Search results

In the present scenario of global competition and economic recession, most of the organizations are facing tough challenge to survive in the market because of shortening product life cycle and reducing profit margin. Customers are seeking better design, production and delivery, which have made firms to concentrate on flexibility in supply chains. Therefore, the purpose of this study is to identify major factors and develop a suitable framework for flexibility in supply chains.

Based on literature review, about 14 factors have been identified. To develop relationship among these factors, a team of five experts from industry and academia was formed. Based on inputs from experts, different relationships are developed among factors to form structural self-interaction matrix (SSIM). Based on this matrix, a flexibility framework is developed by interpretive structural modelling approach.

Top management commitment, strategy development for flexible SC, application of advance technology and IT tools, information sharing in SC members, trust development among supply chain members have emerged as major driving factors. Logistics and warehouse management, suppliers flexibility, distribution flexibility and manufacturing flexibility have emerged as dependent factors.

Framework developed in this study is based on interpretive structural modelling. This framework can be further validated with some case analysis and empirical findings.

Findings of the study can be useful for industry professionals to develop strategies for flexible supply chains. It will help them in taking new initiatives for making supply chains more responsive and proactive for customers demand.

The study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the graph theory matrix approach (GTMA) is applied.

The study presents various barriers to adopt BDA for the SMOs post-COVID-19 pandemic. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the GTMA is applied.

The study identifies barriers to investment in BDA implementation. It categorizes the barriers based on factor analysis and computes the intensity for each category of a barrier for BDA investment for SMOs. It is observed that the organizational barriers have the highest intensity whereas the human barriers have the smallest intensity.

This study may help organizations to take strategic decisions for investing in BDA applications for achieving one of the sustainable development goals. Organizations should prioritize their efforts first to counter the barriers under the category of organizational barriers followed by barriers in data management and human barriers.

The novelty of this paper is that barriers to BDA investment for SMOs in the context of Indian manufacturing organizations have been analyzed. The findings of the study will assist the professionals and practitioners in formulating policies based on the actual nature and intensity of the barriers.

Logistics companies are compelled to improve their efficiency and the environmental performance by introducing the green concept in their operations. The main purpose of the paper is to have continuous monitoring and tracking of logistics operations to enhance the green performance.

This research uses a case study approach. It illustrates a monitoring system to digitize the logistics activities by sending real-time GPS data to the server and capture the surrounding pictures with the help of the internet of things (IoTs) based camera. Data generated through digitization is mathematically analyzed for ensuring a green logistic system. The alerts due to the halts, help in keeping a check on fuel consumption, carbon emissions and security of logistics. Performance indicators such as carbon emissions and the value of travel time saving (VTTS) are selected for the study.

The findings of the study show that the actual travel time and distances are higher than the estimated travel time and distances. It also reveals that actual travel routes with diversions involve a considerably higher amount of carbon emissions during all sample travels. The results indicate a considerable saving in terms of carbon emissions, time and cost savings by effective practices of Green Logistics in Monitoring system (MSGL). These findings can help the top management of logistics companies in formulating effective strategies for technology applications in logistic operations to ensure green performance.

The study has been carried out under certain set of conditions, which may vary depending upon the organizations. Also certain more environmental dimensions for performance monitoring can be used as a future scope of study. Further studies also need to be carried out to widen the scope of the MSGL model at a global level rather than only at local level.

Any organization which deploys transportation as part of their activity can use this MSGL model and then do the mathematical analysis to reduce the CO₂ emissions, reduce the time and extra cost. The value of this study lies in the fact that government is trying different methods and models to reduce pollution. This MSGL should be made compulsory by the government as a part of their policies for environment of the country.

The purpose of this study is to identify factors that are important for logistics organizations from the perspective of manpower readiness for digitization of logistics operations. The study also prioritizes the identified factors and also evaluates the readiness index of manpower for the digitalization of logistics processes.

The factors for manpower readiness are identified through literature review and analysis of a case study. Three major categories of factors are identified. These are organizational, behavioural and technological factors. Under these three major categories of factors, 18 sub-factors are identified. Thereafter, with experts' inputs, the factors are prioritized using Fuzzy analytic hierarchy process (AHP). Further, a case illustration of an Indian logistics company has been taken to understand the current processes, technical capabilities, manpower skills and organization culture. After the case analysis and expert inputs, the manpower readiness index has been evaluated by using graph theory matrix approach (GTMA).

The prioritization of manpower readiness factors has been done using Fuzzy AHP. Organizational factors are found to be the most important factors which require quick attention. Sub-factors that are most important for building competencies in the logistics sector are providing the right training on functional skill development (0.129), top management support and commitment for digitalization (0.117), and organizational culture for process digitalization (0.114), etc. Finally, framework for evaluation of manpower readiness index for logistics operations in the digital age has been illustrated for a case company.

Indian logistics companies can benchmark their readiness index with respect to the best in the industry. Based on the readiness index, logistics companies can analyse their position, gaps from best and worst and can also identify potential areas for improvement.

The novelty of the study lies in the development of a framework for manpower readiness for digitalization in the logistics sector. In literature, this field is very less researched and provides the scope for developing strategies for improving manpower competencies for Industry 4.0. Logistics companies can improve their performance by making their manpower ready based on results obtained for readiness index.

The purpose of this study is to understand the different types of risks affecting the demand for the automotive sector in India. The study is further trying to illustrate an approach for analyzing the relative intensities of these risks in the present uncertain business environment.

Risk on the overall demand is assessed by a combined Bayesian – multi-criteria decision-making approach. Data related to the different factors, affecting their product demand is collected from major automobile firms. Then, weights for these factors are evaluated by applying the analytic hierarchy process approach. Further, these weights are used in the Bayesian analysis network to evaluate the risk intensity for different subgroups, namely, political, economic, social, technological and environmental.

From the literature and experts’ opinion, total 16 risk factors have been finalized and these are further grouped into 5 categories i.e. political, economic, social, technological and environmental. It is observed that the demand for organizations functioning in the automotive sector is more vulnerable to economic risk as compared to other risks considered in the study.

Managers and decision makers of associated organizations can use the proposed framework to assess the demand risks so as to pre-evaluate their demand corresponding to future changes. Factors can be added or removed and importance could be assigned to different risk factors according to the prevailing business environment for an organization or sector. This will also help the organizations to conduct a more effective risk management in an uncertain business environment.

The study will help in better understanding of the various demand risks prevalent in the Indian auto sector. The methodology used, provides a novel approach for assessing the macroeconomic demand risks and can be used by the firms working in the automotive sector. The proposed methodology could be used for assessing supply chain risk or any other business initiative risk. The suggested approach will help managers in devising flexible management techniques so as to mitigate the risk.

The study aims to identify the central paradoxical tensions existing in developing resilience in organisations. The main thrust of this study is to develop a thorough understanding of diverse conflicting tensions in building resilience and develop the possible strategies to surmount these tensions.

Using the case study approach, the study applied theory-elaboration strategy as this study is based on well-established literature from both digitalisation and resilience. The study uses the paradox theory lens in a case study to reconcile both theories with contextual idiosyncrasies.

The paradox theory lens provides perspectives to understand tensions during resilience development and the role of digital transformation in this process. It assesses the potential solutions for surmounting tensions in resilient operations. The mapping of workable solutions with different paradoxes and propositions has been proposed for future empirical research.

The study suggests that practitioners should not consider resilience and sustainability as mutually exclusive; instead, managers must embrace ongoing tensions to bring solutions to address these two essential organisational priorities.

To the best of the authors' knowledge, this is the first empirical study that applies paradox theory to understand how an organisation can build resilience while confronting several paradoxes. The study findings support that resilience practices can move in tandem with environmental sustainability goals rather than being usually mutually exclusive.

The paper aims to incorporate the relationship of reverse logistics into the economic, environmental, and social sustainability, known as triple bottom line and developed a framework for reverse logistics performance evaluation.

The performance measures, based on triple bottom line approach, were selected, and fuzzy analytical hierarchy process and extent analysis approach was applied for estimating the weights, global weights of performance measures and hence, the reverse logistics performance index. Reverse logistics performance of three electronic companies were evaluated and compared for the demonstration of the methodology.

The results show that economic performance has highest performance index followed by environmental performance and social performance. “Recapturing value” and “return on investment” from economic, “minimum energy consumption” and “optimum use of raw material” from environmental and “community complaints” and “customer health and safety” from social perspective have higher performance indexes. Over all, “reduced packaging”, “use of recycled material” and “employee benefits” show very poor performance indexes.

The study will provide useful guidance to the academicians and practitioners for evaluating, improving and benchmarking the reverse logistics performance.

The analysis adds to the very few studies on triple bottom line aspects of reverse logistics and its performance evaluation. Also, fuzzy analytical hierarchy process and extent analysis is used first time being an efficient tool to tackle the fuzziness of the data involved in performance evaluation.

In the present context of a health-concious society, management of pharmaceutical supply chains has become more complex because it involves the life-saving interest of human being and requires the participation of different stakeholders such as pharmaceutical manufacturers, wholesalers, distributors, customers, information service providers and regulatory agencies. Limited research is available in the area of pharmaceutical supply chains. This paper aims to find the gaps in the literature by reviewing research papers on different strategic issues of supply chain management in the pharmaceutical sector.

In total, 136 research papers, mainly from refereed international journals, were reviewed to identify the issues of supply chain management (SCM) in the pharmaceutical supply chain. On the basis of a review, gaps are identified and research agenda is proposed.

It is observed from review that the pharmaceutical sector is not widely researched in developing countries because of many complexities in this supply chain. The share of pharmaceutical firms in the global market is also not very significant. Based on an extensive review of pharmaceutical supply chains, research gaps are identified in different areas such as inventory management, new product development, process development, capacity planning, network design, plant design, pipeline and development management, outsourcing logistics activities, reverse logistics, Lean manufacturing, green SCM and implementation of E-business processes and performance management. These strategic issues have been further classified into three broad categories, i.e. resources, processes and performance.

This paper explores major strategic areas of pharmaceutical supply chains for research. Findings of the paper will be highly useful for researchers to decide direction of future research.

After globalization of markets, product quality and satisfaction of customers have become essential for sustainable growth of small to medium‐sized enterprises (SMEs). The purpose of this paper is to identify and develop the structural relationship among different factors for success of total quality management (TQM) in SMEs.

In this research a total of 11 factors have been identified for successful implementation of TQM. Interpretive structural modelling (ISM) approach has been applied to develop a structural relationship among these factors.

Top management commitment, employees' training and empowerment, supplier development and coordination between departments are found to be the major driving factors for implementing TQM, whereas process management, product/service design, product quality and customer satisfaction are observed as dependent variables.

The paper demonstrates that management of SMEs needs to address driving variables more carefully for successful implementation of TQM.