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Based on social cognitive theory, this study aims to explore the psychological mechanism behind consumer verification behavior following tourism e-commerce live-streaming.

Based on grounded theory, data were collected through 20 semi-structured in-depth interviews and analyzed.

This study identified that companies commonly use reminder messages and secondary promotions to facilitate the verification of tourism live-streaming products. Throughout this process, consumers undergo various psychologies related to verification. Specifically, they experience four positive verification psychologies: fear of missing out, anticipated emotions, status self-esteem and promotional perception. They also encounter two negative verification psychologies: psychological reactance and invasiveness. In addition, environmental factors such as the type of tourism live-streaming products and tourism destinations, along with individual trait factors like cognitive miserliness, tourism experience, autonomy, regulatory mode and impulsiveness, play significant roles in shaping verification behavior. These factors collectively influence the formation of verification behavior.

This study can provide recommendations for tourism companies to conduct marketing events following live-streaming. It is one of the earlier comprehensive studies discussing how to promote verification behavior following tourism e-commerce live-streaming. It helps to understand the psychological mechanism underlying the formation of verification behavior.

This paper proposes a framework for director evaluation in the context of Chinese state-owned enterprises (SOEs), taking into account the influences of traditional and modern Chinese ideologies.

Following the Delphi method, a series of semi-structured interviews were conducted with Chinese SOE directors.

The framework used has been validated by examining seven dimensions of virtue and four dimensions of competence functions in Chinese SOEs. Effective and representative characteristics of each dimension are identified through interviews.

First, through this research, indicators of virtue have been materialized and those of competence have been specified in a broader range. Second, this research provides advice for training of candidate directors whose experience were in private firms before they step in as SOE directors.

Oppositional brand loyalty (OBL) has become widespread and has thus received growing scholarly attention in recent years. Although opposition behaviors have distinct manifestations, their differential antecedents remain underexplored. Drawing from the identity-based motivation model, this article aims to examine the impact of brand identification and brand disidentification on the two distinct dimensions of OBL (i.e. brand avoidance and trash talk) according to their different intensity and activation levels (passive or active). In addition, article aims to examine the moderating role of perceived inter-group rivalry.

The authors collected survey data and obtained 392 valid questionnaires from smartphone users. Structural equation modeling was used for hypothesis testing.

The results show that brand identification has a significant positive effect on avoidance of rival brands, but not on trash talk; brand disidentification has a significant positive effect on both avoidance and trash talk of rival brands; and perceived inter-group rivalry positively moderates the relationship between brand disidentification and trash talk, but does not alter the relationship between brand disidentification and brand avoidance.

This study extends the literature on OBL by investigating differential antecedents of two distinct dimensions of brand opposition. It provides more complete understanding of the formation of OBL by examining the role of users’ relationship with a focal brand, its competing brand and inter-group relationship.

Oppositional loyalty toward rival brands is prevalent. Although its antecedents have increasingly received scholarly attention, the literature is rather disparate. Based on identity theory, this study aims to propose that oppositional loyalty is a brand identity-driven outcome and provides a unified framework for understanding the formation and activation of brand identity in influencing oppositional loyalty.

Structural equation modeling was used to test the theoretical framework based on an online survey of 329 brand community members. Multigroup analysis was used to test the moderating effect of inter-consumer brand rivalry and brand community engagement.

The results show that self-brand similarity, brand prestige and brand uniqueness lead to consumers’ brand identity (i.e. consumer-brand identification), which, in turn, facilitates oppositional loyalty. Furthermore, the results indicate that inter-consumer brand rivalry and brand community engagement are identity-salient situations that strengthen the relationship between consumer-brand identification and oppositional loyalty.

Identity has great power in shaping consumer behaviors. Fostering consumer-brand identification is critical for firms to prevent consumers from switching to competing brands. Inter-consumer brand rivalry and brand community engagement can help firms consolidate their customer base by evoking consumers’ brand identity.

This investigation makes theoretical contributions by providing a unified theoretical framework to model the development of oppositional loyalty based on identity theory.

The study aims to examine how different types of green brand ritual (GBR) influence customer engagement behavior and the mediation mechanisms and boundary conditions of the positive and negative pathways.

The study conducts two online experiments to collect data from a total of 940 consumers in China. Hypotheses are tested by independent samples t-test, two-way ANOVA and Hayes' PROCESS model.

Different kinds of GBR have different effects on customer engagement behavior. Internal GBR is more likely to play a positive role by inciting connectedness to nature. External GBR is more likely to play a negative role by inciting psychological resistance. This dual effect is especially pronounced for warm brands rather than competent brands.

The study pioneers the brand ritual into the field of interactive marketing and enriches its dual effect research. Additionally, the study figures out whether the category of brand ritual can trigger negative effect.

Inappropriate brand rituals are worse than no rituals at all. The results provide guidance for green companies to design effective brand rituals to strengthen the connection with consumers. Green brands should describe brand rituals in vivid detail and consciously lead consumers to immerse themselves in them.

This study aims to investigate the promoting effects of the quantity and quality of online review user-generated photos (UGPs) on perceived review usefulness. The research further tests the hindering effect of human facial presence in review photos on review usefulness.

Based on review samples of restaurants in a tourist destination Las Vegas, this study used an integrated method combining a machine learning algorithm and econometric modeling.

Results indicate that the number of UGPs depicting a restaurant’s food, drink, menu and physical environment has positive impacts on perceived review usefulness. The quality of online review UGPs can also enhance perceived review usefulness, whereas facial presence in these UGPs hinders perceived review usefulness.

Findings suggest that practitioners can implement certain tactics to potentially improve consumers’ willingness to share more UGPs and UGPs with higher quality. Review websites could develop image-processing algorithms for identifying and presenting UGPs containing core attributes in prominent positions on the site.

To the best of the authors’ knowledge, this study is the first to present a comprehensive analytical framework investigating the enhancing or hindering roles of review photo quantity, photo quality and facial presence in online review UGPs on review usefulness. Using the heuristic-systematic model as a theoretical foundation, this study verifies the additivity effect and attenuation effect of UGPs’ visual elements on judgements of online review usefulness. Furthermore, it extends scalable image data analysis by adopting a deep transfer learning algorithm in hospitality and tourism.

The purpose of this study is to investigate union effects on wages, employment, and productivity in China. The relationships between unionization and these three economic variables are first tested at the national level and then examined in the eastern, central, and western regions, respectively.

Provincial-level panel data from 1994 to 2014 are used in this study, compiled from various Chinese Statistics Year Books, and covering 29 provinces. The Ordinary Least Square is firstly employed to examine union impacts. Then, in view of the endogeneity of unionization, the Two-Stage Least Square estimation with instrument variables is adopted to reexamine union effects. Overidentification tests are conducted, verifying the validity of these instruments.

At the national level, Chinese unions have significantly positive effects on wages but no significant effect on employment and productivity. In the eastern region, unions are significantly related to increased employment. In the western region, union activity not only significantly promotes wages but also improves productivity. In the central region, unionization has no significant impact. These findings suggest that equipping Chinese unions with a collective and cooperative face can generally help them improve workers' interests. Their effectiveness varies across the three economic regions.

Compared with the survey data conducted in certain cities and industries, the provincial-level panel data used in this article have the advantage of capturing the overall effects of unionization. An instrument variable method is used to address the endogeneity issue. After exploring union effects at the national level, this paper focuses on observing the differences in union roles in three economic regions.

This paper aims at multi-attribute and multi-program group decision making when the attribute weights are completely unknown and the attribute value information is in the form of the interval number.

This is an artificial intelligence algorithm for designing information gathering in group decision making. The authors propose the nonlinear programming model to gather information based on plant growth simulation algorithm (PGSA). The authors collect each program on each attribute group decision preference ordering interval and then use them to find the preference vector and the preference matrix. The entropy method is used to determine the weight of each attribute by the constructed preference matrix. According to the possibility degree matrix of each attribute, the combined effect vector is established by the priority weight vector method, which sorts and selects the best decision making program.

To the authors' knowledge, the application of PGSA in the field of management decisions to collect program on each attribute group decision making preference interval number is the first trial in literature. It has retained more valuable decision making information from all experts without distortion.

In practice, a real number may not be an accurate representation, but only gives a range of values to describe the attributes. This study provides a useful measurement of interval number information for managers to evaluate military science, venture capital, and environmental assessment, etc.

The methodology considers the complete information to ensure no information distortion even with large and complex systems. The authors adopt computer artificial intelligence algorithms to obtain the objective evaluation, which is meaningful for both research studies and practical use.

The purpose of this study is to test the impact of time and price sensitivity on consumer satisfaction and purchase intention on online-to-offline (O2O) takeout platforms and explore the moderating effect of purchase preference on time sensitivity and satisfaction, as well as price sensitivity and satisfaction, in order to guide market pricing.

A structural equation model (SEM) of customer purchase intention was constructed, and the relationships between the variables (time sensitivity, price sensitivity, satisfaction and purchase intention) were examined. The completed questionnaires of 349 respondents were collected from the Questionnaire Star platform in China. The research model and hypotheses were then tested. Analytic hierarchy procedure was used to determine the moderating effect of purchase preference. Finally, the study proposes a pricing strategy for customer-active selective services.

Satisfaction positively influences purchase intention, and price sensitivity significantly increases satisfaction and further increases purchase intention; however, time sensitivity negatively affects satisfaction. Specifically, purchase preference has strongly moderated the relationship between time, price sensitivity and satisfaction. In addition, the findings show that when purchase preference is high, the effect of price sensitivity on satisfaction is stronger, suggesting the importance of purchase preference in strengthening purchase intentions. The research work recommends a pricing strategy involving value-added pricing primarily for time-sensitive customers, which can help build a high-end brand image and reduce price competition. Reduced pricing is mainly for price-sensitive customers, which is conducive to stimulating consumption within a specific time. This pricing strategy is important for adjusting market sensitivity and flexibility.

This research provides new ideas for related disciplines and guidance for the differentiated pricing and promotion of takeout platforms, as well as a theoretical basis for the diversified development of takeout platforms, improvement of personalized service quality and enhancement of customer stickiness. This study fills gaps in the existing literature on the moderating effect of purchase preference on time sensitivity and satisfaction and price sensitivity and satisfaction.

To investigate transverse vibration of the eccentric rotor in a 12/8 poles switched reluctance motor (SRM), a transverse analytical vibration model is built by finite element method (FEM) under the interaction of radial magnetic resultant and vibration displacement. External forces, including radial magnetic resultant and centrifugal force, are also derived in detail, according to the variation of airgap and current and other intermediate parameters with rotation angle.

The transverse vibration response of the eccentric rotor including radial magnetic resultant and vibration displacement is solved by Newmark-β method, after inputting the currents of three phase windings under angle position control strategy. The basic characteristics of radial magnetic resultant and vibration displacement are reflected in time and frequency domain.

The magnetic resultant vector of the eccentric rotor presents multi-petals star geometric shape. The frequency distribution of magnetic resultant relates to rotation speed, current waveform and the least common multiple of the stator and rotor teeth. However, the frequency distribution of the vibration displacement also relates closely to the first-order critical whirl speed of the rotor. When the rotor is running at certain speeds, it will display superharmonic resonance and show abundant displacement locus.

By using this analytical model and solving process proposed in this paper, the nonlinear coupled vibration response of the eccentric rotor in SRM can be analyzed and discussed rapidly; only the stator’s winding currents obtained by experiment or electromagnetic simulation is needed as input.