Search results
1 – 10 of 141Aditi Saha, Rakesh D. Raut, Mukesh Kumar, Sanjoy Kumar Paul and Naoufel Cheikhrouhou
This paper aims to explore the underlying intention behind using blockchain technology (BLCT) in the agri-food supply chain (AFSC). This is achieved by using a conceptual…
Abstract
Purpose
This paper aims to explore the underlying intention behind using blockchain technology (BLCT) in the agri-food supply chain (AFSC). This is achieved by using a conceptual framework based on technology acceptance models that considers various factors influencing user behavior toward implementing this technology in their practices.
Design/methodology/approach
The conceptual framework developed is empirically validated using structural equation modeling (SEM). A total of 258 respondents from agri-food domain in India were involved in this survey, and their responses were analyzed through SEM to validate our conceptual framework.
Findings
The findings state that food safety and security, traceability, transparency and cost highly influence the intention to use BLCT. Decision-makers of the AFSCs are more inclined to embrace BLCT if they perceive the usefulness of the technology as valuable and believe it will enhance their productivity.
Practical implications
This study contributes to the existing literature by providing thorough examination of the variables that influence the intention to adopt BLCT within the AFSC. The insights aim to benefit industry decision-makers, supply chain practitioners and policymakers in their decision-making processes regarding BLCT adoption in the AFSC.
Originality/value
This study investigates how decision-makers’ perceptions of BLCT influence their intention to use it in AFSCs, as well as the impact of the different underlying factors deemed valuable in the adoption process of this technology.
Details
Keywords
Aditi Saha, Rakesh Raut and Mukesh Kumar
The purpose of this paper is to identify the challenges surrounding the implementation of digital technology (DT) agri-food supply chain (AFSC) and explore how these challenges…
Abstract
Purpose
The purpose of this paper is to identify the challenges surrounding the implementation of digital technology (DT) agri-food supply chain (AFSC) and explore how these challenges relate to the various sustainability dimensions. Additionally, it aims to assess how these challenges are interconnected in relation to achieving sustainable development goals (SDGs).
Design/methodology/approach
The study employs a mixed-method approach utilizing the EFA-ISM-Fuzzy DEMATEL technique. To support and validate the findings, exploratory factor analysis (EFA) categorized 12 critical challenges in sustainable dimensions from 141 participants' responses. Furthermore, interpretive structural modeling (ISM) and decision-making trial and evaluation (DEMATEL) methods were used to obtain the interrelationship and hierarchical structure of the challenges.
Findings
The study identified 12 critical challenges while adopting DT in AFSC. These challenges were categorized into four sustainable dimensions: technological, economic, environmental and social. These challenges hinder the achievement of SDGs as well. Lack of regulatory and policy framework with security and privacy issues were the key challenges faced while adopting DT. These observations emphasize the necessity for government and policymakers to prioritize tackling the identified challenges to successfully endorse and execute DT initiatives in AFSC while also fulfilling the SDGs.
Research limitations/implications
The implication underscores the need for collaboration among various stakeholders, such as governments, policymakers, businesses and researchers. By collectively addressing these challenges, DT can be leveraged optimally, fostering sustainable practices and making progress toward achieving the SDGs within the AFSC.
Originality/value
The study uses a combination technique of EFA and ISM-DEMATEL to identify the challenges faced in Indian AFSC while adopting DT and categorizes the interrelation between the challenges along with fulfilling the SDGs.
Details
Keywords
Aswin Alora and Mukesh Kumar Barua
Supply chain disruptions can have severe negative consequences on companies. However, studies measuring the financial impacts of supply chain disruptions are largely confined to…
Abstract
Purpose
Supply chain disruptions can have severe negative consequences on companies. However, studies measuring the financial impacts of supply chain disruptions are largely confined to developed nations and large companies. Therefore, this study aims to analyze the impact of supply chain disruption on small companies in the context of an emerging nation. Further, an attempt has been made to classify supply chain disruptions and measure its impact by its type.
Design/methodology/approach
In this research, the event study on 335 supply chain disruption events for a 10 year period starting from 2009 to 2019 has been used.
Findings
The results state that the Indian small and medium companies lost −4.49% of shareholder wealth in disruption. The findings also indicate that the financial and environmental disruptions can have severe effect on shareholder wealth as compared to other category.
Research limitations/implications
The study is confined to a developing country. Considering multiple countries can provide comparative results and therefore a global consensus could be achieved.
Practical implications
The outcomes of the results help managers to plan and prioritize supply chain disruptions, regulatory authorities can plug any possible insider trading practices for small companies in the event of supply chain disruptions. Investors can plan and take prudent investing decisions based on the nature of the disruptions.
Originality/value
To the best of the knowledge, this is the first study measuring the supply chain disruption effects on smaller companies in an emerging nation. The study is also novel in incorporating financial disruptions and measuring source wise impact on shareholder wealth.
Details
Keywords
Sarthak Dhingra, Rakesh Raut, Mukesh Kumar and B. Koteswara Rao Naik
This study aims to identify several perspectives that affect the adoption of blockchain technology in India (BCTA) and evaluate their impact. To study the sector’s influence on…
Abstract
Purpose
This study aims to identify several perspectives that affect the adoption of blockchain technology in India (BCTA) and evaluate their impact. To study the sector’s influence on adoption and the impact of BCTA on the performance of the Indian healthcare supply chain (HSCP) using BCTA as a mediating variable.
Design/methodology/approach
In this study, we first developed a conceptual model based on Organizational Information Processing Theory and Technology-Organization-Environment, then formulated hypotheses. Based on this, a questionnaire was developed, and data were gathered from experts in the Indian healthcare industry who were familiar with blockchain technology. AMOS 19 was used to analyze data using structural equation modelling.
Findings
All the factors have a significant positive influence on BCTA. Healthcare supply chain factors influenced the adoption most dominantly, followed by technological, environmental, organizational and record-keeping unit factors. Both the public and private sectors of HSCP benefited significantly from BCTA.
Practical implications
This research work is fruitful for healthcare practitioners, top management, academicians and policymakers in assessing BCTA’s impact on the HSCP.
Originality/value
We have attempted to evaluate the possible BCTA impact on HSCP. BCTA as a mediating variable and considering different perspectives for a holistic view of adoption in the Indian context add to this work’s originality.
Details
Keywords
Sourabh Kumar and Mukesh Kumar Barua
This research identifies the supply chain performance indices and designs an evaluation framework to assess and compare the Indian petroleum supply chain performance. We presented…
Abstract
Purpose
This research identifies the supply chain performance indices and designs an evaluation framework to assess and compare the Indian petroleum supply chain performance. We presented a case study of three Indian petroleum companies. For this purpose, we identified fifteen performance criteria extracted from previous literature and expert inputs and classified them into four groups.
Design/methodology/approach
A fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) method is employed for evaluating the performance of the Indian petroleum supply chain.
Findings
The design and evaluation framework suggests that the top three performance measurement criteria, the purity of the products, compliance with environmental laws, and new technology adoption. The result findings also indicate that company C contributes to a maximum satisfaction level of 77%. Simultaneously, companies A and B hold satisfaction levels of 72% and 67%.
Practical implications
The managers should ensure that environmental standards, new technology adoption, and quality are significant concerns in the petroleum supply chain. The managers should follow national and international policies to preserve the environment and ensure safety in operational activities.
Originality/value
This paper makes two contributions in the domain of performance measurement of the petroleum supply chain. First, it identifies the prominent supply chain performance indices. Second, it proposes a model to assess and compare the performance of Indian petroleum companies.
Details
Keywords
Sourabh Kumar and Mukesh Kumar Barua
Disruptive technologies can significantly contribute to the sustainability of operations in the petroleum supply chain. The present study aims to identify the prime sustainable…
Abstract
Purpose
Disruptive technologies can significantly contribute to the sustainability of operations in the petroleum supply chain. The present study aims to identify the prime sustainable dimensions and disruptive technologies implementation in the supply chain of the petroleum industry. The authors used content analysis in the literature and experts input to explore the sustainable dimensions and disruptive technologies in the supply chain.
Design/methodology/approach
This study used a hybrid method of hesitant fuzzy set and regret theory to identify the prominent sustainability dimensions and prominent disruptive technologies. This method emphasizes the decision-makers psychological characteristics under uncertain environments.
Findings
The result indicates that social responsibility, labor practices, safety and technical standards hold the most prominent sustainable dimensions in the petroleum supply chain. Further, the result also depicts that when consider an equal degree of regret and rejoice, artificial intelligence and big data could significantly enhance operations sustainability in the petroleum industry.
Research limitations/implications
This study considers only 11 sustainable dimensions and 43 sustainable factors, whereas other dimensions and factors could also be considered in future research. The research uses hesitant fussy set and regret set theory to identify the prominent sustainable dimensions and disruptive technologies, whereas other multiple-criteria decision-making (MCDM) techniques can also be used.
Originality/value
To the best of the authors’ knowledge, this is the first paper to explore the sustainable dimensions (environmental, social and economic) and disruptive technologies in the supply chain of the petroleum industry. This research intended to guide the practitioners, policymakers and academicians to emphasize their effort toward sustainable operations supply chain management.
Details
Keywords
Mukesh Kumar, K.S. Sujit and Vincent Charles
The purpose of this paper is to propose the microeconomics concept of elasticity to estimate the SERVQUAL gap elasticity to derive important insights for service providers to…
Abstract
Purpose
The purpose of this paper is to propose the microeconomics concept of elasticity to estimate the SERVQUAL gap elasticity to derive important insights for service providers to develop the right strategies to bridge the overall gap in service.
Design/methodology/approach
The dimensions of SERVQUAL adopted from Parasuraman et al. (1988) and Kumar et al. (2009) are first verified for their unidimensionality using structural equation modeling and reliability in the context of United Arab Emirates banking industry. Furthermore, the technique of dominance analysis is used to derive the relative importance of dimensions for different groups of banks. Finally, the stepwise log-linear regression models are used to estimate the gap elasticity to measure the responsiveness of the overall SERVQUAL gap to a change in customers’ perception on different dimension.
Findings
The results reveal that the dimension which is prioritized as the most important dimension need not to be the one to be targeted under the resource constraint to react faster to the changes of customers’ banking behavior.
Originality/value
This is probably the first attempt to examine the service quality through gap elasticity. This method is especially useful when the traditional approach to measure relative importance of critical factors fails to clearly discriminate between two or more dimensions, which, in turn, may lead to failure in decision making to choose the right strategies to bridge the overall gap in the service.
Details
Keywords
Community detection is a significant research field in the study of social networks and analysis because of its tremendous applicability in multiple domains such as recommendation…
Abstract
Purpose
Community detection is a significant research field in the study of social networks and analysis because of its tremendous applicability in multiple domains such as recommendation systems, link prediction and information diffusion. The majority of the present community detection methods considers either node information only or edge information only, but not both, which can result in loss of important information regarding network structures. In real-world social networks such as Facebook and Twitter, there are many heterogeneous aspects of the entities that connect them together such as different type of interactions occurring, which are difficult to study with the help of homogeneous network structures. The purpose of this study is to explore multilayer network design to capture these heterogeneous aspects by combining different modalities of interactions in single network.
Design/methodology/approach
In this work, multilayer network model is designed while taking into account node information as well as edge information. Existing community detection algorithms are applied on the designed multilayer network to find the densely connected nodes. Community scoring functions and partition comparison are used to further analyze the community structures. In addition to this, analytic hierarchical processing-technique for order preference by similarity to ideal solution (AHP-TOPSIS)-based framework is proposed for selection of an optimal community detection algorithm.
Findings
In the absence of reliable ground-truth communities, it becomes hard to perform evaluation of generated network communities. To overcome this problem, in this paper, various community scoring functions are computed and studied for different community detection methods.
Research limitations/implications
In this study, evaluation criteria are considered to be independent. The authors observed that the criteria used are having some interdependencies, which could not be captured by the AHP method. Therefore, in future, analytic network process may be explored to capture these interdependencies among the decision attributes.
Practical implications
Proposed ranking can be used to improve the search strategy of algorithms to decrease the search time of the best fitting one according to the case study. The suggested study ranks existing community detection algorithms to find the most appropriate one.
Social implications
Community detection is useful in many applications such as recommendation systems, health care, politics, economics, e-commerce, social media and communication network.
Originality/value
Ranking of the community detection algorithms is performed using community scoring functions as well as AHP-TOPSIS methods.
Details
Keywords
Mukesh Kumar, Joginder Singh, Sunil Kumar and Aakansha
The purpose of this paper is to design and analyze a robust numerical method for a coupled system of singularly perturbed parabolic delay partial differential equations (PDEs).
Abstract
Purpose
The purpose of this paper is to design and analyze a robust numerical method for a coupled system of singularly perturbed parabolic delay partial differential equations (PDEs).
Design/methodology/approach
Some a priori bounds on the regular and layer parts of the solution and their derivatives are derived. Based on these a priori bounds, appropriate layer adapted meshes of Shishkin and generalized Shishkin types are defined in the spatial direction. After that, the problem is discretized using an implicit Euler scheme on a uniform mesh in the time direction and the central difference scheme on layer adapted meshes of Shishkin and generalized Shishkin types in the spatial direction.
Findings
The method is proved to be robust convergent of almost second-order in space and first-order in time. Numerical results are presented to support the theoretical error bounds.
Originality/value
A coupled system of singularly perturbed parabolic delay PDEs is considered and some a priori bounds are derived. A numerical method is developed for the problem, where appropriate layer adapted Shishkin and generalized Shishkin meshes are considered. Error analysis of the method is given for both Shishkin and generalized Shishkin meshes.
Details
Keywords
Mukesh Kumar, Muna Ahmed Al-Romaihi and Bora Aktan
The current study aims to investigate the determinants of nonperforming loans (NPLs) in the GCC economies during the period spanning 2000 to 2018. It also examines whether the…
Abstract
Purpose
The current study aims to investigate the determinants of nonperforming loans (NPLs) in the GCC economies during the period spanning 2000 to 2018. It also examines whether the worldwide financial crisis of 2007–2008, which brought the issue of non–performing loans to the greater attention of academics and policymakers, had a substantial impact on NPLs in this region.
Design/methodology/approach
The sample consists of 53 conventional banks from GCC countries, and the basic data for the study is obtained from various sources such as Bankscope, IMF World Economic Outlook, World Bank and Chicago Board of Options Exchange Market Volatility Index. The estimations were done by dynamic panel data regression modeling using system generalized methods of moments.
Findings
The findings reveal that both, the non-oil real GDP growth rate and inflation have favorable effects on NPLs. On the other hand, domestic credit to the private sector and the volatility index have an adverse effect on NPLs. Furthermore, the period-wise analysis shows that the relevance and significance of the determinants of NPLs vary between the precrisis and postcrisis periods. It is also reflected through the intercept dummy, which is found to be significant, indicating that the financial crisis, as a global economic factor, had a significant impact on NPLs. A number of robustness tests are applied, which indicate that the results are mostly robust and consistent in terms of the significance of the explanatory variables and the direction of their relationship with the dependent variable.
Practical implications
Policymakers and bank authorities must strive to maintain a healthy economy and implement macroprudential policies to improve the financial stability of banks and reduce credit risk.
Originality/value
To the best of the authors’ knowledge, this is likely the first study that empirically investigates the influence of the financial crisis on NPLs in the context of GCC economies. In addition, the research spans 19 years to produce more conclusive results.
Details