A DEA-based tool for tracking best practice exemplars: The case of telecommunications in EBRD countries

Abstract

Benchmarking is a strategic management tool that can help to gain competitive advantage, but the question is how to decide the relevant practice exemplars to be used as role models. Data Envelopment Analysis (DEA) is a very helpful method for tracking corresponding benchmarks, but the question remains of how to record them when performance is fluctuating and unstable, as is the case in a transition period to an open market. To address this issue a new DEA-based tool is proposed, the Corresponding Benchmark Matrix (CBM), which helps to reveal ?leader? countries and the most suitable benchmarks for less successful countries. The approach is illustrated for telecommunications in 22 European Bank for Reconstruction and Development (EBRD) countries.

Telecommunications industry efficiency: A comparative analysis of high and middle income countries

“…However, the sample size is small, and the study did not employ statistical analysis to determine if the efficiency of Turk Telecom differs from those of G8 countries. Petrovic, Bojkovic, & Stamenkovic (2018) Nonetheless, the study finds that EU countries performed better than less wealthy South East European countries. Using DEA, Calabrese, Campsi, & Mancuso (2002) infer that efficiency gain is possible through input-output mix rather than through operational scale.…”

“…The few studies on emerging countries with middle incomes are country specific (e.g., Resende & Facanha, 2002;Sharma, Momaya & Manohar, 2010) or regional in focus (e.g., Cabanda, Ariff & Viverita, 2004;Moshi, Mwakatumbula & Mitomo, 2013;Torres & Bachiller, 2013). Some studies (e.g., Lee, Park, & Oh, 2000) report efficiency improvements, whereas others assert the contrary or indicate that efficiency varies with time (e.g., Gokgoz & Demir, 2014;Petrovic, Bojkovic, & Stamenkovic, 2018;Uri, 2006). The incongruence in findings creates ambiguity that this research endeavors to resolve through a comparative analysis of the industry in designated high income countries (HICs) and middle income countries (MICs).…”

An Empirical Study on the Efficiency and Influencing Factors of the Photovoltaic Industry in China and an Analysis of Its Influencing Factors

“…For the selection of input indicators, this paper uses the number of employees in the power industry to measure labor input. In terms of measuring capital investment, the first task is to calculate the net value of fixed assets of the power generation industry by using the capital stock as the capital input standard [24]. The second is to use the installed capacity of power generation as a measure of capital investment.…”

“…Therefore, the cumulative installed capacity of the PV power generation industry was selected for measurement. PV power investments include technical facilities, land and other infrastructure costs [24], which can be considered as cost indicators.…”

“…The research indicated that the levels of technical efficiency are relatively high in the economically developed eastern coastal areas and coal-rich areas. Zhang (2011) [24] sampled the data of thermal power generation panels in 30 provinces and cities in China and applied the SFA method to measure the technical efficiency of the power generation industry. It was found that the overall efficiency level of the power generation industry in China was relatively low-only 0.47.…”