资源约束下的创业导向、资源行动策略与企业成长

资源约束背景下，如何制定有效的创业导向及资源行动策略对动态环境中企业成长具有重要意义。基于动态能力视角，以恒瑞医药为例，探讨其不同发展阶段创业导向、资源行动策略与企业成长间的内在作用机理。结果发现：①高差异性和高合法性是企业资源行动所追求的理想状态，但在不同发展阶段二者的侧重点不同；②创业导向为企业资源行动策略提供方向，而资源行动策略则是创业导向得以实施的保障，二者相互契合，共同促进企业成长；③多重资源约束是企业创业导向和资源行动的直接动因，而企业能力提升是创业导向和资源行动产生的有效结果，该过程中管理者认知为企业资源环境分析、创业导向制定以及资源行动选择提供有力保障。     

Mitigating panic buying behavior in the epidemic: An evolutionary game perspective

The panic buying behavior under public health emergencies will lead to many adverse consequences, such as material waste, price fluctuation and uneven distribution of epidemic prevention materials, which will pose a threat to the social stability and economic development. In this paper, we construct a tripartite game model to explore the strategic choices of the public, merchants and the government in order to effectively respond to the panic buying behavior in the epidemic. The results demonstrate that: (1) Eight evolutionary stable strategies emerge in the panic buying events. The worst scenario can be improved by adjusting some relevant parameters. (2) The probability of the public choosing the strategy of “not involving in panic buying” depends on the potential benefits and losses of snapping up, rather than the extent of price rising. (3) The probability of merchants choosing the strategy of “not bid up price” depends on the intangible benefits. (4) The probability of the government choosing the strategy of “active supervision” depends on the supervision costs and government credibility, rather than the amount of fines. In addition, strategic suggestions to mitigate panic buying behavior are put forward from the perspective of each stakeholder.     

Organizational CQ: Cultural intelligence for 21st-century organizations

We live in an age of massive global disruption. Technological advancements threaten century-old business models, globalization is reordering supply chains, and people need to work with colleagues and customers who have vastly different backgrounds. On top of that, we have been in the midst of a global pandemic, and customers, employers, and investors are demanding more than just a Black Lives Matter social media post from organizations that purport to take social justice seriously. Organizations with high cultural intelligence (CQ) are able to navigate this volatility and complexity effectively. Over the last two decades, scholars from across the world have published hundreds of articles on CQ, the capability to relate and work effectively in complex, culturally diverse situations. Most of the work has examined CQ at the individual level. But what about organizations? Can organizations be culturally intelligent? The emerging research on CQ at the organizational level offers leaders and organizations critical insights for navigating today’s diverse, digital world. Organizational CQ is a firm’s capability to function effectively in a complex and unpredictable multicultural world. This article stresses the importance of the culturally intelligent organization and explains how to develop organizational CQ.     

Green consumption behavior prediction based on fan-shaped search mechanism fruit fly algorithm optimized neural network

Predicting consumption behavior is very important for adjusting supplier production plans and enterprise marketing activities. Conventional statistical methods are unable to accurately predict green consumption behavior because it is characterized by multivariate nonlinear interactions. The paper proposes an optimized fruit fly algorithm (FOA) and extreme learning machine (ELM) model for consumption behavior prediction. First, to address the problem of uneven search direction of FOA leading to insufficient search ability and low efficiency, the paper proposes a sector search mechanism instead of a random search mechanism to improve the global search ability and convergence speed of FOA. Second, to address the issue that the initial weights and hidden layer bias values of the ELM are randomly generated, which affects the learning efficiency and generalization of the ELM, the paper uses an improved FOA to optimize the weights and bias values of ELM for improving the prediction accuracy. Taking the green vegetable consumption behavior of Beijing residents as an example, the results show the optimization of the initial weight and threshold of ELM by the GA, PSO, FOA, and SFOA, the prediction accuracy of the GA-ELM, PSO-ELM, FOA-ELM, and SFOA-ELM models all surpass those of ELM. Compared with BPNN, GRNN, ELM, GA-ELM, PSO-ELM, and FOA-ELM models, the RMSE value of SFOA-ELM was decreased by 9.45%, 8.40%, 11.89%, 5.84%, 2.22%, and 2.69%, respectively. These findings demonstrate the effectiveness of the SFOA-ELM model in green consumption behavior prediction and provide new ideas for the accurate prediction of consumption behaviors of other green products with similar characteristics.     

Effects of augmented reality technology characteristics on customer citizenship behavior

In recent years, augmented reality (AR) technology has received considerable attention from academics and practitioners. Although AR technology has a bright side, its dark side has been relatively overlooked. Therefore, this study aimed to investigate the effects of AR technology characteristics on customer citizenship behavior via two conflicting mechanisms: customer immersion and customer fatigue. The study also explored the boundary conditions of customer experience. A total of 247 questionnaires were collected from customers who had prior experience of using IKEA's AR mobile shopping application. A structured model was analyzed using SmartPLS 3 and PROCESS Macro for mediation and moderated mediation effects. The study enriches the current knowledge on AR technology by demonstrating that AR technology can lead to customer citizenship behavior in relation to a brand's AR technology. Interestingly, customer immersion was found to positively mediate the relationship, but customer fatigue was found to negatively mediate it. Furthermore, customer experience was found to strengthen the positive mediation effect of customer immersion and weaken the negative mediation effect of customer fatigue.     

Depletion of psychological,financial, and social resources in the hospitality sector during the pandemic

This study details how psychological, financial, and social factors shape employee deviant interpersonal behaviors during a pandemic. Data were collected with a survey of 372 front-line employees of hotels and analyzed with PLS-SEM. The findings showed social disconnectedness and perceived risk of unemployment leads to perceived isolation, which further creates depression in employees. The findings also showed that depression is positively related to employee deviance. Financial strain is a major cause of perceived isolation, depression, and deviant behaviors among front-line employees. Results also proved that social support reduces fear of isolation, depression, and employee deviance. This study provides guidelines that hotels need to understand the psychological stance of employees and design policies to overcome employee perceived fears and psychological disorders.     

组织信息化环境下知识流动对组织创造力的影响

通过解析知识流动和组织信息化环境的内部构成，探究知识溢出/知识扩散、高管支持/ICT应用对组织创造力的差异性影响，以及不同组织信息化环境对知识流动与组织创造力关系的调节作用。利用信息化程度较高的企业数据，使用层级回归分析进行实证检验。结果表明：组织创造力受知识流动的正向影响，知识扩散对其的正向影响更强；组织信息化正向影响组织创造力，相比ICT应用，高管支持对组织创造力的正向影响更强；高管支持在知识溢出/知识扩散与组织创造力之间的正向调节作用显著；ICT应用对知识扩散与组织创造力的强化作用显著强于对知识溢出与组织创造力之间的调节作用。     

Does china income FSDs follow Benford? A comparison between Chinese income first significant digit distribution with Benford distribution

Since Benford’s law is an empirical phenomenon that occurs in a range of data sets, this raises the question as to whether or not the same thing might be true in terms of the Chinese income distribution data. We focus on the first significant digit (FSD) distribution of Chinese micro income data from the 2005 Inter-Census sample, which corresponds to 1% of Chinese population and other micro income data from the China family panel studies (CFPS) and Chinese General Social Survey (CGSS). We use information theoretic-entropy based methods to investigate the degree to which Benford’s FSD law is consistent with the FSD of Chinese income data and our findings suggest consistency between the Chinese FSD income distribution and Benford’s distribution. The close connection between the two distributions has implications for the quality of the sample of Chinese micro data.     

网络强度、组织冗余与创新模式——对200家样本企业问卷调研数据的实证检验

通过社会网络带来资源冗余进而对创新选择产生影响，这一机制已成为当今企业可持续发展的重要路径。运用200份企业样本调研数据，对网络强度、不同类型组织冗余及两种创新模式进行实证检验，结果发现，网络强度显著正向直接影响利用式创新和探索式创新;网络强度还通过正向影响未吸收冗余对两种创新产生正向间接影响作用;未吸收冗余与创新模式间具有显著正向影响关系,而吸收冗余在三者影响路径关系中检验结果不显著，可能是受企业自身因素或条件影响所致。最后，根据研究结论提出3点重要管理启示。