Non‐parametric computational measures for the analysis of resource productivity

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Abstract

In this study, we assumed that 28 European countries (Decision Making Units (DMUs)) aimed to accomplish higher economic outputs, using fewer resources and producing fewer emissions in the form of environmental degradation. In this context, we studied the drivers of total factor productivity change (TFPCH) in DMUs, associated with either managerial capabilities (effi-ciency change (EC)) or innovations (technical change (TC)) in resource‐saving production methods, before and after the integration of CO2 (carbon dioxide) emissions as an additional variable (unde-sirable output) in the initial model of one output (gross domestic product (GDP)) and five inputs (labor, capital, energy, domestic material consumption and recycled municipal waste). The primary focus of this study is to identify best practices that policymakers can adopt as they attempt to reduce productivity loss. Our results highlight the weak areas of individual countries and seem to indicate the action that should be taken to improve their productivity by taking into consideration the main driving force behind productivity and technical efficiency change. Our findings reveal that an effective use of technological developments is determined as important strategic information for ensuring managerial performance.

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APA

Bampatsou, C., & Halkos, G. (2021). Non‐parametric computational measures for the analysis of resource productivity. Energies, 14(11). https://doi.org/10.3390/en14113114

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