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This study provides a configurational examination of how policy designs influence the innovation performance of the emergency industry in China.

This study employs the Data Envelopment Analysis Malmquist index (DEA-Malmquist) to quantify the innovation performance of the emergency industry and then codes the innovation policies to calculate the syntactic components based on institutional grammar tools (IGTs). The configurations of syntactic components were determined by applying the fuzzy-set qualitative comparative analysis (fsQCA).

The results indicate that rules- and norms-oriented policy designs would improve the innovation performance of China's emergency industry. In the developed provinces, the “Deontic” and “aIm” combinations in the policy are useful for improving performance. In the developing provinces, the ambiguity of the “aIm” and “Context” conditions in the policy is leading to low performance. Additionally, a lack of strategy-oriented policy design would also result in poor performance.

Most previous studies used substitute variables to understand policy impacts. This study contributes to identifying the impacts of the syntactic components of policy designs on the innovation performance of the emergency industry. The findings can assist policymakers in developing more effective policies to stimulate innovation development in the emergency industry.

Conducting innovation in low-carbon technology is vital to boost the low-carbon economy. Collaborative innovation among industry-university-research (IUR) is an effective mode of developing low-carbon technologies. There is a lack of visualization and analysis of the spatial-temporal of such collaboration among the IUR. This paper aims to serve as insights to guide IUR’s collaborative innovation in Chinese universities to promote low-carbon technologies.

This paper uses IncoPat to collect patent data. Collaborative patent output on low-carbon technologies was selected as the indicator to measure the effectiveness of IUR collaboration. The temporal evolution trend of the collaborative patent output in Chinese universities is analyzed.

The collaborative patent output of the Chinese IUR varies greatly among the regions, evolving from stronger in the east and weaker in the west, to stronger in the south and weaker in the north region. The triple helix (TH) innovation system in China’s low-carbon sector is dominated by intraregional collaborative innovation, while there is a weak bilateral synergy between universities and research institutions.

This paper innovatively developed a novel TH model that characterize the regional differences of the IUR collaboration in low-carbon technology innovation of Chinese universities. A new attempt focuses on the spatial-temporal evolution of the collaborative innovation of IUR to promote low-carbon technologies.

This study aims to investigate the role of interfirm communication on the complementary effect between corporate political action (CPA) and research and development (R&D) investments under transaction costs.

A quasi-experiment study design was used, combining business game simulation and a public goods experiment with communication as a controlled variable. A fixed-effect regression analysis was performed on panel data collected from 72 students.

The findings indicate that collective CPA is positively and significantly associated with R&D investments, particularly when interfirm communication is present. Conversely, for non-communicating firms, the effect is limited to the relationship between individual CPA and R&D investment.

Despite advancing the research on political ties and innovation, the study acknowledges limitations related to framing effects and institutional variability.

The complementary effects indicate that institutional arrangements (i.e. business associations) may foster interfirm communication and cooperation in CPA efforts, mitigating opportunistic behaviours and legitimising CPA strategy towards innovation.

This study contributes to understanding how firms’ political and R&D decisions can positively impact innovation, despite the challenges of ex post transaction costs.

The positive effect of communication on political action and cooperation on firms’ innovation, even in weak institutional environments, is highlighted. An innovative methodological approach combining business games and economic experiments was used to examine participants’ decisions under transaction costs.

This study aimed to facilitate a rapid evaluation of track service status and vehicle ride comfort based on car body acceleration. Consequently, a low-cost, data-driven approach was proposed for analyzing speed-related acceleration limits in metro systems.

A portable sensing terminal was developed to realize easy and efficient detection of car body acceleration. Further, field measurements were performed on a 51.95-km metro line. Data from 272 metro sections were tested as a case study, and a quantile regression method was proposed to fit the control limits of the car body acceleration at different speeds using the measured data.

First, the frequency statistics of the measured data in the speed-acceleration dimension indicated that the car body acceleration was primarily concentrated within the constant speed stage, particularly at speeds of 15.4, 18.3, and 20.9 m/s. Second, resampling was performed according to the probability density distribution of car body acceleration for different speed domains to achieve data balance. Finally, combined with the traditional linear relationship between speed and acceleration, the statistical relationships between the speed and car body acceleration under different quantiles were determined. We concluded the lateral/vertical quantiles of 0.8989/0.9895, 0.9942/0.997, and 0.9998/0.993 as being excellent, good, and qualified control limits, respectively, for the lateral and vertical acceleration of the car body. In addition, regression lines for the speed-related acceleration limits at other quantiles (0.5, 0.75, 2s, and 3s) were obtained.

The proposed method is expected to serve as a reference for further studies on speed-related acceleration limits in rail transit systems.

Although the literature provides insights into the role of experiential learning based on prototypes in identification of latent customer need, it offers different views on the role of product prototypes in improving the efficacy of learning customer need, and also neglects the role of vicarious learning in prototype-based experiential learning. In a data-rich environment, market big data create new opportunities to learn from vicarious, digitalized experiences that are not observable with prototype-based learning. Therefore, the purpose of this study is to compare the effects of product prototype strategies – basic prototype strategy and enhanced prototype strategy – on identification of latent customer needs, and determine how each prototype strategy interacts with vicarious learning based on market big data to identify latent customer needs.

We collected data from 299 Chinese manufacturing firms via on-site surveys to explore our research question. All of our hypotheses were supported by the regression results.

This study finds that both the enhanced and basic prototype strategies (experiential learning from direct market experience based on prototyping) have positive effects on latent need identification, but the effect of enhanced prototypes is stronger. Furthermore, the enhanced and basic prototype strategies have different interaction effects with market big data (vicarious learning from indirect market experiences) on latent need identification.

This research extends the literature on prototype-based learning for latent need identification. It also contributes to the experiential prototype-based learning literature by exploring the role of vicarious learning based on market big data.

We aim to provide a systematic literature review of the determinants and consequences of labor investment efficiency in an international context. First, we offer a theoretical discussion of labor investment efficiency, followed by an examination of its measurement. Next, we review the determinants of labor investment efficiency, categorizing them into firm fundamentals including financial reporting quality, governance and controls, corporate social responsibility/environmental regulation and macroeconomic determinants. Finally, we review the limited empirical literature on the consequences of labor investment efficiency. We also provide some suggestions for future research.

We perform a systematic literature review using the Preferred Reporting Items for a Systematic Review of Meta-Analysis (PRISMA) guidelines to examine archival studies investigating the determinants and consequences of labor investment efficiency. Using a Boolean search strategy on the Scopus and PRISMA selection criteria, we review 86 published archival research articles from 2014 to the end of August 2024.

Our review highlights that firm-level fundamental factors including financial reporting quality have profound implications for labor investment efficiency. Effective governance mechanisms also help mitigate agency conflicts and information asymmetries and alleviate labor investment inefficiencies. Furthermore, the influence of regulations including ESG-related regulations and macroeconomic factors play a crucial role in shaping labor investment decisions. We find very little research on the consequence of labor investment efficiency.

Our review has highlighted that well-functioning corporate governance tools are effective in mitigating inefficient labor investments. Stakeholders, therefore, should ensure that firms have effective internal governance mechanisms in place and that external governance regulations complement and where necessary act as substitutes for internal governance mechanisms to optimize labor investments.

To the best of our knowledge, this study represents the first systematic review of extant research on labor investment efficiency. Our review highlights some research gaps, particularly about the consequences of labor investment efficiency and offers some suggestions for future research.

This study aims to investigate how relationship conflict (RC) hinders green customer integration (GCI) and which strategy could be developed to alleviate the negative effect of RC.

The authors use a sample of 206 Chinese firms to examine hypothesized relationships drawing on social exchange theory and buyer-supplier relationship perspective. Methods including exploratory factor analysis and confirmatory factor analysis are used to assess reliability and validity. Hypotheses are tested using hierarchical regression analysis. Post hoc analysis is adopted to evaluate the robustness.

The results show that RC negatively relates to GCI. Normative commitment partially mediates the relationship between RC and GCI, while the mediating role of instrumental commitment is insignificant. In addition, coercive influence strategy positively moderates the RC-normative commitment and RC-GCI relationships.

While this study clarifies the mechanism of how RC impedes GCI and how to address RC in buyer-supplier relationships, it could be more meaningful to extend the current research and figure out how to address RC in different supply chain relationships. Besides, it will make sense to conduct longitudinal studies and explore the dynamic nature of RC in supply chain relationships.

In practice, firms find it challenging to achieve GCI owing to the ubiquitous existence of RC. The findings reveal that RC detriments GCI partially through normative commitment, and the use of coercive influence strategy mitigates the detriments of RC. Thus, the authors provide solutions for firms to address RC for achieving GCI.

RC is unavoidable in organizational interactions. Prior studies have not revealed the processes through which RC relates to GCI. The authors bridge the gap by exploring the mediating role of organizational commitment and the moderating role of influence strategy, which offers a better understanding of how RC is associated with GCI, and add knowledge of addressing RC for achieving GCI.

This study aims to investigate the impact of channel diversity on constructive and destructive conflicts in manufacturer-distributor relationships, as well as the mediating role of distributor opportunism and the moderating role of distributor network centrality.

This paper collected channel dual data to represent channel behavior in manufacturer-distributor relationships accurately. Using 208 matched manufacturer distributor bilateral data from Chinese B2B firms validate the conceptual model. This paper tested the proposed hypothesis using AMOS 24.0 software.

Channel diversity strengthens constructive conflict and weakens destructive conflict between manufacturers and distributors. Distributor opportunism plays a mediating role between channel diversity and constructive conflict. Distributor network centrality reinforces the positive impact of channel diversity on constructive conflict and the impact of channel diversity on destructive conflict.

This research contributes significantly to developing channel diversity and conflict theory by expanding the dyadic view to a network view. It also provides valuable insights for managers, highlighting the importance of maintaining a good relationship with distributors with high network centrality. The research results allow the constructive aspects of channel conflict to manifest fully and enhance the effectiveness of channel management. Distributor firms should prioritize communication and contact with network members to increase their network centrality, enabling them to take more initiative, exert influence and establish advantageous cooperative partnerships with manufacturers.

This study aims to understand the impact of extreme weather events on fast-moving consumer goods (FMCG) consumption and to examine the role of anticipated product scarcity and FMCG types on such behavior.

This paper conducted five studies, combining archival data analysis with behavioral experiments. The archival data included sales data from a supermarket chain and weather data from the National Weather Service. The experiments were designed to test the effect of extreme weather cues on consumption, the psychological mechanism behind this effect and moderators.

This research found that consumers’ anticipation of extreme weather events significantly increases their consumption of FMCGs. This research further discovered that these behaviors are driven by anticipated product scarcity and moderated by consumers’ altruisms and FMCG types.

Limitations of the research include the reliance on reported sales data and self-reported measures, which could introduce biases. The authors also primarily focused on extreme weather events, leaving other types of disasters unexplored. Furthermore, cultural differences in disaster response might influence results, yet the studies do not fully address these nuances. Despite these limitations, the findings provide critical insights for FMCG retailers and policymakers, suggesting strategies for managing demand surges during disasters. Moreover, understanding consumer behavior under impending disasters could inform intervention strategies, potentially mitigating panic buying and helping ensure equitable resource distribution. Last, these findings encourage further exploration of environmental influences on consumer behavior.

The findings have practical implications for products, brand managers and retailers in managing stock levels and product distribution during disasters. Furthermore, understanding the psychological mechanisms of these behaviors could inform policymakers’ designs of public interventions for equitable resource allocation during extreme weather events.

The research provides significant social implications by highlighting how extreme weather events impact FMCG consumption. This understanding can guide public policymakers in creating efficient disaster management plans. Specifically, anticipating surges in FMCG purchases can inform policies for maintaining price stability and preventing resource shortages, mitigating societal stress during crises. Moreover, these findings encourage public education around responsible purchasing during disasters, potentially reducing panic buying. By collaborating with FMCG manufacturers and retailers, governments can ensure a steady supply of essentials during extreme weather events. Thus, the research can play a crucial role in enhancing societal resilience in the face of impending disasters.

To the best of the authors’ knowledge, this is the first study to integrate the impact of extreme weather events on consumption behavior with the psychological theory of anticipated product scarcity. The unique focus on FMCGs offers a novel perspective on consumer behavior literature.

Drawing on the principal-agent theoretical perspective, we assert that sellers’ opportunism is acknowledged as an essential component that could determine the quality of the relationship between buyers (principals) and sellers (agents). The primary aim of this research is to investigate the influence of seller behavior vs outcome-based reputation and seller’s perceived freedom on opportunistic behavior in the Chinese e-commerce platform context.

The data collected from 436 e-commerce platform sellers were analyzed and interpreted using structural equation modeling.

The results indicate that both behavior-based and outcome-based reputations positively impact sellers’ perceived freedom but negatively impact their opportunism. Additionally, while perceived freedom of objectives reduces opportunism, freedom of action increases it. The study also highlights the significant moderating roles of prevention mechanisms and ethical ideology.

This study extends the principal-agent perspective by integrating the seller’s reputation as a potential source of preventing sellers from behaving opportunistically on e-commerce platforms.