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Owing to the development of the smaller-sized rotational machinery, the demand for the high-speed and low-resistance gas bearing increases rapidly. The research of micro gas bearing in the condition of rarefied gas state is still not satisfied. Therefore, the purpose of this paper is to present a numerical investigation of the effect of misalignment and rarefaction effect on the comprehensive performance of micro-electrical-mechanical system (MEMS) gas bearing.

The Fukui and Kaneko model is expanded to 2D solution domain to describe the flow field parameters. The finite element method is used to discretize the equation. Newton–Raphson method is used to solve the nonlinear equations for the static performance of gas bearing, and partial deviation method is adopted for the solution of dynamic equations.

The static and dynamic characteristics of MEMS gas bearing are calculated, and the comparison is made to study the influence of rarefaction effect and misalignment. The results show that the rarefaction effect will decrease bearing load capacity compared with traditional solution of Reynolds equation, and the misalignment will reduce the stability of bearing. The influence of misalignment on gas film thickness is also analyzed in this paper.

The investigation of this paper emerges the change regularity of comprehensive performance of MEMS gas bearing considering rarefaction effect and misalignment, which provides a reference for the actual manufacturing of MEMS gas bearing and for the safety operation of micro dynamic machinery.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2020-0023/

This study aims to construct a theory of multi-dimensional organizational innovation cultures and innovation performance in transitional economies and explore the moderating effect of team cohesion on this theoretical relationship.

Using data collected from 175 manufacturing firms in transitional economies, this study constructs a new theory framework of multi-dimensional organizational innovation cultures (knowledge sharing, organizational innovation atmosphere, team decision-making and organizational change) and firms’ innovation performance and also explores the moderating effect of team cohesion on this theoretical relationship.

The findings show that there are positive relationships between knowledge sharing, organizational innovation atmosphere, team decision-making, organizational change and innovation performance of firms. Furthermore, team cohesion plays a positive moderating role in this relationship.

It extends the general understanding of multi-dimensional organizational cultures management in the context of transition economies by exploring the differences between the Chinese and Vietnamese firms in terms of the impact of organizational innovation culture on innovation performance.

This study constructs a new theory framework of multi-dimensional organizational innovation cultures along the four dimensions of knowledge sharing, organizational innovation atmosphere, team decision-making and organizational change. These factors together have rarely been examined before. Hence, the findings extend existing research on organizational cultures management. Moreover, a new idea for this study is that the authors consider team cohesion as a moderating variable between organizational innovation culture and innovation performance of firms, hence providing both theoretical discussion and empirical validation of the impact of team cohesion on this relationship. It thus extends existing research on the team theory.

Given that women around the world face more exclusion in terms of limited access to economic and innovation activities than men do, it is understandable that some female-led start-ups in weak institutional environments engage in bribery to help reduce the difficulties they encounter in the face of intense business competition. However, the link between bribery and product innovation performance is unclear. The purpose of this study is to investigate the relationship between bribery and product innovation performance for female-led start-ups, as well as the roles of institutional support and self-control in this link.

This empirical study evaluates survey data from female-led manufacturing start-ups in China's Yangtze River Delta region to investigate the relationship between bribery and product innovation performance.

This research shows that bribery has an inverted U-shaped impact on product innovation performance in female-led manufacturing start-ups, meaning that the product innovation performance of these firms initially increases but then decreases as the bribery intensity (i.e. the frequency and amount of bribes) increases. The authors also focus on the roles of institutional support and self-control in this link, where the authors find that this relationship is steeper for firms with strong institutional support, as well as for individual female entrepreneurs who have high levels of self-control.

The findings of this study indicate that policymakers should undertake efforts to improve institutional quality (e.g. increasing clarity around decisions, providing more institutional support, etc.) and to guide female entrepreneurs to cultivate higher levels of self-control, as such efforts would reduce the appeal of, and the opportunity for, bribery.

To date, very few studies focus specifically on female-led enterprises in the field of bribery research. The research findings presented here on the effect of bribery in female-led start-ups on firm product innovation performance are useful to researchers, policymakers and businesspeople, as they provide a better understanding of bribery in female-led start-ups in China, which can also be extrapolated to encompass other transition economy contexts.

Carbon trading mechanism has been adopted to foster the green transformation of the economy on a global scale, but its effectiveness for the power industry remains controversial. Given that energy-related greenhouse gas emissions account for most of all anthropogenic emissions, this paper aims to evaluate the effectiveness of this trading mechanism at the plant level to support relevant decision-making and mechanism design.

This paper constructs a novel spatiotemporal data set by matching satellite-based high-resolution (1 × 1 km) CO₂ and PM_2.5 emission data with accurate geolocation of power plants. It then applies a difference-in-differences model to analyse the impact of carbon trading mechanism on emission reduction for the power industry in China from 2007 to 2016.

Results suggest that the carbon trading mechanism induces 2.7% of CO₂ emission reduction and 6.7% of PM_2.5 emission reduction in power plants in pilot areas on average. However, the reduction effect is significant only in coal-fired power plants but not in gas-fired power plants. Besides, the reduction effect is significant for power plants operated with different technologies and is more pronounced for those with outdated production technology, indicating the strong potential for green development of backward power plants. The reduction effect is also more intense for power plants without affiliation relationships than those affiliated with particular manufacturers.

This paper identifies the causal relationship between the carbon trading mechanism and emission reduction in the power industry by providing an innovative methodology for identifying plant-level emissions based on high-resolution satellite data, which has been practically absent in previous studies. It serves as a reference for stakeholders involved in detailed policy formulation and execution, including policymakers, power plant managers and green investors.

As of December 2021, WeChat had more than 1.2 billion active users worldwide, making it the most active online social media in mainland China. The term social commerce is used to describe new online sales through a mix of social networks and/or peer-to-peer communication or marketing strategies in terms of allowing consumers to satisfy their shopping behaviour through online social media. Thus, given the numerous active users, the development of online social media and social commerce on WeChat is a critical issue of internet research.

This empirical study takes WeChat as the online social media research object. Questionnaires for WeChat users in China were designed and distributed. All items are designed as nominal and ordinal scales (not Likert scale). The obtained data was put into a relational database (N = 2,342), and different meaningful patterns and rules were examined through data mining analytics, including clustering analysis and association rules, to explore the role of WeChat in the development of online social media and social commerce.

Practical implications are presented according to the research findings of meaningful patterns and rules. In addition, alternatives to WeChat in terms of further development are also proposed according to the investigation findings of WeChat users’ behaviour and preferences in China.

This study concludes that online social media, such as WeChat, will be able to transcend the current development pattern of most online social media and make good use of investigating users’ behaviour and preferences, not only to stimulate the interaction of users in the social network, but also to create social commerce value in social sciences.

Based on the perspective of knowledge management capability, this paper aims to reveal the internal mechanism of the digital empowerment of mobile social platforms to improve the operational performance of Chinese traditional retail enterprises. Such improvements have crucial theoretical value and practical implications for Chinese traditional retail enterprises to achieve transformation and sustainable development.

This study applied the typical analysis method, selected China’s leading mobile social platform, WeChat, as a typical case, and observed and analyzed the public data of the traditional retail industry and social platforms and interviews with relevant enterprises. On this basis, this study used the inductive and deductive methods of qualitative research to conduct an in-depth analysis of the mechanism by which WeChat’s digital empowerment improves the operational performance of Chinese traditional retail enterprises. It also discussed the critical role and path knowledge management capabilities play in this mechanism.

This research demonstrated that mobile social platforms empower Chinese traditional retail enterprises to build diversified digital channels, enhance the knowledge acquisition capability of enterprises and thus improve their performance; empower Chinese traditional retail enterprises to build digital community networks, enhance the knowledge diffusion capability of enterprises and thus improve their performance; and empower Chinese traditional retail enterprises to integrate online and offline businesses, enhance the knowledge integration capability of enterprises and thus improve their performance.

This study clarifies the internal mechanism of how the digital empowerment of mobile social platforms can improve the performance of Chinese traditional retail enterprises. This mechanism implies that knowledge management capabilities (knowledge acquisition, diffusion and integration capability) are the underlying logic for Chinese traditional retail enterprises to achieve higher performance levels. This has important practical implications for managers of Chinese traditional retail enterprises to leverage the digital infrastructure of mobile social platforms to achieve the sustainable development of enterprises.

This study provides an in-depth analysis of how the traditional retail industry uses digital social platforms to improve operational performance from the perspective of knowledge management capabilities, which can further promote the theoretical research and practical development of digitalization and knowledge management. At the same time, this study explored the research on the operational performance of Chinese traditional retail enterprises from the perspective of knowledge management capabilities and expanded the research on knowledge management in related fields. The authors have initially sorted out the impact of knowledge management capabilities on the operational performance of Chinese traditional retail enterprises in the digital era. This will help better understand the role and function of knowledge management in strategic transformation and expand the application of knowledge management theory.

The authors seek to crack the model of new retail by outlining the unique business model known as community-based omni-channel and data-enabled ecosystem.

The study’s analyses of Hema cases and other examples reveal a new omni-channel model, a community-based and data-enabled ecosystem model.

The ecosystem targets local customers within a limited geographical range. It is also data-enabled and effectively leverages large-scale data on consumers, store operations, supply chains and logistics to ensure the smooth functioning of the ecosystem.

The authors hope the typology brings new insights to the development of omni-channel retail.

How to improve the resilience of service firms in the crisis, such as the COVID-19 epidemic, to maintain a sustainable competitive advantage becomes a growing concern worldwide. Digital platform capability (DPC) provides a series of opportunities and advantages for service firms to shape resilience in the crisis. This study aims to clarify the effect and mechanism of DPC on service firms’ resilience, and provides a new mediator (strategic learning [SL]), as well as two boundary conditions (legal inefficiency [LIE] and legal incompleteness [LIC]).

Questionnaires were used to obtain firm data, and executives answered these key questions. Data from 293 service firms during the COVID-19 period were used for hypothesis testing.

DPC was positively related to the adaptive capacity (AC) and planning capacity (PC) of service firms. SL mediated the positive effect of DPC on the AC and PC of service firms. The positive effect between DPC and SL was weakened when LIE and LIC were high.

This study suggests that it is a very desirable measure to improve DPC to gain organizational resilience (OR) in the crisis. In addition, a SL process in the crisis is crucial, because service firms need to absorb key strategic information from digital platforms to cope with uncertainty. The services firms need to realize that the benefits of DPC will be weakened in the dysfunctional institutional environment of LIE and LIC.

To the best of the authors’ knowledge, this study is the first to link the DPC with the resilience of service firms, and provides a new explanation mechanism and some boundary conditions for this important relationship. Furthermore, this study takes a step forward, because these efforts respond to the widespread call of the literature on digitalization and OR, and provide new insights for understanding digital resilience.

High-tech enterprises, as the national innovation powerhouses, have garnered considerable interest, particularly regarding their technological innovation capabilities. Nevertheless, prevalent research tends to spotlight the impact of individual factors on innovative behavior, with only a fraction adopting a comprehensive viewpoint, scrutinizing the causal amalgamations of precursor conditions influencing the overall innovation proficiency of high-tech enterprises.

This paper employs a hybrid approach integrating necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) to examine the combinatorial effects of antecedent factors on high-tech enterprises' innovation output. Our analysis draws upon data from 46 listed Chinese high-tech enterprises. To promote technological innovation within high-tech enterprises, we introduce a novel perspective that emphasizes technological innovation networks, grounded in a network agents-structure-environment framework. These antecedents are government subsidy, tax benefits, customer concentration, purchase concentration rate, market-oriented index and innovation environment.

The findings delineate four configurational pathways leading to high innovative output and three pathways resulting in low production.

This study thereby enriches the body of knowledge around technological innovation and provides actionable policy recommendations.

The purpose of this paper is to investigate the impact of fairness concern on the optimal pricing, carbon emission reduction (CER), green marketing efforts (GME) and utility of supply chain members in a two-echelon low-carbon supply chain composed of one manufacturer and one retailer. First, three basic models that consider the manufacturer’s different attitudes toward the retailer’s fairness concern are constructed. The optimal decisions of these models are obtained. Second, these optimal solutions are compared, and the effects of some key parameters including fairness concern on the optimal decisions and utility are examined for the three models. Furthermore, the manufacturer may misestimate the retailer’s fairness concern; therefore, an extended model is proposed.

The authors adopt the manufacturer-led Stackelberg game theoretic framework, where the manufacturer decides the wholesale price and CER level and, then, the retailer determines the retail price and GME.

The results show that fairness concern has a negative impact on the wholesale price, the level of CER and GME, and fairness concern are not always beneficial for maximizing utility, although it is related to whether the manufacturer pays attention to the retailer’s fairness concern. The manufacturer will gain more utility when considering the fairness concern of retailers than non-consideration. Overestimating or underestimating the fairness concern of the retailers does not lead to benefits for the manufacturer.

This study has the following two limitations that need to be addressed in future research. First, the authors only consider the fairness concern of a single retailer but not peer-induced fairness among multiple competing retailers, which can be taken into account in future studies. Second, the demand function is linearly related to price, CER and GME. Because of the uncertainty of market information, the uncertainty demand function can be further considered.

This paper simultaneously considers the factors CER, GME and fairness concern. The utility function of the retailer is established according to taking the Nash bargaining solution as a fairness reference point, and four different models are constructed and compared.