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The purpose of this study is to explore and model the strategies to overcome the barriers of Lean Six Sigma (LSS) implementation in Indian small manufacturing enterprises (SMEs).

In this research, 31 strategies of LSS implementation in SMEs have been identified through detailed literature review and out of them, 13 are finalized using statistical tools like CIMTC and Importance-Index analysis. Moreover, the consistency of finalized strategies was examined through reliability test using SPSS software version 22. The finalized strategies are modelled through interpretive structural modelling (ISM) and classified them using MICMAC based on their driving and dependency power.

The key findings of this techno-managerial study are identification and modelling of 13 strategies to overcome adoption challenges of LSS in context of Indian SMEs. The usage of ISM-MICMAC approach provides the guidance to industrialist consider the mutual interaction of strategies during planning and scheduling for LSS projects.

Due to human involvement and judgements, there may be chance of biasness and subjectivity during construction of self-interaction matrix. Also, the number of identified strategies to overcomes barriers of LSS adoption may vary by altering nature, scope and region of research.

Literature is full of studies regarding LSS barriers and its rankings. Also, few studies explored the solutions of LSS barriers and prioritized them. To the best of the authors’ knowledge, our study is very rare to witness which expose the strategies to overcome the barriers and frame the mutual interaction are per the driving and dependence power of strategies. The application of ISM-MICMAC approach suggests a roadmap for implementing LSS approach efficiently through considering developed ISM model of strategies in context of SMEs.

This paper aims to determine whether there is a relationship between intellectual capital and social capital and internal control weaknesses and assess the relationship between the variables of intellectual capital and social capital and internal control weaknesses.

The statistical population consists of 1,309 firm-year observations from 2014 to 2020. The research hypothesis is tested using statistical methods, including multivariate, least-squares and fixed-effects regression.

The results demonstrate a negative and significant relationship between intellectual capital, social capital and internal control weaknesses. The study also finds that increased intellectual and social capital quality improves human resource utilization, control mechanism, creativity and firm performance. The results also show that intellectual capital and social capital enhancement will reduce internal control weaknesses in the upcoming years.

This paper is the pioneer study on the relationship between intellectual capital and social capital and internal control weaknesses in Iran, carried out separately and in exploratory factor analysis. This paper considers intellectual capital components for theoretical factor analysis, including human capital, structural capital and customer capital. Internal control weakness is assessed based on financial, non-financial and information technology (IT) weaknesses.

The purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.

Using four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.

The authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.

The authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.

This paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).

This study aims to investigate the association between corporate governance (CG) and the corporate social responsibility (CSR) information disclosure as well as the moderating role of state-ownership between CG and CSR disclosure.

To examine the relationship between CG and CSR disclosure, this study used the feasible general least squares and generalized method of moments method on a sample of 165 non-financial quoted companies over the 2015–2018 period, which account for about three-fourths of the Vietnamese stock exchange.

The findings suggest that enterprises with smaller board size consisting mainly of independent directors have a higher CSR disclosure level. Moreover, when the chief executive officer is concurrently the chairman of the board, the level of CSR disclosure falls. Additionally, the moderating role of state ownership enhances CSR disclosure.

The empirical results of this study form a solid foundation for policymakers and other stakeholders’ decisions in investing or establishing policies.

This study provides empirical evidence on the relationship between CG and CSR disclosure in Vietnam – a developing country with no legal requirement on CSR disclosure. Moreover, this study emphasizes the moderating role of state ownership between CG and CSR disclosure, which clarifies the role of state ownership in establishing CG mechanisms.

This study examines the effect of board characteristics on the tax aggressiveness of listed companies on the Colombo Stock Exchange in Sri Lanka.

The sample consists of 264 firm-year observations of non-financial listed companies in Sri Lanka from 2014 to 2019. The dynamic panel system GMM technique was used to test the hypotheses, and further analyses were performed using the propensity score matching technique.

All four effective tax rate measures' mean values were lower than the statutory tax rate, indicating the likelihood of tax planning. Whether board attributes are likely to mitigate tax aggressiveness is uncertain because the results are inconsistent and depend on the ETR measure. Similarly, the logistic regression results derived using the PSM approach are inconsistent, suggesting that board characteristics may have a limited effect on tax aggressiveness. Hence, the corporate governance-tax aggressiveness nexus is limited in the case of Sri Lanka.

This investigation is limited to non-financial listed companies in Sri Lanka and incorporates only four tax aggressiveness measures. Findings are imperative for policymakers, regulators, and professional bodies to improve corporate governance codes and rules to enhance organisational transparency toward corporate tax payments.

Aggressive tax planning by companies will reduce government tax revenue, hinder social progress, and cause public mistrust of large corporations and institutions.

This study provides insight into the nexus between corporate governance and tax aggressiveness in a middle-income economy in South Asia hit by an economic crisis where tax revenue has fallen and tax enforcement is weak.