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Book part
Publication date: 4 December 2020

Abdelkebir Sahid, Yassine Maleh and Mustapha Belaissaoui

Abstract

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Strategic Information System Agility: From Theory to Practices
Type: Book
ISBN: 978-1-80043-811-8

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Article
Publication date: 14 August 2017

Surya Prakash, Gunjan Soni and Ajay Pal Singh Rathore

The purpose of this paper is to assist a manufacturing firm in designing the closed-loop supply chain network under risks that are affecting its supply quality and logistics…

792

Abstract

Purpose

The purpose of this paper is to assist a manufacturing firm in designing the closed-loop supply chain network under risks that are affecting its supply quality and logistics operations. The modeling approach adopted aims at the embedding supply chain risks in a closed-loop supply chain (CLSC) network design process and suggests optimal supply chain configuration and risk mitigation strategies.

Design/methodology/approach

The method proposes a closed-loop supply chain network and identifies the network parameter and variables required for closing the loop. Mixed-integer-linear-programming-based mathematical modeling approach is used to formulate the research problem. The solutions and test results are obtained from CPLEX solver.

Findings

The outcomes of the proposed model were demonstrated through a case study conducted in an Indian hospital furniture manufacturing firm. The modern supply chain is mapped to make it closed loop, and potential risks in its supply chain are identified. The supply chain network of the firm is redesigned through embedding risk in the modeling process. It was found that companies can be in great profit if they follow closed-loop practices and simultaneously keep a check on risks as well. The cost of making the supply chain risk averse was found to be insignificant.

Practical implications

Although the study was conducted in a practical case situation, the obtained results are not indiscriminate to the other circumstances. However, the approach followed and proposed methodology can be applied to many industries once a firm decides to redesign its supply chain for closing its loop or model under risks.

Originality/value

By using the identified CLSC parameters and applying the proposed network design methodology, a firm can design/redesign their supply chain network to counter the risk and accordingly come up with planned mitigation strategies to achieve a certain degree of robustness.

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Article
Publication date: 13 March 2017

Avinash Panwar, Bimal Nepal, Rakesh Jain, Ajay P.S. Rathore and Andrew Lyons

The purpose of this paper is to investigate the impact of lean practices on performance improvement of process industries in India.

1646

Abstract

Purpose

The purpose of this paper is to investigate the impact of lean practices on performance improvement of process industries in India.

Design/methodology/approach

Based on a survey of Indian process industries, this paper proposes two sets of hypothesis to examine if there is any statistically significant impact of lean practices on certain specific performance metrics. First, the sample is classified into two classes of process industries: the adopters of lean and those who have not yet adopted the lean practices in their manufacturing operations. Then statistical tests are conducted to measure the differences in the level of performance between the two classes of Indian process industries with respect to nine performance measures. The survey results are augmented by two in-depth case studies. Case studies include one from lean adopter firms (a refinery) and another from the firms that have not yet adopted the lean practices (a primary metal manufacturing unit).

Findings

A survey result of 121 Indian process industries shows that adoption of lean practices results in a positive impact on inventory control, waste elimination, cost reduction, productivity, and quality improvement in process industries. On the other hand, based on the sample data on Indian process industries, no statistically significant improvement could be found on the lot size or space utilization between lean adopters and their counterparts.

Practical implications

This research provides guidance to the managers on how adoption of lean practices results in better performance in process industries in several operational areas.

Originality/value

To the knowledge, this study is the first attempt to analyze the impact of lean practices on a set of specific performance metrics in Indian process industry. Although this study focuses on the Indian process industry, the authors believe that findings of the research can inform other practitioners and researchers who are considering implementing lean in process industry sector in other developing countries like India.

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Industrial Management & Data Systems, vol. 117 no. 2
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 21 June 2019

Aniruddha Anil Wagire, A.P.S. Rathore and Rakesh Jain

In recent years, Industry 4.0 has received immense attention from academic community, practitioners and the governments across nations resulting in explosive growth in the…

1852

Abstract

Purpose

In recent years, Industry 4.0 has received immense attention from academic community, practitioners and the governments across nations resulting in explosive growth in the publication of articles, thereby making it imperative to reveal and discern the core research areas and research themes of Industry 4.0 extant literature. The purpose of this paper is to discuss research dynamics and to propose a taxonomy of Industry 4.0 research landscape along with future research directions.

Design/methodology/approach

A data-driven text mining approach, Latent Semantic Analysis (LSA), is used to review and extract knowledge from the large corpus of the 503 abstracts of academic papers published in various journals and conference proceedings. The adopted technique extracts several latent factors that characterise the emerging pattern of research. The cross-loading analysis of high-loaded papers is performed to identify the semantic link between research areas and themes.

Findings

LSA results uncover 13 principal research areas and 100 research themes. The study discovers “smart factory” and “new business model” as dominant research areas. A taxonomy is developed which contains five topical areas of Industry 4.0 field.

Research limitations/implications

The data set developed is based on systematic article refining process which includes the keywords search in selected electronic databases and articles limited to English language only. So, there is a possibility that other related work may not be captured in the data set which may be published in other than examined databases and are in non-English language.

Originality/value

To the best of the authors’ knowledge, this study is the first of its kind that has used the LSA technique to reveal research trends in Industry 4.0 domain. This review will be beneficial to scholars and practitioners to understand the diversity and to draw a roadmap of Industry 4.0 research. The taxonomy and outlined future research agenda could help the practitioners and academicians to position their research work.

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Journal of Manufacturing Technology Management, vol. 31 no. 1
Type: Research Article
ISSN: 1741-038X

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Article
Publication date: 9 September 2021

Syamsul Anwar, Taufik Djatna, Sukardi and Prayoga Suryadarma

Supply chain risks (SCRs) have uncertainty and interdependency characteristics that must be incorporated into the risk assessment stage of the SCR management framework. This study…

305

Abstract

Purpose

Supply chain risks (SCRs) have uncertainty and interdependency characteristics that must be incorporated into the risk assessment stage of the SCR management framework. This study aims to develop SCR networks and determine the major risk drivers that impact the performance of the sago starch agro-industry (SSA).

Design/methodology/approach

The risk and performance variables were collected from the relevant literature and expert consultations. The Bayesian network (BN) approach was used to model the uncertain and interdependent SCRs. A hybrid method was used to develop the BN structure through the expert’s knowledge acquisitions and the learning algorithm application. Sensitivity analyses were performed to examine the significant risk driver and their related paths.

Findings

The analyses of model indicated several significant risk drivers that could affect the performance of the SSA. These SCR including both operational and disruption risks across sourcing, processing and delivery stage.

Research limitations/implications

The implementation of the methodology was only applied to the Indonesian small-medium size sago starch agro-industry. The generalization of findings is limited to industry characteristics. The modelled system is restricted to inbound, processing and outbound logistics with the risk perspective from the industry point of view.

Practical implications

The results of this study assist the related actors of the sago starch agro-industry in recognizing the major risk drivers and their related paths in impacting the performance measures.

Originality/value

This study proposes the use of a hybrid method in developing SCR networks. This study found the significant risk drivers that impact the performance of the sago starch agro-industry.

Details

International Journal of Productivity and Performance Management, vol. 71 no. 6
Type: Research Article
ISSN: 1741-0401

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Article
Publication date: 19 August 2019

Shoufeng Cao, Kim Bryceson and Damian Hine

Supply chain risks (SCRs) do not work in isolation and have impact both on each member of a chain and the performance of the entire supply chain. The purpose of this paper is to…

1197

Abstract

Purpose

Supply chain risks (SCRs) do not work in isolation and have impact both on each member of a chain and the performance of the entire supply chain. The purpose of this paper is to quantitatively assess the impact of dynamic risk propagation within and between integrated firms in global fresh produce supply chains.

Design/methodology/approach

A risk propagation ontology-based Bayesian network (BN) model was developed to measure dynamic SCR propagation. The proposed model was applied to a two-tier Australia-China table grape supply chain (ACTGSC) featured with an upstream Australian integrated grower and exporter and a downstream Chinese integrated importer and online retailer.

Findings

An ontology-based BN can be generated to accurately represent the risk domain of interest using the knowledge and inference capabilities inherent in a risk propagation ontology. In addition, the analyses revealed that supply discontinuity, product inconsistency and/or delivery delay originating in the upstream firm can propagate to increase the downstream firm’s customer value risk and business performance risk.

Research limitations/implications

The work was conducted in an Australian-China table grape supply chain, so results are only product chain-specific in nature. Additionally, only two state values were considered for all nodes in the model, and finally, while the proposed methodology does provide a large-scale risk network map, it may not be appropriate for a large supply chain network as it only follows the process flow of a single supply chain.

Practical implications

This study supports the backward-looking traceability of risk root causes through the ACTGSC and the forward-looking prediction of risk propagation to key risk performance measures.

Social implications

The methodology used in this paper provides an evidence-based decision-making capability as part of a system-wide risk management approach and fosters collaborative SCR management, which can yield numerous societal benefits.

Originality/value

The proposed methodology addresses the challenges in using a knowledge-based approach to develop a BN model, particularly with a large-scale model and integrates risk and performance for a holistic risk propagation assessment. The combination of modelling approaches to address the issue is unique.

Details

Industrial Management & Data Systems, vol. 119 no. 8
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 18 September 2019

Md. Abdullah Al Zubayer, Syd Mithun Ali and Golam Kabir

Risk management has emerged as a critical issue in operating a supply chain effectively in the presence of uncertainties that result from unexpected variations. Assessing and…

530

Abstract

Purpose

Risk management has emerged as a critical issue in operating a supply chain effectively in the presence of uncertainties that result from unexpected variations. Assessing and managing supply chain risks are receiving significant attention from practitioners and academics. At present, the ceramic industry in Bangladesh is growing. Thus, managers in the industry need to properly assess supply chain risks for mitigation purposes. This study aims to identify and analyze various supply chain risks occurring in a ceramic factory in Bangladesh.

Design/methodology/approach

A model is proposed based on a fuzzy technique for order preference using similarity to an ideal solution (fuzzy-TOPSIS) for evaluating supply chain risks. For this, 20 supply chain risk factors were identified through an extensive literature review and while consulting with experts from the ceramic factories. Fuzzy-TOPSIS contributed to the analysis and assessment of those risks.

Findings

The results of this research indicate that among the identified 20 supply chain risks, lack of operational quality, lack of material quality and damage to inventory were the major risks for the ceramic sector in Bangladesh.

Research limitations/implications

The impact of supply chain risks was not shown in this study and the risks were considered independent. Therefore, research can be continued to address these two factors.

Practical implications

The outcome of this research is expected to assist industrial managers and practitioners in the ceramic sector in taking proactive action to minimize supply chain risks. A sensitivity analysis was performed to determine the relative stability of the risks.

Originality/value

This study uses survey data to analyze and evaluate the major supply chain risks related to the ceramic sector. An original methodology is provided for identifying and evaluating the major supply chain risks in the ceramic sector of Bangladesh.

Available. Open Access. Open Access
Book part
Publication date: 18 July 2022

Fabian Akkerman, Eduardo Lalla-Ruiz, Martijn Mes and Taco Spitters

Cross-docking is a supply chain distribution and logistics strategy for which less-than-truckload shipments are consolidated into full-truckload shipments. Goods are stored up to a

Abstract

Cross-docking is a supply chain distribution and logistics strategy for which less-than-truckload shipments are consolidated into full-truckload shipments. Goods are stored up to a maximum of 24 hours in a cross-docking terminal. In this chapter, we build on the literature review by Ladier and Alpan (2016), who reviewed cross-docking research and conducted interviews with cross-docking managers to find research gaps and provide recommendations for future research. We conduct a systematic literature review, following the framework by Ladier and Alpan (2016), on cross-docking literature from 2015 up to 2020. We focus on papers that consider the intersection of research and industry, e.g., case studies or studies presenting real-world data. We investigate whether the research has changed according to the recommendations of Ladier and Alpan (2016). Additionally, we examine the adoption of Industry 4.0 practices in cross-docking research, e.g., related to features of the physical internet, the Internet of Things and cyber-physical systems in cross-docking methodologies or case studies. We conclude that only small adaptations have been done based on the recommendations of Ladier and Alpan (2016), but we see growing attention for Industry 4.0 concepts in cross-docking, especially for physical internet hubs.

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Article
Publication date: 6 February 2017

Surya Prakash, Gunjan Soni, Ajay Pal Singh Rathore and Shubhender Singh

The purpose of this paper is to present a methodology to analyze the risks present in perishable food supply chain and to determine the most effective risk mitigation strategies…

5310

Abstract

Purpose

The purpose of this paper is to present a methodology to analyze the risks present in perishable food supply chain and to determine the most effective risk mitigation strategies. It is achieved by understanding the dynamics between various risks in perishable food supply chain and modeling them using interpretive structural modeling (ISM).

Design/methodology/approach

Four categories and 17 types of risk are established from literature and conducting brainstorming sessions with managers/engineers in Indian dairy firms. A methodology is proposed using ISM, risk priority number and risk mitigation number to prioritize risk mitigation strategy decisions for the dairy industry.

Findings

For a perishable food supply chain, risk positioned at lower levels (levels 1 or 2) in the hierarchy should be targeted first, while formulating mitigation strategies. To investigate further, risk- enabling factors which are identified for an Indian dairy firm for these levels 1 and 2 risks and mitigation strategy prioritization show that supplier side risks are more dominant followed by market risks and process risks.

Research limitations/implications

This proposed methodology has not been statistically validated or empirically tested, and factors taken are in the Indian context, but the authors believe that the study is highly relevant to other markets as well because the ISM-based analysis is for generic perishable food supply chain environment.

Practical implications

This study provides a useful approach to managers/decision makers to identify, analyze and prioritize risk in the supply chain. It also provides insights into the mutual relationships of supply chain risks which would help them to focus on the effective risk mitigation strategies formulation. The study provides the insights to benchmark and risk management in the dairy industry environment with priority considerations.

Originality/value

This paper provides an integrated approach to identifying, quantify, analyze, evaluate and mitigate the risks of perishable food (in the dairy environment) in the Indian context.

Details

Benchmarking: An International Journal, vol. 24 no. 1
Type: Research Article
ISSN: 1463-5771

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Book part
Publication date: 30 September 2022

Gourav Roy and Varsha Jain

The last few years have witnessed massive artificial intelligence (AI) and gaming adoption that has navigated the emerging markets. Moreover, according to the WOG summit (world…

Abstract

The last few years have witnessed massive artificial intelligence (AI) and gaming adoption that has navigated the emerging markets. Moreover, according to the WOG summit (world government summit report, by Nielsen) 2020 reports, AI with gaming mechanisms are expected to enrich marketing services in the coming future in the emerging markets. Countries such as India, China and South Korea contribute significantly to this area, and recent forecasting allows the need to increase in emerging markets. Similarly, these countries have a maximum number of youth gamers and AI-driven technology adopters. The adoption of AI-driven technologies and amplification of gamification in marketing services are new phenomena. Moreover, gaming and AI dynamics are relatively new in emerging countries and need greater attention. Thus, this book chapter proposes a dyad model that would explain users' and companies' perspectives to understand the role of AI and gamification for the emerging markets. The chapter will explain how AI-driven gamification helps the users of emerging markets. The chapter will also illustrate how companies in emerging markets use AI for gamification. Therefore, the dyad model would also comprehend the gap, opportunities and challenges in this area and the subsequent strategies to help all the stakeholders.

Details

Management and Information Technology in the Digital Era
Type: Book
ISBN: 978-1-80382-296-9

Keywords

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