The concept of sustainability has become increasingly important for organisations and has permeated a number of
managerial and organisational decisions. Sustainability, as defined by its 'triple-bottom line' factors of economic,
environmental and social dimensions, is the underlying framework we use to develop and apply a strategic
justification tool for project evaluation with sustainability implications. An activity based management
methodological framework is used as a vehicle to frame decisions around using corporate sustainability. An
illustrative application of this technique investigates how an organisation would select from one of two competing
reverse logistics providers. This process requires that we introduce issues relevant to three major sustainability
factors (and their sub factors) and how they are influenced by a reverse logistics provider decision. The dual
contribution of this paper includes investigating the design and development of the strategic sustainability evaluation
framework and the linkage of reverse logistics to economic, environmental and social sustainability dimensions.
Interpretive structural modeling (ISM) has been applied to a number of organizational decision problems. It is a
technique that is helpful to managers in organizing the relationships among a series of factors that may influence their
decision. The decision support technique has a long history dating back to the late 1960's and early 1970's. Yet, its
application and investigation by researchers to a variety of topical areas has not occurred until very recently. This lack
of application is especially true for investigation into topics related to environmentally conscious manufacturing (ECM).
We find that the barriers to this organizational practice can be further investigated and analyzed with ISM. This paper
seeks to provide an illustrative example of this procedure. More complete evaluation and implementation of this
technique is recommended for its validation.
Green house gas (GHG) emissions have been tied to global climate change. One popular policy instrument that seems to have gained credibility with explicit mention of its application in the Kyoto Protocol is the use of permit trading and cap-and-trade mechanisms. Organizations functioning within this environment will need to manage their resources appropriately to remain competitive. Organizations will either have the opportunity to purchase emissions credits (offsets) from a market trading scheme or seek to reduce their emissions through different measures. Some measures may include investment in new technologies that will reduce their reliance on GHG emitting practices. In many countries, large organizations and institutions generate their own power to operate their facilities. Much of this power is generated (or bought) from GHG producing technology. Specific renewable energy sources such as wind and solar photovoltaic technology may become more feasible alternatives available to a large percentage of these organizations if they are able to take advantage and incorporate the market for GHG emissions trading in their analyses. To help organizations evaluate investment in these renewable energy technologies we introduce a real options based model that will take into consideration uncertainties associated with the technology and those associated with the GHG trading market. The real options analysis will consider both the stochastic (uncertainty) nature of the exercise price of the technology and the stochastic nature of the market trading price of the GHG emissions.
This paper provides an efficiency analysis of practices in Solid Waste Management of manufacturing companies in Wales. We apply data envelopment analysis (DEA) to a data set compiled during the National Waste Survey Wales 2003. We explore the relative performance of small and medium sized manufacturing enterprises (SME; 10-250 employees) in Wales. We determine the technical and scale environmental and economic efficiencies of these organizations. Our evaluation focuses on empirical data collected from companies in a wide diversity of
manufacturing industries throughout Wales. We find significant differences in industry and size efficiencies. We also find correlations that exist among environmental and economic efficiencies. These variations show that improvements can be made using benchmarks from similar and different size industries. Further pursuit of an investigation of possible reasons for these differences is recommended.
Globalization results in both pressure and drivers for Chinese enterprise to improve their environmental performance. As a developing country, China has to balance economic and environmental performance. Green supply chain management (GSCM) is emerging to be an important approach for Chinese enterprises to improve performance,
possibly on both these dimensions. Using empirical results from 89 respondents on GSCM practice in Chinese manufacturing enterprises, we examine the relationships between pressures, practice and performance. The results will look at multiple dimensions of GSCM practice and performance, as well as various pressures they face.
Discussion of the results will include practical implications for organizations, not only in China, but internationally who face similar pressures and seek to implement similar programs.
Environmental management, to be effective, requires performance evaluation and process improvement. This is especially the case in fossil-fueled electricity generating plants. Although eco-efficient management of these types of organizations are critical to local, national and global environmental issues, few studies have focused on performance measurement and eco-efficiency improvements in this industry. This study evaluates the eco-efficiencies of the top 100 major U.S. fossil-fueled electricity generating plants from
1998 data. Using a multi-criteria non-parametric productivity model (data envelopment analysis) efficiency scores are determined. These efficiency scores are treated by a clustering method in identifying
benchmarks for improving poorly performing plants. Efficiency measures are based on three resource input measures including boiler generating capacity, total fuel heat used, and total generator capacity, and four output measures including actual energy generated, SO2, NOx, and CO2 emissions. The purpose of this paper is two-fold, to introduce the methodology’s application to eco-efficiency performance measurement and show some characteristics of the benchmarked plants and groups.
The service industry and the manufacturing industry are interlinked in a supply chain situation. Part of the effectiveness of some manufacturing industry environmental performance based on remanufacturing and recycling is dependent on service industry decisions. In the information technology arena, personal computers (PCs) are the hard equipment of the service industry. The end-of-life decisions made by the service industry, and in this case the banking industry will have implications for the amount of systems within the waste or reverse logistics stream for manufacturers. Looking at some of the issues (and presenting a model for evaluation) related to decision making concerning end-of-life disposition for PCs is something this paper investigates. The analytical hierarchy process (AHP) is applied in this circumstance. The development of the model, its application, and results, provide the basis for much of the discussion in this paper.
Organizations realize that a strong supporting logistics or electronic logistics (e-logistics) function is important from both commercial and consumer perspectives. The implications of e-logistics models and practices cover the forward and reverse logistics functions of organizations. They also have direct and profound impact on the natural environment. This paper will focus on a discussion of forward and reverse e-logistics and their relationship to the natural environment. After discussion of the many pertinent issues in these areas, directions of practice and implications for study and research are then described.
Clean manufacturing, pollution reduction, and waste minimization, have been in the limelight for the past decade as the best way to achieve industrial environmental. This paper reports the findings of an exploratory survey conducted of seven companies in the Central Massachusetts Region that have made the decision to approach the Surface Cleaning Lab (SCL or SCLab) of the Toxics Use Reduction Institute (TURI) seeking a substititte for toxic chemicals they currently use. We examine the factors associated with the decision to approach the SCL, and the factors associated with the decision to implement the recommendation of the SCL. The strongest factors in their final decision to seek a substitute are regulatory in nature, as reported by the six companies. Only one of the seven companies reports implementation of the recommendations made by the SCLab. The main determining factors for not implementing the recommendation were those associated with the quality of the substitute recommended, and employee satisfaction. This is one of the few studies that investigates motivational factors for substitutability for environmentally sensitive purposes.
Ecoefficiency is critical for organizations that seek to be both environmentally conscious and profitable. Ecoefficiency supports and aids in determining "win-win" strategies for organizations. Studying and managing organizations from this perspective requires an evaluation of ecoefficiency. To aid researchers and managers develop measures for ecoefficiency we review the use of data envelopment analysis (DEA) for this purpose. DEA theory and application have gone through major growth. Yet, its use as a tool for environmental performance evaluation has been limited. In this paper we provide a number of DEA models and some extensions and how they can be utilized from both the practitioner and researcher perspective. An illustrative example from published data helps to gain insight into the various models, their capabilities and limitations.
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