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An efficiency comparison of direct and indirect channels in Taiwan insurance marketing
Chiang Ku Fan and Shu Wen Cheng
Graduate Institute of Finance and Insurance, Shih Chien University, Taipei, Taiwan, Republic of China
Abstract
Purpose – The purpose of this paper is to compare the efficiency of bancassurance, an indirect marketing channel formed through the creation of subsidiaries, with an insurer’s own team, a direct marketing channel, in the Taiwan insurance sector. Design/methodology/approach – This paper uses the Charnes, Cooper, and Rhodes (CCR) model to measure the decision-making units’ (DMU) operating efficiency. Findings – The three major findings are: the efficiency score of a direct marketing channel is significantly higher than that of a comparable indirect marketing channel. The efficiency relationship between the indirect marketing channel and the direct marketing channel is independent. A marketing efficiency evaluation, when divided into different marketing channels for evaluation, provides meaningful results for marketing decision-makers. Originality/value – By comparing the efficiency between two different insurance marketing channels, managers in life insurance companies can make a more informed choice. Keywords Direct marketing, Marketing, Insurance, Taiwan Paper type Research paper

Comparison of direct and indirect channels 343

Introduction Bancassurance, a method of distributing insurance products, has become a global trend that is gradually breaking down traditional barriers in how businesses supply financial products and services (Benoist, 2002). The last 15 years have witnessed many changes in how the financial services industry in Europe, the USA, and Latin America is organized, including the closer integration of banks and insurers. For example, bancassurance is highly developed in France where banking networks account for a significant proportion of life insurance sales, although it is taking longer to make inroads into the non-life market (Benoist, 2002). In the UK, traditional barriers between banking and insurance are disappearing and being replaced by integrated institutions offering a range of services (Morgan, 1994; Salomon, 1990). In the USA, deregulation under the Gramm-Leach-Bliley Act (GLBA) of 1999 legalized bancassurance and is likely to lead to its geographic spread. The new law allows the formation of financial holding companies that can offer a wide range of financial products, including underwriting, insurance and securities, commercial and merchant banking, investment in real estate, and other financial activities (Field et al., 2007). Bancassurance is flourishing in Argentina, and in Brazil large banks play an important role in distributing insurance products. Bancassurance is a growing sector in Mexico due to the role banks played in the creation of pension funds following pension reform in 1997. Joint ventures between local and foreign

Direct Marketing: An International Journal Vol. 3 No. 4, 2009 pp. 343-359 q Emerald Group Publishing Limited 1750-5933 DOI 10.1108/17505930911000900

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insurance companies in Mexico were common prior to 2000, and foreign insurers have established many partnerships with Mexican banks (Benoist, 2002). The bancassurance model for financial firms has become more important for Taiwan’s financial services industry since passage of the Merger Law of Financial Institutions and the Financial Holding Company Law in 2000 and 2001, respectively. As a result of these two laws, insurance companies, banks, and securities firms can affiliate under common ownership and cross-sell financial products and services to existing and potential customers. “Over-banking” in Taiwan has also contributed to the growth of bancassurance. Most banks were owned by the Taiwan government before 1991 (Chen and Yeh, 1998). Following the Commercial Bank Establishment Promotion Decree in 1991, the banking environment changed substantially when private local and foreign banks entered the Taiwan market The Decree, which acted as a deregulation trigger, set off the over-banking problem. In order to eliminate the extra capacity and inefficiency resulting from over-banking, other non-traditional businesses, such as bancassurance, became more common in Taiwanese bank operations. In order to enter the insurance market rapidly and build marketing channels cost-effectively, new insurance entrants adopted the bancassurance model. The banking industry in Taiwan has experienced tremendous change and increased earnings growth from insurance products. Banking networks represent the major distribution channel for life insurance products. According to a report by the Financial Supervisory Commission of the Republic of China, bancassurance accounted for 34 percent of total first year life insurance premium income in Taiwan in 2007, behind insurance companies’ own sales teams’ revenue of 60 percent but ahead of brokers and general agents, who had less than four percent. The number of insurance sales representatives employed by agencies and brokerages tripled to about 142,000. The increased number of agencies and brokerages affiliated with banks account for 70 percent of all new entries. The growth rate of insurance premiums from these banking agents now exceeds that from traditional underwriters of insurers. Before 2002, the model of an insurance selling channel was “leveraged life distribution,” where (Flur et al., 1997) the leading player was a large life insurance company with a range of effective distribution channels, including insurance companies, their own sales representative, general agencies, and independent agencies or brokerages. According to the Taiwan Insurance Institute (TII), from 1995 to 2001 less than 1.5 percent of total premium income came from agencies and brokerages. The remaining premiums were earned through insurance companies’ own sales representatives. After deregulation in 2002 and the emergence of bancassurance, Taiwan companies migrated to leveraged bank distribution as a primary selling channel. This model requires a large bank with a range of effective distribution channels, including branches, mail, phone, automatic teller machines, and a sales force. Prior empirical studies evaluated the efficiency of bancassurance from the bank viewpoint, assessing its profitability as a bank product. But since bancassurance is also an insurance company product, we need to assess it from the insurance viewpoint as well. McKillop et al. (1996) investigated cost efficiency in large Japanese banks and found that different cost function specifications led to different results. Bergendahl (1995) claimed that the economic reasons for banks selling multiple products included efficiently using fixed capacity resources, customer demand for several products from

a single channel, and product combination strategy. On the other hand, most insurance companies believe that increasing the number of marketing channels to attract more customers and sales represents the way to profitability. Besides, using their own sales representatives, insurance companies try to sell products through banks. Bancassurance becomes an insurer’s second marketing channel for selling insurance. But is the bancassurance channel (indirect marketing channel) more profitable than an insurer’s own sales representatives (direct marketing channel)? No research has yet compared the efficiency between different insurance marketing channels. To fill this research gap, our study focuses on the bancassurance model formed through the creation of subsidiaries and compares the efficiency of this model to that of direct marketing channels in Taiwan. This study employed the data envelopment analysis (DEA) approach to compute the efficiencies of indirect marketing channels (through bancassurance) and direct marketing channels (through an insurer’s own sales representatives) separately. The empirical results confirm the efficiency of both indirect marketing channels through subsidiaries and direct marketing channels through an insurer’s own sales representatives in Taiwan. By comparing the efficiency between these two different channels, the marketing decision-maker in life insurance companies can make a more informed choice. Literature review Direct and indirect marketing in the Taiwanese Insurance Industry Direct marketing refers to the movement of goods and services form producers to customers without intermediaries or middlemen (Kotler and Keller, 2006; Bearden et al., 2004). It allows marketers to obtain a more direct response from customers and allows customers to browse through a greater selection of products than retail outlets carry. Customers can also shop in the comfort of their homes or offices (Wilkinson et al., 2007). Direct marketing is thus becoming an integral element in the marketing manager’s arsenal (Scovotti and Spiller, 2006). Today, direct marketing is a fundamental tool in a growing variety of business, including banking, employment services, home mortgages, and insurance (Bearden et al., 2004). According to Thomas (2007), direct marketing is almost always more efficient than mass marketing. As markets become increasingly fragmented, more firms use a strategy of multiple channels to appeal to as many potential buyers as possible. The idea is to allow customers to buy the way they want to and where they want to (Bearden et al., 2004). In Taiwan, an insurer’s own sales representatives and bancassurance are two major marketing channels for insurance companies. The sales representatives, as employees of the insurance company, are considered a direct marketing channel. Bancassurance, which is sold through an intermediary bank, is an indirect marketing channel. Bancassurance refers to a method of distributing insurance through banks. A bank becomes an insurer’s marketing channel as well as an intermediary between the insurance company and customers. Even though deregulation has effectively removed restrictions on combining banking and insurance, banks in Taiwan are prohibited from directly distributing insurance products through their branch network. They cannot offer banking products or services directly through insurance companies either. However, according to the report of the Financial Supervisory Commission in 2007, over 80 percent of banks

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formed alliances with insurance agencies or brokerages where they usually have 100 percent ownership of the agency or brokerage subsidiaries. The bancassurance business practices of Taiwanese banks clearly differ from those of universal-type financial firms that provide a range of financial products or services within the same firm. Banks and insurance companies may engage in bancassurance activities under various strategic umbrellas. According to the Organization for Economic Cooperation and Development (OECD) (1992), for banks the main structural operations for bancassurance may take the form of minority or majority holdings, full-fledged acquisition, creation of subsidiaries, or joint ventures with holding companies. Owing to the prevalence of bancassurance mergers to both the European and the American financial systems (Field et al., 2007), most studies deal with bancassurance formed through mergers and acquisitions and transactions (Carow, 2001; Field et al., 2007; Boubakri et al., 2008). Few researchers have explored the efficiency of bancassurance as an alternative strategy of insurance companies, focusing instead on bancassurance as a standard bank product (OECD, 1992; Figure 1). Background on efficiency measurement Efficiency (or cost-efficiency) is defined either as a characteristic of organizational outputs (“effectiveness,” “equity,” “quality,”, etc.) or inputs (“economy,” “cost”) or as a relationship between outputs and inputs (Meimand et al., 2002). In each case, efficiency can be viewed as a transformation ratio:
[. . .] what has been produced or the value of what has been produced per unit of what has been consumed, or the value of what has been consumed in the process of production (Kao and Hwang, 2008).

The efficiency measurement has been applied to numerous fields, including marketing ´ (Keh et al., 2006; Wu, 2003), athletics (Garcia-Sanchez, 2007), technology (Jerzmanowski, 2007), information systems (Gebauer and Schober, 2006; Philip, 2007), public policy (Durlauf, 2005; Vine et al., 2003), banking efficiency (McCune, 2007; Yao et al., 2007), bancassurance, and even insurance. The efficiency of bancassurance Many studies of bancassurance focused on benefits or enhanced value in bank-insurance consolidation. Bergendahl (1995) claimed that the economic reasons for banks selling multiple products include efficiently using fixed capacity resources, customer demand for several products from a single channel, and product combination strategy. In contrast, early research findings of Baumol et al. (1982) implied that there was no benefit from bank-insurance consolidation for existing insurance companies.
Bancassurance Serving with insurance

Insurer

Agency

Bank

Customers

Figure 1. Bancassurance channel in Taiwan

Creating a subsidiary

But Dimon (1984) proposed that spanning both short- and long-term liability/asset structures in the financial intermediation process and attracting and keeping individual customers and corporate clients make bank-insurance consolidation beneficial to both insurers and banks. Other studies of the effect of bank expansion into non-traditional industries focus mainly on the risk reduction and value enhancement effects of bank consolidation (Hughes et al., 1999; Carow, 2001; Mamun et al., 2005). Saunders and Walter (1994) and Hughes et al. (1999) show that bank consolidation is consistent with risk reduction. Felgren (1985) argued that banks had greater cost advantages in selling insurance products than insurance companies themselves because banks already have extensive branch networks. Carow (2001) found that bank stock prices after entry into the insurance industry do not change significantly. Most early research results about bancassurance agreed that banks gained benefits or cost advantages in bank-insurance consolidation, but the findings were not consistent when the studies looked at insurers’ benefits from bancassurance. The studies on bank-insurance consolidation revealed no consensus on whether bancassurance would be a profitable strategy to an insurance company. There were also many studies on the efficiency of insurance companies which evaluated the performance of various insurance business activities. The efficiency of insurers Most studies employed the DEA to explore the efficiency of insurers’ business activities (Figure 2). Pree et al. (1995) used the DEA to help insurance companies monitor and control legal service and costs. Cummins et al. (1999) used the DEA to examine the relationship among mergers and acquisitions, efficiency, and economies of scale in the US life insurance industry over the period 1988-1995. They found that acquired firms achieved greater efficiency gains than firms that were not involved in M&As. Lin (2002) applied the DEA to measure efficiency scores and to examine whether life insurers in Taiwan took advantage of the new market structure after deregulation. Results showed no change for overall efficiency, no pure technical efficiency change, and no scale efficiency change after deregulation. Mahlberg and Url (2003) analyzed a panel of Austrian insurance companies from 1992 to 1999 to assess their response to the challenges of the single market for the insurance industry by means of the DEA. Their efficiency measure is likely to identify such insurance companies as inefficient compared to other companies, although these companies may offer favorable terms to consumers. Tone and Sahoo (2005) applied the DEA model to examine the performance of the Life Insurance Corporation of India and found a significant difference in the cost efficiency scores over the period 1994-2001. Brockett et al. (2005) used the DEA coupled with distribution-free rank-order statistics to study the relative efficiency of the different organizational structures used by US property
Traditional efficiency analysis Inputs Outputs 1. Business & administrative expense Incomes 2. Commission & acquisition expense

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Figure 2. The traditional DEA

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and liability insurance companies. Meimand et al. (2002) described a modified DEA process to solve the problem of assessing relative branch performance in the Accident Compensation Corporation, the New Zealand state-owned, no-fault, personal injury compensation insurance company. The factors in their DEA inputs were rehabilitation and compensation costs and number of full-time cases and claims managers in the branch. On the output side, the factors included right the first time, number of claimants managed starting each month, number of claimants starting each month expected to have left in less than 12 months, and number of weekly compensation payments meeting the target dates. Yao et al. (2007) used a panel data set of 22 insurance companies over the period 1999-2004 to evaluate their efficiency by applying a DEA approach. In their study, labor and capital were input factors while premium, benefits, and claims costs were output factors to measure the efficiency of insurance companies. Similarly, by using the DEA approach, Jeng et al. (2007) examined the efficiency changes of US life insurers before and after demutualization in the 1980s and 1990s. The inputs used in their model were labor, business service, eEquity cost, assets and underwriting and investment expenses. On the output side, the factors included benefit payments and return on assets. To gain valuable managerial insights for insurers, the latest studies used a modified DEA approach to evaluate the efficiency of an insurance company. Hwang and Kao (2006) and Kao and Hwang (2008) modified the conventional DEA by taking into account the series of relationships of the two sub-processes within the whole process (Figure 3). The relational model developed in their paper was more reliable in measuring the efficiencies and could identify the causes of inefficiency more accurately. The inputs used in the first stage are operating expense and insurance expense. The outputs of the system, which were also the outputs of the second stage, are underwriting profits and investment profits. There were also two intermediate products in the system, which were the outputs of the first stage as well as the inputs of the second stage: direct written premiums and reinsurance premiums. Wu et al. (2007) and Yang (2006) employed a two-stage DEA approach to assess production and investment efficiency simultaneously for the Canadian life and health insurance industry. This model allowed integration of the production and investment performance for the insurance companies, provided management with an overall performance evaluation and suggested how to achieve efficiency systematically for the insurers involved. The input factors in their DEA model were labor expense, general operating expense, capital equity, and claims incurred. The outputs were net premiums written and net income.
Two-stages efficiency analysis Marketability efficiency Inputs 1. Business & administrative expense Outputs 1. Direct premiums written 2. Reinsurance premiums Profitability efficiency Inputs 1. Direct premiums written 2. Reinsurance premiums Output 1. Net underwriting premium 2. Investment income

Figure 3. The two-stage DEA

2. Commission & acquisition expense

Summary of literature review When insurance companies sell insurance through their own sales representatives, it is considered direct marketing. When they sell insurance through bancassurance, it is considered indirect marketing. Previous studies of bank-insurance consolidation reported that bancassurance is a profitable strategy for a bank, but there is no consensus on whether insurers gain benefits or cost advantage in selling insurance product through bancassurance channels. Early studies on the efficiency of insurance, no matter what stage they evaluated, did not focus on insurance marketing channels, nor did they mention the efficiency comparison between direct and indirect marketing channels. Figure 4 shows that bancassurance is banks selling insurance for insurers. When banks sell bancassurance, business and administrative expenses come out of their profits. Insurers have these same expenses plus the added cost of commission and acquisition expense? But when insurers’ own sales representatives sell bancassurance, the cost to the insurer is less.

Comparison of direct and indirect channels 349

Marketability efficiency

Inputs from insurer 1. Business & administrative expense 2. Commission & acquisition expense

Inputs from bank Business & administrative expense

Output Bancassurance Premiums

Indirect marketing channel efficiency Inputs from insurer 1. Business & administrative expense 2. Commission & acquisition expense

Output Premiums

Own sales Representatives

Direct marketing channel efficiency

Figure 4. Efficiency comparison between direct marketing channels and indirect marketing channels

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The inputs and outputs used for evaluating the efficiency of insurance companies in prior studies are reported in Table I. This study selects some appropriate inputs and outputs to assess the efficiency of traditional selling channels and bancassurance channels. Methodology The DEA methodology According to the concept of efficiency for the performance evaluation method, the main comparison is between input-output relations. The DEA efficiency assessment model used envelope line technology to replace the general economics of individual production function, a theory based on Farrell’s (1957) work on the concept of technical efficiency. Three scholars (Charnes et al., 1978) expanded the single input single output model to the concept of multiple inputs-multiple outputs, creating a form to assess the decision-making units’ (DMU’) relative efficiency. This can use non-identical units for a number of inputs and outputs various renovation to a single value, which was obtained for a value prefecture institutions organizational efficiency, commonly known as Charnes, Cooper, and Rhodes (CCR) model. This study used the CCR model to measure the DMU’ operating efficiency. The theoretical description follows.
Inputs Outputs References Meimand et al. (2002)

350

Table I. The inputs and outputs used for evaluating the efficiency of insurance companies

1. Right first time 1. Rehabilitation and compensation 2. Number of claimants managed costs starting this month 2. Number of full-time cases and claims 3. Number of claimants starting this managers in the branch month expected to have left in less than 12 months 4. Number of weekly compensation payments which have met the target timeliness 1. Direct written premiums 1. Business administration expenses 2. Reinsurance premiums received 2. Commissions 3. Acquisition expenses 1. Labor 1. Premium 2. Capital 2. Benefits 3. Claim costs 1. Labor expenses 1. Net premiums written 2. Net income 2. General operating expenses 3. Capital equity 4. Claims incurred 1. Direct written premiums 1. Operating expenses 2. Reinsurance premiums 2. Insurance expenses 3. Underwriting profit 3. Direct written premiums 4. Investment profit 4. Reinsurance premiums 1. Labor 1. Benefit payments 2. Business services 2. Return on assets 3. Equity cost 4. Asset 5. Underwriting and investment expenses

Hwang and Kao (2006) Yao et al. (2007) Wu et al. (2007)

Kao and Hwang (2008) Jeng et al. (2007)

Charnes et al. (1978), following Farrell (1957), assessed the efficiency of the theoretical basis, through two inputs, the outputs of a single model, and expanded to a multiple inputs and multiple outputs model, the fixed pay scale under the assumption that using linear programming method, the production border, and to assess each unit for the relative efficiency, the law is known as the DEA model CCR. Suppose k DMUs, each DMU k ðk ¼ 1; · · · ; N Þ; using the m input species xik ði ¼ 1; · · · ; m; k ¼ 1; · · · ; N Þ . 0, production n outputs yrk ðr ¼ 1; · · · ; s; k ¼ 1; · · · ; N Þ . 0, as can be in a DMU k expected that the efficiency values are: Pn ur yrk Max H k ¼ Pr¼1 m i¼1 vi xik subject to Pn ur yrk H k ¼ Pr¼1 #1 m i¼1 vi xik ð1Þ

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yrk, amount of the r th output for the k th DMU; xik, amount of the i th input for the k th DMU; ur, the weight assigned to the r th output; vi, the weight assigned to the i th input; 1, non-Archimedean quantity is arbitrary small positive values. Because equation (1) the scores-planning (fractional programming) model is not easy to solve, Charnes et al. (1978) converted it to the linear programming (linear programming) model: Max H k ¼ n X r¼1 n X r¼1 m X i¼1

ur yrk

subject to ur ; vi $ 1 . 0;

ur yrk 2

vi xik # 0

ð2Þ

i ¼ 1; · · · ; m; r ¼ 1; · · · ; n; k ¼ 1; · · · ; N

Equation (2) in the input items portfolio weighted average value of the one cases, the items for output weighted average portfolio maximum efficiency is used to indicate the relative value. But its limitation – the number (n þ k þ m þ l) – was significantly more than the number of variables (n þ k), can use dual conversion pairs (duality) mode, reducing restrictions on the number of convenience-type solution, as follows: ! m n X 2 X þ S ik þ S rk Min H k ¼ uk 2 1 i¼1 N X k¼1 N X k¼1 r¼1

subject to

lk xik 2 uk xik þ S 2 ¼ 0 ik

lk # 1

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1; lk ; S 2 ; S þ $ 0; ik rk

N X k¼1

lk xik 2 S þ ¼ yrk rk

ð3Þ

i ¼ 1; · · · ; m; r ¼ 1; · · · ; n; k ¼ 1; · · · ; N ; u unconstrained:

352

lk for all DMU and the best allocation of DMU combination of Equation (3) linear equations, the weights u efficiency of a practical value. S 2 and S þ are the input ik ik and output variables variance, the representative of the actual value and the best efficiency of the difference between the value that can be used to understand the inputs and outputs of the number of places for improvement. When u ¼ 1, S 2 ¼ S þ ¼ 0, the ik ik DMU stayed relatively efficient. When DMU stay relative efficiency, and can be adjusted through the following then optimum efficiency goals can be achieved: x* ¼ u* xik 2 S 2* ik ik k y* ¼ yrk þ S þ* rk rk Defining input-output factors in DEA model The input-output factors used in this paper are in Table II. Results and conclusions Based on equations (2) and (3), an evaluation of input-output information published in the “Life Insurance Review of Republic of China” by the TII was conducted. The input-output data of direct marketing channels and indirect marketing channels are shown in Tables III and IV. Results, including efficiency scores and rankings of the direct marketing channels and the indirect marketing channels evaluated by the DEA method, are shown in Table V. There are nine life insurance companies that are relatively efficient in direct marketing channels: Aegon Life, ING Life, Life Insurance Department of CTC, China Life, Shin Kong Life, Global Life, Sinon Life, Singfor Life, and Allianz President Life. The two life insurance companies which are relatively efficient in indirect marketing channels are Cathey Life and Allianz President Life. Some life insurance companies, including Global Life, ING Life, and Singfor Life, may be relatively efficient in direct marketing channels but perform poorly in indirect marketing channels. Cathey Life is the only life insurance company that performs relatively efficiently in bancassurance channels but poorly in
The direct marketing channel Outputs The indirect marketing channel Outputs 1. Premium income

S 2 , S þ , and ik ik

ð4Þ

Inputs

Inputs

Table II. Inputs and outputs used in two channels

1. Number of sales 1. Premium representatives income 2. Number of branches 3. Business and administrative expenses 4. Commission and acquisition expenses

1. Agency fee and commissions from insurers 2. Number of branches 3. Number of financial specialists 4. Operation expenses

DMU 663 1,058 15,047 1,554 312 3,354 5,536 12,024 54,579 3,181 35,360 3,213 26,228 6,515 85 14,202 985 697 1,811 861 1,224 36 862,406 199 17 34 34 23 2,317,991 7,571 8,656 1,073,777 657,046 4 63 6 2,289 50 387 22 18 125 8 407,832 1,726,253 2,984,152 21,539,918 1,077,404 9,975,193 1,833,190 14,872,046 1,461,253 359,219 702,362 2,293,418 4,805,150 13,920,353 1,940,669 20,667,440 2,057,888 7,601,018 2,911,320 640,177 6,594,178 242,679 77,902 1,392,109 6,317,577 4,105,370 43 320,612 235,942 31 498,500 785,053 30 32 3 1,337,867 973,365 7,974,846 5,180,074 1,467,436 5,867,026

(I) Number of sales representatives (person) 39,376,458 15,203,579 116,799,934 4,177,513 4,481,615 16,925,834 35,100,691 39,870,808 352,477,888 52,521,993 225,750,147 35,499,745 181,469,347 74,541,820 8,214,122 59,916,191 6,845,080 9,848,189 27,176,489 19,895,808 54,436,693

(I) Number of branch

(I) Business and administrative (I) Commission and acquisition (O) Premium expense (NT$1,000) expense (NT$1,000) income (NT$1,000)

Aegon Life New York Life ING Life Manulife Limited (Taiwan branch) 5. Winterthur Life (Taiwan branch) 6. Life Insurance Department of CTC 7. Taiwan Life 8. PCA Life 9. Cathey Life 10. China Life 11. Nan Shan Life 12. Kuo Hua Life 13. Shin Kong Life 14. Fubon Life 15. Global Life 16. MassMutual Mercuries Life 17. Sinon Life 18. Singfor Life 19. Far Glory Life 20. Hontai Life 21. Allianz President Life

1. 2. 3. 4.

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Table III. Input and output data of life insurance companies’ direct marketing

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DMU 622,411,480 479,369,138 76,322,413 5,976,932 18,992,540 20,610,926 97,138,413 193,672,983 150,288,268 724,662,312 115,846,432 3,523,130 442,960,598 1,099,233,216 11,447,678 206,571,787 82,617,688 160,350,758 170,105,999 38,025,923 2,051,472,296 1,083 824 868 1,632 507 2,327 557 2,378 620 2,028 1,732 1,673 495 2,225 2,373 533 15,973 69,137 11,236 52,835 45,217 51,226 11,115 70,277 67,014 21,012 28,370 25,680 29,956 45,207 18,097 63,292 800 19,388 125 3,203 2,096 1,576 1,498 57,007 42,190 40,022

1. 2. 3. 4.

Aegon Life New York Life ING Life Manulife Limited (Taiwan branch) 5. Winterthur Life (Taiwan branch) 6. Life Insurance Department of CTC 7. Taiwan Life 8. PCA Life 9. Cathey Life 10, China Life 11. Nan Shan Life 12. Kuo Hua Life 13. Shin Kong Life 14. Fubon Life 15. Global Life 16. MassMutual Mercuries Life 17. Sinon Life 18. Singfor Life 19. Far Glory Life 20. Hontai Life 21. Allianz President Life

Table IV. Input and output data of life insurance companies’ indirect marketing channel in Taiwan (I) Agency fee and commission from insurer (NT$) (I) Number of branch (I) Number of financial specialist (person) (I) Operation expense (NT$) 179,250,125.7 135,771,383.8 92,481,208.88 3,961,994.138 37,529,782.95 29,963,164.75 121,142,220.7 39,957,502.21 70,020,964.99 76,792,577.2 105,759,348.9 31,538,316.1 135,555,168.1 138,099,516.5 44,126,329.73 39,225,409.54 57,331,577.89 66,148,202.75 124,588,453.5 46,967,099.07 131,528,713 (O) Premium (NT$) 11,018,592,095 6,536,526,090 1,550,777,980 12,083,970 228,290,792 1,320,042,415 3,417,932,756 2,568,470,637 19,296,977,302 17,215,492,517 1,822,735,178 29,511,338 21,200,667,644 31,927,578,988 293,520,817 3,566,112,574 3,377,510,088 1,928,318,770 8,194,343,335 286,173,166 41,894,000,323

DUM 1. Aegon Life 2. New York Life 3. ING Life 4. Manulife Limited (Taiwan branch) 5. Winterthur Life (Taiwan branch) 6. Life Insurance Department of CTC 7. Taiwan Life 8. PCA Life 9. Cathey Life 10, China Life 11. Nan Shan Life 12. Kuo Hua Life 13. Shin Kong Life 14. Fubon Life 15. Global Life 16. MassMutual Mercuries Life 17. Sinon Life 18. Singfor Life 19. Far Glory Life 20. Hontai Life 21. Allianz President Life

Efficiency of direct marketing channel Score Rank 1.0375588 0.5525651 3.8618071 0.1745235 0.6745078 1.6149558 0.5453965 0.6922748 0.4291839 1.2859215 0.4711988 0.866524 1.1151603 0.8364381 1.6533419 0.3831604 1.3444489 4.4818925 0.8130196 0.5624665 1.6491851 9 16 2 21 14 5 17 13 19 7 18 10 8 11 3 20 6 1 12 15 4

Efficiency of indirect marketing channel Score Rank 0.44333433 0.34755053 0.15824621 1.57 £ 102 2 9.36 £ 102 2 0.49879969 0.27403643 0.44853633 2.56205374 0.76529365 0.12253967 6.52 £ 102 2 0.87989514 0.98889495 0.19969045 0.31838455 0.4186742 0.20804704 0.51068684 5.93 £ 102 2 1.38932089 9 11 16 21 18 7 13 8 1 5 17 19 4 3 15 12 10 14 6 20 2

Comparison of direct and indirect channels 355

Table V. Indirect marketing channel and direct marketing channel efficiency of 21 life insurance companies in Taiwan

direct marketing channels. There are six life insurance companies that perform equally poorly in both direct and indirect marketing channels: New York Life, Manulife Limited (Taiwan branch), Nan Shan Life, MassMutual Mercuries Life, and Hontai Life. The only life insurance company that performs relatively efficiently in both direct and indirect marketing channels is Allianz President Life. The researchers conducted the Mann-Whitney U test and the Spearman rank correlation test to determine whether there is a significant difference between inefficiency score and rank between direct and indirect marketing channels. Table VI shows that there is a significant efficiency score difference between the direct and indirect marketing channels ( p , 0.05). The efficiency mean of direct marketing channels is higher than that of indirect marketing channels. Table VII shows the Spearman’s rank correlation statistics, which indicate that there is no efficiency rank relationship for the 21 life insurance companies between the direct and indirect marketing channels ( p . 0.05). The Mann-Whitney U test (Figure 5) and the Spearman rank correlation test (Figure 6) indicate that the efficiency of direct marketing channels is significantly higher than that of
Efficiency score mean Direct marketing channel Indirect marketing channel 0.7620 0.4198 SD 0.26038 0.32835 Mann-Whitney U test ( p-value) 87.000 (0.001) Table VI.

Note: Mann-Whitney U test of efficiency comparison in direct marketing channels and indirect marketing channels

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indirect marketing channels. The efficiency rank of direct marketing channels is independent of indirect marketing channels. There is no efficiency rank relationship between a life insurance company’s own sales representatives and its bancassurance representatives in Taiwan. Thus, insurance companies with good efficiency in direct marketing will not necessarily perform with equal efficiency in indirect marketing. Managerial implications This study suggests four managerial implications: (1) Direct marketing is more efficient than indirect marketing. This confirms Thomas’s (2007) findings discussed in the literature review, that all successful marketing is now direct marketing. In the Taiwanese insurance environment, life insurance companies with multiple products may use a single-channel strategy in one situation and a multiple-channel strategy in another. Life insurance companies cannot, however, neglect their traditional direct marketing channels while they develop the bancassurance business. (2) The efficiency relationship between indirect and direct marketing channels is independent. Those life insurance companies that perform better in direct marketing
Direct marketing channels – indirect marketing channels Spearman’s r p-value

356

0.311 0.170

Table VII.

Note: Spearman’s rank correlation coefficients of efficiency in direct marketing channels and indirect marketing channels

5 Efficiency score 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Insurance companies Direct marketing channel Indirect marketing channel

Figure 5. The efficiency scores comparison of each insurance company between sales representatives channel and bancassurance channel

Rank of efficiency score

25 20 15 10 5 0 1 2 3 4 5

Direct marketing channel Indirect marketing channel

Figure 6. The efficiency ranks comparison of each insurance company between sales representatives channel and indirect marketing channel

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 Insurance companies

channels may not perform similarly in indirect marketing channels. How bancassurance representatives perform has nothing to do with the insurer’s own sales team but is related to the banks they select. Therefore, to perform better in indirect marketing channels, Taiwan insurers must choose appropriate partner banks. (3) The research findings suggest that a marketing efficiency evaluation of a life insurance company, when divided into different marketing channels for evaluation, can provide meaningful results for decision-makers in determining marketing strategies. (4) According to the report of the Insurance Institution of Taiwan (IIT) in 2007, the majority of products sold by insurers’ own sales representatives are life insurance products. The only product that bancassurance representatives prefer to sell is investment-linked insurance. Therefore, whether the efficiency difference in different marketing channels can be attributed to different products sold is a topic for future research.
References Baumol, W.J., Panzar, J.C. and Willig, R.D. (1982), Contestable Markets and the Theory of Industry Structure, Harcourt Brace Jovanovich, New York, NY. Bearden, B., Ingram, T. and LaForge, B. (2004), Marketing: Principles and Perspectives, McGraw-Hill, New York, NY. Benoist, G. (2002), “Bancassurance: the new challenges”, The Geneva Papers on Risk and Insurance, Vol. 27 No. 3, pp. 295-303. Bergendahl, G. (1995), “The profitability of bancassurance for European banks”, International Journal of Bank Marketing, Vol. 13 No. 1, pp. 17-29. Boubakri, N., Dionne, G. and Triki, T. (2008), “Consolidation and value creation in the insurance industry: the role of governance”, Journal of Banking & Finance, Vol. 32, pp. 56-68. Brockett, P.L., Cooper, W.W., Golden, L.L., Rousseau, J.J. and Wang, Y. (2005), “Financial intermediary versus production approach to efficiency of marketing distribution systems and organizational structure of insurance companies”, The Journal of Risk and Insurance, Vol. 72 No. 3, pp. 393-412. Carow, K.A. (2001), “The wealth effects of allowing bank entry into the insurance industry”, The Journal of Risk and Insurance, Vol. 68 No. 1, pp. 129-50. Charnes, A., Cooper, W.W. and Rhoades, E. (1978), “Measuring the efficiency of de-cession making units”, European Journal of Operational Research, Vol. 2 No. 6, pp. 429-44. Chen, T.Y. and Yeh, T.H. (1998), “Study of efficiency evaluation in Taiwan’s banks”, International Journal of Service Industry Management, Vol. 9 No. 5, pp. 402-15. Cummins, D., Tennyson, S. and Weiss, M.A. (1999), “Consolidation and efficiency in the US life insurance industry”, Journal of Banking & Finance, Vol. 23, pp. 325-57. Dimon, D.W. (1984), “Financial intermediation and delegated monitoring”, Review of Economic Studies, Vol. 51, pp. 393-414. Durlauf, S.N. (2005), “Racial profiling as a public policy question: efficiency, equity, and ambiguity”, American Economic Review, Vol. 95 No. 2, pp. 132-6. Farrell, M. (1957), “The measurement of productive efficiency”, Journal of the Royal Statistical Society, General 120, Series A, Part 3, pp. 253-81.

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Felgren, S. (1985), “Bank as insurance agencies: local constraints and competitive advances. Federal Reserve Bank of Boston”, New English Economic Review, September-October, pp. 34-9. Field, L.P., Froser, D.R. and Kolarl, J.W. (2007), “Bidder returns in bancassurance mergers: is there evidence of synergy”, Journal of Banking & Finance, Vol. 31 No. 12, pp. 3646-62. Flur, D.K., Huston, D. and Lowie, L.Y. (1997), “Bancassurance”, The McKinsey Quarterly, Vol. 3, pp. 126-32. ´ Garcia-Sanchez, I.M. (2007), “Efficiency and effectiveness of Spanish football teams: a three-stage-DEA approach”, Central European Journal of Operations Research, Vol. 15 No. 1, pp. 21-45. Gebauer, J. and Schober, F. (2006), “Information system flexibility and the cost efficiency of business processes”, Journal of the Association for Information Systems, Vol. 7 No. 3, pp. 122-46. Hughes, J.W., Lang, W., Mester, L. and Moon, C. (1999), “The dollars and sense of bank consolidation”, Journal of Banking & Finance, Vol. 23, pp. 291-324. Hwang, S.N. and Kao, T.L. (2006), “Measuring managerial efficiency in non-life insurance companies: an application of two-stage data envelopment analysis technique”, International Journal of Management, Vol. 23, pp. 699-720. Jeng, V., Lai, G.C. and McNamara, M.J. (2007), “Efficiency and demutualization: evidence from the US life insurance industry in the 1980s and 1990s”, The Journal of Risk and Insurance, Vol. 74 No. 3, pp. 683-711. Jerzmanowski, M. (2007), “Total factor productivity differences: appropriate technology vs efficiency”, European Economic Review, Vol. 51 No. 8, pp. 2080-110. Kao, C. and Hwang, S.N. (2008), “Efficiency decomposition in two-stage data envelopment analysis: an application to non-life insurance companies in Taiwan”, European Journal of Operational Research, Vol. 185 No. 1, pp. 418-29. Keh, H.T., Chu, S. and Xu, J. (2006), “Efficiency, effectiveness and productivity of marketing in services”, European Journal of Operational Research, Vol. 170 No. 1, pp. 265-76. Kotler, P. and Keller, K. (2006), Marketing Management, 12th ed., Prentice-Hall, Englewood Clips, NJ. Lin, L.F. (2002), “Deregulation and efficiency in the Taiwan life insurance industry”, PhD dissertation, Temple University, Philadelphia, PA. McCune, J. (2007), “Efficiency has been flat. Where is it headed”, ABA Banking Journal, Vol. 99 No. 5, p. 14. McKillop, D.G., Glass, J.C. and Morikawa, Y. (1996), “The composite cost function and efficiency in giant Japanese banks”, Journal of Banking & Finance, Vol. 20, pp. 1651-71. Mahlberg, B. and Url, T. (2003), “Effects of the single market on the Austrian insurance industry”, Empirical Economics, Vol. 28, pp. 813-38. Mamun, A., Hassan, M.K. and Maroney, N. (2005), “The wealth and risk effects of Gramm-Leach-Bliley Act (GLBA) on the US banking industry”, Journal of Business Finance & Accounting, Vol. 32, pp. 351-88. Meimand, M., Cavana, R.Y. and Laking, R. (2002), “Using DEA and survival analysis for measuring performance of branches in New Zealand Accident Compensation Corporation”, Journal of the Operational Research Society, Vol. 53, pp. 303-13. Morgan, G. (1994), “Problems of integration and differentiation in the management of ‘Bancassurance’”, The Service Industries Journal, Vol. 14 No. 2, pp. 53-169. OECD (1992), Insurance and Other Financial Service: Structural Trends, The Organization for Economic Cooperation and Development, Paris.

Philip, G. (2007), “Is strategic planning for operational efficiency”, Information Systems Management, Vol. 24 No. 3, pp. 247-64. Pree, D., Jude, C.D. and Kathryn, R. (1995), “A tool to insurance company management assess attorney efficiency and productivity”, CPCU Journal, Vol. 48 No. 3, pp. 155-62. Salomon, B. (1990), Multinational Money Center Banking: The Evolution of a Single European Banking Market, Salomon Bros, London. Saunders, A. and Walter, I. (1994), Universal Banking in the United States: What Could We Gain? What Could We Lose?, Oxford University Press, Oxford. Scovotti, C. and Spiller, L.D. (2006), “Revisiting the conceptual definition of direct marketing: perspectives from practitioners and scholars”, Marketing Management Journal, Vol. 16 No. 2, pp. 188-202. Thomas, A.R. (2007), “The end of mass marketing: or, why all successful marketing is now direct marketing”, Direct Marketing: An International Journal, Vol. 1 No. 1, pp. 6-16. Tone, K. and Sahoo, B.K. (2005), “Evaluating cost efficiency and returns to scale in the Life Insurance Corporation of India using data envelopment analysis”, Socio-Economic Planning Sciences, Vol. 39, pp. 261-85. Vine, E., Hamrin, J., Eyre, N., Crossley, D., Maloney, M. and Watt, G. (2003), “Public policy analysis of energy efficiency and load management in changing electricity businesses”, Energy Policy, Vol. 31 No. 5, pp. 405-31. Wilkinson, T.J., McAlister, A. and Widmier, S. (2007), “Reaching the international consumer: an assessment of the international direct marketing environment”, Direct Marketing: An International Journal, Vol. 1 No. 1, pp. 17-37. Wu, D., Yang, Z., Vela, S. and Liang, L. (2007), “Simultaneous analysis of production and investment performance of Canadian life and health insurance companies using data envelopment analysis”, Computers & Operations Research, Vol. 34, pp. 180-98. Wu, Z. (2003), “Market efficiency in the reformed Chinese grain marketing system”, China Economic Review, Vol. 14 No. 2, pp. 115-31. Yang, Z. (2006), “A two-stage DEA model to evaluate the overall performance of Canadian life and health insurance companies”, Mathematical and Computer Modeling, Vol. 43, pp. 910-9. Yao, S., Jiang, C., Feng, C. and Willenbockel, D. (2007), “WTO challenges and efficiency of Chinese banks”, Applied Economics, Vol. 39 No. 5, pp. 629-43. About the authors Chiang Ku Fan received a PhD from the Idaho Sate University, USA and he is an Associate Professor of Graduate Institute of Finance and Insurance of Shih Chien University in Taipei, Taiwan. His main research interests are in bancassurance, insurance and bank service, MCDM, efficiency analysis, human resources management in insurance industry. He has published over 20 journal articles in the Journal of Grey System, Journal of Information & Optimization Sciences, Journal of Social Science, The Business Review, The Journal of American Academy of Business and International Journal of Training Development, among others. Chiang Ku Fan is the corresponding author and can be contacted at: chiangkufan@hotmail.com Shu Wen Cheng is a Graduate Student of Graduate Institute of Finance and Insurance at Shih Chien University, Taipei, Taiwan. She obtained a bachelor degree in Risk Management and Insurance from Shih Chien University. Her research focuses on bancassurance and life insurance management. Her research results have been published in the Journal of Social Science and some conferences. To purchase reprints of this article please e-mail: reprints@emeraldinsight.com Or visit our web site for further details: www.emeraldinsight.com/reprints

Comparison of direct and indirect channels 359…...

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