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This chapter provided systematic and comprehensive analysis on trawl fisheries management and conservation measures in the Straits of Malacca. Detailed analysis is conducted on Malaysian fishery management framework particularly domestic country's trawl fishery status, legal structure, input-control strategies, ecosystem protection plan, pollution, law enforcement, and complementary measures that designed to reduce and prevent overfishing in the exclusive economic zone (EEZ) of Malacca Straits. Gaps and challenges found in existing trawl fisheries literature are presented followed by recommendations for improvement in the management and conservation of trawl fisheries.

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.

Conventional theories of financial management are notably inconspicuous when considering the influence of heuristic-driven biases and fundamental and technical anomalies on institutional investors' investment decision-making performance and market efficiency, particularly, in emerging Asian economies. This study aims to explore the mechanism by which heuristic driven biases (i.e. cognitive heuristic biases and recognition-based heuristic biases) influence institutional investors' investment decision-making, investment performance and perceived market efficiency, with a mediating role of fundamental and technical anomalies and the moderating role of financial knowledge in Pakistan.

Data were collected through a survey completed by 180 institutional investors trading on the Pakistan Stock Exchange. Structural equation modeling was used to analyze the data and test the hypotheses.

The results suggest that heuristic-driven biases have a significant negative influence on perceived market efficiency and investment performance and a significant positive effect on investment decisions of institutional investors. Fundamental and technical anomalies appeared to mediate these relationships. The results also revealed that financial knowledge moderates these relationships.

This study pioneers research on the links among heuristic-driven biases, financial knowledge, fundamental and technical anomalies and institutional investors' decisions and performance. This adds to the understanding of the role that heuristic-driven bias plays in investment management activities and enhances the appreciation of various behavioral aspects and their influence on investment decision-making and performance in an emerging market. It also contributes to the literature on behavioral finance, specifically the role of heuristics in investment strategies, which is still in its initial stage in developed countries, let alone in developing countries. The current research contributes to the literature by defining heuristic-driven biases as antecedents and fundamental and technical anomalies as intervening variables for irrational investment decision-making and poor investment performance. In addition, this study underlines the significance of utilizing financial knowledge to manage the antecedents and repercussions of fundamental and technical anomalies.

This study aims to investigate the influence of the digitalization of corporate social responsibility (CSR) on the sustainable competitive performance (SCP) of small- and medium-sized enterprises (SMEs) in an emerging economy and to examine the moderating effect of digital organizational culture on this relationship.

Data collection was conducted through a survey completed by 311 owners and top managers operating in service, trading and manufacturing sector SMEs positioned within the twin cities of Pakistan. A convenient purposively sampling technique and snowball method were used for data collection, and structural equation modeling was used for data analysis.

The results of this study suggest that CSR digitalization has a markedly positive influence on the SCP. Digital organizational culture appears to moderate these relationships.

This study highlights the importance of considering CSR digitalization and fostering a digital organizational culture for SMEs to achieve SCP. The findings provide valuable insights for strategic decision-makers, including owners, CEOs and senior management of SMEs, to enhance their knowledge concerning how and why a digital organizational culture makes it easier to digitalize CSR activities, with the ultimate objective of ensuring SCP and SME growth. Overall, the findings of this study have practical implications for policymakers and managers in SMEs as they can promote the adoption of digital technologies in CSR initiatives and develop a digital organizational culture within the organization. This would contribute to enhancing the SCP of SMEs. Thus, this research is beneficial for business actors, policymakers and researchers seeking to enhance SMEs’ SCP.

This study provides valuable guidance to the senior management of SMEs regarding successfully adopting and integrating digital technologies into their CSR practices. This integration can lead to increased social and environmental benefits, which positively impact both business and society. Policymakers can use these findings to develop policies and initiatives to encourage CSR digitalization among SMEs. By providing support and incentives for digital transformation, policymakers can help SMEs adopt digital tools to improve their CSR performance, contributing to economic growth and sustainability.

This study pioneers research on the links between CSR digitalization, digital organizational culture and the SCP of SMEs. This study contributes to the literature by defining CSR digitalization as an antecedent to the SCP of SMEs. In addition, this study underlines the significance of CSR digitalization for the achievement of SMEs’ SCP of SMEs with the moderating role of digital organizational culture. Overall, this study enriches the resource base view literature through empirical evidence.

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.

Risk assessment is imperative for disaster risk reduction. The risk is rooted to various physical, social, economic, demographic and environmental factors that determine the probable magnitude of loss during an extreme event. By way of bringing a conceptual model into practice, this paper aims to examine the flood risk of the Srinagar city.

The “risk triangle” model has been adopted in the present investigation evaluating parameters, reflective of hazard (intensity), exposure (spatial) and vulnerability (sensitivity) using Landsat-8 operational land imager scene (10 September 2014), global positioning system, Cartosat-1 digital elevation model and socioeconomic and demographic data (Census of India, 2011). The authors characterise flood hazard intensity on the basis of variability in water depth during a recent event (September 2014 Kashmir flood); spatial exposure as a function of terrain elevation; and socioeconomic structure and demographic composition of each municipal ward of the city as a determinant factor of the vulnerability. Statistical evaluation and geographic information system-based systematic integration of all the multi-resolution data layers helped to develop composite flood risk score of each ward of the city.

Principal deliverable of this study is flood risk map of the Srinagar city. The results reveal that approximately 46 per cent of the city comprising 33 municipal wards is at high risk, while rest of the area, i.e. 17 and 37 per cent, exhibit moderate and low levels of risk, constituting 23 and 12 municipal wards, respectively. It is very likely that the municipal wards expressing high risk may witness comparatively more damage (impact) during any future flood event. Thus, there is a need of planned interventions (structural and non-structural) to minimise the emergent risk.

Very rare attempts have been made to bring theoretical models of disaster research in practice; this is mainly because of the complexities associated with the data (selection, availability and subjectivity), methodology (integration, quantification) and resolution (spatial scales). In this direction, this work is expected to have considerable impact, as it provides a clear foundation to overcome such issues for the studies aiming at disaster risk assessment. Furthermore, using varied primary and secondary data, this paper demonstrates the relative (municipal wards) flood risk status of the Srinagar city, which is one of the key aspects for flood hazard mitigation.

This study aims to explore and clarify the mechanism by which recognition-based heuristic biases influence the investment decision-making and performance of individual investors, with the mediating role of fundamental and technical anomalies.

The deductive approach was used, as the research is based on behavioral finance's theoretical framework. A questionnaire and cross-sectional design were employed for data collection from the sample of 323 individual investors trading on the Pakistan Stock Exchange (PSX). Hypotheses were tested through the structural equation modeling (SEM) technique.

The article provides further insights into the relationship between recognition-based heuristic-driven biases and investment management activities. The results suggest that recognition-based heuristic-driven biases have a markedly positive influence on investment decision-making and negatively influence the investment performance of individual investors. The results also suggest that fundamental and technical anomalies mediate the relationships between the recognition-based heuristic-driven biases on the one hand and investment management activities on the other.

The results of the study suggested that investment management activities that rely on recognition-based heuristics would not result in better returns to investors. The article encourages investors to base decisions on investors' financial capability and experience levels and to avoid relying on recognition-based heuristics when making decisions related to investment management activities. The results provides awareness and understanding of recognition-based heuristic-driven biases in investment management activities, which could be very useful for decision-makers and professionals in financial institutions, such as portfolio managers and traders in commercial banks, investment banks and mutual funds. This paper helps investors to select better investment tools and avoid repeating the expensive errors that occur due to recognition-based heuristic-driven biases.

The current study is the first to focus on links recognition-based heuristic-driven biases, fundamental and technical anomalies, investment decision-making and performance of individual investors. This article enhanced the understanding of the role that recognition-based heuristic-driven biases plays in investment management. More importantly, the study went some way toward enhancing understanding of behavioral aspects and the aspects' influence on investment decision-making and performance in an emerging market.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

Analyzing and reducing entropy generation is useful for enhancing the thermodynamic performance of engineering systems. This study aims to explore how polymers and nanoparticles in the presence of Lorentz forces influence the fluid behavior and heat transfer characteristics to lessen energy loss and entropy generation.

The dispersion model is initially used to examine the behavior of polymer additives over a magnetized surface. The governing system of partial differential equations (PDEs) is subsequently reduced through the utilization of similarity transformation techniques. Entropy analysis is primarily performed through the implementation of numerical computations on a non-Newtonian polymeric FENE-P model.

The numerical simulations conducted in the presence of Lorentz forces provide significant insights into the consequences of adding polymers to the base fluid. The findings suggest that such an approach minimizes entropy in the flow region. Through the utilization of polymer-MHD (magnetohydrodynamic) interactions, it is feasible to reduce energy loss and improve the efficiency of the system.

This study’s primary motivation and novelty lie in examining the significance of polymer additives as agents that reduce entropy generation on a magnetic surface. The author looks at how nanofluids affect the development of entropy and the loss of irreversibility. To do this, the author uses the Lorentz force, the Soret effect and the Dufour effect to minimize entropy. The findings contribute to fluid mechanics and thermodynamics by providing valuable insights for engineering systems to increase energy efficiency and conserve resources.

This study aims to unveil the determinants of employer branding (EB) that attracts and retains the employees working in the Indian higher education sector using the factor-analytic approach.

The study is cross-sectional, and the data were collected from 141 employees working in the higher education sector. Exploratory factor analysis and independent t-test were deployed to analyze the data.

The results of independent samples t-test explicate that perception of male and female university employees pertaining to EB factors of employee attraction (EA) and employee retention (ER) is congruent. Further, the perception of employees in public and private universities on EB factor is similar for ER and non-similar for EA.

The present research is an effort to unveil the employee attraction and retention factors that play a vital role in showcasing an employer as a great place to work in the Indian higher education sector.