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.     

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.     

Market impact: a systematic study of the high frequency options market

This paper deals with a fundamental subject that has seldom been addressed in recent years, that of market impact in the options market. Our analysis is based on a proprietary database of metaorders—large orders that are split into smaller pieces before being sent to the market—on one of the main Asian markets. In line with our previous work on the equity market [Said, E., Bel Hadj Ayed, A., Husson, A. and Abergel, F., Market impact: A systematic study of limit orders. Mark. Microstruct. Liq., 2018, 3(3&4), 1850008.], we propose an algorithmic approach to identify metaorders, based on some implied volatility parameters, the at the money forward volatility and at the money forward skew. In both cases, we obtain results similar to the now well-understood equity market: Square-Root Law, Fair Pricing Condition and Market Impact Dynamics.     

新农科建设背景下江西高校涉农专业人才培养的思考

新农科建设是新农业新乡村新农民新生态建设的必然要求,顺应了新时代社会的发展规律,致力于培养爱农业、懂技术、善经营的高水平实用技能型卓越农林新人才。"新农科"建设宣言的提出对高等院校涉农专业人才的培养提出了更高的期许和要求。目前江西高校存在涉农专业人才数量紧缺且离农化趋势严重,涉农专业精品课程少、设置不够合理,涉农专业人才培养结构与行业需求脱轨,科研成果转化率不高的问题。本文从新农科建设的角度出发,针对江西高校在涉农专业人才培养过程中出现的问题提出了相应的对策。     

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。     

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。     

The effect of mobile application-driven customer participation on bakery purchase behavior: Evidence from a field experiment

This paper empirically examines individual and joint effects of two types of customer participation (CP)—mandatory and replaceable—within a mobile app on bakery purchase behavior. This research conducts a field experiment to track customer decisions on whether to participate in in-app CP events—store loyalty program enrollment and store satisfaction survey—and whether to change their purchasing amount and frequency. After controlling other influencing factors, the authors performed ANOVA with the sample of 19,065 bakery customers’ behavioral decisions. The results confirm that mandatory CP has a positive effect on purchase behavior, while replaceable CP has mixed effects across stores. In addition, the results confirm that customers who engaged in both types of CP increased their purchase amount and frequency, compared to customers who engaged in one type or neither. The study suggests hospitality firms should motivate customers to engage in mandatory and replaceable CP to enhance customer loyalty cost-effectively.