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Examining dominance in influencing leadership perceptions for men and women has received significant scholarly attention. The studies typically show that dominance is beneficial for men in attaining leadership positions but not for women. However, the studies were predominantly conducted more than two decades ago. Given the developments in gender research, this study extends the dominance line of inquiry by probing the impact of dominance need on leader emergence for men versus women in self-managed work teams. Furthermore, this study aims to examine if team dominance needs dispersion posits as a boundary condition for the combined impact of dominance needs and gender on leader emergence.

The authors conducted a longitudinal study that lasted one semester and involved 44 ad hoc self-managed work teams.

This study found that dominance needs facilitated leader emergence regardless of gender, and team dominance needs dispersion. Furthermore, men with high dominance needs were likelier to emerge as leaders than women with high dominance needs in high dominance needs dispersion teams. By contrast, women low in dominance needs received a harsher penalty in their leadership emergence than men low in dominance needs in low dominance needs dispersion teams

These results depart from the usual findings regarding the backlash effects that dominant women face and paint a rosy picture regarding the use of dominance in shaping leader emergence. However, the findings support the notion in gender stereotypes research that women are judged more critically than men in ascending to leadership positions.

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

This study aims to examine the effects of network externalities and diffusion of innovation on users’ perceived usefulness and perceived enjoyment, and in turn subjective well-being and intention to use in the smart living context.

To explore different types of smart living services, the data collected come from surveying 512 users of smart home services and 570 users of smart living apps. Structural equation modeling is used to analyze the data, and post hoc interviews are conducted to provide insights into our conceptual model of smart living services.

Compatibility and perceived service complementarity are the most influential determinants of users’ perceived usefulness and perceived enjoyment toward smart living services. Perceived usefulness has a greater impact on users’ intention to use and their subjective well-being than perceived enjoyment. Interestingly, perceived enjoyment exerts a stronger influence on subjective well-being than on intention to use.

This study is one of the first to provide empirical evidence in the context of smart living services, contributing to transformative service literature by extending the understanding of technology use and its influence on user well-being into a less explored service context. This study also advances users’ intention to use and subjective well-being of technology adoption in the service context by integrating perspectives from network externalities and diffusion of innovation.

This paper aims to examine the relationship between environmental, social and governance (ESG) performance and text-based corporate innovation based on a sample of India’s ESG-disclosed companies from financial year 2011–2012 to 2021–2022. Further, it endeavors to investigate the moderating role of heightened climate policy uncertainty (CPU) in this relationship.

To verify these hypotheses, the authors first construct a corporate innovation index for India using a sophisticated natural language processing model on each firm-year’s management discussion and analysis reports. Next, the authors use a panel fixed effects model to examine how ESG performance impacts corporate innovation and its moderating and mediating components.

Empirical evidence suggests higher ESG performance bolsters text-based corporate innovation. After addressing endogeneity issues with the system GMM estimator and two-stage least square IV, incorporating additional control variables and using alternative innovation measurement, the baseline results remain unchanged. Next, the authors find this link is mediated by reducing information asymmetry, financial constraints and managerial myopia. The authors also observe that increased CPU favorably moderates the ESG-innovation nexus. Additionally, the heterogeneity research shows that ESG only positively impacts innovation in specific industries and firms in their growth and mature life cycle phases.

The results demonstrate that sustainable and ethical business practices can foster corporate innovation. Thus, this study may provide valuable insight for investors, managers and policymakers.

To the best of the authors’ knowledge, this is the first study to examine the relationship between ESG performance and text-based corporate innovation using a machine learning model.

For nearly 2 decades, the push-pull-mooring (PPM) model has been used frequently by scholars to explain consumers’ service switching intention and behavior. However, heterogeneity and incomparability between PPM model studies are prevalent issues: The chosen predictor variables, their categorization, their measurement, reported effect sizes, and effect directions vary considerably. By addressing these issues, the present meta-analytical review enables future researchers applying the PPM model to identify relevant variables and use valid measurements.

Based on 148 empirical studies employing the PPM model, the variables used to predict consumers’ service switching intention and behavior, their frequency of use, their categorization into push, pull, and mooring factors, and their measurement are assessed. The effect sizes and directions of the relationships between these variables and consumers’ service switching intention and behavior are analyzed using meta-analytic structural equation modeling. Additionally, the predictive capacity of this model and the influence of moderators are assessed.

Among the 148 empirical studies, 382 different independent variables were used. The three most frequently used and distinctly categorized independent variables are dissatisfaction (push), alternative attractiveness (pull), and switching costs (mooring). Overall, 152 unique sources were cited to measure these variables and the dependent variables. Dissatisfaction and alternative attractiveness increase switching intention, which positively affects switching behavior, while switching costs decrease switching intention. The model explains 30% of the variance in switching intention and 31% of the variance in switching behavior.

This study provides the first meta-analytical review of the PPM model to guide future research systematically.

The paper aims to examine whether CSR communication about a company’s support for climate change created using different content framing categories (positive vs negative) can lead climate change-sceptical audiences to positively influence their evaluations of the credibility of CSR communication, of a company and its actions, and lead to higher purchase intentions.

The paper used an experimental design. About 266 respondents recruited via the Prolific platform were invited to participate in an online study. A between-subject design was used, and data was analysed using the bootstrapping technique, allowing to identify moderators of the relationship between CSR communication framing and different evaluations of a company.

The paper provides empirical support for the role of political preferences and climate change beliefs in predicting the preference for positive attribute framing among climate change sceptical audiences. It is argued that climate change sceptics are still in the process of deliberation about whether climate change is occurring.

The research findings may not be generalizable to countries where support for climate change is low, and a technique like attribute framing may not lead to noticeable differences in message reception.

The paper underscores the impact of the type of attribute framing in CSR communication on different aspects of company evaluations depending on beliefs in climate change. Commercial communicators should additionally invest in climate change education to address the climate change challenge.

Addressing climate change effectively requires support from companies to communicate their CSR efforts purposefully and to address climate change sceptical audiences.

The paper identifies beliefs in climate change as an important moderator of CSR communication attribute framing effectiveness.

The heat transport phenomenon in which energy transfers due to temperature differences is an important topic of interest for scientists in recent times. It is because of its wide range of applications in numerous domains such as electronics, heat dispersion, thermoregulation, cooling mechanism, the managing temperature in automotive mobile engines, climate engineering, magnetoresistance devices, etc. On account of such considerations, the magnetohydrodynamic (MHD) entropy rate for nanomaterial (CoFe₂O₄/C₂H₆O₂) and hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) is analyzed. The Darcy–Forchheimer relation is utilized to describe the impact of a porous medium on a stretched sheet. Two nanoparticles molybdenum (MoS₄) and cobalt ferrite (CoFe₂O₄) are combined to make hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂). Heat flux corresponds to the Cattaneo–Christov model executed through heat transfer analysis. The influence of dissipation and heat absorption/generation on energy expression for nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) and hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) is described.

Nonlinear partial differential expressions have been exchanged into dimensionless ordinary differential expressions using relevant transformations. Newton’s built-in shooting method is employed to achieve the required results.

Concepts of fluid flow, energy transport and entropy optimization are discussed. Computational analysis of local skin friction and Nusselt number against sundry parameters for nanomaterial (CoFe₂O₄/C₂H₆O₂) and hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) is engrossed. Larger magnetic field parameters decay fluid flow and entropy generation, while an opposite behavior is observed for temperature. Variation in magnetic field variables and volume fractions causes the resistive force to boost up. Intensification in entropy generation can be seen for higher porosity parameters, whereas a reverse trend follows for fluid flow. Heat and local Nusselt numbers rise with an increase in thermal relaxation time parameters.

No such work is yet published in the literature.

This study aims to investigate the relationship between extrinsic rewards and employee creativity through the intervening mechanism of perceived organisational support (POS) and work engagement. The moderating role of intrinsic motivation on the relationship between work engagement and employee creativity is also examined.

The authors report the results of a survey completed by 372 respondents employed in the United Arab Emirates. Structural equation modelling was applied to test the hypothesised relationships.

The main findings are that extrinsic rewards influence employee creativity through POS and work engagement. Moreover, the effect of work engagement on employee creativity is moderated by intrinsic motivation. This model effect is stronger for employees with high intrinsic motivation.

Convenience sampling was used, which limits its generalisability. Also, the data were collected through a cross-sectional survey at one point in time.

Managers should consider provision of extrinsic rewards and support to increase employee motivation and engagement in creative work.

This study contributes to the limited amount of available literature on creativity and rewards adding to our knowledge about the influence of extrinsic rewards on creativity considered in the presence of intrinsic motivation. Theoretical and practical recommendations are discussed.

Building on memory-dominant logic, this study proposes a theoretical model explaining the antecedents and consequences of memorable activation experience.

Through a qualitative research methodology – a narrative review, an analysis of current activation trends, eight interviews and content validity evaluation by five experts – this study hypothesized that six antecedents (positive emotions, novelty, meaningfulness, involvement, experience intensification and serendipity) positively influence memorable activation experience, which in turn significantly affects two managerial outcomes: positive word-of-mouth and sponsor recall. To evaluate the proposed hypotheses, this study analyzed data collected from consumers who participated in a sponsorship activation by Lafleur (n = 215) and Salon de jeux de Québec (n = 306) using partial least squares structural equation modeling (PLS-SEM).

The results indicate that all antecedents, except for novelty, have a significant impact on memorable activation experience, which positively impacts positive word-of-mouth and sponsor recall.

By extending the scope of memorable experience to the sponsorship field, this study enhances its conceptualization and application. It also contributes to a better understanding of designing activations to increase the likelihood of memorability, thus improving their effectiveness.

The study examines the effects of corporate governance and countrywide institutions and risk factors on corporate liquidity.

Using firm-level data, the authors analyze the effect of corporate governance and various economic, regulatory and social institutions on the liquidity of firms operating in the Middle East and North Africa (MENA) region. The authors use fixed-effects, firm-specific and country-level controls, disaggregated analysis, sensitivity and endogeneity analysis to test the robustness of the estimates.

The corporate governance characteristics of firms influence in diverse ways their liquidity decisions. The independence and diversity of the board and institutional ownership are especially strong predictors. The effect also depends on the size of the firm and the degree of economic development and exhibits time sensitivity and nonlinearity. Enforcement institutions and risk factors play a strong role.

The analysis contributes to the literature by using a large sample of countries and firms over a larger period, distinguishing between poorer and richer countries and using sensitivity and endogeneity analysis. The analysis considers explicitly the role of regulatory and enforcement conditions, social structures and religious beliefs.