When push comes to shove: How coach versus student athlete misconduct affects event attendance intentions

Though onand off-the-field misconduct is common among U.S. college athletic programs, little is known regarding the ramifications that may result. Drawing on social learning theory, the current research suggests consumers intentions (e.g., likelihood of attending a game) differ depending on violator's team role. Across one qualitative and five experimental studies, we demonstrate that consumers' intentions are influenced by violator's team role, such that likelihood of attending a game is lower when a coach (vs. student athlete) misbehaves, an effect driven by evaluation of the academic institution. This effect is robust across both winning and losing records and moderated by perceived fairness of the university's actions toward the violator.     

On linking the perceived values of mobile shopping apps,customer well-being,and customer citizenship behavior: Moderating role of customer intimacy

Marketing studies that seek to determine the drivers of Customer Citizenship Behavior (CCB) are still relatively rare, especially for its multi-faceted relationship with perceived values in the context of online transactions. This study seeks to bridge this research gap by exploring the relationship between the perceived values of mobile shopping applications (MSApps) and CCB through perceived well-being based upon the social exchange theory. This study also makes another original contribution by investigating the moderating role of customer intimacy. A quantitative approach was adopted by collecting data through a web survey and then applying structural equation modelling, as well as cluster and multigroup analyses to test the proposed hypotheses. Perceived values were found to influence consumer well-being, thus predicting CCB, with consumer intimacy playing a significant moderating role in this relationship. This study is one of a few seeking to verify the drivers of CCB for MSApps, and it is the first of its kind to investigate consumer intimacy as a moderating factor. The findings will prove useful to providers of MSApps and retailers.     

The impact of adopting customization policy and sustainability for improving consumer service in a dual-channel retailing

In recent decades sustainability and dual-route retailing have been adopted by many big industries. Companies are now bound to maintain such strategies that fulfill the sustainable goals developed by the United Nations. Industries face a huge penalty if carbon emissions exceed a certain boundary. Moreover, factories should maintain sufficient flow in retail chains and product quality. This paper demonstrates 3-pillar sustainability in dual channel retailing, empowering firms to integrate the financial-economic pillar with the non-financial (environmental, social, and ethical) pillar. The core product is made available through the traditional channel and customized products are through online channels. The model is enabling the customers with customization provisions where they can influence the products. Thus, as a novel approach, the article incorporates a presumed threshold limit on the product's (standard and customized) selling price difference. Due to customization, a new product is developed which needs extensive quality checks. The study introduces an investment in checking the quality of the customized product which reduces the probability of customization defects exponentially. Additionally, current research adapts the carbon emission cost, penalties charged to a firm for overshooting the limit, and social costs in a smart supply chain. It also exemplifies that production is directly proportional to financial investments in meeting sustainability objectives. The numerical analysis reflects that as production increases, penalty costs decrease at a significant rate but after reaching optimal production penalty cost again starts to increase. It is observed that the downfall of penalty is 20% more for the single-channel than dual. Adaptation of the customization policy makes the retailing strategy more cost-effective. The model exemplifies that it is more economical to adopt dual-channel retailing compared to single-channel as there is approximately a 14.0625% reduction in total cost in dual-channel retailing. Moreover, an 80% improved quality is observed with a financial investment, which improves consumer satisfaction.     

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.     

A comparative study of eight COVID-19 protective measures and their impact on Swiss tourists’ travel intentions

A comparative vignette-based experimental survey design incorporating various socio-psychological factors, linked to the Theory of Planned Behavior (TPB), the Health Belief Model (HBM) and the Domain-Specific Risk-Taking scale (DOSPERT) was carried out to test variations in eight travel-related COVID-19 protective measures on Swiss tourists’ travel intentions. Among the tested measures, vaccination passports, surgical masks and quarantining are those that stand out the most, with surgical masks having the greatest acceptance and willingness to adopt while traveling. Quarantining, on the other hand, appears to have a deterrent influence on travel intentions, and vaccination passports have the lowest perceived barriers during travel, but the highest perceived benefits in mitigating the spread of the infection. The discussion of individual differences has specific implications for tourism management against the background of our empirical findings.     

智慧居家养老服务协同供给的优化路径研究——以广西钦州市智慧居家养老项目的实践经验为例

智慧居家养老服务的协同供给可以形成社会联动效应，降低公共服务成本。运用公共服务协同供给分析框架，通过交叉分类方法从协同主体的利益与目标两个变量的耦合性出发分析广西钦州市智慧居家养老项目中养老服务主体间不同种类的协同关系，可以从加强政府领导、形成合作联盟、建立市场标准、创新扶持政策4个方面完善政府、企业、社会组织之间不同类型的协同供给，实现社会资源的高效利用以及向智慧居家养老服务的发展和转变。     

Addressing plastic pollution through green consumption: Predicting intentions to use menstrual cups in the Philippines

Plastic pollution is a global environmental crisis that poses a huge threat to the health of people and marine ecosystems worldwide. A significant source of plastic pollution is menstrual hygiene management, and an approach that can help address this crisis is the usage of washable and reusable menstrual cups. Using an extended theory of planned behavior model that includes self-identity and perceived quality, the study predicted intentions to use menstrual cups in the Philippines. Structural equation modeling results showed that perceived quality predicted attitudes towards menstrual cup usage. Moreover, attitudes, perceived behavioral control, and self-identity predicted intentions to use menstrual cups. There were also some differences in the factors and predictors of intentions between non-users and regular users of menstrual cups. Among regular users, perceived behavioral control did not predict intentions. These findings provide empirical support for the extended model, and provides insights for governments, non-government organizations, and corporations in promoting the usage of menstrual cups to address the global plastic pollution crisis.     

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.     

基于区块链技术的建筑材料供应链质量数据安全共享方法

传统方法在建筑材料供应链质量数据安全共享中应用效果不佳，不仅数据误码率比较高，而且数据共享时延比较长，无法达到预期的数据安全共享效果。为此提出基于区块链技术的建筑材料供应链质量数据安全共享方法。利用区块链技术对建筑材料供应链质量数据属性加密，建立建筑材料供应链质量数据安全共享链，整合建筑材料供应链质量数据加密、解密程序，通过对用户身份验证实现对质量数据安全共享，以此完成基于区块链技术的建筑材料供应链质量数据安全共享。实验证明，设计方法的数据误码率在1%以内，数据共享时延在1s以内，具有良好的数据安全共享效果。     

基于SD模型的装配式建筑供应链脆弱性研究

装配式建筑供应链的运作存在很多不确定性。为提高供应链管理效率，促进建筑业的发展，运用供应链运作参考(SCOR)模型对装配式建筑供应链脆弱因子进行识别，将装配式供应链系统划分为6个子系统；通过系统动力学（SD）模型对供应链脆弱性进行仿真。结果表明，装配制造流程是脆弱性最大的子系统，整个供应链的脆弱性随着建筑项目的推进而增大。