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Based on goal orientation theory, this study aims to examine how and when employees' performance goal orientations (PGOs) affect their change-supportive behavior in entrepreneurial firms undergoing change.

A two-wave time-lagged research design was applied to collect data from companies undergoing change in China.

The results showed that employees' performance-proving goal orientation (PPGO) was positively related to change-supportive behavior, and employees' performance-avoiding goal orientation (PAGO) was negatively related to change-supportive behavior. Openness to change played a mediating role in these mechanisms, and employees' learning goal orientation (LGO) played a moderating role.

By solving the mechanism of the relationship between PGOs and change-supportive behavior that has not been explored before, this study answers the question of how and when different PGOs affect support behavior.

The purpose of this study is to enrich the literature on employee relations with a new model focusing on the effect of institutional structure and that of employees’ organizational identification on the relationship between institutional structure in an organization and employees’ pro-environmental behaviors, which represents an alternative approach for understanding employees’ pro-environmental performance.

We collect multi-level and multi-source data from 52 four- or five-star hotels in China (N = 963). For data analysis, we adopt the approach of multilevel structural equation modeling.

The results suggest that organizations’ green institutional structure (G-structure) can significantly influence employees’ organizational identification, which in turn can increase their pro-environmental performance.

We propose a new multi-level theoretical perspective to explain employees’ pro-environmental behaviors. While prior studies on the issue mainly consider only the effects of such micro-level variables as ability, motivation and personality, we focus on the effect of organizational institution and its interaction with micro-level variables so that we can evaluate the effect a commonly-studied contextual variable, i.e. green institutions, on the behaviors. Moreover, in this new theoretical model, we also take into account the effect of another insufficiently-tested micro-level variable, i.e. employees’ identification, which has not been considered as frequently as other micro-level variables in studying employees’ pro-environmental performance. Our results highlight the importance of all these variables and suggest a valuable alternative model for more comprehensive research of employees’ green performance.

Urbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.

We employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.

The results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.

This paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

This case reviews the development of Dianping. After seeing Zagat's unique business model in the United States, founder Zhang Tao found that he could bring it to China and bring about local innovation. At the beginning of its establishment, the collection and promotion of comment content was the major challenge for Dianping. At the same time, Dianping faced legal issues. To solve these problems, the review mechanism of Dianping was designed to a certain extent to ensure the fairness of the review. With the advent of the mobile Internet era, Dianping began to develop a new business model. Relying on its high-quality “word-of-mouth” content and mass basis, Dianping launched group buying, online restaurant ordering, and other businesses. Dianping has always been open to strategic partners. Since 2015, Dianping has undergone historical changes, merging with Meituan. Since then, Dianping has continuously adjusted its business and organizational structure to maintain its competitiveness. Gradually, Dianping has changed from an independent business entity into a business unit of Meituan.

The use of a force sensor to estimate the external force of manipulator not only needs to deal with the signal noise of the sensor itself but also needs to solve the coupling interference of the sensor itself, especially the axial force. The purpose of this paper is to develop a three-dimensional fiber Bragg grating (FBG) wrist force sensor, which has a simple structure and reduces the coupling influence between several axes.

A particular separation elastic structure with four FBGs is devised for the three-axial force sensor. One FBG is suspended on the profile of central cylinder and the other three FBGs are pasted on the elastic beam surface of the over and under measuring bodies, respectively. Finite element analysis (FEA) simulation has been implemented to the strain distribution characteristics, the output characteristics of each direction and the coupling effects of the structure. Furthermore, theoretical derivation and experimental results are used to compare, which have a good consistency.

The experiment results show that the maximum repeatability error of the sensor is 6.75%, the maximum nonlinear error is 5.36%, the maximum coupling interference is 4.73% and the minimum sensitivity is 1.58 pm/N.

A three-dimensional force sensor based on FBG adopts a particular separation elastic structure. The sensor can reduce the coupling influence between several axes, especially the coupling interference in the z-direction is 0.

This paper aims to prepare an oil-impregnated porous polytetrafluoroethylene (PTFE) composite with advanced tribological properties using citric acid as a novel pore-forming agent.

Citric acid (CA) was used to form pores in PTFE, and then oil-impregnated PTFE composites were prepared. The pore-forming efficiency of CA was evaluated. The possible mechanism of lubrication was proposed according to the tribological properties.

The results show CA is an efficient pore-forming agent and completely removed, and the porosity of the PTFE increases with the increase of the CA content. The oil-impregnated porous PTFE exhibits an excellent tribological performance, an increased wear resistance of 77.29% was realized in comparison with neat PTFE.

This study enhances understanding of the lubrication mechanism of oil-impregnated porous polymers and guides for their tribological applications.

This study aims to measure whether admittance in the quarantine ward due to COVID-19 can affect one’s mental health. Nowadays, many countries worldwide are battling with the threat of the COVID-19 contagion, and it is difficult to understand how the pandemic leaves psychological impacts on one’s well-being.

This research used qualitative and quantitative approaches to assess the psychological impacts of quarantine due to COVID-19. Population of the present study were 250 patients who were admitted in quarantine centres of Pakistan. The data analysis was conducted through univariate analysis using (ANVOVA) software.

This study found that patients who were quarantined due to the COVID-19 infection displayed multiple psychological symptoms such as a lack of self-control, anxiety, low general health and vitality, depression and negative well-being.

There is an urgency to provide psychological treatments to each afflicted person and their family members to establish a healthy community.

This research investigates whether admittance in the quarantine ward due to COVID-19 can affect mental health in Pakistan.

“Metaverse” has become a buzzword in the Chinese stock market. However, it remains unclear whether a firm's metaverse-related announcements will elicit positive stock market reactions. Whether and how stakeholder reactions are influenced by a firm's metaverse-related readiness also needs to be further explored. This study aims to discuss the aforementioned objective.

The authors derived a set of factors based on readiness theory and business ecosystem literature and extend them into the context of the metaverse. The authors used a sample of 642 Chinese listed firms in 2021 to investigate the hypotheses through the event study.

The study’s findings show that metaverse coverage induces a positive stock market reaction, but it is subject to three moderating effects. The authors introduce the novel concepts of IT readiness, ecosystem readiness and digital infrastructure readiness as the moderators. Stakeholders perceive metaverse announcements as overhyped, and stock prices do not fluctuate significantly after a metaverse announcement when the listed firms are not ready to embrace the metaverse.

This study is one of the first that introduces the event study method into the metaverse research, and it reveals that different levels of readiness influence stakeholders' evaluations and reactions to corporate metaverse coverage. This provides empirical evidence on metaverse development in China from the stock market's perspective.