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The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners.

Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses.

The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners’ intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners’ intentions to use IoT.

These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners’ intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field.

This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector.

This paper aims to examine whether reconciling profit maximization and social welfare as two possible aspirations of company is feasible.

The possible corporate goals are presented by drawing an arc from purely profit-maximizing organizations via a combination of profit and social objectives to organizations clearly serving social utility. In addition to this sorting principle, the order of the different positions presented also takes into account the number of goals and goal-setters.

The primary finding of the study is that none of the business concepts discussed here met the initial expectations as for economic and social objectives. The study points to the need to redefine the purpose of business within a broader social science framework.

For a critical perspective, this paper considers only those standpoints that emphasize a certain form of social utility beyond profitability resulting from business activity directly or indirectly.

In addition to revealing the relationship between the two aspirations, the novelty of the paper lies in the attempt to explore through normative critique and empirical evidence the validity of the expectations regarding the goals.

With the rapid rise in the number of start-ups, corporate social responsibility (CSR) can principally contribute to the nation’s socioeconomic development, making it more critical. This study aims to explore the effect of sustainability practices on a firm’s performance with competitive advantage (CA) and innovation (INN) as the mediating variable.

An exhaustive literature review was done to identify the constructs relationship for this study, and a questionnaire was used to gather the data from the start-up owners. In total, 400 samples were received, and partial least squares structural equation modeling was used for testing and validating the proposed hypotheses.

CSR and financial performance (FP) have a significant relationship. According to this study’s findings, innovation and CA substantially mediate the relationship between a firm’s FP and CSR. This study will highlight how CSR practices stimulate organizational creativity, problem-solving and strategic thinking. It will also demonstrate how CSR can foster a culture of innovation that generates long-term value and positively impacts FP.

It will aid in improving the knowledge of start-up owners that CSR is more than just pure altruism or philanthropy; instead, it must be promoted strategically as an investment that boosts productivity and creativity while also bringing overall financial benefits to the company. It will ultimately enhance the start-ups’ ability to improve the economy and society. Furthermore, this study holds the potential to inform policy discussions and recommendations for fostering responsible business practices in the Indian start-up ecosystem. Policymakers can benefit from insights into how regulations and incentives can be designed to encourage start-ups to adopt CSR practices that not only fulfill legal obligations but also contribute to their CA and FP.

This study provides empirical validity to establish linkages between sustainability measures on the FP concerning start-ups that were not considered in the prior studies. Identifying the current conceptual framework and CA and Innovation as the two major factors influencing CSR in Indian enterprises is a novel contribution. This study aims to fill the research gap. By unravelling the intricate dynamics between CSR, FP and CA, the research contributes to the understanding of how start-ups can navigate the complex interplay of social responsibility and business success in the Indian context.

With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.

The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.

The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.

The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.

This paper aims to examine a new approach to understanding the interrelationships between destination brand gender, stereotypes, destination brand identification and brand advocacy, as well as the mediating role of destination warmth (vs. competence) in the connections between destination brand femininity (vs. masculinity) and destination brand identification.

A qualitative study and literature review were conducted to revisit and refine the items on the scale. Preliminary item reduction was qualitatively grounded in focus groups, a panel of experts, and a pilot study. A follow-up quantitative evaluation of two studies (N1 = 705 and N2 = 472) was conducted to test seven hypotheses using exploratory factor analysis and confirmatory factor analysis with structural equation modeling.

The findings provide robust evidence for the interrelationships among destination brand gender, stereotypes, destination identification and destination advocacy. The outcomes also reveal that warmth is more important than competence for destination identification. Finally, the results indicated that only destination warmth serves as a partial mediator in the association between destination brand masculinity and femininity, on the one hand, and destination identification, on the other hand.

This article adds to the destination branding literature by using social role theory and the stereotype content model to explore novel connections among destination brand gender, stereotypes, destination brand identification and brand advocacy.

This study applies the target similarity model to examine the effects of servant leadership on supervisor commitment and supervisor citizenship behavior. The mediating role of supervisory commitment is explored to determine the relationship between servant leadership and supervisor citizenship behavior. The difference in supervisor gender is examined in the linkage between servant leadership and supervisory commitment.

The data were collected through a survey of 478 salespeople in the retail industry. Structural equation modeling (SEM) techniques were used to verify the hypotheses of this study.

The findings showed significant support for the direct and indirect effects of servant leadership on supervisor commitment and supervisor citizenship behavior. Furthermore, the positive relationship between servant leadership and supervisory commitment was stronger among female supervisors than male supervisors.

Due to the scarcity of studies conducted on the linkages of servant leadership, supervisory commitment and supervisory citizenship behavior, this study theoretically and empirically contributes to the leadership literature as it is the first study to investigate these direct and indirect relationships. Similarly, this study examined gender differences in servant leadership to fill the gap in the research field.

Workflow optimisation is crucial for establishing a viable acute stroke (AS) intervention programme in a large tertiary care centre. This study aims to utilise Lean Six Sigma (LSS) principles to enhance the hospital's workflow.

The Action Research methodology was used to implement the project and develop the case study. The study took place in a large tertiary care academic hospital in India. The Define-Measure-Analyse-Improve-Control approach optimised the workflow within 6 months. Lean tools such as value stream mapping (VSM), waste audits and Gemba were utilised to identify issues involving various stakeholders in the workflow. Sigma-level calculations were used to compare baseline, improvement and sustainment status. Additionally, statistical techniques were effectively employed to draw meaningful inferences.

LSS tools and techniques can be effectively utilised in large tertiary care hospitals to optimise workflow through a structured approach. Sigma ratings of the processes showed substantial improvement, resulting in a five-fold increase in clinical outcomes. Specifically, there was a 43% improvement in outcome for patients who underwent acute stroke revascularisation. However, certain sigma ratings deteriorated during the control and extended control (sustainment) phases. This indicates that ensuring the sustainability of quality control interventions in healthcare is challenging and requires continuous auditing.

The article presents a single case study deployed in a hospital in India. Thus, the generalisation of outcomes has a significant limitation. Also, the study encounters the challenge of not having a parallel control group, which is a common limitation in quality improvement studies in healthcare. Many studies in healthcare quality improvement, including this one, are limited by minimal data on long-term follow-up and the sustainability of achieved results.

This study pioneers the integration of LSS methodologies in a large Indian tertiary care hospital, specifically targeting AS intervention. It represents the first LSS case study applied in the stroke department of any hospital in India. Whilst most case studies discuss only the positive aspects, this article fills a critical gap by unearthing the challenges of applying LSS in a complex healthcare setting, offering insights into sustainable quality improvement and operational efficiency. This case study contributes to the theoretical understanding of LSS in healthcare. It showcases its real-world impact on patient outcomes and process optimisation.

Although virtual worlds, such as the Metaverse, can disrupt the hospitality sector, few empirical investigations have critically evaluated the scope and scale of this disruption from an industry perspective. This study aims to rectify this knowledge gap by exploring the opportunities and challenges of the Metaverse as seen by hospitality professionals.

This is a Delphi study conducted with UK-based senior hospitality industry practitioners experienced in designing and implementing digital innovations within their organisations.

The Metaverse is most likely to be adopted by hospitality organisations willing and able to take risks, such as large and/or chain-affiliated enterprises. The Metaverse will not replace traditional hospitality services but supplement and enhance them with new layers of service. The main applications are in the context of events and experiences. The Metaverse will also provide the “try before you buy” option, revealing the opportunities to design digital twins of physical businesses. Young and technology-savvy individuals are most likely to first adopt the Metaverse. The key challenges of the adoption are attributed to the technological unpreparedness of hospitality organisations; market immaturity; inflated customer expectations; a skills gap among hospitality employees; and regulatory issues. These challenges require the engagement of various stakeholders to create an operational and monitoring framework for hospitality organisations to embrace the Metaverse.

This study highlights how the Metaverse can disrupt the hospitality industry at the level of strategic planning and business operations.

To the best of the authors’ knowledge, this is one of the first empirical investigations of the potential of the Metaverse from the viewpoint of hospitality industry practitioners.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.

In social marketplaces, follower ego networks are integral social capital assets for online sellers. While previous research has underscored the positive impact of the follower number on seller performance, little attention has been given to the structure of follower networks and their value implications. This research investigates two structural properties of follower networks—network centralization and density—and examines their main and contingent effects on sellers’ sales performance.

A 13-month panel dataset of 1,150 sellers in Etsy, a social marketplace for handmade and vintage products, was collected and analyzed. A fixed effects model was adopted to validate the hypotheses on the main effect of centralization and density, as well as the moderating effects of two store attributes: store age and product diversification.

We find that both network centralization and density negatively impact sellers’ sales performance, and these effects vary across store age and product diversification levels. Specifically, the negative effect of network centralization is less pronounced for older stores than young ones, whereas the negative effect of density is more severe for stores with high product diversification.

This research contributes to social commerce research by highlighting the significance of network structure, alongside network size, in assessing the value of followers and offers practical guidance for sellers in social marketplaces seeking to optimize their follower networks.