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The purpose of this paper is to examine (1) how the recovery speed using promotional investment and (2) distributed production using additive manufacturing (AM) improve the resilience of the supply chain to manage any disruptions in the diffusion of green products.

The environmental performance, service level performance and economic performance are the measures of interest. These measures are studied through the integration of inventory and production planning (I&PP) of the reverse logistics system and consumer behavior using Bass (1969) model of diffusion of innovation under the paradigm of Industry 4.0 architecture. The Taguchi experimental design framework was used for the simulation analysis.

The adoption patterns based on the Bass model in conjunction with recovery speed and production on AM during the disruption period suggest that there exist tradeoff decisions between various combinations of information-sharing and I&PP policies.

The extensive sensitivity analyses provide real-time support for managerial decisions. Besides the potentials of Industry 4.0 capabilities, the present research suggests paying close attention to the recovery speed in conjunction with the inventory management system.

The integration of consumers' behavior (Bass model) to digital technologies is an additional contribution of the present research toward sustainability issues from the social perspective.

Previous research studies have discussed resilience to manage the ripple effect. However, none of them have addressed the changing scope of resilience to manage the ripple effect caused by the disruption in the diffusion of green products in a reverse logistics setup.

Short product life cycle and/or mass customization necessitate reconfiguration of operational enablers of supply chain (SC) from time to time in order to harness high levels of performance. The purpose of this paper is to identify the key operational enablers under stochastic environment on which practitioner should focus while reconfiguring a SC network.

The paper used interpretive structural modeling (ISM) approach that presents a hierarchy-based model and the mutual relationships among the enablers. The contextual relationship needed for developing structural self-interaction matrix (SSIM) among various enablers is realized by conducting experiments through simulation of a hypothetical SC network.

The research identifies various operational enablers having a high driving power towards assumed performance measures. In this regard, these enablers require maximum attention and of strategic importance while reconfiguring SC.

ISM provides a useful tool to the SC managers to strategically adopt and focus on the key enablers which have comparatively greater potential in enhancing the SC performance under given operational settings.

The present research realizes the importance of SC flexibility under the premise of reconfiguration of the operational units in order to harness high value of SC performance. Given the resulting digraph through ISM, the decision maker can focus the key enablers for effective reconfiguration. The study is one of the first efforts that develop contextual relations among operational enablers for SSIM matrix through integration of discrete event simulation to ISM.

The purpose of this paper is to analyze the case of a manufacturing firm situated in an industrial city of India, focusing on supply chain management issues of the concerned organization from two operational perspectives: supply side (or the procurement side) and the distribution side of the system.

The authors first considered the outsourcing decision‐making problem in a static environment using analytical expression by means of a variable fraction of demand. Next, the authors extended the scope of this problem by considering outsourcing decisions in a dynamic environment, using the sequential decision‐making approach with various operational and inventory factors. Finally, the authors carried out the study of the distribution side of the supply chain of industry using discrete event simulation.

It was observed that, in the case study organization, because of the rather unstructured approach in dealing with the outsourcing perspective, the authors suggested the adoption of a more scientific approach in computation of fraction of demand to be outsourced. Further, since the distribution network typically experienced high inventory levels throughout the supply chain, it was decided upfront to optimize this performance measure.

The primary objectives of this exercise are to: address the operational concerns of a real‐life manufacturing environment; apply the theoretical models in a realistic environment, and compare the results of theory with practice; and provide actionable managerial recommendations.

As global markets become more customer oriented, rapid response rates are now often among the most important metrics in business. To achieve the required agility, many companies are forced to take decisions of whether to vertically integrate a value chain or to outsource some of its operations. The purpose of this paper is to develop a sequential decision modeling process to enable determination of optimal outsourcing policy decisions with respect to the variables such as warehouse inventory, in‐house manufacturing capacity and the ordering cost to the outsource supplier.

In this paper, a discrete dynamic programming‐based modeling framework is developed for analyzing outsourcing policies for supply chain management problems. Specifically, the assumed situation entails a dynamic decision between in‐house production vis‐à‐vis outsourcing, which is contingent upon several factors such as demand during the period under consideration, available inventory, available production capacity of the firm, ordering cost to the outsourced supplier and the fixed capital cost of machine capacity enhancement.

The framework enables the determination of a time‐based outsourcing policy, which is a prescription regarding: the optimum quantities to be produced in‐house vs those to be outsourced, and the level of capacity to be set in each period.

The problem investigates useful managerial decisions that are relevant to a real life dynamic situation within a manufacturing industry when effecting outsourcing decisions.

The aim of this study is to highlight the value of the success rate performance of a surgery while planning patient flow within a supply chain of a health care organization/hospital.

The paper has considered one of the common surgeries, cataract, and the complications that subsequently result from this surgery. The study employs interpretive structural modeling (ISM) approach to draw a roadmap to study various complications causing cataract that subsequently help in planning and coordination of patient flow.

The study finds that there is a hierarchy of causes and certain complications, the persistence of which gives a higher success rate performance in cataract surgery as compared to others.

The paper provides leverage to the decision maker while organizing the patient flow depending upon the information of hierarchy of complication of a disease, and accordingly ensures the availability of resources to the patient.

The study is of value in identifying the degree of complications from cataract surgery. Given the degree of complication, the patient logistics can be planned myopically in a health care organization which largely depends upon the degree of success rate. The paper attempts to suggest that the hierarchy obtained through ISM can be implemented in the modules of an enterprise resource planning (ERP) set up.

The modern business community understands the importance of long-term satisfaction of consumer. Enabling the consumer to return products is a significant part of the equation. The purpose of this paper is to analyze the sustainable boundaries in terms of their relationship toward greening a supply chain.

Using interpretive structural modeling the research presents a hierarchy-based model to realize the driving power and dependence of sustainable boundary enablers.

The research shows that there exists a group of enablers having a high driving power and low dependence requiring maximum attention and of strategic importance while another group consists of those variables which have high dependence and are the resultant actions.

This classification provides a useful tool to supply chain managers to differentiate between independent and dependent variables and their mutual relationships which would help them to focus while making strategic, tactical or operational decisions as and when required while designing a green supply chain.

This research assumes importance in context of greening a supply chain when globally enterprises are getting a lot of pressure from consumers as well as the regulatory measures from the government. Sustainability demands that the resources be used in lean manner through information coordination with all partners in a supply chain. The findings of this study would help delineate those variables that should to be necessarily considered to design a sustainable supply chain.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting‐edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Frequent change is an endemic feature within today's increasingly complex world. Technology evolves relentlessly and in many product categories trends come and go to an extent that the latest must‐haves soon become unfashionable. Within such a climate, sustaining competitive advantage is a tough assignment for any organization. Success therefore demands the ability to respond swiftly to these ever‐changing needs. A high degree of flexibility is essential and that places supply chain management firmly under the microscope. For any supply chain to function smoothly, it is fundamental that effective collaboration occurs across the network of different partners involved. Get the dynamics wrong and poor resource utilization, inventory pile‐ups or shortages and order backlogs are unwelcome consequences. Waste becomes an issue and the bottom line takes a hit.

The paper provides strategic insights and practical thinking that have influenced some of the world's leading organizations.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy‐to digest format.

The long-term sustainability of microfinancing institutions (MFIs) is essential for poverty reduction. This study aims to empirically evaluate whether contemporary microfinance economics supports the institutionalization of MFIs, which are crucial for the socioeconomic development of marginalized communities.

This research examines the flow of funds from wealthy economic areas (high-income countries, richer urban areas and capital-rich corporations) to poorer regions (low-income countries, poorer rural areas, female borrowers and financially constrained microenterprises) as a proxy for microfinance economics. Financial sustainability and institutionalization are assessed through return on assets and operational self-sufficiency. The study also considers credit risk as a key independent variable. Using panel data analysis of 333 MFIs from the USA and India, covering 2008–2018, sourced from the Microfinance Information Exchange data set on the World Bank website, this paper analyzes these dynamics.

Results show that credit risks negatively affect the financial sustainability of MFIs in both developed and developing countries. Contrary to expectations, the development status of a nation positively moderates the impact of credit risks on financial sustainability. In developing countries, intra-nation investments do not yield additional returns for MFIs or interact with credit risks. However, the economics of microfinance support the institutionalization of MFIs in these regions.

This study provides valuable empirical evidence on the relationship between microfinance economics and institutionalization, addressing a critical need in the microfinancing sector.