Search results

Work-related use of information and communication technologies (ICTs) after hours can be potentially detrimental to employee well-being. In the current study, we examine whether psychological detachment mediates the link between work-related use of ICTs after hours and fatigue and whether affective commitment exacerbates this mediated relationship.

We collected two waves of data from 295 employees in Vietnam, with 51% being female and an average age of 37.81 years old (SD = 7.93).

Work-related use of ICTs after hours was positively related to employees' fatigue via psychological detachment. The negative relationship between work-related use of ICTs after hours and psychological detachment was stronger for employees with higher affective commitment.

Organizations are encouraged to set policies and procedures to reduce work-related use of ICTs after hours to protect employee health; when work-related use of ICTs after hours is necessary, organizations should provide employees, especially those with higher affective commitment, with resources and strategies to better detach from this experience.

Our findings contribute to the understanding of how work-related use of ICTs after hours might adversely affect employee well-being through psychological detachment and that more committed employees can be more affected in this process.

The current study aims to identify work-related use of information and communication technologies after-hours (W_ICTs) from passive and active perspectives and examine mechanisms and different effects of information and communication technologies on employee innovation behavior.

Experience sampling method (ESM) was employed to capture dynamic within-person variance in daily-behaviors and daily-mood. In total, 92 employees completed an identical online survey each day for ten workdays.

The findings showed that the influence patterns and mechanisms of passive and active W_ICTs were utterly different. Passive W_ICTs was negatively associated with employee innovation behavior via emotional exhaustion, while active W_ICTs was positively associated with employee innovation behavior through perceived insider status. Furthermore, differential leadership significantly narrowed the positive relationship between passive W_ICTs and emotional exhaustion. However, differential leadership did not significantly moderate the relationship between active W_ICTs and perceived insider status.

This study is an important step forward in dividing W_ICTs into passive and active W_ICTs and discovers a dual path of two types of W_ICTs on employee innovation behavior. Findings of this study have heuristic value for future research.

The ubiquity of mobile phone use has generated a common phenomenon called phubbing, a reference to snubbing someone in social settings and instead concentrating on one's phone. Despite numerous adverse effects of phubbing argued in previous research, the group of phubbers is growing intensively. The purpose of this study is to investigate the potential transmission of phubbing between marital partners to raise public awareness of the propagation of phubbing.

A two-wave study with a 3-month interval was conducted, using matched husband–wife data from 253 Chinese couples. Husbands and wives separately completed questionnaires about their spouses’ phubbing and their marital quality. The dyadic data analysis method was applied to test the research hypotheses.

The results confirm the transmission of phubbing and show a pronounced gender asymmetry in the process of phubbing transmission. Phubbing could be transmitted from wives to husbands, but not vice versa. Specifically, only wives' phubbing significantly undermine relationship quality, while relationship quality was negatively related to both husbands' phubbing and wives' phubbing.

This study contributes to a better understanding of the mechanism of phubbing transmission and provide support for reciprocity theory and social role theory. Results can cause public attention to the transmissibility of phubbing and provide enlightenment on the management of personal phone behavior and offer insight into research on technology use in other types of interpersonal relationships.

The purpose of this paper is to gain more insight into the relationship between social media activities and thinking styles, and its potential mechanism.

The current study conducted four studies using an experimental method and eye-tracking method to evaluate prediction.

Results from studies 1 and 2 showed that social media activities influence individuals’ self-construal, and the impact of self-construal on the relative reliance on cognitive vs affective thinking styles. Study 3 supports the hypothesis that social media activities influence individual’s thinking styles, and self-construal is a critical mediator in this process. Furthermore, the authors replicated these findings using an experimental method and eye-tracking method (Study 4), which enabled us to better understand the consumer’s psychological experience when using social media.

This paper contributes to the social media activity literature in the following ways. First, this research advances the knowledge of social media by demonstrating that social media activities can have significant effects on thinking styles. Second, the current research brings important insights to the literature on self-construal. Finally, using eye-tracking methods, the authors also provided some new insights on consumer thinking and behavior.

The purpose of this study is to employ a user-centered approach to identify subgroups of people with similar profiles based on their perceptions of multiple dimensions of digital products' coolness and to test the differences across subgroups in the intention to use these products.

In Study 1, 1,161 adults rated a virtual digital product on four dimensions of coolness. In Study 2, 660 college students made similar ratings and also reported their intention to use a real digital product. Participants' ratings were analyzed using a user-centered approach, namely latent profile analysis.

Study 1 identified groups of participants who had similar profiles of product ratings on the four dimensions of coolness: niche cool, mass cool, uncertain cool and uncool. Study 2 replicated the findings of Study 1 and in addition showed that these groups varied in their intention to use the product and in whether a specific dimension increased or decreased this intention.

The cross-sectional data preclude inferences about causality, calling for experimental or longitudinal research. Additionally, future research should explore whether the results generalize to other product categories and other age groups.

Managers should design digital products, segment the market and develop flexible strategies based on combined responses to dimensions of coolness perception.

The present research employed a user-centered approach to identify groups of people who share similar patterns of coolness perception. This study provides new insight that was not available in variable-centered research.

The purpose of this paper is to investigate and review the impact of the use of statistical quality control (SQC) development and analytical and numerical methods on average run length for econometric applications.

This study used several academic databases to survey and analyze the literature on SQC tools, their characteristics and applications. The surveys covered both parametric and nonparametric SQC.

This survey paper reviews the literature both control charts and methodology to evaluate an average run length (ARL) which the SQC charts can be applied to any data. Because of the nonparametric control chart is an alternative effective to standard control charts. The mixed nonparametric control chart can overcome the assumption of normality and independence. In addition, there are several analytical and numerical methods for determining the ARL, those of methods; Markov Chain, Martingales, Numerical Integral Equation and Explicit formulas which use less time consuming but accuracy. New ideas of mixed parametric and nonparametric control charts are effective alternatives for econometric applications.

In terms of mixed nonparametric control charts, this can be applied to all data which no limitation in using of the proposed control chart. In particular, the data consist of volatility and fluctuation usually occurred in econometric solutions. Furthermore, to find the ARL as a performance measure, an explicit formula for the ARL of time series data can be derived using the integral equation and its accuracy can be verified using the numerical integral equation.