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This study aims to explore the perceptions of young consumers, a rapidly growing market segment in Taiwan’s restaurant industry, and analyze the composition and structure of background music alongside the physical environment in luxury restaurants. This study identifies key factors that significantly influence customer emotions and examine the moderating effect of service encounter pace on customer emotions and satisfaction for offering practitioners practical insights to enhance young consumers’ dining experiences.

This study used partial least squares structural equation modeling (PLS-SEM) for hypothesis testing. The research model was evaluated within the context of luxury restaurants, and moderation analyses were conducted to assess the impact of service encounter pace on customer satisfaction.

The study reveals that luxury restaurants’ physical environment and background music significantly affect pleasure and arousal. Notably, arousal positively influences customer satisfaction, while pleasure does not. The findings also support that service encounter pace creates a fully moderated effect between customer emotion (pleasure and arousal) and customer satisfaction.

The findings assist luxury restaurant management in developing effective servicescapes that evoke positive customer emotions and establish an optimal service encounter pace, thereby enhancing overall customer satisfaction.

This study enriches our understanding of the dining experiences of Taiwanese Gen Y consumers in luxury restaurants. It also sheds light on emerging hospitality trends and explores the perceptions of younger generations, potentially including Generation Z.

Using surveys of Amazon and Tmall Global users, this paper aims to empirically investigate the issue of platform technological selection. We explore the impact of switching costs on users’ intentions to use an app-enabled cross-border e-commerce (CBEC) platform based on an extended technology acceptance model (TAM). The results suggest that the higher the switching cost of a platform is, the greater the users’ satisfaction and intention to use this platform. Therefore, for the platform, a moderate switching cost will be beneficial for retaining users.

Based on the TAM, this paper takes the switching costs as the starting point and focuses on exploring the relationships among switching costs, perceived usefulness, perceived ease of use, perceived reliability, satisfaction and intention to use. Online surveys of users of Amazon and Tmall Global are adopted as the main instruments of this research. We collected a total of 408 valid responses from Amazon users and 490 from Tmall Global users. For the data analysis, this study conducts frequency analysis, a test analysis of the reliability and validity of the measures, correlation analysis, and path analysis using a structural equation model.

The results show that switching costs positively affect the users’ satisfaction and intentions to use a CBEC platform through perceived usefulness, perceived ease of use and perceived reliability.

The questionnaire respondents were predominantly Chinese due to the constraints of the survey conditions. In fact, China has a high penetration rate in CBEC, and Chinese users have rich experience using the Amazon and Tmall Global platforms.

The development of CBEC has ups and downs, and users frequently switch platforms. Considering how platforms can stand out from the crowd and retain users, we believe that a moderate increase in the switching cost of the platform is helpful for companies to address these problems, and the implications of the results are particularly valid for decision-makers of CBEC platforms and companies.

Amazon and Tmall Global are the two largest CBEC platforms in the world. Using these two companies as examples for comparison can effectively identify the differences between the platforms and the conclusions are representative. We suggest that platforms can improve user satisfaction and willingness to use by establishing VIP communities, issuing coupons, providing shipping services as well as convenient after-sale complaint channels, and improving the platform’s easy-to-use interface, as ways to further enable the platform to retain more users and stand out in fierce competition.

This paper addresses an interesting and practical issue related to the effects of introducing switching costs in an extended TAM applied to CBEC platforms.

Digital product and service innovations (DPSI) has attracted widespread attention from both management scholars and practitioners. Previous studies have documented that information technology (IT) capability and digital orientation positively influence DPSI performance. However, the question of whether and how digitalization capability can facilitate DPSI performance remains unresolved. This paper fills these gaps by investigating the mediating role of improvisation capability and the moderating role of technological turbulence.

This study used two-wave data from 240 matched digital transformation department leaders and senior managers from Chinese firms and examined the hypotheses deploying hierarchical regression and bootstrapping.

Our analyses reveal positive, significant links between digitalization capability and improvisation capability and between improvisation capability and DPSI performance. The findings further show that the effect of digitalization capability on DPSI performance is partially mediated by improvisation capability and that technological turbulence strengthens the indirect relationship between digitalization capability and DPSI performance through improvisation capability.

Integrating resource-based view, this research provides evidence that the extent to which improvisation capability mediates the relationship between digitalization capability and DPSI performance depends on technological turbulence. It provides a new direction for digitalization capability and DPSI performance.

Focusing on the social influence processes in the context of massively multiplayer online role-playing games (MMORPGs), this study aims to investigate the nomological network of social influence factors, a topic seldom explicitly articulated in the literature in this unique context.

This study adopts a mixed-methods approach to develop and test a context-specific model of social influence processes in MMORPGs. First, the authors conducted qualitative interviews with MMORPG players to identify the drivers shaping players' perceptions of social influences. Second, the authors formulated and tested a research model with quantitative data collected from 450 respondents of an online survey.

Through the qualitative study, the authors identify leader enthusiasm, social support and social presence as the critical drivers of social influence factors. The result of the quantitative study validates the influences of the critical drivers and demonstrates the impact of social influences on MMORPG players' we-intention to continue playing games.

This research extends the social influence theory by identifying contextualized drivers that shape MMORPG players' perception of social influences determining their we-intention to continue playing games. MMORPG service providers can draw on these drivers to leverage social influences to increase players' we-intention of continuance.

While the phenomenon of technostress has received significant attention from researchers in recent years, empirical findings concerning the consequences of specific forms of techno-stressors have remained scattered and contradictory. The authors aim to integrate the conclusions of previous studies to understand the effects of specific techno-stressors on strain and job performance.

This study employs meta-analytic techniques to calibrate the findings of 67 studies investigating more than 63,100 employees.

In general, not all techno-stressors have adverse effects. In particular, techno-uncertainty does not impact job performance. In addition, relative weight analyses reveal the relative importance of techno-complexity and techno-insecurity as predictors of both strain and job performance. Finally, this study finds that the effects of specific techno-stressors on job performance vary depending on research participants' gender, educational attainment and employment status.

First, this study provides a more nuanced view of the effects of specific techno-stressors. Second, this research clarifies the relative importance of specific techno-stressors as predictors of strain and job performance. Finally, this study reveals the moderating effects of demographic variables on the relationships between specific techno-stressors and job performance.

This study investigates the moderating effects of consumers’ occupations on their purchase intentions (PIs) for food takeout services using a modified unified theory of acceptance and use of technology model. It evaluates how different occupations influence the relationships between social influence (SI), expectation confirmation (EC), facilitating conditions (FC) and PI.

The study collected data from individuals in various occupations, including technical/associate professionals, executives/professionals, administrative/service workers and manual/operative workers. The data were analyzed using structural equation modeling, while hierarchical analysis assessed how occupation moderated the relationships between latent variables (SI, EC and FC) and PI.

Different occupations have a certain moderating effect on the relationships between SI/EC/FC and PI. For the technical and associate professionals and manual and operative occupations, the moderating effect of FC on PI is stronger than that of EC and SI. For executives and professionals and administrative and service occupations, the moderating effect of EC on PI is stronger than that of SI and FC.

This study provides new insights into how occupational differences influence consumer behavior in the context of online food ordering services. The results expand the application of the unified theory of acceptance and use of technology model and the understanding of the influence of occupation on consumer’ behavior.

The purpose of this study is to reveal the significant contribution of MXene on enhancing tribological properties and to obtain the influence mechanism of various factors on friction characteristics of rolling bearing under extreme conditions.

Under extreme working conditions, the friction characteristics of rolling bearings directly determine the safety and reliability of the transmission system. In this study, MXene is added to the origin lubricating grease (OLG) of rolling bearing to enhance their friction characteristics. Then, the effects of inner ring speed, radial load, grease filling volume and other factors on the friction coefficient of rolling bearing are analyzed using the Taguchi method.

The results indicate that the ranking of various factors affecting the friction coefficient is: radial load, inner ring speed, MXene additive content in grease and grease filling volume. Especially, the radial load and inner ring speed exhibit extremely significant effects, while the MXene additive content in grease (P < 0.05) has a significant influence on the friction coefficient of rolling bearing. The optimal condition for rolling bearing lubricated with MXene additives lubricating grease (MALG) achieves the lowest friction coefficient of 0.0049 under 1,000 rpm, 9 kN and 35% grease filling volume.

This study could offer reference solution for utilizing MXene nano-lubrication to fufill the demands of precision, heavy-load, or long-lifespan bearings. Furthermore, the lubrication approach has the potential to be expanded into aerospace, defense, and various industrial fields, thereby significantly promoting its practial engineering applications.

This study aims to investigate the configurational effects of five rules – artificial intelligence (AI)-based hiring decision transparency, consistency, voice, explainability and human involvement – on applicants' procedural justice perception (APJP) and applicants' interactional justice perception (AIJP). In addition, this study examines whether the identified configurations could further enhance applicants' organisational commitment (OC).

Drawing on the justice model of applicants' reactions, the authors conducted a longitudinal survey of 254 newly recruited employees from 36 Chinese companies that utilise AI in their hiring. The authors employed fuzzy-set qualitative comparative analysis (fsQCA) to determine which configurations could improve APJP and AIJP, and the authors used propensity score matching (PSM) to analyse the effects of these configurations on OC.

The fsQCA generates three patterns involving five configurations that could improve APJP and AIJP. For pattern 1, when AI-based recruitment with high interpersonal rule (AI human involvement) aims for applicants' justice perception (AJP) through the combination of high informational rule (AI explainability) and high procedural rule (AI voice), there must be high levels of AI consistency and AI voice to complement AI explainability, and only this pattern of configurations can further enhance OC. In pattern 2, for the combination of high informational rule (AI explainability) and low procedural rule (absent AI voice), AI recruitment with high interpersonal rule (AI human involvement) should focus on AI transparency and AI explainability rather than the implementation of AI voice. In pattern 3, a mere combination of procedural rules could sufficiently improve AIJP.

This study, which involved real applicants, is one of the few empirical studies to explore the mechanisms behind the impact of AI hiring decisions on AJP and OC, and the findings may inform researchers and managers on how to best utilise AI to make hiring decisions.

Drawing on social information processing theory, this study investigates how platform leadership influences employees’ innovative behavior. Specifically, we propose a theoretical model that incorporates creative self-efficacy as a mediator and organizational identification as a moderator.

Multisource data were collected in three waves from 304 employees and their 65 leaders in China.

Hierarchical linear modeling (HLM) results reveal: (1) a positive association between platform leadership and subordinates’ innovative behavior; (2) creative self-efficacy as a mediator in the relationship between platform leadership and subordinates’ innovative behavior and (3) organizational identification as a moderator in the indirect relationship between platform leadership and subordinates’ innovative behavior through creative self-efficacy, with the indirect effect being stronger when organizational identification is high than when it is low.

From a cross-level perspective, our findings revealed the underlying mechanisms and boundary conditions under which platform leadership influences followers’ innovative behavior.

This study aims to provide empirical evidence to verify the dimensional structure of artificial intelligence (AI) Chatbot quality and examine the impact of these dimensions on consumer satisfaction and brand advocacy among Gen Z in the fast food industry in Egypt.

The empirical data was obtained with an electronic self-administered survey instrument from 397 young consumers who had prior experience using AI Chatbots across multiple fast food brands in Egypt. Structural equation modeling was used to analyze the formulated hypotheses.

The results showed that AI Chatbot quality dimensions, specifically information authenticity and system compliance, significantly enhance young consumers’ satisfaction. In addition, information authenticity of AI Chatbot quality was observed to wield a significant influence on young consumers’ advocacy. In contrast, an insignificant relationship was noticed between satisfaction and advocacy. Moreover, the mediating role of consumer satisfaction was not established.

Given that Gen Z is more technology savvy and computer literate, marketers and practitioners of fast food brands should invest in AI tools to respond to young consumers’ expectations and improve their perception of their services.

This study uses stimulus-organism-response theory to understand the mediating effect of young consumers’ satisfaction in the relationship between AI Chatbot quality and consumer brand advocacy within the fast food industry. Also, it introduced two novel main constructs of AI Chatbot quality, namely, information authenticity and system compliance.