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Drawing on self-determination theory (Deci and Ryan, 2012) and Hew’s (2016) five-factor model, our study aimed to investigate the impact of two online training design factors (instructor accessibility and active learning) on learner’s self-efficacy and learning outcome amid the COVID-19 pandemic.

A randomized pretest-posttest control group field experiment was designed to assess participants’ self-efficacy and learning outcome of an online training program - territory business management plan, under three conditions: instructor accessibility, active learning, and controlled. Participants (N=87) were medical sales representatives from a Fortune-Global 500 pharmaceutical company’s subsidiary office in China. Data was analyzed with 2 (time) x 3 (group) MANOVA with time (pretest and posttest) as a repeated measure to investigate differences in changes in self-efficacy and learning outcome between three groups.

Overall, participants’ self-efficacy and learning outcome were significantly improved via the online training program for all three groups. Specifically, the impact of the training on learning outcome was the strongest for the active learning group, less strong for the instructor accessibility group, and the least strong for the control group.

Our research contributes towards understandings of the effectiveness of online talent training programs by examining two critical instructional design factors during a time of crisis. Our findings suggest that active learning (interactions with the training materials by purposeful self-reflection) might be a stronger predictor for increasing learning outcome than instructor accessibility (receiving feedback and tutoring sessions from the instructor) for online training programs.

This study aims to clarify influencing factors of overcapacity of new energy enterprises in China and accurately predict whether these enterprises have overcapacity.

Based on relevant data including the experience and evidence from the capital market in China, the research establishes a generic univariate selection-comparative machine learning model to study relevant factors that affect overcapacity of new energy enterprises from five dimensions. These include the governmental intervention, market demand, corporate finance, corporate governance and corporate decision. Moreover, the bridging approach is used to strengthen findings from quantitative studies via the results from qualitative studies.

The authors' results show that the overcapacity of new energy enterprises in China is brought out by the combined effect of governmental intervention corporate governance and corporate decision. Governmental interventions increase the overcapacity risk of new energy enterprises mainly by distorting investment behaviors of enterprises. Corporate decision and corporate governance factors affect the overcapacity mainly by regulating the degree of overconfidence of the management team and the agency cost. Among the eight comparable integrated models, generic univariate selection-bagging exhibits the optimal comprehensive generalization performance and its area under the receiver operating characteristic curve Area under curve (AUC) accuracy precision and recall are 0.719, 0.960, 0.975 and 0.983, respectively.

The proposed integrated model analyzes causes and predicts presence of overcapacity of new energy enterprises to help governments to formulate appropriate strategies to deal with overcapacity and new energy enterprises to optimize resource allocation. Ten main features which affect the overcapacity of new energy enterprises in China are identified through generic univariate selection model. Through the bridging approach, the impact of the main features on the overcapacity of new energy enterprises and the mechanism of the influence are analyzed.

The purpose of this study is to empirically explore how firms configure centrifugal and centripetal forces in promoting breakthrough innovation (BI), thus improving their strategic performance (SP) in the artificial intelligence (AI) context.

This study applies the centrifugal and centripetal forces model to a survey sample of 285 Chinese AI firms. Fuzzy-set qualitative comparative analysis (fsQCA) and propensity score matching (PSM) are integrated to explore the configurational effects of three centrifugal forces—the autonomy of technical experts, knowledge search and alliance network—and two centripetal forces—strictness of organisational institutions (SOI) and human–human–AI collaboration (HHAC)—on BI, examining whether the configurations that enhance BI can further improve SP.

The results indicate that the strictness of innovation institutions (SII) and strictness of ethical institutions (SEI) are equally important for determining SOI. Three configurations can improve BI when SOI and HHAC are the core conditions; only one of three configurations can further improve SP significantly.

By introducing SOI composed of equally important levels of SII and SEI and HHAC, this research is one of the few empirical studies to explore the mechanisms behind the impact of centrifugal and centripetal forces on BI and SP, which may help researchers and managers address innovation challenges in the AI context.

In the Western world, Carl Jung was the first to posit a theory of synchronicity to explain the startling divinatory power of the I Ching. Yet long before his time and unbeknownst to the West, the Chinese had already institutionalized as their tradition, simple practices for enabling decisions grounded on the synchronous concept. The purpose of this paper is to explain the process from within the context of Chinese Buddhist spirituality.

The approach here is to provide the background of Han Chinese Buddhism in modern China and within it, the wide practices of Kuan Yin spirituality and introducing the tools that the Chinese devised for consulting the Goddess of Mercy, as Kuan Yin is otherwise known. Then a discussion is made, for the first time, of the underlying mechanics as well as the mind and energy aspects. Having so introduced the religious background, spirituality, tools and mechanics, the processes of temple consultations for decisions are then explained. In the discussion, a framework for classifying decisions is outlined along with probability concepts. There is also the requirement for the inquirer to seek a metaphorical interpretation of the poetic imagery as contained in the Qian (a slip of paper).

Through writing this paper, the author wishes readers, both managerial and those in research, to understand what is still the approach (even more widely in China now than before) in how the Chinese – in and outside of China – approach the task of making major, complex decisions. These practices which date from antiquity clearly suggest the Chinese had gone beyond Jungian synchronicity in translating the theory into practice for decision making. In other words, they had long recognized the need for tools, techniques and approaches to help them make complex, difficult decisions: decisions that often go beyond the rational boundaries of the mind.

With the rising impact of the Chinese on the global economy and society, there is clearly a need for works that explain major Chinese processes such as the making of decisions. The art of decision making by the Chinese on the basis of what Jung theorized as synchronicity should become much better understood by researchers and managers.

There are very few academic papers exploring the process of Kuan Yin consultation in decision making by the Chinese. Yet this can be seen across many temples in everyday China and overseas Chinese communities as well as in Japan, Korea and Vietnam. The understanding of such processes is necessary for anyone, who wishes to grasp the minds of the Chinese as regards the process involved in the making of major decisions.

The authors study the effectiveness of the anti-corruption campaign in all of mainland China's provinces in terms of risk and volatility spillovers.

A nonlinear model describes interdependencies and determines how shocks and uncertainty spillovers from the first suspects to the rest of the country are dynamically transmitted.

The authors find that both idiosyncratic and systematic risk increase after the first investigation, suggesting that investors do react to the political shocks induced by the new policy. However, even if the scope of the inquiry expands, as the current policy is almost certain to be maintained, investors do not need to update their beliefs, stock news about their political costs does not matter and shocks cease to spread.

In this paper, the authors contribute to the literature by examining the financial effects of China's anti-corruption campaign and determining whether such a large-scale campaign affects risk. Qian and Wen (2015) and Ke et al. (2016) show that the anticorruption campaign has a negative impact on the consumption of luxury goods. Agarwal et al. (2020) provide evidence that government officials' access to credit decreases following the anti-corruption campaign. According to Zhang (2018), firms are less prone to commit fraud after the anti-corruption campaign. However, Griffin et al. (2018) find little evidence that the anti-corruption campaign reduces corporate corruption. Kim et al. (2018) assess market reaction during the investigation and discover that the anti-corruption examination has a significant positive influence on Chinese financial markets. The authors intend to fill the gap in the literature concerning the campaign's impact on risk and volatility spillovers across the country during the first stage of the campaign.

This paper aims to investigate the effect of intellectual capital (IC) on the operating efficiency of non-life insurance firms in China.

The authors use a dynamic data envelopment analysis model called dynamic slacks-based measure (DSBM) model to estimate the operating efficiency of 32 Chinese non-life insurance firms. Using a panel data set for the period from 2006 to 2010, the authors run ordinary least squares (OLS) regressions to find the relationship between IC and efficiency performance.

The authors find that the insurers have almost monotonically decreasing efficiency for the period from 2006 to 2010. Regression results show that human capital, structural capital and relational capital are significantly and positively related to operating efficiency.

This study suggests that managers of the Chinese non-life insurers should devote attention to the investments in IC to stay sustainable.

This is the first paper to examine the impact of IC on operating efficiency in the Chinese non-life insurance industry. This study differs from prior studies in that the authors use the DSBM model proposed by Tone and Tsutsui (2010) for evaluating the operating efficiency using a dynamic process.

The purpose of this paper is to explore the means for enhancing the image and business legitimacy of a socially discredited industry – pawnbroking in pre-1949 China – are explored. Previous studies suggest companies operating within such industries cannot solely rely on hard marketing strategies “to maximize sales and profits as they do with soaps and shoes” (Davidson, 2003, p. 7). Instead, they must find soft strategies for improving company and industry image and legitimacy.

This research relies on qualitative analysis of historical data and documents.

Soft strategies deployed by Chinese pawnbrokers – such as interpretations, moral value advocacies and institutionalized arrangements – contributed substantially to improving pawnbroking’s image and business legitimacy.

Interconnections among ethical values, image, business legitimacy and select marketing strategies are clarified. The efficacy of historically analyzing previously implemented business strategies and their embedding contexts is discussed.

Strategies Chinese pawnbrokers used to mitigate their previously negative image and boost their business legitimacy suggest strategies current socially disapproved companies can use to improve their image and business legitimacy.

A historical analysis of pre-1949 Chinese pawnbroking can suggest soft marketing strategies for overcoming consumers’ negative company and industry impressions.

The purpose of this study is to explore and prioritize the factors that determine the social insurance contribution of unorganized workers.

A two-stage procedure was adopted to recognize and prioritize factors influencing the social insurance participation of unorganized workers: first, crucial factors influencing unorganized workers’ contribution towards social insurance were identified by employing exploratory factor analysis, and in the second phase, the fuzzy analytical hierarchal process was applied to rank the specified criteria and then sub-criteria by assigning weights.

Four broad factors were identified, namely, economic, political, operational and socio-psychological, that significantly influence unorganized workers’ contribution towards social insurance. Later findings revealed that the prime influencer of unorganized workers’ contribution is employment contracts followed by average earnings, delivery of quality services, eligibility and accessibility.

The research findings are feasible as the basic propositions are based on real-world scenario. The identification and ranking of factors have the potential to be used as a checklist for policymakers when designing pension and social insurance for unorganized workers. If it is not possible to consider all, the criteria and sub-criteria assigned upper rank can be given priority to extend pension coverage for a large group of working poor.

The key factors driving social insurance contributions have been highlighted by studying the stakeholders’ perceptions at a micro level. By comprehending the challenges, there is a possibility of covering a large section of the working poor into social insurance coverage.

This paper is believed to be one of its kinds to acknowledge a combination of factors that determine the contribution of unorganized workers to social insurance. This study is an empirical investigation to prioritize the essential drivers of social insurance participation by low-income cohorts in the context of emerging countries. The present approach of employing fuzzy logic has also very limited use in social insurance literature yet.

This exploratory study investigates how mentoring is perceived and undertaken by the concerned parties, namely, mentor and protégé, and organizations in the context of Thailand.

A qualitative approach using dyadic case studies (of manager and subordinates) was taken to reflect whether mentoring is formally established in Thai business organizations, what benefits are experienced by mentors and mentees (protégés) and how the Thai business organizations can fully benefit from mentoring system. Based on the sample case studies, it is found that mentoring is perceived as teaching and advising how to perform a job well and mainly by one's supervisor. Factors that influence the effectiveness of mentoring system include clear organizational policies, HRM practices (i.e. orientation, training and development, performance appraisal, rewards, etc.), mentoring evaluation, trust and integrity and perceived risk.

This study aims to examine how Chinese rural-urban migrant workers' socio-economic status was associated with their decent work.

Grounded in the psychology of working theory (PWT), this study tested the path from rural-urban migrant workers' socio-economic status to decent work via work volition, with this path moderated by environmental uncertainty and trade union support. 470 rural-urban migrant workers from four manufacturing enterprises were investigated.

Results indicated that rural-urban migrant workers' socio-economic status was positively associated with rural-urban migrant workers' decent work through work volition. In addition, environmental uncertainty weakened the impact of socio-economic status on work volition while trade union support strengthened the relationship between socio-economic status and work volition.

The study contributes to the growing research on the PWT by testing its utility among rural-urban migrant workers in the Chinese context. The study also identifies the crucial effects of environmental uncertainty and trade union support, which are distinctive characters of contemporary China, in the formation process of rural-urban migrant workers' decent work. A detailed explanation of the results and implications is discussed in the end.