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.     

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.     

Website quality and users' intention to use digital libraries: Examining users’ attitudes,online co-creation experiences,and eWOM

This research aims to examine how the website quality affects the intention of digital library users to use the website by considering factors of user's attitudes, online co-creation experiences, and electronic word-of-mouth. The statistical population of the research is composed of the users of Astan Qods Razavi digital library, which is one of the oldest digital libraries in Iran. Data was collected from 402 participants who use the library and analyzed in SPSS and PLS softwares. Construct validity was assessed and confirmed using convergent validity and divergent validity. Data reliability was assessed and confirmed using Cronbach's alpha and composite reliability. The research confirms that website quality affects the attitudes of users towards the website and their intention to participate in online co-creation and eWOM. The effects of user's attitudes to the online co-creation experience, eWOM, and intention to use the library, as well as the effects of the online co-creation experience and eWOM on the intention to use the digital library were also confirmed. Considering the results of the research, it is recommended to digital libraries to provide an efficient user-friendly website designed to increase user participation and establish close contact with them and in this way increase their intention to use digital library services.     

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.     

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.     

Factors influencing buying behavior of Lebanese consumers towards fashion brands during economic crisis: A qualitative study

The purpose of this article is to contribute to an understanding of the impact of the Lebanese economic crisis on fashion buying behavior. It uses a qualitative approach by conducting semi-structured interviews with 29 Lebanese consumers. The study reveals that consumer fashion purchases are motivated by emotional, social, and functional drivers. It also indicates that subjective norms, such as societal and cultural values dictate buying behaviors. The findings provide further insights into social media and highlight its influence on shaping trends and making fashion products desirable. The article concludes that Lebanese consumers exhibit impulsive buying behavior, and explains how fashion brands can remain relevant amidst a wrenching economic crisis.     

中国农药施用与农业经济增长脱钩状态：时空特征与影响因素

[目的]明确农药施用与农业经济增长关联状态及其影响因素,为实现"控药减害增收"的目标提供借鉴。[方法]基于2005—2015年数据利用脱钩理论和对数平均分解指数法分解进行分析。[结果]中国农业经济增长伴生大量农药施用,仅少数省域表现出农药施用和农业经济增长扩张绝对脱钩的理想状态,东北西北部分省域农业经济增长则以更大幅度的农药投入增长为代价。中西部地区劳动力规模和技术进步效应是推动农药施用与农业经济增长脱钩的因素;东部地区种植规模变化、劳动力规模和技术进步因素均是推动农药施用和农业经济增长脱钩的因素;东北地区仅劳动力规模效应成为推动脱钩的力量。[结论]推动农药施用与农业经济增长脱钩需要强化农业科技的创新与普及,完善农业生产过程中的技术支撑,推动农业病虫害监测预警,加大对环境友好型低污染农药和肥料的推广度;构建农户施药的多重约束机制,完善农业病虫灾害保险减少农户对生产过程的风险感知,发挥农业合作社对农户施药行为的规制作用,完善产品分级认证和安全准入制度;通过农地合理流转和农业机械化等方式集约利用农业生产资源;因地制宜推动农药施用与农业经济增长脱钩,结合区域资源优势和农业发展阶段有针对性地设计对策措施。