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This paper aims to investigate the innovation pathway of gerontechnological enterprises under the market-organization-technology (MOT) perspective through configuration analysis.

Based on the analytical framework of technology, organization and market, this paper conducts configuration analysis on the cases of 55 elderly-friendly enterprises in China combined with fuzzy-set qualitative comparative analysis (fsQCA).

First, this study identifies the three first-level preconditions affecting innovation performance: organization's architectural innovation, technology adapting to aging and market environment attention on the innovation pathway of gerontechnological enterprises. These three first-level conditions include six sub-conditions. Second, this study investigates three innovation pathways by analyzing the configuration effects of preconditions: Configuration 1, technology-balanced type; Configuration 2, organization-market linkage type and Configuration, 3 balanced type. Third, there are differences in the distribution of different configuration types in subdivided industries. The technology-balanced configuration is mainly concentrated in design-driven innovative enterprises, the organization-market linkage configuration is mainly concentrated in medical auxiliary equipment enterprises and the balanced configuration is mainly concentrated in smart elderly care service platform enterprises empowered by digital technology. Fourth, there are differences in the innovation impact paths of the same configuration type. However, the essence lies in the high-level innovation performance formed by the coordinated evolution of technology, organization and market factors, reflecting the characteristics of the same goal through different routes.

The authors' study generates new insights for innovation managers of gerontechnological enterprises about the innovation pathway.

This research enriches innovation management by integrating the linkage adaptation relationship among market, organization and technology factors; further research studies on the different configuration types suitable for different types of enterprises, as well as differentiated innovation pathways under the same configuration type, could contribute to the study on the innovation pathway under a premise of MOT.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

Previous research has analyzed the consequence of network stability; however, little is known about how partner type diversity influence network stability in R&D network. Based on knowledge-based view and social network theory, the purpose of this paper is to unravel the internal mechanisms between partner type diversity and network stability through the mediating role of knowledge recombination in R&D network.

The authors collected an unbalanced panel patent data set from information communication technology industry for the period 1994–2016. Then, the authors tested the different dimensions of partner type variety and its relevance in the R&D network and the mediating role of knowledge recombination through adopting the multiple linear regression.

Results indicate an inverted U-shaped relationship between partner type diversity (variety and relevance) and network stability, whereas knowledge recombination partially mediate these relationships.

From the perspective of R&D networks, this paper explores that there are the under-researched phenomena the antecedent of network stability through nodal attributes (i.e. partner type variety and partner type relevance). Moreover, this paper empirically examined the mediating role of knowledge recombination in the partner type diversity–network stability relationships. The novel perspective allows focal firm to recognize importance of nodal attributes, which are critical to fully excavate the potential capabilities of cooperating partners in R&D network.

This study aims to investigate the critical success factors of digital transformation in the construction industry and identify whether the respondents' profiles influence their perceptions of critical success factors for digital transformation.

To achieve the objectives, a literature review was first conducted based on technology-organization-environment (TOE) framework. Then a questionnaire survey was carried out. A total of 86 people were surveyed in this study, mainly from the construction industry. At the level of data processing, SPSS was used for analysis. Among the main tests used were the Shapiro–Wilk test, reliability analysis, mean rank analysis, Kruskal–Wallis test and Mann–Whitney U test.

The study identified 15 critical success factors of digital transformation and found the three most important factors of digital transformation. Furthermore, respondents with different years of experience, enterprises with different sizes and different years made no difference in the perception of factors. Respondents' different occupations and types of enterprises created a bias in the perception of factors for digital transformation.

Firstly, the small sample size of the questionnaire limits the reference value of data analysis for certain groups. In addition, this study focuses broadly on construction enterprises without specifically examining different types of enterprises, thus lacking depth in its findings.

This study establishes a connection between TOE theory and the construction industry through an extensive literature review, identifying relevant factors and providing a reference for future research.

The study's results would enrich the research on digital transformation in the construction industry and provide a reference for the digital transformation of construction enterprises.

This study aims to present the results of a comparative study on the most key reasons for the failure of sustaining activities of operational improvement (OI) methodologies from the different types of manufacturing enterprises that located in Vietnam.

This study presents survey results from 30 local manufacturing enterprises and 21 foreign direct investment (FDI) enterprises located in Vietnam – a developing country. The authors utilize a combination method to collect data, including online and direct survey. The targeted interviewees selected to answer the questionnaire are manufacturing managers and top managers working in productivity, quality, engineering and other departments in respective firms. The developed questionnaire is verified by five experts to ensure the validity and soundness.

The study uncover that 21 local enterprises (70%) have not issued standard forms for OI deployment and supervision, while 17 foreign enterprises (81%) have adopted a systematic management and clearly indicators for evaluation of OI outputs. In addition, the top three reasons for OI failure are differences between local and foreign enterprises. In term of OI methodologies, most of participated enterprises implemented Lean tools and principles while only 7.8% of the participated enterprises applied Six Sigma. Three vital findings are uncovered, including, first, 30% of local enterprises standardize and supervise forms of OI.

There is a limitation in sample size, with the number of participants of 51 enterprises. Among the participants, 27% of local enterprises are small and medium-sized enterprises (SMEs) while 60% of FDI enterprises from large-sized group. This was limited to making a generated conclusion in the comparison of failure factors between two types of enterprises. This partly affects the radical comparison of failure factors between local and FDI enterprises.

To the best of the authors' view, this is the first empirical study that compares the reasons for the failure for sustaining OI between local and foreign enterprises in a developing country. The result from this study will make contributions for further research in considering OI failure factors and then enhance effectiveness of OI methodologies in manufacturing companies.

Do corporate social responsibility (CSR) practices necessarily increase their social capital? The key to answering this question lies in understanding the impact of the interactive behavior of CSR and social capital on the sustainable operation and development of enterprises. This paper finds that existing studies cannot accurately describe the inherent interaction between CSR and social capital, and the results verified by econometric models are often abstract and do not adequately reflect the actual business situation of enterprises.

This article tries to make a breakthrough in two aspects: the article identifies the common practice object of CSR and social capital by using the “stakeholder” mechanism and puts forward the hypothesis of the relationship between CSR and social capital by observing the interaction behavior between enterprises and stakeholders; based on the perspective of sustainable development, the article proposes the elements of “trust, norm and rationality,” analyzes the behavioral choices of enterprises in social responsibility practice and social capital accumulation and clarifies the inherent relationship between them.

The article points out the impact of the multifaceted nature of the relationship between CSR practices and social capital enrichment on the sustainable development of enterprises and proposes that manufacturing enterprises in transformation and innovation should be analyzed using an objective position rather than value judgment.

This paper synthesizes the assessment data from the questionnaire, interview data and sustainability analysis to answer the questioning of existing research: CSR does not necessarily increase corporate social capital, and the relationship between the two is complex and multifaceted, depending on the specific target and business state of the company. The focus of this paper is to analyze in detail the three relationship assumptions that form when companies interact with their stakeholders, based on the sustainability perspective of “trust,” “norms” and “rationality.”

Energy conservation and environmental protection industry (ECEPI) is a strategic choice to promote energy conservation and emission reduction, develop green economy and circular economy. However, China’s ECEPI is still in the stage of rapid development and the overall scale is relatively small, what development periods have the ECEPI experienced? This study aims to contribute to a better understanding of collaborative innovation evolution based on social network analysis from the perspective of multi-dimensional proximity.

Methodologically, this study uses social network analysis method to explore the co-evolution of multidimensional collaboration networks. It divides China’s ECEPI into four periods based on national policies from 2001 to 2020. This contribution constructs collaborative innovation networks from geographical, technological and organizational proximity.

The results show that the collaborative innovation network was initially formed in the central region of China, gradually expanded to neighboring cities and the core positions of Beijing, Jiangsu and Guangdong have been continuously consolidated. C02F has been the core of the collaboration networks, and the research focus has gradually shifted from the treatment of wastewater, sewage or sludge to the separation field. Enterprises always occupy a dominant position in the collaboration networks.

This research investigates the dynamic evolution process of collaborative innovation network in China’s ECEPI from the perspective of multidimensional proximity, explores the community structure, important nodes and multidimensional proximity features in the network, expands the research perspective on evolution characteristics of innovative network and the research field of social network analysis. Theoretically, this study enriches collaborative innovation theory, social network theory and multi-dimensional proximity theory.

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.

An alliance portfolio can help latecomer firms to acquire the necessary knowledge and resources to catch up with market leaders. However, how latecomer firms construct an alliance portfolio in terms of the nature of windows of opportunity has not been fully analyzed. This paper aims to explore how latecomer firms can build appropriate coalitions according to the nature of the window of opportunity to achieve technological catch-up in different catch-up phases.

Based on a longitudinal case study from 1984 to 2018 of Sunny Group, now a leading manufacturer of integrated optical components and products, this paper explores the process of technological catch-up of latecomer firms building different types of alliance portfolio in different windows of opportunity.

This paper finds that there is a sequence when latecomers build an alliance portfolio in the process of catch-up. When the uncertainty of opportunity increases, the governance mechanism of the alliance portfolio will change from contractual to equity-based. Also, latecomer firms build market-dominated and technology-dominated alliance portfolios to overcome their market and technology disadvantages, respectively.

These conclusions not only enrich the theory of latecomer catch-up from the perspective of windows of opportunity but also expand research on alliance portfolio processes from a temporal perspective.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.