Search results

The purpose of this paper is to identify and determine the connection of various antecedents from educational literary works with Halal purchase intention. It also aims to investigate which antecedents, among all antecedents, have the highest possible participation toward the development of Halal food purchase intention. Consumers across the globe have an ever increasing demand for Halal items nowadays. Similarly, food stuff in Halal category has an increased acceptance across the globe. Numerous researches have therefore focused on Halal food perception, Halal understanding and its approval in various areas of the world.

A total of 300 respondents were taken from four major cities of Pakistan to examine the relationship of factors that influence customer’s Halal purchase intention. Data were collected through structured questionnaire having seven-point Likert scale. It was divided into eight sections with statements measuring Halal Awareness, Halal Marketing, Subjective norms, Religion and Religiosity, Attitude, Subjective norms, Perceived Behavioural control, Halal Certification and Purchase Intention.

The paper draws the findings that most of the customers rely on Halal Marketing, Personal and Societal perception and Halal certifications. On the other hand, least importance was given to their religious beliefs when making a purchase decision. The findings also suggest that customers are influenced by Halal Marketing and Branding practices of food products as they are being influenced by the sales promotions and celebrity endorsements. It has also been found that customers are willing to spend considerable efforts and money to purchase Halal food.

The paper clarifies the strategies for Halal food manufacturers and marketers who are following Islamic Marketing philosophy as a base for their marketing campaigns. The study also provides a detailed insight into various behavioural, societal and marketing dimensions that guides the customers about their purchase intentions.

This study aims to present a unique hybrid metaheuristic approach to solving the nonlinear analysis of hall currents and electric double layer (EDL) effects in multiphase wavy flow by merging the firefly algorithm (FA) and the water cycle algorithm (WCA).

Nonlinear Hall currents and EDL effects in multiphase wavy flow are originally described by partial differential equations, which are then translated into an ordinary differential equation model. The hybrid FA-WCA technique is used to take on the optimization challenge and find the best possible design weights for artificial neural networks. The fitness function is efficiently optimized by this hybrid approach, allowing the optimal design weights to be determined.

The proposed strategy is shown to be effective by taking into account multiple variables to arrive at a single answer. The numerical results obtained from the proposed method exhibit good agreement with the reference solution within finite intervals, showcasing the accuracy of the approach used in this study. Furthermore, a comparison is made between the presented results and the reference numerical solutions of the Hall Currents and electroosmotic effects in multiphase wavy flow problem.

This comparative analysis includes various performance indices, providing a statistical assessment of the precision, efficiency and reliability of the proposed approach. Moreover, to the best of the authors’ knowledge, this is a new work which has not been explored in existing literature and will add new directions to the field of fluid flows to predict most accurate results.

This study aims to investigate the mediating effect of innovation on the relationship between KM (KM) capabilities and organisational performance in the context of construction firms operating in Pakistan. Worldwide innovation predicts the performance of any firm. Today, the construction industry in Pakistan is booming, which reinforces the need for a study on innovation and KM in this sector.

This empirical study uses a correlational research design. An online survey questionnaire was used as a data collection method. Through convenient sampling, the sample comprised 277 employees from different construction firms working under the Defence Housing Authority (a construction company operating in major cities) in Pakistan. Data were analysed through partial least squares-structural equation modelling (Smart PLS-SEM version 3) to assess the hypothesis.

Data analysis reveals that KM dimensions, knowledge acquisition, application and protection positively and significantly influence organisational performance; however, knowledge conversion is insignificant. Furthermore, innovation positively and substantially mediates the relationship between knowledge acquisition, application, protection, organisational performance and the insignificant terms of knowledge conversion.

This study is limited to the construction industry, and future research should be conducted on larger scales for better generalisation. Other mediators between KM and organisational performance (i.e. organisational complexity, workplace environment, employee knowledge-sharing attitude) should be investigated.

These results are crucial and encourage managers in the construction industry, especially from a developing country like Pakistan, to understand the importance of innovation, the application of KM and the essential role it has in boosting business performance.

This research contributes to the scholarly debate on the mediating role of innovation in the relationship between KM and organisational performance. It also expands the literature on KM through an empirical investigation on the innovation of the construction industry in Pakistan from a management perspective.

Numerous researchers have probed the peristaltic flows because of their immense usage in industrial engineering, biomedical engineering and biological sciences. However, the investigation of peristaltic flow in two-phase fluid of a rotating frame in the presence of a magnetic field has not been yet discussed. Therefore, to fulfill this gap in the existing literature, this paper will explicate the peristaltic flow of two-phase fluid across a rotating channel with the effect of wall properties in the presence of a magnetic field. The purpose of this study is to investigate the two-phase velocity distribution and rotation parameter when magneto-hydrodynamics is applied.

The constituent equations are solved under the condition of low Reynolds number and long wavelength. The exact method is used to attain the subsequent equations and a comprehensive graphical study for fluid phase, particulate phase velocity and flow rates are furnished. The impacts of pertinent parameters, magnetic field and rotation are discussed in detail.

It is witnessed that the velocity profile of particulate phase gets higher values for the same parameters as compared to the fluid phase velocity. Moreover, the axial velocity increases with different values of particle volume fraction, but in case of magnetic field and rotation parameter, it shows the opposite behavior.

The outcomes of study have viable industrial implementations in systems comprising solid-liquid based flows of fluids involving peristaltic movement.

The investigation of peristaltic flow in two-phase fluid of a rotating frame in the presence of a magnetic field has not been yet discussed. Therefore, to fulfill this gap, the present study will explicate the peristaltic flow of two-phase fluid across a rotating channel with the effect of wall properties in the presence of magnetic field.

The discussion on energy efficiency has been increasing due to the increasing population, emissions of degradable and harmful pollutants, and clean energy substitutes are being developed in order to manage and control the energy requirements all over the world. Against this backdrop, the factors of technological innovation and environmental regulations have been determined as key indicators for the evaluation of sustainable developments and practices in the energy efficiency evaluation studies.

A two-stage analysis process has been configured for evaluation of the energy efficiency. The first stage includes the estimation of the Total factor energy efficiency scores using the data envelopment Multiplier input-oriented methodology, while the second stage includes the exploration of the impact of technological innovation and government environmental regulations on the Total factor energy efficiency scores obtained in the first step through the application of a spatial regression model.

This paper highlights the link between the need for and impact of energy efficiency innovations and shows that the energy efficiency goal can be fulfilled by incorporating laws on sustainability and incorporating strict regulations that allow for the use of clean energy, low carbon energy technologies.

The present study, furthermore, provides evidence from 15 countries, five from three different continents, i.e. Asia, Europe and Africa so that a cross-country performance of these factors can be evaluated. The main contribution of the present study is the evaluation of the technological innovation on energy efficiency. There have been studies evaluating various factors on the development of energy-efficient practices; however, the focus on the role of technological innovation and governmental regulations has been scarce.

Material selection, driven by wide and often conflicting objectives, is an important, sometimes difficult problem in material engineering. In this context, multi-criteria decision-making (MCDM) methodologies are effective. An approach of MCDM is needed to cater to criteria of material assortment simultaneously. More firms are now concerned about increasing their productivity using mathematical tools. To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material. In addition, by using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the inherent ambiguities of decision-makers in paired evaluations are considered in this research. It goes on to construct a mathematical bi-objective model for determining the best item to purchase.

The entropy perspective is implemented in this paper to evaluate the weight parameters, while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system. The intermediate pipes are used to join the components of the exhaust systems. The materials usually used to manufacture intermediate pipe are SUS 436LM, SUS 430, SUS 304, SUS 436L, SUH 409 L, SUS 441 L and SUS 439L. These seven materials are evaluated based on tensile strength (TS), hardness (H), elongation (E), yield strength (YS) and cost (C). A hybrid methodology combining entropy-based criteria weighting, with the TOPSIS for alternative ranking, is pursued to identify the optimal design material for an engineered application in this paper. This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes. After that, the authors searched for and considered eight materials and evaluated them on the following five criteria: (1) TS, (2) YS, (3) H, (4) E and (5) C. The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes, on their performance and on the cost. In this structure, the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment. This essentially measures the quantity of information each criterion contribution, indicating the relative importance of these criteria better. Subsequently, the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative. The results show that SUS 309, SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.

The material matrix of the decision presented in Table 3 was normalized through Equation 5, as shown in Table 5, and the matrix was multiplied with weighting criteria ß_j. The obtained weighted normalized matrix V_ij is presented in Table 6. However, the ideal, worst and best value was ascertained by employing Equation 7. This study is based on the selection of material for the development of intermediate pipe using MCDM, and it involves four basic stages, i.e. method of translation criteria, screening process, method of ranking and search for methods. The selection was done through the TOPSIS method, and the criteria weight was obtained by the entropy method. The result showed that the top three materials are SUS 309, SUS 432L and SUS 436 LM, respectively. For the future work, it is suggested to select more alternatives and criteria. The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality (ELECTRE), Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE).

The results provide important conclusions for material selection in this targeted application, verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design.

This study aims to test the Kuznets curve between economic growth and child labor, along with the influence of exports, household size and rural population in the context of Pakistan.

To achieve the research objective, this study applied the unit root test, bound co-integration test, and autoregressive distributive lags (ARDL) method for the period of 1972–2021.

The findings show an inverted U-shaped relationship between economic growth and child labor indicating that at the beginning stage of economic development, child labor increases due to lower per capita household and subsequently, in the long-run of economic development, child labor decreases due to the higher per capita households. Moreover, the results also show that exports, household size and rural population have a positive influence on increasing child labor.

The policymakers and government of Pakistan need to focus on long-term economic growth policies, ensure free quality education and cheap equipment which practices minimum manpower to reduce the threat of child labor.

Having long-run economic growth, the government of Pakistan need to equally benefit the households and the poor population to reduce child labor and enhance the social welfare of society.

To the best of the authors’ knowledge, this is the first study that investigates the Kuznets curve relationship between economic growth and child labor in the context of Pakistan. Moreover, this study contributes to the reduction in child labor through long-term economic growth in the context of Pakistan.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0387

The purpose of this paper is to reviews some of the learnings, challenges and solutions suggested by the article author regarding the role of implementing emotional intelligence by corporate social responsible (CSR) leaders and offers ideas for future research. The aim is to offer a positive conclusion to the problems and their solutions.

The study investigates the relationship between emotional intelligence and effective CSR leadership. The author evaluates the body of research on the issue and provides a reassuring assessment of the problems and recommendations.

Having emotional intelligence is essential for executives who wish to implement successful CSR initiatives. It allows CEOs to create a culture of social responsibility inside their organizations, highlight the importance of CSR initiatives and strengthen relationships with stakeholders. Key emotional intelligence traits, including self-awareness, self-regulation, motivation, empathy and social skills, are necessary for effective CSR leadership.

The study focuses on the role of emotional intelligence in corporate social responsibility leadership, offering a unique perspective on the subject. It also explores practical solutions and ideas for future research, adding originality and value to the existing body of literature on emotional intelligence and CSR leadership.

The volume of data being generated by various sectors in recent years has increased exponentially. Consequently, professionals struggle to process essential data in the current competitive world. The purpose of the study is to explore and provide insights into the Big Data Analytics (BDA) studies in different sectors.

This study performs a systematic literature review (SLR) with bibliometric analysis of BDA adoption (BDAA) in the supply chain and its applications in various sectors from 2014 to 2018. This paper focuses on BDAA studies have been carried out across different countries and sectors. Also, the paper explores different tools and techniques used in BDAA studies.

The benefits of adopting BDA, coupled with a lack of adequate research in the field, have motivated this study. This literature review categorizes paper into seven main areas and found that most of the studies were carried out in manufacturing and service.

This research insight and observations can provide practitioners and academia with guidance on implementing BDA in different sustainable supply chain sectors. The article indicates a few remarkable gaps in the future direction and trends regarding the integration of BDA and sustainable supply chain development.

The study derives a new categorization of BDA, which investigates how data is generated, organized, captured, interpreted and evaluated to give valuable insights to manage the sustainable supply chain.

Acceptance and use of mobile shopping as the preferred shopping medium is becoming the new normal today. The proliferation of mobile shopping practices follows unsteady growth patterns in different countries. Despite challenges of price, quality and privacy matters, young consumers still lead the race to engage in mobile shopping activity in developing countries. This research investigates the determinants that either support or hinder the mobile shopping intentions of aspirant young consumers in Pakistan.

The present research applies a consumer-centric approach to the technology adoption framework to unearth the behavioral patterns of these young consumers in Pakistan. Employing the structural equation modeling technique, this research examines the significant effect of structural assurance, perceived risk, trust and various unified theory of acceptance and use of technology (UTAUT) model constructs on behavioral intention to engage in mobile shopping.

This research examines the significant effect of structural assurance, perceived risk, trust and various UTAUT model constructs on behavioral intention to engage in mobile shopping. Results also demonstrate a significant moderating effect of structural assurance and prior shopping experience on the relationship between perceived risk, trust and mobile shopping intentions. Further, the mobile shopping patterns for the male and female segment indicate a significant difference for perceived risk, trust structural assurance and social influence. The research contributes to the growing body of knowledge which advocates the application of consumer-centric customized model approach to explore various factors that either facilitate or impede the adoption of mobile shopping in a developing economy.

The study validates the need to enforce structural assurance mechanism for facilitating mobile shopping in a developing country. It also offers practical implications for online businesses and marketers striving to attract and retain more mobile customers.

The study offers practical implications for online businesses and marketers striving to attract and retain more mobile customers.

This study offers fresh insights about driving elements and impediments of mobile shopping behavioral intentions. Structural assurance and prior shopping experience appear to influence the mobile shopping behavior through direct and indirect effect.