What makes social media-based supplier network involvement more effective for new product performance? The role of network structure
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.
References (95)
- et al.
Retaining winners: Can policy boost high-growth entrepreneurship?
Research Policy
(2016) - et al.
Use of social media applications for supporting new product development processes in multinational corporations
Technological Forecasting and Social Change
(2017) - et al.
The influence of supply network structure on firm innovation
Journal of Operations Management
(2014) - et al.
Social media and innovation: A systematic literature review and future research directions
Technological Forecasting and Social Change
(2019) A note on social capital and network content
Social Networks
(1997)- et al.
The link between eco-innovation and business performance: A Taiwanese industry context
Journal of Cleaner Production
(2014) Market orientation, Guanxi, and business performance
Industrial Marketing Management
(2011)- et al.
Actors’ heterogeneity in innovation networks
Industrial Marketing Management
(2012) - et al.
How can clusters sustain performance? The role of network strength, network openness, and environmental uncertainty
Research Policy
(2010) - et al.
Bridges or isolates? Investigating the social networks of academic inventors
Research Policy
(2013)
How does technological diversity in supplier network drive buyer innovation? Relational process and contingencies
Journal of Operations Management
Using social power and influence to mobilise the supply chain into knowledge sharing: A case in insurance
Information & Management
We’re all connected: The power of the social media ecosystem
Business Horizons
Structural investigation of supply networks: A social network analysis approach
Journal of Operations Management
Absorptive capacity, innovation, and financial performance
Journal of Business Research
The effects of network sharing on knowledge-sharing activities and job performance in enterprise social media environments
Computers in Human Behavior
Influence of contingent factors on the perceived level of supplier integration: A contingency perspective
Journal of Engineering and Technology Management
Supplier involvement in NPD: A quasi-experiment at Unilever
Industrial Marketing Management
The effect of network relationship on the performance of SMEs
Journal of Business Research
The impact of informal social interaction on innovation capability in the context of buyer-supplier dyads
Journal of Business Research
The effect of social networks structure on innovation performance: A review and directions for research
International Journal of Research in Marketing
The value of social media for innovation: A capability perspective
Journal of Business Research
Employment background influence on social media usage in the field of European project management and communication
Journal of Business Research
PLS path modeling
Computational Statistics & Data Analysis
Social media technology usage and customer relationship performance: A capabilities-based examination of social CRM
Journal of Business Research
A critical view of knowledge networks and innovation performance: The mediation role of firms’ knowledge integration capability
Journal of Business Research
How social media applications affect B2B communication and improve business performance in SMEs
Industrial Marketing Management
Guanxi as a governance mechanism in business markets: Its characteristics, relevant theories, and future research directions
Industrial Marketing Management
Relative buyer-supplier relational strength and supplier's information sharing with the buyer
Journal of Business Research
Are relational ties always good for knowledge acquisition? Buyer–supplier exchanges in China
Journal of Operations management
Multiple regression: Testing and interpreting interactions
The strategic impact of external networks: Subsidiary performance and competence development in the multinational corporation
Strategic Management Journal
Whither Japanese keiretsu? The transformation of vertical keiretsu in Toyota, Nissan and Honda 1991–2011
Asia Pacific Business Review
Specification, evaluation, and interpretation of structural equation models
Journal of the Academy of Marketing Science
Don’t go it alone: Alliance network composition and startups’ performance in Canadian biotechnology
Strategic Management Journal
The socio-cultural environment for entrepreneurship: A comparison between East Asian and Anglo-Saxon countries
Journal of International Business Studies
On social network analysis in a supply chain context
Journal of Supply Chain Management
Social media use and participation: A meta-analysis of current research
Information, Communication & Society
Taiwan's bicycle industry A-Team battles Chinese competition with innovation and cooperation
Strategy & Leadership
Brokerage and closure: An introduction to social capital
Managing information processing needs in global supply chains: A prerequisite to sustainable supply chain management
Journal of Supply Chain Management
Vectors into the future of mass and interpersonal communication research: Big data, social media, and computational social science
Human Communication Research
The role of ego network structure in facilitating ego network innovations
Journal of Supply Chain Management
Enhancing the performance of supplier involvement in new product development: The enabling roles of social media and firm capabilities
Supply Chain Management: An International Journal
Open innovation: Where we've been and where we're going
Research-Technology Management
Cited by (17)
Revealing the determinants of residents' recycling behavior of express delivery packaging: Insights from the network embeddedness
2024, Environmental Impact Assessment ReviewMapping the relationship between social media usage and organizational performance: A meta-analysis
2023, Technological Forecasting and Social ChangeLeveraging supplier involvement for fueling manufacturers' firm creativity
2022, Industrial Marketing ManagementThe more engagement, the better? The influence of supplier engagement on new product design in the social media context
2022, International Journal of Information ManagementCitation Excerpt :Therefore, it remains to be explored whether the role of SE in new product design is ‘the more, the better’ in the context of social media. Furthermore, social media provides a common platform that enables mutual communication among manufacturers and their supplier networks, allowing members to communicate effectively and share experiences and technical information through virtual media (Cheng & Shiu, 2020; Kwayu et al., 2021). Such inter-firm knowledge sharing provides opportunities for mutual learning and empowers firms to create genuinely new values (Wang J, 2020).
Data strategies for global value chains: Hybridization of small and big data in the aftermath of COVID-19
2022, Journal of Business ResearchSocial media use: A review of innovation management practices
2022, Journal of Business ResearchCitation Excerpt :Social media also differs in terms of technological interfaces and functionalities, both of which promote strong ties among platform members (Hurmelinna-Laukkanen et al., 2021). Thus, a social-media-based network structure is considered a contingency factor between network interactions and innovation performance (Cheng & Shiu, 2020). Platform feature richness.
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.
Eric Shiu is an academic researcher in innovation. He has published widely in journals including Transportation Research Policy and Practice, Psychology and Marketing, Technovation, International Journal of Innovation Management, and many others. He is affiliated with the University of Birmingham in the UK.