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In the vibrant world of social commerce (SC), where information flows freely, interactions thrive and online purchases abound, there is an escalating challenge. Users are uninstalling and disengaging due to approach and avoidance stimuli, a trend mirroring the approach-avoidance motivation model (AAMM). Our study, anchored in AAMM and the stimulus-organism-response (SOR) model, aims to dive into the complex dynamics of these factors that shape users' SC continuance intentions.

Our findings, drawn from 472 SC users in Malaysia, paint an intriguing research framework via PLS-SEM analysis by testing the proposed hypotheses. A purposive sampling technique was utilized, deliberately selecting respondents based on specific criteria. Subsequently, data were gathered through the distribution of face-to-face questionnaires at selected shopping malls, facilitating a focused and comprehensive exploration of consumer perspectives.

The empirical results demonstrate the following: (1) Users' determination to stay engaged on SC platforms hinges on approach factors, like emotional support, surveillance gratification and multisensory gratification. (2) Simultaneously, avoidance factors such as technostress and perceived deception exert their negative influence. (3) Flow experience, rooted in flow theory, emerges as the underlying mechanism connecting these duality stimuli, influencing the continuance intention.

In a departure from conventional research, our study pioneers a comprehensive approach and boldly confronts the research gap by introducing a rich tapestry of antecedents, embracing both the appeal of approach factors and the deterrence of avoidance ones, using the AAMM that sheds light on how individuals navigate between embracing opportunities and avoiding pitfalls based on perceived gains and losses. This holistic approach enables us to redefine our understanding of digital engagement dynamics, offering a captivating journey into the realm of user experience and intention that transcends the ordinary.

Digital platforms transform supply chains. However, no unified theoretical understanding of digital platforms exists. Thus, the underlying research aims at investigating platform theories for supply chain management tasks.

The authors conduct a systematic literature review to identify relevant theories in the context of digital platforms and synthesize the respective findings for supply chain management tasks.

In total, 43 papers and 41 different relevant theories are identified. The most prominent theories are the resource-based view, transaction cost economics, internalization theory and the dynamic capabilities approach. Digital platforms alter and change the boundary decisions of firms. Therefore, they have various implications for supply chain management tasks such as make-or-buy decisions or the orchestration of resources to sustain a competitive advantage.

The identified supply chain theories as well as platform theories and their overlap provide a meaningful starting point for discussing and developing new and platform-based supply chain management approaches in the B2B domain.

The conducted systematic literature review provides a first starting point for building a holistic theoretical approach to digital platforms in supply chains. Thus, the paper contributes a missing link for discussing digital platforms and their theoretical foundations for supply chain management tasks.

The purpose of this manuscript is to investigate the influence of the satisfying of plane strain conditions on the prediction of the localized necking and to evaluate this effect by the different hardening models.

High-order anisotropic Drucker yield function, two types of hardening models, namely Hollomon power and Voce saturated, and the modified maximum force criterion (MMFC) are employed to predict the forming limit strains of AA3104-H19 alloy. Two identification methods, namely conventional and plane strain constrained, are applied and forming limit diagrams of the material are predicted by the incorporation of the anisotropic Drucker criterion and the hardening models into the MMFC for both calibration methods.

The enhancement in the prediction accuracy of the forming limits provided by the implementation of the plane strain constrained method is strongly dependent upon the selected hardening model type in the MMFC. About 18% improvement in the prediction of the biaxial limit strains is provided via Hollomon power law hardening, whereas the opposite result is occurred in case that the Voce saturated hardening law is used, and the predictions match with the experimental data only in the plane strain point and its surroundings.

The plane strain constrained identification method precisely predicts the location of the plane strain point on the yield locus and also any yield stress or anisotropy coefficient in the plane strain state is not required during the calibration, therefore the method can reduce the number of the required experiments for the constitutive characterization, and it will be attractive for both academy and industry. Additionally, the improvement in the prediction of the biaxial forming limits can be provided by applying of this method along with the appropriate hardening law.

Fluid flows through rotatory disks are encountered in industrial and practical engineering processes, such as computer storage devices, gas turbine rotators, rotating machinery, air cleaning machines, etc. The primary purpose of this research is to examine the combined aspects of variable electrical conductivity, thermal radiation, Soret and Dufour effects on a magnetohydrodynamic Maxwell single-walled carbon nanotubes–graphene oxide–multi-walled carbon nanotubes–copper (SWCNT–GO–MWCNT–Cu)/sodium alginate tetra-hybrid nanofluid flow through a stretchable rotatory disk.

The modeled administrative equations of the present flow problem are converted to a non-dimensional system of ordinary differential equations by applying suitable similarity conversion and then solved numerically by implementing the bvp4c method. The impressions of noteworthy dimensionless parameters on velocity, temperature, concentration distributions, Nusselt number, skin friction and Sherwood number are reported via graphs and tables.

The authors figured out that the developed values of the rotation parameter diminish the temperature but enhance both the radial and angular velocities. Further, the mass and heat transmission rates are better for tetra-hybrid nanofluids than for ternary and hybrid nanofluids.

The present study emphasizes a special type of fluid called the tetra-hybrid nanofluid. The existing literature has not discussed the Maxwell tetra hybrid nanofluid flow through a stretchable rotatory disk with variable electrical conductivity. Besides, the novel aspects of magnetohydrodynamics, thermal radiation, Soret and Dufour effects are also incorporated into the present flow problem.

The present study aimed to explore the consequences of perceived authenticity in artificial intelligence (AI) assistants and develop a serial-mediation architecture specifying causation of loyalty in human–AI relationships. It intended to assess the predictive power of the developed model based on a training-holdout sample procedure. It further attempted to map and examine the predictors of loyalty, strengthening such relationship.

Partial least squares structural equation modeling (PLS-SEM) based on bootstrapping technique was employed to examine the higher-order effects pertaining to human–AI relational intricacies. The sample size of the study comprised of 412 AI assistant users belonging to millennial generation. PLS-Predict algorithm was used to assess the predictive power of the model, while importance-performance analysis was executed to assess the effectiveness of the predictor variables on a two-dimensional map.

A positive relationship was found between “Perceived Authenticity” and “Loyalty,” which was serially mediated by “Perceived-Quality” and “Animacy” in human–AI relational context. The construct “Loyalty” remained a significant predictor of “Emotional-Attachment” and “Word-of-Mouth.” The model possessed high predictive power. Mapping analysis delivered contradictory result, indicating “authenticity” as the most significant predictor of “loyalty,” but the least effective on performance dimension.

The findings of the study may assist marketers to understand the relevance of AI authenticity and examine the critical behavioral consequences underlying customer retention and extension strategies.

The study is pioneer to introduce a hybrid AI authenticity model and establish its predictive power in explaining the transactional and communal view of human reciprocation in human–AI relationship. It exclusively provided relative assessment of the predictors of loyalty on a two-dimensional map.

The purpose of this paper is to explore the factors influencing the encountering information adoption of virtual live streaming from the perspective of the immersion experience. In addition, the paper aims to provide new theoretical perspectives and analytical frameworks for virtual live information behavior.

Based on a review of relevant literature and theories, a model of the encountering information adoption of virtual live streaming users is constructed. In order to complete the empirical study, two experiments and questionnaires have been designed to investigate the relationship between high and low immersion experiences. A total of 1,332 valid survey samples were collected and analyzed, utilizing the structural equation model. In order to delineate the regimes, Gradient Boosted Regression Tree (GBRT) and Lasso regression were further utilized.

The research findings indicate that users' immersion experience in virtual live streaming has a positive effect on perceived usefulness, trust, and commitment. Furthermore, perceived usefulness and trust have a positive effect on users' emotional arousal and enhance the content experience, while commitment has a negative effect on the content experience. The emotional arousal and content experience of users contribute to their encountering information adoption. The effect of immersion experience on encountering information adoption is partially mediated by perceived usefulness, trust, commitment, emotional arousal, and content experience. The relationship between content experience and encountering information adoption is moderated by digital literacy to a significant extent. In the context of virtual live streaming, the factors influencing users' encountering information adoption can be divided into three distinct regimes. The most significant factors affecting encounter information adoption are trust and commitment, which are located in the first regime. Emotional arousal and digital literacy are situated in the third regime, with the least significant influence on encountering information adoption.

This study constructs a model of virtual live streaming users' encountering information adoption and explores the formation mechanism of encountering information adoption from the perspective of immersion experience, which provides a new perspective for further understanding the influence of virtual live-streaming users' encountering information adoption.

Green financial technology (FinTech) has received attention for promoting green finance investment and sustainable development. However, how consumer social responsibility and long-term orientation influence the continuance intention of green FinTech users remains unknown in the literature. To fill this gap, consumer social responsibility and long-term orientation are combined with the unified theory of acceptance and use of technology to develop a research model to investigate their moderating effects on the continuance intention of green FinTech users.

A random probability sampling method was adopted, and 377 valid responses were collected to verify the proposed model. Partial least squares structural equation modeling was employed for the data analysis.

Performance expectancy, effort expectancy, social influence and facilitating conditions have significant positive impacts on the continuance intentions of green FinTech users. Surprisingly, consumer social responsibility enhances the effects of performance expectancy and social influence on continuance intention but negatively moderates the effect of facilitating conditions on continuance intention. Moreover, a long-term orientation can increase the impact of facilitating conditions on continuance intention but decrease the impact of performance expectancy on continuance intention.

This paper proposes a research model that reveals how consumer social responsibility and long-term orientation moderate the relationship between the unified theory of acceptance and use of technology (UTAUT) and the continuance intention of green FinTech users to fill a gap in the literature.

This study aims to understand the mechanisms driving individuals to utilise and engage in edu-business and contribute to the industry’s development, even when they face criticism. To that end, this paper, focussing on corporate stories, explores the cultural strategies education companies employ to expand their businesses overseas.

This paper examines the case study of Kumon Institute of Education, a key player in the Japanese edu-business sector. The analysis is based on interviews conducted between 2019 and 2021 with four public relations officers who possess extensive knowledge of the company’s history. Additionally, it draws on government and company documents, as well as newspaper articles. The analysis focusses on the narrative isomorphism between the company and the government from the provider’s perspective.

Kumon’s corporate stories and narratives have been shaped by the history, culture and policies of Japan, its country of origin, rather than adopting a bottom-up approach or embracing neoliberal values. As the company expanded its international reach, its Japanese identity became a cornerstone of its narrative, heightening the appeal of its stories through the use of expert discourse and historic cultural resources. Recently, a synergy has developed between the public and private sectors in the realm of education export, reinforcing the distinctly Japanese nature of the company, which is particularly appealing to both users and employees.

This paper focusses on the edu-business itself, analysing cultural strategies that go beyond the functional aspects of management or services to understand how edu-businesses have attracted people.

The primary focus of this study is to tackle a critical industry issue concerning energy inefficiency. This is achieved through an investigation into enhancing heat transfer in solar radiation phenomena on a curved surface. The problem formulation of governing equations includes the combined effects of thermal relaxation, Newtonian heating, radiation mechanism, and Darcy-Forchheimer to enhance the uniqueness of the model. This research employs the Cattaneo–Christov heat theory model to investigate the thermal flux via utilizing the above-mentioned phenomenon with a purpose of advancing thermal technology. A mixture of silicon dioxide (SiO_2)\ and Molybdenum disulfide (MoS_2) is considered for the nanoparticle’s thermal propagation in base solvent propylene glycol. The simulation of the modeled equations is solved using the Shifted Legendre collocation scheme (SLCS). The findings show that, the solar radiation effects boosted the heating performance of the hybrid nanofluid. Furthermore, the heat transmission progress increases against the curvature and thermal relaxation parameter.

Shifted Legendre collocation scheme (SLCS) is utilized to solve the simulation of the modeled equations.

The findings show that, the solar radiation effects boosted the heating performance of the hybrid nanofluid. The heat transmission progress increase against the curvature and thermal relaxation parameter.

This research employs the Cattaneo–Christov heat theory model to investigate the thermal flux via utilizing the above-mentioned phenomenon with a purpose of advancing thermal technology.

Using the residual dividend theory, this study examines the impact of capital expenditures and working capital on the dividend policies of publicly listed companies in Indonesia.

Using data on public companies (other than those in the financial sector) listed on the Indonesia Stock Exchange from 2011 to 2020, this study collected 870 observations (firm-years). This study employs a regression analysis technique using the STATA application program. The main variables in this study are capital expenditure and working capital, and the control variables are sales growth, firm size, leverage, profitability, liquidity and dummy variables for state-owned enterprises. The dependent variable of dividend policy is proxied by the dividend payout ratio.

This study’s results support the residual dividend theory’s hypothesis, in which capital expenditure negatively affects a company’s dividend policy. This study also analyzes this effect on companies that pay cash dividends at quantile positions of 25, 30, 50 and 60. The results show that the effect of capital expenditure on cash dividend payments is more pronounced in the case of companies whose cash dividends are in the 50th quantile. This result holds across different specification and endogeneity tests.

This study analyzes the residual dividend theory in Indonesian companies, focusing on localized factors and investment priorities. It challenges traditional Western dividend policies and provides empirical data that enhances the theory’s robustness. The findings have practical implications for investors, policymakers and corporate decision-makers in the Indonesian market.