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Although user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.

The authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.

The authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.

This study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.

The proliferation of smartwatches in the digital age has radically transformed health and fitness management, offering users a multitude of functionalities that extend beyond mere physical activity tracking. While these modern wearables have empowered users with real-time data and personalized health insights, their environmental implications remain relatively unexplored despite a growing emphasis on sustainability. To bridge this gap, this study extends the UTAUT2 model with smartwatch features (mobility and availability) and perceived security to understand the drivers of smartwatch usage and its consequent impact on environmental sustainability.

The proposed theoretical model is evaluated based on data collected from 303 smartwatch users using a hybrid structural equation modeling–artificial neural network (SEM-ANN) approach.

The PLS-SEM results supported smartwatch features’ effect on performance and effort expectancy. The results also supported the role of performance expectancy, social influence, price value, habit and perceived security in smartwatch usage. The use of smartwatches was found to influence environmental sustainability significantly. However, the results did not support the association between effort expectancy, facilitating conditions and hedonic motivation with smartwatch use. The ANN results further complement these outcomes by showing that habit with a normalized importance of 100% is the most significant factor influencing smartwatch use.

Theoretically, this research broadens the UTAUT2 by introducing smartwatch features as external variables and environmental sustainability as a new outcome of technology use. On a practical level, the study offers insights for various stakeholders interested in smartwatch use and their environmental implications.

The global emphasis on sustainability is driving organizations to embrace financial technology (Fintech) solutions as a means of enhancing their sustainable performance. This study seeks to unveil the intermediary role played by green finance and competitiveness, along with the moderating impact of digital transformation (DT), in the intricate relationship between Fintech adoption and sustainable performance.

Drawing on existing literature, we construct a comprehensive conceptual framework to thoroughly analyse these interconnected variables. To empirical validate of our model, a dual structural equation modelling–artificial neural network) SEM–ANN approach was employed, adding a robust layer of validation to our study’s proposed framework. A sample of 438 banking employees in Pakistan was collected using a simple random sampling technique, with 411 samples deemed suitable for subsequent analysis. Initially, data scrutiny and hypothesis testing were carried out using Smart-PLS 4.0 and SPSS-23. Subsequently, the ANN technique was utilized to assess the importance of exogenous factors in forecasting endogenous factors.

The findings from this research underscore the direct and significant influence of Fintech adoption and DT on the sustainable performance of banks. Notably, green finance and competitiveness emerge as pivotal mediators, bridging the gap between Fintech adoption and sustainable performance. Moreover, DT emerges as a critical moderator, shaping the relationships between Fintech adoption and both green finance and competitiveness. The integration of the ANN approach enhances the SEM analysis, providing deeper insights and a more comprehensive understanding of the subject matter.

This study contributes to the enhanced comprehension of Fintech, green finance, competitiveness, DT and the sustainable performance of banks. Recognizing the importance of amalgamating Fintech adoption, green finance and transformational leadership becomes essential for elevating the sustainable performance of banks. The insights garnered from this study hold valuable implications for policymakers, practitioners and scholars aiming to enhance the sustainable performance of banks within the competitive business landscape.

The countryside population has always been depended on the revenues earned from agricultural yields. These yields often suffer losses in the absence of coordination guidelines in the post-yield supply chains (PYSC). This study aims to identify, address and mitigate the post-yield supply chain impediments (PYSCIs) that lead to enormous amounts of waste and revenue losses. These are the parameters that require government and stakeholders’ attention for alleviation from losses.

Structural equation modelling (SEM) was performed to categorise the identified PYSCIs as “standard measures”. The motive for SEM results is to attract the stakeholders’ attention toward PYSCIs for business sustainability. The PYSCIs were clustered into three “standard measures” (i.e. strategic, tactical and operational measures) for revenue generation and reduced fresh produce spoilage in the countryside.

The SEM results suggest that the focus should be on revising minimum support prices and government support for initiatives, subsidy schemes and incentives at the strategic level. Tactical initiatives focus on linking markets including exports, research and development, attitude towards certification, value addition process adoption and reduced number of stages in the supply chain. The operational initiatives are attitudes towards agriculture and entrepreneurship, transportation infrastructure, supply chain coordination, information visibility, scientific design for packaging and handling and storage space availability for both long and short term at the village level.

This study was performed in India; thus, the research outcomes of this study are restricted to adaption into the developing sub-continents with sub-tropical climates.

The existing level of losses in the PYSC demands introspection and policy changes at the farm level. In the era of cold chains, the Internet of Things, and other advanced mechanisms, a few elementary parameters must be worked upon to reduce PYSC losses. These parameters were identified as impediments to PYSC, requiring public, government and stakeholders’ attention. There is an urgent need for guidelines to be issued to mitigate losses. SEM was performed to attract the public, government and stakeholders’ attention toward impediments to fresh produce spoilage, opportunity generation and business sustainability.

This study uses a novel SEM approach where the PYSCIs were identified and empirically validated in an Indian context. The SEM approach will help in effective decision-making. Similar studies to manage the PYSCIs to reduce fresh produce spoilage with standard measures have not been reported in the literature.

This study explores the enablers of students “entrepreneurial intentions by identifying the factors that raise students” interest in embracing an entrepreneurial career.

Entrepreneurship education is increasingly attracting attention as a means of fostering entrepreneurial activity and creating a culture of innovation. Developing students' entrepreneurial intentions is critical to promote entrepreneurship. This research is built on a mixed method approach of partial least squares structural equation modelling and fuzzy-set qualitative comparative analysis.

The factors that influence students ‘entrepreneurial intentions are identified: business incubation programmes, non-reimbursable grants for entrepreneurial students, networking events to promote entrepreneurship, mentoring services, innovation labs for business idea validation and entrepreneurship courses. This knowledge can help develop effective entrepreneurship education programmes. The study also provides actionable insights for educational institutions and policymakers. It underscores the need for innovative educational platforms such as entrepreneurial bootcamps. It also highlights the value of advanced learning environments such as decision theatres to foster a culture of entrepreneurship and innovation.

The study contributes to the body of knowledge on entrepreneurship education. It highlights the need for a multidisciplinary approach to understand the factors that shape students’ entrepreneurial intentions.

To support the advancement of an underrepresented category of research in the field of entrepreneurial teams, this study proposes and tests a novel empirical model that connects two team emergent states, namely team entrepreneurial passion (TEP) and transactive memory systems (TMSs), and their influence on team performance.

The data were gathered using an online questionnaire distributed to undergraduate students who had formed entrepreneurial teams as part of a course assignment. Two methods were executed on the obtained data, namely partial least-square structural equation modelling (PLS-SEM) and necessary condition analysis (NCA).

The results uphold the hypothesised mediation role of TMSs between TEP and team performance. Of the two direct relations in the model, only the necessary conditions were present for the effect of TEP on TMSs.

The issue of the small sample size, a common feature in entrepreneurial team research, as discussed in the methodical section of the paper, is sidestepped with the use of PLS-SEM tools. Nonetheless, a larger sample size could have increased confidence in the results' validity. In addition, a longitudinal approach to data collection and analysis could have been used to augment that confidence further.

Three practical implications stem from the empirical findings. First, it lends support for implementing teaching approaches and task designs that are envisaged to improve team functioning in university classrooms. Making a business plan boosts students' desire to exploit the received knowledge and find a venture, so the teaching effort in entrepreneurship courses can have real-world consequences.

By testing the mediation model, new insights are made into the associations between team emerging states and, subsequently, team performance. In addition, this study responds to recent calls in the literature to incorporate NCA in an entrepreneurial setting.

Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.

Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.

Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.

By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.

The study seeks to propose a linear model by applying complexity theory and resource-based theory to investigate how hotels achieve competitive advantage and organizational performance during the Covid-19 pandemic from the perspective of hotel leaders.

Using a standardized questionnaire and convenience sampling approach hotel managers and administrative employees were surveyed online. A total of 354 participants from five provinces in China were examined using Smart PLS and fsQCA 3.0 for analysis. The utilization of the asymmetric method facilitates the elucidation of relationships that may not be readily apparent when employing conventional symmetric approaches.

The results display a significant impact of transformational leadership (TL) on market orientation (MO), competitive advantage (CA) and organizational performance (OP). The results show numerous combinations using fsQCA that can be utilized to increase OP within the hotel industry.

At present, there is a lack of substantial empirical evidence to comprehensively investigate the impact of TL on MO, CA and OP in the field of hospitality research specifically in the context of the Covid-19. The study also contributes by providing an explanation of the factors that contribute to the development of a higher organizational performance base through TL, MO and CA during the Covid-19 pandemic.

This study aims to examine the determinants of retailer social responsibility (RSR) in Old Dhaka City and their impact on RSR practices.

A cross-sectional design was used to collect primary data from 180 retailers through a questionnaire survey. The study used partial least squares structural equation modeling to analyze the data and examine the relationships among the determinants of RSR.

The study found that economic and ethical factors positively and significantly affect RSR practices, while social and environmental factors negatively but not significantly affect RSR practices. Cultural factors were also found to positively and significantly affect RSR practices.

This study provides insights for retailers and policymakers to enhance their RSR practices by considering economic, ethical and cultural factors. The findings also contribute to the existing literature on stakeholder theory by highlighting the importance of considering multiple stakeholders in RSR practices.

This study provides insights into the determinants of RSR in a unique setting in associating stakeholder theory and in Bangladesh, which has received limited attention in the literature on RSR.

This study aims to develop an interrelation model between critical parameters for assessing the construction readiness (CR) of abandoned housing projects, using Malaysia as a case study. To achieve that aim, the study objectives are to (1) identify critical parameters for assessing the CR of abandoned housing projects; (2) develop underlying constructs to categorize interrelated critical parameters and (3) assess the influence of the underlying constructs on the CR of abandoned housing projects.

This study identifies potential parameters for assessing the CR of abandoned housing projects by reviewing existing literature and interviewing industry professionals. Then, the list was used to develop a questionnaire survey. The collected survey data were analyzed using normalized mean analysis to identify the critical parameters. Exploratory factor analysis (EFA) was used to develop underlying constructs to categorize interrelated critical parameters. Finally, the influence of the underlying constructs on the CR of abandoned housing projects was examined through partial least squares structural equation modeling (PLS-SEM).

The analyses suggest that 21 critical parameters are affecting the CR of abandoned housing projects. The critical parameters can be categorized into four underlying constructs: construction site evaluation, management verification, uncertainties mitigation and document approval. Finally, the analyses confirmed that all four constructs affect the CR of abandoned housing projects.

This study is a pioneering effort to quantitatively analyze the parameters for assessing the CR of abandoned housing projects. The findings significantly benefit researchers and industry professionals by providing a list of critical parameters associated with the CR of abandoned housing projects.