Consumer perception of a new convergence product: A theoretical and empirical approach

Technological Forecasting & Social Change 92 (2015) 312–321

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Technological Forecasting & Social Change

Consumer perception of a new convergence product: A theoretical and empirical approach Misuk Lee a,1, Youngsang Cho b,⁎ a b

Korea Environment Institute, 215 Jinheungno, Eunpyeong-gu, Seoul, 122-706, South Korea Department of Information & Industrial Engineering, Yonsei University, 50 Yonsei-Ro, Seodaemun-gu, Seoul, 120-749, South Korea

a r t i c l e

i n f o

Article history: Received 28 January 2014 Received in revised form 17 October 2014 Accepted 17 December 2014 Available online 28 January 2015 JEL classification: O33 D11 L82

a b s t r a c t The purpose of this study is to develop a new framework for the market analysis of new convergence products based on their attributes and consumer utility. We propose a theoretical model to analyze the effect of convergence products on existing markets, and categorize convergence products into three types and derive the consumer demand for each type. We empirically apply our theoretical model to analyze the Internet Protocol Television service in South Korea. This study might provide meaningful implications for the demand analysis of new convergence products in that it approaches the phenomenon of technological convergence from product and market perspectives. © 2014 Elsevier Inc. All rights reserved.

Keywords: Convergence Bundling Market analysis Similarity

1. Introduction Due to advances in information and communication technology (ICT), many firms have begun to integrate several existing products or functions into a single product called a convergence product. In this case, convergence can be defined as a phenomenon wherein individual services or products are provided to the consumer as one (Kim, 2005; Yoffie, 1997; Bayus et al., 2000; Stobbe and Just, 2006). Some studies define convergence as a process by which products originally operated independent of one another grow together through digital technology (Hanson, 2000; Covell, 2000; Stieglitz, 2003). Examples of device convergence are televisions with videocassette recorders (TV/VCR) and smart phones such as iPhones, while the Internet Protocol Television (IPTV) service is ⁎ Corresponding author. Tel.: +82 2 2123 5727; fax: +82 2 364 7807. E-mail addresses: [email protected] (M. Lee), [email protected] (Y. Cho). 1 Tel.: +82 2 6922 7862; fax: +82 2 380 7644.

http://dx.doi.org/10.1016/j.techfore.2014.12.006 0040-1625/© 2014 Elsevier Inc. All rights reserved.

a typical example of a service convergence between broadcasting and telecommunication. Since these products possess the characteristics of new and existing products simultaneously, it is important to analyze the interrelationships among these products for a firm's business strategy (Shocker et al., 2004). Moreover, a new convergence product blurs or completely removes the boundaries of existing industries (Lind, 2005; Pennings and Puranam, 2001; Siedlok et al., 2010). However, few studies exist on convergence products that theoretically or empirically analyze the relationship among related markets and the manner in which these boundaries change. The term ‘convergence’ is an entirely new concept, but it is similar to traditional bundling. Generally, convergence and bundling are considered to be identical notions and are used interchangeably in a majority of studies (Bayus et al., 2000; Nelson and Tagliavia, 2000; Bang, 2005; Kim, 2005). Even though convergence and bundling products are similar to each other by definition, there are important differences between them. According to the bundling typology employed by

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Stremersch and Tellis (2002), a convergence product corresponds to product bundling, not to price bundling, and to mixed bundling, not pure bundling. In addition, according to the bundling typology of Simonin and Ruth (1995), a convergence product is limited to integrated product or single product bundles; in other words, a convergence product has a high degree of product integration and a low/high degree of recognisability. As compared with bundling, there are several different characteristics of convergence products. First, individual products can become a substitute or complementary product to each other due to the introduction of a convergence product, despite being independent originally. Second, as a convergence product tends to suffer a functional or quality loss, the utility derived from the attributes of one product within a convergence product is equal to or less than that of the original single product. Third, a convergence product provides additional utility derived from attributes that are created by the convergence process but are not included in single products. The main purpose of this study is to develop a theoretical framework for the market analysis of a new convergence product. For this purpose, first, we define a convergence product and its type from the viewpoint of the product's attributes. Our definition of a convergence product using product similarity may be useful as a starting before the development of a theoretical model. Second, we develop a theoretical model for analyzing the relationship between a new convergence product and related existing products based on a consumer utility function. The demand for a convergence product is described in the demand surface of existing products through the consumer's reservation price and purchase conditions. This approach provides the market position of a new convergence product as well as its effect on existing markets. Lastly, we conduct a market analysis on Internet Protocol Television (IPTV) service in South Korea using the proposed model and confirm its applicability to empirical analysis. The remainder of this study is organized as follows. The next section provides the basic concept of our theoretical model and a paradigm for the market analysis of a convergence product. Section 3 shows the process of empirical analysis using our theoretical model and empirical results in detail. The last section provides a summary as well as the implications and limitations of this study. 2. Theoretical model 2.1. Consumer utility The reservation price is defined as the maximum price that a consumer is willing to pay for a product or service (Cameron and James, 1987). Consumers purchase a product when their reservation price vi is greater than the market price pi; in other words, a purchase is made when the net utility Ui(=vi − pi) of the product purchase is greater than or equal to zero. For the purpose of discussing a convergence product case, let us assume that A and B are two independent products in the market; vA and vB are the consumer's reservation prices and pA and pB are the market prices of each product, respectively. Then, we can say that consumers purchase product A when UA ≥ 0, namely vA ≥ pA, and purchase product B when UB ≥ 0, namely vB ≥ pB.

313

Since a product can be perceived as a bundle of product attributes (Lancaster, 1966), the utility a consumer derives from a product purchase is represented as the sum of the partial utilities of its individual attributes. According to this concept, the utility of a convergence product is also defined as the sum of the partial utilities of attributes since the attributes of tie-in products have a significant impact on a consumer's decision to purchase the convergence product (Jun and Kim, 2007; Joo and Lee, 2008). Hence, a consumer's utility or reservation price for a convergence product can be represented as follows (Jung, 2004): vconvergence ¼

X

v0single þ μ;

ð1Þ

where vconvergence is a consumer's gross utility of a convergence product, v ′single is the partial utility derived from the attributes of a single product which is included in a convergence product, and μ is the additional utility derived from attributes that are not included in single products but are created by convergence. For example, in a mobile handset with a camera function, v ′single implies the utility derived from the attributes of a digital camera (e.g., pixels, zoom, and flash) and the utility derived from the attributes of a mobile phone (e.g., voice quality, telephone directory, portability, and battery life). The variable μ implies a newly created value such as editing or the wireless transmission of images. It may be ascertained that the consumer's reservation price for a convergence product is related to those of existing products. However, as mentioned earlier, a convergence product tends to suffer a functional or qualitative loss, while the qualitative attributes of individual products in bundling remain unchanged. In other words, the utility derived from the attributes of product A within a convergence product is equal to or less than that of the original single product A. Therefore, assuming that a new convergence product ‘AB’ is developed through the integration of the two existing products A and B, the consumer's reservation price for AB is defined as follows: vAB ¼ αvA þ βvB þ μ;

ð0 b α ≤ 1; 0 b β ≤1Þ;

ð2Þ

where α and β represent how the functional attributes of existing products A and B are maintained within a convergence product, which can be defined as a similarity index between a convergence product and an existing product. In addition, μ reflects a characteristic of a convergence product—one that is not a simple and physical integration, but the creation of additional value. In reality, a convergence product has not only benefits such as portability gain and convenience; it also incurs costs, such as complexity and switching cost. The variable μ therefore considers all these characteristics, on the whole. To investigate the conditions of a convergence product purchase, we assume that there are three products in the market simultaneously: two existing products A and B, and a new convergence product AB. Although a convergence product suffers a quality loss when compared with an original product, there is an additional benefit obtained through integration that motivates a consumer to purchase the convergence product. The condition for a consumer's purchase of a convergence product AB can be expressed as follows: vAB ¼ αvA þ βvB þ μ ≥pAB ;

ð3Þ

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where pAB is the market price of a convergence product AB. Table 1 shows the purchase conditions of each product. By rearranging this equation in terms of vA and vB, the purchase conditions for products A, B, and AB can be derived in the demand surface of existing products. 2.2. Types of convergence products In this study, three types of convergence products are defined based on the similarity between existing products and a convergence product: partial convergence, one-way convergence, and full convergence. A partial convergence product is defined as a product that partially comprises the attributes of existing products A and B. In other words, consumers can use part of the functions of existing products through a convergence product. This type of convergence is a general case and can be perceived as an early stage of convergence product development. Moreover, the market boundary of such a product is difficult to define. A one-way convergence product is defined as a product that comprises all the attributes of product A, but just a few of the attributes of product B. In this case, the convergence product is perceived as an improved version or successive generation of product A. Therefore, it is expected that such a one-way convergence product shares a potential market with the existing product A. A full convergence product is defined as a product that comprises all the attributes of both existing products A and B. In other words, consumers can fully utilize the functions of both existing products through a convergence product without a quality loss. This type of convergence product can be perceived as being similar to traditional bundling or as a perfect version of partial convergence. The market for full convergence products is expected to integrate existing markets into a new market. 2.3. Demand for three types of convergence products Based on the classification of convergence types above, a theoretical model for the market analysis of each convergence type can be derived. First, under the condition of 0 b α b 1 and 0 b β b 1, a convergence product AB is a case of partial convergence. With the assumption of αpA + βpB + μ ≥ pAB, the consumer's purchase conditions are illustrated in Fig. 1. The coordinates of point Q are ((pAB − βpB − μ)/α, pB), and the

Table 1 Conditions of purchase. Product

Existing product

Convergence product

Nothing

A

B

A, B

Nothing

AB

vA b pA, vB b pB, αvA + βvB vA N pA, vB b pB, αvA + βvB vA b pA, vB N pB, αvA + βvB vA N pA, vB N pB, αvA + βvB

vA b pA, vB b pB, αvA + βvB vA N pA, vB b pB, αvA + βvB vA b pA, vB N pB, αvA + βvB vA N pA, vB N pB, αvA + βvB

+ μ b pAB

+ μ b pAB

+ μ b pAB

+ μ b pAB

+ μ N pAB

+ μ N pAB

+ μ N pAB

+ μ N pAB

coordinates of point R are (pA, (pAB − αpA − μ)/β). In addition, we assume two conditions, pAB − βpB − μ N 0 and pAB − αpA − μ N 0.2 As indicated in Fig. 1, it is possible that consumers in Areas I, II, and III purchase both a convergence product and existing products because of their positive net utility. However, consumers compare the utilities of the convergence and existing products due to the overlapping of attributes. To begin with, it is possible that consumers in Area I can purchase both product A and convergence product AB because their net utilities for each product are positive. However, the convergence product AB partially comprises the attributes of product A, so consumers in Area I should compare their net utility for the two products and purchase product AB if UAB ≥ UA. The purchase condition of the convergence product in Area I is vB ≥ ((1 − α)/β) ⋅ vA + (pAB − pA − μ)/β, which passes point R when vA = pA. In the same manner, consumers in Area II purchase product AB when vB ≤ (α/(1 − β)) ⋅ vA + (pB + μ − pAB)/(1 − β). On the other hand, in Area III, it is possible that consumers purchase three products from the viewpoint of their net utility. However, consumers purchase convergence product AB if UAB ≥ UA + UB. Therefore, it is evident that the market for convergence product AB is created in the area of vB ≤ − ((1 − α)/(1 − β)) ⋅ vA + (pA + pB + μ − pAB)/(1 − β). Based on these conditions, the demand for convergence product AB is illustrated in Fig. 2. Assuming that a consumer's reservation price has a uniform distribution, the total demand for product AB can be calculated as the area of □QRST. Second, under the conditions of α = 1 and 0 b β b 1, convergence product AB exhibits one-way convergence. Since a one-way convergence product comprises all the attributes of product A, it is reasonable to consider a one-way convergence product as a perfect substitute or successive generation of product A. Therefore, in this case, it is expected that convergence product AB shares the potential market with existing product A as illustrated in Fig. 3. In addition, the market for product A is enlarged due to the introduction of convergence product AB (ΔQRT). Lastly, under the condition that α = 1 and β = 1, convergence product AB has the characteristic of full convergence. This type of convergence can be perceived as being similar to traditional bundling or as a perfect version of partial convergence. Compared with the other convergence types, the demand of a full convergence product occupies a large portion of the existing market for products A and B as illustrated in Fig. 4. Since a full convergence product comprises all the attributes of existing products, it can play the role of a substitute in terms of functionality. Hence, the market for a full convergence product is expected to integrate existing markets into a new market for product AB. In addition, the demand shape illustrated in Fig. 4 is the same as the demand for a bundling product discussed in previous literature (Adams and Yellen, 1976; Lee, 1999); this is because a full convergence product is similar to traditional bundling.

2 These two conditions are necessary to determine the positions of the xintercept and the y-intercept in Fig. 1. If the market price of a convergence product does not satisfy these conditions, the relationship between demand for the convergence product and similarity index is not clearly defined.

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Fig. 1. Conditions of convergence product purchase. Fig. 3. Demand for a one-way convergence product.

2.4. Implications for empirical analysis In this section, three types of convergence products are defined from the perspectives of the similarity of their functions and attributes. Moreover, the market for a convergence product is described based on a consumer's purchase conditions and a graphical approach. The theoretical market analysis indicates that each type of convergence product shows unique market forms and has a relationship with existing products. These results provide important implications for the change in market boundaries caused by the introduction of a convergence product. First, the market for a partial convergence product is located at the intersection of the markets of existing products. Since a partial convergence product does not contain all the attributes of existing products, it is less likely to be a perfect substitute in the existing markets. Accordingly, a partial convergence product has the characteristics of an independent product as well as a substitute product in the market.

Second, the market for a one-way convergence product tends to overlap the market for an existing product. A one-way convergence product comprises all the attributes of product A, but only a part of the attributes of product B. Therefore, a oneway convergence product may enlarge the existing market for product A and negatively affect the market for product B. Finally, in the case of a full convergence product, its market is more likely to substitute for the existing markets of products A and B. Since this type of convergence product comprises all the attributes of existing products, it can play the role of traditional bundling without quality loss. Therefore, it can be expected that a full convergence product might substitute for existing markets; in the long run, it may integrate them into one market, even if the existing products are independent of each other. Fig. 5 describes three types of convergence products and the formation of their markets. This diagram can be used for a new typology of convergence and a theoretical background for the market analysis of a new convergence product. In addition, this

Fig. 2. Demand for a partial convergence product.

Fig. 4. Demand for a full convergence product.

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Fig. 5. Diagram of convergence types and their market.

information can be used as a starting point for a demand analysis of a new convergence product. 3. Empirical analysis This section presents the process of empirical analysis using consumer preference data for a new convergence product as well as an empirical result of the market of the IPTV service in South Korea. The IPTV service is considered a convergence service in that it is not only ‘a broadcasting service based on a telecommunication network’, but also ‘a telecommunication service including a broadcasting service’. With technological improvements, its market has been growing rapidly. This service is an appropriate target for our empirical analysis because it entails two separate services – broadcasting and telecommunications – that are integrated and provided as a single service to consumers. The process of the empirical analysis is as follows. First, the consumer utility function is estimated using the consumer preference data on the IPTV service and existing services. Then, consumer reservation prices for each service can be derived from the utility function. Second, the similarity between two products and any additional utility created by convergence are measured; this data represents the linear relationship among the consumer reservation prices of the three services. By combining information concerning similarities, additional utility, and the market price of each service with the distribution of consumer reservation price, our theoretical model empirically derives the relationship between the IPTV service market and existing markets. Finally, the market potential of the IPTV

service is calculated and, by combining early-market data, its diffusion pattern is examined. We also analyze how the predicted demand of the IPTV service based on the consumer perception in 2008 has varied in the current market according to technological improvements. 3.1. Data This study uses consumer survey data from a survey of 500 people conducted by Park et al. (2008) between August 7 and August 27, 2008 in Seoul, South Korea. The main purpose of the survey was to investigate consumer behavior concerning the use of broadcasting and telecommunication services in South Korea. From this survey data, we use the conjoint data concerning Internet, pay-TV, and IPTV services. Each of the Internet, pay-TV, and IPTV services is considered as an attribute in itself in the conjoint survey.3 Table 2 shows the list of the attributes and price levels considered in the conjoint survey. Each respondent ranks four alternatives in order of preference from 1 to 4 based on the combination of service and price. This process is then repeated for four alternative sets. This kind of survey is useful in that it can provide more information than a survey in which only the best preferred alternative is selected.4 3 The purpose of this conjoint survey is not to investigate consumer preference for the individual attributes of services, but to derive the consumer reservation price for each service. Therefore, this survey assumes the minimum number of attributes necessary for calculating consumer reservation price. 4 The details of this survey are found in Park et al. (2008).

M. Lee, Y. Cho / Technological Forecasting & Social Change 92 (2015) 312–321 Table 2 Attributes and price levels in conjoint survey.

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Table 3 Estimation results of mixed logit model.

Attribute

Price of each service (wona)

Parameter

Mean

Variance

Internet service Pay-TV service IPTV service

20,000/30,000 10,000/15,000 10,000/15,000

γi0 γi1 γi2 γi3 γip

1.0560 10.4376a 7.4072a 7.2631a 1.4700b

6.4910 17.9142 7.9698 18.9498 1.6074

a

The currency of South Korea ($ 1 1120 won in 2008).

a b

3.2. Utility function and reservation price The consumer utility function is estimated by using the rank-ordered data on the following four alternatives: Internet service, pay-TV service, IPTV service, and nothing. The utility function, which includes each service as an attribute in itself, is represented by Eq. (4): U i j ¼ γ i0  X i;nothing þ γ i1  X i;Internet þ γ i2  X i;payTV þ γ i3  X i;IPTV −γip  X i;price þ ε i ;

ð4Þ

where Uij is the utility of consumer i from alternative j; the variables Xi,j are the dummy variables for each service j; Xi,price is the price of each service; and εi is an error term. The parameter γij is the marginal utility of each alternative, which needs to be estimated. As the purpose of this estimation is to derive the consumer reservation price of each service individually, a mixed logit model is used for the estimation of utility. Generally, it is assumed – albeit unrealistically – that all consumers have an identical preference for a logit model or probit model. However, a mixed logit model considers the heterogeneity of consumer preference. As a result, the parameters of Eq. (4) can have different coefficients for each consumer according to the assumption of the distribution for his or her reservation price. A Bayesian approach using Gibbs sampling is used for the estimation of the mixed logit model (Allenby and Rossi, 1999; Chiang et al., 1999; Train, 2003). By assuming the distributions of each attribute and price, the consumer reservation price is calculated as γij/γip (j = 1, 2, 3), which is derived from Jedidi and Zhang (2002). A normal distribution is assumed for the attributes of the Internet and pay-TV services, and a log-normal distribution is assumed for the attribute of IPTV service and price. Table 3 provides the mean and variance of each parameter from the estimation results of the mixed logit model. From the result, the average reservation prices for Internet, pay-TV, and IPTV services every month are 105,164 won, 88,334 won, and 83,485 won, respectively.5 In comparing these figures to the market price of each service from Table 2, the estimated average reservation prices for each service seem somewhat high; therefore, it is necessary to understand them in terms of relative value, rather than absolute value. Table 4 shows correlations among coefficients. In this matrix, each option has a positive correlation with each other except for ‘nothing’ option. It is reasonable because a consumer 5

The estimation results in Table 3 provide information on the distribution of each coefficient that represents the effect of each attribute on consumer utility. As 500 respondents provide answers regarding the four-alternative set, each coefficient for 2000 observations is drawn through the Bayesian estimation process. Consequently, reservation prices for 2000 observations are calculated.

Statistically different from zero at the 99% level. Statistically different from zero at the 90% level.

who has a high preference for IPTV also tends to adopt Internet or pay-TV service. 3.3. Convergence type of IPTV service Using the pair of reservation prices from the mixed logit model, the linear equation of three reservation prices is derived as follows: RP IPTV;i ¼ α  RP internet;i þ β  RP payTV;i þ μ þ ηi ; ð0 b α ≤1; 0 b β ≤1Þ;

ð5Þ where ηi is an error term. Eq. (5) represents the linear relationship among the reservation prices of each service. Therefore, a multiple regression analysis is conducted with regard to the reservation price of the IPTV service as a dependent variable, and that of Internet and pay-TV as independent variables. To restrict the range of similarity coefficients, α and β can be substituted with 1/(1 + exp(−α ′)) and 1/(1 + exp(−β ′)), respectively. Table 5 shows the estimation result of the multiple regression analysis. From the estimation result, it can be said that the IPTV service has the characteristics of the pay-TV service (i.e., similarity of 90%), and that it has the characteristics of the Internet service (i.e., similarity of 4%). In other words, based on consumer perception, the IPTV service is similar to the pay-TV service; consumers also perceive IPTV as a service that is nearly different from Internet service. Hence, present-day IPTV service can be defined as a partial convergence product that integrates Internet and pay-TV services. Additionally, the parameter μ, which denotes the additional value created by convergence, is not statistically significant. Therefore, except for the functions of the pay-TV and Internet services, there is no additional utility that the consumer can acquire through the IPTV service. The IPTV service is known as a convergence service that provides video on demand (VOD) and broadcasting services over an IP-based network. However, the similarity value between the IPTV and Internet services is a mere 0.04, based on consumer perception, because consumers cannot directly experience the typical functions of Internet service through the

Table 4 Correlation matrix of each coefficient. Parameter

γi0

γi1

γi2

γi3

γip

γi0 γi1 γi2 γi3 γip

1.0000 −0.2788 −0.1719 −0.1686 −0.1780

−0.2788 1.0000 0.6064 0.4805 0.4556

−0.1719 0.6064 1.0000 0.7416 0.0184

−0.1686 0.4805 0.7416 1.0000 0.0971

−0.1780 0.4556 0.0184 0.0971 1.0000

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Table 5 Estimation results of similarity index. Parameter α β μ a b

Estimate

P-value a

0.0403 0.9019b −0.0423

0.040 0.000 0.785

Statistically different from zero at the 95% level. Statistically different from zero at the 99% level.

present-day IPTV service in South Korea. Consequently, the contribution of Internet service to the IPTV service is too small to create a synergistic effect based on consumer perception. Therefore, consumers have little chance to experience additional utility from the IPTV service under current conditions. Nevertheless, it can be expected that the future IPTV service will feature a full convergence product with technological improvements, leading to increased value for IPTV service subscribers. 3.4. Market analysis of IPTV service From the estimation results of the mixed logit model, we can derive the distribution of the consumer reservation price of the Internet and pay-TV services on a two-dimensional plane. By adding the information of α, β, μ, and the market price of each service, the market size of a partial convergence product can be derived. Fig. 6 illustrates the distribution of the consumer reservation price of existing services and the market size of the IPTV service; this is the result of our proposed model. The number of consumers in the pentagon within Fig. 6 denotes the demand for IPTV service. As seen in Fig. 6, the consumers in the two-dimensional plane of the reservation prices of existing services are not uniformly distributed. Because our theoretical model in former section is developed under the assumption that consumers are uniformly distributed, it is inappropriate for the real market;

the heterogeneity of consumer preference needs to be reflected in an empirical analysis, without losing the generality of our theoretical model. The results of the market analysis can be changed according to the assumptions of consumer preference distribution. The area of the pentagon in Fig. 6, for example, represents the demand for IPTV service under the assumption of uniform distribution, but consumers are not uniformly distributed within the pentagon. From the calculation with consideration for consumer heterogeneity, 28.4% and 27.7% of the pay-TV and Internet service markets, respectively, overlap with the new market of the IPTV service. These relationships have different meanings in different circumstances. First, existing pay-TV services – such as cable and satellite broadcasting – are considered competitors of the IPTV service (Lee et al., 2006; Yoon et al., 2008; Park et al., 2008). This means that 28.4% of the market potential of pay-TV service has a strong possibility of being transferred to the IPTV service. On the other hand, an Internet service subscription is presently necessary for the use of IPTV service; thus, it can be said that 27.7% of the market potential of the Internet service will use the IPTV service in addition to the Internet service. In other words, there will not necessarily be a market extraction of Internet service. Of course, in the future when the IPTV service has the characteristics of a full convergence product, it should be regarded as a substitute not only for the pay-TV service but also for Internet service. The size of the market potential of the IPTV service is calculated as follows. First, we estimate, separately, the market potential of the Internet and pay-TV services. Because the market of the existing services has almost reached its saturation level, it is easy to estimate the diffusion model using the market data of each service. To estimate the market potential of the Internet service, the Bass model is used:  nInternet ðt Þ ¼

Fig. 6. Market analysis of IPTV service.

N Internet ðt−1Þ MInternet  ðMInternet −NInternet ðt−1ÞÞ;



pInternet þ qInternet

ð6Þ

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319

Table 6 Estimation results of market growth for Internet, pay-TV, and IPTV. Parameter

(a) Internet Estimate

P-value

pInternet qInternet MInternet apayTV bpayTV MpayTV aIPTV bIPTV R2

0.1488a 0.3076 15,055,480b

0.013 0.277 0.000

a b

(b) Pay-TV

0.3479

(c) IPTV

Estimate

P-value

−6.5209b 0.8126b 17,275,970b

0.000 0.000 0.000

0.9977

Estimate

P-value

−2.9921b 0.2440b 0.8876

0.000 0.000

Statistically different from zero at the 95% level. Statistically different from zero at the 99% level.

where nInternet(t) and NInternet(t) represent the subscribers and the cumulative subscribers to the Internet service at time t, respectively; and the parameters MInternet, pInternet, and qInternet represent the market potential, the innovation coefficient, and the imitation coefficient of the Bass model, respectively. Table 6-(a) shows the estimation results of the Bass model using annual data of Internet service subscribers from 1998 to 2008.6 According to the estimation results, the market potential of the Internet service in South Korea is approximately 15 million households. On the other hand, a logistic model, as seen in Eq. (7), is used to estimate the market potential of the pay-TV service7: NpayTV ðt Þ ¼

M  payTV ; 1 þ exp −apayTV −bpayTV t

In addition, it is possible to forecast the diffusion pattern of the IPTV service by combining information on the derived market potential and data in the early market. Table 6-(c) shows the estimation results of the logistic model for the IPTV service market using the market potential and monthly data of IPTV subscribers from 2006 to 2008.10 In this table, the meaning of each parameter is identical to that of the pay-TV service. Fig. 7 describes the actual and estimated numbers of South Korean subscribers to the IPTV service as well as their diffusion pattern according to the results of the empirical analysis. 3.5. Discussion

ð7Þ

where NpayTV(t) equals the cumulative subscribers to the payTV service at time t; and the parameters MpayTV, apayTV, and bpayTV represent the market potential, initial level, and growth rate of diffusion, respectively. Table 6-(b) shows the estimation results of the logistic model using annual data of pay-TV service subscribers from 1995 to 2008.8 According to the estimation results, the market potential of the pay-TV service is about 17.3 million households. By combining the market potentials of the existing services and the information derived from Fig. 6, the size of the market potential of the IPTV service can be calculated. Under present conditions, if 27.7% of Internet service users also subscribe to the IPTV service and 28.4% of the pay-TV service market is absorbed into the new market of the IPTV service, the market potential of the IPTV service will be 5.24 million households, excepting any overlaps in service.9

6 Data from Korea Communications Commission (http://eng.kcc.go.kr/user/ ehpMain.do). 7 It does not matter whether the Bass model or the logistic model is used to estimate market potential because the Internet and pay-broadcasting service markets have almost reached saturation level. We use both models for estimation and adopt the one that performs best. 8 Data from Korea Information Society Development Institute (http://www. kisdi.re.kr/kisdi/jsp/fp/eng/main.jsp). 9 Those consumers who did not subscribe to existing services but subscribe to the IPTV service are ignored in this analysis due to the market saturation of existing services.

As the empirical result is derived from the consumer survey, it needs to be understood based on current conditions and various assumptions. Although the IPTV service is explained in the questionnaire as being a service that has not only the attributes of existing Internet and broadcasting services but also those of various interactive services, consumers nonetheless perceive that the IPTV service does not feature the functions of the Internet service. The characteristics of the IPTV service in South Korea are similar to those of the pre-IPTV service, which do not provide real-time broadcasting channels and various other interactive services. Therefore, it seems that the consumers answering the survey conducted in August 2008 had the pre-IPTV service in mind. The predicted market potential of 5.24 million households is also based on the assumption that the current technological level of the IPTV service is maintained. Of course, that assumption does not necessarily hold; the technology of the IPTV service is being improved continuously. As the potential market of the IPTV service will grow in concert with technological development, some consideration of technological development is needed for the market analysis of a convergence product. Since the purpose of the consumer survey used in this study was to estimate consumer reservation price, each service is considered as an attribute in itself. In this case, the possibility of technological development cannot be considered in the processes of the consumer survey or the market analysis. One alternative is to organize consumer utility function by

10 Data from Korea Information Society Development Institute (http://www. kisdi.re.kr/kisdi/jsp/fp/eng/main.jsp).

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Household (1,000) 6000 5000 4000 3000 2000 1000 0 2006

2007

2008

2009

2010

2011

2012

2013

2014

2015 year

IPTV (actual)

Fig. 8. Subscribers of pre-IPTV and IPTV services in South Korea.

IPTV (estimated)

Fig. 7. Demand forecasting of IPTV services.

individual attributes and consider the effects of technological developments or attribute-level improvements on consumer utility. This approach is expected to derive the results of demand forecasting with various scenarios. Actually, the pre-IPTV service has evolved into the IPTV service including real-time broadcasting through technological development in South Korea. That is driving the results that pre-IPTV subscribers decrease rapidly with the transition to the IPTV service, while the subscribers to total IPTV services increase (Fig. 8).11 It is a good example to present how the predicted market potential of the IPTV service in 2008 can change by technological development until 2011. On the other hand, the empirical results are derived based on the current condition that consumer reservation prices are drawn out from the distribution of consumer preference through a simulation process. Therefore, it should be mentioned that the forecasting results of this study can change according to assumptions vis-à-vis consumer distribution and the simulation process used to draw the consumer reservation price from it. 4. Conclusions The purpose of this study is to develop a theoretical framework for market analysis of a new convergence product. For this purpose, previous studies on bundling and convergence are reviewed in order to understand the specific characteristics of convergence. In addition, three types of convergence are defined by similarity index: partial, one-way, and full convergence. The market demand of a convergence product is investigated through a mathematical and graphical approach, and the diagram of convergence types and their markets is illustrated. Finally, the theoretical model is applied to the empirical analysis to confirm its applicability and usefulness. This study has several significant implications. First, it approaches the technological convergence phenomenon from product and market perspectives. For this, convergence is newly defined via three types that focus on its characteristics, such as attribute similarity and additional utility. This typology can provide a new standard of classification to studies of 11 Data from Information Communication Technology Index (http://www. icti.or.kr/en/Main/Main.aspx).

convergence. According to this typology, bundling can be considered as a part of a convergence product. This study provides a theoretical model for market analysis of a new convergence product using similarity level and consumer's utility. It is a discriminative approach from the theory of traditional bundling. The concept and theory of this study can be applied to other empirical analyses in various forms. In addition, this study provides a direction for the demand analysis of a new convergence product. When a demand analysis is initiated, this study can provide useful information on the relationship between a convergence product and existing products; the market definition becomes clear and the burden of analysis decreases. Therefore, this study can be perceived as a work that integrates a theoretical model in economics and demand analysis in the field of business. The model proposed in this study is different from existing methods used to estimate consumer choice probabilities via conjoint analysis in that convergence products and existing products are not exclusive of each other. Since existing products can have not only a substitutive or complementary relationship but also relationships in which they are independent of each other, a new convergence product is not always a competitor of existing products. Thus, our model can be applied to a greater variety of occasions related to consumer choice than existing methods. Moreover, our approach can be used as a kind of forecasting-by-analogy method; we forecast the market of a new convergence product directly through its relationship with existing products, while some previous studies have used subjective assumptions in the process of the demand. Despite these contributions, there is room for improvement of this study. First, the assumption of consumer distribution can be relieved. Second, the main issues in the bundling literature can be analyzed through a modification of the theoretical model, i.e., the effect of substitution/complementarity between products on the bundling strategy. Third, the change of price and the effect of convergence on price sensitivity are beyond the scope of this research. It will be insightful to provide different messages on attributes versus price of a convergence product. Fourth, in the empirical analysis, the estimation of utility function which consists of each product attributes could be more useful for the future research. Finally, various empirical studies can be executed according to the convergence type and application of the theoretical model. This kind of work for the development of an advanced model can be pursued in future research.

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