Author:
Chaharlang Yusof,Soleimani Hamed,Mehdizadeh Esmaeil,Alinezhad Alireza
Abstract
Today, achieving managerial success and ongoing improvement depend greatly on the performance evaluation of service and economic units. On the other hand, we are aware that strategy is the primary driver of an organization’s long-term development and that, even if the right strategies are adopted, this effort will be ineffective if the strategy is not effectively executed. A balanced scorecard is an essential tool for strategy implementation. The network data envelopment analysis model, on the other hand, is recommended for the relative analysis and assessment of decision-making units in evaluating and improving the organizations’ performance with multiple inputs and outputs. The four components of the balanced scorecard are financial (retrospective indicators), and processes, customers, and learning and growth (prospective indicators). According to investigations, in addition to the four previously mentioned fields, a balanced scorecard for urban services (municipality) also encompasses the social responsibility field. In order to design performance evaluation indicators, this article attempted to use BSC while also attempting to evaluate performance using DEA. The Shahriar city municipal units of Ferdowsieh, Vahidie, Sabashahr, Shahedshahr, Andisheh, Baghestan, and Shahryar have all adopted this hybrid model. The findings indicate that the municipality of Andisheh city is efficient, while the remaining municipalities are inefficient. Nevertheless, the Baghestan municipality performs well and is effective in terms of social responsibilities.
Subject
Building and Construction,Civil and Structural Engineering,Architecture
Reference28 articles.
1. Kaplan, R.S., and Norton, D.P. (1996). Translating Strategy into Action: The Balanced Scorecard, Harvard Business School Press.
2. Charnes, A., Cooper, W.W., Lewin, A., and Seiford, L.M. (1994). Data Envelopment Analysis: Theory, Methodology and Applications, Kluwer Academic Publishers.
3. Measuring the efficiency of decision making units;Charnes;Eur. J. Oper. Res.,1978
4. Cone-ratio data envelopment analysis and multi-objective programming;Charnes;Int. J. Syst. Sci.,1989
5. The balanced scorecard: Measures that drive performance;Kaplan;Harv. Bus. Rev.,2005