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This study aims to empirically assess the influence of supply chain capabilities and total quality management on sustainable supply chain performance, factoring in the role of leadership and the moderating impact of institutional pressures.

The researchers designed a self-administered survey, garnering responses from 278 participants. Preliminary analyses addressed nonresponse bias, examining assumptions like homoscedasticity and data normality. Confirmatory factor analysis was employed to ensure reliability and construct validity before hypothesis testing. Regression outcomes corroborate all posited assumptions, further strengthening the extant literature.

The research outcomes demonstrate the positive association between supply chain capabilities and TQM and sustainable supply chain performance, particularly under institutional pressure. Data from the cement manufacturing sector further corroborated these findings. This study lends empirical support to the tenets of institutional theory.

The presented model delineates how leadership impacts TQM and supply chain capabilities to amplify sustainable supply chain outcomes. Incorporating institutional pressure as a moderating variable introduces a fresh and enlightening dimension to the discussion.

This study aims to explore the spillover effects of data breaches from a consumer perspective in the e-commerce context. Specifically, we investigate how an online retailer’s data breach affects consumers’ privacy risk perceptions of competing firms, and further how it affects shopping intention for the competitors. We also examine how the privacy risk contagion effect varies depending on the characteristics of competitors and their competitive responses.

We conducted two scenario-based experiments with surveys. To assess the spillover effects and the moderating effects, we employed an analysis of covariance. We also performed bootstrapping-based mediation analyses using the PROCESS macro.

We find evidence for the privacy risk contagion effect and demonstrate that it negatively influences consumers’ shopping intention for a competing firm. We also find that a competitor’s cybersecurity message is effective in avoiding the privacy risk contagion effect and the competitor even benefits from it.

While previous studies have examined the impacts of data breaches on customer perceptions of the breached firm, our study focuses on customer perceptions of the non-breached firms. To the best of the authors’ knowledge, this study is one of the first to provide empirical evidence for the negative spillover effects of a data breach from a consumer perspective. More importantly, this study empirically demonstrates that the non-breached competitor’s competitive response is effective in preventing unintended negative spillover in the context of the data breach.

This research aims to update the literature about the importance of reliability in supply chain (SC) and to find out the SC determinants.

This research surveys while contributing to the academic grasp of supply chain reliability (SCR) concepts. The study found 45 peer-reviewed publications using a structured survey technique with a four-step filtering process. The filtering process includes data reduction processes such as an evaluation of abstract and conclusion. The filtered study focuses on SCR and its determinants.

One of the major findings is that most of the study has focused on mathematical and conceptual studies. Also, this study provides the answer to a question like how can reliability be better accepted and evolved within the SC after finding the determinants of SCR.

The observed methodological gap in understanding and development of SCR was identified and classified into three categories: mathematical, conceptual and empirical studies (case studies and survey’s mainly). This research will aid academics in developing and understanding the determinants of SCR.

Political risk has been identified as a major impediment to the success of foreign invested projects, in developing countries. Infrastructure projects are especially sensitive to host-country political climates. Governance in emerging economies can be unstable, which adversely impacts infrastructure projects, given their high capital-intensity, long operational periods and high asset specificity. While the detrimental impact of political risk is well documented, the mitigation of such impacts on infrastructure projects remains largely unexamined. This study, therefore, addresses this by exploring the available identified political risk management (PRM) strategies based on resilience theory and evaluating their effectiveness.

A mixed-method approach was employed to identify PRM strategies. Firstly, a comprehensive literature review identified 40 potential PRM strategies. However, the applicability of those 40 strategies was uncertain due to the scarcity of PRM studies. Thus, expert interviews, drawing on the insights of Chinese infrastructure industry professionals with experience in FII, were applied to review the identified strategies. This process reduced the pool of applicable strategies to 34. Subsequently, 356 questionnaires were sent out to investors from China, Australia and Singapore, with 218 valid responses returned. Based on the data collected from the surveys, statistical analysis was used to evaluate and classify applicable PRM strategies.

Results reveal the most effective top five strategies for offsetting the detrimental effects of political risk on foreign infrastructure investment to be: (1) selection of suitable markets and projects; (2) maintaining good relationship with government; (3) purchasing political insurance; (4) utilizing capable contractors from both host country and home country; and (5) adopting an appropriate entry mode. The 34 strategies were further consolidated into four meta-strategies through factor analysis, resulting in the formulation of a strategy selection matrix.

The findings of this study offer a rational means by which infrastructure investment practitioners considering projects in developing countries, may arrive at an optimal political risk mitigation strategy. The findings also offer government of host countries directives to improving the political environment in order to attract foreign investment flows into local infrastructure projects.

The aim of this research is to propose a quantitative approach to evaluating the quality of services provided, helping organizations to make strategic decisions by better understanding the characteristics that satisfy consumers.

The approach was based on the integration of the Kano model with SERVQUAL, adapted by the satisfaction equations of Albuquerque et al. (2022) and fuzzy systems theory. Through this, it was possible to infer which attributes influence customer satisfaction, identifying the ranges of satisfaction and, with the help of fuzzy, reducing the imprecision of customer perceptions.

A total of 42% of the attributes were classified as unidimensional, with attribute 11 (Reliability) and attribute 9 (Courtesy) having the highest satisfaction values. Attractive attributes accounted for 38% of the sample, with attribute 29 (Variety of products) and attribute 7 (Location) having the greatest impact on satisfaction. On the other hand, attribute 30 (Order Delay) and attribute 31 (Waiting for payment) caused more dissatisfaction among consumers (ranges −0.6, −0.71, respectively). In addition, Variety of products was the most satisfactory, while Order Delay generated the most dissatisfaction among users.

The originality of this research lies in its contribution to organizations in relation to the services offered by investigating a gap in the studies that use the Kano model, integrated with SERVQUAL, which do not include reverse attributes in their equations and analyses. With the help of fuzzy sets, the subjectivity of the individual can be translated into data for greater clarity of information.

The purpose of this study is to analyse the recently highly debated topics of the Tax avoidance–Corporate social responsibility (CSR) performance nexus and to further investigate the impacts of engaging in socially responsible activities on financial performance and bank debt financing constraints, at a disaggregate level (firm level).

The sample for this study includes all publicly listed companies headquartered in BRICS countries from 2014 to 2020. The study employs detailed financial accounting information and the Environmental, Social and Governance scores released by Thomas Reuters EIKON database, which is regarded as the most authoritative indicator of CSR performance. Both pooled and panel data regression models are employed, and robustness tests that use a wide range of model specifications, measures and estimators are performed.

The study finds robust evidence that corporate tax avoidance is negatively associated with CSR performance. The authors also find that firms with better CSR performance have healthier financial performance and lower costs of bank debt. Overall, the research findings are supportive of the corporate culture theory, which suggests that firms behave ethically consistent in both CSR practices and tax payment.

CSR performance and the engagement of tax avoidance activities have been documented in the literature to be vital elements investors care about. This study focuses specifically on the association between them and further elaborates their impacts in the financial markets. To the best of the authors' knowledge, this is the first study which investigates the nexus in a sample that includes the most powerful emerging markets in the world. The results of this study are generalisable in terms of the implications of CSR management to many other emerging markets.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

This study aims to explore the perceptions of investors regarding the risks associated with funding renewable energy projects in India, as well as the various factors that influence these perceptions. The investigation is limited to debt providers and seeks to pinpoint the primary risks that bankers perceive and the drivers that shape these perceptions.

This study draws on interviews and surveys of Indian bank executives, investigating how finance providers perceive risks in the Indian context and the factors driving such perceptions. Qualitative interviews have been used for operationalizing “risk perception” within the renewable energy domain, followed by a quantitative survey and exploratory factor analysis.

The authors find that experience and capacity are the most important factors that account for 30% of the overall variance. The second factor, which accounts for 15% of the variance, includes the perceived risks in funding renewable energy projects as compared to infrastructure projects. Among individual risks, the authors find that bankers perceive technological risk to be the lowest (5%) and contractual and regulatory risks as the highest (66%) in renewable energy projects.

The study contextualizes risk perception toward renewable energy investments in the Indian context by drawing from the risk perception literature and qualitative interviews with senior bankers. It presents empirical evidence on the decision-making behavior of bankers, who are important stakeholders of the renewable energy ecosystem. The main limitation of the study is the relatively small sample, and generalizing the results to the broader population might require a larger sample. This will facilitate the use of confirmatory factor analysis and structural equation modeling, which can facilitate a more comprehensive understanding of risk perceptions in renewables financing.

Insights gained can be used to provide policy recommendations for improving the financing ecosystem of renewable energy projects. The research significantly contributes to the extant literature within the renewable energy financing domain for emerging economies.

This study aims to investigate the relationship between stock liquidity, future investment, future investment efficiency and the moderating effect of financial constraints.

To serve the purpose of the study, the data of 178 companies listed on the Tehran Stock Exchange in 2012–2017 were examined. In this research, two Amihud liquidity and stock trading turnover measures were taken for the liquidity. Due to variance heterogeneity, the FGLS test was used. Moreover, a modified multiple regression analysis was used to investigate the moderating role of financial constraints.

The results showed a significant positive relationship between the firm stock liquidity in the current year and the next year investment; the firm stock liquidity (based on the stock trading turnover) in the current year and the next two years’ investment; the firm stock liquidity (based on the trading turnover index) in the current year and the next year investment efficiency; and the firm stock liquidity (based on the stock trading turnover) in the current year and the next two years’ investment efficiency. Moreover, financial constraints negatively moderated the relationship of firm stock liquidity (based on trading turnover index) in the current year and investment in the next year; investment in the next two years; investment efficiency in the next year; and investment efficiency in the next two years.

Given the importance of investment and investment efficiency in emerging markets especially in Asian emerging markets, and because the predicted impacts through financing constraints are usually unclear, this paper attempted to fill the existing gap and be innovative in this regard.

The adaptability of multi-functional industrial buildings can be an important factor in their reuse. This utility requires the evaluation of factors that are effective apart from physical interventions. Therefore, this study used a combined method to investigate the factors affecting the reuse of the case studies of Iran and their adaptation to the theories proposed in the field of industrial heritage. This study aims to achieve effective strategies in adaptive reuse of industrial heritage buildings.

Hence, six factors in the economic, social, technological, environmental and legal sectors were analyzed based on PESTEL analysis and the interactions of the proposed matrix factors were evaluated. The results from this evaluation were integrated based on conceptual similarities and examined by SWOT technique as the main factors. Finally the criteria obtained from SWOT analysis has been approved by a Delphi survey.

Consequently, the interaction of the findings to determine the strategy was multiplied in a matrix and the resulting concepts were identified. Finally, 23 strategies were extracted as the factors affecting the reuse of industrial heritage buildings and dealing with future issues. According to the results, the most important strategies are government policies and interventions. Also, the determination of the status of ownership, supervision by the Ministry of Cultural Heritage over the preservation and revitalization of industrial heritage buildings and intervention policies for defining the uses related to an industrial building fall into this category.

The findings of this study indicate that an adaptive view of the above strategies and the indicators of each factor could affect the adaptive reuse of the industrial heritage.