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There is a dearth of research that investigates the impact of national culture on budgeting and management indexes in the public sector across developing countries. Limited studies in accounting and management have explained the role of national culture in shaping organisational and individual values. It is posited that national cultural variables impact budget transparency and performance management. This study contributes to the literature by examining these relations in 16 developing countries.

Adopting an unbalanced timing framework, the current paper seeks to fulfill this gap and applies four cultural dimensions from the GLOBE study (House et al., 2004) as explanatory variables to investigate whether national culture is associated with budget transparency and performance management or not, particularly in the context of developing countries. The paper uses budget transparency as the first dependent variable, based on the OECD database from Qi and Mensah (2011), along with performance management as the second dependent variable, from the BTI Project (2016), according to the leadership's political performance management.

Generally, the empirical findings reveal a minimal relation among GLOBE cultural variables with budget transparency and performance management. Particularly, the empirical findings indicate that only performance orientation has a significant relation with budget transparency and performance management.

The findings of this paper suggest that any plan to improve a nation's budget transparency should consider the links between budgeting, performance management and the culture of those that run them.

The formal adoption of new methods by performance management may not be enough without accompanying efforts to transform performance orientation as an index of national culture.

With suitable optimization criteria, hybrid models have proven to be efficient for preparing portfolios in capital markets of developed countries. This study adapts and investigates these methods for a developing country, thus providing a novel approach to the application of banking and finance. Our specific objectives are to employ a stochastic dominance criterion to evaluate the performances of over-the-counter (OTC) companies in a developing country and to analyze them with a hybrid model involving particle swarm optimization and artificial neural networks.

In order to achieve these aims, the authors conduct a case study of OTC companies in Iran. Weekly and daily returns of 36 companies listed in this market are calculated for one year during 2014–2015. The hybrid model is particularly interesting, and the results of the study identify first-, second- and third-order stochastic dominances among these companies. The study’s chosen model uses the best performing combination of activation functions in our analysis, corresponding to TPT, where T represents hyperbolic tangent transfers and P represents linear transfers.

Our portfolios are based on the shares of companies ranked with respect to the stochastic dominance criterion. Considering the minimum and maximum numbers of shares to be 2 and 10 for each portfolio, an eight-share portfolio is determined to be optimal. Compared with the index of Iran OTC during the research period of this study, our selected portfolio achieves a significantly better performance. Moreover, the methods used in this analysis are shown to be as efficient as they were in the capital markets of developed countries.

The problem of optimizing investment portfolios has to allow for correlations among returns from the financial maintenance period under consideration if an asymmetric distribution of returns exists (Babaei et al., 2015). Therefore, it is desirable to select an appropriate criterion in order to prepare an optimal portfolio and prioritize investment options. Although a back propagation technique is very popular in artificial neural (ANN) training, it is time-consuming to train a network in this way, and other methods such as particle swarm optimization (PSO) should be considered instead. In the hybrid combination of PSO and ANN, it is not the structure of a neural network that changes. Rather, the weighting method and the training technique chosen for the network are the important aspects, and these relate to PSO, so the only role ANN plays in this process is to reduce the errors.

The hybrid model combining ANN and PSO is seen to be considerably successful for generating optimal results and appropriate activation functions. These results are consistent with the theoretical findings of Das et al. (2013) and an application of the simple PSO in a study conducted by Pederson and Chipperfield (2010). Our research results also confirm the efficiency of stochastic dominance criteria as noted in the studies conducted by Roman et al. (2013), ANN as in a study carried out by Kristijanpoller et al. (2014) and PSO as in studies conducted by Liu et al. (2015) and Deng et al. (2012). These studies were carried out in the capital markets of developed countries, whereas the authors’ analysis relates to a developing country.

The authors deduce that the tools and methods whose efficiency was proven in the capital markets of developed countries also apply to, and demonstrate efficiency in, two novel applications of portfolio optimization within developing countries. The first of these is gaining familiarity with the theory and practice of these research tools and the methods that enrich financial knowledge of investors in developing countries. The second of these is the application of tools and methods identified by investors in the capital markets of developing countries, which enables optimal allocation of financial resources and growth of the markets. The authors expect that these findings will contribute to improving the economies of developing countries and thus help with economic development and facilitation of improving trends.

Poverty is a global problem and the phenomenon is alarming in the third world including the Muslim Countries (MCs). This paper analyses Islam's view on poverty based on its ideological norms and values. Poverty has been defined from an Islamic perspective that leads to two poverty levels and hence two poverty lines which are quite different from the conventional of concepts of poverty. The basic Islamic sources suggest that Islam dislikes poverty and it provides a conducive framework for alleviation of poverty. Three broad categories of poverty alleviation measures have been analysed. First, the positive measures which include income growth, functional distribution of income, and equal opportunities to all. Second, the preventive measures which are control of ownership and prevention of malpractices in economics and business that lead to income concentration. Third, corrective measures which include compulsory transfer payments, recommended transfer payments, and state responsibility. The positive measures are expected to lead to high level income and its equitable distribution, the preventive measures are expected to limit concentration of wealth, while the corrective measures are meant for correcting imbalances in the distribution of income and wealth, and to upgrade economic conditions of the worse‐off population in the society. If these measures are applied, the problem of poverty could be solved quite substantially. The paper concludes with some recommendations with respect to poverty alleviation in the context of MCs.

This study aims to examine the value relevance of earnings in terms of predicting the value variables such as cash flow, capital investment (CI), dividend and stock return under the Indian institutional settings.

The study used panel Granger causality tests to examine causality relationships among variables and panel data regression models to check the statistical associations between earnings and value variables.

Based on a data set of 7,280 Bombay Stock Exchange-listed firm-years spanning over ten years from March 2009 to March 2018, the results show higher sensitivity of earnings toward cash flows, CI, divided and stock return and vice-versa. Further, the findings deduced from the empirical results demonstrate that earnings are positively related to value variables. Overall, the results established that earnings are value-relevant and have predictive ability to forecast the value variables that facilitate investors in portfolio valuation. The results are consistent with the predictive view of the value relevance of earnings. Several robustness checks confirm these results.

This study brings new empirical evidence from a distinct capital market, India, and provides a new facet to the value relevance debate in terms of its prediction view. The study is among earlier attempts that jointly measure the ability of earnings in forecasting different value variables by taking a uniform sample of firms at the same period. Hence, the study provides a comprehensive view of the predictive ability of reported earnings.

The purpose of this paper is to examine the extent of human capital (HC) reporting in leading Bangladeshi firms using the HC reporting framework, thereby making a contribution to the body of knowledge in the area of HC reporting practice in a developing country context.

Using the technique of content analysis, three years of annual reports of 32 leading manufacturing and service sector companies listed on the Dhaka Stock Exchange (DSE), selected on the basis of the market capitalization, were examined to identify any HC reporting trends.

The findings reveal that the HC reporting practices of leading Bangladeshi firms are not as low as projected in relation to the total list of items reported. The most commonly disclosed HC items are information on employee training, number of employees, career development and opportunities that firms provide, and employee recruitment policies. Moreover, as a result of a degree of intervention on the part of some Bangladeshi regulators, the extent of reporting has increased during 2009/2010.

The principal limitations of the study are that it is based on a small non‐random sample of firms taken from a single country and drawing solely annual reporting information.

This is the first paper that documents HC‐related disclosures in the context of a transitional economy such as Bangladesh using multi year‐data. The study contributes to the HC literature by providing empirical evidence of the status of HC reporting in a developing country context.

This paper aims to conceptualize the nexus between the participatory finance and the higher ethical objectives within the Islamic moral economy, also termed as Maqasid al Shari’ah.

Insights from the extant Islamic economics and finance literature are integrated through an interpretative systematic review using the principles from critical interpretative synthesis (CIS).

A coherent framework is synthesized comprising the typology of the Maqasid al Shari’ah, the axioms of participatory finance and their nexus which is formulated by theorizing the common thread of meaning through the axioms of participatory finance and Maqasid al Shari’ah at the interpretative level. This framework postulates that the participatory finance fits well in the ethos and the value system of Islam. Moreover, “social well-being” invariably provides the nexus between the Maqasid al Shari’ah and participatory finance.

This study contributes to the Islamic economics and finance literature by integrating the dissenting views from the divergent literature related to the basic philosophy of Shari’ah and participatory finance and provides grounds for policy implications, particularly, for designing the financial products. Moreover, it demonstrates an application of interpretative systematic review in Islamic banking and finance research.

Many developed countries have been using environmental taxes in their economic systems for many years. These taxes have a great impact on reducing the environmental damages of companies and individuals in society. But many developing countries have not used this tool effectively yet, and some countries face barriers to the effective implementation of environmental taxes that make it difficult and unsuccessful. To increase the effectiveness of the implementation of environmental taxes, governments must prioritize barriers and solutions to overcome its barriers. The identified knowledge gap of the pre-literature review is that an overview of the identification which completely considers all barriers and solutions of environmental taxes implementation does not exist. In response to this knowledge gap, this study aims to identify and prioritize the barriers and solutions of environmental taxes implementation.

Ranking the barriers and solutions is a complicated multi-criteria decision making (MCDM) problem that requires consideration of multiple feasible alternatives and conflicting tangible and intangible criteria. This study addresses the prioritization of solutions of Environmental Taxes implementation by proposing hybrid MCDM methods based on the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and the Fuzzy Technique for order preference by similarity to an ideal solution (Fuzzy-TOPSIS) under fuzzy environment. Fuzzy AHP is used to determine the weight of each barrier using a pairwise comparison, and fuzzy TOPSIS is used to finalize the ranking of solutions for more effective implementation of environmental taxes.

The results showed that environmental tax reform (ETR) (S3) has the highest value among the solutions for more effective implementation of environmental taxes. The result of the proposed model is validated by performing sensitivity analysis.

This study could foster research on the discussion of these barriers and precise ways of implementing solutions to pay more attention to environmental taxes.

Ratings of solutions can be a guide and help governments to improve the implementation of environmental taxes or even develop this policy by being aware of the ranking of barriers and solutions.

This paper creates a new perspective on the effective implementation of environmental taxes, which is closely related to improving environmental performance and increasing social welfare through improving the tax system.

For the first time, this study comprehensively identifies barriers and solutions for more effective implementation of environmental taxes and ranks them using two MCDM techniques.

The success of any organization in a knowledge-based economy depends on effective knowledge transferring and then proper use of the transferred knowledge. As is known, optimizing the knowledge transferring costs in a product portfolio plays an important role in improving productivity, competitive advantage and profitability of any organization. Therefore, this paper aims to determine an optimal product portfolio by minimizing the konlwedge transferring costs.

Here, a fuzzy binary linear programming model is used to select an optimal product portfolio. The model is capable of considering the knowledge transferring costs while taking into account the human-hours constraints for each product by a fuzzy approach. Using fuzzy ranking functions, a reasonable solution of the model can be achieved by classical or metaheuristic algorithms.

Numerical experiments indicate that the proposed fuzzy model is practically effective.

The contributions of this work essentially consist of considering knowledge transferring costs in selecting an optimal product portfolio and using the fuzzy data which make the model more realistic.

Managing project completion within the stipulated time is significant to all firms' sustainability. Especially for software start-up firms, it is of utmost importance. For any schedule variation, these firms must spend 25 to 40 percent of the development cost reworking quality defects. Significantly, the existing literature does not support defect rework opportunities under quality aspects among Indian IT start-ups. The present study aims to fill this niche by proposing a unique mathematical model of the defect rework aligned with the Six Sigma quality approach.

An optimization model was formulated, comprising the two objectives: rework “time” and rework “cost.” A case study was developed in relevance, and for the model solution, we used MATLAB and an elitist, Nondominated Sorting Genetic Algorithm (NSGA-II).

The output of the proposed approach reduced the “time” by 31 percent at a minimum “cost”. The derived “Pareto Optimal” front can be used to estimate the “cost” for a pre-determined rework “time” and vice versa, thus adding value to the existing literature.

This work has deployed a decision tree for defect prediction, but it is often criticized for overfitting. This is one of the limitations of this paper. Apart from this, comparing the predicted defect count with other prediction models hasn’t been attempted. NSGA-II has been applied to solve the optimization problem; however, the optimal results obtained have yet to be compared with other algorithms. Further study is envisaged.

The Pareto front provides an effective visual aid for managers to compare multiple strategies to decide the best possible rework “cost” and “time” for their projects. It is beneficial for cost-sensitive start-ups to estimate the rework “cost” and “time” to negotiate with their customers effectively.

This paper proposes a novel quality management framework under the Six Sigma approach, which integrates optimization of critical metrics. As part of this study, a unique mathematical model of the software defect rework process was developed (combined with the proposed framework) to obtain the optimal solution for the perennial problem of schedule slippage in the rework process of software development.

The purpose of this paper is to investigate the process by which the level of immersion in virtual reality-based behavioral simulation (VR-BS) impacts on the non-cognitive and cognitive outcomes. The cognitive outcome is measured using the increase in the level of Sharia financial literacy, while the noncognitive outcome is measured using the behavioral intention to use VR-BS.

The method consists of two parts: First, the development of VR-BS, in the context of sharia financial literacy, using the waterfall model. Second, testing the effectiveness of VR-BS using the theory of interactive media effects framework. The participants were 142 students from three secondary schools (two Islamic religious schools and one public school) in Yogyakarta and Central Java, Indonesia. Partial least squares structural equation modeling was used for testing the hypotheses.

VR-BS creates a perceived coolness and vividness, which in turn has an impact on increasing the participants’ engagement. Also, the use of VR has an impact on natural mapping, which increases a user’s engagement through its perceived ease of use. As predicted, the user’s engagement affects VR’s behavior, mediated by the user’s attitude toward VR media. VR’s interactivity, however, does not impact on the cognitive aspect.

The participants were not randomly selected, as the data were collected during the COVID-19 pandemic. As a result, the majority of the participants had never tried VR before this study. The participants, however, were digital natives.

It is implied from the findings that Islamic financial business actors and the relevant government agencies (e.g. the Indonesian Financial Services Authority [OJK], the Ministry of Education, Culture, Research and Technology and the Ministry of Religious Affairs) should collaborate to best prepare the future generation of ummah by using VR-BS in their joint promotion and education programs. The results of the current study reveal that the use of VR-BS may attract people to engage in Islamic financial activities. By engaging in such activities, or at least engaging in real-life simulations/classes/workshops, people may gradually acquire more knowledge about Islamic finance.

As predicted, the user’s engagement has an impact on behavior toward VR-BS, which is mediated by attitude toward VR-BS.