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.     

Is online-to-offline customer care support essential for consumer service?

Customer satisfaction is the main pillar for convenient and profitable retailing. The retail sector continuously tried to develop new strategies to improve consumer satisfaction. It is impossible to provide each service directly to the consumer by the retailer. In this direction, the retailer establishes customer care to provide the best service to consumers. Consumer care can provide promotional or prevention services, increasing the consumer's satisfaction level. This study is developed to show the impact of retailers' customer care service for an offline-to-online retailing strategy. The demand is consumer support, advertisement, and selling price dependent. For maintaining consumer service, some free home delivery policies are offered, when consumers ordered more than a certain percentage of the amount. Finally, the total profit of this O2O retailing system is calculated by the classical optimization technique. Some special cases are discussed in the numerical section to prove the impact of customer care services. Numerical results prove that customer care support enhances the profit by 48.20%, whereas investment in the advertisement and home delivery strategy helps the retail industry to earn 44.80% and 16.74% more profit, respectively. Finally, from this study, it is clear that customer care activities are essential to increase the profit of the retailing sector.     

The relation between municipal and government bond yields in an era of unconventional monetary policy

In this paper, we investigate how the 5‐year Swedish municipal bond yield has been related to the corresponding yield on government bonds during the period that the Riksbank has conducted unconventional monetary policy in terms of bond purchases. Using daily Swedish data on bond yields from February 2015 to January 2018, we first conduct an event study to assess the short‐run effects of the Riksbank's bond‐purchase announcements. We then estimate bivariate vector autoregressive models to study the dynamic relationship between the yields. Results from the event study suggest that the accumulated short‐run effect of the Riksbank's announcements was to lower the government bond yield by approximately 40 to 50 basis points and municipal bond yields by 30 to 35 basis points. Our vector autoregressive analysis indicates—in line with the event study—that an unexpected decrease in the government bond yield initially increases the municipal bond‐yield spread. However, after approximately 4 weeks, the effect has been reversed and the municipal bond‐yield spread is lower than it was initially. By conducting this analysis, we contribute to the understanding of the transmission of unconventional monetary policy.     

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.     

Workplace bullying and presenteeism in the cruise industry: Evaluating the effect of social support

A cruise ship constitutes a unique research laboratory for the study of workplace bullying and presenteeism because of its manifestation of the phenomena and situations that traditionally characterize total institutions. This study analyzes the role of workplace bullying as a potential risk factor for presenteeism in the workplace and the moderating role of social support. Results confirmed that work-related bullying is positively connected to the phenomenon of presenteeism, whereas person-related bullying is negatively related. The findings also confirmed the role of social support, specifically supervisor support, as a moderating agent of this relationship. The supporting details are further elaborated, and the main implications for the future of the cruise industry are presented. The findings can facilitate cruise line companies in designing prevention plans and implementing well-targeted anti-bullying policies according to the type of workplace bullying experienced by workers that can substantially improve their effectiveness.     

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.     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

iSDS: a self-configurable software-defined storage system for enterprise

ABSTRACT

Storage is one of the most important aspects of IT infrastructure for various enterprises. But, enterprises are interested in more than just data storage; they are interested in such things as more reliable data protection, higher performance and reduced resource consumption. Traditional enterprise-grade storage satisfies these requirements at high cost. It is because traditional enterprise-grade storage is usually designed and constructed by customised field-programmable gate array to achieve high-end functionality. However, in this ever-changing environment, enterprises request storage with more flexible deployment and at lower cost. Moreover, the rise of new application fields, such as social media, big data, video streaming service etc., makes operational tasks for administrators more complex. In this article, a new storage system called intelligent software-defined storage (iSDS), based on software-defined storage, is described. More specifically, this approach advocates using software to replace features provided by traditional customised chips. To alleviate the management burden, it also advocates applying machine learning to automatically configure storage to meet dynamic requirements of workloads running on storage. This article focuses on the analysis feature of iSDS cluster by detailing its architecture and design.     

Evaluation of workplace lactation support among employers in two Pennsylvania cities

A majority of mothers with infants less than 1 year old participate in the labor force. Employers can modify the physical and social environments at work to accommodate breastfeeding employees and enable continued participation in the labor force. The purpose of our article is to (1) characterize breastfeeding policies and programs currently offered at workplaces in two Pennsylvania cities and (2) identify improvement areas to support breastfeeding employees in the workplace. We partnered with two business groups on health in Pennsylvania and electronically administered a survey to their employer members. Responses were aggregated into a workplace lactation support score based on physical space, time, policy, and resources. Higher scores indicate that employers offered a large number of workplace lactation supports. We conclude by offering specific improvement opportunities that include a written policy communicated to all employees and the formal communication of lactation services. Employers can utilize workplace lactation support scores to elect interventions that are feasible for implementation in their organizations.     

Combining wavelet decomposition with machine learning to forecast gold returns

This paper combines the discrete wavelet transform with support vector regression for forecasting gold-price dynamics. The advantages of this approach are investigated using a relatively small set of economic and financial predictors. I measure model performance by differentiating between a statistically-motivated out-of-sample forecasting exercise and an economically-motivated trading strategy. Disentangling the predictors with respect to their time and frequency domains leads to improved forecasting performance. The results are robust compared to alternative forecasting approaches. My findings on the relative importances of such wavelet decompositions suggest that the influences of short-term and long-term trends are not stable over the full evaluation period.