Abhinav Kumar Sharma, Indrajit Mukherjee, Sasadhar Bera and Raghu Nandan Sengupta
The primary objective of this study is to propose a robust multiobjective solution search approach for a mean-variance multiple correlated quality characteristics optimisation…
Abstract
Purpose
The primary objective of this study is to propose a robust multiobjective solution search approach for a mean-variance multiple correlated quality characteristics optimisation problem, so-called “multiple response optimisation (MRO) problem”. The solution approach needs to consider response surface (RS) model parameter uncertainties, response uncertainties, process setting sensitivity and response correlation strength to derive the robust solutions iteratively.
Design/methodology/approach
This study adopts a new multiobjective solution search approach to determine robust solutions for a typical mean-variance MRO formulation. A fine-tuned, non-dominated sorting genetic algorithm-II (NSGA-II) is used to derive efficient multiobjective solutions for varied mean-variance MRO problems. The iterative search considers RS model uncertainties, process setting uncertainties and response correlation structure to derive efficient fronts. The final solutions are ranked based on two different multi-criteria decision-making (MCDM) techniques.
Findings
Five different mean-variance MRO cases are selected from the literature to verify the efficacy of the proposed solution approach. Results derived from the proposed solution approach are compared and contrasted with the best solution(s) derived from other approaches suggested in the literature. Comparative results indicate significant superiorities of the top-ranked predicted robust solutions in nondominated frequency, closeness-to-target and response variabilities.
Research limitations/implications
The solution approach depends on RS modelling and considers continuous search space.
Practical implications
In this study, promising robust solutions are expected to be more suitable for implementation than point estimate-based MOO solutions for a real-life MRO problem.
Originality/value
No evidence of earlier research demonstrates the superiority of a MOO-based iterative solution search approach for mean-variance MRO problems by simultaneously considering model uncertainties, response correlation and process setting sensitivity.
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The vaccine supply chain (VSC) performance remains under stress during pandemic outbreaks than conventional vaccination drives due to desired vaccination coverage. Therefore, it…
Abstract
Purpose
The vaccine supply chain (VSC) performance remains under stress during pandemic outbreaks than conventional vaccination drives due to desired vaccination coverage. Therefore, it is essential to identify the crucial performance objectives (POs) and their interrelationship structure and prioritize them to improve performance in a pandemic VSC.
Design/methodology/approach
This study combines the decision-making trial and evaluation laboratory based analytic network process (DANP) method with spherical fuzzy sets (SFS) to explore critical POs of the pandemic VSC in the balanced scorecard framework. The SFS theory tackles the uncertainty of POs and DANP interlaced causal relationships among crucial POs to the pandemic VSC while ranking them for prioritization.
Findings
This work identifies 32 issues associated with pandemic VSC and maps them against 13 POs. Effective communication, adequate health financing and operating cost optimization are the most critical POs, and operational issues listed under them must be prioritized to improve the overall VSC performance for future pandemics. The relationship structure among these POs is also summarized using the balanced scorecard framework in a strategy map.
Research limitations/implications
The strategy map proposed in this study can help practitioners to address the causality among different POs and underlying issues for the sudden expansion of vaccination programs during pandemics from an economic, social and operational perspective.
Originality/value
To the best of the authors’ knowledge, this is the first empirical study to suggest improving the VSC performance during the pandemic by focusing on the causative relationship and priority of different detected POs.
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Sasadhar Bera and Subhajit Bhattacharya
This exploratory study examines and comprehends the relative importance of mobile app attributes from a consumer perspective. Both quantitative and qualitative analysis approaches…
Abstract
Purpose
This exploratory study examines and comprehends the relative importance of mobile app attributes from a consumer perspective. Both quantitative and qualitative analysis approaches explore users' behavior and attitudes toward the priorities of mobile app attributes and preferences, identifying correlations between attributes and aggregating individual attributes into groups.
Design/methodology/approach
Online convenience sampling and snowball sampling resulted in 417 valid responses. The numerical data are analyzed using the relative to an identified distribution (RIDIT) scoring system and gray relational analysis (GRA), and qualitative responses are investigated using text-mining techniques.
Findings
This study finds enhanced nuances of user preferences and provides data-driven insights that might help app developers and marketers create a distinct app that will add value to consumers. The latent semantic analysis indicates relationship structure among the attributes, and text-based cluster analysis determines the subsets of attributes that represent the unique functions of the mobile app.
Practical implications
This study reveals the essential components of mobile apps, paying particular attention to the consumer value component, which boosts user approval and encourages prolonged use. Overall, the results demonstrate that developers must concentrate on its functional, technical and esthetic features to make an app more exciting and practical for potential users.
Originality/value
Most scholarly research on apps has focused on their technological merits, aesthetics and usability from the user's perspective. A post-adoption multi-attribute app analysis using both structured and unstructured data is conducted in this study.
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Sasadhar Bera, Pradeep Kumar and Subhajit Bhattacharya
The paper aims to investigate the cardiology department’s operational system for improving flexibility by minimizing the patient waiting time and simultaneously maximizing the…
Abstract
Purpose
The paper aims to investigate the cardiology department’s operational system for improving flexibility by minimizing the patient waiting time and simultaneously maximizing the utilization of service capacity in an uncertain environment. This article also proposes a policy framework that suggests a pool of additional resources and inter-firm collaboration can boost healthcare service delivery excellence.
Design/methodology/approach
A discrete event simulation (DES) approach is followed for modeling patient flow and determining the service capacity to respond to demand variability and uncertainty. The model's outputs are used to minimize patient waiting time, maximize the utilization of the resources and match the service capacity with the patient demand.
Findings
This research has tested two hypotheses and proved that an increase in waiting time decimates the throughput rate, and additional resources deployment in bottleneck activity positively impacts the throughput rate. The simulated scenarios prescribe an enhanced service capacity with quality care and further contribute to operational performance in reduced waiting time and cost. The results indicate that flexibility reduces the patient waiting time and maximizes the throughput rate.
Practical implications
The study guides the healthcare policymakers to develop flexible competence and facilitate service mechanisms that are adaptive and robust while operating under a volatile environment. The article contributes to the healthcare literature that conjoins flexibility through simulation and resource utilization.
Originality/value
This research is based on real-life primary data collected from healthcare providers. This study adds value to the healthcare systems to adopt strategic decisions to build flexibility through resource allocation, sharing and coordinated care.
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Piyush Gupta, Piyush Pranjal, Sasadhar Bera, Soumya Sarkar and Amit Sachan
Considerable amount of purchases in business-to-business (B2B) markets make through the tendering process. As technology keeps driving B2B procurement, both the…
Abstract
Purpose
Considerable amount of purchases in business-to-business (B2B) markets make through the tendering process. As technology keeps driving B2B procurement, both the supplier/contractor and buyer firms have settled down in their respective roles in the electronic-tendering environment. Researchers have ignored the supplier-side e-tender-driven marketing process that might lead to substantively successful financial performance. The purpose of this study is to improve the performance of an e-tender-driven marketing process of an original equipment manufacturer (OEM) incorporating the stakeholder's inputs.
Design/methodology/approach
Discrete event simulation modelling (DESM) has been used as a methodology to model, analyse and improve the process with the involvement of stakeholders at every stage of the study. Different scenarios are analysed to identify the near-optimal scenario based on agreed-upon key performance indicators.
Findings
Scenario that incorporated man-power sharing and eliminating avoidable activities gives the near-optimal solution for implementation.
Research limitations/implications
This study highlights that better insights can be gained by adopting the process-oriented view of the marketing–operations interface. Embracing a stakeholder-based consultative approach gives research a more practical outlook and reduces the gap between theory and practice. Suggestions for further research are provided.
Practical implications
B2B organizations, where lines between marketing and operations are blurred, can improve their marketing processes by implementing operations research tools.
Originality/value
This study provides an attempt to improve the performance of a supplier-side e-tender-driven marketing process of an OEM using the DESM methodology incorporating stakeholder's inputs.
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Naveen Virmani, Sasadhar Bera and Rohit Kumar
The purpose of the study is two-fold. First, to find out the different barriers that prevent the implementation of sustainable manufacturing practices in the case of Micro, Small…
Abstract
Purpose
The purpose of the study is two-fold. First, to find out the different barriers that prevent the implementation of sustainable manufacturing practices in the case of Micro, Small and Medium Enterprises (MSMEs). Second, quantifying the relative intensity of these barriers to understand the importance and dependence power of the observed variables.
Design/methodology/approach
Primary data were collected via structured questionnaires from 150 Indian MSMEs working in the automobile industry. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) was performed. Finally, barriers are ranked using graph theory and matrix approach (GTMA), considering the inheritance and interaction among the observed variables.
Findings
There are a total of 22 barriers to “sustainable manufacturing”. EFA and CFA models confirmed four different categories of barriers. In order of importance, they are ranked as – production and operations related; organization related; collaboration related; and government rules and regulations.
Practical implications
The findings show that there are multiple barriers to sustainable manufacturing. The barriers are categorized into four major categories, and their ranking provides an opportunity for prioritization from both policy and managerial perspectives. The barriers can be overcome through both policy interventions as well as through best practice sharing, benchmarking and organizational-wide initiatives.
Originality/value
The study is among the first studies that provide valuables insights on what are the 22 different barriers to sustainable manufacturing and its relevance to the MSMEs working in the automobile industry. The study would provide further opportunities for similar studies in different sectors.
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Pratik Rai, Sasadhar Bera and Pritee Ray
The study aims to develop an integrated quantitative approach and suggest a framework to assess the impact of a technological intervention on the internal process dimension of the…
Abstract
Purpose
The study aims to develop an integrated quantitative approach and suggest a framework to assess the impact of a technological intervention on the internal process dimension of the vaccine supply chain (VSC) system for multiple administered regions.
Design/methodology/approach
An evaluation index system is developed by selecting suitable performance indicators (PIs) that define the objectives of a VSC. Then multicriteria decision-making (MCDM) methods are applied to obtain pre and post-intervention relative ranks for the regions and performance scores of the objectives. A bilateral data envelopment analysis (DEA) compares significant efficiency differences between improvement and deterioration groups.
Findings
This study demonstrates that technological intervention improves the internal process dimension of a VSC for the regions under consideration. The empirical study delivers two groups of regions showing improvement or deterioration in relative performance ranking due to the technological intervention. However, the efficiency-based bilateral comparison may reveal an insignificant difference between the two groups.
Practical implications
Decision-makers associated with VSC will find the suggested model helpful in assessing the impact of technological intervention. They can easily identify specific objectives of VSC's internal process dimension, whether a particular region has observed an improvement or deterioration in its relative performance and maximize the outcome by focusing on the areas of concern for a specific region.
Originality/value
This study is the first to provide a quantitative approach that empirically determines relative performance improvement or deterioration of different regions for a set of identified VSC objectives in the context of the Indian states.
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Disha Bhanot, Varadraj Bapat and Sasadhar Bera
The purpose of this paper is to explore the factors which are crucial in determining the extent of financial inclusion in geographically remote areas. The study also aims to…
Abstract
Purpose
The purpose of this paper is to explore the factors which are crucial in determining the extent of financial inclusion in geographically remote areas. The study also aims to provide suggestive measures for banks to tap unexplored markets.
Design/methodology/approach
Primary data were collected via structured questionnaire from 411 households from the states of Assam and Meghalaya in north‐east India. Factors significantly contributing to inclusion were identified using a logistic regression model.
Findings
Level of financial inclusion in north‐east India remains very low. Income, financial information from various channels and awareness of self help groups (SHGs), and education are influential factors leading to inclusion. Nearness to post office banks increases the likelihood of inclusion. Factors like area terrain and receipt of government benefit individually do not facilitate inclusion. However, recipients of government benefits in plain areas show increased level of inclusion.
Research limitations/implications
The study was restricted to north‐east India, which limits the generalizability of the findings.
Practical implications
Banks and policy makers should work in close co‐ordination to spread financial information as those efforts are seen to directly impact inclusion, thereby providing new business opportunities to banks.
Originality/value
Using primary data, this study explores the potential predictors of financial inclusion in geographically remote areas. The study is unique in capturing the conditional relationships among variables which are bound to exist in real life scenarios. The findings of the paper are valuable for banks and policy makers.