Search results

Monetary incentives have been widely adopted by brands to promote consumer engagement in their brand communities on social networking sites. This paper aims to explore how the interactions triggered by an emerging monetary incentive, red packets, affect consumers’ brand attitude in the context of WeChat brand groups (WCBGs).

According to whether brands ask for commercial returns from consumers, two types of interactions were identified, namely, exchange red packet interaction (ERPI) and communal red packet interaction (CRPI). The corresponding influences on brand attitude were examined in three experiments.

Compared to CRPIs, ERPIs elicit greater normative community pressure, inducing a less favorable brand attitude. Moreover, this impact is moderated by the time frame of brand communities. In the long-term WCBGs, a significant difference exists between ERPIs and CRPIs, while such difference attenuates or even disappears in short-term WCBGs.

When using red packets as an engagement strategy, brand managers should be alert to their potential negative influence. Specifically, in short-term brand communities, ERPIs enable managers to acquire commercial returns without hurting brand attitude. In long-term brand communities, managers are advised to implement CRPIs to foster a positive brand attitude.

This study investigates red packet interactions in brand communities, which have been widespread but unexplored. The results expand the literature by addressing the undermining effect of ERPI and the moderating effect of the time frame.

Rural homestays have emerged as an interesting option for tourists. This study aims to assess the role of destination attractiveness factors and travel motivations in homestay choice. The moderating role of need for uniqueness towards enhancing these relationships is also examined.

A survey of 201 Indian tourists who had visited rural homestays in the Uttarakhand state of India was conducted. Data were analyzed using SPSS and WarpPLS, based on structural equation modelling approach.

Results indicate that two destination attractiveness factors – (a) cultural and rural attractions and (b) destination location and transportation – have a significant association with rural homestay choice. Further, need for uniqueness enhances the relationship between natural attractions and choosing rural homestays.

Although there are several studies on rural homestays, there is scant research on the factors influencing the choice of rural homestays from a tourists’ perspective. Besides, studies on rural homestay tourism have not assessed the role of need for uniqueness in influencing such choices. The implications of the study for destination marketers, homestay operators and owners are discussed which would hopefully aid in attracting discerning tourists to the rural homestays to such regions.

This study aims to develop a high-performance nanofluid that can be used in titanium alloys machining. Titanium alloys are difficult-to-cut materials and difficult to be lubricated. This study explored the lubrication performance of various carbon nanoparticles in water-based lubricants for titanium alloys.

The lubricating and antiwear properties of the developed cutting fluid were tested by a tribo-tester. The lubricant performance was evaluated through friction coefficient, wear volume and surface quality. The lubrication mechanism was analyzed through surface morphology, wettability and bonding analysis.

The lubricating performance of four kinds of carbon nanoparticles on titanium alloys was tested and the results showed that single-layer graphene had the smallest COF and wear volume. The interaction between nanoparticles and debris was an important factor that influenced the lubrication performance of nanoparticles for titanium alloy. Moreover, the hybrid nanofluid with graphene and spherical graphite in a ratio of 1:2 achieved a balance between lubricating performance and price, making it the optimal choice.

The developed lubricant containing carbon nanoparticles that can lubricate titanium alloys effectively has great potential in machining titanium alloy as a high-performance cutting fluid in the future.

This paper fulfills an identified need for water-based lubricant for titanium alloys considering the bad tribological properties.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0124/

The purpose of this paper is to investigate the impact of the COVID-19 pandemic on company innovation, specifically centering on the quantity and quality of innovation. The paper aims to provide a comprehensive understanding of whether the epidemic inhibits innovation and the role of digital transformation in mitigating this negative impact.

The paper uses a quasi-experimental study of the COVID-19 pandemic and constructs a differential model to analyze the relationship between the epidemic and firm innovation in three dimensions: total, quantity and quality. The paper also uses a difference-in-difference-in-differences model to test whether digital transformation of firms mitigates the negative impact of the epidemic and its mechanism of action.

The results show that COVID-19 significantly reduced the overall level of firm innovation, primarily in terms of quantity rather than quality. Furthermore, this study finds that digital transformation plays a pivotal role in mitigating the pandemic’s adverse impact on innovation. By addressing financing constraints and countering demand insufficiency, digital transformation acts as a catalyst for preserving and fostering innovation during and after the pandemic.

This study extends the current research on the pandemic’s impact on firm innovation at the micro level. It offers valuable insights into strategies for fostering digital transformation among Chinese enterprises in the post-pandemic era.

This study aims to examine the spatial spillover effect and its mechanism of the impact of China–US relations on Chinese enterprises’ OFDI.

This study takes the relations between China and the United States (China–US relations), one of the most important great power relations in the 21st century, as the research object, employing a spatial spillover perspective informed by bilateral and multilateral theory, information transfer theory and realism and institutionalism. This study utilizes micro-level data on Chinese firms’ outward foreign direct investment (OFDI) for 2008–2023 to study the spatial spillover effects and mechanism involved in the impact of China–US relations on Chinese firms’ OFDI.

Results show that China–US relations increase Chinese enterprises’ OFDI in countries other than the US, demonstrating spatial spillovers in the impact of China–US relations on Chinese firms’ OFDI. This spatial spillover effect is characterized by a full cycle, time variation and imbalance. The mechanism analysis shows that this spatial spillover is realized through the neighboring country effects and great power demonstration effects. Heterogeneity analysis shows that firms’ independent research and development (R&D) capabilities, China’s economic power and the cultural distance between China and the host country can buffer the impact of changes in China–US relations on Chinese firms’ OFDI.

This study provides a comprehensive understanding of the role of international relations in influencing OFDI and offers useful insights for developing countries to promote high-level opening-up.

First, this study examines the spatial spillover effects of China–US relations on Chinese firms’ OFDI, expanding the perspective of the impact of diplomatic relations on cross-border economic activities. Second, this study enriches the research on the mechanism by which diplomatic relations affect OFDI by arguing that this spatial spillover is realized through the neighboring country effect and the great power demonstration effect. Third, this study confirms the role of enhancing the competitiveness of multinational corporations (MNCs), upgrading the country’s comprehensive national strength, and promoting cultural exchanges in buffering exogenous shocks of changes in China–US relations.

This paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological environment in the Yangtze River Economic Belt of China. The purpose of this study is to provide some theoretical basis and tool support for management departments and relevant researchers engaged in industrial sustainable development.

This study uses the driving force pressure state impact response analysis framework to build a comprehensive evaluation index system. Based on the center point triangle whitening weight function, it classifies the panel grey clustering of improvement time and index weight.

The results show that there are great differences in the level of industrial ecological development in different regions of the Yangtze River Economic Belt, which further illustrates the scientificity and rationality of the evaluation method proposed in this paper.

Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. The improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.

Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. In order to improve the effectiveness of industrial ecological evaluation, the improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.

the new model proposed in this paper complements and improves the grey clustering analysis theory of panel data, that is, aiming at the subjective limitation of using time degree to determine time weight in panel grey clustering, a comprehensive theoretical method for determining time weight is creatively proposed. Combining the DPSIR (Driving force-Pressure-State-Influence-Response) model model with ecological development, a comprehensive evaluation model is constructed to make the evaluation results more authentic and comprehensive.

The purpose of this paper is to present a new approach for selecting the good heavy oil reservoirs to develop preferentially, which can avoid the huge economical loss resulted from wrong decision.

A new method of ranking the development priority of heavy oil reservoir is present, in which the neural network is applied for the first time to acquire reservoir parameters' weights through training samples and the genetic algorithm is used to optimize the joint weighs of neurons in case that neural network falling into local minimum. Additionally, the paper establishes subordinate function of every parameter. Eventually, comprehensive evaluation values of all heavy oil reservoirs are obtained.

The method can ensure the veracity and creditability of the parameters' weights, avoid the randomicity brought by experts.

Accessibility of the data of many heavy oil reservoirs is the main limitation.

A very useful and new method for the decision makers of heavy oil reservoirs development.

The new approach of ranking the development priority of heavy oil reservoir based on the neural network and the genetic algorithm. The paper is aimed at the leaders who manage the development of heavy oil reservoirs.

The game strategies differ when different regions participate in the oil game. Under what circumstances will different participants choose cooperation or sanction strategies? This is the core issue of this paper.

Regarding the current and future game behavior between different regions in the oil trade, this paper constructs an evolutionary game model between two regions to explore the possibility of sanctions strategies between the two sides in different situations.

The research finds: (1) When the benefits of in-depth cooperation between the two regions are greater, both sides tend to adopt cooperative strategies. (2) When the trade conflict losses between the two regions are smaller, both sides adopt sanctions strategies. (3) When a strong region trades with a weak region, if the former adopts a sanctions strategy, the net profits are greater than the benefits of in-depth cooperation between the two regions. If the latter adopts a sanctions strategy, the net profits are less than the trade conflict losses between the two regions. There will be the strong region adopting a sanctions strategy and the weak region adopting a non-sanctions strategy. At this time, the latter should reasonably balance the immediate and future interests and give up some current interests in exchange for in-depth cooperation between the two regions. Otherwise, it will fall into the situation of unilateral sanctions by the strong against the weak.

There is no paper in the existing literature that uses the evolutionary game method to analyze the oil game problem between the two regions. This paper constructs a two-party evolutionary game model composed of crude oil importers and crude oil exporters and, based on this, analyzes the evolutionary stability between the two regions under sanctions and cooperation strategies, which enriches the energy research field.

Companies allowing employees to self-report business expenses face the risk of expense fraud because some occasionally engage in dishonest behavior to receive reimbursements for their use. Drawing on the technology acceptance model, this study aims to investigate the effects of perceived usefulness, perceived ease of use and perceived security on the trust in e-reimbursement systems and the relationship with honest disclosure intention.

A self-administered questionnaire was distributed to 254 respondents, with the partial least squares structural equation modeling used to analyze the data.

The findings showed that perceived security and perceived usefulness explained trust in e-reimbursement systems, whereas perceived ease of use had no significant effect on it. Corporate governance and trust in e-reimbursement systems have a positive relationship with whistleblowing intention. At the same time, corporate governance mediates the relationship between trust in e-reimbursement systems and honest disclosure intention.

This study sheds light on using e-reimbursement systems within organizations to prevent fraudulent reimbursements and offers recommendations to management on enhancing employees’ intention to engage in honest disclosure behavior through e-reimbursement systems.

This paper aims to develop a Mini-Tribometer for in-situ observation of subsurface.

To observe the change of the microstructure during wear in real time, an in-situ observation mini-tribometer was developed according to the requirements of the basic frictional experiments and carried out the verification experiments.

The subsurface images and the tribological data obtained from the mini-tribometer clearly show that the graphite in the matrix moves to the surface and takes part in lubrication mainly in the form of extrusion and peeling off, and the migration of graphite in the copper-based composite to the frictional interface to act as lubricant and to result in the decrease of the friction coefficient. The experimental results of the developed tribometer are accurate, which can provide important references for further research on the wear mechanism of materials.

The developed in-situ observation mini-tribometer can be used to observe the dynamic wear mechanism of the frictional pairs, which is very important for optimization of material design and tribological performances.