This study aimed to understand the agri-entrepreneurial traits of undergraduate university students using machine learning (ML) algorithms.
Abstract
Purpose
This study aimed to understand the agri-entrepreneurial traits of undergraduate university students using machine learning (ML) algorithms.
Design/methodology/approach
This study used a conceptual framework of individual-level determinants of entrepreneurship and ML. The Google Survey instrument was prepared on a 5-point scale and administered to 656 students in different sections of the same class during regular virtual classrooms in 2021. The datasets were analyzed and compared using ML.
Findings
Entrepreneurial traits existed among students before attending undergraduate entrepreneurship courses. Establishing strong partnerships (0.359), learning (0.347) and people-organizing ability (0.341) were promising correlated entrepreneurial traits. Female students exhibited fewer entrepreneurial traits than male students. The random forest model exhibited 60% accuracy in trait prediction against gradient boosting (58.4%), linear regression (56.8%), ridge (56.7%) and lasso regression (56.0%). Thus, the ML model appeared to be unsuitable to predict entrepreneurial traits. Quality data are important for accurate trait predictions.
Research limitations/implications
Further studies can validate K-nearest neighbors (KNN) and support vector machine (SVM) models against random forest to support the statement that the ML model cannot be used for entrepreneurial trait prediction.
Originality/value
This research is unique because ML models, such as random forest, gradient boosting and lasso regression, are used for entrepreneurial trait prediction by agricultural domain students.
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Arun Kumar Verma, Vincentraju Rajkumar, M. Suman Kumar and Shiv Kumar Jayant
This paper aims to explore the application of drumstick (Moringa oleifera) flower (DF) as a functional antioxidative ingredient in goat meat product.
Abstract
Purpose
This paper aims to explore the application of drumstick (Moringa oleifera) flower (DF) as a functional antioxidative ingredient in goat meat product.
Design/methodology/approach
Dried DF was included in the product formulation at 1% (Treatment I) and 2% (Treatment II) levels. The physicochemical, colour, textural and sensory quality as well as storage stability of nuggets with DF were determined against control.
Findings
The dried DF was found to be rich source of protein and dietary fibre, possessing good antioxidant potential. Chromatographic analysis of DF extract showed presence of 14 active principles known to have antioxidative properties. Inclusion of dried DF decreased pH values of emulsion (p = 0.005) as well as nuggets (p < 0.001) and increased (p < 0.001) the ash, dietary fibre and phenolic contents. The added DF affected the product’s lightness (p = 0.017), yellowness (p < 0.001, hardness (p < 0.001), adhesiveness (p = 0.032), cohesiveness (p = 0.006), gumminess and chewiness (p < 0.001). Sensory characteristics of control and product with DF were statistically similar except low (p = 0.002) flavour score for Treatment II. DF inclusion lowered (p < 0.001) thiobarbituric acid reactive substances number and total plate count.
Research limitations/implications
DF can be used as a source of antioxidants and dietary fibre in goat meat nuggets to enhance their health value, functionality and storage stability.
Originality/value
Foods including goat meat nuggets enriched with goodness of functional ingredients like dietary fibre and natural antioxidants are gaining consumer’s preference globally. Inclusion of drumstick flower in goat meat nuggets significantly increases the dietary fibre and antioxidants making such products healthier and more stable. Consumption of goat meat nuggets added with drumstick flower is expected to improve consumer’s well-being as well.
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Ankit Mahindroo, Harsh Vardhan Samalia and Piyush Verma
Reverse logistics (RL) is a strategic instrument across industries. The rapid evolution of online marketplaces has led to frequent product returns with variations across…
Abstract
Purpose
Reverse logistics (RL) is a strategic instrument across industries. The rapid evolution of online marketplaces has led to frequent product returns with variations across diversified businesses. These marketplaces have caused potential losses due to fraudulent returns, hence requiring a commitment of resources to RL. With information systems (IS) playing a role in improved supply chain performance, the purpose of this paper is to analyse the impact of a conceptualized IS framework on achieving RL strategic outcomes, under the individual moderating influence of resource commitment (RC) and return frequency.
Design/methodology/approach
Data have been collected through a questionnaire from top to middle management executives managing the supply chain, logistics and IS. Moderated regression analysis was conducted on the collected sample using Hayes’ (2013) process modeling.
Findings
The study depicts that IS capability, IS for logistics, IS partnership quality and IS for value addition lead to RL strategic benefits. Also, return frequency and RC act as relatively strong moderators with a negative impact. When analyzed for the individual IS constructs, RC has a stronger moderating impact than return frequency.
Practical implications
The IS usage framework can be used effectively by practitioners for enhancing strategic RL performances depending on variations in committed resources and return frequency for individual industries.
Originality/value
The study proposes an IS usage framework for achieving enhanced RL strategic outcomes and emphasizes on the moderating role played by RC and return frequency for producing the results.
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Naveed R. Khan, Muhammad Rahies Khan, Wasim Ahmad and Rana Muhammad Sohail Jafar
The environmental performance of organizations has come under public policy limelight since the phenomenal increase of natural resource degradation and industrial waste. Thus…
Abstract
The environmental performance of organizations has come under public policy limelight since the phenomenal increase of natural resource degradation and industrial waste. Thus, green concepts have been put forward, but the implementation of green practices faces many barriers and challenges. These barriers require attention as organizational practices are negatively affecting the environment leading to global warming and climate change. Therefore, this chapter systematically identifies four internal barriers including inadequate management commitment and support, insufficient technology competence and infrastructure, financial constraints, the uncertainty of economic benefits, and eight sub barriers within an organization concerning green concepts implementation. Moreover, this chapter also identifies four external barriers including lack of stakeholder's interest, inadequate environmental administrative support, scarce academic research, and lack of green collaborative practices, and eight sub barriers outside an organizational context concerning green concept implementation. The barriers in this research were identified by reviewing the existing literature on the topic. This chapter advances the green literature by identifying multiple barriers and challenges to the successful implementation of green concepts in organizations. This is of significance as if these barriers are tackled strategically, it would reduce environmental degradation problems and help make financial gains. Moreover, this research can help managers understand the key barriers to green concept implementation and provide guidance to them when attempting to implement green practices in their organizations. This research would also motivate researchers to extend further investigation on how to overcome such barriers and find out strategies to mitigate the barriers to green concept implementation to effectively address environmental issues.
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Arne Walter, Kamrul Ahsan and Shams Rahman
Demand planning (DP) is a key element of supply chain management (SCM) and is widely regarded as an important catalyst for improving supply chain performance. Regarding the…
Abstract
Purpose
Demand planning (DP) is a key element of supply chain management (SCM) and is widely regarded as an important catalyst for improving supply chain performance. Regarding the availability of technology to process large amounts of data, artificial intelligence (AI) has received increasing attention in the DP literature in recent years, but there are no reviews of studies on the application of AI in supply chain DP. Given the importance and value of this research area, we aimed to review the current body of knowledge on the application of AI in DP to improve SCM performance.
Design/methodology/approach
Using a systematic literature review approach, we identified 141 peer-reviewed articles and conducted content analysis to examine the body of knowledge on AI in DP in the academic literature published from 2012 to 2023.
Findings
We found that AI in DP is still in its early stages of development. The literature is dominated by modelling studies. We identified three knowledge clusters for AI in DP: AI tools and techniques, AI applications for supply chain functions and the impact of AI on digital SCM. The three knowledge domains are conceptualised in a framework to demonstrate how AI can be deployed in DP to improve SCM performance. However, challenges remain. We identify gaps in the literature that make suggestions for further research in this area.
Originality/value
This study makes a theoretical contribution by identifying the key elements in applying AI in DP for SCM. The proposed conceptual framework can be used to help guide further empirical research and can help companies to implement AI in DP.
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Shyam Sunder Agrawal and Suraj Kumar Mukti
This chapter examines the role of sustainable finance in propelling India's economic growth, drawing insights from a comprehensive review of 50 research papers. Employing a…
Abstract
This chapter examines the role of sustainable finance in propelling India's economic growth, drawing insights from a comprehensive review of 50 research papers. Employing a Boolean search strategy, the analysis delves into the influence of environmental, social and governance (ESG) factors on various entities within the Indian financial ecosystem. This chapter explores how sustainable finance practices, embraced by businesses, financial institutions and policymakers, can contribute to long-term economic prosperity while mitigating environmental and social risks. Key findings illuminate opportunities and challenges associated with integrating sustainability principles into financial decision-making. This chapter explores how India’s progress in establishing itself as a significant participant in sustainable finance can be attributed to a variety of key initiatives and policy interventions. The government's dedication to promoting environmental sustainability and facilitating the shift towards a green economy is clearly demonstrated through the implementation of diverse regulations and frameworks by regulatory entities. This chapter provides valuable guidance for stakeholders seeking to leverage sustainable finance for a more resilient and inclusive Indian economy.
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Amitabh Anand, Ritu Tripathi, Anjana Karumathil and Tanvika Kalra
Advanced bibliometric methods have emerged as key tools in mapping the history and trends of a discipline. This paper aims to demonstrate on applying various bibliometric methods…
Abstract
Purpose
Advanced bibliometric methods have emerged as key tools in mapping the history and trends of a discipline. This paper aims to demonstrate on applying various bibliometric methods to track a journal’s impact and review its knowledge contribution. In doing so, the authors take the case of IIMB Management Review (IMR) journal focused on management discipline, in consideration of its 10 years of publication presence.
Design/methodology/approach
Using bibliometric and Scopus metric methods, the authors map and analyze the productivity of IMR Journal and map its knowledge contributions.
Findings
The authors identify the IMR journal’s impact, its growth, the most prolific authors/affiliations, key research hotspots, cross-country collaboration and emerging trends over the past decade.
Originality/value
A 10-year longitudinal review helps the target group identify the main themes. It also provides key empirical insights to the journal editorial board and library managers for future planning and growth of the journal.
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The purpose of this paper is to examine Philip B. Crosby’s 14 quality principles and analyze the interaction between them. Hitherto no research has been published on the…
Abstract
Purpose
The purpose of this paper is to examine Philip B. Crosby’s 14 quality principles and analyze the interaction between them. Hitherto no research has been published on the implementation of total quality management (TQM) using Crosby’s 14 principles. To fill this gap, interpretive structural modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) analysis have been designed to prioritize, sequence and categorize variables to find both the dependence and driving power of these variables.
Design/methodology/approach
At the initial stage experts from industry as well as from academia were contacted to provide an input for ISM methodology and examine interactions between identified variables. In this approach, interpretations of the interrelationships among variables have been discussed, whereas MICMAC analysis is used to discover dependence and driving power.
Findings
The results of the investigation revealed that “Management Commitment,” “Quality Improvement Team,” “Quality Awareness,” “Supervisor Training,” “Goal Setting” and “Cost of Quality Evaluation” are strategic requirements; “Corrective Action,” “Zero Defects Day” and “Error Cause Removal” are tactical requirements. “Recognition,” “Quality Measurement,” “Quality Councils” and “Do It Over Again” are operational requirements for TQM applications.
Originality/value
ISM is used as a part of this research to provide valuable insights into interrelationships among Crosby’s quality principles through a systematic framework. The research opens up a new focus area on the implementation of TQM for services as well as for the manufacturing industry.
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Oluwatoyin Esther Akinbowale, Heinz Eckart Klingelhöfer and Mulatu Fekadu Zerihun
The purpose of this study is to use a decision support model based on the Analytical Hierarchy Process (AHP) and Pareto analysis (PA) for ranking the impact of different kinds of…
Abstract
Purpose
The purpose of this study is to use a decision support model based on the Analytical Hierarchy Process (AHP) and Pareto analysis (PA) for ranking the impact of different kinds of cybercrime in organisations in the financial sector to support decisions on cybercrime mitigation.
Design/methodology/approach
From a structured questionnaire to the staff of 17 licensed banks in South Africa in charge of management, administration and operations, the perceived effect of cybercrime on the organisation’s goals, namely, organisation’s profitability, goodwill, customers’ satisfaction and risk management was derived. The pairwise comparison of the organisation’s goals and identified forms of cybercrime was done using the AHP.
Findings
The results obtained indicate that there was a consensus (100% of the answers) that the effect of cybercrime has negatively impacted the organisation’s objectives profitability and goodwill. Also, still 95.23% of the respondents agreed that the effect of cybercrime has negatively impacted the level of customers’ satisfaction, while only 7.15% saw an impact on the organisation’s risk management processes. Using these results in the AHP, analysis delivers a hierarchical order about the relevance of prevalent forms of cybercrime for the organisation´s cybercrime mitigation. The PA further shows the magnitude of the forms of cybercrime relative to each other.
Practical implications
Hence, this study provides a decision support framework for organisational management in the quest to explore the impact of cyber fraud. It can serve as a practical guided approach for the application of AHP analysis for the existing and emerging forms of cybercrime.
Originality/value
The novelty of this study lies in the fact that the combination of the AHP and PA to support solving a multi-criteria decision problem relating to the prevalence of cybercrime has not been sufficiently highlighted by the existing literature.
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Bijoylaxmi Sarmah and Zillur Rahman
With increased competition in service sector due to dynamic nature of customers’ taste and preferences, service providers have realized the importance of co-creating with…
Abstract
Purpose
With increased competition in service sector due to dynamic nature of customers’ taste and preferences, service providers have realized the importance of co-creating with customers across various stages of new service development. Co-creating with customers require a focused attention on the psychological variables that influence customers to participate in developing a new service. However, availability of scant literature creates difficulty in comprehending co-creative hotel service innovation practices, especially in developing country like India. The purpose of this paper is to explore the inter-relationships among the customer participation in hotel service innovation variables with the help of interpretive structural modeling (ISM) approach.
Design/methodology/approach
ISM approach is used to determine the direction of customer participation and categorization of psychological variables with their driving and dependence power. Identification of related variables was done through a review of literature initially and arrived at a common consensus through brainstorming sessions with academicians and hotel industry experts.
Findings
The results indicate that a few variables possess higher driving power that include: consumer innovativeness, customer participative behavior, customer socialization, willingness to co-create, role clarity, customer ability and their interlinking. Thus, the research contributes in the development of relationship among various identified variables of customer participation in service innovation (CPSI) using ISM.
Research limitations/implications
This study suggests that hoteliers should co-create with customers to develop new services by understanding their psychological variables that play a crucial role determining their active participation in new hotel service offerings.
Practical implications
This study suggests that hoteliers should co-create with customers to develop new services by understanding the enablers of customer participation in co-creative hotel service innovation. Hoteliers can have hierarchical map of their customers for co-creating at different stages of service innovation or can segregate the variables as per their driving and dependence power for enhanced applicability of the variables. Further, the observed inter-relationships among the CPSI variables can guide the managers in planning and implementing identified relationships for successful implementation of co-creative service innovation.
Originality/value
To the best of the authors’ knowledge this study is the first to provide an integrated model using ISM and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) analysis with a goal to identify and classify various key enablers of customer participation in co-creative hotel service innovation in India. The authors believe that this study will enhance the understanding of the psychological factors influencing customer-firm co-creative service innovation activities and help the academicians and industry practitioners to select right enablers for customer participation in co-creative hotel service innovation. Thus, this study will be the foundation for studying co-creative service innovation using the ISM and MICMAC approaches.