Measuring input-specific productivity change based on the principle of least action

Abstract

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Input‐Specific Dynamic Productivity Change: Measurement and Application to European Dairy Manufacturing Firms

“…(). Yet another approach to measuring an input‐specific Luenberger indicator is based on the Principle of Least Action that is related to the notion of least distance and the determination of closest strongly efficient targets (Aparicio et al ., ).…”

Graph productivity change measure using the least distance to the pareto-efficient frontier in data envelopment analysis

“…Therefore, this measure does not reach the strongly efficient frontier ∂ s T CRS ð Þ and it does not calculate the least distance to this frontier. Directional distance function for time t can be calculated by the following DEA 3 The only related paper within this line is Aparicio et al [9]. However, this paper considers a specific case of input orientation and develops an approach for the measurement of input-specific productivity change.…”

“…Hence, it was not developed for the general framework of the full input-output space, as the current paper does. Also, the paper by Aparicio et al [9] develops a model that only works under the assumption of dealing with only one output. optimization program:…”

“…Hence, Tone's [55] approach by incorporating a computation solution for units outside technology, avoids the problem of infeasibilities in the productivity change measure. 5 Moreover, models (8) and (9) resort to the strongly efficient frontier as any slacks-based measure does (see [46,54]). However, a problem appears when using models (10) and (11) for which the subset of the corresponding frontier used to calculate the distance between the assessed unit and the technology does not always match the strongly efficient frontier.…”

“…To determine that, one can compute the directional distance function of Chambers et al [24], model (5), resorting, for example, to the reference vector g ¼ 1 m ; 1 s ð Þ , where 1 p is a vector of p ones. In particular, D k x h 0 ; y h 0 ; 9 In this way, from the optimal value of ( 17) we can derive the following additive-type distance function:…”