This study aims to identify the trending topics, emerging themes and future research directions in supply chain management (SCM) through multiple source of data. The insights…
Abstract
Purpose
This study aims to identify the trending topics, emerging themes and future research directions in supply chain management (SCM) through multiple source of data. The insights would be of use to academics, practitioners and policymakers to leverage latest developments in addressing current and future challenges.
Design/methodology/approach
This study uses a multiple source of data such as published literature and social media data including supply chain blogs and forums contents on business-to-business (B2B) firms to identify trending topics, emerging themes and future research directions in SCM. Topic modeling, a machine learning technique, is used to derive the topics and themes. Examining supply chain blogs and forums offer a valuable perspective on current issues and challenges faced by B2B firms. By analyzing the content of these online discussions, the study identifies emerging themes and topics of interest to practitioners and researchers.
Findings
The study synthesizes 1,648 published articles and more than 1.3 lakh tweets, discussions and expert views from social media, including various blogs and supply chain forums, and identifies six themes, of which three are trending, and the other three are emerging themes in the supply chain. Rather than aggregate implications, the study integrates findings from two databases and proposes a framework encompassing the drivers, processes and impacts on each theme and derives promising avenues for future research.
Originality/value
Prior literature has majorly used published research articles and reports as a primary source of information to identify the trending theme and emerging topics. To the best of the authors’ knowledge, this is the first study of its kind to examine the potential value of information from social media, such as blogs, websites, forums and published literature to discover new supply chain trends and themes related to B2B firms and derive encouraging possibilities for future research.
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Anup Kumar, Santosh Kumar Shrivastav and Subhajit Bhattacharyya
This study proposes a methodology based on data source triangulation to measure the “strategic fit” for the automotive supply chain.
Abstract
Purpose
This study proposes a methodology based on data source triangulation to measure the “strategic fit” for the automotive supply chain.
Design/methodology/approach
At first, the authors measured the responsiveness of the Indian automobile supply chain, encompassing the top ten major automobile manufacturers, using both sentiment and conjoint analysis. Second, the authors used data envelopment analysis to identify the frontiers of their supply chain. The authors also measured the supply chain's efficiency, using the balance sheet. Further, the authors analyzed the “strategic fit” zone and discussed the results.
Findings
The results indicate that both the proposed methods yield similar outcomes in terms of strategic fitment.
Practical implications
The study outcomes facilitate measuring the strategic fit, thereby leveraging the resources available to align. The methodology proposed is both easy to use and practice. The methodology eases time and costs by eliminating hiring agencies to appraise the strategic fit. This valuable method to measure strategic fit can be considered feedback for strategic actions. This methodology could also be incorporated possibly as an operative measurement and control tool.
Originality/value
Data triangulation meaningfully enhances the accuracy and reliability of the analyses of strategic fit. Data triangulation leads to actionable insights relevant to top managers and strategic positioning of top managers within a supply chain.
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The aim of this paper is to investigate the failure probability in an irregular area in pipeline (elbow) over its lifetime. The reliability analysis is performed by using of an…
Abstract
Purpose
The aim of this paper is to investigate the failure probability in an irregular area in pipeline (elbow) over its lifetime. The reliability analysis is performed by using of an enhanced first-order reliability method / second-order reliability method (FORM/SORM) and Monte Carlo simulation methods: a numerical model of a corroded pipeline elbow was developed by using finite element method; also, an empirical mechanical behavior model has been proposed. A numerical case with high, moderate and low corrosion rates was conducted to calculate the deferent reliability indexes. The found results can be used in an application case for managing an irregular area in pipeline lifetime. Hence, it is necessary to ensure a rigorous inspection for this part of a pipeline to avoid human and environmental disasters.
Design/methodology/approach
The present paper deals a methodology for estimating time-dependent reliability of a corroded pipeline elbow. Firstly, a numerical model of corroded elbow is proposed by using the finite element method. A mechanical behavior under the corrosion defect in time is studied, and an empirical model was also developed.
Findings
The result of this paper can be summarized as: a mechanical characterization of the material was carried out experimentally. A numerical model of a corroded pipeline elbow was developed by using the finite element method. An empirical mechanical behavior model has been developed. The reliability of a corroding pipe elbow can be significantly affected by corrosion and residual stress. A proportional relationship has been found between probability of failure and corrosion rate. The yield stress and pressure service have an important sensitivity factor.
Originality/value
Aiming to help Algerian gas and oil companies' decision makers, the present paper illustrates a methodology for estimating time-dependent reliability of a corroded pipeline elbow over its lifetime using numerical models by applying the finite element method. Firstly, a numerical model of a corroded pipe elbow was developed and coupled with an empirical mechanical behavior model, which is also proposed. A probabilistic is then developed to provide realistic corrosion parameters and time modeling, leading to the real impact on the lifetime of an elbow zone in pipeline. The reliability indexes and probability of failure for various corrosion rates with and without issued residual stress are computed using Monte Carlo simulation and FORM.
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Rahul Khurana and Santosh Rangnekar
The study emphasizes the role of an individual's mindfulness and temperance in making employees fit their organizations by comparing the direct effect of mindfulness and its…
Abstract
The study emphasizes the role of an individual's mindfulness and temperance in making employees fit their organizations by comparing the direct effect of mindfulness and its indirect effect through temperance on the employees' person–organization fit (P-O fit). Data were collected from 185 Indian employees working at managerial positions in manufacturing and service industries through an online questionnaire in a cross-sectional research design. Structure equation modelling (SEM) was used to test the associations, and it was observed that mindfulness among employees is positively related to their P-O fit. Similarly, employees' temperance is also positively associated with their P-O fit. Furthermore, it is observed that temperance acts as a partial mediator between mindfulness and P-O fit. Mindful employees would be more aware of their surroundings, making them aware of the values that the workplace demands. The same awareness would compel the employees to have temperance (self-control) to keep their values in line with organizational values. The study contributes to the virtue theory and the value congruence theory in the organizational context. This study recommends that the management promotes mindfulness and temperance among the employees through various interventions and new technological aids to promote the P-O fit of the employees. To the best of our knowledge, this original work has novelty to investigate the relationship of mindfulness with P-O fit, taking into account the role of temperance of the employee.
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Aakash Khindri and Santosh Rangnekar
Drawing insights from Piaget's theory of cognitive development and exploring their applicability to working adults while assessing the role of tenure, as appreciated by multiple…
Abstract
Drawing insights from Piaget's theory of cognitive development and exploring their applicability to working adults while assessing the role of tenure, as appreciated by multiple studies associated with adaptability and openness, the current study examines the influence of work experience in the relationship between an individual's adaptability and openness to people's ideas in the context of the Indian workplace. The study followed a cross-sectional survey-based design, and data were gathered from 202 junior, middle and senior executives from Indian manufacturing and service organizations. Using PROCESS macro in SPSS, the moderating effect of work experience on the linkage between adaptability to situations and openness to people's ideas was examined. The study results depicted that adaptability to situations is positively associated with a person's openness to people's ideas. Such a result indicates that promoting adaptability among employees could lead to openness in behaviour towards ideas of their colleagues and other people, which may promote team cohesiveness and learning in the long run. Also, the work experience of employees was found to be moderating the relation between adaptability and openness such that the increasing years of work experience tend to enhance the positive relationship between adaptability and openness. These results suggest that as the work experience increases, the positive association between adaptability and tendency to be open towards people's ideas strengthens. Further, the implications for the domains of research and practice, limitations of the study and directions for future studies have been discussed.
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Anjali Dutta and Santosh Rangnekar
This study aims to investigate the relationship between individuals' preference for teamwork and communities of practice (CoPs) mediated by individuals' concern for team members…
Abstract
This study aims to investigate the relationship between individuals' preference for teamwork and communities of practice (CoPs) mediated by individuals' concern for team members built from the perspective of social learning system for knowledge sharing and learning. A cross-sectional study with data collected from the respondents through a convenience, non-random, non-probability sampling technique was employed in this research. The data of 240 were collected from the respondents belonging to manufacturing and service organizations in India and analyzed through confirmatory factor analysis, multiple regression analysis and PROCESS macro from Hayes with bootstrapping technique. The findings from the analysis showed a positive relationship between individuals' preference for teamwork and CoPs, while concern for team members mediated the relationship between preference for teamwork and CoPs. When employees prefer to work in teams, they positively consider participating in CoPs. Thus, organizations should strategically formulate conditions for employees to enable them to prefer working in teams and groups so that they collaborate as CoPs for knowledge creation, sharing and learning. Such learning through CoPs can pave the way for skill development and high-quality performance, thereby evolving as a framework for human capital development. This chapter provides an understanding of the relationship between individual employees' preference for teamwork and CoPs, mediated by individuals' concern for team members in an Indian context. Implications for theory and practice are discussed, along with limitations and future research direction.
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Esrafil Ali, Biswajit Satpathy and Santosh Kumar Prusty
This paper aims to understand the two-way interaction between corporate social responsibility (CSR) and the attractiveness of organization to job seekers (AOJS).
Abstract
Purpose
This paper aims to understand the two-way interaction between corporate social responsibility (CSR) and the attractiveness of organization to job seekers (AOJS).
Design/methodology/approach
A system dynamics model is developed in the form of a causal loop diagram (CLD) that explains the CSR-AOJS interaction dynamically. To test the credibility of the developed model, the survey data are used to validate the causal relationships in the CLD.
Findings
This study found that developing an effective strategy or tool by capturing various essential CSR elements can attract potential job seekers.
Originality/value
The developed model is relevant to policymakers, decision-makers and managers when strategizing the CSR plan to attract potential job seekers.
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This study investigates the overall publications of The TQM Journal since its inception with an aim to identify the trending topics and emerging trends.
Abstract
Purpose
This study investigates the overall publications of The TQM Journal since its inception with an aim to identify the trending topics and emerging trends.
Design/methodology/approach
The quantitative bibliometric and social network analysis techniques composed of keywords, co-occurrence network and keyword cluster detection are employed to conduct the investigation. A total of 968 papers published in The TQM Journal till August 2022 were sourced from the SCOPUS database to conduct the analysis.
Findings
The research identifies five themes from the published articles namely, customer service experience and satisfaction; quality management and organizational performance; quality measurement tools and models; quality and sustainable development; and quality and competitive advantage. The study also identifies the most significant articles, authors and countries published in the journal and shows that Industry 4.0 is the trending topic and quality 4.0 the new emerging trend in the journal.
Research limitations/implications
The analysis is carried out only for papers published in The TQM Journal till August 2022; those after this month are not included in the analysis. The outcome of this study is dynamic in nature and subject to change over time as more papers, citations and collaborations are added to the list.
Originality/value
This is the first article of its kind to explore The TQM Journal publications with an aim to identify trending and emerging topics and also the most valuable authors based on the number of publications and citations through the bibliometric analysis.
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Nandkumar Mishra and Santosh B. Rane
The purpose of this technical paper is to explore the application of analytics and Six Sigma in the manufacturing processes for iron foundries. This study aims to establish a…
Abstract
Purpose
The purpose of this technical paper is to explore the application of analytics and Six Sigma in the manufacturing processes for iron foundries. This study aims to establish a causal relationship between chemical composition and the quality of the iron casting to achieve the global benchmark quality level.
Design/methodology/approach
The case study-based exploratory research design is used in this study. The problem discovery is done through the literature survey and Delphi method-based expert opinions. The prediction model is built and deployed in 11 cases to validate the research hypothesis. The analytics helps in achieving the statistically significant business goals. The design includes Six Sigma DMAIC (Define – Measure – Analyze – Improve and Control) approach, benchmarking, historical data analysis, literature survey and experiments for the data collection. The data analysis is done through stratification and process capability analysis. The logistic regression-based analytics helps in prediction model building and simulations.
Findings
The application of prediction model helped in quick root cause analysis and reduction of rejection by over 99 per cent saving over INR6.6m per year. This has also enhanced the reliability of the production line and supply chain with on-time delivery of 99.78 per cent, which earlier was 80 per cent. The analytics with Six Sigma DMAIC approach can quickly and easily be applied in manufacturing domain as well.
Research limitations implications
The limitation of the present analytics model is that it provides the point estimates. The model can further be enhanced incorporating range estimates through Monte Carlo simulation.
Practical implications
The increasing use of prediction model in the near future is likely to enhance predictability and efficiencies of the various manufacturing process with sensors and Internet of Things.
Originality/value
The researchers have used design of experiments, artificial neural network and the technical simulations to optimise either chemical composition or mould properties or melt shop parameters. However, this work is based on comprehensive historical data-based analytics. It considers multiple human and temporal factors, sand and mould properties and melt shop parameters along with their relative weight, which is unique. The prediction model is useful to the practitioners for parameter simulation and quality enhancements. The researchers can use similar analytics models with structured Six Sigma DMAIC approach in other manufacturing processes for the simulation and optimisations.