Search results

Prior research has investigated the development of Islamic communities. The authors contribute to this line of research by analyzing the effects of Islamic values and Islamic religious practices on entrepreneurship intentions in Islamic communities. Using theory of planned behavior as a theoretical lens, they also take into account that the relationship between religion and entrepreneurial intentions can be mediated by individual’s attitude toward entrepreneurship.

The authors analyze primary data obtained from a sample of 1,895 Pakistani university students. They also use structural equation modeling to perform a nuanced assessment of the relationship between Islamic values and practices and entrepreneurship intentions and to account for mediating effects.

The results show that both Islamic values and Islamic practices positively influence entrepreneurship intentions. Both effects are mediated by the attitude toward entrepreneurship.

The authors contribute to prior research on entrepreneurship in Islamic communities by applying a more fine-grained approach to capture the link between religion and entrepreneurship. Further, they contribute to the literature on entrepreneurship intentions by showing that the influence of religion on entrepreneurship intentions is mainly due to religious values and practices, which shape the attitude toward entrepreneurship and thereby influence entrepreneurship intentions in religious communities.

The present study aims to investigate the impact of corporate governance proxies by ownership structure and firm-specific characteristics, i.e. firm size, leverage, growth opportunities, previous year dividend, firm risk, profitability, and liquidity on dividend behavior of the Pakistan Stock Exchange (PSX) listed firms.

Final sample of the study consists of 140 PSX-listed firms. The study covers a period of six years, starting from 2015 to 2020. Dividend payout dummy, dividend payout ratio, and dividend yield were used to assess the dividend behavior of the sample firms. The appropriate regression procedures (logistic, probit, ordinary least square (OLS), and fixed effect regression) are used to test the study hypothesis. To check the robustness of the result, a system GMM estimation technique is also used in the present study.

The study reveals that institutional ownership, foreign ownership, and individual ownership have a significant positive whereas managerial ownership has a significant negative impact on the dividend decision of sample firms. Among firm-specific characteristics, it was found that liquidity, profitability, and the previous year's dividend were significantly positive, while growth opportunities were significantly inversely associated with dividend payout decisions of PSX-listed firms.

This study sheds light on the relationship between dividend policy, ownership structure, and firm-specific factors in the context of an emerging market like Pakistan. The study's findings have important implications for managers, minority shareholders, lawmakers, and investors looking for guidance on the dividend policy of publicly-traded non-financial firms.

The literature lacks studies that together analyze the ownership characteristics and firm-specific variables on dividend decisions, particularly in the context of developing economies. The current study aims to fill this gap.

The role of insurance is a backbone for consumers to secure their future. It is important to know where to invest and what are the benefits. Therefore, for the Muslim segment, Islamic insurance system provides Riba (interest)-free environment where consumers invest their money and recover their losses according to sharia. This paper aims to examine the determinants that influence purchase intention of consumers toward Islamic insurance (Takaful) adoption in Pakistan with the help of the modified theory of planned behavior (TPB).

The authors added four specific variables related to Islamic sharia compliance in the conventional form of the TPB. The relationship among the variables is assessed by using partial least squares structural equation modeling, while the data are collected from 305 respondents.

The results suggest that attitude, subjective norm and perceived behavioral control are strong predictors of an Islamic insurance adoption in Pakistan. Moreover, factors such as compatibility, relative advantage and awareness have positive and significant impacts on takaful participation. A negative but insignificant relation is found between perceived risk and intention.

This paper provides insight for understanding the factors that lead to consumers' purchase intention of Islamic insurance.

This paper makes a unique contribution to the literature with reference to Pakistan, being a pioneering attempt to investigate the factors of Islamic insurance adoption by modifying the TPB and applying more rigorous statistical techniques like confirmatory factor analysis (CFA) and partial least square structural equation modeling.

Depleting reserves of crude oils and their adverse environmental effects have shifted focus toward environment friendly and biobased lubricant base oils. Natural oils and fats act as good lubricants but they have low oxidation and thermal stability which makes them unsuitable for modern day uses. This paper aims to produce trimethylolpropane ester biolubricant from cottonseed oil and study the effects of its use in spark ignition (SI) engines.

In this work, cottonseed oil is converted to TMP lubricant by a two-step based catalyzed esterification. The lubricants thermophysical properties are then analyzed and a 20% blend with synthetic poly-alpha olefin is used in an spark ignition engine.

The produced lubricant has viscosity @100^oC of 4.91 cSt, a viscosity index of 230 and a flash point of 202^oC. When used as a 20% blend in a petrol engine, the rate of oil deterioration was reduced by 18%, however, the overall wear increased by 6.7%. However, this increase is offset by its improved environmental impacts.

In its current state, such a biolubricant can be used as an additive to most commercially available lubricants to improve oil deterioration characteristics and environmental impact. However, further work on improving biolubricant’s wear characteristics is needed for the complete replacement of mineral oil-based lubricants.

This study aims to analyze the trends manifested in literature from the area of knowledge management and performance, with emphasis on bibliometric analysis.

To explore the studies focused on the area under investigation, the authors performed a search in ISI Web of Science and Scopus using the combination of keywords such as “Knowledge management” AND “Performance.” Generally, this study covered a period of 33 years, from 1988 to 2021 because the first study was published in 1970 and the databases have not covered all the journals and studies which date back to the early 1970s or 1980s. The final data set comprised 1,583 publications with 40 articles removed during the screening and eligibility process.

The results of the bibliometric analysis indicate that the interest in the area of knowledge management and performance has significantly increased, especially from 2000 to 2021. The application of bibliometric analysis on the relationship between knowledge management and performance uncovered various themes, productive authors and widely cited documents. The study highlighted how the knowledge management–performance relationship has evolved over the years and how the interplay between knowledge management and performance may help the firms in gaining the sustainable competitive advantage.

To the best of the author’s knowledge, this study is the first of its kind to conduct the bibliometric analysis on knowledge management and performance. This study can be a starting point for scholars interested in understanding how knowledge management is related to performance.

There is a growing interest in how firms respond to environmental degradation and societal challenges. Firms respond through their sustainability reports, but assurance of the reports gives confidence to the stakeholders. This study aims to identify the main research development in sustainability assurance which is rising in global studies.

This study uses a bibliometric analysis to assess the global trend in sustainability assurance studies. The methodology is based on descriptive, performance and science mapping. The set is based on 655 documents from the Scopus database, covering the period from 2005 to 2022.

The findings from the study suggest that sustainability studies are relevant, and the researcher's examination of the domain has dramatically increased from 2014 to date. This is due to the rise in the concerns expressed by stakeholders in satisfying themselves about the firm's responsibility to the Sustainable Development Agenda 2030. The findings also show that most research on sustainability assurance is from Spain, the USA, the United Kingdom (UK) and Australia. However, the UK has the most collaboration in terms of co-authorship. It is suggestive that the UK has more links than Spain, which is the most productive country with more publications. This may be attributed to the influx of more international students completing a second and third degree in the UK. The study highlights intellectual foundations and emerging trends and outlines avenues for future studies.

This study is limited to the data obtained from the Scopus database.

This study is the first bibliometric study of the sustainability assurance domain.

This study aims to use a qualitative approach to explore and clarify the mechanism by which heuristic-driven biases influence the decisions and performance of individual investors actively trading on the Pakistan Stock Exchange (PSX). It also aims to identify how to overcome the negative effect of heuristic-driven biases, so that finance practitioners can avoid the expensive errors which they cause.

This study adopts an interpretative approach. Qualitative data was collected in semistructured interviews, in which the target population was asked open-ended questions. The sample consists of five brokers and/or investment strategists/advisors who maintain investors’ accounts or provide investment advice to investors on the PSX, who were selected on a convenient basis. The researchers analyzed the interview data thematically.

The results confirm that investors often use heuristics, causing several heuristic-driven biases when trading on the stock market, specifically, reliance on recognition-based heuristics, namely, alphabetical ordering of firm names, name memorability and name fluency, as well as cognitive heuristics, such as herding behavior, disposition effect, anchoring and adjustment, repetitiveness, overconfidence and availability biases. These lead investors to make suboptimal decisions relating to their investment management activities. Due to these heuristic-driven biases, investors trade excessively in the stock market, and their investment performance is adversely affected.

This study provides a practical framework to explore and clarify the mechanism by which heuristic-driven biases influence investment management activities. To the best of authors’ knowledge, the current study is the first to focus on links between heuristic-driven biases, investment decisions and performance using a qualitative approach. Furthermore, with the help of a qualitative approach, the investigators also highlight some factors causing an increased use of heuristic variables by investors and discuss practical approaches to overcoming the negative effects of heuristics factors, so that finance practitioners can avoid repeating the expensive errors which they cause, which also differentiates this study from others.

This article aims to systematically review the literature published in recognized journals focused on cognitive heuristic-driven biases and their effect on investment management activities and market efficiency. It also includes some of the research work on the origins and foundations of behavioral finance, and how this has grown substantially to become an established and particular subject of study in its own right. The study also aims to provide future direction to the researchers working in this field.

For doing research synthesis, a systematic literature review (SLR) approach was applied considering research studies published within the time period, i.e. 1970–2021. This study attempted to accomplish a critical review of 176 studies out of 256 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioral finance domain-related explicitly to cognitive heuristic-driven biases and their effect on investment management activities and market efficiency as well as on the origins and foundations of behavioral finance.

This review reveals that investors often use cognitive heuristics to reduce the risk of losses in uncertain situations, but that leads to errors in judgment; as a result, investors make irrational decisions, which may cause the market to overreact or underreact – in both situations, the market becomes inefficient. Overall, the literature demonstrates that there is currently no consensus on the usefulness of cognitive heuristics in the context of investment management activities and market efficiency. Therefore, a lack of consensus about this topic suggests that further studies may bring relevant contributions to the literature. Based on the gaps analysis, three major categories of gaps, namely theoretical and methodological gaps, and contextual gaps, are found, where research is needed.

The skillful understanding and knowledge of the cognitive heuristic-driven biases will help the investors, financial institutions and policymakers to overcome the adverse effect of these behavioral biases in the stock market. This article provides a detailed explanation of cognitive heuristic-driven biases and their influence on investment management activities and market efficiency, which could be very useful for finance practitioners, such as an investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making their financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on cognitive heuristic-driven biases displayed by investors. The current study is original in discussing the role of cognitive heuristic-driven biases in investment management activities and market efficiency as well as the history and foundations of behavioral finance by means of research synthesis. This paper is useful to researchers, academicians, policymakers and those working in the area of behavioral finance in understanding the role that cognitive heuristic plays in investment management activities and market efficiency.

This paper aims to examine the factors affecting the implementation of corporate social responsibility (CSR) sustainably in mobile operators in the kingdom of Bahrain.

The research relies on the existing literature as a secondary data source. The primary data was collected through questionnaires distributed to three leading mobile operators in the Kingdom of Bahrain. The research's population numbered 1,689, and the sample size was 313; the simple random sampling method was used for data collection with a response rate of 87.2% out of a total sample size of 273 respondents. In addition, the responses were analyzed using statistical package for the social sciences (SPSS) software version 24.0; specifically, Spearman's rank correlation was used to test the hypotheses. The research design was quantitative, so a nonparametric procedure was applied to test the hypotheses.

The research produced positive relationships between the independent variables (economic, legal, ethical, philanthropic and environmental responsibilities) and the dependent variable: CSR implementation by Bahrain mobile operators; therefore, the five proposed hypotheses were accepted; furthermore, the highest positive correlation coefficient was 0.735 for environmental responsibility, and the lowest correlation coefficient was 0.533 for economic responsibility.

The research produced positive relationships between the independent variables (economic responsibility, legal responsibility, ethical responsibility, philanthropic responsibility and environmental responsibility) and the dependent variable: CSR implementation by Bahrain mobile operators; therefore, the five proposed hypotheses were accepted; furthermore, the highest positive correlation coefficient was 0.735 for environmental responsibility, and the lowest correlation coefficient was 0.533 for economic responsibility.

The outcomes of the research mainly suggest that mobile operators assign employees who have been working with the company for more than 7 years to implement CSR; due to their engagement to implement CSR as a sustainable practice more than others with less than 3 years or 3-6 years in Bahrain mobile operators. Besides, the research provides a starting point by which other researchers could investigate CSR in other sectors in the Kingdom of Bahrain.

The research provided a framework for Bahrain mobile operators to assist them in enhancing the implementation of CSR in a sustainable manner, which are economic, legal, ethical, philanthropic and environmental responsibilities.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.