Examining user information disclosure on artificial intelligence-generated content platforms: A privacy calculus perspective

As a negative behavior, user discontinuance may undermine user retention and reduce the competitive advantage of generative AI platforms. Extant research has focused on the positive behaviors such as user adoption and continuance of generative AI, and has seldom explored the formation mechanism underlying user discontinuance of generative AI. The purpose of this research is to explore generative AI user discontinuance intention from a dual perspective of enablers and inhibitors. We used a mixed method of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to conduct data analysis. The results revealed that discontinuance intention is influenced by both the enablers (misinformation, algorithm bias, low transparency, and dissatisfaction) and the inhibitors (perceived anthropomorphism, perceived intelligence, perceived interactivity, and flow experience). The results contribute to a comprehensive understanding of generative AI user discontinuance. They also suggest that generative AI platforms need to be concerned with both enablers and inhibitors in order to prevent user discontinuance and ensure a sustainable development.

Examining generative AI user addiction from a C-A-C perspective

As a passive information behavior, information avoidance (IA) may undermine the sustainable development of social media platforms. Previous research has focused on the enabling effect of negative cognitions and emotions on IA, and has seldom considered the inhibitors of IA. This research tries to fill the gap by integrating a dual perspective of both enablers and inhibitors. Drawing on the cognitive dissonance theory (CDT) and psychological empowerment theory (PET), this research examined social media users’ IA. We adopted a mixed method of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to conduct data analysis. The results showed that social support (SS) and information quality (IQ) affect psychological empowerment (PE), which further inhibits IA. In contrast, social comparison (SC), and perceived overload (PO) affect cognitive dissonance, which leads to IA. The fsQCA results found three paths that trigger users’ IA. The results imply that social media platforms need to mitigate cognitive dissonance and enhance PE in order to prevent users’ IA. This research contributes to a comprehensive understanding of the development process of IA. The limitation is that the results need to be generalized to other samples, such as the elderly.

PurposeThis article aims to investigate the influence of generative AI (GAI) use on digital performance (DP) from its formation and boundary mechanisms, as well as to further reveal specific solutions that achieve a high level of DP.Design/methodology/approachUsing social support (SS) theory, this article proposes a research model and then adopts a hybrid method of partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to analyze 304 questionnaire data in China.FindingsThe results indicate that (1) GAI used for work and social positively influences SS, which in turn enhances DP. In particular, informational support exerts a greater effect on digital-enabled task performance. Emotional support exerts a greater effect on digital-enabled innovative performance. (2) Innovative culture (IC) strengthens the effect of GAI used for work on informational support and emotional support, as well as the effect of GAI used for social and emotional support. (3) Four solutions lead to a high level of digital-enabled task performance, and three solutions lead to a high level of digital-enabled innovative performance.Originality/valueFor academics, this article adopts a hybrid method to illustrate the relationship between GAI used for various purposes and different types of DP from the formation mechanism of SS and the boundary mechanism of IC, as well as to reveal the synergistic effect of GAI use, SS and IC on DP. For practices, this article provides managers with insights to increase DP regarding employee training and organizational culture building.

Short video storytelling has become an important channel for destination marketing. However, how to take advantage of short video storytelling to enhance festival attractiveness is unclear. Based on narrative transportation theory, this study analysed 494 questionnaires through the hybrid exploration method of structural equation model (SEM) and fuzzy-set qualitative comparative analysis (fsQCA), to deeply explore the mechanism and conditional configuration of short video storytelling affecting festival attractiveness. The findings reveal that the effect of short video storytelling on festival attractiveness is significant, and partly mediated by narrative transportation. Moreover, compared with future-oriented people, present-oriented people are more likely to immerse themselves in short video storytelling and be attracted by festivals. Additionally, novelty, a core condition for high festival attractiveness, significantly strengthens the effects of storytelling and narrative transportation on attractiveness. Overall, this study expands the theoretical knowledge of short video storytelling in festival marketing and supports destination managers to formulate effective short video marketing strategies for destination festivals.

As a passive behavior, intermittent discontinuance may lead to user defection and undermine the continuous development of generative artificial intelligence. From a cognition-affect-conation perspective, this research examined the enablers and inhibitors of generative AI user intermittent discontinuance. We adopted a mixed method of structural equation modeling and fuzzy-set qualitative comparative analysis. The results indicated that privacy concern and information hallucination influence cognitive dissonance, which further leads to intermittent discontinuance. In contrast, perceived intelligence, anthropomorphism, and personalization influence affective commitment, which prevents intermittent discontinuance. The results imply that generative AI companies need to be concerned with both cognitive dissonance and affective commitment in order to prevent user intermittent discontinuance.

Viral effects of social network and media on consumers’ purchase intention

PurposeCompensatory consumption focuses on the psychological value of products. Special agricultural products have symbolic and social functions that effectively meet psychological needs and stimulate compensatory consumption behavior. The social commerce context not only enriches consumer experience but also influences consumer purchase decisions. This study constructs a model based on the elaboration likelihood model (ELM) and the stimulus-organism-response (SOR) theory to explore the mechanism of compensatory consumption behavior of special agricultural products in a social commerce context.Design/methodology/approachThis study uses a two-stage method of partial least squares structural equation model (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to analyze 523 valid samples collected through random sampling. PLS-SEM was used to examine the relationships and effects between the variables; fsQCA was used to conduct a cohort analysis between the variables to further reveal the complexity and diversity of compensatory consumption behaviors.FindingsPLS-SEM indicates that product attributes and social affordances influence consumers’ triggering of compensatory consumption behavior for control and belongingness needs. fsQCA shows that there are three different modes, and the satisfaction of belongingness or control needs is a necessary condition for triggering compensatory consumption behavior.Originality/valueThere is limited research on compensatory consumption behavior specifically focused on special agricultural products. This study explores the influencing factors and mechanisms of compensatory consumption behavior related to special agricultural products. The occurrence of compensatory consumption behavior is not only influenced by product attributes but also by the social commerce environment. In marketing strategies, it is important to not only consider product characteristics but also pay attention to consumers’ social and psychological needs.

PurposeThis study aims to investigate the relationship between patient satisfaction (PS) and the parameters in healthcare and supply chain management (HLSCM).Design/methodology/approachThe structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) method have been employed to identify correlation and possible configuration of causal factors that influence PS, including lack of resilience (LS), lack of visibility (LV), cost management (CM) and integration and interoperability (II).FindingsThe results from SEM confirmed that PS is highly correlated with lack of visibility, CM and II as critical parameters. Moreover, fsQCA findings state that the configuration of high levels of both resilience and lack of visibility, as well as high levels of II, are crucial for PS.Research limitations/implicationsThe researchers also identified the configuration of factors that lead to low PS. The study’s results could assist healthcare providers in improving their supply chain operations, resulting in more effective and efficient healthcare service delivery and ultimately improving PS.Originality/valueThe fsQCA method used in the study provides a more nuanced understanding of the complex interplay between these factors. The inclusion of supply chain management characteristics as parameters in the evaluation of PS is a novel aspect of this research. Previous studies largely focused on more traditional factors such as physical care, waiting times and hospital amenities. By considering supply chain management factors, this study provides insights into an under-explored area of PS research, which has important implications for healthcare providers looking to improve their operations and PS.

Explaining consumer implementation intentions in mobile shopping with SEM and fsQCA: Roles of visual and technical perceptions

The digital transformation of Chinese construction enterprises is crucial for achieving sustainable and high-quality development in the construction industry. However, there is still a lack of in-depth research on the impact mechanism of digital transformation in construction enterprises. The purpose of this study is to explore the multiple influencing factors and complex causal relationships of digital transformation in construction enterprises and promote the deep integration of digitalization and construction enterprises. To this end, based on the dual-effect perspective (net effect perspective of a single influencing factor and configuration effect perspective of multiple influencing factors), using the “technology–organization–environment” framework (TOE framework) to construct a research model of influencing factors for digital transformation in construction enterprises. A sample of 236 construction enterprise managers was surveyed, and partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) methods were used to empirically analyze the dual effects of influencing factors for digital transformation in construction enterprises. The results show that: (1) from the net effect perspective, there are seven factors that significantly impact digital transformation in construction enterprises; (2) from the configuration effect perspective, there are three paths that can achieve high-level digital transformation in construction enterprises, and one path that leads to low-level digital transformation; (3) from the dual-effect perspective, top management support and policy support are key factors for digital transformation in Chinese construction enterprises. The research results enrich the relevant research on digital transformation in construction enterprises and provide a reference basis for promoting digital transformation in construction enterprises.

Invented by the sociologist Charles Ragin in the 80 to identify the configurations explaining a phenomenon, the Qualitative Comparative Analysis (QCA) method has been used in management sciences since mid of years 2000s. Research in management information systems seems to be an exception, with rare papers that appeared recently. However, this method offers several advantages to explore aspects, like equifinality, causal complexity, sensitivity to outliers and attention to the limited diversity of observed configurations. The aim of this paper is to present the features, benefits and limitations of this method for research in IS and an illustration of fuzzy-set QCA, one of the two main versions of QCA. This variant of the method is applied to the issue of the contribution of Product Lifecycle Management (PLM) to respect the planned development time in the co-development of new products. QCA method identifies necessary and sufficient conditions for a result. In the illustration, we identified five possible configurations for a good respect of development time. In particular, we have highlighted a configuration where the use of the three PLM sub-systems is sufficient for a good respect of development time. QCA method is used to address the causal complexity notably through equifinality and the management of asymmetric configurations for a positive and negative result.

PurposeThis paper proposes that the trade-off between medical benefits and privacy concerns among mHealth users extends to their disclosure intentions, manifested as individuals simultaneously holding intentions to tend to disclose in the near future and to reduce disclosure in the distant future. Consequently, this paper aims to explore the privacy decision-making process of mHealth users from the perspective of a dual trade-off.Design/methodology/approachThis paper constructs the model using the privacy calculus theory and the antecedent-privacy concern-outcome framework. It employs the construal level theory to evaluate the impact of privacy calculus on two types of disclosure intentions. The study empirically tests the model using a data sample of 386 mHealth users.FindingsThe results indicate that perceived benefits positively affect both near-future and distant-future disclosure intentions. In contrast, perceived risks just negatively affect distant-future disclosure intention. Additionally, perceived benefits, near-future and distant-future disclosure intentions positively affect disclosure behavior. The findings also reveal that privacy management perception positively affects perceived benefits. Personalized services and privacy invasion experience positively affect perceived benefits and risks, while trust negatively affects perceived risks.Originality/valueThis paper considers the trade-off in the privacy calculus phase as the first trade-off. On this basis, this trade-off will extend to the disclosure intention. The individuals’ two times of trade-offs between privacy concerns and medical benefits constitute the dual trade-off perspective. This paper first uses this perspective to explore the privacy decision-making process of mHealth users. This paper employs the construal level theory to effectively evaluate the impact of privacy calculus on both disclosure intentions in mHealth, extending the theory’s applicability. Moreover, we introduce antecedents of privacy calculus from the perspectives of platform, society, and individuals, enhancing the study’s realism. The research findings provide a basis for mHealth platforms to better cater to users’ privacy needs.

LBS(Location-Based Service) is one of the smartphone application services which has been receiving great attention recently. Various applications of smartphone use LBS to provide innovative services. However, use of LBS raises privacy concerns because the location information of users is constantly exposed. Privacy calculus perspective attempts to understand the characteristics of the user's privacy. It is based on the risk-benefit analysis in the economics' perspective. That is, when the benefit expected through personal information disclosure is higher than risk, we are willing to provide personal information. This research suggested a research model based on the privacy calculus perspective to clarify the effect of information disclosure intention of smartphone LBS application users. Based on the main factors of privacy calculus, perception of privacy risk and privacy benefit, the relationship of the perceived value and the information disclosure intention was empirically analyzed by utilizing structural equation modeling(SEM) methodology. According to the results of the empirical analysis, it was found that all relations have statistically significant explanatory power except the relation between privacy concern and information disclosure intention. This study showed a strong evidence of antecedent factors based on privacy calculus of personal information disclosure in smartphone LBS applications.

Cultural heritage virtual tourism offers users a novel digital heritage experience, becoming an essential channel for cultural dissemination and preservation. However, how to stimulate users’ continuous behavioral intention remains unresolved. This study integrates the Stimulus–Organism–Response theory (SOR) and experience economy theories to construct a comprehensive model, exploring factors influencing users’ continuous intentions in cultural heritage virtual tourism. By analyzing data from 451 valid questionnaires through structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) methods, several key findings emerged. The SEM results show that (1) esthetics, entertainment, escapism, education, and connection experiences all positively affect perceived value and satisfaction; (2) except for escapism, other experiences positively influence cultural identity; and (3) perceived value, satisfaction, and cultural identity significantly impact continuous intention. The FsQCA results show that (1) in high continuous intention scenarios, perceived value, satisfaction, and cultural identity are core conditions, while esthetics, entertainment, escapism, education, and connection act as supporting conditions, enhancing users’ willingness to continue engaging under different configurations; (2) in low continuous intention cases, the absence of escapism, satisfaction, cultural identity, education, esthetics, and connection weakens users’ virtual tourism experiences, leading to a decline in continuous usage intentions. This study provides theoretical and practical insights for promoting users’ continuous intentions in cultural heritage virtual tourism.