Abstract

The institutions of world repute, like the United Nations, the World Bank, etc., assess and rank countries or firms based on various criteria pertaining to key areas to evaluate their performance and publish them as Indexes. These ranking tools aid decision-makers in formulating policies and procedures44PAP-Policies and procedures. (PAP) to achieve performance efficiency. In the real world, identifying the closest, most efficient country or firm whose PAP can be emulated with minimal effort is a management dilemma. These Indexes contain only output data, which compounds the problem. This paper uses Data envelopment analysis55DEA- Data envelopment analysis. (DEA) to resolve these issues. Each country or firm under evaluation is referred to as Decision-making unit66DMU-Decision-making unit. (DMU). The novelty of this study emanates from 1) segregating countries or firms into several frontiers using Pure Output Model-based Context-Dependent Data envelopment analysis77POMCDD-Pure output model-based context-dependent data envelopment analysis. (POMCDD), 2) proposing a technique to identify the most attractive nearest DMU that is performing better and is easy to emulate, 3) identifying the “Region of introspection” by using the translation technique of Pillar-Index scores concerning DMU under evaluation to demarcate reference DMU for the concerned Pillar, and 4) suggesting techniques such as “Rapid gain,” “Best yield”, and “Least effort” which are proposed to identify reference DMUs for the concerned Pillar. A case study analysis of the Logistics Performance Index88LPI-Logistics Performance Index. (LPI) is carried out to substantiate the contributions. The countries ranked in the Logistics Performance Index are segregated into several efficient frontiers using the POMCDD technique. The attractiveness of each country is evaluated relative to the frontiers of poorly performing countries. The translation of Pillar-Index scores concerning the country under evaluation is used to identify reference countries for that Pillar. The developed framework is helpful to the policy-makers in analyzing published Indexes.

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