Optimal selection and investment-allocation decisions for sustainable supplier development practices

Organization’s sustainability performance is influenced by its suppliers’ sustainability performance. This relationship makes sustainable supplier development a strategic competitive option for a buyer or focal organization. When considering sustainable supplier development practices (SSDPs) adoption, organizations have to balance and consider their limited financial resources and operational constraints. It becomes necessary to both select the best SSDPs set and investment allocation among the selected SSDP set such that the organization can maximize overall sustainability performance level. In this paper, an integrated formal modeling methodology using DEMATEL, the NK model, and multi-objective linear programming model is used support this objective. The proposed methodology is evaluated in a practical sustainable supply chain field study of an equipment manufacturing company in China. Through case study, we found that the interdependency among SSDPs must be considered in SSDPs selection and investment allocation problem. Theoretical, managerial and methodology implications, conclusions, and directions for future research are also presented. © 2023, The Author(s)

An empirical study of an inventory-distribution system

This paper discusses the simulation results of a system consisting of a factory warehouse, and five regional distribution centers, each handling the same four products. The independent variables are demands, leadtimes, cost-rate structures. The basic data for this study has been taken from an appliance manufacturing company. Simulation experiments were conducted for three levels of each of the independent variables. The performance of the systems was measured against five important management criteria: average investment in inventories, average annual inventory carrying cost, average shortage cost per year, average reordering cost per year, and total number of reorders within the system per year. Analysis of variance was used to investigate the respective influence of each of the independent variables on each individual performance measure. The results of our study are new and of special interest, because they highlight the differences between the performance trends resulting from a single-item model and those resulting from a complex system, in terms of variations of the independent variables. This study proves that the trend of any performance-measure provided by a single-item single-location model should never be used to project that very trend of the aggregate performance of a complex inventory-distribution system.

Institutional and Stakeholder Effects on Carbon Mitigation Strategies

The latest IPCC report foreshadows a far gloomier picture of climate change consequences than previously held by demonstrating how avoiding environmental damage requires transforming the world economy at a speed and scale that has “no documented historic precedent.” One of the options to address climate change is adoption of mitigation strategies to reduce carbon emissions on national, sectoral, and corporate levels. This research analyzes mitigation responses by organizations facing institutional and stakeholder pressures while dealing with the risk and opportunities presented by climate change. Our research indicates that different types of institutional pressures—coercive, normative, and mimetic—lead to different and, in certain situations, more active responses from companies. We find that coercive pressures are about equal or more effective than normative or mimetic pressures for adoption of mitigation strategies

Formalizing organizational product deletion through strategic cross-functional evaluation: A Bayesian analysis approach

Product deletion is a strategic organizational decision. Using multiple literature streams, we identify antecedents and relationships of product deletion across four functional areas—marketing, supply chain, finance, and sustainability. Using a field data sample from eight organizations, we apply Bayesian analysis to identify various relationships between product deletion across various functional performance measures. We complete additional simulation analyses using two dependent variable distribution methods (balanced and unbalanced) and validate using parametric logistic regression methodology for robustness checks. The results show predictive relationships exist amongst the functional performance measures and product deletion. High performance across organizational functions results in decreased odds of product deletion; but not as large a margin as expected. If improved product performance is identified across all functions especially cost dimensions, the likelihood of product deletion decreases. Amongst these functions, surprisingly supply chain performance is a better indicator of a product\u27s candidacy for deletion. The integrative findings are exploratory but provide insights for further research development and practical implementation. © 2023 Elsevier B.V