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.

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Purpose – In the present era of intense competition, industries are adopting lean manufacturing for successful survival. The concept of lean manufacturing is new for Indian process industries. The purpose of this paper is to investigate the status of lean manufacturing in Indian process industries in terms of lean practices, reasons and challenges of implementing lean manufacturing. Design/methodology/approach – A survey was carried out to assess the level of lean implementation in Indian process industries. Statistical tests were conducted to assess the significant lean practices, reasons and challenges of implementing lean in Indian process industries. Findings – It is observed that the level of implementation of lean manufacturing in Indian process industries is still low. Results indicate that Indian process industries those who have implemented lean found lean to be very useful to reduce wastes and to increase quality. Major lean practices being implemented by Indian process industries are primarily those which are related to waste elimination or improvement in quality. Indian process industries found that important challenges to implement lean are to produce in small batches, to arrange for lean experts and to impart training to employees. Research limitations/implications – In the present study, the sample size is small and hence, the findings should be generalized cautiously. Although the study indicates that lean can be very useful if implemented in Indian process industries but further empirical studies are required to quantify performance improvements through adoption of lean. Originality/value – The paper explores status of lean adoption in Indian process industries. Considering the unique characteristics of process industries, the present research would be helpful for making strategies to implement lean in process industry setups.

Traditionally, the lean paradigm has been applied to discrete manufacturing of items that can be easily put together and taken apart. The process industry, on the other hand, transforms raw materials into cohesive units that are basically blended into a final product with parts that cannot be disassembled and then reassembled. The current lean literature provides numerous commendable examples of theory and practices of lean principles in discrete manufacturing. However, its application in process industry is limited. Furthermore, there is no systematic accounting of the lean literature in this sector, which may have contributed to lesser awareness in the industry. This paper provides a state-of-the-art review of lean manufacturing literature with respect to its applications in process industry. It contributes to the classification of literature in a manner which helps to identify strategies suitable for the adoption of lean concepts in process industry. The paper seeks to synthesise the literature with an emphasis on identifying the scope for lean in process industry and associated benefits. The review also presents an analysis of the lean tools and techniques that have been applied or have potential application in the process industry and the challenges to implement lean. We believe that such a comprehensive review will not only facilitate the adoption of lean in process industry but will also provide agenda for further research by exposing voids in the knowledge base.

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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.

Purpose The research on supply chain risk management (SCRM) is visibly on the rise, although its literature still lacks the state of the art that critically analyzes its content. The SCRM literature seems to require studies that utilize risk typology, sources of risk, etc. for reviewing the topic. The purpose of this paper is to bridge the gap by synthesizing the information obtained from 343 articles across 85 journals. This study also presents a critical analysis of the content of SCRM in a structured manner to identify the directions for future research. Design/methodology/approach A systematic literature review (SLR) was devised and adopted, which involved the selection, classification, and evaluation of 343 research articles published over a period of 11 years (2004-2014). The content of extant SCRM literature was critically analyzed and synthesized from the perspective of the risk management process (RMP). Findings The analysis of extant literature shows that there is a marked rise in research in the SCRM area, especially after the year 2005. It was observed that not only risk but also different forms of uncertainties make supply chain (SC) operations difficult to manage. The SCRM actions yielded most benefits when their implementation was at chain or network level and managed strategically. The analysis also reveals that the manufacturing sector is most affected by risks and highly investigated by researchers. Practical implications A complete process for SCRM based on risk stratification, objectives of risk management, and RMP will be a guiding model for firms to manage risks. The research gaps identified and future directions provided here will encourage researchers and managers to devise new methods, tools, and techniques to address the risks in modern SC operations. Originality/value An SLR and risk-based content classification of SCRM literature were performed. To identify, locate, select, and analyze the SCRM literature, a structured and systematic process was adopted with some very rarely used methods such as two levels of search keywords, and strings were formulated to locate the most relevant articles in major academic databases.