Objective – The global industry is transforming into a digital world, evidenced by digital transformation performed by almost all of the industry sectors. One of the digital drivers is the support of connectivity provided by the telecommunication industry. The increasing mobile subscribers, along with the growth of mobile data traffic, is the sign of digital transformation itself. However, the rise of OTT (Over the Top) service providers tends to acquire the revenue share of the current telecom industry, seeing the trend of voice and SMS revenue that projected to decline. Methodology/Technique – This research is intended to measure the impact of increasing mobile data traffic that mostly caused by OTT services to telecom efficiency. The efficiency measurement & analysis were performed using the Stochastic Frontier Approach (SFA) & Data Envelopment Analysis (DEA) method. Findings – By using the SFA method, Maxis (Malaysia) got the highest efficiency score (0.98), followed by AIS (Thailand) with efficiency score 0.94 and Indosat Ooredoo (Indonesia) as the least efficient telecom provider (0.5). However, by using the DEA method, TLKM (Indonesia) got the highest efficient (0.98), and Celcom Axiata (Malaysia) was the least efficient (0.73/0.8). Novelty – The compelling results of this study are variable total asset variable had a significant negative impact on the efficiency score, and the variable of mobile data traffic was not significantly impacting the efficiency value (t-Ratio 0.71). Type of Paper: Empirical. Keywords: Telecom Operators; Efficiency; Mobile Data Traffic Reference to this paper should be made as follows: Hendrawan, R; Nugroho, K.W.A; Permana,G.T. 2019. Efficiency Perspective on Telecom Mobile Data Traffic, J. Bus. Econ. Review 5(1) 38 – 44 https://doi.org/10.35609/jber.2020.5.1(5) JEL Classification: M10, M15, M19.
Objective -The telecom industry is one of the optimistic industries that is still growing. In South East Asia, between 2008-2017, the number of subscribers increased 10.07% annually, and revenue for the industry grew 6.08% annually. However, Net Profit Margin, EBITDA, and EBIT value during the same period declined at the time revenue amount was increasing. One of the visible health factors and part of the valuation factor is stock value. Hence the research question of this study is: What is the impact and significance of telecom operators' efficiency to stock value? Methodology/Technique -In this study, efficiency will be measured and analyzed using Stochastic Frontier Approach (SFA) method. By using same method, the impact of efficiency to stock value will be measured, as well as the significance level. Findings -The results of this research show that from 14 telecom operators observed, TLKM (Indonesia) obtained the highest efficiency score (0.984) whereas StarHub (Malaysia) had the lowest efficiency score (0.405). TLKM (Indonesia) and AIS (Thailand) had a similar efficiency score given the fact that the behaviour of the subscribers is similar and they have the same country characteristic. Novelty -All of the input and output variables have a positive impact on the efficiency parameter except Total Asset which has negative impact on the efficiency score. By using further analysis of the t-Ratio between the variables and efficiency, it can be seen that stock value is impacted by the efficiency parameters but this impact is not significant (t-Ratio 1.35).
This study aims to analyze the efficiency of telecommunications companies and find out the variables of efficiency of telecommunications companies in Southeast Asia in the period of 2008-2017 involving 14 telecommunications operators using the Stochastic Frontier Analysis method. The results of these studies show that the telecommunications companies in Southeast Asia still had room to improve their profit efficiency scores for 0,984 -0,689 = 0.295. Furthermore, the results show that input variables such as Personal, capex and opex have a positive effect on the value of efficiency which means that each increase in the variable Capex, Opex and Personal Expenses will have an impact in increasing the value of efficiency Whereas the total assets have negative effects on the efficiency value of telecommunications operators. Output variables consisting of revenue, subscribers and ARPU have a significant effect on the value of efficiency. These three output variables in the SFA measurement method have a positive influence on the efficiency of telecommunication operators. Inflation used as an environmental variable in measuring the efficiency of telecommunication operators shows that it does not have a significant impact on the efficiency value of telecommunications operators.
Objective - The telecommunications industry in Southeast Asia continues to grow, as evidenced by the market penetration that continues to increase from 3.8% in 2000 to 71.1% in 2017. However, although the number of subscribers and revenue from telecommunication operators continued to grow between 2008 to 2017, the data shows that the EBITDA margin and ARPU value decrease with the growth rate (CAGR) -1.12% and -4.42%. Methodology/Technique - This study measures and analyzes the efficiency of 14 operators in Southeast Asia between 2008 to 2017 by using the Data Envelopment Analysis (DEA) method. Findings - The results show that of the 14 telecom operators examined, Telkomsel (Indonesia) was the most efficient operator with an efficiency value of 0.97 and contributed from subscriber and revenue output variables which far exceeded the average of other operators. The most efficient telecommunication companies thereafter were StarHub (Singapore) and SingTel (Singapore) with an efficiency rating of 0.96 and 0.95 as represented from ARPU output variables that far exceeded the average of other operators. Novelty - True Move operators became the telecommunication companies with the lowest efficiency because the value of its output variables (subscribers, revenue and ARPU) was far below average and did not show any positive correlation to its efficiency value. Type of Paper - Empirical. Keywords: Data Envelopment Analysis (DEA); Efficiency; Telecommunication Industry; Southeast Asia. JEL Classification: M1, M10, M19.
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