Muhammad Imran Malik, Faisal Nawaz Mir, Saddam Hussain, Shabir Hyder, Asim Anwar, Zia Ullah Khan, Noman Nawab, Syed Farjad Ali Shah and Muhammad Waseem
This paper aims to examine the mediating role of environmental concern in the relationship of green purchase awareness and purchasing behavior of fast food consumers keeping in…
Abstract
Purpose
This paper aims to examine the mediating role of environmental concern in the relationship of green purchase awareness and purchasing behavior of fast food consumers keeping in view the theory of planned behavior.
Design/methodology/approach
A quantitative, cross-sectional design is used by collecting primary responses through a validated questionnaire. In all, 1,008 male and female buyers of fast food were sampled. Structural equation modeling is applied.
Findings
The results revealed that green purchase awareness has a positive relationship with green purchase behavior, and environmental concern has no mediation in the relationship. Upon having awareness, the respondents adopted green or pro-environmental behavior, but at the same time, they were found having least concern for the protection of environment.
Research limitations/implications
This is a cross-sectional study with questionnaire. Multiple sources of data collection results in weakening self-reporting bias.
Practical implications
Implications count toward individuals, enterprises and society at general.
Originality/value
The study highlights the issue of not having concern for the protection of the environment even after having green purchase awareness. This is the first time the environmental concern is examined as a mediator in the selected relationship. The contradictory results of having no environmental concern differentiate this study from others.
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Hassaan Tariq, Faisal Shahzad, Asim Anwar and Ijaz Ur Rehman
This study investigates the impact of insider-ownership of publicly traded firms on their performance, cost of debt (COD) and cost of equity. We use a sample of 104 non-finance…
Abstract
This study investigates the impact of insider-ownership of publicly traded firms on their performance, cost of debt (COD) and cost of equity. We use a sample of 104 non-finance listed companies of Pakistan for the period from 2006 to 2016. Our study is conducted in Pakistan as a developing country in which insider-ownership is dominant, and a weak external corporate governance mechanism increases the payoffs from insider-ownership. We use feasible generalized least square (FGLS) regression methods to examine these hypotheses. Based on agency theory, we find that insider-ownership enhances firm performance. Furthermore, our results show that insider-ownership reduced the COD and equity. Higher ownership decreases the opportunistic behavior of insiders. It also reduces the creditor’s perception of the likelihood of default on loan payments and reduces agency issues among shareholders. The insider will invest in positive NPV projects which will help maximize shareholders’ wealth and minimize the COD. Similarly, the relationship between insider-ownership and cost of equity is significant but negative. Supporting the convergence of interest increase in ownership helps in aligning the goals of managers and stakeholders whereby the insider will focus on value creation by minimizing equity cost.
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Dominik Rozkrut, Malgorzata Tarczynska-Luniewska, Guru Asish Singh and Mateusz Piwowarski
Purpose: Sustainable and responsible business is strongly associated with activities that minimise negative environmental or social impacts. As a result, the utility of big data…
Abstract
Purpose: Sustainable and responsible business is strongly associated with activities that minimise negative environmental or social impacts. As a result, the utility of big data is becoming a reality, opening up exciting possibilities for ESG monitoring and assessment. This study systematises existing knowledge and provides recommendations for big data in ESG monitoring and assessment.
Methodology/approach: Theoretical and exploratory focusing on a literature review.
Conclusions: Results indicate different levels of progress and challenges related to ESG and big data. Awareness and adoption of ESG and big data practices is growing, accompanied by regulatory pressure.
Significance: Understanding the relationship between big data and ESG is critical to properly conducting sustainable and responsible business practices. The urgency and necessity of developing standards for constructing big data cannot be overstated for ensuring consistency between existing policies and the SDGs and for the effective use of big data in ESG monitoring and assessment.
Limitations: A lack of data quality and standardisation in reporting for ESG assessments. Standardisation efforts are growing as data challenges, especially data availability, are major constraints. Large data sets offer exciting opportunities, analysed mainly from the perspective of existing applications for measuring sustainability goals.
Future research: An in-depth analysis of case studies that combine ESG issues with big data infrastructure. Fundamental is knowledge and understanding of companies’ ESG practices and understanding big data issues. We can standardise approaches to using new data sources and move towards deepening our measurable dimension of sustainability assessment.
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Introduction: The current study provides a conceptual base for big data analytics in the insurance industry that might be useful for academics, researchers, and practitioners…
Abstract
Introduction: The current study provides a conceptual base for big data analytics in the insurance industry that might be useful for academics, researchers, and practitioners conducting future studies in the respective field.
Purpose: This study intends to investigate the transformative impact of big data analytics in the insurance industry. It elaborates on how advanced data analytics techniques are reshaping the insurance landscape, from customer acquisition and retention to risk modeling, pricing, and claims management.
Methodology: The current study incorporates a thorough review of existing literature, industry reports and academic articles related to big data analytics in the insurance sector. The aim is to develop an in-depth comprehension of the subject by synthesizing key insights and trends.
Findings: The findings underscore the evolutionary potential of the insurance sector through big data analytics, emphasizing its role as a catalyst for innovation, efficiency, and growth. Embracing data-driven strategies is essential for insurers to adapt to evolving market dynamics, meet customer expectations, and maintain a competitive edge in the digital age.
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Anwar ul Haq, George Magoulas, Arshad Jamal, Asim Majeed and Diane Sloan
E-learning environments and services (ELES) adoption and success rates challenge ELES designers, practitioners and organisations. Enterprise decision makers continue to seek…
Abstract
Purpose
E-learning environments and services (ELES) adoption and success rates challenge ELES designers, practitioners and organisations. Enterprise decision makers continue to seek effective instruments in launching such systems. The purpose of this paper is to understand users’ perceptions of ELES effectiveness and develop a theoretical framework which improves understanding of success factors for adoption.
Design/methodology/approach
Grounded theory method is used to reflect on the relationships between changing users’ requirements and expectations, technological advances and ELES effectiveness models. A longitudinal study collecting data from social media blogs over four years was authenticated based on the context evaluation, language structure and conversational constructs.
Findings
Identification of a new core dimension named “Concept Functionality” which can be used to understand the relationships between e-learning effectiveness factors including the relationships with other domains such as security. The findings are also used to validate major existing models for the success of ELES.
Practical implications
The new framework potentially improves system design process in the fields of education technology, enterprise systems, etc.
Originality/value
Concept functionality dimension can offer more insights to understand ELES effectiveness and further improve system design process in a variety of domains including enterprise systems, process modelling and education technology.
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Suresh Kumar, Hyder Ali, Muhammad Asim and Waseem Sajjad
1. Understand the impact of macroeconomic factors on investment portfolios:Students will learn how macroeconomic conditions, such as changes in policy rates by central banks…
Abstract
Learning outcomes
1. Understand the impact of macroeconomic factors on investment portfolios:Students will learn how macroeconomic conditions, such as changes in policy rates by central banks, influence investment decisions and portfolio performance. They will analyze how these factors can lead to significant financial challenges for managed funds.2. Develop strategic financial decision-making skills:Through examining the case, students will practice making strategic financial decisions under uncertain and volatile market conditions. They will explore various options for managing an underperforming investment fund and the potential outcomes of these choices.3. Evaluate risk management techniques:The case provides a platform for students to understand different risk management strategies, including the trade-offs between holding long-term bonds versus reinvesting in short-term securities. They will assess the risks and benefits of these strategies and how they impact fund stability and performance.4. Enhance skills in portfolio management:Students will gain practical experience in portfolio management by examining the fund’s investment decisions, performance metrics and the process of presenting and defending investment proposals. This will involve analyzing the financial and strategic implications of different asset allocations.5. Apply theoretical concepts to real-world scenarios:The case encourages students to apply theoretical concepts such as yield to maturity (YTM) calculation, discounted cash flow analysis, capital asset pricing models and benchmarking against indices to real-world scenarios. This helps bridge the gap between academic principles and practical application in finance.
Case overview/synopsis
The case study centered on the Sukkur IBA University in Pakistan, highlighting the challenges faced by its student-managed fund (SMF). From November 2015 to January 2023, the case study offers a comprehensive examination of the fund’s activities in the financial services and higher education domains. Mr Shankar Talreja, the fund manager, contemplating with significant investment losses because of macroeconomic fluctuations, specifically the rising policy rates by the State Bank of Pakistan. These losses challenge the sustainability of the SMF, which serves as a practical learning platform for students. The primary dilemma revolves around whether to continue operating the fund amid consistent losses or to dissolve it, redirecting resources to other educational programs. This case focuses on financial decision-making, risk management and investment strategies, tailored for academic settings.
Complexity academic level
This case study is intended for use in graduate- and undergraduate-level courses on corporate strategy, investment management and finance. It is appropriate for graduate students who are looking to apply these concepts more deeply as well as undergraduate students who have a strong foundation in finance due to the complexity of the financial concepts involved, such as risk management, portfolio strategy and macroeconomic impacts.
Supplementary material
Teaching notes are available for educators only.
Subject Code
CSS1: Accounting and Finance.
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Xinyue Hao, Emrah Demir and Daniel Eyers
The purpose of this study is to provide a holistic understanding of the factors that either promote or hinder the adoption of artificial intelligence (AI) in supply chain…
Abstract
Purpose
The purpose of this study is to provide a holistic understanding of the factors that either promote or hinder the adoption of artificial intelligence (AI) in supply chain management (SCM) and operations management (OM). By segmenting the AI lifecycle and examining the interactions between critical success factors and critical failure factors, this study aims to offer predictive insights that can help in proactively managing these factors, ultimately reducing the risk of failure, and facilitating a smoother transition into AI-enabled SCM and OM.
Design/methodology/approach
This study develops a knowledge graph model of the AI lifecycle, divided into pre-development, deployment and post-development stages. The methodology combines a comprehensive literature review for ontology extraction and expert surveys to establish relationships among ontologies. Using exploratory factor analysis, composite reliability and average variance extracted ensures the validity of constructed dimensions. Pearson correlation analysis is applied to quantify the strength and significance of relationships between entities, providing metrics for labeling the edges in the resource description framework.
Findings
This study identifies 11 dimensions critical for AI integration in SCM and OM: (1) setting clear goals and standards; (2) ensuring accountable AI with leadership-driven strategies; (3) activating leadership to bridge expertise gaps; (4) gaining a competitive edge through expert partnerships and advanced IT infrastructure; (5) improving data quality through customer demand; (6) overcoming AI resistance via awareness of benefits; (7) linking domain knowledge to infrastructure robustness; (8) enhancing stakeholder engagement through effective communication; (9) strengthening AI robustness and change management via training and governance; (10) using key performance indicators-driven reviews for AI performance management; (11) ensuring AI accountability and copyright integrity through governance.
Originality/value
This study enhances decision-making by developing a knowledge graph model that segments the AI lifecycle into pre-development, deployment and post-development stages, introducing a novel approach in SCM and OM research. By incorporating a predictive element that uses knowledge graphs to anticipate outcomes from interactions between ontologies. These insights assist practitioners in making informed decisions about AI use, improving the overall quality of decisions in managing AI integration and ensuring a smoother transition into AI-enabled SCM and OM.
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Prakash Kumar Gautam, Dhruba Kumar Gautam and Rakshya Bhetuwal
This study aims to analyse the role of work–life balance (WLB) experiences and job satisfaction on turnover intentions (TI) among nurses working in private sector hospitals.
Abstract
Purpose
This study aims to analyse the role of work–life balance (WLB) experiences and job satisfaction on turnover intentions (TI) among nurses working in private sector hospitals.
Design/methodology/approach
The research followed the analytical research design with a self-administered questionnaire survey using a five-point Likert scale. Responses from 386 nurses working in different positions in private sector hospitals were collected. The collected data were examined using descriptive and inferential statistics using structural equation modelling. Data validation, path coefficient analysis and a mediation effect test were conducted using Smart PLS 4 with a 5% significance level. WLB was examined with three dimensions: work interference with personal life, personal life interference with work and work–personal life enhancement.
Findings
The study established a significant relationship between personal life interference with work and work–personal life enhancement with job satisfaction. Also, the result revealed a significant negative relationship between interferences of WLB and TI. The study also established a partial and full mediation of job satisfaction about two WLB dimensions with TI.
Originality/value
This research suggests emphasizing WLB and job satisfaction to discourage TI. This research can be used by managers and policymakers alike to improve the scenario and take measures accordingly. This study also provides theoretical implications based on the boundary theory.
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Shumaila Naz, Syed Arslan Haider, Shabnam Khan, Qasim Ali Nisar and Shehnaz Tehseen
At the forefront of current research is the investigation of how big data analytics capability (BDAC) and artificial intelligence capability (AIC) can enhance performance in…
Abstract
Purpose
At the forefront of current research is the investigation of how big data analytics capability (BDAC) and artificial intelligence capability (AIC) can enhance performance in concert. Therefore, current study intended to conduct more deep research into emerging phenomena and attempts to cover the gap by exploring how entrepreneurial orientations (EO) emphasize the use of two emerging capabilities under the moderating role of environmental dynamism which in turn augment co-innovation and hotel performance.
Design/methodology/approach
Data were collected from four-star and five-star hotels located in Kula Lumpur and Langkawi in Malaysia. A total of 260 responses were obtained from IT staff and senior managers with the assistance of a Manpower agency for data analysis. The hypotheses were examined by analyzing the data using PLS-SEM technique through Smart PLS 3 software.
Findings
The result revealed that EO has a positive and significant effect on co-innovation (CIN). Additionally, the BDAC and AIC have been tested and proven to be potential mediators between EO and CIN. Also, environmental dynamism as moderator has positive and significant effect on BDAC and co-innovation performance, however, not significant impact on AIC and co-innovation performance. Lastly, findings displayed positive and significant moderated mediation impact of environmental dynamics on BDAC and CIN with hotel performance, but not significant influence on AIC and co-innovation with hotel performance. For theoretical corroboration of the research findings, the current study integrated EO, resource-based view theory and contingent dynamic capabilities (CDC), because neither single stance can explicate an extant research framework.
Practical implications
This study anticipated the several implications for the entrepreneurs of hospitality industry. Managers are recommended to invest in the entrepreneurial traits of the employees/organizations and make strategic readjustment of their capabilities for sustained business performance.
Originality/value
The study goes beyond the normal inquiry by investigating moderated mediation impact of environmental dynamism between two emerging capabilities, co-innovation and hotel performance relationships. Another novelty of this study is to culminate the exploitation and adoption of emerging IT-based capabilities in cross domains of management, entrepreneurship, information systems management within the hotel industry.