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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.

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 solve the problem of high output voltage fluctuation and low efficiency caused by the misalignment of the magnetic coupling structure in the wireless charging system for electric vehicles. To address these issues, this paper proposes a dual LCC-S wireless power transfer (WPT) system based on the double-D double-layer quadrature (DDDQ) coil, which can realize the anti-misalignment constant voltage output of the system.

First, this paper establishes the equivalent circuit of a WPT system based on dual LCC-S compensation topology and analyzes its constant-voltage output characteristics and the relationship between system transmission efficiency and coupling coefficient. 1. Quadruple D (Ahmad et al., 2019) and double-D quadrature pad (DDQP) (Chen et al., 2019) coils have good anti-misalignment in the transverse and longitudinal directions, but the magnetic induction intensity in the center of the coils is weak, making it difficult for the receiving coil to effectively couple to the magnetic field energy. 2. Based on the double-D quadrature (DDQ) structure coil that can eliminate the mutual inductance between coupling coils and cross-coupling, Gong et al. (2022a) proposed a parameter optimized LCC-LC series-parallel hybrid topology circuit, which ensures that the output current fluctuation is controlled within 5% only when the system is misaligned within the 50% range along the X direction, achieving constant current output with anti-misalignment. The magnetic coupling structure’s finite element simulation model is established to analyze the change in magnetic induction intensity and the system’s anti-misalignment characteristics when the coil offsets along the x and y axes. Finally, an experimental prototype is developed to verify the constant voltage output performance and anti-misalignment performance of the system, and the proposed anti-misalignment system is compared with the systems in existing literature, highlighting the advantages of this design.

The experimental results show that the system can achieve a constant voltage output of 48V under a time-varying load, and the output voltage fluctuates within ±5% of the set value within the range of ±60 mm lateral misalignment and ±72 mm longitudinal misalignment.

Based on the dual LCC-S WPT system, the mutual inductance between the same side coils is reduced by adding decoupling coils, and the anti-misalignment characteristics and output power of the system are improved in a certain range. It is aimed at improving the stability of the system output and transmission efficiency.

The purpose of this paper is to highlight the role an intentional and cohesive research group for doctoral researchers and supervisors can play in surfacing and de-mystifying many of the implicit doctoral literacy practices involved in doctoral study.

This participatory, collaborative project, involving 11 doctoral researchers and three supervisors, was conducted in two stages. In the first stage, doctoral researchers and supervisors engaged in a discussion which resulted in a shared concept map. The concept map was then used as a prompt for stimulated recall interviews in which the participants reflected on the connections and peer learning afforded by the research group.

Drawing on ideas from Communities of Practice theory, the data revealed that the research group, including both supervisors and doctoral students, developed knowledge, relational connections and an awareness of a range of doctoral literacies.

This paper makes suggestions for how those in doctoral education can develop and embed research groups into institutional practices.

This study demonstrates the significant role a research group which is structured, intentional and guided plays in supervisors’ and doctoral students’ development of doctoral literacies and the fundamental intellectual and relational connections afforded by participating in such communities.

This study presents a systematic framework for maintenance strategy development of manufacturing process machinery. The framework is developed based on the reliability-centred maintenance (RCM) approach to minimise the high downtime of a production line, thus increasing its reliability and availability. A case study of a production line from the ghee and soap manufacturing industry in Taiz, Yemen, is presented for framework validation purposes. The framework provides a systematic process to identify the critical system(s) and guide further investigation for functional significant items (FSIs) based on quantitative and qualitative analyses before recommending appropriate maintenance strategies and specific tasks.

The proposed framework integrates conventional RCM procedure with the fuzzy computational process to improve FSIs criticality estimation, which is the main part of failure mode effect criticality analysis (FMECA) applications. The framework consists of four main implementation stages: identification of the critical system(s), technical analysis, Fuzzy-FMECA application for FSIs criticality estimation and maintenance strategy selection. Each stage has its objective(s) and related scientific techniques that are applied to systematically guide the framework implementation.

The proposed framework validation is summarised as follows. The first stage results demonstrate that the seaming system (top and bottom systems) caused 50% of the total production line downtime, indicating it is a critical system that requires further analysis. The outcomes of the second stage provide significant technical information on the subject (seaming system), helping team members to identify and understand the structure and functional complexities of the seaming system. This stage also provides a better understanding of how the seaming system functions and how it can fail. In stage 3, the application of FMECA with the fuzzy computation integration process presents a systematic way to analyse the failure mode, effect and cause of items (components of the seaming system). This stage also includes items’ criticality estimation and ranking assessment. Finally, stage four guides team members in recommending the appropriate countermeasures (maintenance strategies and task selection) based on their priority level.

This paper proposes an original maintenance strategies development framework based on the RCM approach for production system equipment. Specifically, it considers a fuzzy computational process based on the Gaussian function in the third stage of the proposed framework. Adopting the fuzzy computational process improves the risk priority number (RPN) estimation, resulting in better criticality ranking determination. Another significant contribution is introducing an extended item criticality ranking assessment process to provide maximum levels of criticality item ranking. Finally, the proposed RCM framework also provides detailed guidance on maintenance strategy selection based on criticality levels, unique functionality and failure characteristics of each FSI.

The aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management activities and to ascertain some substantial gaps related to them.

For doing research synthesis, systematic literature review approach was applied considering research studies published within the time period, i.e. 1980–2020. This study attempted to accomplish a critical review of 59 studies out of 118 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioural finance domain-related explicitly to recognition-based heuristics and their effect on investment management activities.

The survey and analysis suggest investors consistently rely on the recognition-based heuristic-driven biases when trading stocks, resulting in irrational decisions, and an investment strategy constructed by implementing the recognition-based heuristics, would not result in better returns to investors on a consistent basis. Institutional investors are less likely to be affected by these name-based behavioural biases in comparison to individual investors. However, under the context of ecological rationality, recognition-based heuristics work better and sometimes dominate the classical methods. The research scholars from the behavioural finance community have highlighted that recognition-based heuristics and their impact on investment management activities are high profile areas, needed to be explored further in the field of behavioural finance. The study of recognition-based heuristic-driven biases has been found to be insufficient in the context of emerging economies like Pakistan.

The skilful understanding and knowledge of the recognition-based heuristic-driven biases will help the investors, financial institutions and policy-makers to overcome the adverse effect of these behavioural biases in the stock market. This article provides a detailed explanation of recognition-based heuristic-driven biases and their influence on investment management activities which could be very useful for finance practitioners’ such as 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 its financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on recognition-based heuristic-driven biases displayed by investors. The current study is original in discussing the role of recognition-based heuristic-driven biases in investment management activities by means of research synthesis. This paper is useful to researchers, academicians, and those working in the area of behavioural finance in understanding the role that recognition-based heuristics plays in investment management activities.

Introduction: India has the 15th-largest domestic natural gas consumption (NGC), critical to sustainable economic growth. Promoting natural gas will have a crucial impact on production in all industries.

Purpose: This research gives an overview of NGC and gross domestic product (GDP) in India from 1990 to 2021 and investigates the association and nature of causality between NGC and GDP in India.

Methodology: For the years 1990 through 2021, we used annual statistics from the NGC and the GDP of India. Both research variables data have been taken from the World Bank Indicator.

Findings: There is no causality and correlation between natural gas and GDP in India.

Practical Implications: Based on the research, the Government of India can create different policies for substituting natural gas for other energy sources to have a healthier impact on a sustainable environment in the short and long term. In the future, researchers can work on environmental degradation and GDP.

This study aims to provide insights into the drivers of student engagement in food waste reduction strategies in educational institutions. The proposed research model integrates social media celebrities' attractiveness, expertise and trustworthiness with the value belief norm (VBN) theory to explore their influence on students' behaviour towards food waste reduction.

The data were collected from 417 students enrolled in public and private universities in the Riyadh and Macca regions of Saudi Arabia to evaluate the proposed model. The partial least squares-structural equation modelling (PLS-SEM) was employed to analyse the responses.

The results showed that VBN theory's components, such as values (biospheric, altruistic and egoistic), beliefs (new ecological paradigm, awareness of consequences and aspirations of responsibility) and norms significantly and positively influence food waste reduction behavioural intentions. It was also discovered from the results that social media celebrities' attractiveness, expertise and trustworthiness influence food waste reduction behavioural intentions.

This study contributes significantly to the literature by identifying factors influencing student engagement in food waste reduction strategies in educational institutions where limited research exists. It fills this research gap by developing a novel theoretical framework integrating social media celebrities' attributes with the VBN theory to explain these factors.

Zakat has succeeded in becoming one of the safety nets for welfare during the crisis. As a result, continuous improvement is a necessity, especially through strengthening technology adaptation. This study aims to explore the factors determining Muslim behavior on their intention to pay zakat by taking into consideration the adoption of digital technology using the modified Unified Theory of Acceptance and Use of Technology (UTAUT).

The data collected were 265 respondents who live in urban and suburban areas. They were processed using the partial least square structural equation modeling (PLS-SEM) design. Furthermore, the multigroup analysis (MGA) was conducted to capture the difference results between urban and suburban.

The findings show that performance expectancy, social influence, facilitating conditions, perceived security and privacy and zakat literacy significantly increase the intention of Muzakki to adopt financial technology. Perceived security and privacy has succeeded in being an important predictor of digital payment adoption for Muzakki. This paper provides a specific description of the adoption of Muzakki living in urban and suburban areas by using MGA. The research findings illustrate that there is a different urgency between the related variables. Suburban communities have more significant results regarding the research model used.

This research provides new component variables that can drive individuals’ intentions to use digital services to pay zakat online by using the redesigned UTAUT model. Further research can explore more variables related to zakat digitalization, such as social media interaction, by conducting in-depth interviews with stakeholders to improve zakat performance in this digital era.

The result of this research recommends that zakat institutions enhance their zakat literacy and education among the Muslim population to improve zakat performance. The government should pay attention to the digital ecosystem to attract the community to use a digital platform.

This research modified the UTAUT model by integrating several other important constructs to produce more comprehensive findings in investigating the factors that can influence an individual's intention to pay zakat through an online digital platform. This study also examined the indirect effect to obtain significant results by positioning perceived security and privacy as an intervening variable. The implementation of the MGA was conducted to divide research respondents into two categories (urban and suburban) and compare the test results.

Analyzing the impact of integrated reporting (IR) on international firms' value relevance, considering diverse information such as income, cash flows, risks, uncertainties and various capitals.

This paper used a sample of 300 international companies between 2010 and 2019. This paper collected the data from the Thomson Reuters Eikon database. Quantitative methods were used to test the hypotheses. Furthermore, the feasible generalized least squares (FGLS) method was performed to test the hypotheses.

The results suggest that IR and value relevance positively correlate, confirming the hypothesis. Moreover, this paper verified these results by conducting robustness tests on the contribution of the framework and guidelines prepared by the International Integrated Reporting Council (IIRC) in 2013.

This study enables users to evaluate company transparency and the relevance of disclosed nonfinancial information, providing valuable insights for report preparers and investors seeking profitable opportunities.

The interest in this research was motivated by the authors’ research field, which is innovative, as few studies have been conducted to explain the relationship between IR and value relevance. Similarly, this paper incorporated into their analysis the importance of the framework created by the IIRC in 2013 in preparing and presenting an integrated report. This paper considered the contribution of this framework to the creation of information content. This design has been overlooked in previous studies. However, this paper mobilized the FGLS method, which has been little used in previous studies.