Mohamed Abdel Basset, Mai Mohamed, Arun Kumar Sangaiah and Vipul Jain
Strategic planning is an organization’s process of describing its strategy, or direction, and making decisions on allocating its resources to track this strategy. SWOT analysis is…
Abstract
Purpose
Strategic planning is an organization’s process of describing its strategy, or direction, and making decisions on allocating its resources to track this strategy. SWOT analysis is one of the most commonly used techniques for strategic planning. SWOT examines the strengths (S) and weaknesses (W) agents of the community together with opportunities (O) and threats (T), for selecting and implementing the best strategy which helps in achieving its goals. The purpose of this paper is to enhance the performance of SWOT analysis regarding the quantitative side of strategies, select the best strategy from different strategies and deal effectively with vague and incompatible information, which occurs usually in actual life.
Design/methodology/approach
This study used the neutrosophic analytic hierarchy process (AHP) incorporated with SWOT analysis.
Findings
By adding the neutrosophic AHP to SWOT analysis, the performance of SWOT analysis is enhanced through determining the quantitative values and dealing with vague and inconsistent information effectively leading to improved decisions.
Research limitations/implications
The developed integrated methodology is validated in a real-life case of Starbucks company. For the case study of Starbucks company, the proposed model helps in determining different strategic plans and, further, ranking these plans effectively, which will help the company to compete with its competitors and develop itself by obtaining a competitive advantage over its competitors in an uncertain business environment.
Practical implications
In the case study of Starbucks company, the proposed model helps to determine the different strategic plans, rank these plans which help the company compete with its competitors, develop itself and grow.
Originality/value
This research is the first to address SWOT analysis with neutrosophic AHP.
Details
Keywords
Hardik Shah, Shilpa Jain and Vipul Jain
Teams have become the dominant mode of work in contemporary organizations and critical for successful completion of various tasks, projects and overall organizational…
Abstract
Purpose
Teams have become the dominant mode of work in contemporary organizations and critical for successful completion of various tasks, projects and overall organizational effectiveness. Organizational factors such as organizational culture have often been investigated as contributing to team performance since it is difficult to develop and engage teams. But the effect of (organizational) team culture on team effectiveness (TE) has received less support. Therefore, this paper examines how factors such as organization team culture (OTC) affect different dimensions of TE in a power sector organization which has undergone a business transformation resulting in adoption of team-based work structures.
Design/methodology/approach
Survey instrument capturing the variables of organizational team culture and TE was administered to mid-level managers in a power sector organization in India. Structural equation modeling (SEM) was used to test the model fit for the proposed model.
Findings
A key finding of the research was that team culture (OTC dimensions) (i.e. participation, communication, trust, training inputs and support and support for teamwork) contribute to TE.
Originality/value
OTC and its impact on creating effective teams, particularly in the power sector, is an original contribution of this research. The OTC and TE framework may be used to diagnose team weaknesses and concerns and to design effective HR interventions.
Details
Keywords
Eleonora Bottani, Piera Centobelli, Mosé Gallo, Mohamad Amin Kaviani, Vipul Jain and Teresa Murino
The purpose of this paper is to propose an artificial intelligence-based framework to support decision making in wholesale distribution, with the aim to limit wholesaler…
Abstract
Purpose
The purpose of this paper is to propose an artificial intelligence-based framework to support decision making in wholesale distribution, with the aim to limit wholesaler out-of-stocks (OOSs) by jointly formulating price policies and forecasting retailer’s demand.
Design/methodology/approach
The framework is based on the cascade implementation of two artificial neural networks (ANNs) connected in series. The first ANN is used to derive the selling price of the products offered by the wholesaler. This represents one of the inputs of the second ANN that is used to anticipate the retailer’s demand. Both the ANNs make use of several other input parameters and are trained and tested on a real wholesale supply chain.
Findings
The application of the ANN framework to a real wholesale supply chain shows that the proposed methodology has the potential to decrease economic loss due to OOS occurrence by more than 56 percent.
Originality/value
The combined use of ANNs is a novelty in supply chain operation management. Moreover, this approach provides wholesalers with an effective tool to issue purchase orders according to more dependable demand forecasts.
Details
Keywords
Gunjan Soni, Surya Prakash, Himanshu Kumar, Surya Prakash Singh, Vipul Jain and Sukhdeep Singh Dhami
The Indian marble and stone industry has got the potential to contribute well to the development of the emerging economy. However, unlike the other Indian industries, stone and…
Abstract
Purpose
The Indian marble and stone industry has got the potential to contribute well to the development of the emerging economy. However, unlike the other Indian industries, stone and marble industries are highly underrated sectors, which may become a critical factor for development. This paper analyses the sustainability factors in supply chain management practices.
Design/methodology/approach
A literature review is used to identify the barriers and drivers in sustainable supply chain management practices. Interpretive structural modeling has been used to obtain a hierarchy of barriers and drivers along with driving power and dependence power analysis. Further, MICMAC analysis is used for segregating the barriers and drivers in terms of their impact on sustainability.
Findings
The findings of the work of this research are that the attention of society, government, and commercial banks should be more toward the unorganized condition of stone and marble sector. There should be an increase in the commitment of stakeholders to reduce pollution and install safety, by enforcing more relevant laws and regulations and creating the importance of environmental awareness.
Originality/value
The main contribution of this research is to identify the barriers and drivers of sustainable supply chain management in a stone and marble industry. The paper proposes a sound mathematical model to prioritize the critical factors for responsible production and consumption of resources from sustainability perspectives of stone industry.
Details
Keywords
Balan Sundarakani, Rukshanda Kamran, Piyush Maheshwari and Vipul Jain
Supply chain is the area that requires effective and integrated means of communication, shared risk, collaboration and orchestration in order to work successfully and the cloud…
Abstract
Purpose
Supply chain is the area that requires effective and integrated means of communication, shared risk, collaboration and orchestration in order to work successfully and the cloud computing has lot to offer to this domain. Cloud computing has appeared as a modern paradigm in supply chain networks for creating intelligent industries of future. The purpose of this paper is to propose a framework that can transform supply chain stakeholders toward Industry 4.0.
Design/methodology/approach
Cloud computing is attributed with increasing competitiveness by focusing on cost reduction, greater elasticity, flexibility and maximum utilization of resources which results in successfully achieving business goals. This paper proposes a Hybrid Supply Chain Cloud model, which integrates the infrastructure, the resources and the configurations of platforms.
Findings
This research paper is aimed at proposing a hybrid cloud that essentially helps in integrating the supply chain network with the flexibility and efficiency. It is important that a supply chain network adds value to ensure customer satisfaction and this can be best achieved by collaborating it with hybrid cloud.
Research limitations/implications
This research provides a consistent central management and comprehensive view of all computing resources, which gives organizations the knowledge they need to optimize workload placement.
Practical implications
The findings derived from this research aim to facilitate policy makers and practitioners to develop effective courses of action in current and future supply chain management. Therefore, upon implementation, this model can provide long-term benefits for the organizations by improving the overall efficiency of its supply chain network.
Originality/value
The proposed hybrid cloud will provide deep level of integration in Industry 4.0 situation and thereby brought up portable comprehensive infrastructure based on resources and required configuration in real-time environment.
Details
Keywords
Gunjan Soni, Vipul Jain, Felix T.S. Chan, Ben Niu and Surya Prakash
It is worth mentioning that in supply chain management (SCM), managerial decisions are often based on optimization of resources. Till the early 2000s, supply chain optimization…
Abstract
Purpose
It is worth mentioning that in supply chain management (SCM), managerial decisions are often based on optimization of resources. Till the early 2000s, supply chain optimization problems were being addressed by conventional programming approaches such as Linear Programming, Mixed-Integer Linear Programming and Branch-and-Bound methods. However, the solution convergence in such approaches was slow. But with the advent of Swarm Intelligence (SI)-based algorithms like particle swarm optimization and ant colony optimization, a significant improvement in solution of these problems has been observed. The purpose of this paper is to present and analyze the application of SI algorithms in SCM. The analysis will eventually lead to development of a generalized SI implementation framework for optimization problems in SCM.
Design/methodology/approach
A structured state-of-the-art literature review is presented, which explores the applications of SI algorithms in SCM. It reviews 56 articles published in peer-reviewed journals since 1999 and uses several classification schemes which are critical in designing and solving a supply chain optimization problem using SI algorithms.
Findings
The paper revels growth of swarm-based algorithms and seems to be dominant among all nature-inspired algorithms. The SI algorithms have been used extensively in most of the realms of supply chain network design because of the flexibility in their design and rapid convergence. Large size problems, difficult to manage using exact algorithms could be efficiently handled using SI algorithms. A generalized framework for SI implementation in SCM is proposed which is beneficial to industry practitioners and researchers.
Originality/value
The paper proposes a generic formulation of optimization problems in distribution network design, vehicle routing, resource allocation, inventory management and supplier management areas of SCM which could be solved using SI algorithms. This review also provides a generic framework for SI implementation in supply chain network design and identifies promising emerging issues for further study in this area.
Details
Keywords
Surya Prakash, Sameer Kumar, Gunjan Soni, Vipul Jain, Saty Dev and Charu Chandra
Collaboration methods are unique strategies that can help organizations hedge against external and internal supply chain risks without stressing their relationships with supply…
Abstract
Purpose
Collaboration methods are unique strategies that can help organizations hedge against external and internal supply chain risks without stressing their relationships with supply chain partners. However, selecting the most appropriate collaboration method from a given set of strategies is a multifaceted challenge. This paper aims to address this issue.
Design/methodology/approach
The decision maker's dilemma of fighting data uncertainty in input parameters to check the efficacy of a given collaboration or mitigation approach is tackled by the integration of Grey theory with the technique for order of preference by similarity to ideal solution (TOPSIS) method. The proposed technique is applied and tested for an Indian diesel generator-set manufacturer to identify the most apposite set of sustainable collaboration strategies.
Findings
The results showed that when a firm is bidding for different horizontal collaboration strategies across its supply chain system technology and resource-sharing-centered collaboration strategies are the prominent option. In the case of the company's vertical collaboration deployment, the focus should be kept on information sharing to achieve impactful collaboration. The outcome of the analysis helped the Indian manufacturer to adopt transparent order and production information sharing with its regional distributors and core suppliers within its supply chain.
Originality/value
This study demonstrates from a methodological perspective the successful application of the Grey-TOPSIS approach that effectively captures data uncertainty. It also integrates sustainability parameters in collaboration strategy criteria selections.
Details
Keywords
Dheeraj Chandra, Vipul Jain and Felix T.S. Chan
The increasing prevalence of a wide range of infectious diseases, as well as the underwhelming results of vaccination rates that may be traced back to problems with vaccine…
Abstract
Purpose
The increasing prevalence of a wide range of infectious diseases, as well as the underwhelming results of vaccination rates that may be traced back to problems with vaccine procurement and distribution, have brought to the fore the importance of vaccine supply chain (VSC) management in recent years. VSC is the cornerstone of effective vaccination; hence, it is crucial to enhance its performance, particularly in low- and middle-income countries where immunization rates are not satisfactory.
Design/methodology/approach
In this paper, the authors focus on VSC performance improvement of India by proposing supply contracts under demand uncertainty. The authors propose three contracts – wholesale price (WSP), cost sharing (CS) and incentive mechanism (IM) for the government-operated immunization program of India.
Findings
The authors' findings indicate that IM is capable of coordinating the supply chain, whereas the other two contracts are inefficient for the government. To validate the model, it is applied to a real-world scenario of coronavirus disease 2019 (COVID-19) in India, and the findings show that an IM contract improves the overall efficiency of the system by 23.72%.
Originality/value
Previous studies focused mainly on the influenza VSC industry within developed nations. Nonetheless, there exists a dearth of literature pertaining to the examination of supply contracts and their feasibility for immunization programs that are administered by the government and aimed at optimizing societal benefits. The authors' findings can be beneficial to the immunization program of India to optimize their VSC cost.
Details
Keywords
Sameer Kumar, Yogesh Marawar, Gunjan Soni, Vipul Jain, Anand Gurumurthy and Rambabu Kodali
Lean manufacturing (LM) is prevalent in the manufacturing industry; thus, focusing on fast and accurate lean tool implementation is the new paradigm in manufacturing. Value stream…
Abstract
Purpose
Lean manufacturing (LM) is prevalent in the manufacturing industry; thus, focusing on fast and accurate lean tool implementation is the new paradigm in manufacturing. Value stream mapping (VSM) is one of the many LM tools. It is understood that combining LM implementation with VSM tools can generate better outcomes. This paper aims to develop an expert system for optimal sequencing of VSM tools for lean implementation.
Design/methodology/approach
A proposed artificial neural network (ANN) model is based on the analytic network process (ANP) devised for this study. It will facilitate the selection of VSM tools in an optimal sequence.
Findings
Considering different types of wastes and their level of occurrence, organizations need a set of specific tools that will be effective in the elimination of these wastes. The developed ANP model computes a level of interrelation between wastes and VSM tools. The ANN is designed and trained by data obtained from numerous case studies, so it can predict the accurate sequence of VSM tools for any new case data set.
Originality/value
The design and use of the ANN model provide an integrated result of both empirical and practical cases, which is more accurate because all viable aspects are then considered. The proposed modeling approach is validated through implementation in an automobile manufacturing company. It has resulted in benefits, namely, reduction in bias, time required, effort required and complexity of the decision process. More importantly, according to all performance criteria and subcriteria, the main goal of this research was satisfied by increasing the accuracy of selecting the appropriate VSM tools and their optimal sequence for lean implementation.
Details
Keywords
Gaurav Kabra, Anbanandam Ramesh, Vipul Jain and Pervaiz Akhtar
The humanitarian supply chain (HSC) area is rich with conceptual frameworks with a focus on the importance of information and digital technology (IDT) applications. These…
Abstract
Purpose
The humanitarian supply chain (HSC) area is rich with conceptual frameworks with a focus on the importance of information and digital technology (IDT) applications. These frameworks have a limited scope in investigating and prioritizing barriers to IDT adoption in HSCs. The present study thus identifies and prioritizes the barriers to IDT adoption in organizations involved in HSCs.
Design/methodology/approach
By using a literature review allied with expert discussions and a fuzzy analytic hierarchy process (F-AHP), the study identifies and prioritizes a comprehensive set of barriers that organizations involved in HSCs may consider to improve IDT adoption.
Findings
The study investigates five main barriers (strategic, organizational, technological, financial and human) interlocked with 25 sub-barriers impacting the level of IDT adoption in organizations involved in HSCs. The findings indicate that strategic barriers (SBs) are of greatest importance, followed by organizational, technological, financial and human barriers. The findings indicate the difference in ranking barriers influencing the adoption of IDTs in HSCs compared to the commercial supply chain.
Research limitations/implications
Although a three-step method adopted for this study is rigorous in terms of the way this research is conducted, it is essential to report that prioritization is based on the subjective opinions of the experts.
Practical implications
The findings aim to assist policymakers and practitioners in developing effective strategies to improve IDT adoption in organizations engaged in HSCs. Moreover, the prioritization of barriers provides a systematic way to overcome any barriers to improve HSC performance.
Originality/value
This study is first of its kind that investigates and prioritizes the barriers to IDT adoption in HSCs.