Elsevier

Journal of Business Research

Volume 118, September 2020, Pages 299-310
Journal of Business Research

What makes social media-based supplier network involvement more effective for new product performance? The role of network structure

https://doi.org/10.1016/j.jbusres.2020.06.054Get rights and content

Highlights

  • Social media-based supplier network involvement enhances buying firm's new product performance.

  • This performance enhancement effect is even stronger when network strength is greater.

  • The same effect is even stronger when network heterogeneity is greater.

  • However this effect is lessened when network density is greater.

Abstract

Fueled by continuing advances in information and social media, the ever-improving social media networks provide firms with unique opportunities to communicate conveniently with their supply chain partners in a dynamic manner. However, a critical unknown is whether buying firms, aiming at enhancing new product performance, can benefit from their suppliers’ participation in social media networks. Building on social network theory, and using a longitudinal design and secondary proxy dataset of 256 buying firms and their suppliers, the authors find that social media-based supplier network involvement can generate superior new product performance of buying firms. Additionally, social media-based supplier network involvement is more effective for new product performance when this network of suppliers shows strong network strength and network heterogeneity. In contrast, network density is found to be counter-productive. The results provide guidelines for managers interested in improving their innovation outcomes through social media networks.

Introduction

Various aspects of supplier involvement in new product development (NPD) have been investigated, such as knowledge protection (Jean, Sinkovics, & Hiebaum, 2014), timing of involvement (Laursen & Andersen, 2016), informal social interaction (Liu, Huang, Dou, & Zhao, 2017), and the role of firm capabilities (Cheng & Krumwiede, 2018). Supplier involvement in NPD refers to the resources (capabilities, investments, information, knowledge, ideas) that suppliers provide, the tasks they carry out, and the responsibilities they assume regarding the development of a new product for the benefit of a buying firm (Jean et al., 2014). For example, Toyota’s success is attributed primarily to the heavy involvement of its suppliers in the NPD process, in which suppliers are obligated to reciprocate in knowledge exchange to the extent that suppliers frequently share novel knowledge (Aoki & Lennerfors, 2013). Recently, the use of social media has been proposed as a valid alternative to other, more conventional, means of supplier involvement (e.g., Bhimani et al., 2019, Cheng and Krumwiede, 2018, Bashir et al., 2017).

Social media is defined as applications encompassing easily accessible mobile and web instruments that allow individuals to create, share, and seek content, as well as to communicate and collaborate with one another (Du et al., 2016, Trainor et al., 2014). Social media has made much use of instant communication applications, such as Twitter, WhatsApp, Facebook Messenger, and Line, as noted in Hanna, Rohm, & Crittenden (2011) and updated by Muninger et al., 2019, Pivec and Maček, 2019. One form of instant communication applications is “closed-loop social media networks”, which are used for private communication within pre-designated groups (Kane, Alavi, Labianca, & Borgatti, 2014).

Closed-loop social media networks involve not only those networks for individuals/units within firms, but also those within a defined group of firms in close collaboration with each other (Keinänen & Kuivalainen, 2015). Social media networks used in business settings tend to be closed-loop in nature, due to the sensitivity and secrecy of the information shared among manufacturers, suppliers, business partners or business customers (Keinanen & Kuivalainen, 2015). As a result, the use of closed-loop social media networks leads to more professional use, less network transparency, and more information security and control (Wang, Pauleen, & Zhang, 2016). Although existing research indicates some features of closed-loop social media networks (e.g., Wang et al., 2016, Keinänen and Kuivalainen, 2015), theoretical and empirical research on how firms use closed-loop social media networks to enhance their new product performance remains scarce (Bhimani et al., 2019). To address this research gap, we focus specifically on how buying firms use closed-loop social media networks to provide venues for communication and collaboration with their supply chain partners, to effectively and efficiently develop their new products. For simplicity, we refer to the use of closed-loop social media networks as “social media” in the remainder of this manuscript.

The supply chain management literature (e.g., Cheng and Krumwiede, 2018, Bashir et al., 2017) has acknowledged the benefit of involving suppliers in the NPD process via using social media, that is, social media-based supplier involvement. This refers to those suppliers directly involved in the NPD process of the buying firms to which they supply parts and materials, who rely on social media to exchange knowledge regarding product design, product testing, and product commercialization (Cheng & Krumwiede, 2018). An added benefit rarely cited in previous literature is that social media-based supplier involvement enables many-to-many (as opposed to one-to-one) simultaneous communications among the focal buying firm and its suppliers (Bashir et al., 2017). Apparently, social media provides a more effective alternative for buying firms to communicate directly and immediately with suppliers incorporating their knowledge into the ideation stage, development stage, or launch stage of their NPD process (Roberts, Piller, & Lüttgens, 2016). However, despite a growing scholarly interest in social media-based supplier involvement, these previous studies (e.g., Cheng and Krumwiede, 2018, Bashir et al., 2017) highlight only separate one-on-one social media-based supplier involvement, with much less attention given to whether the research results and resulting theories are largely the same if the research focus is on the effects of many-to-many social media-based supplier network involvement. To investigate the issue of social media-based supplier involvement within closed-loop networks, we rely on network content of social network theory, which refers to resources that flow within and across social networks, while network structure refers to the pattern of collaborative relationships of a network graph (Dobrow, Chandler, Murphy, & Kram, 2012).

Network content to support collaboration network beyond organizational boundaries seems to be recognized in the literature as a critical feature for accelerating NPD (e.g., Lin and Lin, 2016, Phelps et al., 2012). In this regard, social media-based supplier network content, such as social media-based supplier involvement, is expected to provide buying firms with much quicker and richer access to new knowledge that can be important for NPD. It is important to note that one key implied difference in communication modes between this study and previous studies (e.g., Cheng and Krumwiede, 2018, Bashir et al., 2017) is that the former allows for many-to-many communications, virtually and simultaneously, resulting in a group of the focal buying firm and its pre-designated suppliers connected via social media, which can rightly be called a defined supplier network. In addition, there are a number of previous studies using the term “supplier network” as part of a variable in their studies (e.g., Bellamy et al., 2014, Terpend and Ashenbaum, 2012, Mahmood et al., 2011). Further, the term “supplier network involvement” represents a group-based variable, which is a collection of involvements among suppliers in the same network (Lynch, O'Toole, & Biemans, 2016). Taken together, we deem it appropriate to use the term “social media-based supplier network involvement” in the remainder of this manuscript. As for supplier network structure, research based on social network theory suggests that supplier network structure is essential in supply chain networks because the supplier network structure can be an effective governance mechanism that creates co-operative bonding between suppliers and the buying firms to whom they supply parts and materials (Carnovale and Yeniyurt, 2015, Bellamy et al., 2014). Therefore, social media-based supplier network structure represents a contingency factor that influences the impact of social media-based supplier network involvement on new product performance.

Overall, this study investigates the following two research questions: (1) Whether buying firms can benefit from their social media-based supplier network involvement in their pursuit of improved new product performance; and (2) To what extent does the effect of social media-based supplier network involvement on buying firms’ new product performance vary with social media-based supplier network structure? By addressing the above research questions, the current study contributes to the literature in two ways.

First, our study contributes to the collaborative innovation literature by offering a new position on the relationship between supplier involvement and buyers’ new product performance. While most existing research focuses on supplier involvement in buyers’ NPD (Suurmond, Wynstra, & Dul, 2020), we develop novel insights into the use of social media networks across suppliers and buyers involved in NPD, which enables us to uncover interplays across supplier–buyer and within supplier social media networks in the NPD process.

Second, despite the importance of suppler involvement to buyers’ NPD, few studies have investigated how social media-based supplier network structure differentially shapes buyers’ NPD success. The results of this study not only indicate that social media-based supplier network strength and network heterogeneity enhance buyers’ new product performance, but also that network density is found to be counter-productive. As such, we extend the social network literature by detailing various forms of social media-based supplier network structures and how they influence buyers’ NPD success, aspects that have not been addressed in previous research. These findings are not only theoretically important, but can also contribute to reducing the scarcity of empirical research on social media network structure (Muller & Peres, 2019). As Bhimani et al. (2019) reveal, buying firms today rely heavily on the collaboration of their social media-based supplier networks when developing new products. These firms can learn from the findings for improving their new product performance.

Section snippets

Social media-based supplier network involvement

Social network theory, referring to a social structure of relationships and links, which can be established in the form of exchanges among individuals, businesses, and organizations (Burt, 1997), suggests that firms are interconnected with one another and embedded in various external social networks, which enable the firms to gain efficient access to rich and diverse knowledge (Burt, 1997). The rationale for this process that builds on social network theory is that network configurations and

Sample

The target population was defined as high-tech firms and their suppliers based in Taiwan that had used social media in their NPD projects. These firms were selected for two reasons. First, this study chose high-tech industry in Taiwan as its research setting because, compared with other industries, the high-tech industry has been under the most pressure to innovate and introduce new products (Cheng, Yang, & Sheu, 2014). Second, to maintain their competitive advantage in the China market,

Analyses and results

Hypotheses 2, 3, and 4 posit the interaction effects between social media-based supplier network involvement and social media-based supplier network strength, network heterogeneity, and network density, respectively. We employed hierarchical moderated regressions to test our hypotheses because this approach allows for a comparison between alternative models with and without interaction terms (Aiken & West, 1991). In addition, this approach offers some better benefits than other methods (e.g.,

Discussion

This study is motivated by a need to improve our understanding of why some firms benefit more from their social-media based supplier network in their NPD activities than their counterparts. Building on social network theory, this study examines whether and how social media-based supplier network involvement and social media-based supplier network structure might enhance buying firms’ new product performance. The results of integrating a longitudinal design with secondary proxy dataset of 256

Colin C.J. Cheng is an academic researcher in innovation. He has published widely in journals including Journal of Product Innovation Management, Technovation, International Journal of Production Economics, Supply Chain Management, and many others. He is affiliated with National Taipei University.

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