourced NPD on Supplier Task

Performance: The Role of Relationship Multiplexity – considers the prevalent industrial

context of outsourced NPD. In outsourced NPD, a firm outsources NPD activities to an external supplier that executes the product development work. Yet, as the outsourcing customer is highly knowledgeable and may start thinking about technological avenues to follow in the NPD project, customers increasingly participate in the supplier’s NPD process. In many outsourced NPD projects, the involvement of the customer in the NPD project is complicated by the multiplex nature of the relationship between the customer and supplier: a customer may also be a partner of, competitor against, or even supplier to its supplier firm (Ross and Robertson 2007; Tuli, Bharadwaj, and Kohli 2010).

Prior research important to this topic can be found in the fields of marketing and strategic management. Role theory (Biddle 1986; Katz and Kahn 1966), which has its roots in the sociology literature, forms the theoretical basis of our analysis. Specifically, we propose how customer participation affects the task performance of the developing supplier under conditions of (i) customer-as-partner, (ii) customer-as-competitor, and (iii) customer-as-supplier multiplexity. In this chapter, we consider the effects of customer involvement at both sides of the dyad by analyzing the effects on the customer’s perception as well as the supplier’s own perception of supplier task performance. We test our hypotheses using a proprietary data set on 140 outsourced NPD projects, composed of multiple sources of archival data, survey data, and key qualitative insights.

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Chapter 4 – Managing the Crowd: Prize Structure and Creativity in Online Idea

Generation Contests – deals with online idea generation contests, a nascent application

of open innovation. Unlike the research contexts central to Chapters 2 and 3, in which the external party had a supplier or a customer role, online idea generation contests enable the involvement of external parties without any relationship to the firm. In these contests, an idea generation challenge is disclosed as an open call to the ‘crowd’: an undefined group of individuals external to the firm (Howe 2006, 2008). Those that compete in these crowdsourcing contests do not receive any upfront or guaranteed payment for their efforts. Instead, they are motivated by the possibility of winning a prize (Afuah and Tucci 2012). In Chapter 4, we examine the effects of prize structure characteristics of online idea generation contests on idea creativity, a core element of innovation strategy (Im and Workman 2004).

Relevant extant work on idea generation contests has been done in both marketing and strategic management. Our theoretical angle is rooted in psychology. Specifically, we use arguments from motivation theory (Amabile 1996; Deci and Ryan 1985) to form our hypotheses. We propose how a contest’s (i) total prize value, (ii) number of prizes, and (iii) prize spread affect the creativity of the ideas submitted in the contest. Controlling for the endogeneity of the number of contestants, we test our hypotheses using a proprietary dataset on 106 online idea generation contests, complemented with data supplied by expert judges.

We find that total prize value and number of prizes increase idea creativity, while prize spread decreases idea creativity. Furthermore, the effects of prize structure characteristics on idea creativity are interdependent. Contest sponsors who are unable to offer a high total prize value can increase idea creativity by having many prizes of low value. Contest sponsors should strive to set prizes of equal value as prize spread decreases idea creativity, especially for contests with few prizes.

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“Consider your verdict,” the King said to the jury. “Not yet, not yet!” the Rabbit hastily interrupted.

“There's a great deal to come before that!”

Lewis Carroll, Alice’s Adventures in Wonderland, Chapter 11

Chapter 2

The Role of Supplier and Customer Involvement

in New Product Development:

A Meta-Analysis

2.1 INTRODUCTION

Understanding the drivers of successful new product development (NPD) has been a long-standing goal of managers and researchers. NPD is associated with high resource requirements, large investments, long time horizons, and substantial risk (Cooper and Kleinschmidt 1995). A recent benchmarking study (Barczak, Griffin, and Kahn 2009) reports that firms require about seven ideas for every single NPD project initiated. Furthermore, NPD projects take about three years to complete. In addition, firms commercialize only one product for every eleven NPD projects started, and only about half of these market introductions are reported to be successful. It is therefore not surprising that a recent worldwide survey by PricewaterhouseCoopers shows that 97% of the CEOs consider improving NPD performance a top priority, and a major and lingering concern (Percival and Shelton 2013).

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involvement as a way to improve NPD performance (Johnsen 2009). In the 1990s, the role of the customer as an external resource became more important: in an attempt to find new sources of value, firms let customers participate in innovation processes (Prahalad and Ramaswamy 2004). Accordingly, academia started to examine customer involvement in NPD as well. However, despite the accumulating body of research on NPD, an integrative review that consolidates prior findings on the role of supplier and customer involvement in NPD is still lacking.

The purpose of this study is to provide an integrative meta-analysis of research on both supplier and customer involvement in NPD. We limit our analysis to the situation in which a firm involves suppliers and/or customers in an internal NPD project, and thus exclude other, more formal forms of collaborative NPD between two firms, such as joint ventures. Using correlations obtained from 140 studies from a wide range of fields, including marketing, strategic management, operations management, and supply chain management, we propose and test a model that encompasses the antecedents and consequences of both supplier and customer involvement. Specifically, we focus on a firm’s resources (in technology and marketing) and environmental uncertainty (with respect to technology and the market) as drivers of its use of supplier and customer involvement in NPD. We extend prior research (e.g., Barczak, Griffin, and Kahn 2009) by taking into account the multifaceted nature of NPD success (Griffin and Page 1996) and by investigating the effects of supplier and customer involvement on three measures of NPD performance: product innovativeness, speed to market, and cost performance. In addition, we extend the literature on external party involvement (e.g., Chesbrough 2003) by explicitly comparing supplier and customer involvement in NPD as two different strategies to access external resources.

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The rest of this essay is organized as follows. First, we describe the resource-based view, which is the foundation to our theory. Second, we develop our hypotheses that explain the effects of a firm’s internal resources and environmental uncertainty on the use of supplier and customer involvement in NPD. Subsequently, we present our hypotheses on the consequences of supplier and customer involvement, in terms of product innovativeness, speed to market, and cost performance. Then, we explain the data collection procedure and offer the results. We conclude with the study’s implications for research and practice.

2.2 CONCEPTUAL BACKGROUND

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knowledge, competences, and capabilities in the NPD project (Ragatz, Handfield, and Scannell 1997).

Along the same lines, we define customer involvement in NPD as the extent to which customers participate in the focal firm’s NPD project (Fang 2008). Typically, customers involved in an NPD project participate by providing information on customer needs and preferences, by providing feedback on product concepts and prototypes, and/or by co-developing technology (Fang 2008; Gruner and Homburg 2000). For this purpose, the focal firm can organize customer visits, customer workshops, and product tests with customers. During these activities, the interaction between the firm and the involved customer allows the firm to access external customer knowledge, competences, and capabilities.

The goals of our meta-analysis are to examine the antecedents and consequences of supplier and customer involvement in NPD. The conceptual framework guiding our analysis is depicted in Figure 2.1.

FIGURE 2.1: Antecedents and Consequences of Supplier and Customer Involvement in NPD

First, we argue that the extent to which a firm involves suppliers and customers to access external resources depends on its internal resources and the external

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circumstances the firm faces in the form of environmental uncertainty (cf. DeSarbo et al. 2005). We distinguish between a firm’s technological and marketing resources, and between technological and market uncertainty. Second, we argue how supplier and customer involvement in NPD contribute to NPD performance, in terms of product innovativeness, speed to market, and cost performance.

2.3 ANTECEDENTS OF SUPPLIER AND CUSTOMER INVOLVEMENT

We start our theory development by examining the antecedents of supplier and customer involvement in NPD. We distinguish between internal resources and environmental uncertainty.

Effects of Firm Resources on Supplier and Customer Involvement in NPD

Firm resources refer to all assets, capabilities, organizational processes, information,

knowledge, etc. controlled by the firm that enable the firm to formulate and implement strategies to improve its competitive position (Barney 1991). Extant research finds that firm resources play an important role in the NPD process. For example, Cooper (1979) shows that technical proficiency and marketing knowledge are key to the NPD process. Moenaert and Souder (1990) study R&D and marketing personnel as important actors in the NPD process. Similarly, Calantone and Di Benedetto (1988), Song and Parry (1997), and Song and Montoya-Weiss (2001) describe how technical and marketing resources are key inputs to the innovation process. Thus, both technological resources as well as marketing resources have been recognized as playing a role in the development of new products.

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marketing and product launching capabilities (Cooper 1979). We expect that both types of firm resources – technology and marketing – affect the extent to which firms involve suppliers and customers in the NPD process.

Technological resources and supplier involvement. We argue that a firm’s internal

resources are a necessary condition for firms to deploy the resources sourced from external parties. As a firm has accumulated more domain-specific prior knowledge and skills, it is better able to recognize, value, and employ externally sourced knowledge (Cohen and Levinthal 1990).

Firms with more internally developed technological resources have a higher absorptive capacity to process supplier knowledge in the NPD project (Cassiman and Veugelers 2006), which may lead to higher levels of supplier involvement in NPD for four reasons. First, a firm with more internally developed technological resources is more likely to understand its current technological knowledge deficiencies, which increases the involvement of suppliers as a way to use the externally sourced knowledge to fill its internal knowledge gaps. Second, a firm with more internally developed technological resources is better able to assimilate supplier know-how and subsequently employ it in its own NPD project (Cohen and Levinthal 1990), which may also increase the extent of supplier involvement in NPD. Third, a firm with high levels of internal technological resources is more proficient to jointly develop new knowledge with the involved supplier. Fourth, a firm with a strong R&D track record can better judge and select fruitful technologies among those offered among the supplier base (Narasimhan, Rajiv, and Dutta 2006), making supplier involvement more attractive.

Turning to the supplier’s perspective, LaBahn and Krapfel (2000) note that a supplier is more willing to participate in a firm’s NPD project when the latter has a stronger internal technological resource base, because this also offers the supplier more learning opportunities. In sum, we expect that firms with stronger internal technological resources will more intensely involve suppliers in their NPD projects. We hypothesize:

H1SI: A firm’s technological resources increase supplier involvement in NPD

Technological resources and customer involvement. We expect that a firm’s

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customers in NPD projects. Prior research has suggested that new technology-intensive products are best developed through extensive involvement of customers in the NPD project (Neale and Corkindale 1998), because customer involvement leads to better insight into market opportunities for these products. We argue that a stronger technological resource base improves a firm’s ability to evaluate, select, and translate these market opportunities into new products. First, a firm that has accumulated more technological knowledge and skills can better evaluate the technical feasibility and realism of customer input (cf. Kim and Wilemon 2002) and can therefore select the most promising customer ideas (Huston and Sakkab 2006). Second, strong technological knowledge and high levels of design and engineering skills are necessary to effectively translate unmet customer needs and preferences into new products (Narasimhan, Rajiv, and Dutta 2006). Thus, customer involvement is likely to be a more attractive strategy for firms with a stronger technological resource base.

Turning to the perspective of the customer, one key motivation for customers to be involved in the firm’s NPD activities is to increase the fit between the product and their requirements (Fang, Palmatier, and Evans 2008). However, involvement in an NPD project also requires time and effort from the customer’s behalf (Brockhoff 2003) for which the firm possibly competes with other manufacturers seeking the customer’s participation. The translation of customer input into usable products requires technological resources. Therefore, the likelihood that a customer is willing to participate in a firm’s NPD project is higher when the latter has more technological resources, because it has a higher ability to turn the customer input into a product that suits the customer’s needs. In sum, we expect that a firm with more internal technological resources will more intensely involve customers in its NPD efforts. Reflecting our thinking, we hypothesize:

H1CI: A firm’s technological resources increase customer involvement in NPD

Marketing resources and customer involvement. We argue that a firm with strong

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offer easier access to customer input (Chen, Li, and Evans 2012), which makes it more likely to involve customers in NPD. Second, a firm with more marketing resources is more likely to understand its current market knowledge deficiencies (Atuahene-Gima 2005), which may increase the use of customer involvement as a way to fill its knowledge gaps. Third, a firm with more marketing resources is better able to translate information about customer needs and preferences into promising market introductions. Specifically, a firm’s market sensing abilities and its ability to formulate product concepts based on customer needs and preferences render customer involvement in NPD a more attractive strategy.

Turning to the perspective of the customer, a firm’s marketing resources improve its channel bonding capabilities, which strengthen the relationship between the customer and the firm. It is expected that the resulting improved customer relationships will make customers more willing to share their input with the firm (Ritter and Walker 2003). In sum, a firm with more marketing resources is more likely to intensely engage its customers in NPD. We hypothesize:

H2CI: A firm’s marketing resources increase customer involvement in NPD

Marketing resources and supplier involvement. We expect that a firm’s marketing

resources affect supplier involvement in NPD as well, for three reasons. First, a firm that has superior access to marketing assets and that has stronger marketing capabilities is more externally oriented (Day 1994). As a result, the firm will be more motivated to source external knowledge from suppliers. Second, a firm with an external orientation has stronger market-sensing abilities (Day 1994), which will aid in selecting the technological assets that are most promising from a market point of view from those available in the supplier resource base. This will make supplier involvement in NPD a more attractive strategy for firms with a strong marketing resource base.

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we expect that a firm with stronger internally developed marketing resources will demonstrate higher levels of supplier involvement in NPD. Accordingly, we hypothesize:

H2SI: A firm’s marketing resources increase supplier involvement in NPD

Effects of Environmental Uncertainty on Supplier and Customer Involvement in NPD

The strategic choices of a firm are not only influenced by its resources but also by its environment (Porter 1980). We distinguish between two types of environmental uncertainty: technological uncertainty and market uncertainty. We define technological uncertainty as the extent to which technology in an industry is in a state of flux (Jaworski and Kohli 1993). Under high levels of technological uncertainty, firms struggle to understand new and incompletely specified processes or products (Burkhardt and Brass 1990; Rindfleisch and Heide 1997). We define market uncertainty as the speed and the unpredictability with which customer needs and preferences change (De Luca and Atuahene-Gima 2007; Rindfleisch and Heide 1997).

Technological uncertainty and supplier involvement. We expect technological

uncertainty to increase a firm’s need to involve suppliers in NPD projects. Under conditions of technological uncertainty, a firm needs to remain flexible in terms of technological resources (John, Weiss, and Dutta 1999). By involving suppliers in NPD, a firm can broaden its technological options and assure itself of the resource flexibility that is necessary to face technological uncertainty. Furthermore, accessing externally developed technological resources reduces the focal firm’s technology development risk substantially (Bidault, Depres, and Butler 1998), which also increases the attractiveness of supplier involvement to the focal firm. We hypothesize:

H3SI: Technological uncertainty increases supplier involvement in NPD

Technological uncertainty and customer involvement. Technological uncertainty is

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avenues available. Interacting with customers results in increased first-hand market insight, which provides direction in such changing product markets (Narver and Slater 1990). Customer involvement under conditions of technological uncertainty may be beneficial to the involved customer as well, as being involved may contribute to choosing the technology that offers the most customer benefits. Thus, in technological uncertain environments, customer involvement helps a firm to align technological choices with customer needs (Von Hippel 1986). Accordingly, we hypothesize:

H3CI: Technological uncertainty increases customer involvement in NPD

Market uncertainty and customer involvement. We expect that a high level of market

uncertainty increases customer involvement in NPD. Changing customer needs and preferences increase a firm’s need for market resources. Customer involvement can fulfill the firm’s need for additional market resources by providing first-hand market insights about customer needs and preferences (Fang 2008). External resources from customers can reduce the market uncertainty a firm faces in several ways. For example, customers can offer feedback about product concepts that fit their needs best. Involved customers can also assure their needs are met by assisting in designing a product, which is expected to increase customers’ willingness to be involved in the focal firm’s NPD project. Further along in the NPD process, customers may play a role in field testing, which contributes to a better fit between the newly developed product and a customer’s usage situation. In sum, under conditions of market uncertainty, involving customers in NPD allows the firm to respond to new demand curves (Slater and Narver 1995). We hypothesize:

H4CI: Market uncertainty increases customer involvement in NPD

Market uncertainty and supplier involvement. Under conditions of market

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expect that market uncertainty increases the likelihood to involve suppliers in the NPD project:

H4SI: Market uncertainty increases supplier involvement in NPD

2.4 CONSEQUENCES OF SUPPLIER AND CUSTOMER INVOLVEMENT

We continue our theory development by examining the consequences of supplier and customer involvement in NPD. Prior research has reported inconsistent results as to the effects of supplier and customer involvement on NPD performance. For example, Potter and Lawson (2013) report positive effects of supplier involvement on NPD performance, whereas Millson and Wilemon (2002) show negative effects of supplier involvement. As to customer involvement, Brettel and Cleven (2011) find that it improves the performance of NPD projects, but Knudsen (2007) reports a negative influence of customer involvement. These inconsistencies in prior research may be attributable to the multifaceted nature of NPD performance (Griffin and Page 1996). Recognizing that no single measure is able to completely gauge the performance of an NPD project (Griffin and Page 1996), we set out to examine the effects of supplier and customer involvement on three interrelated, yet distinct measures of NPD performance: product innovativeness, speed to market, and cost performance.

A product’s level of innovativeness is defined as its newness in terms of technology and market (Kleinschmidt and Cooper 1991). A product is high on technological newness when its development requires the use of new technology, engineering, design, and production processes (Kleinschmidt and Cooper 1991). A product is high on market newness when it serves new customers, fills new customer needs, and faces new competitors on the market (Kleinschmidt and Cooper 1991). Innovative products can disproportionally contribute to firm profitability (Wind and Mahajan 1997), and are crucial to maintain a competitive advantage (Abernathy and Clark 1985).

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production startup, excluding market introduction (Cooper and Kleinschmidt 1986). Speed-to-market is also referred to as time to market (Tatikonda and Montoya-Weiss 2001), project completion time (Terwiesch and Loch 1999), product development time (Lilien and Yoon 1989), and lead time (Ulrich et al. 1993).

In turn, developing products with a high speed to market comes – literally – at a cost. Increasing the speed of development lowers a project’s cost performance (Bayus 1997; Langerak, Rijsdijk, and Dittrich 2009). Thus, we also study cost performance. We define cost performance as the firm’s ability to keep developing costs within budget (Kessler 2000). Increasingly intense competition forces firms to improve the efficiency of their product development activities (Rothwell 1994), which underlies the importance of paying attention to cost performance in NPD.

We now discuss the effects of supplier and customer involvement in NPD on each of these performance measures: product innovativeness, speed to market, and cost performance.

Effects of Supplier and Customer Involvement in NPD on Product Innovativeness

Supplier involvement and product innovativeness. We argue that supplier

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focal firm (Walter et al. 2003). Third, suppliers can also be a source of market insight (Song and Thieme 2009). A supplier may have invested in marketing activities directed at its supply chain and may have developed insights about customer demands and unfulfilled market opportunities that can be relevant and valuable to the developing firm. In turn, the focal firm can use these external marketing resources to increase its product innovativeness. We offer the following hypothesis:

H5SI: Supplier involvement in NPD increases product innovativeness

Customer involvement and product innovativeness. We expect that intensively

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innovativeness. Hence, overall, customer involvement in NPD has the potential to increase product innovativeness. We hypothesize:

H5CI: Customer involvement in NPD increases product innovativeness

Effects of Supplier and Customer Involvement in NPD on Speed to Market

Supplier involvement and speed to market. Prior research has suggested three ways

in which supplier involvement may help reduce the speed to market of a newly developed product. First, by involving suppliers, additional personnel join the focal firm’s project team and may take over non-core tasks, such as the development of particular components or the execution of testing activities. This may reduce the workload of the focal firm (Clark and Fujimoto 1991), and allows it to specialize into tasks that require the firm’s key competencies and skills (Eisenhardt and Tabrizi 1995). As a result, the critical path of development projects may be shortened (Brown and Eisenhardt 1995; Ragatz, Handfield, and Petersen 2002), improving speed to market. Second, by involving suppliers more intensively in the NPD process, the focal firm is more likely to identify potential technical problems in the product specification, product design, or production early on (Knudsen 2007; Zirger and Hartley 1994). This eliminates rework, thereby speeding up the NPD process (Ragatz, Handfield, and Petersen 2002). Third, involving suppliers increases the number of technological perspectives held among the NPD team members (Eisenhardt and Tabrizi 1995), which reduces the time needed to solve technical problems, in case any occur. Fourth, closely involving suppliers in an NPD project contributes to a better coordination of communication and information exchange between the parties, which reduces delays and helps to achieve time goals (Ragatz, Handfield, and Petersen 2002). Therefore, we hypothesize:

H6SI: Supplier involvement in NPD increases speed to market

Customer involvement and speed to market. In contrast to involved suppliers, who

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and Srinivasan 2004), as customer input requires processing before it can be used (Sethi 2000). Thus, instead of speeding up the NPD process, involving customers adds extra tasks that the focal firm must execute, thereby increasing development time and reducing speed to market. The reduced speed to market as a result of involving customers in the NPD project can be partially compensated for. A firm that involves customers in NPD is likely to identify product benefit misspecifications and product design flaws in an earlier stage, which could save rework in later stages of the NPD process (Campbell and Cooper 1999; Koufteros, Vonderembse, and Jayaram 2005). However, such time benefits can only be attained when customers become involved in various stages of the NPD process. Specifically, customer involvement is valuable during the preliminary market and technical analysis, because the insight gained can reduce costs and problems in the more costly and risky stages of (post-) development (Campbell and Cooper 1999). In addition, customer involvement is critical during the testing and evaluation stages of the project, because it provides pre-commercialization feedback (Campbell and Cooper 1999). However, the more NPD stages in which customers are involved, the more customer-related project tasks are added to the focal firm’s task list in a project. Thus, net, we expect that customer involvement in NPD lengthens rather than shortens the NPD project. Reflecting our thinking, we hypothesize:

H6CI: Customer involvement in NPD decreases speed to market

Effects of Supplier and Customer Involvement in NPD on Cost Performance

Supplier involvement and cost performance. We expect that supplier involvement in

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NPD process allows firms to eliminate design and production problems early on in the NPD process (Knudsen 2007; Zirger and Hartley 1994), which reduces costly rework (Ragatz, Handfield, and Petersen 2002). We expect:

H7SI: Supplier involvement in NPD increases cost performance

Customer involvement and cost performance. Also customer involvement is likely to

affect the cost performance of NPD. On the one hand, involved customers provide resources to the NPD process that the company may not have access to (Feng 2012; Gruner and Homburg 2000), saving the focal firm the costs of acquiring these resources on the market. In addition, interacting with customers during the NPD project can improve a firm’s understanding of customer needs (Brown and Eisenhardt 1995), which helps it to prevent mistakes in the design phase of the project. As a result, costly changes to the product design later in the project can be avoided (Campbell and Cooper 1999; Koufteros, Vonderembse, and Jayaram 2005). On the other hand, the coordination of involving customers in the NPD process is associated with additional costs (Bajaj, Kekre, and Srinivasan 2004; Bensaou 1997). For example, additional customer visits, workshops and product tests with customers, and development team meetings aimed at gathering customer knowledge must be organized. In addition, processing the newly gained customer information and translating it into usable resources for the NPD project takes substantial resources from the focal firm (Sethi 2000), which ultimately lowers the project’s cost performance. We expect that these additional costs for coordination and processing, which can be substantial as they affect each project task in which customers participate, outweigh the potential cost savings achieved. We hypothesize:

H7CI: Customer involvement in NPD decreases cost performance

2.5 METHOD

Literature Search

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the following search strategies. First, via a computerized search, we retrieved studies on either supplier or customer involvement in the ABI Inform Global and ECONLIT databases using the keywords “supplier involvement,” “supplier participation,” “supplier collaboration,” “supplier integration,” “customer involvement,” “customer participation,” “customer collaboration,” “customer integration,” “customer co-creation,” “customer co-development,” and “customer coproduction.”

Second, we executed an issue-by-issue search for the following journals: Academy of

Management Journal, Administrative Science Quarterly, International Journal of Research in Marketing, Industrial Marketing Management, Journal of the Academy of Marketing Science, Journal of Management, Journal of Marketing, Journal of Marketing Research, Journal of Product Innovation Management, Management Science, Marketing Science, Organization Science, and Strategic Management Journal. Third, we examined the SSRN

network for unpublished studies and work in progress to address the “file-drawer” problem (Rosenthal 1991). Fourth, we examined the reference sections of eight reviews on NPD (e.g., Calantone, Harmancioglu, and Dröge 2010; Cankurtaran, Langerak, and Griffin 2013; Henard and Szymanski 2001; Evanschitzky et al. 2012). Finally, we examined the reference sections of all studies identified in the previous four steps to retrieve any study that might have been overlooked in the process.

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and that also lacked sufficient statistical information to allow the computation of a correlation coefficient using the formulas in Hunter and Schmidt (1990, p. 272).

A total of 140 studies were eligible for inclusion in the meta-analysis (see the Appendix for an overview). Three of these studies were unpublished at the time of data collection. Some studies merely reanalyzed previously reported data (e.g., De Toni and Nassimbeni 1999, 2000), or reported subsamples of data that were expanded in later studies (e.g., Liker, Kamath, and Wasti 1998; Wasti and Liker 1997, 1999). Other studies examined data from more than one sample (e.g., Lin et al. 2005). In all, we obtained 119 independent samples, reported in 140 studies. Supplier (customer) involvement in NPD was studied in 91 (54) independent samples.

Data Collection Procedure

Correlations between variables of interest were recorded. In case correlations were not reported, we converted phi, standardized beta, and univariate F to correlation coefficients using the formulas provided by Hunter and Schmidt (1990, p. 272) and Peterson and Brown (2005, p. 179).

All harvested correlations were categorized on the basis of operationalizations of the construct. In a number of cases, multiple variables within one sample referred to the same underlying construct. To correct for the interdependence of the recorded correlation coefficients, these correlations were combined into a composite correlation following the formulas of Hunter and Schmidt (1990, pp. 435-348).

Testing our hypotheses requires that we collect the correlations between every pair of constructs in our model, rather than only the correlations between supplier (customer) involvement and their hypothesized antecedents and consequences (cf. Geyskens, Steenkamp, and Kumar 1999). As a result, we also extracted correlations for every pair of constructs in our model (e.g., marketing resources and technology resources) from the same set of primary studies.

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TABLE 2.1: Construct Definitions and Representative Measures

Construct Definition Representative measures

Product innovativeness

Degree to which the developed product is innovative (is new or technologically

groundbreaking, and/or fulfills new customer needs)

Kouferos, Cheng, and Lai (2007); Lau, Tang, and Yam (2012)

Speed to market

Degree to which the developed product arrives on the market timely, measured by e.g. time to market and development speed

Feng et al. (2012); Wynstra et al. (2012)

Cost

performance

Degree to which the developed product's cost targets are met, measured by e.g. percentage over budget

Primo and Amundson (2002); Ragatz, Handfield, and Petersen (2002) Supplier

involvement

The extent to which suppliers work together with the focal firm in the NPD project, measured by e.g. intensity of supplier collaboration, supplier integration, and supplier participation

Sánchez and Pérez (2003a,b); Sherman, Souder, and Jenssen (2000)

Customer involvement

The extent to which customers work together with the focal firm in the NPD project, measured by e.g. intensity of customer collaboration, customer participation, and customer co-development

Athaide and Zhang (2011); Mishra and Shah (2009)

Technological resources

Technological assets, knowledge, capabilities, and organizational processes of the focal firm, measured by e.g. R&D investments, patents, and technological proficiency

Cousins et al. (2011); Un, Cuervo-Cazurra, and Asakawa (2010) Marketing

resources

Marketing assets, knowledge, capabilities, and organizational processes of the focal firm, measured by e.g. level of market forecasting ability, market knowledge and market response capability

Chen, Li, and Evans (2012); Souder, Sherman, and Davies-Cooper (1998)

Technology uncertainty

The rate of change in the technological environment

Jean, Sinkovics, and Hiebaum (2013); Petersen, Handfield, and Ragatz (2003)

Market uncertainty

The rate of change with respect to the composition of customers, and their needs, preferences, and demand; and nature of competitive actions

Chen, Li, and Evans (2012); Lau, Tang, and Yam (2012)

Product importance

Strategic importance of the product(s) developed, e.g. project criticality

Fang (2008); Gulati and Sytch (2007)

Firm size Scale and scope of organizational operations, e.g. number of employees and plant size

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After extracting the correlations, we corrected them for measurement error in both measures as well as for dichotomization of truly continuous variables, following Geyskens et al. (2009). We subsequently transformed the corrected correlations into Fisher’s z-coefficients (Lipsey and Wilson 2001). Next, we pooled the correlation coefficients for each pair of constructs in our model, by averaging and weighting the individual corrected study effects by an estimate of the inverse of their variance (Lipsey and Wilson 2001) to give greater weight to more precise estimates. Finally, we reconverted the pooled z-transformed study effects back to correlation coefficients (Hedges and Olkin 1985).

Estimation

We estimate our model on the pooled meta-analytic correlation matrix and use the harmonic mean of the sample sizes of each entry in the meta-analytic correlation matrix (N = 1,513) as the sample size for our analysis. Our hypotheses require that we simultaneously test the impact of internal resources and environmental uncertainty on the involvement of suppliers and customers in NPD, as well as the effects of supplier and customer involvement on NPD performance. Testing these equations independently would result in biased estimates due to the endogeneity of the decision to involve suppliers and customers in NPD in the performance equation (cf. Hamilton and Nickerson 2003). We therefore estimate the following system of equations using full information maximum likelihood:

(1) SI = β1 * RESTECH + β2 * RESMKT + β3 * UNCTECH+ β4 * UNCMKT + β5 * FSIZE

+ β6 * PRODIMPO + ε1

(2) CI = γ1 * RESTECH + γ2 * RESMKT + γ3 * UNCTECH+ γ4 * UNCMKT + γ5 * FSIZE

+ γ6 * PRODIMPO + ε2

(3) PERF_INNO = δ1 * SI + δ2 * CI + δ3 * RESTECH + δ4 * RESMKT + δ5 * UNCTECH

+ δ6 * UNCMKT + δ7 * FSIZE + ε3

(4) PERF_SPEED = ζ1 * SI + ζ2 * CI + ζ3 * RESTECH + ζ4 * RESMKT+ ζ5 * UNCTECH

+ ζ6 * UNCMKT + ζ7 * FSIZE + ε4

(5) PERF_COST = η1 * SI + η2 * CI + η3 * RESTECH + η4 * RESMKT+ η5 * UNCTECH

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where SI (CI) = supplier (customer) involvement in NPD, RESTECH (RESMKT) = technological (marketing) resources of the focal firm, UNCTECH (UNCMKT) = technological (market) uncertainty, FSIZE = firm size, PRODIMPO = strategic importance of the product developed, PERF_INNO = product innovativeness, PERF_SPEED = speed to market, and PERF_COST = cost performance.

We control for firm size (e.g., Fang 2008; Lau, Tang, and Yam 2010) in the involvement and the performance equations. Larger firms are expected to be more likely to involve customers and suppliers in their NPD as they have more financial resources to allocate to strategic collaborations (Koufteros, Cheng, and Lai 2007). In addition, larger firms have more personnel that they may dedicate to innovation, and are thus more likely to develop more innovative products. Also, larger firms are more likely to have NPD procedures in place which help speed up the development process and contribute to keeping costs down (cf. Hitt, Hoskisson, and Kim 1997).

Furthermore, we control for the influence of product importance (e.g., Athaide, Stump, and Joshi 2003) in the involvement equations, since firms may be more prone to allocate external resources to strategically important development projects.

Finally, in the performance equations, we also control for potential direct effects of the firm’s technological and marketing resources and technological and market uncertainty (cf. Gatignon and Xuereb 1997; Kessler 2000; Tomlinson 2010).

Because the decisions to involve suppliers and customers in NPD may be related in ways other than the model accounts for, we allow the residuals of equations (1) and (2) to be correlated. Similarly, because the different performance indicators may have common antecedents other than those specified, we allow the residuals of equations (3), (4), and (5) to be correlated (see Franke and Park 2006 for a similar practice).

2.6 RESULTS

Table 2.2 reports the meta-analytic correlations for the focal relationships in our model. We report the following summary statistics for each bivariate relationship of interest to our study: the number of samples reporting on the bivariate relationships k,

the total sample size N, the average corrected correlation (), the corresponding

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TABLE 2.2: Meta-Analytic Bivariate Effects for the Hypothesized Relationshipsa 95% Confidence

Interval

Predictor k N b _SE

Predictors of supplier involvement

R&D resources 12 4450 .15 * .02 .11 .19

Marketing resources 2 142 .21 .11 -.01 .43

Technological uncertainty 13 1736 .46 * .03 .40 .52

Market uncertainty 5 733 .09 .05 .00 .18

Predictors of customer involvement

Technological resources 11 4091 .20 * .02 .15 .24

Marketing resources 5 609 .31 * .05 .21 .41

Technological uncertainty 11 1524 .15 * .03 .08 .21

Market uncertainty 8 1050 .07 .04 .00 .15

Predictors of product innovativeness

Supplier involvement 21 6467 .21 * .02 .18 .25 Customer involvement 23 6605 .25 * .02 .22 .29 Predictors of speed to market

Supplier involvement 22 2449 .37 * .03 .32 .42 Customer involvement 15 1687 .19 * .03 .12 .25 Predictors of cost performance

Supplier involvement 16 2339 .26 * .03 .21 .31

Customer involvement 7 838 .17 * .05 .07 .26

* p < .01

a_{k = number of samples; N = total sample size;} = estimate of corrected population

correlation; SE = estimated standard error of .

b_{The corrected mean correlation coefficients (ρ) are sample-size weighted, measurement}

error- and dichotomization-corrected estimates of the population correlation coefficients. Table 2.3 shows the full meta-analytic correlation matrix that we used to estimate Equations (1) – (5). Each cell in this matrix represents a meta-analysis of several samples. With the exception of the “marketing resources – supplier involvement” relationship (k = 2, N = 142), all focal relationships included data from at least 5 samples

( = 12.2, = 2,480).2_{Note that no individual sample contained all correlations of}

interest. Thus, the total number of samples analyzed is much larger than the number of samples contributing to any individual meta-analytic correlation.

2_{Some relationships in our meta-analytic correlation matrix were based on rather small numbers of}

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