Corporate strategies to manage the business-ecological environment interface have evolved against the backdrop of regulatory pressures and stakeholder activism. Despite its relevance with respect to sustainable development, a well developed theory encompassing all aspects of corporate environmental behaviour, especially incorporating incentive compatible public policy measures, is yet to be developed. This paper is a step in this direction, aiming to assimilate contributions related to different aspects of corporate environmental behaviour, capturing the transition from environmental management to environmental strategy. In the process we identify areas where there is a need for further research. We fi nd that there is plenty of scope in developing more complex models to explain a manager's rationale for adopting sustainable strategies in the backdrop of the policy regime, and in conducting more empirical (both descriptive and quantitative) work to obtain clearer insights into managerial decisions.

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Assessing sustainable development, especially of the mining and minerals sector, is a challenge. This paper is an attempt to address this challenge by developing a methodology using fuzzy logic that encompasses the definitions, fundamentals, economic underpinnings and criteria of sustainable development. The paper starts by distinguishing the newly conceptualized ‘assessment for sustainability’ from the generally practiced ‘sustainability assessment’, framework, clarifying that the former looks at the process in question and lays out the path to be followed to assess sustainability, while the latter is just a static report. It then highlights the inherent limitations of the three traditional sustainability assessment tools and attempts to improve upon these limitations by proposing a model using fuzzy logic, weak sustainability criteria and context‐dependent sustainability indicators to assess sustainable development of the mining and minerals sector. As an illustration, the paper demonstrates how the proposed methodology can be applied to a reference town, where mining is the primary economic activity. The results derived can be used internally for identification of ‘hot spots’ as well as externally for sustainability reporting and stakeholder engagement. Assessment for sustainability also facilitates monitoring, estimating the degree of sustainability and defines a course of action for stakeholders as well as policy‐makers to improve a project's degree of sustainability. Copyright © 2011 John Wiley & Sons, Ltd and ERP Environment.

PurposeThe purpose of this paper is to present a modeling approach for aggregate and disaggregate level models for cluster‐based diffusion of a new technology. The aggregate approach refers to the diffusion modeling of a product at the overall population level, while the disaggregate approach refers to the diffusion process at the individual entity level.Design/methodology/approachThe pattern of diffusion of a new technology in a representative two‐cluster situation is studied. In the aggregate level modeling, a diffusion model is developed in which potential adopters of both clusters learn about the new technology from each other. This is done by a Lotka‐Volterra type of dynamical system of equations. Then, to focus on relatively micro‐level phenomena, such as different propensities of imitation and innovation of firms within a cluster, an agent‐based disaggregate model for cluster‐based diffusion of technology is proposed. In these disaggregate models, the effects of heterogeneity and the inter‐cluster and intra‐cluster distances between the agents are captured.FindingsThe results highlight two major points: first, both aggregate and disaggregate models are in agreement with each other, and second, both of the models exhibit a form similar to the Bass model. Thus, consistent with the general theme of why the Bass model fits without decision variables, it is found that the Bass model, when extended appropriately, can be expected to work well also in the cluster‐based technology diffusion situation.Practical implicationsThis modeling approach can be applied to the modeling of those situations in which heterogeneous industrial units are present in geographical clusters. It can also be applied in the related contexts such as diffusion of practices (e.g. quality certifications) within a multi‐divisional organization or across various networked clusters.Originality/valueFor a homogenous population, the Bass model has been used extensively to predict the sales of newly introduced consumer durables. In comparison, little attention has been given to the modeling of the technology adoption by the industrial units present in disparate groups, called clusters. The major contribution of this paper is to propose a framework for cluster‐based diffusion of technological products, and then to present an analysis of that framework using two different methodologies.

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