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11 – 20 of 29Satyendra Kumar Sharma, Ravinder Singh and Rajesh Matai
Strategic sourcing and supply risk management have become interesting topics of research in the recent years. Automotive industry experts are increasingly focussing on improving…
Abstract
Purpose
Strategic sourcing and supply risk management have become interesting topics of research in the recent years. Automotive industry experts are increasingly focussing on improving the supply efficiency and performance towards gaining sustainable competitive advantage. This study aims to classify, through an exhaustive review of past literature, the various enablers and barriers of strategic sourcing risk management (SSRM) and use them to identify the problems in the automobile sector.
Design/methodology/approach
For the purpose of this research, responses were collected through structured questionnaire from respondents belonging to senior management cadre in the industry. Factor analysis and force field analysis tools have been used for analysis.
Findings
Through independent exploratory factor analysis (EFA), four SSRM enablers, namely, supplier risk assessment, data sharing in supply network, partnership with supplier and supply flexibility, were identified. Similarly EFA revealed four SSRM barriers, namely, cost focus, ad hoc or poor planning, data security/privy breaches and hard visualization of SSRM benefits. Through a force field analysis, it was found out that the barriers had a higher impact on the SSRM initiatives than enablers.
Practical implications
The research suggests the ways how managers can reduce the impact of barriers and increase the enabling forces.
Originality/value
This paper enumerates the barriers and enablers together on the same platform to prioritize and evolve strategies to overpower the barriers and strengthen the enablers.
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Himanshu Seth, Saurabh Chadha and Satyendra Sharma
The purpose of this study is to get insights into working capital management (WCM) practices and the determinants of its efficiency prevailing in the Indian manufacturing sector…
Abstract
Purpose
The purpose of this study is to get insights into working capital management (WCM) practices and the determinants of its efficiency prevailing in the Indian manufacturing sector using firm-specific as well as macro-economic variables by examining three efficiency models, i.e. cash conversion cycle (CCC), cash conversion efficiency (CCE) and net working capital level (NWCL).
Design/methodology/approach
The study uses panel data techniques on 1,207 firms of the Indian manufacturing sector, as well as on its nine key manufacturing industries from 2008 to 2018 for the analysis.
Findings
Several firm-specific variables such as net fixed asset ratio, size of the firm, profitability, firm’s growth, asset turnover ratio, age of the firm, interest rate and leverage have significant effect on WCM efficiency, whereas total assets growth rate, gross domestic product growth rate and inflation rate have insignificant effect on WCM efficiency.
Research limitations/implications
The study provides new empirical evidence on the short-term liquidity management of manufacturing firms prevailing in the developing countries such as India. The findings are particularly relevant in the present scenario when the liquidity levels are decelerating and there is a marked slowdown in private credit flows to the manufacturing sector due to the problem of burgeoning non-performing assets.
Originality/value
This study examines WCM efficiency exhaustively by incorporating both firm-specific and macro-economic variables using three efficiency measures, i.e. CCC, CCE and NWCL, results of which emerged as an answer to an efficient WCM.
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Na Zhou, Alice Chang-Richards, Kevin I-Kai Wang and Kim Natasha Dirks
This study aims to develop an architectural prototype of a Cyber-Physical System (CPS), as well as lay a technological foundation for future smart housing with improved health and…
Abstract
Purpose
This study aims to develop an architectural prototype of a Cyber-Physical System (CPS), as well as lay a technological foundation for future smart housing with improved health and well-being outcomes for its occupants.
Design/methodology/approach
This study deploys smart sensors to monitor the key environmental parameters of a house. Using Internet of Things technology, a prototype of a CPS has been developed for capturing the environmental conditions over time. A case study involving a property in New Zealand was undertaken to validate the prototype.
Findings
The study proposes a monitoring platform, enabled by the CPS and smart sensing devices, that collects, shares, stores, analyses and visualises indoor environment data. The reliability and accuracy of the monitoring system were enhanced by comparing the activity of house occupants with sensor data.
Research limitations/implications
Due to limited time, the prototype was tested in one house for a period of one month. Air quality was not considered in this study. However, the work suggests that such an approach provides an effective solution for government organisations and housing agencies to collect information for the purpose of assessing building thermal performance.
Originality/value
This research proposes a new lens consisting of a home environment monitoring application with health and well-being implications. It could also be used to inform the future design of healthy homes and buildings, both in New Zealand and internationally.
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Himanshu Seth, Saurabh Chadha and Satyendra Sharma
This paper evaluates the working capital management (WCM) efficiency of the Indian manufacturing industries through data envelopment analysis (DEA) and empirically investigates…
Abstract
Purpose
This paper evaluates the working capital management (WCM) efficiency of the Indian manufacturing industries through data envelopment analysis (DEA) and empirically investigates the influence of several exogenous variables on the WCM efficiency.
Design/methodology/approach
WCM efficiency was calculated using BCC input-oriented DEA model. Further, the panel data fixed effect model was used on a sample of 1391 Indian manufacturing firms spread across nine industries, covering the period from 2008 to 2019.
Findings
Firstly, the WCM efficiency of Indian manufacturing industries has been stable over the analysis period. Secondly, the capacity to generate internal resources, size, age, productivity, gross domestic product and interest rate significantly influence WCM efficiency.
Research limitations/implications
First, the selected study period has observed various economic uncertainties including demonetization and recession, so the scenario might differ in normal conditions or country-wise. Second, the findings might not be generalizable to the developed economies, since the current study sample belongs to a developing economy, which further provides scope for comparative study.
Practical implications
An efficient model for managing the working capital comprising most vital determinants could enhance the firms' valuation and goodwill. Also, this study would be helpful for financial executives, manufacturers, policymakers, investors, researchers and other stakeholders.
Originality/value
This study estimates the industry-wise WCM efficiency of the Indian manufacturing sector and suggests measures to the concerned parties on areas to focus on and provide evidence on the estimated relationships of firm-level and macroeconomic determinants with WCM efficiency.
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Anirudh Tusnial, Satyendra Kumar Sharma, Parth Dhingra and Srikanta Routroy
The paper develops a decision-making model for supplier selection combining quality function deployment (QFD), analytic hierarchy process (AHP) and technique for order preference…
Abstract
Purpose
The paper develops a decision-making model for supplier selection combining quality function deployment (QFD), analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). The efficacy of the model was demonstrated by applying it for supplier selection of lithium ion batteries.
Design/methodology/approach
The proposed methodology involved identifying customer requirements for lithium ion batteries and translating them to requisite technical characteristics using QFD. Further, separate sourcing, safety and sustainability-related supplier parameters were proposed taking into account the manufacturer's point of view. The relative weight of each parameter was then calculated using AHP, and finally, TOPSIS was used to select the best supplier.
Findings
The proposed methodology was applied to six suppliers of lithium ion batteries, and the obtained results were used to select the most and least preferred suppliers.
Practical implications
The obtained results cannot be generalized and are valid to the case environment. However, the proposed approach can be used for any environment related to supplier selection after capturing the corresponding parameters. The proposed approach does not restrict the number of parameters to be considered.
Originality/value
Many researches related to supplier evaluation are reported in literature, but few studies are available related to supplier performance evaluation for lithium ion batteries using QFD, AHP and TOPSIS. The study will provide a guideline for comparing and selecting supplier on the basis of performance in general and its application to lithium ion batteries in specific.
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Swati Panda, Satyendra C. Pandey, Audhesh K. Paswan and Lou E. Pelton
Although multiple forms of governance mechanisms have been studied to address the opportunistic behavior in franchising, research has not shed light on franchise systems operating…
Abstract
Purpose
Although multiple forms of governance mechanisms have been studied to address the opportunistic behavior in franchising, research has not shed light on franchise systems operating in emerging markets despite exponential growth in these markets. To address this gap, this study aims to test the direct effects of different governance mechanisms on franchisee’s opportunism and moderating effects of franchisee’s relationship satisfaction on the relationship between different governance mechanisms and franchisee’s opportunism.
Design/methodology/approach
Survey data from 151 franchise owners were used to test the conceptual model and research hypotheses. The confirmatory factor model and structural equation model were tested by using AMOS.
Findings
Findings suggest that formalization and solidarity in franchising relationships negatively affect franchise opportunism. By contrast, franchisees, who are otherwise satisfied with their franchisor, find centralization and formalization oppressive and, therefore, engage in opportunistic activities.
Research limitations/implications
The study makes important contributions related to franchising in emerging markets. It addresses opportunistic behavior by franchisees in emerging markets and the role played by different governance mechanisms in curbing such behavior. The study has some limitations related to its cross-sectional design and its focus on a single emerging country, among others.
Originality/value
This study is among the first to examine the role of governance mechanisms to address franchisee’s opportunism in an emerging market context. The study’s findings have important theoretical and practical implications for governance design in business-to-business relationships in emerging markets.
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Himanshu Seth, Saurabh Chadha, Namita Ruparel, Puneet Kumar Arora and Satyendra Kumar Sharma
The purpose of this paper is to empirically investigate the relationship between working capital management (WCM) efficiency and exogenous variables of the Indian manufacturing…
Abstract
Purpose
The purpose of this paper is to empirically investigate the relationship between working capital management (WCM) efficiency and exogenous variables of the Indian manufacturing sector along with its sub-industries that are involved in export activities.
Design/methodology/approach
Panel regression (fixed effects) was used on a sample of 563 Indian manufacturing firms involved in export activities, covering a time period from 2008 to 2018.
Findings
Industry-wise results showed a significant relation of leverage, net fixed asset ratio, profitability, asset turnover ratio, total asset growth rate and productivity with cash conversion cycle (CCC).
Research limitations/implications
Firstly, having taken a sample from a developing economy, the results of our study may be generalizable only among developing contexts. Secondly, the time period taken in this study (2008–2018) has witnessed several economic fluctuations such as recession and demonetization which might differ for the firms or countries in normal conditions.
Practical implications
An improved working capital model could advance the firms' performance by reducing the CCC of the firm, thereby creating efficiency in WCM. In addition, the results of this study could be helpful for many stakeholders such as working capital managers, debt holders, investors, financial consultants and others for monitoring the firms.
Originality/value
This study contributes to the existing literature in the relation between WCM efficiency and exogenous variables of the Indian manufacturing firms engaged in the export activities. Moreover, this study is one of the few research studies to investigate this relationship among Indian export firms in different industries, thus filling the gap in similar work done in other countries.
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Srikanta Routroy, Aayush Bhardwaj, Satyendra Kumar Sharma and Bijay Kumar Rout
The purpose of this paper is to evaluate the agility performance level of manufacturing supply chains using Taguchi loss functions (TLFs) and design of experiment (DoE).
Abstract
Purpose
The purpose of this paper is to evaluate the agility performance level of manufacturing supply chains using Taguchi loss functions (TLFs) and design of experiment (DoE).
Design/methodology/approach
The proposed methodology is used for capturing the various agility losses using appropriate TLFs and the aggregated agility loss is calculated at different situations using DoE. The aggregated agility loss is analysed for comparing manufacturing supply chain agility performance.
Findings
The proposed methodology was applied to three Indian auto component supply chains, i.e. X, Y and Z. In total, 27 experiments were carried out using DoE and obtained results show that agility performance level is the highest for X followed by Z, whereas agility performance level is the least for Y.
Research limitations/implications
The proposed methodology is generic in nature and can be applied to a specific environment for comparing performance of different supply chains. The user has to identify the relevant agility enablers and capture the appropriate TLFs for the specific environment in which agility performance level has to be calculated and compared.
Practical implications
The proposed methodology provides an effective approach for evaluating agility performance. It can be used by the supply chain manger to assess the supply chain agility performance level of own company with its competitors. These comparisons will help the manufacturing company to find the areas where it should focus.
Originality/value
Many studies and researches related to implementation and evaluation of agile manufacturing are reported in the literature but very few studies are available for evaluating the supply chain agility performance. This study will definitely provide a guideline for measuring and comparing manufacturing supply chain agility performance in general and Indian automotive supply chain in specific.
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