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This paper systematically reviewed research work on drivers of teamwork, which will reinforce construction work teams to enhance workers’ safety performance. This study adds to the existing but limited understanding of teamwork drivers on construction workers’ safety performance. This paper presents scholars and industry-based professionals with critical initiatives that have to be implemented in organisations to get positive results in safety while working in teams with an emphasis on systems drivers of teamwork on safety performance at the organisational level, which will help in providing information on the functioning of the teams and contribute towards improved safety performance of team workers.

This study aims to systematically examine the existing body of knowledge on drivers of teamwork by analysing 53 publications from the years 1997–2021. The Scopus search engine was used to conduct a systematic review and germane publications were collated.

According to the findings of the review, since 1997, there has been a burgeoning concern in the research of drivers of teamwork and its impact on workers’ safety performance. After performing a systematic review, 37 drivers of teamwork were identified. The top five drivers are effective communications, team workers’ relations, leadership, shared knowledge and information, and team training. Moreover, it was noted that the United States and Australia have been the international regions of focus for most of the research in the area of drivers of teamwork from the years 1997–2021. The 37 drivers of teamwork are distributed into six major socio-technical components: people drivers; culture drivers; metrics drivers; organisational and management practices and procedures drivers; infrastructure drivers and technology drivers.

The results reported present research scholars and professional practitioners with an overview of the drivers of teamwork that could be implemented in the construction industry to streamline potential implementations and improve safety performance of construction workers.

A list of teamwork drivers has been developed to ratify potential empirical research in the area of construction safety. The results would contribute to the existing but restricted understanding of drivers of teamwork in the construction industry.

Firms in emerging economies are generally at a disadvantage in terms of resources, which may limit their digital transformation. The Chinese government has designed and promulgated a series of wind power policies from the perspectives of support and regulation. The former provides scarce resources for enterprises and thus alleviating financial constraints. While the latter increases the demands for advanced technologies, thereby triggering resource bricolages. This study aims to clarify the impact of industrial policy on the digital transformation of the Chinese wind power industry, and the role of financing constraint and resource bricolage in the above relationship.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study clarifies the impact and mechanism of industrial policy on firm digital transformation with fixed effect regression models.

Empirical results indicate that both supportive and regulatory policies are the cornerstone of the digital transformation of the Chinese wind power industry. Financial constraint and resource bricolage, respectively, mediate the impact of supportive and regulatory policies. However, the mix of supportive and regulatory policies inhibits digital transformation. Moreover, industrial policies are more effective for the digital transformation of state-owned enterprises, as well as enterprises in economically underdeveloped regions.

This study investigates the path of government intervention driving firm digital transformation from the resource-related perspective (i.e. financial constraint and resource bricolage), and its analytical framework can be extended based on other theories. The combined effects of cross-sectoral policies (e.g. wind power policy and digital infrastructure policy) can be further assessed. The marginal net benefit of government intervention can be calculated to determine whether it is worthwhile.

This study emphasizes the necessity of government intervention in the digital transformation of enterprises in emerging economies. The governments should align the policy targets, clarify policy recipients and modify policy process of different categories of industrial policies to optimize the effectiveness of policy mix. Given that the effectiveness of government intervention varies among different categories of enterprises, the competent agencies should design and promulgate differentiated industrial policies based on the heterogeneity of firms to improve the effectiveness and efficiency of industrial policies.

This is one of the earliest explorations of industrial policies’ effect on the digital transformation of the renewable energy sector in emerging economies, providing new evidence for institutional theory. Meanwhile, this study introduces financial constraint and resource bricolage into the research framework and attempts to uncover the mechanism of industrial policy driving the digital transformation of enterprises in emerging economies. Besides, to expand the understanding of the complex industrial policy system, this study assesses the effectiveness of the industrial policy mix.

Enterprise Risk Management (ERM) is a strategy and approach that enables organizations to manage risk strategically from a systems standpoint. The ERM assists businesses in structuring their systems to generate strategic flexibility (SF), which leads to increased firm performance (FP) through strategic enterprise management (IS-SEM) and strategic momentum (SM).

The study is based on data gathered in Brazil and India. The complex link was discovered using partial least square structural equation modeling (PLS-SEM) using 330 Brazilian and Indian sample sizes.

The findings show that ERM influences IS-SEM and SM, which improves SF and FP. Furthermore, the study claims that IS-SEM can help improve strategic momentum and flexibility in the face of environmental uncertainty (ENU). Thus, it indicated that specific combinations of ENU connected with ERM and IS-SEM lead to obtaining high and extremely high levels fuzzy set qualitative comparative analysis (fsQCA) post hoc analysis of strategic momentum and flexibility.

The findings help executives understand how ERM and accounting information systems (AIS) can help achieve SM and SF, hence promoting FP in situation specific ENU setups in developing economies. The findings enhance executives' comprehension of how ERM and IS-SEM can significantly contribute to achieving SM and SF, thereby driving FP in the situation-specific ENU configurations in developing economies.

Research indicated that specific combinations of (ENU) connected with ERM and IS-SEM lead to obtaining high and extremely high levels fuzzy set qualitative comparative analysis (fsQCA) post hoc analysis of strategic momentum and flexibility.

Globalisation has benefitted both developed and emerging markets. However, few recent studies have pointed out that globalisation has failed to deliver promising results. This research aims to examine the impact of globalisation on different performance aspects of an emerging market like India.

We examined the impact of globalisation on different performance aspects of a country at the national, industry and firm levels. We have defined the performance dimensions for country-level analysis as GDP and unemployment. We have defined the performance dimensions as profitability for industry and firm-level analysis. The effects of globalisation on the critical economic performance aspects in the Indian setting are covered in the first part. In the second part, we used the panel regression approach to evaluate the impact of overseas revenue on the employability and profitability of select Indian auto firms. We have chosen the auto industry for industry analysis because of its extensive integration with other production fields. In the third section, we discussed how globalisation has improved the profitability of two Indian car companies.

This study finds that globalisation has benefitted nearly every aspect of the Indian economy's performance. India has gained from national, industry and firm globalisation.

This study is the first of its kind to examine the impact of globalisation on a country's performance across different levels, including national, industry and firm levels. We have studied the Indian context to develop a theory that globalisation still benefits emerging markets.

This study aims to investigate the impact of ChatGPT on users’ continuous knowledge contributions in online question-and-answer (Q&A) communities based on social exchange theory and stimulus-organism-response (SOR) theory.

Data were collected from a Chinese online Q&A community, and the difference-in-differences (DID) model was employed to verify the proposed hypotheses.

The results show that ChatGPT negatively impacts users’ continuous knowledge contributions in online Q&A communities, with variations observed across different knowledge domains.

This study is the first attempt to examine the impact of ChatGPT on users’ continuous knowledge contributions in online Q&A communities. The findings provide valuable insights for community managers to develop strategies for mitigating the effects of ChatGPT on online Q&A communities.

The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and implementation.

The research employed two experimental designs and one pilot study to investigate the ethical and moral implications of different levels of AI implementation in the hospitality industry, the intersection of self-congruency and ethical considerations when AI replaces human service providers and the impact of psychological distance associated with AI on individuals' ethical and moral considerations. These research methods included surveys and experimental manipulations to gather and analyze relevant data.

Findings provide valuable insights into the ethical and moral dimensions of AI implementation, the influence of self-congruency on ethical considerations and the role of psychological distance in individuals’ ethical evaluations. They contribute to the development of guidelines and practices for the responsible and ethical implementation of AI in various industries, including the hospitality sector.

The study highlights the importance of exercising rigorous ethical-moral AI hiring and implementation practices to ensure AI principles and enforcement operations in the restaurant industry. It provides practitioners with useful insights into how AI-robotization can improve ethical and moral standards.

The study contributes to the literature by providing insights into the ethical and moral implications of AI service robots in the hospitality industry. Additionally, the study explores the relationship between psychological distance and acceptance of AI-intervened service, which has not been extensively studied in the literature.

This study aims to explore the holistic context of organisational staff retention in small, medium and large organisations. It also aims to identify the factors affecting the retention of organisations of different sizes.

The study implements an empirical test of a model created during previous research with the participation of 511 employees. The responses to the online questionnaire and the modelling were analysed using the partial least squares structural equation modelling method. The models were tested for internal consistency reliability, convergent and discriminant validity, multicollinearity and model fit.

Two models were tested by organisation size, which revealed a total of 62 significant correlations between the latent variables tested. Identical correlations were present in both models in 22 cases. After testing the hypotheses, critical variables (nature of work, normative commitment, benefits, co-workers and organisational commitment) were identified that determine employees’ organisational commitment and intention to leave, regardless of the size of the organisation.

As a result of this research, the models developed are suitable for identifying differences in organisational staffing levels, but there is as yet no empirical evidence on the use of the scales for homogeneous groups of employees.

The results show that employees’ normative commitment and organisational commitment are critical factors for retention. Of the satisfaction factors examined, the nature of work, benefits and co-workers have a significant impact on retention in organisations, so organisational retention measures should focus on improving satisfaction regarding these factors.

The readers of the journal would appreciate the work, which highlights the significance of employee psychology and retention for organisational success.

The study is based on primary data and, to the best of the authors’ knowledge, is one of the few studies that take a holistic approach to organisational staff retention in the context of the moderating effect of organisational size. This study contributes to a comprehensive understanding of the phenomenon of employee retention and in contrast to previous research, examines the combined effect of several factors.

This study aims to investigate the variation in overvaluation proxies and volatility across industry sectors and time.

Using industry sector data from the S&P Capital IQ database, this study applies traditional cross-sectional regressions to investigate the relationship between overvaluation and volatility over the 2001–2020 time period.

This study finds that the most volatile industry sectors generally do not coincide with overvalued industry sectors in the cross-section, implying that there are limitations to price-multiple methods for forecasting future volatility. Rather, this study finds that historical volatility significantly increases the goodness-of-fit when modeling volatility in the cross section of industry sectors. The findings of this study imply that firms should increase disclosures and transparency about corporate practices to decrease downside risk that stems from bad news. In addition, the findings underline the consistency between market efficiency and high levels of volatility in periods of significant uncertainty.

This study proposes a novel approach to examining the cross section of volatility across time for industry sectors.

The study intends to evaluate first the performance of Indian institutions ranked in the National Institutional Ranking Framework 2019. Second, it compares the performance of Indian institutions with international rankings. Third, it spotlights a model for predicting the criteria that will improve these institutions' national and international rankings.

The cluster analysis has been undertaken to group the sample of 100 institutions into three groups. Further, discriminant analysis has been performed to uncover the criteria that cause significant variations in the ranking. Third, a comparative study is conducted on the international ranking parameters to explore the factors responsible for their lower rank in the global ranking.

The results reveal that most institutions are low-performing for “research and professional practice” and “peer perception” criteria. Meanwhile, the performance of top-ranked institutions is unsatisfactory on the “outreach and inclusivity” criterion. The study also finds that the national ranking of Indian institutions is significantly affected by the “research and professional practice” and “peer perception” scores, which also results in their low rank in the Times Higher Education (THE) ranking.

This study can be an exemplary model for any developing nation to upgrade its higher education institutions' (HEIs’) performance in international tables

The government can develop policies to better low-performing universities and initiate policy changes in the incapacitated spheres for building a globally distinctive image for the Indian universities. The policymakers can recognise the institutions showcasing excellent research and teaching performance and encourage them accordingly to be the best research or teaching universities as it is not possible for every university to be the best in teaching and research aspect both.

The policymakers can also focus more on developing research collaboration form other countries and industry for research universities and professional staff from leading industries for teaching collaborations for the rest. The HPIs should focus on creating a global image for themselves and MPIs and LPIs should be encouraged to raise their national ranking.

The study is a novel attempt to present the present state of Indian institutions grounded on all the national ranking criteria. It further compares the performance of sample NIRF institutions with international rankings criterion to suggest policy changes for improving their performance at the global level.

This study investigates the service quality dimensions of hotel resorts in renowned beach destinations of Thailand. It also explores the relationship between review text sentiment expressed in online platforms and the satisfaction ratings provided for those reviews.

The study employs a two-step analysis approach: first, supervised and unsupervised machine learning via support vector machine (SVM) and latent Dirichlet allocation (LDA) are used to identify service quality dimensions, and second, SmartPLS with PROCESS macro is applied to analyze the moderating roles of quality signals and reviewer’s experience on the relationship between sentiment and satisfaction rating. The dataset comprises 102,179 online reviews from TripAdvisor, focusing on 187 selected hotels rated from 3 to 5 stars.

Eight service quality dimensions were identified, including leisure activities, tangibles and surroundings, reliability, responsiveness, service process, food, empathy and ambience. The study underscores that the service process stands as the sole dimension exhibiting negative sentiment. Furthermore, the analysis revealed a robust positive association between sentiment of review texts and satisfaction, and reviewers’ experience and brand affiliation influenced the relationship between customer sentiment and satisfaction.

Hotel managers should focus efforts on maintaining tangible aspects while enhancing existing service quality level of other dimensions, particularly those related to intangible elements. Independent hotels might implement quality audit to ensure that service quality gaps are monitored.

This study contributes an examination of the moderating roles of quality signals and reviewer’s experience on the relationship between review sentiment and satisfaction rating in online reviews.