Search

COVID-19 pandemic have provided us an opportunity to retrospect, our traditional practices, operations, supply chain functions and their linkages with firm competitiveness. The recovery to the new normal of operational excellence is the challenging task ahead. The critical a question in post-pandemic recovery can be—How can the firms rebound to operational excellence and achieve the benchmarks of international competitiveness with the current uncertainties in both demand and supply sides? Trigger the thinking on the challenging issue, we had invited the scholarly articles, empirical studies, reviews and perspective papers based on the theme “Rebound to Higher Levels of Operational Excellence and Export competitiveness”. This work presents the editorial summary of the special issue and suggest pathways and possible research and managerial, policy level directives towards the Operational Excellence and Export competitiveness. The study utilizes three specific inputs- (a) Academic resources, (b) Industrial Discourse and (c) International trade and Government initiatives to present the directives for further research interventions. While, this multi-perspective consideration does not represent the comprehensive systematic literature review or the empirical research, but it enables us to explore the challenges, enablers and decision-making approaches for rebounding operational excellence towards export competitiveness.

The COVID-19 outbreak is a worldwide disaster that has disrupted several aspects of human life and its community living. This pandemic has also affected the existing supply chain and the way it was being managed. Therefore, this study’s primary objective is to identify and discuss the significant impact of COVID-19 on the current supply chain, with specific reference to the medical supply chain. This article then recommends the potential solution measures that can reduce the impact of COVID-19 on the existing supply chain during and after the COVID-19 pandemic. In order to do so, we have identified and discussed various significant impacts of COVID-19 on the supply chain. Identifying the impacts helps the policy planner formulate the policies to mitigate these impacts and recover the supply chain at their functional level. Further, this study also suggests possible solution measures that can be adopted to reduce the disruption of the supply chain. These solution measures help management develop the action plan for early recovery from the COVID-19 disruption.

AbstractCompetitive market is forcing big organizations to utilize the untapped potential of Medium Size Manufacturing Enterprises (MSME). In the era of outsourcing, MSMEs are the important links in the supply chain, making it more effective and efficient. The new competition is in terms of reduced cost, improved quality products with higher performance, a wider range of products and better services, all delivered simultaneously to enhance value to the customer. MSMEs play an important role in Indian economy and with the liberalization facing tremendous challenges, but their strength lies in the competitiveness of their products in the world market. Lean manufacturing system (LMS) is characterized by shorter product development and manufacturing lead-time, team based work organizations, low setup/changeover times, multifunctional workers and JIT deliveries from few reliable suppliers. But the concepts of LMS are not well adopted in MSMEs. LMS as a manufacturing strategy can help a MSME to improve its processes and align it to the requirements of its customers. LMS has a set of tools and techniques; the choice is situation specific. MSMEs have the required structure for implementing Lean Manufacturing System. This paper discusses the issues of MSMEs and presents a case to demonstrate the improvements achieved in an Indian mid size auto component’s manufacturing unit after the implementation of LMS.

The faster parts, information and decisions flow through supply chains, the faster they can respond to customer needs and to the demands of the market. In the last decade, interest has been focused on the volatile market conditions and thus, the issue of demand information sharing is paid much attention. The principal objective of this study is to understand the potential values of sharing timely supply information with random demands at retail outlets. This paper proposes a theoretically rigorous framework for the modelling, qualitative analysis and computation of solutions to supply chain network problems within an equilibrium context in the case of non-stationary demands and information associated with supply chains. More specifically, a mathematical model to understand the potential values of sharing timely supply information with random demands is presented in this research. In dynamic supply chain networks, an unforeseen change may occur at any material and gradually influence the material flow at downstream stages with time. Therefore, in this paper, the impact of the change from the time aspect and the expenditure aspect is quantified respectively. By implementing the proposed algorithm, a participant at the downstream stage can figure out how long and how much the change may impact on its own performance just when the change occurs on the upstream stage. The aim of this research is not only to demonstrate the existence of bullwhip effect, but also to quantify it, i.e. to quantify the increase in variability at each stage of the supply chain and derive the market equilibrium conditions. Efficacy of the proposed approach is demonstrated with an illustrative numerical example.

Although information plays a major role in effective functioning of supply chain networks (SCNs), studies that deal specifically with the dynamics of supply chains are few. This problem is relatively new since fast communications and the means to employ it for effective management of supply chains did not exist till recently. In order to provide a vehicle for dynamic modelling and analysis of supply chain operations in vague and uncertain environments, we propose a fuzzy enhanced high level petri net (FEHLPN) model. The proposed model captures the capability of petri nets for graphical and analytical representation of dynamic SCNs with the management of uncertain information provided by fuzzy logic. The dynamics associated with two production planning and control policies are modelled, viz. make-to-stock and assemble-to-order in vague and ambiguous situations in electronic commerce environment. A fuzzy set and fuzzy truth-values are attached to an uncertain fuzzy token to model imprecision and uncertainty. The proposed FEHLPN incorporates essential aspects of rule-based systems, such as conservation of facts, refraction, and closed-world assumption.

Continuous improvement is an imperative for being competitive. The studies show that total quality management (TQM) is an effective tool for continuous improvement. The literature on quality management shows that there is need of a model which can compare the industries on the basis of components of TQM. This paper describes the multi-attribute decision model using the analytic hierarchy process for the assessment of the quality status of industry.

In this paper, a multistage, single-product serial batch-production system is considered in which the demand is deterministic and cost factors, viz. inventory carrying, ordering, set-up, etc., are known. The objective is to minimize the total variable cost. A model is suggested which combines the purchasing policy of the raw materials and the production policy of the finished product. An experimental procedure is carried out to compare the model against a benchmark providing a lower bound for the total variable costs. The model is also compared with an instantaneous production-rate case. The results suggest that the model offers an interesting scope for heuristic procedures. The possible application domain of the model is also discussed.