Exploring the Impact of Sports and Fitness Live Streamer Attributes on Consumer Well-Being: Symmetric and Asymmetric Modeling Approaches

PurposeThis study aims to propose guidelines for the joint use of partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to combine symmetric and asymmetric perspectives in model evaluation, in the hospitality and tourism field.Design/methodology/approachThis study discusses PLS-SEM as a symmetric approach and fsQCA as an asymmetric approach to analyze structural and configurational models. It presents guidelines to conduct an fsQCA based on latent construct scores drawn from PLS-SEM, to assess how configurations of exogenous constructs produce a specific outcome in an endogenous construct.FindingsThis research highlights the advantages of combining PLS-SEM and fsQCA to analyze the causal effects of antecedents (i.e., exogenous constructs) on outcomes (i.e., endogenous constructs). The construct scores extracted from the PLS-SEM analysis of a nomological network of constructs provide accurate input for performing fsQCA to identify the sufficient configurations required to predict the outcome(s). Complementing the assessment of the model’s explanatory and predictive power, the fsQCA generates more fine-grained insights into variable relationships, thereby offering the means to reach better managerial conclusions.Originality/valueThe application of PLS-SEM and fsQCA as separate prediction-oriented methods has increased notably in recent years. However, in the absence of clear guidelines, studies applied the methods inconsistently, giving researchers little direction on how to best apply PLS-SEM and fsQCA in tandem. To address this concern, this study provides guidelines for the joint use of PLS-SEM and fsQCA.

The impact of voice assistants’ intelligent attributes on consumer well-being: Findings from PLS-SEM and fsQCA

Recently, IoV-based services and vehicles have come to the forefront as part of the growing market for the automobile industry. Since IoV-based services and vehicles were introduced, they have been expected to grow rapidly. However, contrary to optimistic expectations for future market growth, the IoV-based services and vehicles market has appeared to hit a roadblock and remains at an early market stage. Therefore, research of the determinants leading to consumers’ intention to accept and purchase IoV-based services and vehicles is significant for either academics or practitioners. Drawing upon the extended unified theory of acceptance and use of technology acceptance model (UTAUT2), the perceived risk theory, and the initial trust model, we developed an integrated conceptual model and explored what and how various determinant antecedent conditions fit together on consumer intention to accept IoV-based services and vehicles. The proposed model and hypotheses were assessed by both symmetric (partial least square structural equation modeling, PLS-SEM) and asymmetric (fsQCA) approaches using online survey datasets with 362 Chinese consumers. The findings suggest that PLS-SEM and fsQCA are complementary analytical techniques providing comparable results. PLS-SEM results indicate that performance expectancy, price value, habit, and initial trust have significant effects on behavioral intention to accept IoV services. Despite other determinants, e.g., effort expectancy, social influence, facilitating conditions, hedonic motivation, and perceived risk, have no significant effect. FsQCA results reveal twelve different configurations of determinants resulting in a high level of behavioral intention to accept IoV services, and eight causal paths equifinally leading to the negation of behavioral intention to accept IoV services. These findings suggest that several conditions that were not significant in PLS-SEM are sufficient conditions when combined with other conditions. This study enriches relevant research studies on IoV-based services acceptance and provides relevant insights and marketing suggestions for incentivizing consumers to accept the IoV-based services.

While adopting chatbots powered by artificial intelligence could enhance knowledge sharing, it also causes challenges due to the “dark side” of these agents. However, research on the factors influencing chatbots for knowledge sharing is lacking. To bridge this gap, we developed the integrated chatbot acceptance-avoidance model, which looks at the positive and negative determinants of using chatbots for knowledge sharing. Through a comprehensive questionnaire survey of 447 students, the research model is evaluated using the partial least squares-structural equation modeling (PLS-SEM), a symmetric approach, and fuzzy set qualitative comparative analysis (fsQCA) as an asymmetric approach. The PLS-SEM results supported the positive role of performance expectancy, effort expectancy, and habit and the negative role of perceived threats in affecting chatbot use for knowledge sharing. Although PLS-SEM results revealed that social influence, facilitating conditions, and hedonic motivation have no impact on chatbot use, the fsQCA analysis revealed that all factors might play a role in shaping the use of chatbots. In addition to the theoretical contributions, the findings provide several managerial implications for universities, instructors, and chatbot developers to help them make insightful decisions and promote the use of chatbots.

Participating in community leisure activities has become an important way for the public to pursue good health and a high quality of life. However, few studies have focused on the health and welfare effects of participating in urban leisure activities during the COVID-19 pandemic. In response to this gap in the literature, this study drew on the stimulus–organism–response (SOR) theory to examine the effects of community leisure on subjective well-being during the pandemic from the perspective of urban residents. A sample of 1041 urban residents in Beijing, China, was empirically analyzed by applying partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA). The PLS-SEM results revealed the net effects of the pandemic influence, leisure satisfaction, leisure environment, and community identity on subjective well-being. The fsQCA provided causal methods for realizing subjective well-being and a necessary condition analysis supplemented the necessary antecedents. The results showed that (1) higher levels of pandemic influence and leisure environment increased leisure satisfaction; (2) pandemic influence, leisure environment, and leisure satisfaction had a positive effect on community identity; (3) pandemic influence, leisure satisfaction, and community identity also combined with leisure environment and leisure time to positively influence subjective well-being; and (4) leisure satisfaction and community identity mediated the impacts of pandemic influence and leisure environment on subjective well-being. This paper contributes not only to empirical evidence but also to theory by constructing and enriching the research models of community leisure and subjective well-being. The practical implications for the public, community managers, and policymakers are also discussed.

In contrast to daytime leisure, the distinctive experiences of nighttime leisure and their effects on individuals’ subjective well-being remain inadequately examined. This study selects Chongqing as the research subject and uses 400 valid survey responses, applying Structural Equation Modeling (symmetric approach) and Fuzzy-Set Qualitative Comparative Analysis (asymmetric approach) to examine the symmetric and asymmetric impacts of nighttime leisure involvement on subjective well-being. The findings reveal the mediating roles of leisure experience and leisure benefits between nighttime leisure involvement and subjective well-being, while also identifying the significant moderating effect of the nighttime ambiance in this process. Additionally, the study identifies three combination pathways that promote high levels of subjective well-being in nighttime leisure contexts. This research not only enriches the theoretical literature on nighttime leisure but also provides new perspectives and strategies for optimizing the development of urban nighttime economies.

PurposeRecent literature in the field of car dashcams has called upon further investigation into the significance of e-word-of-mouth (e-WOM) in car dashcams. The purpose of this study is to investigate the antecedents’ impact on users’ e-WOM behaviour.Design/methodology/approachA purposive sampling technique was used to obtain responses from the 398 respondents through a five-point Likert scale. The hypotheses were verified through a hybrid model combining partial least squares structural equation modelling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) approaches.FindingsFindings indicated that perceived information quality, performance quality and resilience quality influenced users’ e-WOM behaviour, while perceived system quality did not. Additionally, users' pro-social orientation moderated the relationship between perceived system quality and e-WOM, while their novelty-seeking orientation moderated the relationship between perceived resilience quality and e-WOM. FsQCA provided deeper insights into e-WOM behaviour by revealing complex interactions among factors through various antecedent configurations, enhancing understanding of how to promote positive e-WOM.Practical implicationsThis study provides valuable insights for marketers, product designers and policymakers to customise products, marketing campaigns and policies to encourage dashcam usage and enhance road safety and driving behaviour.Originality/valueThis study explores e-WOM behaviour related to car dashcams, contributing to the growing empirical literature. It applies and extends the McLean and DeLone Information System Success model by incorporating performance quality (operational) and resilience quality (adaptability) to better understand factors influencing limited e-WOM on car dashcams.

The current study investigates the determinants of retention intentions among coaches. The study focuses on the effects of individual factors, namely psychological collectivism, felt obligation, and affective commitment, on retention intention and configurational combinations of individual factors causing high retention intention among coaches in Taiwan. Data were collected from 200 Taiwanese coaches through a questionnaire and subjected to partial least squares structural equation modeling (PLS-SEM) while complemented with fuzzy-set qualitative comparative analysis (fsQCA). The results of symmetric analysis (PLS-SEM) show that psychological collectivism positively influences felt obligation and affective commitment and indirectly influences retention intention through felt obligation and affective commitment, whereas both felt obligation and affective commitment are significantly associated with retention intention among Taiwanese coaches. The results of asymmetric analysis (fsQCA) provide five configurational models that explain the high levels of retention intentions, while felt obligation and affective commitment are found as necessary conditions in all five models. Meanwhile, psychological collectivism's four out of five sub-dimensions are considered both core and peripheral conditions depending on configurations, somewhat contrary to the prior studies. Most interestingly, the absence of goal priority, one of psychological collectivism's sub-dimensions, is considered a core condition for four of the five identified solutions. As such, fsQCA may allow us to capture the complex casualty that symmetric modeling may not capture. The complementary analysis between symmetric and asymmetric findings provides more insightful information about the effects of psychological collectivism, felt obligations, and affective commitment on retention intentions.

This study examines the antecedents that shape Generation Z users’ intentions to select niche tourism destinations on Douyin, considering gender differences and extending the Technology Acceptance Model (TAM) framework. Using data from 687 Chinese Generation Z participants, this study employs partial least squares structural equation modeling (PLS-SEM), multi-group analysis (MGA), and fuzzy-set qualitative comparative analysis (fsQCA) to offer further insights. The results of the symmetric methods indicate that social interaction, informativeness, and trust contribute to perceived usefulness. For Generation Z male users, perceived usefulness (β = 0.175, p < 0.004) and perceived playfulness (β = 0.202, p < 0.001) are key drivers of visit intention. In contrast, for Generation Z female users, visit intention is greatly impacted by perceived creativity (β = 0.312, p < 0.001), personalization (β = 0.241, p < 0.001), and perceived attractiveness (β = 0.295, p < 0.001). Notably, perceived ease of use does not significantly affect visit intention for either group. The fsQCA findings further show multiple causal pathways leading to high visit intention. The distinctive contribution of this study lies in its integration of symmetric and asymmetric analytical approaches to uncover gender-based mechanisms through which short video platforms shape travel decision-making. It also extends the applicability of TAM within the intersecting domains of tourism and social media.

PurposeConsumer satisfaction towards a brand is one of a firm’s important performance outcomes. However, building a strong green brand to foster consumers’ satisfaction is often challenging for firms. Drawing on the dynamic capability and mechanism-enabling perspectives of ambidexterity. The purpose of this research is to explore mechanisms of perceived brand performance and green trust through which green brand ambidexterity acts as a facilitator of consumer satisfaction.Design/methodology/approachThe hypothesized relationships were tested by both partial least squares structural equation modelling (PLS-SEM; symmetric approach) and fuzzy set qualitative comparative analysis (fsQCA; asymmetric approach) with data collected from a green consumer questionnaire survey in Hong Kong.FindingsThe results from PLS-SEM indicate that green brand ambidexterity affects consumer satisfaction through multiple mediating paths of perceived brand performance, green trust-consumer and the sequential integration of perceived brand performance and green trust. Results from fsQCA further reinforced these findings.Research limitations/implicationsThe present research provides a nuanced understanding of how ambidexterity enhances consumer satisfaction in the context of a green brand by identifying multiple mechanisms.Originality/valueThere is a lack of research on how green brand ambidexterity affects green brand outcomes from the perspective of value creation for consumers. The present research fills this gap by providing more comprehensive explanations of mechanisms for green brand ambidexterity to facilitate consumer satisfaction. It also offers a better understanding of how the effects of green brand ambidexterity are viewed on a path-dependency that is aligned with the dynamic capability perspective of ambidexterity and how green trust forms a critical path to enable green brand ambidexterity and perceived brand performance to enhance consumer satisfaction.

With the rapid expansion in the use of intelligent voice assistants (IVAs) in people's daily lives, how to improve users' continuous intention is crucial for the sustainable development of intelligent voice technology. Utilizing the stimulus-organism-response (S-O-R) framework, we propose a theoretical model to examine how three dimensions of interactivity (ie, two-way communication, responsiveness, perceived control) impact individuals' affective reactions (ie, psychological ownership, subjective well-being) and continuance intention of IVAs and how that effect differs technology readiness. To validate the proposed model, 412 valid samples were collected in China and underwent analysis using a comprehensive approach that incorporated partial least squares-structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The findings from the PLS-SEM analysis indicate that three dimensions of interactivity have significant impacts on affective reactions to varying degrees, thus affecting users' continuance intention. Among these dimensions, responsiveness is the strongest predictor of affective reactions. Additionally, the impact of subjective well-being on continuance intention is stronger when users with high technology readiness. Finally, the results from fsQCA support the PLS-SEM findings and provide three configurations with different combinations of antecedents that sufficiently explain high continuance intention. Our findings reveal the internal mechanisms through which the three dimensions of interactivity impact users' continued usage of IVAs. This study is among the first to examine the effects of dimensions of interactivity on behavioral intentions, utilizing both symmetric (PLS-SEM) and asymmetric (fsQCA) methodologies to identify the most significant dimensions of interactivity and determine sufficient combinations of dimensions to predict users' intention to continue using IVAs. These findings offer valuable and fresh insights for both theoretical understanding and practical application.

A brand’s perceived coolness enhances its appeal and can be crucial to brand success. Building on the model of goal-directed behaviour (MGB), this study investigates how the perceived coolness of Airbnb, influences consumers’ behavioural intentions regarding the platform. The proposed hypotheses were tested using partial least squares structural equation modelling (PLS-SEM). The study sample consisted of 557 U.S. travellers who had had an Airbnb accommodation experience in the past six months. Fuzzy-set qualitative comparative analysis (fsQCA) was subsequently employed to uncover the causal configurations of consumers’ desire and behavioural intentions toward Airbnb. The PLS-SEM results demonstrated the critical role of perceived coolness in influencing one’s desire and behavioural intentions toward Airbnb. The fsQCA findings suggested that causal configurations inform consumers’ behavioural intentions toward Airbnb across generations. Anticipated emotions applied to all configurations. This study extends the relevant literature by incorporating perceived coolness into the MGB model in the Airbnb context. Findings also contribute to the literature by revealing causal configurations via fsQCA. Airbnb providers should seek to develop and enhance the four identified facets of perceived coolness. The consumer market should also be classified generationally. The roles of anticipated emotions cannot be ignored.

The creativity of fitness coaches is crucial for maintaining the competitiveness of fitness enterprises. This study aimed to explore the factors, mechanisms, and moderating effects influencing the creativity of fitness coaches (n = 732) in Chinese fitness businesses, using partial least squares structural equation modeling (PLS-SEM) analysis. The results indicate that curiosity and sport commitment have a positive impact on knowledge-sharing and flow experience. In addition, knowledge-sharing and flow experience positively influence creativity. Importantly, the curiosity and sport commitment of fitness coaches affect creativity through knowledge-sharing and flow experience. Finally, social media usage positively moderates the relationship between knowledge-sharing and creativity. The findings of this study provide meaningful information and decision-making references for professionals in the fitness industry and academic researchers. Future efforts should emphasize the protection of fitness coaches' creative achievements, with policymakers encouraged to establish relevant legal frameworks to safeguard innovation within the industry.

Index

Although an increasing number of studies explore the factors influencing users’ privacy concerns regarding social robots, the existing understanding of this issue remains largely fragmented. Previous studies have mainly focused on the "net effect" between variables, leaving the complexity of causal configurations, and the holistic impact of design characteristics of social robots on user privacy concerns remains unclear. Based on the Stimuli-Organism-Response (S-O-R) framework and Communication Privacy Management Theory (CPMT), this study integrates social robot design characteristics such as Anthropomorphism, Warmth, Competence, and Transparency into causal configurations, and uses Perceived Privacy Risk and Perceived Privacy Control as mediating variables to propose a Comprehensive conceptual model. Based on valid data from a sample of 198 Chinese social robot users, this study conducted empirical analyses of the conceptual model using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (FsQCA). PLS-SEM results show that anthropomorphism, warmth, competence, and transparency are key factors influencing privacy concerns, and perceived privacy risk mediates the relationship between warmth, information transparency, and privacy concerns. The FsQCA results further validated the findings of PLS-SEM and identified five configurations of factor combinations that led to higher levels of user privacy concerns. Among them, the combination of high anthropomorphism design, high competence, and low warmth of social robots is the core configuration that leads to users’ privacy concerns. Overall, this study broadens our understanding of social robot users’ privacy concerns and reveals the causal complexity behind social robot users’ privacy concerns. It provides some theoretical and practical insights for subsequent scholars and designers.