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1.
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. 相似文献
2.
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. 相似文献
3.
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. 相似文献
4.
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. 相似文献
5.
为实现对多科性医院大数据治理水平的分析和评估,在数据管理成熟度模型和能力成熟度模型基础上,构建多科性医院大数据治理能力成熟度评价模型。将医院大数据治理能力成熟度分为初始级、程序级、规范级、管理级和优化级五个等级,基于医院内部大数据治理特征,建立包括三级指标的成熟度评价指标体系。然后,分别用客观赋权法及组合赋权法确定各指标权重,并结合未确知测度理论和评价方法,量化评估两个三甲多科性医院大数据治理能力的成熟度。结果表明,两种赋权方法下两家医院的大数据治理能力水平均处于规范级,与两家医院大数据治理的实际情况相吻合。未确知测度理论与信息熵权相结合,可以平衡指标测量主观性和评价结果稳定性,建立的模型能为多科性医院大数据治理提供具有参考价值的决策信息。 相似文献
6.
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. 相似文献
7.
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。 相似文献
8.
9.
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. 相似文献
10.
游客旅游行为失范时有发生,威胁着旅游资源与环境安全。心理归因影响个体行为逻辑,归因偏差是解释心理归因的经典理论。本文引入归因偏差理论,采用实证方法探究旅游行为失范背后的归因偏差因素,为减少旅游行为失范提供心理学依据。研究发现,归因偏差能够引致旅游者心理认知偏差,后者直接引发和助推旅游行为失范。心理环境和群体心理对引致旅游者的心理认知偏差和行为失范具有显著作用,归因偏差成为旅游者弱化旅游行为失范结果的心理屏障,可激发或促进旅游行为失范的发生或持续。研究认为旅游地可从完善硬件监控、控制游客流量、强化失范行为负面教育、发挥在场监督作用等方式削弱归因偏差效应。 相似文献