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We develop a procedure and the requisite theory for incorporating preference information in a novel way in the efficiency analysis of Decision Making Units. The efficiency of Decision Making Units is defined in the spirit of Data Envelopment Analysis (DEA), complemented with Decision Maker's preference information concerning the desirable structure of inputs and outputs. Our procedure begins by aiding the Decision Maker in searching for the most preferred combination of inputs and outputs of Decision Making Units (for short, Most Preferred Solution) which are efficient in DEA. Then, assuming that the Decision Maker's Most Preferred Solution maximizes his/her underlying (unknown) value function, we approximate the indifference contour of the value function at this point with its possible tangent hyperplanes. Value Efficiency scores are then calculated for each Decision Making Unit comparing the inefficient units to units having the same value as the Most Preferred Solution. The resulting Value Efficiency scores are optimistic approximations of the true scores. The procedure and the resulting efficiency scores are immediately applicable to solving practical problems.efficiency analysis, data envelopment analysis, multiple criteria decision making, value function

Purpose -Consumer values increasingly favor sustainable development in products and services, thereby fostering the need to develop new operational and managerial practices that support sustainability in supply chain management. The purpose of this study is to identify relevant product features related to sustainable development in this context, and use the choice of mobile phone as an example in measuring their importance. Design/methodology/approach -The study used two different methods (qualitative and quantitative) in two phases. First it organized focus-group discussions in order to identify the features of sustainability that affect the choice of a mobile phone. The most significant features served as a starting point for the choice of attributes to be included in the final step, choice-based conjoint analysis (CBC), which assesses respondents' value functions by means of latent class clustering. Between the two major phases it carried out two additional pre-tests in order to reduce the number of attributes. Findings -The results provide fundamental information concerning the relative importance of sustainability features in the selection of a mobile phone. The study identified four different clusters of purchasers: updaters, budgeters, environmentalists, and long-life users. According to the findings, some consumers are willing to pay a premium for sustainability features. The authors discuss the potential implications of the results in the context of supply chain design. Originality/value -The literature on supply chain management tends to see the consumers as a "black box". This paper reports the first results of opening this box by linking the supply chain perspective to consumer choice behavior.

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In this paper, we consider the problem of incorporating additional preference information into Value Efficiency Analysis by using the "price" information of inputs and outputs. This is done to improve the accuracy of the estimation of the Value Efficiency Scores. Value Efficiency developed by Halme et al [1998] is an efficiency concept, which takes into account the decision maker's preferences. Value Efficiency Analysis is based on the assumption that an implicitly known value function reaches its maximum at the Most Preferred Solution on the efficient frontier. The Most Preferred solution is an input-output vector preferred to all other possible input-output vectors. The ultimate goal is to measure a need to improve (radially) the values of inputs and/or outputs to make them equally preferred to the Most Preferred Solution. Because we do not know the value function, we approximate the indifference curves of all possible value functions satisfying certain assumptions by their tangents at the Most Preferred Solution. The resulting cone of the tangents consists of points less or equally preferred tothe Most Preferred Solution. However, in addition to the Most Preferred Solution information about the "prices" of inputs and outputs may be available as well. We show how this information can be incorporated into the analysis and illustrate the approach by an example on the performance of municipal dental units in Finland.