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Manufacturers increasingly resort to digital transformation to shape their competitiveness in the digital economy era, while supply chain (SC) collaborative innovation helps them cope with market uncertainties. However, whether and how digital transformation can facilitate SC collaborative innovation remain unclear. To address this gap, we aims to investigate the effects of digital transformation (strategy and capability) on SC collaborative (process and product) innovation and market performance.

We use partial least squares-structural equation modelling (PLS-SEM) with a sample of 210 Chinese manufacturers to investigate the effects of digital transformation (strategy and capability) on SC collaborative (process and product) innovation and market performance.

The results show that digital strategy and capability positively impact SC collaborative process and product innovation, which enhances market performance. In addition, SC collaborative innovation mediates the relationship between digital transformation and market performance.

This study contributes to the literature by identifying how digital transformation drives SC collaborative innovation towards improving market performance and providing practical guidance for enterprises in promoting digital transformation and SC collaborative innovation.

This study aims to examine the effect of supplier supply network (SSN) resources on buyer–supplier collaborative product innovation. The existing relevant studies from the network perspective are focused more horizontally on the mobilization of the firm’s entire supplier network resources and less vertically on the utilization of the individual supplier's supply network resources. Therefore, this paper takes a contingency perspective, regards the buyer as the receiver of a supplier’s supply network resources and, based on the theoretical motivation–opportunity–ability framework, explores the important motivation and ability factors that may weaken or enhance the product innovation value of the network resources.

This paper develops a new research model that assesses how the innovation utilization effectiveness of SSN resources is contingent on a buyer’s perception of the SSN effects and relative absorptive capacity on the SSN. A large sample questionnaire is designed and collected from 300 Chinese high-tech manufacturing firms and their suppliers. An empirical test is carried out in which multiple regression analysis is applied to 246 valid sample data.

The results show that SSN resources can significantly enhance buyer–supplier collaborative product innovation; however, the innovation utilization effectiveness is limited by the buyer’s relative absorptive capacity for the SSN and perception of the SSN effects. Specifically, if a buyer perceives that a greater innovation effect of a supplier’s supply network is correlated with an improved relative position in the SSN or with higher network structural equivalence and network cognitive congruence between the buyer and the supplier on the SSN, then the buyer will be more motivated and capable of transforming the SSN resources into actual product innovation value.

The research results provide useful guidance for firms to effectively mobilize their SSN resources to tap into the supplier innovation value for a sustainable competitive advantage.

This paper extends the research on supplier innovation value to the SSN field. Through linking dyadic and network levels of analysis, this paper reveals the value and uniqueness of product innovation utilization of a specific supplier’s supply network resources in the buyer–supplier relationship and provides a new research perspective for future studies on related issues.

The purpose of this study is to empirically investigate the extent to which two types of commercial partnerships (business partner and non-business partner) affect the collaborative innovation of firms in emerging economies. Specifically, the roles of two commercial partnerships are investigated. Additionally, the study explores the moderating effect of external technological uncertainty and internal dynamic capabilities on the relationship between two commercial partnerships and on collaborative innovation.

Using a sample of 370 high-tech firms in China, the authors applied the partial least squares structural equation modeling approach to model these relationships.

The findings reveal opportunities and challenges for companies according to two intensities of commercial partnership for collaborative innovation. The partnership contribution to innovation and competiveness is different within the two routes and ranges. The findings indicate that (1) intense commercial relationships with business partners have a stronger positive significant impact on collaborative innovation than those with non-business partners and (2) non-business partners have a weaker positive impact on collaborative innovation at high external technological uncertainty. It was also found that (3) the positive impact of business partners on collaborative innovation is weakened when a firm has high dynamic capabilities, whereas the positive impact of non-business partners is strengthened.

Insight into the roles of two commercial partnerships in achieving collaborative innovation facilitates the advancement of the theoretical understanding of the circumstances under which cooperative innovation can be more effective under different partnerships.

A key strategic question is whether comprehensiveness enables firms to make better strategic decisions in various environments. In the process of innovation, companies must choose different types and quantities of partners, and they must regulate their partners’ innovative behavior by establishing a corresponding network structure and relationship rules. The current study focuses on analysis of how different intensities of commercial partnerships affect collaborative innovation. This research provides a theoretical framework that creates a new classification of commercial relations with regard to collaborative innovation, and it highlights the difference between the two types of partnerships. This study finds that there are many problems in the selection of innovative partners in China’s high-tech companies. Therefore, companies should strengthen their understanding of cooperative innovation, and they should build and manage highly efficient innovation networks. This study helps companies, high-tech industry associations, academia and government to take enhanced, informed actions.

Based on media choice theories and real option theory, this study aims to explore the role of communication media portfolio in achieving collaborative innovation with suppliers.

Using data of the Study of Competitiveness, Technology and Firm Linkages 2002 collected by the World Bank and the Enterprise Survey Organization of the Chinese National Bureau of Statistics, this study employed logit model to test the hypotheses. Moreover, some robustness analyses were conducted.

This study suggests that media multiplicity increases the probability for a firm to achieve collaborative innovation with suppliers on the basis of real option theory. Furthermore, distance from the suppliers and relationship formality make media multiplicity further important in collaborative innovation with suppliers.

Through investing how communication media portfolio affecting collaborative innovation with suppliers and the contingency factors, this study complements existing studies just concentrating on supplier capabilities, relationships with suppliers and characteristics of supplier network. Moreover, this study contributes in the information system field by exploring the role of media portfolio rather than individual media.

This study is aimed at making an inspection of the effects of collaborative innovation network characteristics on firm innovation performance, and the intermediary roles of knowledge transfer efficiency is taken into account.

This study used a convenient sampling method to obtain population and samples. Using data obtained by publishing online and paper questionnaires, and using on-site interviews in Anhui Province in the Yangtze River Delta region of China, descriptive analysis, regression analysis and correlation analysis are utilized to study the direct influence of collaborative innovation network characteristics on knowledge transfer efficiency as well as firm innovation performance, and the intermediary roles of knowledge transfer efficiency on firm innovation performance, respectively. In this study, 3,000 questionnaires were distributed to the employees of enterprises engaged in research and development (R&D) activities, of which 2,560 were valid. With the help of SPSS24.0 software, the reliability and validity of the questionnaire was analyzed.

The results are indicative of that network centrality and relationship strength positively affect knowledge transfer efficiency and firm innovation performance. Nevertheless, network scale has no significant correlation with knowledge transfer efficiency and enterprise innovation performance. In addition, knowledge transfer efficiency is an intermediary between collaborative innovation network characteristics and enterprise innovation performance, and positively affects enterprise innovation performance, which demonstrated that managers should take advantage of collaborative innovation network characteristics to elevate knowledge transfer efficiency because well-realized transferals of knowledge can help accelerate the coordination of resources in knowledge, and finally bring about the advancement of firm's innovation abilities and performance.

There are few previous studies that fully examined the relationships among collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. This paper developed previous researches on the relationships between collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. The mediation of knowledge transfer efficiency on the relationship between collaborative innovation network characteristics and firm innovation performance is analyzed. Further, studies on collaborative innovation network characteristics using data obtained from employees engaged in R&D activities are very limited in the literature. On account of that, the findings in this study may make sense to the innovation ability of innovative enterprise and expand the literature in the field of enterprise strategic management and knowledge management.

This analysis shows that collaborative innovation network characteristics have both positive and negative effects on firm innovation performance. Therefore, business managers should pay attention to their position in the collaborative innovation network and maintain the relationship strength with other innovation subjects. Special consideration should be given to the knowledge transfer of innovative enterprises, so as to improve firm innovation performance practically.

The study may provide additional understandings for researchers, government managers, universities and enterprises with regard to strategic management from the visual angle of innovation ecosystems. It is instrumental in the exploration of the mechanisms enabling firm innovation performance.

The purpose of this paper is to propose and empirically investigate the concept of networking capability (NC) for the management of supplier relationships and their dynamics in order to leverage product innovations. NC in the context of supplier relationships is conceptualized based on dynamic capabilities aimed at relationship initiation, relationship development, and relationship ending. Furthermore, the study tests the interaction of NC with relationship proclivity as an organizational feature, and analyzes latent classes of NC affecting product innovation.

This study brings together prior research on company routines related to inter-firm networking, the dynamic capability approach to strategy, and literature on inter-firm innovation. The study utilizes multiple informant survey data gathered from 156 firms operating in the automotive parts industry in Iran. Data are analyzed with partial least square structural equation modeling, as well as latent class analysis using finite mixture modeling (FIMIX-PLS).

This research provides evidence for the positive influence of NC with respect to supplier relationships on firm product innovation, as well as overall firm performance. Relationship proclivity is shown to amplify this effect. At the same time, the research illustrates that NC may be applied in different combinations in the context of supplier relationship portfolio management. Two mechanisms are tentatively identified: firms using “static optimization” focus mainly on supplier relationship development capabilities, while those using “dynamic optimization” utilize supplier relationship initiation and ending capabilities.

This research focuses on one setting (i.e. the automotive parts industry in Iran). Further studies need to broaden these findings to other industries and countries, specifically those which show a different cultural make-up from Iran. Furthermore, this research indicates the existence of two distinct mechanisms as to how different aspects of NC impact product innovation. While it is reasonable to identify these mechanisms as networking “strategies,” this study does not clarify whether this represents intended strategies by firms or relates to emerging capability patterns.

The study contributes to managerial knowledge by illustrating the need for a dynamic approach with regard to networking-related routines in supplier relationships in the context of product innovation. This study suggests that managers should devote equal attention to strengthening existing supplier relationships as well as to initiating new supplier relationships (e.g. screening for promising partners and signaling firm’s relationship value to attract new counterparts) and managing non-performing supplier relationships (e.g. by developing routines to exit from those supplier relationships).

The paper contributes to a better understanding of dynamic approaches to networking with suppliers and their impact on product innovation from the perspective of the focal firm. It furthermore provides a fine-grained understanding of different latent classes of firms in terms of how they utilize networking capabilities.

This paper aims to investigate the role of knowledge management in collaborative innovation and identifies the knowledge management approaches for supporting collaborative innovation community capacity building (CICCB) in organizations. The importance of collaborative innovation in developing organizational competitiveness is increasingly being recognized in both theory and practice worldwide. Collaborative innovation, however, is still under-explored from the trans-disciplinary perspective of knowledge management and community capacity building.

A comprehensive review of the related literature in collaborative innovation and knowledge management is conducted. Three demands for CICCB, including trust building for enhancing the effectiveness, sustainability building for improving the efficiency and extensibility building for developing the competitiveness in organizations, are identified, which paves the way for the development of a holistic approach to effective CICCB.

Three roles of knowledge management in supporting CICCB are identified, including the reformation of knowledge management for convergence in collaboration, the remediation of knowledge activities for synergy in communication and the reconfiguration of knowledge artifacts for the integration of knowledge management activities in connectivity. A holistic approach is proposed for effective CICCB in organizations, including the multi-dimensional convergence for trust building in collaboration, the multi-directional synergy for sustainability building in communication and the multi-layer integration for extensibility building in connectivity.

Insights about how organizations can better support CICCB through effective knowledge management for improving their competitiveness are provided based on the identification of the demand for CICCB and the role of knowledge management in collaborative innovation. The development of a holistic approach to effective CICCB can help organizations better utilize their limited resources for developing their competitiveness in today’s dynamic environment.

This paper is the first step of a comprehensive study on the role of knowledge management in supporting CICCB in organizations in today’s dynamic environment. It provides a solid foundation for the investigation of the models, approaches and mechanisms for effective CICCB through knowledge management in organizations.

Green innovation in supply chains is crucial for socioeconomic development and stability. Factors that influence collaborative green innovation in the supply chain are complex and diverse. Exploring the main influencing factors and their mechanisms is essential for promoting collaborative green innovation in supply chains. Therefore, this study analyzes how upstream and downstream enterprises in the supply chain collaborate to develop green technological innovations, thereby providing a theoretical basis for improving the overall efficiency of the supply chain and advancing green innovation technology.

Based on evolutionary game theory, this study divides operational scenarios into pure market and government-regulated operations, thereby constructing collaborative green innovation relationships in different scenarios. Through evolutionary analysis of various entities in different operational scenarios, combined with numerical simulation analysis, we compared the evolutionary stability of collaborative green innovation behavior in supply chains with and without government regulation.

Under pure market mechanisms, the higher the green innovation capability, the stronger the willingness of various entities to collaborate in green innovation. However, under government regulation, a decrease in green innovation capability increases the willingness to collaborate with various entities. Environmental tax rates and green subsidy levels promote collaborative innovation in the short term but inhibit collaborative innovation in the long term, indicating that policy orientation has a short-term impact. Additionally, the greater the penalty for collaborative innovation breaches, the stronger the intention to engage in collaborative green innovation in the supply chain.

We introduce the factors influencing green innovation capability and social benefits in the study of the innovation behavior of upstream and downstream enterprises, expanding the research field of collaborative innovation in the supply chain. By comparing the collaborative innovation behavior of various entities in the supply chain under a pure market scenario and government regulations, this study provides a new perspective for analyzing the impact of corresponding government policies on the green innovation capability of upstream and downstream enterprises, enriching theoretical research on green innovation in the supply chain to some extent.

Selecting suitable and competent partners is an important prerequisite to improve the performance of collaborative product innovation (CPI). The purpose of this paper is to propose an integrated multi-criteria approach and a decision optimization model of partner selection for CPI from the perspective of knowledge collaboration.

First, the criteria for partner selection are presented, considering comprehensively the knowledge matching degree of the candidates, the knowledge collaborative performance among the candidates, and the overall expected revenue of the CPI alliance. Then, a quantitative method based on the vector space model and the synergetic matrix method is proposed to obtain a comprehensive performance of candidates. Furthermore, a multi-objective optimization model is developed to select desirable partners. Considering the model is a NP-hard problem, a non-dominated sorting genetic algorithm II is developed to solve the multi-objective optimization model of partner selection.

A real case is analyzed to verify the feasibility and validity of the proposed model. The findings show that the proposed model can efficiently select excellent partners with the desired comprehensive attributes for the formation of a CPI alliance.

Theoretically, a novel method and approach to partner selection for CPI alliances from a knowledge collaboration perspective is proposed in this study. In practice, this paper also provides companies with a decision support and reference for partner selection in CPI alliances establishment.

The aim of the study was to examine the role of collaborative approaches (productive collaboration, collaborative innovation and collaborative risk management) in disaster risk situations. Thus, the study focused on the effect of productive collaboration and collaborative innovation on collaborative risk management, and the effect of collaborative risk management and collaborative innovation on adaptability.

Data were collected from nongovernmental organizations (NGOs). The Covariance Based Structural Equation Modeling software was used to obtain results on the influence of productive collaboration and collaborative innovation on collaborative risk management, the influence of collaborative innovation on adaptability and the influence of collaborative risk management on adaptability.

Findings indicated that both productive collaboration and collaborative innovation influence collaborative risk management, and both collaborative innovation and collaborative risk management influence adaptability.

The study mainly focused on the NGOs eliminating the government, beneficiaries and other actors that may be involved in disaster risk situations. The research has implications to decision makers in government, NGOs and other actors concerned with disaster risk management.

Countries worldwide are focusing on collaborative innovation and productive collaboration in addition to collaborative risk management to respond to epidemics and natural disasters. Despite the relevance of the collaborative initiatives, empirical research explaining the relevance of the variables to adaptability of actors during epidemics or natural disasters is still lacking.