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The demand for over-the-top (OTT) video streaming services has grown manifold in the last few years. With increasing competition in the OTT market, it is vitally important for businesses to understand OTT retail consumers' continuance intentions. This study aims to understand the antecedents of the continuance intention of OTT platforms and distinguish the most essential and best-performing predictor variables of continuance intention.

The study employs an integrated research model based on the theory of planned behavior (TPB), flow theory and habit. Data collected from OTT retail consumers (n = 383) using the online survey method are analyzed using partial least squares structural equation modeling.

The results elucidated which TPB antecedents and dimensions of flow experience affect OTT platforms' continuance intention. The most important factors affecting continuance intention were habit, attitude and perceived behavioral control, while the best-performing factors were perceived behavioral control, perceived enjoyment and attitude.

The study is unique in harmoniously integrating conscious cognitive intention, intrinsic motivation and habit of performing an activity to explain OTT platforms' continuance intention.

The concept of ubiquitous assimilation in e-commerce, denoting the seamless integration of technologies into customer shopping experiences, has played a pivotal role in aiding e-satisfaction and, consequently, fostering patronage intention. Among these, text-based chatbots are significant innovations. In light of this, the paper aims to develop a conceptual framework and comprehend the patronage behaviour of artificial intelligence-enabled chatbot users by using chatbot usability cues and to determine whether the social presence and flow theories impact e-satisfaction, which leads to users’ patronage intention. The current research provides insights into online travel agencies (OTAs), a crucial segment within the travel and tourism sector. Given the significance of building a loyal clientele and cultivating patronage in this industry, these insights are of paramount importance for achieving sustained profitability and growth.

The research framework primarily focused on the factors that precede e-satisfaction and patronage intention among chatbot users, which include social presence, flow, perceived anthropomorphism and need for human interaction. The researchers collected the data by surveying 397 OTA chatbot users by using an online questionnaire. The data of this cross-sectional study were analysed using covariance-based structural equation modelling.

Findings reveal that e-satisfaction is positively linked with patronage intention and the variables of social presence and flow impact e-satisfaction along with chatbot usability cues. There were direct and indirect relations between chatbot usability and e-satisfaction. Moreover, the personal attributes, “need for human interaction” and, “perceived anthropomorphism” were found to moderate relations between chatbot usability cues, social presence and flow.

The impact of chatbot’s usability cues/attributes on e-satisfaction, along with perceived attributes – social presence and flow in the realm of OTAs contributes to the human–chatbot interaction literature. Moreover, the interacting effects of perceived anthropomorphism and the need for human interaction are unique in the current contextual relations.

Virtual reality (VR) offers unprecedented immersion and interactivity in education, and working and learning from home have become the norm during the COVID-19 pandemic. This study empirically investigated the factors affecting the use of a VR online learning system (VROLS).

To explore factors affecting users’ continuance behavioral intentions toward using VROLSs, a research framework was formed comprising factors that constitute benefits (i.e. pull factors) and costs (i.e. push factors); these factors included perceived value, flow and social influence. The data for this study were collected via online survey questionnaires. A total of 307 valid responses were used to examine the hypotheses in the research model, employing structural equation modeling (SEM) techniques.

Perceived value, flow experience and the number of peers using VR primarily affect the decision to adopt a VROLS. The pull factors of spatial presence, entertainment and service compatibility, along with the push factors of complexity and visual fatigue, affect perceived value. Therefore, we conclude that perceived value is a primary factor positively influencing both flow experience and the decision to adopt the service.

This study contributes to a theoretical understanding of factors that explain users’ intention to use VROLSs.

This study aims to integrate the social cognitive theory and flow theory to examine how e-skills self-efficacy (ESSE) and trust-building self-efficacy (TBSE) impact work-related flow in remote work. It also explores how work-related flow (WOLF) mediates the connection between these factors and employee resilience (ER) in the context of the growing shift toward remote work.

The study tested an empirical mediation model with 535 remote workers from Indian organizations that adopted remote work either before or during the pandemic. Hypotheses were tested using Hayes’ PROCESS macro.

The study confirmed the direct influence of ESSE and TBSE on WOLF. Moreover, a mediation analysis demonstrated that WOLF significantly mediates the association linking ESSE, TBSE and ER.

This study, evaluating experienced remote employees in the quaternary sector, offers data-driven insights for informed organizational decisions. These findings aims to guide HR and training departments in formulating recruitment and training strategies, emphasizing digital skill development to enhance knowledge and skills effectively.

This study highlights the need for remote workers and organizations to be aware of the challenges of remote work. It is among the first to explore the link between ESSE, TBSE and ER, addressing psychological factor, i.e. WOLF, often overlooked in organizational contexts.

This study compares the motives of holding cash between developed (Australian) and developing (Malaysian) financial markets.

For the period 2006–2020, the t-test, fixed-effect and generalised method of moment (GMM) model have been applied to a sample of 1878 (1,165 Australian and 713 Malaysian) firms.

The empirical results reveal that firms in developed financial markets hold higher cash compared to the developing financial markets. The findings confirm that motives to hold cash differ between developed and developing financial markets. The GMM findings further show that cash holdings (CH) in Australia are higher due to higher ratios of cash flow, research and development (R&D) and return on assets (ROA), and lower due to larger dividend payments. In the Malaysian market, however, cash flows and R&D are ineffectual, ROA falls and dividend payments rise CH.

The study helps managers, practitioners and investors understand that firms' distinct economic, institutional, accounting and financial environments are important. To attain the desired outcomes, they must thus comprehend and consider these considerations while developing suitable liquidity strategies.

To the authors' best knowledge, this is the initial research demonstrating how varied cash motives and their ramifications are in developed and developing financial markets. Therefore, this study identifies the importance that CH motives varied among financial markets and that findings from a particular market cannot be generalised to other markets because of the market and financial structural variations.

Grounding on the goal-setting theory and flow theory, this study explored the mechanism underlying the association between transfer design (TD); identical elements and training transfer (TT). Specifically, the authors explored a moderated mediation process of trainer performance and motivation to improve work through learning (MTIWL) that has received less consideration in the TT literature.

Data were collected using the retro-perspective survey method. The first survey was administered offline (t1: the day when leadership intervention was completed. Subsequently, trainees were requested to participate in an online survey (t2: 12–14 weeks later). In all, 355 executives participated.

The results of structural equation modeling (SEM) analyses suggested that trainees’ MTIWL mediational impact between leadership intervention triggers (transfer design and identical elements), and TT was supported. In addition, the indirect impact of these variables on TT was found to be significant when the trainer had high performance than when it was low. This confirmed the trainer’s performance as a potential moderator in the TT process.

This study is limited to the exploration of leadership intervention variables on TT. The findings have implications for leadership professionals and scholars who use leadership intervention and motivation metrics to predict TT.

This study offers a moderated mediation mechanism for enhancing TT through leadership intervention triggers. The proposed conceptual model included MTIWL as mediator and trainer performance during leadership intervention as moderator.

In the competitive realm of destination branding, understanding the factors that lead tourists to develop a deep emotional connection with a destination’s brand is essential. At the heart of this emotional bond lies destination brand love – an exceptionally profound sentiment transcending mere satisfaction or preference. This concept has recently garnered attention from both tourism academia and industry practice. However, there remains a void in exploring the factors and mechanisms that pave the way for tourists to develop deep affection for a destination’s brand. This study examines the influences of self-congruence and destination immersion on destination brand love. In addition, the linkages from the four facets of self-congruence to destination brand love via the mediating role of destination brand immersion are also scrutinized.

With data collected from 421 tourists in Vietnam, the partial least squares structural equation modeling (PLS-SEM) approach was applied to test the research model and hypotheses.

The results reveal that (1) ideal and ideal social self-congruence impact destination brand love, (2) all four facets of self-congruence impact destination brand immersion and (3) there is an indirect effect of the four facets of self-congruence on destination brand love, mediated by destination brand immersion.

The study’s findings provide evidence that destination characteristics must be symbolic of the destination brand and consistent with its image among tourists, which is essential in understanding the complex behavior of tourists. Indeed, the results indicate that facets of self-congruence significantly influence both destination brand immersion and destination brand love. Therefore, destination marketers should develop marketing strategies that emphasize personal relevance to the tourist destination to increase their sympathy and love for the destination.

Adapting self-congruence theory and the psychology of flow theory, this study presents a model that elucidates both the direct and indirect relationships among the four facets of self-congruence: destination brand immersion and destination brand love based on the aspects of congruence between tourists and destinations. From this, it helps to explore the factors and mechanisms that pave the way for tourists to develop deep affection for a destination’s brand.

The study aims to explore the digital fashion trend within the Metaverse, characterized by non-fungible tokens (NFTs), across Twitter networks. Integrating theories of diffusion of innovation, two-step flow of communication and self-efficacy, the authors aimed to uncover the diffusion structure and the influencer's social roles undertaken by social entities in fostering communication and collaboration for the advancement of Metaverse fashion.

Social network analysis examined the critical graph metrics to profile, visualize, and cluster the unstructured network data. The authors used the NodeXL program to analyze two hashtag keyword networks, “#metaverse fashion” and “#metawear,” using Twitter API data. Cluster, semantic, and time series analyses were performed to visualize the contents and contexts of communication and collaboration in the diffusion of Metaverse fashion.

The results unraveled the “broadcast network” structure and the influencers' social roles of opinion leaders and market mavens within Twitter's “#metaverse fashion” diffusion. The roles of innovators and early adopters among influencers were comparable in collaborating within the competition venues, promoting awareness and participation in digital fashion diffusion during specific “fad” periods, particularly when digital fashion NFTs and cryptocurrencies became intertwined with the competition in the Metaverse.

The study contributed to theory building by integrating three theories, emphasizing effective communication and collaboration among influencers, organizations, and competition venues in broadcasting digital fashion within shared networks. The validation of multi-faceted Social Network Analysis was crucial for timely insights, highlighting the critical digital fashion equity in capturing consumers' attention and driving engagement and ownership of Metaverse fashion.

About 70% of all aircraft accidents are caused by human–machine interaction, thus identifying and quantifying performance shaping factors is a significant challenge in the study of human reliability. An information flow field model of human–machine interaction is put forward to help better pinpoint the factors influencing performance and to make up for the lack of a model of information flow and feedback processes in the aircraft cockpit. To enhance the efficacy of the human–machine interaction, this paper aims to examine the important coupling factors in the system using the findings of the simulation.

The performance-shaping factors were retrieved from the model, which was created to thoroughly describe the information flow. The coupling degree between the performance shaping factors was calculated, and simulation and sensitivity analysis are based on system dynamics.

The results show that the efficacy of human–computer interaction is significantly influenced by individual important factors and coupling factors. To decrease the frequency of accidents after seven hours, attention should be paid to these factors.

The novelty of this work lies in proposing a theoretical model of cockpit information flow and using system dynamics to analyse the effect of the factors in the human–machine loop on human–machine efficacy.

Digital natives constitute a substantial part of consumers nowadays. Yet, a theoretical understanding of the factors driving their engagement with new-age digital services is lacking. This study therefore aims to examine digital natives’ continuance usage of the proliferating over-the-top (OTT) services. To address these objectives, the study uses a comprehensive model that primarily integrates perceived value, cognitive absorption and customer brand engagement theories.

Data were collected using an online personal questionnaire targeting active digital natives OTT service users using the online software tool SurveyMonkey. A sample of 1,415 digital natives was analysed using structural equation modelling.

The findings indicated that continuance usage is predicted by all three theories. The results illustrate that cognitive absorption and customer brand engagement are the most critical in enhancing continuance usage. Gender effects on digital natives’ value perceptions were found. The model explains 57% of the variance in users’ continuance usage.

The study adds valuable contributions to the existing literature that are relevant to digital natives’ engagement with new-age digital services. The proposed integrated model and the role of gender in value formations provide managers with novel insights when designing effective strategies to increase continuance usage for the largest consuming generation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2022-0133