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An Approach to Integrating Environmental Considerations Within Managerial Decision‐Making
Author(s) -
Subramanian Ravi,
Talbot Brian,
Gupta Sudheer
Publication year - 2010
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/j.1530-9290.2010.00243.x
Subject(s) - competitor analysis , remanufacturing , industrial ecology , context (archaeology) , profit (economics) , business , product (mathematics) , production (economics) , production planning , sustainability , computer science , environmental economics , industrial organization , process management , operations research , marketing , economics , manufacturing engineering , engineering , ecology , paleontology , geometry , mathematics , macroeconomics , biology , microeconomics
Summary Recent environmental trends, including (1) an expansion of existing command and control directives, (2) the introduction of market‐based policy instruments, and (3) the adoption of extended producer responsibility, have created a need for new tools to help managerial decision‐making. To address this need, we develop a nonlinear mathematical programming model from a profit‐maximizing firm's perspective, which can be tailored as a decision‐support tool for firms facing environmental goals and constraints. We typify our approach using the specific context of diesel engine manufacturing and remanufacturing. Our model constructs are based on detailed interviews with top managers from two leading competitors in the medium and heavy‐duty diesel engine industry. The approach allows the incorporation of traditional operations‐planning considerations—in particular, capacity, production, and inventory—together with environmental considerations that range from product design through production to product end of life. A current hurdle to implementing such a model is the availability of input data. We therefore highlight the need not only to involve all departments within businesses but also for industrial ecologists and business managers to work together to implement meaningful decision models that are based on accurate and timely data and can have positive economic and environmental impact.