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.     

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.     

粤港澳大湾区制造业集聚与区域创新

以2009—2020年粤港澳大湾区11个城市为研究对象，探讨制造业集聚与区域创新的关系。研究发现，制造业集聚显著提高区域创新水平，可通过提高企业竞争这一路径实现。进一步分析发现，金融业集聚对区域创新发展具有显著的正向关系，金融产业和制造业产融协同集聚显著提高区域创新水平。研究结果表明，制造业集聚加剧产业内部企业创新竞争，带动区域创新发展，且金融业在创新中起到积极的推动作用。指出应鼓励区域企业创新竞争，优化营商环境，为产业融合发展提供保障。     

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.     

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.     

渠道合作情境下合同双元功能对主动和被动投机行为的影响差异研究

基于交易成本理论，在渠道合作情境下，以制造商的合同监督和企业间联合行动为工具测量合同治理的保障功能和协作功能，探讨二者对经销商主动投机行为和被动投机行为的影响差异。通过对512份问卷数据的统计分析，得到以下结论：第一，合同监督有助于抑制经销商的主动投机行为，但对其被动投机行为的影响不显著；第二，企业间联合行动有助于抑制经销商的被动投机行为，但对其主动投机行为的影响不显著；第三，经销商的主动投机行为和被动投机行为均会负向影响合作绩效；第四，经销商的主动投机行为中介合同监督对合作绩效的正向影响，被动投机行为中介企业间联合行动对合作绩效的正向影响。     

在热电联产企业中精益成本管理的评价指标及应用对策

论文从热电联产企业的特征入手,通过对精益成本管理理论的研究,总结出热电联产企业精益成本管理的评价指标,并通过对指标的分析总结出精益成本管理在热电联产企业实际应用中的管理对策。     

德国零售巨头阿尔迪经营战略分析

随着经济全球化的发展,科学技术日新月异,人们的消费结构和消费习惯也在不断地改变,传统的零售业面临着巨大的挑战,但德国阿尔迪依旧在当下保持着零售巨头的称号。论文对德国零售巨头阿尔迪的经营战略进行分析,并结合阿尔迪的经营策略为中国零售业提出建议和启示。     

大学生消费行为调查与分析

大学生是社会消费群体的重要组成部分,他们的消费行为特征受到越来越多人的关注。为了更好地了解大学生的具体消费行为,本文采取问卷调查的方式,以合肥师范学院在校大学生作为调查对象,进一步了解大学生的消费理念、方式以及水平、结构等。最后根据调查结果的数据分析,对大学生理性消费提出具体建议,以引导大学生树立正确的消费观念。