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This study aims to examine the effects of product market competition (PMC) on analysts’ earnings forecast attributes, particularly forecast accuracy and dispersion. The authors also investigate whether investor protection moderates the relationship between PMC and forecast attributes.

The sample covers 49,578 firm-year observations from 38 countries. This study uses an ordinary least squares regression, a Heckman two-stage regression and an instrumental two-stage least squares regression.

This study finds that PMC is associated with higher forecast accuracy and lower dispersion. The results also show that investor protection enhances the effect of PMC on forecast accuracy and dispersion. These findings imply that countries with strong investor protection have a better information environment, as exhibited by the stronger relationship between PMC and analysts’ forecast properties.

The findings highlight the importance of strong governance mechanisms in both the country and industry environments. Policymakers, including government agencies and financial regulators, can leverage these insights to formulate regulations that promote competition, ensure investor protection and facilitate informed investment decisions.

This study advances our understanding of how PMC affects analysts’ earnings forecast attributes. In addition, it pioneers evidence of the moderating role of investor protection in the relationship between PMC and forecast attributes.

Evolved from Toyota’s shop floor in Japan, lean bundles are universally accepted for boosting manufacturing performance. However, extant literature shows mixed findings on the effectiveness of lean bundles in non-Japanese settings. This meta-analysis is aimed at understanding the influence of national culture (NC) differences on the lean bundles-performance relationships.

A total of 224 effects from 12,569 observations across 48 empirical studies from 14 countries are meta-analyzed. Also, weighted least squares (WLS) meta-regression using NC scores from the Global Leadership and Organizational Behavior Effectiveness (GLOBE) study are conducted to test the moderating effect of NC dimensions.

The meta-analysis reveals a positive association between the lean bundles and firm performance; though, the strength of the association varies across the individual lean bundles. The meta-regression results show that lean practices are more effective in countries that value high future orientation, high collectivism, low-performance orientation and high assertiveness.

The results contribute to the literature on the role of local cultural influence on strategies and decisions related to the implementation of continuous improvement (CI) programs in cross-cultural settings.

This study aims to examine the effect of audit firm tenure (AFT) on corporate tax avoidance (CTA) and the moderating effect of the COVID-19 pandemic.

The sample comprises 41,074 firm-year observations from 32 countries from 2015 to 2020, for which data are collected from various sources: financial data from the Refinitiv database, country corporate tax rates from the Tax Foundation, and other country-level data from the World Bank database. The authors use the book tax difference to measure CTA and multiple proxies for AFT.

This study finds that a longer AFT is associated with higher CTA, confirming the notion that long AFT impairs auditor independence. The findings remain robust when considering various AFT proxies, incorporating Hofstede’s cultural factors, using weighted least-squares estimation and addressing endogeneity through propensity score matching. This study also finds a non-linear relationship between extended client and auditor relationships and CTA, supporting the mandatory audit firm rotation regulation and increasing investors’ caution regarding the consequences of extended client–auditor relationships on firm behaviour.

This study offers new evidence on the effect of the COVID-19 pandemic on the link between AFT and CTA and documents a non-linear relationship between AFT, which has not been addressed in prior studies.

The findings of this study have several significant practical implications. First, governments and policymakers gain insights into the consequences of extended auditor–client relationships, hence calling for a review of auditing and taxation regulations. Second, the findings provide important insights into the issue of auditor independence, especially during long engagements and crises such as COVID-19. Finally, investors and tax authorities should be more cautious about the risks of aggressive tax avoidance during crisis periods.

To the best of the authors’ knowledge, this is the first study to use a global data set to investigate the effect of AFT on CTA during the COVID-19 pandemic.

In the last 3 decades, organization-wide programs and practices based on the Total Quality Management (TQM) philosophy have become central to continuous improvement (CI) strategy in both public and private enterprises. However, there is paradoxical evidence of TQM-firm performance linkage in non-Japanese contexts. This study presents a meta-analysis of empirical research on TQM-firm performance linkage and investigates the moderating influence of national cultural (NC) values on this relationship.

Meta-analytical procedures are adopted to analyse 364 effects accumulated from 135 independent samples across 31 nations, for 30,015 firm observations. Additionally, weighted least square (WLS) meta-regression is used to test the moderation effects of four NC dimensions based on the Global Leadership and Organizational Behavior Effectiveness (GLOBE) model.

The meta-analysis results reveal that the strengths of the association varied across five soft and hard TQM dimensions and three firm performance dimensions Meta-regression indicate that the effectiveness of the TQM program is high in cultures which reward collectivist behaviours, equity of power distribution and avoidance of ambiguity in rules/structures.

The study contributes to international operational management theory on cultural influences on the effectiveness of operations strategies and decisions.

This study aims to investigate two issues: (1) a nexus between climate-related financial policies (CRFP) and global value chains (GVC) and (2) the government’s policies to help countries enhance the efficient use of CRFP in improving a country’s likelihood to participate in GVC.

To investigate the connection between GVC and CRFP, the authors incorporate that backward participation is measured using foreign value-added, while domestic value-added is used to measure forward participation, quantified as proportions of gross exports. The study analyses yield significant insights across a span of 20 developing countries and 26 developed countries over the period from 2010 to 2020.

Regarding the first issue, the authors affirm the presence of a linear link between GVC and CRFP, implying that involvement in CRFP is advantageous for both backward and forward participation. Furthermore, the authors identify long-term GVC and CRFP cointegration and confirm its long-term effects. Notably, the expression of a linear relationship between GVC and CRFP appears to be stronger in developing countries.

The study findings, together with previous research, highlight the importance of financial policies relating to climate change (CRFP) in the context of economic growth. Climate change’s consequences for financial stability and GVC highlight the importance of expanded policymakers and industry participation in tackling environmental concerns.

Regarding the second issue, the study findings suggest critical policy implications for authorities by highlighting the importance of financial stability and expanded policymakers in promoting countries' participation in GVC.

This paper investigates the link between GVC performance and CRFP, offering three significant advances to previous research. Moreover, as a rigorous analytical method, this study adopts a typical error model with panel correction that accounts for cross-sectional dependency and stationarity.

Modern renewable energy is crucial for environmental conservation, sustainable economic growth and energy security, especially in developing East African nations that heavily use traditional biomass. Thus, this study aims to examine urbanization and modern renewable energy consumption (MREC) in East African community (EAC) while controlling for gross domestic product (GDP), population growth, foreign direct investment (FDI), industrialization and trade openness (TOP).

This study considers a balanced panel of five EAC countries from 1996 to 2019. Long-run dynamic ordinary least squares (DOLS) and fully modified ordinary least squares estimations were used to ascertain the relationships while the vector error-correction model was used to ascertain the causal relationship.

Results show that urbanization, FDI, industrialization and TOP positively affect MREC. Whereas population growth and GDP reduce MREC, the effect for GDP is not that significant. The study also found a bidirectional causality between urbanization, FDI, TOP and MREC in the long run.

Investing in modern renewable energy facilities should be a top priority, particularly in cities with expanding populations. The governments of the EAC should endeavor to make MREC affordable among the urban population by creating income-generating activities in the urban centers and sensitizing the urban population to the benefits of using MREC. Also, the government may come up with policies that enhance the establishment of lower prices for modern renewable energy commodities so as to increase their affordability.

MREC is a new concept in the energy consumption literature. Much of the research focuses on renewable energy consumption including the use of traditional biomass which contributes to climate change negatively. Besides, the influence of factors such as urbanization has not been given significant attention. Yet urbanization is identified as a catalyst for MREC.

Based on the research of free trade agreements on alleviating service trade policy heterogeneity and its impact on manufacturing exports, this article aims to not only provide a basis for China's strategy of promoting regional economic integration, but also provide a policy reference for the manufacturing industry to expand the export market space.

This study uses the two principles of “answering” and “scoring” to quantify the indicators of service trade policy heterogeneity to test the relationship between heterogeneity of service trade policy, free trade agreement and manufacturing export.

According to empirical study, the export of Chinese manufacturing firms is severely hampered by the variety of service trade regulations, and the bigger the enterprise, the more hampered it is. In comparison to communications, transport and commerce, the financial industry's policy heterogeneity has a greater negative impact on certain industries. The major methods used to reduce the impact of service trade policy heterogeneity on manufacturing exports are product price increases and product quantity reductions. Also, by reducing the heterogeneity of service trade regulations and fostering industrial exports, the free trade agreement that China has signed can be quite successful. The open commitment in the area of national treatment, however, can reduce policy heterogeneity and advance manufacturing.

In the area of market access, the effect of export is superior to the open promise. Thus, in order to effectively support the stabilization of international trade, China should actively encourage the negotiation and signing of higher-quality and mutually beneficial free trade agreements.

The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

This study aims to test mutual fund superiority, comparing the performance of 646 Islamic mutual funds with 475 ethical funds and conventional proxies.

This study uses statistical methods including paired t-statistics of independent samples, one-way Bonferroni test–analysis of variance–F-statistic for testing means equality, the chi-squared test for median equality and regression models corrected for heteroscedasticity. These methods are used to identify superiority of mutual funds and to validate the significance of the results.

The findings confirm the superiority of conventional funds over ethical funds and ethical funds over Islamic funds. Both ethical and Islamic funds, however, outperform conventional proxies during some recessionary periods. Moreover, stronger performance is recorded for Islamic funds in Europe and North America regions and across age and asset allocation categories, but limited support for reversal fund size, composition focus and reversed price effect.

These findings should assist investors when deciding to invest and motivate Islamic and ethical funds to improve their portfolio formation and asset allocation strategies set by their professional managers.

The originality of this study is in its comprehensive approach in that it compares the performance of funds after accounting for such characteristics as fund objectives, size, age, asset allocation, geographical investment focus, fund composition focus, share price levels and the effect of global crises. This study approach is not only original and productive in documenting Islamic funds’ performance for the past three decades (1990–2022) but can also update the literature on these characteristics collectively and individually.

Numerous attempts at installing six sigma (SS) have faced challenges and fallen short of the desired success. Thus, it becomes vital to identify the critical factors and characteristics that play a pivotal role in achieving successful adoption. In this study the research has aimed to highlight that a considerable number of corporate SS initiatives, around 60%, fail primarily due to the improper incorporation of essential elements and flawed assumptions.

To validate the influence of critical success factors (CSFs) on SS accomplishment, the study employed a research design combining exploratory and mixed-methods approaches. A Likert-scale questionnaire was utilized, and a simple random sampling method was employed to gather data. Out of the 2,325 potential participants approached, 573 responses were received, primarily from Germany, the United Kingdom and Sweden. The analysis focused on 260 completed questionnaires and statistical methods including structural equation modeling (SEM), exploratory factor analysis (EFA) and Confirmatory Factor Analysis (CFA) were utilized for data analysis.

The study acknowledged four essential components of CSFs that are imperative for sustaining the success of SS: (1) Competence of belt System employees; (2) Project management skills; (3) Organizational economic capability and (4) Leadership commitment and engagement. These factors were identified as significant contributors to the maintenance of SS’s success.

The practical implications of this research imply that institutions, practitioners, and researchers can utilize the four identified factors to foster the sustainable deployment of SS initiatives. By incorporating these factors, organizations can enhance the effectiveness and longevity of their SS practices.

The investigation's originality lies in its contribution to assessing CSFs in SS deployment within the European automobile industry, utilizing a mixed-methods research design supplemented by descriptive statistics.