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The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

The purpose of this paper is to calculate the financial inclusion index and analyze its dynamics in developing countries.

The authors use the two-stage principal component analysis (PCA) method and consider financial technology innovations to improve the accuracy of the financial inclusion index.

The authors found a downward trend in the financial inclusion index in most developing countries over the study period. The authors also found that a high financial inclusion index is linked to high scores in the Doing Business and high business climate regulation ranking. In addition, the authors observed that the rates of low financial inclusion in developing countries are due to low utilization of and unequal access to financial services.

The analysis suggests that policymakers in developing countries could invest in digital infrastructure to extend access to financial services in remote areas. They could also encourage financial innovation, particularly in financial technologies, by adopting flexible regulatory frameworks. Promoting the financial inclusion of marginalized groups through targeted initiatives tailored to their needs is another solution. They could also encourage the use of financial services by raising awareness and educating populations through training programs. Finally, to improve the business climate, governments could simplify administrative procedures and promote transparency and legal stability.

Unlike previous studies, the use of the two-stage PCA method and the consideration of financial technology (Fintech) innovations such as mobile money in the determinants of the financial inclusion index improve the accuracy of the index.

This study investigates the impact of corporate social responsibility (CSR) on corporate innovation. We selected the listed nonfinancial firms of South Asian Economies. The sample of the study comprised a total of 426 listed manufacturing firms of South Asian Countries for period spans 10 years from 2012 to 2021. In this study, descriptive statistics, multicollinearity diagnostic tests, correlation analysis and two-step dynamic panel system generalized method of moments (GMM) were applied to analyze the data. CSR measured with three proxies' social indicators, environmental indicators, and CSR composite index of social and environmental indicators. However, corporate innovation is captured with number of citations received in a year and number of patents filed in the year. Overall, findings of the study using all measures of CSR shows that CSR significantly and positively related with corporate innovation. Our results find support for CSR-innovation view with all measures of CSR. The findings suggest that the current study is helpful for managers, regulators, policymakers, and researchers. For managers, the study helps them to make the CSR and innovation decision. The policymakers should take appropriate innovative decision while considering factors such as CSR. This study can also be extended by considering this study for developed and emerging economies sample.

The study aims to find out the impact of financial inclusion and financial development on financial stability using panel data from eight countries in the Middle East and North Africa (MENA).

To achieve the aim of the study, the researcher prepared two indicators of financial inclusion and governance to find out the impact of financial development on the relationship between financial inclusion and financial stability. Data on financial inclusion was obtained from the International Monetary Fund, data on financial development and financial stability were obtained from the World Bank.

The results of the fixed and random effect methods show that financial inclusion has a significant positive effect on financial stability. Additionally, financial development represents a moderating variable in the significant positive effect on the relationship between financial inclusion and stability in the MENA countries.

The current study suffers from some limitations that researchers must be aware of in future research. First, there is an inability to determine qualitative aspects such as time and cost when designing a composite indicator of financial inclusion. Second, due to limited data, we used only eight countries from the MENA. It is suggested to expand the sample to include other countries.

This paper contributes to the related literature between financial inclusion and financial stability by confirming or denying the results of previous studies. Also, to the best of the author’s knowledge, this paper is the only one that explains the role of financial development in the relationship between financial inclusion and stability in MENA countries, using a composite index to calculate financial inclusion. Finally, the study seeks to focus the attention of the government and policymakers to build a system of financial inclusion that leads to improving financial stability.

Many environmental problems are due to the unfavorable environmental intentions and cultural–behavioral weaknesses in the relationship between man and nature. This study aims to adopt an environmental psychological perspective to green intention (GI) and green behavior (GB) of agricultural students; to this end, protection motivation theory (PMT) was used as the core of the theoretical base.

This research method was based on descriptive–correlational and causal–relational analyses. The statistical population included agricultural students of Iranian universities with green university standards (N = 5,582). Out of the total population, 384 students were selected as the study sample. The research instrument was a questionnaire whose validity was confirmed using a panel of experts and the average variance extracted. Also, its reliability was verified by Cronbach’s alpha coefficients (0.61 ≤ α ≤ 0.92), principal component analysis and composite reliability index.

The results of structural equation modeling showed that the obtained model is able to explain 36.3% and 5.56% of GB and GI variance changes, respectively. In addition, the results revealed that GI has the greatest effect on GB (β = 0.362).

It is worth to mention that according to the results, most of the independent variables, besides the direct effects they have on students’ GB, also indirectly affect this variable. This effect was performed through the key variable – GI. In other words, it can be concluded that the GI variable successfully mediates the effects of variables such as response efficacy (RE), self-efficacy (SE) and environmental norms (EN). Therefore, it is suggested that in the behavioral changes interventions in GB of agricultural studies, it should be considered that the presence or absence of GI can affect the actual behavior of individuals. In other words, it is recommended that to accelerate actual behavioral changes, behavioral interventionists should first focus on encouraging people’s GI.

It can be said that the conclusion of this research can provide a basis for the successful encouragement of students to GB. First, GI, as a key element, can mediate the impacts of variables such as RE, SE and EN on students’ GB. Second, PS only directly affects students’ GB. Third, RE has no significant impact on GB, but its effect on GI is significant. Fourth, RC affects students’ GI directly, without mediation. Fifth, SE and EN constructs affect students both directly and indirectly GB of students through GI. Knowing the location of the effect of these variables on each other and the role they have in explaining GI and GB of agricultural students presented some suggestions that can prepare the ground for further development of GB. Hence, managers, students, agricultural educators and other users can use these results to accelerate GB changes.

The conclusion of this research might provide a basis for the successful encouragement of students to GB. In interventions to change GB, it would be essential to pay enough attention to the fact that the presence or absence of GI might affect the actual behavior. It is suggested that behavioral interventionists focus on encouraging people’s GI so as to be able to accelerate the actual behavioral changes.

Despite city authorities in Bangladesh being concerned about urban sustainability, they often face difficulties in addressing predominant urban challenges threatening urban sustainability, due to limited relevant literature. To reduce this gap, this study aims to address the predominant urban challenges and assess their severity levels in four city corporations of Bangladesh, e.g. Rajshahi, Sylhet, Barishal, and Gazipur.

Using a mixed-method approach, this study rigorously analyzed field-level data obtained from 1,200 residents across selected cities using diverse statistical techniques. The quantitative analysis included descriptive analysis, exploratory factor analysis, and chi-square tests, whereas qualitative insights were derived through thematic analysis.

The study uncovered nine predominant urban challenges under two crucial factors “Feeble Urban Management” and “Illicit Activities” that collectively explain 62.20% variance. “Feeble Urban Management” explains 44.17% variance, whereas “Illicit Activities” accounts for 18.13%. Within these challenges, uncontrolled urban sprawl, inadequate disaster management, congested roads, and shabby drainage and waste management pose significant threats to urban sustainability. Illicit activities, manifested by encroachment on water sources, grabbing roadside, destruction of natural properties, and activities undermining social security, compound the urban sustainability issue. Severity analysis reveals Sylhet (54.5%), Rajshahi (46.4%), and Barishal (31.2%) as highly impacted, whereas Gazipur exhibits moderate severity (66.7%).

The findings of this study reveal intrinsic insights into urban challenges in Bangladesh that will provide valuable guidance to city authorities, equipping them to implement integrated and effective initiatives and programs that overcome these predominant urban challenges, with a specific focus on Rajshahi, Sylhet, and Barishal city corporations.

The authors aimed to examine how the level of digitalization in Poland and Ukraine affects the contribution of small and medium-sized enterprises (SMEs) to the countries’ gross domestic product (GDP).

The study involved a comparative analysis and statistical modeling of the impact of key economic factors on the contribution of SMEs to Poland’s and Ukraine’s GDP in the 2010–2020 period. The authors used principles of the theory of economic growth and calculated the coefficient of digital competitiveness as a composite indicator consisting of a number of global indices.

The study revealed significant differences between both countries, which can be attributed to a higher level of digitalization in Polish SMEs. The authors used the Polish experience to recommend how to reform Ukraine’s digital economy in postwar recovery.

The contribution of SMEs to Poland’s GDP is higher than that of Ukraine’s because of the higher entrepreneurship rate in the Polish micro and small enterprises (MSEs) sector. The authors found that a unit change in the integrated coefficient of digital competitiveness is related to the greatest change in the contribution of SMEs to the country’s GDP when the other factors in the model equation remain fixed.

The purpose of this paper is to identify the differences between Hungarian family-owned businesses (FOBs) and non-family-owned businesses (NFOBs) concerning the elements of SME competitiveness and financial performance.

The research covers the Hungarian data set of the Global Competitiveness Project (GCP, www.sme-gcp.org) of 738 (data collection between 2018 and 2020) non-listed SMEs, of which 328 were FOBs. The study uses the comprehensive, multidimensional competitiveness measurement of the GCP built on the resource-based view (RBV) and the configuration theory. Financial performance was captured with two composite indicators: short-term and long-term financial performance (LTFP). The comparative analysis between FOBs and NFOBs was conducted using binary logistic regression.

The results show that FOBs are more prone to focusing on local niche markets with higher longevity and LTFP than NFOBs. However, FOBs have lower innovation intensity and less organised administrative procedures. The most contradicting finding is that the FOBs’ higher LTFP is accompanied by significantly lower competitiveness than in the case of NFOBs.

This study goes beyond other GCP studies by including composite financial performance measures among the variables examined. The combination of performance-causing (resources and capabilities) and performance-representing (financial performance) variables provides a better understanding of the non-listed SMEs in terms of family ownership. The results help academia to enrich the RBV-competitiveness, the non-listed SME management and finance literature, and policymakers to design business development and support schemes. They also show future entrepreneurs the impact of family ownership on entrepreneurial success.

The study aims to promote the use of qualitative methods in service research by investigating how these methods are reported in service journals, how the level of reporting has evolved and whether methodological reporting influences the downloads or citations received by qualitative articles.

Methodological reporting practices were identified through content analysis of 318 qualitative articles published in three major service research journals and comparison with prior methodological literature. Regression analysis was used to test how the level of methodological reporting influences article downloads and citations.

The study identifies 29 reporting practices related to 9 key methodological reporting areas. The overall level of methodological reporting in published qualitative articles has increased over time. While differences in the level of reporting between service journals persist, they are narrowing. The level of methodological reporting did not influence downloads or citations of qualitative articles.

Service scholars using qualitative methods should pay attention to methodological reporting as it can improve the chances of being published. Factors such as theoretical contributions are likely to have a greater influence on article impact than methodological reporting.

No prior study has explored methodological reporting practices across different qualitative methodologies or how reporting influences article impact. For authors, reviewers and editors, the study provides an inventory of reporting practices relevant for evaluating qualitative articles, which should lower barriers for qualitative methods in service research by providing practical guidelines on what to focus on when reporting and assessing qualitative research.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.