Adverse effect of social media on generation Z user's behavior: Government information support as a moderating variable

Social media emerged as a primary source of information among young users, but its severe effect on mental state due to information overload, still an area of concern for the researchers. Generation Z users' addiction to the mobile phone/gadgets is increasing with a rise in social media and consequently their behavioral outcomes have transformed completely. Nowadays behavioral issues including stress, fatigue, ‘fear of missing out’ and ‘phubbing’, anxiety etc. rising each day but the relationship among these issues and information overload is less examined. The social media users are unable to filter the trustworthy information due to its enormous size and thus role of information support from government becomes essential. The current study extends the S-O-R theory exploring relationship between the stimulus of enormous information on the responses generated among the Generation Z such as social media fatigue, ‘fear of missing out’, ‘phubbing’ and anxiety. The findings from a sample of 319 users belonging to Generation Z suggest that social media platforms need to understand user's compulsive usage that is resulting into fatigue and consequently anxiety. The role of government information support on reducing fatigue and anxiety is found to be positive. The relationship between ‘fear of missing out’, ‘phubbing’ and anxiety is found significant and shows presence of partial mediation. The study offers significant theoretical and practical implications. It is significant for the service providers and social media platforms to advance interfaces with minimum fatigue for the users and offers information support to the users to reduce stress caused by information load.     

Becoming a tree when I will be dead? Why not! Generation X,Y and Z,and innovative green death practices

Within the theoretical field of ethical consumption, the study focuses on consumer behavior and innovative green death practices. While scarcely investigated in the marketing and consumer behavior research domains, at least four main reasons spur to consider the funeral industry as an interesting subject of enquiry: i) the sector boasts of a significant economic relevance; ii) it is extremely impactful from an environmental and social point of view; iii) it is witnessing interesting innovative processes in the direction of social and environmental sustainability; iv) consumer movements are rising all over the world asking for more sustainable death practices. Thus, adopting an augmented version of the theory of planned behavior (TPB), which includes individuals’ environmentally responsible consumption, and egoistic and altruistic environmental concern, the study investigates behavioral intention to adopt innovative green death practices (a green funeral) of people belonging to three different generations: X, Y, and Z. A purposive sample of 627 Italian people participated in an online the survey. Collected data were analyzed adopting an ordinal logit model. The results confirm the TPB predictive power also in the field of green funeral behavioral intention. Furthermore, environmentally responsible consumption and environmental concern – even though only in its altruistic component – positively influence behavioral intention, and generation exerts a moderating effect among the examined constructs. Overall, the research attempts to enrich the literature on ethical consumption by exploring the underinvestigated phenomenon of buying behavior of unsought and end-of-life products, that of green funerals, and provide managerial recommendations to funeral service sellers.     

数字经济时代会计变革及对策

随着数字经济时代的来临，以人工智能技术为代表的现代信息技术越来越多地应用到会计工作中，会计工作将进入数字会计时代，向共享会计、管理会计、智能会计发展。为了适应数字经济带来的变化，会计机构要成为企业的“数据中心”，发挥管理和服务职能。会计人员要积极学习现代信息技术和管理知识，实现由核算型向管理型转型。     

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.     

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.     

Debt Overhang and Deleveraging in the US Household Sector: Gauging the Impact on Consumption

Using a novel data set for the U.S. states, this paper examines whether household debt and the protracted debt deleveraging help explain the dismal performance of U.S. consumption since 2007 in the aftermath of the housing bubble. By separating the concepts of deleveraging and debt overhang—a flow and a stock effect—we find that excessive indebtedness exerted a meaningful drag on consumption over and beyond wealth and income effects. The overall effect, however, is modest—‐around one sixth of the slowdown in consumption between 2000–06 and 2007–12—and mostly driven by states with particularly large imbalances in their household sector. This might be indicative of non‐linearities, whereby indebtedness begins to bite only when misalignments from sustainable debt dynamics become excessive.     

Viewpoint: Regulating meat consumption to improve health,the environment and animal welfare

Meat consumption has increased significantly in the last 50 years. This trend raises various health and environmental issues, as well as moral concerns regarding farm animal welfare. In this paper, we discuss the regulation of meat consumption in developed countries. Specifically, we discuss possible justifications for this regulation in terms of environmental, health and animal welfare considerations, as well as the effect of fiscal, informational and behavioral regulatory instruments. Finally, we present a list of challenges that policy makers and food scholars may need to confront in the future.     

基于GIS和RS的蓄滞洪区和谐发展的技术路线

应用遥感与地理信息系统技术构建基于GIS模型的蓄滞洪区空间数据库,对蓄滞洪区内的基础地理数据进行存储、管理,并对空间数据进行可视化和空间分析等操作;运用RS技术对蓄滞洪区内的土地利用、生态环境变化等情况进行动态监测,建立蓄滞洪区发展指标体系;探求蓄滞洪区的和谐发展模式,为蓄滞洪区的可持续发展提供科学依据。     

Herding behaviour and the declining value relevance of accounting information: evidence from an emerging stock market

This article sheds light on the underlying mechanisms behind the changes in the value relevance of accounting information in the Karachi Stock Exchange (KSE) during the 1999–2010 period. We find that neither changes in earnings quality nor the earnings lack of timeliness hypothesis can explain the decline in the value relevance of accounting information in the KSE. Based on the stylized facts associated with the growth of the KSE and the broader economics literature, we argue that the reduction in the explanatory power of accounting information vis-à-vis stock returns was caused by herding behaviour. Empirical estimates from state-space model of herding behaviour confirm the existence of herding, and we find that the value relevance of accounting information is significantly lower in periods characterized by herding behaviour. This article is also amongst the first attempts to empirically demonstrate that an expansionary monetary policy and increases in foreign portfolio investment lead to increased levels of herding.