A strategic sustainability justification methodology for organizational decisions: a reverse logistics illustration

Abstract

The concept of sustainability has become increasingly important for organizations and has permeated a number of managerial and organizational 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 using corporate sustainability. An illustrative application of this technique demonstrates how an organization could select between 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 introducing the relationships of reverse logistics to economic, environmental and social sustainability dimensions.

Keywords:

• Sustainability
• Strategic justification
• Reverse logistics

Notes

†The linkage matrix is a preliminary step before the weighting process to determine which metrics the decision-makers may believe to most directly and significantly influence the organizational strategies. Typically an ‘x’ identifier in a QFD-like matrix is used for those linkages. These initial identifiers are valuable to determine whether each strategy has at least one corresponding evaluation metric and if each metric is related to a specific strategy. If a strategy has no metrics, an appropriate metric needs to be determined. If a metric cannot be linked to a strategy, then the metric should be eliminated and organizational resources should not be used to determine values for that metric.

†Organizations may vary the number and level of detail for these metrics. For example, the Social metrics categories represent the highest levels of social impact indicators from Labuschagne et al. (2005). Table 1 provides a broader set of indicators that may be used.

†In this situation we utilize a 0–5 scale for utility values. Scale determination preference is left for the discretion of the analyst or decision-maker. In this set of models we focus on deterministic linear utility relationships, extensibility to non-linear and fuzzy relationships may also be pursued.