Are the fi xed-mobile telcos more competitive? A cross-country eff iciency study

Chi-Kuo Mao, Ministry of Transportation and Communications Taiwan, R.O.C.

Jin-Li Hu* Institute of Business & Management National Chiao Tung University 118, Sec. 1, Chung-HsiaoW. Rd. Taipei City 100 Taiwan, R.O.C.

Chun-Mei Chen Department of Business Administration China University of Technology Taiwan, R.O.C.

Abstract The trend to integrate fi xed-line and mobile service is emerging in the telecom indus- try. This paper compares the eff iciency of fi xed-mobile telcos which off er both fi xed-line and mobile services with fi xed-only and mobile-only telcos for the period 2000-2007. The DEA (data envelopment analysis) method is employed to measure the relative eff iciency of the three carrier groups. These sample operators are leading companies in the telecom industry based upon their rankings in Forbes global 2000 and are divided into the three operating models of mobile-only, fi xed-only, and fi xed-mobile service. The empirical results show that there are signifi cant diff erences among the three groups and for each year across the 8-year period. The strategic decision not to spin-off the mobile business from fi xed-mobile opera- tions was correct. In the future, it is anticipated that a single operating license will authorize the provision of the integrated services of fi xed-line, data, mobile, and broadcasting. There- fore, from the long-term perspective the future for fi xed-mobile service carriers is promising.

Keywords: Data envelopment analysis (DEA); Eff iciency; Fixed-line; Mobile; Telcos

*E-mail: [email protected]

Journal of Information & Optimization Sciences Vol. ( ), No. ( ), pp. 1–27 © Taru Publications 2 C. K. MAO, J. L. HU AND C. M. CHEN

1 1. Introduction 2 As soon as mobile service entered the market in the early 1980s fol- 3 lowing the liberalization of the telecom industry, it became the star busi- 4 ness that enjoyed high growth in the industry. This high growth potential 5 also made mobile business the ‘growth stock’ which could easily win capi- 6 tal gains for investors in stock markets around the world. Following the 7 suggestions of Wall Street underwriters, many incumbents such as PCCW, 8 and KT in Asia BT, Eircom (Ireland), Royal KPN, Swiss- 9 com AG, Belgacom, and France Telecom in Europe and (Mexico) 10 in America split their respective mobile business units from the parent 11 bodies as independent companies for IPOs in their privatization process 12 so as to enjoy a higher valuation of stock prices. Nevertheless, 13 (Singapore), (Australia), Portugal Telecom, and Chunghwa Tele- 14 com (Taiwan), etc. maintained their mobile operations as an integral part 15 of their fi xed-mobile businesses which consist of fi xed-line and mobile as 16 well as Internet and data services. In addition, the incumbents that sold off 17 their mobile business units to become fi xed-only carriers have re-entered 18 the mobile market since 2004 by re-merging their mobile branch for 100% 19 of shareholdings; for example, France Telecom, KPN, Telefonica, Swiss- 20 com, Belgacom, and Telecom Italia moved toward a fi xed-mobile business. 21 It is interesting to note that the stock prices of mobile-only carriers 22 climbed to their peak around early 2000 and have suff ered a continu- 23 ous downturn since then because of the saturation of the mobile market. 24 Nevertheless, the ARPU of 3G in general is better than that of 2G and 25 subscribers could switch from 2G to 3G without adding too much addi- 26 tional cost for acquiring customers. At the same time, stock prices of the 27 fi xed-mobile telcos also declined, but to a less severe degree and showed 28 an up trend in late 2002. Even though the fi xed-only carriers are trying to 29 stop the decline in fi xed-line income, their performance is expected to be 30 not as good as the fi xed-mobile telcos because they lack the additional mo- 31 bile revenue, but this is subject to further verifi cation. In addition, fi xed- 32 mobile operations moving toward establishing an all IP fi ber network in- 33 frastructure might have more opportunities for providing the integrated 34 voice, data and mobile services to satisfy the customers’ advanced needs. 35 Therefore, a single operating license could be considered by the regulators 36 to authorize the provision of the integrated services of fi xed-line, data, 37 mobile and broadcasting to follow the evolution of the industry. Given 38 this observation, the purpose of this paper is to investigate the compara- 39 tive eff iciency among mobile-only, fi xed-only and fi xed-mobile telcos, and 40 FIXED-MOBILE TELCOS 3

1 to provide a basis for commenting on modern telecom carriers’ criteria 2 for strategic planning. This study will further explore the reasons for the 3 incumbents to re-merge their mobile branches and pursues the questions 4 whether they perform relatively better operation eff iciency than before re- 5 merging. 6 Studies of eff iciency are critical for the improvement of telecom pol- 7 icy and management decision-making. The DEA (data envelopment anal- 8 ysis) method has been applied to examine other eff iciency-related issues 9 in the industry. Majumdar (1995) investigated the eff ect of the adoption 10 of new switching technology on carriers’ performance in the U.S. telecom 11 industry by calculating input-conserving and output-augmenting mea- 12 sures. Sueyoshi (1998) explored the economic assertion of NTT by com- 13 paring its performance before and after privatization in 1985. Giokas and 14 Pentzaropoulos (2000) examined the technical eff iciency and economy 15 scale of the Hellenic organization over the period 16 1971 to 1993. Zhu (2000) developed a multi-factor performance model 17 to measure profi tability and marketability for Fortune 500 companies in 18 the bank industry. Uri (2000, 2001a, 2001b) investigated the changing ef- 19 fi ciency resulting from incentive regulation implemented in the United 20 States telecom industry. Lien and Peng (2001) computed the production 21 eff iciency of telecommunications in 24 OECD countries. Pentzaropou- 22 los and Giokas (2002) compared the operational eff iciency of the main 23 European telecom carriers. Tsai et al. (2006) applied the DEA approach 24 with the classical radial measure, A&P eff iciency measure and eff iciency 25 achievement measure, respectively, to compare the productivity eff i- 26 ciency for global telecoms. 27 Mao et al. (2008) studied the issues of FMS patterns of traff ic substitu- 28 tion and penetration substitution. They indicated that during 1997-2004, 29 for those countries such as G7 and NIE with fi xed-line penetration higher 30 than 100%, the FMS is mostly traff ic substitution; and for those countries 31 with fi xed-line penetration lower than 100% such as ASEAN and BRIC, 32 the FMS is mostly penetration substitution. Hu and Chu (2008) applied 33 a two-stage method to examine the production eff iciency of twenty-four 34 telecom fi rms in APEC member countries during the period 1999-2004. 35 They found that scale economies have positive impacts on the eff iciency 36 improvement of Asia-Pacifi c telecom fi rms, but the infl uence of market 37 competition and privatization to their telecommunications performance 38 are ambiguous. 39 This paper is the fi rst study to present results on relative eff iciency 40 for the three major telecom carrier groups from around the world. 4 C. K. MAO, J. L. HU AND C. M. CHEN

1 The DEA data include the output variables of revenue, EBITDA, EBIT, and 2 net income and the input variables of total assets, capital expenditure, and 3 employees. These data are retrieved from UBS Investment Bank database 4 and from the carriers’ Annual Reports on their websites. 5 This paper is organized as follows: Section 2 describes the develop- 6 ment of both mobile and fi xed-line markets in the evolution of the tele- 7 com industry. Section 3 provides an outline of the DEA method to be 8 used in this paper and an analysis of the data. Section 4 shows the DEA 9 results and the cross-country eff iciency comparison. Section 5 concludes 10 this paper. 11 12 2 Telecom industry evolution 13 14 2.1. Mobile Market Development 15 Mobile networks can be established with less capital expenditure 16 than wired ones, because there is no need to run a wire-line into every 17 subscriber’s home. In addition, the convenience of mobility and the per- 18 sonalization of mobile communication caused total mobile calls world- 19 wide to surpass fi xed-line calls in 2003. Mobile replacement of fi xed-line 20 voice calls is becoming more obvious and has become a serious threat to 21 fi xed-line only carriers. 22 23 (1) Fixed Mobile Substitution (FMS) 24 The use of mobile instead of fi xed-line telephony for calls or access 25 is called Fixed Mobile Substitution (FMS) or Fixed to Mobile Sub- 26 stitution (FtM). Mobile communication service includes calls from 27 mobile to mobile and calls from mobile to fi xed-line, while fi xed-line 28 service includes calls from fi xed-line to fi xed-line and from fi xed- 29 line to mobile. According to the ITU (International Telecommuni- 30 cation Unit) in 2003, over a ten-year period from 1993 to 2003, the 31 data show that in 1993 worldwide fi xed-line calls made up 94.7% 32 of total calls, while worldwide mobile calls made up only 5.3% of 33 total calls. Nevertheless, by 2003 worldwide mobile calls reached 34 51.7% of total calls, thus surpassing fi xed-line calls at 48.3%. The 35 percentage of fi xed-to-fi xed calls to total calls slipped from the peak 36 of 89.7% (1993) down to 52.7% in 1998, and dropped further to 23.3 37 % in 2003, which was lower than the 26.7% of mobile-to-mobile 38 calls. This indicates that mobile communication not only replaced 39 but also surpassed fi xed-line communication. Figure 1 shows the 40 details: FIXED-MOBILE TELCOS 5

Source: ITU (International Union), 2003

Figure 1 FMS calls and their change in ratio distribution (1993-2003)

(2) Increasingly saturated mobile market More than fi fty countries have surpassed 80% of the mobile popu- lation penetration ratio (mobile subscribers/population), limiting their penetration growth. By the end of December 2007 UAE (United Arab Emirates) had the highest mobile penetration in the world at 173.4%. Countries with small geographic size, high population density, and fi erce market competition tend to have higher mobile penetration rates. UAE, Macao, Qatar, , and Italy have, in that order, the highest mobile population penetration worldwide. Table 1 lists the rankings for global mobile penetration.

2.2. Fixed-line market development

(1) Traditional telephony revenues drop considerably The liberalization of fi xed-line markets has forced PSTN (Public Switching Telephone Network) operators to greatly lower their once high margin monopoly pricing for international and long distance services, resulting in a serious loss of fi xed-line voice revenue for tra- ditional telecom operators. FMS has aff ected traditional telephony revenue for both incumbent carriers and new fi xed-line operators. 6 C. K. MAO, J. L. HU AND C. M. CHEN Table 1 Table Global mobile population penetration ranking (Dec. 31, 2007) ITU (2008) ITU Mobile Mobile Mobile Penetration Mobile Countries Penetration Countries Mobile Countries Penetration Emirates Arab United 173.4% Ireland Macao 114.9% Oman 114.7% Jamaica Qatar Arabia 93.7% 96.3% China Hong Kong, Italy 89.5% 165.0% Saudi Salvador 146.4% Republic Antigua & Barbuda 128.4% Poland 150.4% Denmark Luxembourg 114.7% Bermuda 133.5% 93.3% 108.7% El Bahamas Czech 129.5% Hungary Korea 135.1% Spain Singapore 109.9% France 90.2% Norway Portugal 89.8% 110.2% S. 112.9% Israel 108.2% Malaysia 126.7% Switzerland 87.9% 105.9% Chile Kingdom Africa 118.9% Netherlands Ukraine 87.1% 126.3% Greece 110.1% Russia Andorra 83.9% 84.8% Rico United 107.6% S. 122.7% Romania 97.3% 119.6% Taiwan Germany 83.5% Uruguay 86.1% 106.7% Venezuela 91.8% States Austria 106.1% Puerto Kuwait 119.3% Sweden Greenland 105.9% Japan 117.6% Maldives 89.9% Iceland 104.0% United 83.9% 115.2% 116.8% Argentina Finland 115.9% Belgium 102.2% Turkey 97.8% Jordan 82.8% 115.4% Latvia 80.5% 97.4% Thailand 80.4% Source: FIXED-MOBILE TELCOS 7

1 The wide spread use of VoIP (Voice over Internet Protocol) is further 2 eroding traditional voice revenue. 3 Comparing revenue for the fi nancial years 1999 and 2003, NTT shows 4 a 51% decrease, while Taiwan’s has a 44% drop. 5 In 2002 KT off ered the service of bundling local calls and long dis- 6 tance calls at a fl at rate to promote fi xed-line use and had a relatively 7 small loss of traditional telephony revenue. Table 2 shows the com- 8 parison of fi xed-line telephony revenue loss for incumbent carriers. 9 For traditional fi xed-line incumbent carriers, asymmetric govern- 10 mental regulations add further operating diff iculties. Because current 11 telecom regulations were formulated based on traditional PSTN tech- 12 nology, there is a regulatory demand for UNE (unbundled network 13 elements) to allow new entrants access to critical network elements 14 of the incumbents’ existing, highly penetrated, and widely covered 15 PSTN network. These regulations that favor new entrants extend 16 even to mobile operators. For example in Taiwan, mobile operators, 17 besides having the right to control pricing for access connection fees 18 between mobile and fi xed-line networks, are not bound by the USO 19 (universal service obligation). The entire mobile business relative to 20 the fi xed-line business provides a complementary function for the 21 end users. 22 23 (2) Data and Internet business as a future hope for the fi xed-line market 24 Following the business development of Internet broadband tech- 25 nology, the incumbents started to build broadband networks, using 26 various technologies such as DSL, FTTX, Wi-Fi, ISDN, Satellite, etc. 27 28 Table 2 29 Fixed carriers’ telephony revenue downward trend 30 31 Downturn 32 Units/ trend Operators Year 1999 2000 2001 2002 2003 (1999-2003) 33 34 NTT ¥ mn 6,394,562 6,171,979 5,866,859 4,735,660 3,162,185 –51% Chunghwa 35 Telecom NT$ mn 133,873 112,463 92,772 78,662 74,684 –44% 36 KT Won mn 56,616 50,223 46,104 47,820 46,927 –17% 37 PCCW HHK$ mn – 7,211 7,615 6,849 6,024 –16% 38 France 39 Telecom € mn 13,698 13,146 13,878 10,792 11,127 –15% 40 Source: Carriers’ Annual Report 8 C. K. MAO, J. L. HU AND C. M. CHEN

1 They developed Internet access data networks and created a new 2 business model for bundling voice, data, and video service to gain 3 additional revenue and profi t. Monaco, S. Korea, Singapore, Hong 4 Kong, Macao, and Denmark have, in that order, the highest broad- 5 band penetration in the world. In 1994 KT Corp. initiated Kornet 6 services to kick-start high-speed Internet access. The competition be- 7 tween KT, Hanaro, and Thrunet has led to low retail prices and the 8 now common ‘free modem and installation’ off er, making S. Korea 9 the country with the second highest level of broadband household 10 penetration. Table 3 shows the ‘top ten’ countries ranked in terms of 11 household penetration in Q1 2008. 12 It is foreseeable that data and Internet businesses are the hope of 13 fi xed-line carriers for future revenue. Nevertheless, the growth of 14 e-mail business has resulted in a diff erent level of cannibalization 15 for incumbent carriers. The turning point for declining telephony 16 revenues for most operators occurred in 1999, coinciding with the 17 increase in Internet e-mail use in the same year. 18 In conclusion, according to ITU data from 1999 and 2002, Japan 19 displayed the greatest negative growth of –39.9% for traditional 20 telephony revenue, followed by Taiwan’s negative growth of -32.9%. 21 Taiwan opened its fi xed-line services in the beginning of 2001, and 22 new entrants inaugurated a fi erce price war. Even though telephony 23 traff ic has grown signifi cantly, voice revenue has declined consider- 24 ably since 2001. Except for Germany, fi xed household penetration 25 from the year 2000 to 2005 declined because of fi xed to mobile sub- 26 stitution (FMS). Table 4 shows the countries’ telephone revenue co- 27 incidence with the downward fi xed-line household penetration. 28 29 Table 3 30 Top ten worldwide broadband household penetration (March 31, 2008) 31 32 Broadband Broadband 33 Household Household 34 Ranking Countries Penetration Ranking Countries Penetration 35 1 Monaco 96% 6 Denmark 84% 36 2 S. Korea 94% 7 Netherlands 83% 37 3 Singapore 88% 8 Israe l82% 38 4 HK 87% 9 Switzerland 81% 39 5 Macao 86% 10 Iceland 80% 40 Source: Statistics from Point-Topic FIXED-MOBILE TELCOS 9

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Table 4 Table

22 household penetration (unit: xed US$ million) 23 24 25 26 27 28 29 30 31 32 33 Telephone revenue growth ratio vs. fi revenue Telephone 34 35 36 37 after 2002) available data not 2004 (Telephone Indicators Telecommunication World ITU, 38 1999-2002 Fixed Household Penetration Household Fixed growth 2000 2001 2002 1998 1999 Telcos\year 1999-2002 2000 Japan 2005 Taiwan 44,689 42,649 51,264 50,753 30,791 –39.9% Singapore –32.9% 3,278 4,455 3,899 4,087 2,615 1,428 1,312 1,041 934 France 189.2% 131.7% –29.4% 926 U.K 186.5% 200.8% 12,833 16,421 16,024 13,423 13,194 –17.7% 121.9% Germany 175.8% 19,107 26,027 23,063 19,358 21,226 140.5% U.S.A –8.0% 18,986 20,241 20,458 20,303 18,060 –11.7% Canada 133.8% 131.7% 227,113 144.6% 167,425 220,010 230,762 210,000 8,536 9,051 8,553 9,207 8,231 –3.8% –4.5% 139.8% 126.7% 182.6% 177.3% 166.3% 153.1% Source: 39 40 10 C. K. MAO, J. L. HU AND C. M. CHEN

1 2.3. The split of incumbents 2 3 (1) Mobile Branch De-Merger 4 There are two models for privatizing traditional telecom carriers. 5 One separates the mobile service from the traditional fi xed-line ser- 6 vice when the mobile service is enjoying high growth in order to 7 establish a new public company through an IPO at the time when 8 the stock price could be off ered at a premium level without hav- 9 ing any of the bad eff ects associated with the fi xed-line operation. 10 This model was popular in the past few years; for example, NTT 11 DoCoMo, , Mobile, Orange SA, AT&T Wire- 12 less, etc. Table 5 shows the details. The other model is not to divide 13 the incumbent’s business and to go public as a fi xed-mobile telco. 14 The public availability of operating licenses for both fi xed-line and 15 mobile services, in addition to the implementation of two models 16 of privatization, has created three types of facility-based carriers: 17 mobile-only, fi xed-only, and fi xed-mobile. In July 1995 Telecom Ita- 18 lia was the earliest operator to separate its mobile branch TIM, and 19 then dramatically merged back with TIM in June 2005. NTT sold 20 off its partial shareholdings in NTT DoCoMo in October 1998. Most 21 of the listed operators de-merged their mobile branch by the year 22 23 24 Table 5 25 Mobile branch de-merger time list 26 27 Parent Carriers Country Mobile Branch De-merger Time 28 Telecom Italia 29 Telecom Italia Italy Mobile (TIM) July 1995 30 NTT Japan NTT DoCoMo October 1998 31 ChinaTelecom China China Mobile (H.K) April 2000 32 Swisscom Switzerland Swisscom Mobile January 2001 33 France Telecom France Orange SA February 2001 34 Telmex Mexico Telcell February 2001 35 Royal KPN Netherlands KPN Mobile NV March 2001 36 Eircom Ireland Eircell May 2001 37 AT & T U.S.A AT & T Wireless July 2001 38 BT Group U.K Cellnet (mmO2) October 2001 39 PCCW Hong Kong CSL December 2001 40 Source: Espicom Intelligence Research for telecom companies FIXED-MOBILE TELCOS 11

1 2001 including Swisscom, France Telecom, Telmex, Eircom, AT&T, 2 BT Group, and PCCW. 3 (2) Mobile Branch Re-Merger 4 5 Table 6 shows the change in the parent operators’ ownership of the 6 mobile branches. FT bought back the mobile shareholdings of spun- 7 off Orange SA in the public market at the end of 2003. FT said it 8 owned 99.02% of the shares of France Telecom as of February 2004, 9 and in June 2004 announced that it owned 100% of Orange SA. TIM 10 (Telecom Italia Mobile), the fi rst company which was spun-off from 11 its mother company Telecom Italia in July 1995, merged back as an 12 integrated company in June 2005. On January 30, 2005, New AT&T 13 (SBC) merged with BellSouth and completed its acquisition on 14 December 29, 2006. In October 2005, KPN bought NTT DoCoMo’s 15 remaining interest of 2.16% in KPN Mobile NV. On December 20, 16 2006 Swisscom bought back ’s 25% stake in Swisscom Mo- 17 bile AG. Belgacom Group’s acquired Vodafone’s 25% stake in Belga- 18 com Mobile in early November 2006. In addition, NTT’s interest in 19 NTT DoCoMo increased from 61.5% in fi scal year 2003 to 63.7% in 20 2007 and to 64.8% in 2008. KT’ interest in KTF also increased from 21 40.7% in 2004 to 52.2% in 2008. Eventually KT declared to merge 22 with KTF as of June 1, 2009. 23 After new AT&T (SBC) completed its acquisition of BellSouth, Bell- 24 South became a part of AT&T, and thereafter AT&T owned 100% 25 of shareholdings for the mobile branch of Cingular Wireless. But 26 AT&T had departed from the fi xed-mobile operating model, thereby 27 clouding its future. In July 2001 AT&T sold off its mobile unit, AT&T 28 Wireless, and later, on November 18, 2002 sold off its broadband 29 business, AT&T Broadband (thereafter merged as AT&T , 30 the largest cable operator in the U.S.). It kept only the long distance 31 business and data service for business and general customers, and 32 IT services. AT&T’s stock price dropped from US$120 per share in 33 the year 2000 to US$14 per share in September 2004, losing 88% of 34 its value. On January 30, 2005, SBC, a RBOC that had originally split 35 from AT&T, announced its plan to acquire the once giant telecom 36 AT&T for US$16 billion. Thereafter, SBC (new AT&T) merged with 37 BellSouth, extending its local broadband regions. A more important 38 reason was to acquire 100% shareholdings of Cingular Wireless in 39 order to be a more infl uential fi xed-mobile telcos. Verizon Wire- 40 less is a joint venture of and Vodafone. 12 C. K. MAO, J. L. HU AND C. M. CHEN

1 2 3 4 5 6 7 8 9 10

11 ective Date own 12 13 14 15 16 17 18 19 20 21 22 6 Table 23 24 25 26 27 28 29 30

31 the operators of mobile branch own shareholdings percentage Parent 32 33 34 35 Telcos’ Annual Report Telcos’ 36 Source: Shareholdings Shareholdings Shareholdings Operators Parent Country Mobile Branch 2004) (May, Eff 37 Telecom France KPN Royal S.A. Telefonica France – 40.00% Swisscom AG – Belgacom Wireless Spain Netherlands NTT Corp. SA Orange Switzerland KPN Mobile NV Italia Telecom KT Swisscom Mobile Moviles Telefonica Belgium SBC Cingular Japan Italia 97.80% BellSouth U.S.A 75.00% 99.02% Verizon 92.44% Mobile Belgacom 2005 October, Communications 2006 December, June, 2004 2006 December, NTT DoCoMo U.S.A TIM 100.0% S. Korea 75.00% 100.0% 100.0% U.S.A Wireless 2006 100.0% Verizon November, KTF 61.50% 100.0% Cingular Wireless 2008 August, 55.00% 56.00% 60.00% 63.7% June, 2005 2006 January, 40.70% 100.0% 100.0% 2008 August, 52.2% 38 39 40 FIXED-MOBILE TELCOS 13

1 On December 15, 2006, Verizon Wireless repaid all of its outstanding 2 public debt; consequently, it ceased to be a reporting company. In 3 conclusion, the incumbents that sold off their mobile business units 4 to become fi xed-only carriers have re-entered the mobile market by 5 buying back their mobile branches to own 100% of shareholdings; 6 for example, France Telecom, KPN, Telefonica, Swisscom, Belga- 7 com and Telecom Italia have moved toward a fi xed-mobile business. 8 Table 6 shows the details. 9 10 3. Methodology 11 12 This study arose from thinking about the following two questions: 13 14 1. Whether mobile-only carriers that split from their parent companies 15 for the purpose of pursuing higher stock prices have a better operat- 16 ing performance than fi xed-only carriers that were formed after the 17 original fi xed-mobile telcos had sold their mobile departments. 18 2. Whether telcos specializing in the single operations of mobile-only or 19 fi xed-only are more competitive than non-split fi xed-mobile carriers. 20 21 3.1. Research structure 22 This research structure assumes a) that the three operating models 23 are independent variables, b) that multi-outputs and multi-inputs are in- 24 tervening variables, and c) that the DEA eff iciency values are dependent 25 variables; and it applies these hypotheses to the three models of business 26 operation. Because this study observes leading global telecom carriers that 27 are public companies, their stock information is therefore available. Since 28 labor is a necessary factor for telecos to generate outputs, the quantity of 29 employees is taken as one of the input variables in this study. The three 30 input variables of total assets, capex (capital expenditure), and number of 31 employees, and the four output variables of revenue, EBITDA,1 EBIT,2 and 32 net income are shown in Figure 2. 33 34 3.2. DEA methodology 35 The traditional ratio-form DEA (Charnes et al. (1978), called the CCR 36 method) is based on the pioneering work of Farrell’s (1957) eff iciency 37 38 39 1EBITDA represents Earnings before Interest, Taxes, Depreciation, and Amortization. 40 2EBIT represents Earnings before Interest & Taxes. 14 C. K. MAO, J. L. HU AND C. M. CHEN

1 2 3 4 5 6 7 8 9 10 Figure 2 11 12 DEA assessment structure 13 measure (relative eff iciency), generalizing a multiple output-input perfor- 14 mance measure in which the ratio of the weighted outputs to weighted in- 15 puts for each observation is maximized. Each DMU’s eff iciency evaluation 16 is viewed as one objective function to be maximized. There are n units or 17 n decision making units (DMUs) and each has m inputs with s outputs. If 18 the ath DMU uses m-dimension input variables xiia (,,)= 1 f m to produce 19 s-dimension output variables yrra (,,),= 1 f s then the overall technical ef- 20 fi ciency (OTE) of DMU ha can be found from the following model: 21 S 22 / uyrra 23 r = 1 Max ha = (1) 24 m / vxi ia 25 i = 1 26 subject to 27 S 28 / uyr rk 29 r = 1 # 112,,,,kn= f 30 m / vxi ik 31 i = 1 32 0011ff##uvimrs,,,,,,,;== 1ff 1 33 r i

34 where xik stands for the ith input of the kth DMU; 35 yrk stands for the rth output of kth DMU; 36 u and vi stand for the weight of the rth output and ith input, 37 r respectively; 38 -4 39 f is a positive Archimedean number which is set to be 10 ; 40 ha is relative eff iciency value. FIXED-MOBILE TELCOS 15

1 Since Equation (1) involves fractional programming and is therefore 2 diff icult to solve by numerical algorithms, Charnes et al. (1978) converted 3 it to another output-oriented linear programming model: 4 s 5 Max ha = / urra y (2) 6 r = 1 subject to 7 m s 8 $ f //vxr ik -= uyrik 01,,,; k n 9 i ==11r 10 /m 11 vxria= 1; i = 1 12 ursr $ f 2 01,,,;= f 13 vrmr $ f 2 01,,.= f 14 15 The input-oriented dual problem after conversion of Eq. (2) becomes: 16 m s - + 17 MSin'ifa -+; / iar/ S aE1 (3) 18 i = 1 r = 1 19 subject to: 20 m + f -+yySrsra / mkrk -ia =01,,,; = 21 k = 1 22 n - f 23 ima xySimia--==/ kik ia 01,,,; k = 1 24 -+ $ 25 SSia,,ram k 0 ; 26 where ia is the overall technical eff iciency score (OTE) of DMU a which is 27 equal to ha ; and and are input and output slack variables, respectively. It 28 is worth noting that the OTE scores obtained by either the output-oriented 29 (Eqs. (1) and (2)) or the input-oriented (Eq. (3)) CCR models are exactly the 30 same, due to the linear (CRS) assumption of the production function here. 31 32 3.3. DEA assessment 33 34 DEA involves the use of linear programming methods to construct 35 a non-parametric piecewise surface (or frontier) over the data, so as to 36 be able to calculate eff iciencies relative to this surface. The eff iciency as- 37 sessment conducted in this study is based on the input and output in- 38 formation of each DMU. This study adopts input-oriented measures to 39 compute and produce OTE, PTE, and SE scores for the three groups over 40 eight years (2000-2007) by DEAP 2.1 software (Coelli, 1996). Compared to 16 C. K. MAO, J. L. HU AND C. M. CHEN

1 the outputs, the inputs are relatively directly controllable by the telecoms. 2 The output levels such as revenues can be aff ected by external factors such 3 as market competition and business cycles. As a result, the input-oriented 4 DEA model is applied in this study. In each DEA model, only the obser- 5 vations in the same year will be incorporated. All the OTE, PTE, and SE 6 scores are obtained from the annual frontier constructed by DMUs in the 7 same year. Therefore, eff iciency scores are relative measures for a DMU to 8 compare to other DMUs. Changing the number of DMUs may change the 9 relative performance of a DMU since it will compare to another eff iciency 10 frontier. 11 12 3.4. Data collection 13 The operating models are divided into the three types of mobile-only, 14 fi xed-only and fi xed-mobile, with nine telcos selected for each model and 15 samples taken from the three regions of Asia-Pacifi c, Europe and Amer- 16 ica. Except for Eircom Ireland and Telmex Mexico, all DMUs are retrieved 17 from the April 2, 2008 issue of Forbes 20003 with its ranking of the top 18 2000 companies in the telecom industry. Therefore, there are twenty-seven 19 DMUs per year before 2004, but from a series of mergers and acquisitions 20 the original DMUs became twenty-three after 2004, and a total of 209 21 DMUs were observed over the eight-year period of 2000-2007. 22 NTT Corp. and NTT DoCoMo, which are included in the top 5 opera- 23 tors by revenues in Forbes 2000, are in fact both independent companies 24 (please see Appendix 1). Of the fi xed-only carriers, BT, PCCW, Eircom and 25 Telmex had sold all of their mobile shareholdings, while the others still 26 owned a percentage of mobile shareholdings (please see Table 3a). Alltel 27 and Verizon Wireless agreed to join to become a single wireless company 28 as of June 7, 2008. Nextel had been merged with Sprint and renamed as 29 Sprint Nextel, but the net income had a defi cit of negative values of $2,006 30 million USD in 2004 and $29,580 million USD in 2007 according to the fi - 31 nancial reports, therefore it was not used as observed DMUs. The key mo- 32 bile-only carrier-Vodafone is ignored in this study because it had negative 33 values of operating income (EBIT) and net income during the period of 34 2000-2003. In addition, its mobile penetration of the U.S. is low only at 54% 35 during 2004. Therefore more Asian mobile operators were selected as the 36 observed DMUs to better represent the comparison of relative operating 37 38 3Forbes 2000: new issue of March 25, 2007 is a comprehensive rating of the world’s biggest 39 and most powerful companies measured by a composite ranking of sales, profi ts, assets, and 40 market value spanning 51 countries and 27 industries (http://www.forbes.com). FIXED-MOBILE TELCOS 17

1 performance. As fi xed-mobile telcos, Portugal Telecom and Nor- 2 way also own cable . 3 All carriers’ fi nancial data for each fi scal year4 are retrieved from Eq- 4 uity Research of UBS Investment Bank.5 The data include total assets, CA- 5 PEX, revenue, EBITDA, EBIT, and net income and are measured in US$ 6 million. The input variables of yearly employee numbers are from carriers’ 7 annual reports given on their websites. 8 All DMUs to be observed should be consistent during these eight 9 years of 2000 to 2007. The amount of net income closely tied to EPS (earn- 10 ings per share) distributed to the investment public is an important mea- 11 surement of the enterprise’s operating performance. The net incomes for 12 many DMUs were negative in fi nancial year 2001, but the DEA approach 13 does not allow any negative variable value. Only the largest negative value 14 for an output is treated as 0. The remaining output values are normal- 15 ized into positive values between 0 and 1. The technique of normaliza- 16 tion adopts ‘upper limit eff ect measure’ to settle the negative output value 17 problem as shown in Equation (4) (Zeleny, 1982): 18 yy- 19 yt = ra r,min , (4) ra yy- 20 rr,,max min

21 where yr,min is the minimum value among output r of all DMUs in the 22 same year; yr,max is the maximum value among output r of all DMUs in t 23 the same year; yra is the actual output r value for DMU a; and yra is the 24 normalized output r value of DMU a. 25 26 4. Empirical results 27 28 4.1. Eff iciency scores 29 The DMUs observed are 28 global telcos during 2000-2004 and some 30 of which merged to become 23 DMUs for the period 2005-2007. They 31 encompass three operating models, and have eight-year descriptive statis- 32 tics, relevant correlation and the resulting eff icient value from DEA linear 33 programming. 34 35 36 37 4Financial year ending time: data end on March 31 for NTT Corp, DoCoMo, BT, KDDI, SingTel, and Telstra end on June 30, and other telcos’ data end on December 31. 38 5UBS Investment Bank Research: covers more than 3000 companies worldwide and has 39 details on valuation, strategy, and economics. (www.ubs.com: Equity/Research/Sectors/ 40 Telecommunication) 18 C. K. MAO, J. L. HU AND C. M. CHEN

1 (1) Descriptive Statistics 2 Descriptive statistics include mean, minimum, maximum, Std. Dev. 3 and N (the number of DMUs) for all input and output variables. The 4 largest negative values are normalized as 0 by the ‘upper limit eff ect 5 measure’. The descriptive statistics are shown in Tables 7. 6 (2) Isotonicity Test 7 8 The correlation coeff icients between an input and an output over 9 eight years are all positive, complying with isotonicity property. That 10 is, an output must not decrease with an increase in any input. All the 11 inputs and outputs in our analysis satisfy the isotonicity property. 12 Adding an extra DMU will not change the original eff iciency values 13 of the original DMUs generated by DEA linear programming; this is 14 true only in the case whereby continuously adding input resources 15 does not result in a decrease in output. Some of the net-income out- 16 puts for DMUs from 2001 and 2002 have negative values and thus 17 there is a little lower correlation coeff icient between net income and 18 other input variables. All the correlation values are shown in Table 8. 19 (3) Eff iciency Comparison 20 Eff iciency score values between 0 and 1 are calculated using the DEA 21 method, and 1 represents the overall eff iciency value (Coelli et al., 22 1998). All the OTE scores obtained by DEA are shown in Appendix 2. 23 24 This research has categorized diff erent types of DMUs to DEA lin- 25 ear programming and the results show a trend similar to Figure 3. For 26 example, the observed samples for mobile-only carriers changed to KDDI 27 28 Table 7 29 30 Descriptive statistics for the years 2000-2007 (US$ mn) 31 Variables Mean Minimum Maximum Std. Dev. N(year) 32 2000-2004 2005-2007 33 Total Assets 31,915 1,359 275,641 3,800 28 23 34 CAPEX 5,036 98 20,700 3,989 28 23 35 Employees 53,843 774 309,050 8,517 28 23 36 Revenue 23,620 840 118,928 23,764 28 23 37 EBITDA 9,380 207 33,783 7,764 28 23 38 EBIT 8,815 0 21,320 7,583 28 23 39 Net Income 2,729 0 14,183 1,980 28 23 40 FIXED-MOBILE TELCOS 19

1 Table 8 2 Correlation among inputs and outputs during 2000-2007 3 4 Variables Revenue EBITDA EBIT Net Income 5 Total Assets 0.90788 0.89692 0.82132 0.74408 6 APEX 0.92156 0.91604 0.80944 0.70170 7 Employees 0.82474 0.86535 0.87684 0.81335 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Figure 3 28 OTE average scorings for three business models 29 30 31 and Vimpelcom (Russia), even without the Taiwan mobile carrier Far 32 EasTone (the eff iciency is 1.000); samples for fi xed-only carriers changed to 33 Belgacom and Swisscom AG, and samples for telcos changed to Telekom 34 Austria, TDC, and Telkom Indonesia. The average OTE values over the 35 eight years show a trend similar to the graph in Fig. 3. This means that the 36 observed samples chosen for this research are representative. 37 Relative to mobile-only or fi xed-only, fi xed-mobile telcos have better 38 eff iciency in 2002, 2003, and 2004. Telcos own mobile, Internet broadband, 39 and data growth markets, and can receive economic benefi t from a larger 40 scale of operation. Dobardzie and Lee (2004) state that the convergence 20 C. K. MAO, J. L. HU AND C. M. CHEN of fi xed-line and mobile (FMC) services presents fi xed-mobile telcos with a golden opportunity not only to generate new revenue streams and act as ‘one-stop shopping’ for customers’ wired and wireless needs, but also to defend themselves eff ectively against mobile substitution. The conver- gence of fi xed-line and mobile in infrastructure, organization, and service, as well as the transition of telecom regulation will be key trends in the future.

4.2. Fixed-mobile can leverage resources Fixed-mobile telcos can leverage various resources, including net- work infrastructure, human resources, and multimedia content, to reduce operating costs and can utilize the same marketing channel to bundle fi xed-line, data, and mobile services to attract customers. Had DoCoMo not separated from NTT in October 1998, NTT could have transferred the excess manpower of NTT fi xed-line to DoCoMo, thereby alleviating the problems arising from privatization and becoming a fi xed-only operation as of November 2000. NTT set up the regional Order Taking & System Operation in May 2002 as NTT and transferred 60,000 em- ployees, including those aged 51 and over, with a 15%-30% pay cut to NTT Outsourcing. DoCoMo added a large number of staff for the growing mo- bile market. The number of employees for DoCoMo increased from 9,342 in year 1998 to 22,100 in year 2007. DoCoMo added 5,002 employees in 2000 and 2,915 in 2001.

4.3. Fixed-mobile service integration The telecom industry is currently involved in a quickening trend to integrate fi xed-line and mobile services. Softbank Group was origi- nally only an ISP to operate broadband service. In May 2004 Softbank announced it was acquiring Japan Telecom, the second fi xed-line opera- tor. It received the 3G license issued by MHAPT (Management, Home Aff airs, Posts and Telecommunication) and merged with Vodafone in Japan to immediately acquire Vodafone’s mobile subscribers and thus entered the 3G market to compete with DoCoMo. Softbank has been moving to become an integrated carrier owning both the fi xed-line and mobile businesses. Strategies for fi xed-line and mobile services have al- ways been diff erent, but this began to change in the second half of 2004. Fixed-line carriers are trying to stop the decline in fi xed-line revenue by integrating services and to satisfy the customers’ experience of seamless communication. FIXED-MOBILE TELCOS 21

1 (1) France Telecom: Because FT owns 100% of Orange SA, it can take 2 advantage of integrating the fi xed-line and mobile platforms to pro- 3 vide a range of new services. For example, by using GPS (Global Po- 4 sitioning System), a customer can convey his location or decide who 5 may dial his phone. FT’s fi xed-line, wireless, and Internet networks 6 can be compatible and complementary. 7 (2) BT Group: Introduced its integrated services of fi xed-line and 8 mobile sets. The subscribers use Bluephone sets through Bluephone 9 stations which when within the range of coverage connect to BT’s 10 fi xed-line network and when outside the range will switch to Vo- 11 daphone’s GSM or 3G networks. Subscribers using the same Blue- 12 phone terminal may share the fi xed-line lower price as well as the 13 convenience of mobile communication. 14 (3) TDC (Tele Danmark Communications): A common number shared by 15 fi xed-line and mobile, single billing, and one voice mailbox. When 16 the call rings it fi rst connects to the mobile set; if the mobile set is 17 turned off then the call is transferred to fi xed-line at home. In case no- 18 body answers the call, then it will be transferred to the voice mailbox. 19 20 (4) KT: On June 1, 2009, KT announced to merge with KTF for keep- 21 ing space with global trends of fi xed/mobile convergence, and fur- 22 ther entered the new era of convergence of the wireless CDMA and 23 wire-line ADSL. 24 25 China’s government was concerned about China Mobile’s growing 26 dominance and worried over fi xed-line operators’ weakening business 27 in the domestic market. Therefore, it announced a detailed restructuring 28 plan in June 2008 creating three new reorganized telcos, China Telecom, 6 29 New , and China Mobile. 30 31 4.4. Regulation change 32 Fixed-mobile telcos avoid unnecessary procedures when dealing 33 with changes in telecom regulations. At present, countries have separate 34 licenses for fi xed-line, data, and mobile service and each is regulated by 35 36 7The fi xed-line operator of China Telecom acquired China Unicom’s CDMA business 37 with cash. The original integrated operator China Unicom keeps the remaining GSM assets 38 and will merge with fi xed-line operator in a stock exchange to form the new China Unicom. For China’s dominant mobile operator China Mobile, there is little struc- 39 tural change other than its parent company’s acquisition of China Railcom, a relatively small 40 fi xed-line operator. 22 C. K. MAO, J. L. HU AND C. M. CHEN

Figure 4 Regulation change in telecom and broadcasting industries

its own rules. In the face of the integration of voice, data, and video, one may foresee that telecom regulation will change from vertical regulation to horizontal integration. A single license will permit the off ering of in- tegrated fi xed-line, data, mobile and broadcasting services. Aggressive operators will be able to establish vertical divisions of electronic commu- nication in infrastructure, network, application and content, and provide mutual support to create new revenue sources. Figure 4 illustrates regula- tion changes for the convergence of electronic communication industries and broadcasting television industries:

5. Concluding remarks This study verifi es that fi xed-mobile telcos are more competitive than mobile-only or fi xed-only carriers only for 2002-2004, while mobile- only carriers have relatively better eff iciency than fi xed-mobile telcos for 2005-2007. Nevertheless, the ARPU of 3G is better than that of 2G follow- ing subscribers’ switch from 2G to 3G. Fixed-line carriers have better ef- fi ciency scores than mobile-only carriers in 2003, but without additional revenue from mobile operations, their scores are not as good as those of the fi xed-mobile telcos. This proves that the decision not to spin-off mo- bile operations from fi xed-mobile operations is correct. Even if the relative eff iciencies of mobile-only carriers are better than those of fi xed-mobile FIXED-MOBILE TELCOS 23

1 telcos during 2005-2007, fi xed-mobile telcos can, however, take advantage 2 of the combined platforms of fi xed-line, mobile and Internet to extend and 3 integrate their networks, human resources, and content to provide diversi- 4 fi ed product/service off erings. Furthermore, they can bundle rates, thus 5 continuing to dominate the development of domestic fi xed-line and mo- 6 bile markets. 7 In the future, one may anticipate that a single operating license will 8 authorize the provision of the integrated services of fi xed-line, data, 9 mobile and broadcasting. Fixed-mobile telcos will have one less procedure 10 to go through to meet changing telecom regulation requirements. New 11 market competitors have installed all new IP fi ber networks to provide 12 cumulative services such as broadband, VoIP, Pay-TV, and E-1 to incor- 13 porate data and Wireless/WiMax over their networks, and will become 14 serious challengers to the fi xed-only carriers. As the line between fi xed- 15 line and mobile services begins to blur, the technical advance of WiMax 16 may replace DSL and 3G for data service. Although the little per minute 17 price diff erence between mobile and fi xed-line will aid the Fixed to Mo- 18 bile Substitution (FtM), bundling broadband services with free VoIP will 19 entice customers back to fi xed-line and will cause Mobile to Fixed Substi- 20 tution (MtF). If VoIP is used extensively in mobile communication, it will 21 hurt mobile-only carriers the most. Fixed-mobile telcos moving toward 22 establishing an all IP Fiber network infrastructure will have more oppor- 23 tunities to provide seamless integrated voice, data and mobile services, 24 and will be more likely to create competitive obstacles for single operation 25 carriers. Therefore, from the long-term perspective the future is promising 26 for fi xed-mobile service carriers. 27 One limitation of this study is that there are not as many leading 28 fi xed-mobile service carriers worldwide for the 2000-2004 period as there 29 are fi xed-only or mobile-only carriers available for observation samples. 30 However, the appearance of free on-line voice software like P2P caused 31 the incumbents to speed up and introduce VoIP to the mass market in the 32 second half of the year 2004. Since the data of this empirical research end 33 at fi nancial year 2007 (some data end on March 31, 2008; Telstra ends on 34 June 30, 2008), the questions of how VoIP displaces PSTN or how carriers 35 might migrate to triple-play services of integrated voice, data and video 36 have not been discussed in depth in this study. Furthermore, the three- 37 year observation period (2005-2007) is insuff icient time for evaluating the 38 patterns of fi xed-mobile service after a series of merger that occurred. 39 These limitations and topics are interesting subjects for further research 40 and investigation. 24 C. K. MAO, J. L. HU AND C. M. CHEN Appendix 1 Telecom rankings in Forbes 2000 (April rankings in Forbes 2, 2008 issue) Telecom 12 1 U.S.A AT&T AT&T U.K U.S.A KT Telecommunications S.Korea Vodafone 12 1 22 20 407 Verizon 34 372 Communications U.S.A 48 3 49 2 Canada 66 Spain 28 Movil 538 78 4 106 Telefonica 5 156 France America Mexico Swisscom 6 163 9 Nextel 7 Canada Japan 168 Switzerland U.S.A. Telecom France 8 Telstra 32 584 31 Sprint 578 China 172 Australia Italy 375 215 12 BCE 10 Canada NTT Group U.K 437 224 13 11 China Mobile Telecom 225 21 China Telenor Italia Noway Telecom 251 15 23 Germany BT Group China 264 Taiwan 444 Chunghwa 14 Japan 522 34 China Telecom KDDI 614 Saudi 294 17 Telecom 524 Telecom 346 Netherlands 574 24 16 KPN 25 Royal Group China Netcom Greece 558 Hellenic 36 26 656 359 537 Saudi Arabia Sweden U.S.A 18 30 S.Africa Russia 29 Group TeliaSonera 27 Mexico 19 Canada 587 MTN Group Communications Qwest China 619 Portugal Singapore Carso Global JSFC Sistema Communications 33 Rogers Telecom Singapore 35 Telecom Portugal China Unicom Kuwait 729 673 Denmark 38 Zain Group TDC Group 37 Indonesia Belgium Indonesia Telekom Belgacom Forbes Telecoms Telecoms Forbes Ranking Country Telcos Ranking Ranking Country Telecoms Forbes Telcos FIXED-MOBILE TELCOS 25

Appendix 2 The OTE scores in the 2000-2007 Period

OTE (crs)/Year 2000 2001 2002 2003 2004 2005 2006 2007 SK Telecom 0.308 0.957 1.000 0.680 1.000 1.000 1.000 1.000 NTT DoCoMo 1.000 0.791 0.457 0.697 0.777 0.865 0.946 0.972 China Mobile (HK) 0.692 0.409 0.475 0.580 0.752 0.987 1.000 1.000 Taiwan Cellular Corp. 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 Far EasTone 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 Telefonica Moviles 0.101 0.502 1.000 0.631 0.780 0.816 0.875 – Telecom Italia Mobile 0.485 1.000 1.000 0.664 0.682 – – – Nextel 1.000 1.000 0.757 1.000 0.926 – – – Verizon Wireless 1.000 1.000 0.838 1.000 1.000 – – –

Average 0.732 0.851 0.836 0.806 0.880 0.945 0.970 0.994

KT Corp. 0.307 1.000 1.000 1.000 1.000 0.654 0.715 0.519 NTT Corp. 1.000 1.000 0.982 1.000 1.000 0.640 0.708 0.685 BT Group 0.776 1.000 0.533 1.000 1.000 1.000 1.000 0.669 Telecom Italia 1.000 1.000 0.496 1.000 1.000 – – – France Telecom 0.760 1.000 0.842 0.835 – – – – Eircom Ireland 1.000 1.000 1.000 1.000 0.926 0.486 0.563 0.990 Bell South 0.449 0.682 0.653 0.699 0.695 – – – SBC 0.466 0.420 0.413 0.985 0.986 – – – Telmex Mexico 0.624 0.733 0.472 0.680 0.765 0.840 0.634 1.000 Verizon Communications 0.394 0.377 0.418 0.447 0.635 – – –

Average 0.678 0.821 0.681 0.865 0.890 0.724 0.724 0.773

China Unicom 0.391 0.118 0.346 0.908 1.000 0.950 0.848 0.896 Chunghwa Telecom 1.000 1.000 1.000 1.000 1.000 0.874 0.961 0.987 Sing Tel 1.000 1.000 1.000 1.000 1.000 0.921 1.000 1.000 Telstra 0.755 0.556 0.662 0.565 0.836 0893 0.987 0.879 Telenor Norway 0.512 1.000 1.000 1.000 1.000 0.694 0.788 0.794 Deutsche Telekom 0.693 1.000 1.000 1.000 0.854 0.639 0.774 0.848

(Continued) 26 C. K. MAO, J. L. HU AND C. M. CHEN

1 Average 0.678 0.821 0.681 0.865 0.890 0.724 0.724 0.773 2 3 Portugal 4 Telecom 0.505 0.405 1.000 1.000 0.708 0.739 0.787 0.796 5 Alltel U.S.A 0.783 1.000 1.000 1.000 1.000 – – – 6 BCE Canada 0.552 0.503 0.633 1.000 1.000 0.837 0.865 0.866 7 Telefonica Moviles - – – – – – – 0.896 8 Telecom Italia – – – – – 0.562 0.582 0.592 9 Verizon 10 Communications – – – – – 0.405 0.613 0.698 11 France Telecom – – – – 1.000 0.865 0.881 0.824 12 New AT&T (SBC) – – – – – 0.678 0.783 0.892 13 Average 0.688 0.731 0.849 0.941 0.940 0.755 0.822 0.844 14 Note: Fixed-only averaged OTE for the 2000-2004 period, excluding Verizon Communications. 15 16 17 18 References 19 [1] A. Charnes, W. W. Cooper, E. Rhodes, Measuring the eff iciency of 20 decision making units, European Journal of Operations Research 2(6) 21 (1978), pp. 429–446. 22 [2] T. Coelli, A Guide to DEAP Version 2.1: A Data Envelopment Analysis 23 (Computer) Program, Armidale: University of New England, 1996. 24 25 [3] T. Coelli, D.S. Rao, G.E. Battese, An Introduction to Eff iciency and Pro- 26 ductivity Analysis, Boston: Kluwer Academic Publishers, 1998. 27 [4] A. Dobardzie, J. Lee, KT’s Foray into Fixed-Mobile Convergence, 28 Ovum Wireline strategy@ovum, August 2, 2004, OVUM Research. 29 [5] M. J. Farrell, The measurement of productive eff iciency, Journal of the 30 Royal Statistical Society. Series A, 120 (3) (1957), pp. 253–290. 31 [6] D. I. Giokas, G. C. Pentzaropoulos. Evaluating productive eff iciency 32 in telecommunications: evidence from Greece, Telecommunications 33 Policy 24 (8-9) (2000), pp. 781–794. 34 35 [7] J. L.Hu and W. K. Chu, Eff iciency and productivity of major Asia- Pacifi c 36 telecom fi rms, Chang Gung Journal of Humanities and Social Sciences, 1(2) 37 (2008), pp. 223–245. 38 [8] D. Lien, Y. Peng, Competition and production eff iciency telecommu- 39 nications in OECD countries, Information Economics and Policy 13 (1) 40 (2001), pp. 51–76. FIXED-MOBILE TELCOS 27

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