Search results

Using WeChat moments as an example, this article explores the impact of user role conflict on privacy concerns, social media fatigue and the three dimensions of discontinuous usage intention: control activities, short breaks and suspend usage intentions. Moreover, the moderating function of self-esteem in this process is examined.

The conceptual model includes role conflict, privacy concerns, social media fatigue, discontinuous usage intention and self-esteem. Three hundred and thirty-one questionnaires were collected using an online survey, and the data were analyzed with structural equation and hierarchical regression modeling.

The results show that (1) role conflict positively affects privacy concerns and social media fatigue; (2) privacy concerns also positively affect social media fatigue; (3) privacy concerns positively affect control activities intentions, although their impact on short breaks and suspend usage intentions is not significant, whereas social media fatigue significantly influences control activities, short breaks and suspend usage intentions; and (4) self-esteem negatively moderates the influence of role conflict on privacy concerns.

A key limitation of this research is that it is designed for WeChat. Therefore, the question of whether other social media platforms face role conflict or discontinuous usage problems should be explored in the future.

The article is interesting in that it focuses on the discontinuous usage of social media and identifies factors that contribute to the discontinuous usage of social media. The findings make some theoretical contributions to, and have practical implications for, research into social media usage.

The purpose of this paper is to understand e-loyalty in the travel industry. Specifically, this paper aims to examine the curvilinear relationship between predictors and e-loyalty.

An empirical study was conducted using an online survey with one of the largest travel companies in China. Structural equation modeling was used to test the models, and pair-wise nested F-tests were used to compare the models.

Results show that the curvilinear model has greater explanatory power of loyalty than traditional linear models. The results of pair-wise nested F-tests show that the loyalty model exhibits statistically significant R2 improvement compared to the linear model. However, the R2 improvement in the integrated model is not statistically different from that in the linear model. Confirmation and satisfaction are found to be salient factors influencing loyalty.

This study makes important contributions to the online community literature by understanding the drivers of loyalty in the travel industry. However, there are limitations. First, this study addressed member loyalty of an online travel community with data collected from one company. Thus, generalizability is limited. Online communities and firms may have different characteristics, resulting in different factors influencing consumer loyalty. The authors plan in the future to collect data from other online travel companies and examine their model with different samples so as to check the generalizability of the current findings. Second, the authors collected a snapshot view on loyalty. Both researchers and managers note that small changes in loyalty and retention can yield disproportionately large changes in profitability (Reichheld et al., 2000). Consumer loyalty may change over time, so to maintain and increase profits, it is important to monitor such change. In the future, the authors plan to conduct a longitudinal study of community members to evaluate their loyalty over time.

As China seeks to gain additional market share in the global tourism market, travel companies should make use of websites as a marketing tool to attract and retain customers. These actions enable a travel company to enhance its competitiveness. More and more people use the internet for tour deals, bookings and finding tour-related information. Effective use of websites can affect the competitiveness of ecommerce companies. E-vendors could assess and adopt the dimensions recommended in this paper to help better understand areas for improvement. It is common today for consumers to buy travel products online instead of going through a travel agent. Considering the importance of reciprocity in formulating consumer satisfaction and loyalty in the virtual environment, companies should monitor reciprocal behavior on the virtual community. With advancement in technologies, consumer behaviors have changed and more consumers prefer social interactions in the virtual world. Companies can analyze posts in the virtual environment to assess reciprocity and may design a mechanism to foster reciprocal behaviors. By leveraging reciprocity, firms can better connect satisfaction with loyalty. More than 70 per cent of executives surveyed by McKinsey (2012) said that they regularly generate value through their Web communities. In addition, to pay attention to consumer to consumer reciprocity in the virtual world, companies should listen to what customers say in their online community, as this attention is an indication of reciprocity between consumers and companies. The ideas and opinions expressed in the online community tell the company customers’ perception of the value of its products and customers’ needs. Such attention to the voices in the online community will help companies to better tailor products/services to meet customers’ needs. Furthermore, the voices expressed in the virtual community are also effective in developing and maintaining new internet marketing opportunities such as email marketing, giveaways, search engine optimization, pay per click and shopping comparison marketing. Companies interested in retaining and attracting customers should leverage their established virtual communities and pay close attention to online posts and evaluate members’ satisfaction. Such effort will provide tangible benefits. As shown in Ye et al.’s study, traveler reviews produce a significant impact on online sales (Ye et al., 2011), with a 10 per cent increase in traveler review ratings, boosting online bookings by more than 5 per cent. This finding suggests that businesses should link online user-generated reviews to business performance in tourism. Finding incentives for users to share might be one way to improve interactivity and further create stickiness on the part of the website.

This paper is one of the first studies to address the need to move beyond linear models of e-loyalty and to additionally examine potential curvilinear and interactive effects. This study also identifies key variables such as reciprocity and satisfaction as determinants of e-loyalty in the Chinese online travel and tourism industry.

The purpose of this paper is to improve the corrosion resistance of the 6061-Al alloy as the battery pack material for electric vehicles, and the nano-SiC/MAO composite coating was prepared.

The corrosion resistance of coatings was evaluated by the global electrochemical test, and the local electrochemical impedance spectroscopy (LEIS) was used to study the local corrosion mechanism. The laser confocal microscope, scanning electron microscope and X-ray diffractometer (XRD) were used to characterise coatings.

Results showed that the impedance of nano-SiC/MAO coating was 1–2 times higher than MAO coating, and the main corrosion product was Al(OH)₃. LEIS results showed that the impedance of the nano-SiC/MAO coating was two times higher than the MAO coating. The defective SiC/Micro-arc oxidation coating still had high corrosion resistance compared to the MAO coating.

The physical model of the local corrosion mechanism for SiC/MAO composite coating in “cavity-fracture collapse” mode was proposed.

Online health monitoring of large complex equipment has become a trend in the field of equipment diagnostics and prognostics due to the rapid development of sensing and computing technologies. The purpose of this paper is to construct a more accurate and stable grey model based on similar information fusion to predict the real-time remaining useful life (RUL) of aircraft engines.

First, a referential database is created by applying multiple linear regressions on historical samples. Then similarity matching is conducted between the monitored engine and historical samples. After that, an information fusion grey model is applied to predict the future degradation trajectory of the monitored engine considering the latest trend of monitored sensory data and long-term trends of several similar referential samples, and the real-time RUL is obtained correspondingly.

The results of comparative analysis reveal that the proposed model, which is called similarity-based information fusion grey model (SIFGM), could provide better RUL prediction from the early degradation stage. Furthermore, SIFGM is still able to predict system failures relatively accurately when only partial information of the referential samples is available, making the method a viable choice when the historical whole life cycle data are scarce.

The prediction of SIFGM method is based on a single monotonically changing health indicator (HI) synthesized from monitoring sensory signals, which is assumed to be highly relevant to the degradation processes of the engine.

The SIFGM can be used to predict the degradation trajectories and RULs of those online condition monitoring systems with similar irreversible degradation behaviors before failure occurs, such as aircraft engines and centrifugal pumps.

This paper introduces the similarity information into traditional GM(1,1) model to make it more suitable for long-term RUL prediction and also provide a solution of similarity-based RUL prediction with limited historical whole life cycle data.