Cumulative strategic capability and performance of early movers and followers in the cyber market

International Journal of Information Management 30 (2010) 239–255

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International Journal of Information Management journal homepage: www.elsevier.com/locate/ijinfomgt

Cumulative strategic capability and performance of early movers and followers in the cyber market Sang-Gun Lee a , Chulmo Koo b,∗ , Kichan Nam c a b c

College of Business, Ajou University, San 5, Woncheon-dong, Yeongtong-gu, Suwon 443-749, Republic of Korea Department of Business Administration, College of Business, Chosun University, Seosuk-dong 375, Dong-gu, Gwang, 501-759, Republic of Korea Department of Service Systems Management & Engineering, School of Management, Sogang University, 1 Shinsoo-dong, Mapo-gu, Seoul 121-742, Republic of Korea

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Article history:

Keywords: Porter’s generic strategies Sand Cone model Early mover Follower Cyber market

a b s t r a c t Today, the cyber market is evolving rapidly in the networked age. In the cyber market, the traditional competitive strategy appears to no longer be effective. This study investigates the strategic choice differences of online firms based on their strategic capabilities and performance. More specifically, the study reviews the advantages and disadvantages of early movers and followers based on Porter’s strategic topology, as well as strategic capabilities derived from Sand Cone model. The results show that early movers have more cumulative strategic capabilities than followers do in market differentiation, innovative differentiation, and cost leadership. However, early movers have better focus strategy than followers. These results have provided new insights for the scholars and entrepreneurs to reexamine traditional strategic approaches and the order of entrance effects in the cyber market. © 2009 Elsevier Ltd. All rights reserved.

1. Introduction The Internet now allows companies located anywhere in the world to project into distant markets without the necessity of creating a physical presence (Kim, Nam, & Stimpert, 2004a). While enthusiasm for e-business, particularly business-tocustomer offerings, has diminished since the Internet boom period of the late 1990s, business conducted through the Internet continues to grow. However, the economic downturn in the year 2000 resulted in the loss of venture capital and increased investor apprehension. With the uncertain nature of the Internet environment, it was not a big surprise to witness the failure of a large number of online initiatives soon after market introduction (Ozer, 2005). Hence, management adopted a more rational and cautious perspective towards e-business investment (Kearns, 2005). Despite tremendous losses, e-business forms such as business-to-business (B2B) and business-to-customer (B2C) operations continue to expand at rates in excess of their traditional counterparts (Kearns, 2005). Recently, the growth of e-commerce has provided firms with a very attractive marketing opportunity (Yan & Ghose, 2009). For instance, in 2007, online retail sales were about $136.4 billion, up from $102.1 billion in 2006. These are projected to reach $176.9 billion in 2010 (Reuters, 2009). As competition becomes increas-

∗ Corresponding author. Tel.: +82 62 230 6831. E-mail addresses: [email protected] (S.-G. Lee), [email protected] (C. Koo), [email protected] (K. Nam). 0268-4012/$ – see front matter © 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijinfomgt.2009.09.003

ingly fierce, the traditional strategies no longer seem effective. Traditional firms are recognizing that the “economies of scale,” considered being a competitive weapon, have transformed from the traditional market to the online market. They also strive to provide satisfaction to e-customers through high service quality and adopt new “rules of the game” (Mellahi & Johnson, 2000). Moreover, the ability of a company to produce great varieties of relatively customized products at remarkably low cost, viz: economics of scope is more important than economics of scale (Levit, 1983). Some followers in a specific cyber market appear to make inroads on an early movers’ market position through imitation of ideas, website design, business models, and marketing skills. Thus, researchers and practitioners are keenly interested in the question as to whether or not an early mover can continue to dominate the preoccupied market or whether a follower may easily enter into a cyber market with a relatively low market entrance cost and idea imitation. Internet-based early movers such as Amazon.com, CDnow.com and Expedia.com created new markets with new business models and innovative processes. Their strategies are quite different from traditional businesses that adopted a competitive strategy, as Internet followers or brick and click firms such as Barnesandnoble.com, Columbiahouse.com and Orbitz.com have done, which involves encroaching on a market by taking advantage of idea imitation and low entrance costs. According to Metcalfe (2000), the early mover dominates the cyber market with a new economic paradigm. In this case, early movers into a new business earn the highest benefits in terms of market share when they manage to support their early mover advantage with certain technologies that a competitor cannot imi-

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tate (Coeurderoy & Durand, 2004). For instance, early movers such as Yahoo!, Amazon and eBay are still thriving by taking a defensive stance and showing positive business performance. However, brick and click can counteract Internet early movers with their own existing infrastructure, inventory warehouse, and marketing networks. There are several comparative studies examining the advantages and disadvantages of early movers and followers (e.g. Coeurderoy & Durand, 2004; Shankar, Carpenter, & Krishnamurthi, 1998), while some of them analyze the relationship between moment of entry and diverse competitive factors to explain organizational performance (e.g. Covin, Slevin, & Heeley, 2000; Shamsie, Phelps, & Kuperman, 2004). In addition, some former researchers investigate the relationship between organizational performance and strategy choice in the traditional industry (e.g. Dess & Davis, 1984; Hambrick, 1983; McFarlan, 1983; Parsons, 1983; Porter, 1980, 1985). Porter (1980, 1985) suggested that strategic positioning in a market determines whether an organization’s profit is above or below the industry average. The fundamental basis of aboveaverage performance in the long run pushes a firm to maintain its competitive advantage. Porter’s argument is that successful businesses should implement at least one of the generic strategies such as cost leadership, differentiation, or focus. D’Aveni (1994) and Lieberman and Montgomery (1988) explained that the market entrance order positively affects organizational performance. However, these studies do not focus on online firms’ strategic capabilities and organizational performance but on traditional industry’s early movers. Studies on early Internet firms have focused mostly on efficient inventory control, improved market reach, the customization of products and services, shortened time to market for new products and services, better payment systems, and lower advertising costs (Berthon, Pitt, & Watson, 1996; Jarvenpaa & Todd, 1996–1997; Kim, Nam, & Stimpert, 2004b; Ozer, 2005). Likewise, in the last two decades, several surveys have exposed limitations in empirical studies that raise doubts about the first mover advantage of cost leadership and differentiation when compared to followers (Ruiz-Ortega & Garcia-Villaverde, 2008). Porter (2001) argued that, in spite of the importance of strategic choice, Internet technology ironically tends to make strategy less important, as most firms believe e-business will provide opportunities to earn additional profits. While Porter (2001) questions first mover advantages on the Internet by arguing that switching costs are quite low, other researchers (e.g. Downes & Mui, 1998; Tapscott, 2001) emphasize the importance of being first movers in the electronic market environment (Varadarajan, Yadav, & Shankar, 2008). Kim et al. (2004a) argued that Porter’s (1980) generic strategic framework is still applicable in the Digital Age, yet, it needs some modification. Thus, in this study, we adopted the Sand Cone model as a complementary tool to cover the limitation of Porter’s generic strategies in explaining the relationships between strategic capabilities and a company’s performance. In addition, there is a limited empirical research on online firms’ strategic capabilities and performance, even though there have been some case studies such as the Javalgi, Cutler, and Todd (2004) study on Amazon.com and eBay.com. Therefore, there is a need to develop new theoretical and empirical models that analyze the competitive factors influencing the performance of early movers and followers in cyber market. The purpose of this study is two-fold. First, we explore the differences in strategic capabilities and organizational performance between early movers and followers in the cyber market. Second, we propose to adapt Porter’s strategic topology and the Sand Cone model’s strategic capability explanation, and then use the resulting modifications to help explain the causal relationship between strategic capabilities and company performance. This paper is organized as follows. We provided the outlines of relevant research on

early movers and followers in Section 2.1 and discussed Porter’s competitive strategy and Sand Cone model in Section 2.2 and 2.3 respectively and developed our hypotheses based on literature review in Section 2.4. Furthermore, we described our methodology, data collection, measurement, and statistical analyses in Section 3. Finally, we discussed the result, concluded the findings, and described the limitations and future research necessary in each section. 2. Theoretical background 2.1. Relevant research on early movers and followers The pattern of the cumulative frequency of innovation adopters over time forms an S-shaped curve. This curve explains the behaviors of adopters, and it is known as the diffusion model. According to Rogers (1995), innovation is defined as a degree of relative quickness regarding the adopting unit’s behavior toward new ideas, objects and practices. Innovation adopters are classified into the categories of innovators, early adopters, early majority, late majority, and laggards. We also adopted the Miles and Snow topology to indicate the difference between innovators and imitators. The Miles and Snow topology provides a complex view of an organization’s environmental processes, organizational structure, management, market, technology, and product characteristics (Smith, Guthrie, & Chen, 1989). The Miles and Snow (1978) topology identified four types of strategies: prospector, defender, analyzer, and reactor. Prospectors are considered innovators and market leaders; they accept higher risk levels and are more willing to invest in new technologies and to explore new markets. Defenders are associated with a stable and established market niche. Analyzers combine the best qualities of prospectors and defenders. Reactors, generally considered the least successful, pursue strategies that actually impede business performance (Kearns, 2005). Based on Rogers’ classification scheme and the Miles and Snow topology, we divide innovation adopters into two groups: the early mover and the follower. Following Varadarajan et al. (2008), we define the first mover as the first firm to enter a market supported by sizeable investments in the production and distribution of the product, and the elapsed time between its entry and that of later entrants is of sufficient magnitude so as to allow the first mover to achieve advantageous resource positions. First mover advantages represent an important topic in strategic management literature and in business practice (Carow, Heron, & Saxton, 2004). There have been a number of studies that support the notion that early movers have a competitive advantage over followers (e.g. Golder & Tellis, 1993; Kim et al., 2004b). However, some researchers dispute this and claim that followers can be outstanding from a variety of perspectives. For instance, even though Porter (1980) argued that cost leadership has a positive impact on market share in general, a study by Coeurderoy and Durand (2004) found that late followers benefit more from cost benefit strategy than early entrants. The cost of leadership might combine its effects with the pioneering advantage. First movers bear specific costs and risks associated with their innovative strategies, and followers can benefit from first movers’ incurred costs and enter more efficiently in case of quick and easy imitation. We summarized the advantages of the early mover and the follower as follows. First, Lieberman and Montgomery (1988) argued that first mover advantages arise from three sources: technological leadership, pre-emption of assets, and the creation of buyer switching costs (Carow et al., 2004). In detail, a firm can gain first mover advantage by being the first in occupying a market position or niche that allows for the gaining of resources, capabilities, and access that late movers cannot easily match (Lieberman &

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Montgomery, 1988). The first mover also can enjoy advantages in customer awareness and loyalty (Lieberman & Montgomery, 1988; Porter, 1985). A first mover can pick the attractive positions and force rivals to take unattractive ones (Porter, 1985). Secondly, in the context of the resource based view of the firm, an early mover can develop a resource that is rare, valuable, difficult to imitate and non-substitutable (Carow et al., 2004). Thus, the early mover takes an advantageous local market position, secures scarce resources, and then extends its production with economies of scale. Third, first movers also have the ability to establish uniqueness in the market, setting up exclusive distribution channels; defining the standards for new technology; securing patents or governmentconferred status; and controlling other scarce resources critical for successful competition (Li, Lam, Karakowsky, & Qian, 2003). Fourth, the early mover can establish its production or service as the market standard to customers (Cahill, 1996; Kim & Mauborgne, 2005). Lieberman (2005) found that first movers enjoyed a premium in market capitalization only in markets characterized by network effects and when first movers entered with patented innovations. However, first movers generally enjoyed only a minimal survival advantage over other firms (Nikolaeva, 2007). What are possible advantages of being a follower? First, the follower may avoid initial market uncertainty. Wernerfclt & Karnani (1987) suggested that organizational performance differs between the early mover and follower at market maturity. That is, as the early mover creates the market and the market matures, the follower can take advantage of the “free ride effect,” allowing the follower to achieve better business performance than the early mover in areas such as customer education, and research and development costs (Schnaars, 1994). Second, the follower can learn lessons from an early mover’s failure. The follower can surpass the early mover by developing new product features or production positioning in the market (Shankar et al., 1998). This is particularly the case when rapid technological innovation allows later adopters to exploit market opportunities in a more cost-effective manner through imitation after technological uncertainties in e-commerce are resolved (Carow et al., 2004; Min & Wolfinbarger, 2005). The ability of later movers to imitate successfully might also depend on their history and experience (Carow et al., 2004). In their discussion of early mover and follower benefits, Mellahi and Johnson (2000) also found that a follower’s imitation of the early mover in the cyber market is dramatically quicker compared to traditional industry. Imitation strategy in some areas, such as reverse auctions, surpasses innovation strategy through technology dependency, rapidly changing markets, technology innovation, information transfer, and information technology diffusion. 2.2. Porter’s competitive strategy Porter’s strategic topology is widely used in strategy literature (Thompson & Strickland, 2001). Porter insisted that as firms implement one or two strategies, strategic choices affect profit and competitiveness. For this paper, we adapted Porter’s (1980, 1985, 1996) topology relevant to cost leadership, differentiation, and focus in our research framework. According to Kim et al. (2004b), Porter’s framework of generic strategies has two advantages. Firstly, Porter’s framework is inherently tied to firm performance. Secondly, it overlaps with other strategies. For instance, Porter’s strategy of differentiation resembles Miles and Snow’s (1978) prospector strategy, and Porter’s strategy of cost leadership is similar to Miles and Snow’s defender and Hambrick’s (1983) and Dess and Davis’s (1984) cost leadership strategies. Porter (1980, 1985) distinguished three generic strategic orientations. First, firms can compete based on their costs of production to preserve higher margins over their competitors. This cost leadership strategy implies that firms can increase their market share by

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improving their cost structure. Second, firms can choose a market differentiation strategy. For instance, they may develop a competitive advantage by gaining customer loyalty either by innovating and upgrading their products or by offering a unique image via marketing. Finally, Porter distinguishes the focus strategy, which is the application of either cost leadership or differentiation strategy to more narrowly targeted customers. Furthermore, Porter (2001) published an updated study that showed the Internet does not destruct existing traditional corporate or industry structures, but as firms use the Internet technology, the Internet itself is considered a strategic choice. Then firms concurrently gain a competitive advantage through the technology. He suggested that offline firms restructure existing organization activities based on the Internet or combine the Internet and existing activities to successfully rebuild a rigorous offline organization, while online organizations should conduct their own unique differentiation strategy instead of imitating the strategy of rigorous offline market positioning. Kim et al.’s (2004a) study concluded that cost leadership strategy exhibited the lowest performance among other strategies on the Internet. Firms pursuing a hybrid cost leadership/differentiation strategy exhibited the highest performance; moreover, brick and click firms showed the superior performance. His finding suggests that cost leadership and differentiation must be combined to be successful in e-business. In addition, Ruiz-Ortega and Garcia-Villaverde (2008) found that information technology capabilities and low cost have an impact on the firm’s performances, regardless of their moment of entry into the market (Yan & Ghose, 2009). Lumpkin, Droege, and Dess (2002) argued that under online environment, a focus firm’s market niche should appropriately fixed the demand, be big enough to be profitable, but small enough to lessen the attractiveness to potential new entrants. In addition, the advantages and disadvantages of using Internet-based strategies for overall cost leaders, differentiators, and focusers are summarized in Table 1 below. Even though Porter’s strategic topology has been supported, his strategic capability has been criticized by some researchers. Gurau (2007) noted that since the 1980s, various authors have criticized this model, outlined its limitation in both theory and practice (e.g. Aktouf, Chenoufi, & Holford, 2005; Dawes & Sharp, 1996; Kay, 1993; Wagner & Digman, 1997). Some radical critics come from Hill (1988), Wright (1987), and Chrisman, Hoffer, and Boulton (1988), as they argued that generic strategies are too general. Wagner and Digman (1997) and Kaya, Alpkan, and Aytekin (2003) state that the possible coexistence of the two main generic strategies (low cost and differentiation) is explained by the fact that industry characteristics are the determinants of cost, while the determinants of differentiation are based on market characteristics. Alpkan, Bulut, and Mert (2005) test this model in the context of Turkish firms, and conclude that the generic strategies are not alternative to each other. In short, the most important limitation of this theory is the rigid and static nature of the strategic concept, while in reality the management science is permanently evolving (Gurau, 2007). Porter theory emphasizes that the bases for generic strategies are the main sources of competitive advantage. However, Porter’s theory fails to acknowledge that the sources of organizational competitive advantage might change in time (Gurau, 2007). 2.3. Sand Cone capability Despite its limitations, Porter’s frameworks are also still valuable tools in a managerial context. Nonetheless, Gurau (2007) noted that it is important to apply this model having a clear understanding of their shortcoming and take into account alternative models or analytical frameworks, which can complement the Porter’s vision of generic competitive forces. Therefore, we chose the Sand Cone

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Table 1 Advantages and disadvantages of internet based strategies. Overall cost leader Advantages

Disadvantages

Differentiation

Focus

Inventory reduction

Tailored customer management systems

Limited market size discourages new entrants

Increased buyer power More efficient delivery systems Improved warehouse management

Ability for customers to customize products and services

High specialization within specific market niche

Channel conflict Higher threats from substitution and imitation

Customer may find little value in customizable products and services

Overextension of market niche encourages substitution and imitation

Decreased information asymmetry makes comparison shopping easy Neglect of bricks and mortar business

Dilution of brand image or company reputation

Overly narrow market niche induces low demand for product or service

Source: Lumpkin et al. (2002).

model to cover the limitation of Porter’s topology. This model is able to illustrate the structure of four different capabilities contributing to organization strategies as cumulative relationships. The authors proposed that quality was the most deeply oriented capability, and serves as a foundation for the rest of cone (Takala, Leskinen, Sivusuo, Hirvela, & Kekale, 2006). The conventional trade-off model states that unless there is some slack in the system, improving any one of the four basic manufacturing capabilities – quality, dependability, speed and cost – must necessarily be at the expense of one or more of the other three. In the short term, this seems to be the case. Ferdows and De Mayer (1990) suggested trade-off theory does not apply in all cases. Rather, certain approaches change the trade-off relationship into a cumulative one — i.e., one capability is built upon another, not in its place (it is like building up bigger Sand Cones by pouring on more sand) as shown in Fig. 1. Therefore, Ferdows and De Mayer (1990) tried to explain this question through their Sand Cone model, which shows how strategic capabilities can represent a cumulative relationship instead of a trade-off. They also insisted that “to build a cumulative and lasting manufacturing capability, management attention and resources should go first toward enhancing quality, then, while the efforts to enhance quality are further expanded, attention should also be paid

to improving the dependability of the production system, then and again while efforts on the previous two are further enhanced, production flexibility should also be improved, and finally, while all these efforts are further getting enlarged, direct attention can be paid to cost efficiency” (p. 168).

2.4. Hypotheses development Based on previous studies of strategic topology and strategic capability, we assume that Porter’s strategic topology becomes comprehensive through a cumulative relationship instead of a trade-off relationship in strategic capability. This idea will help answer our question “Why do early movers survive, while later entrants fight against heavy odds in the volatile e-business market place?” According to AMR Research (Shepherd, 2000), early mover advantages in the cyber market are as follows: improved stock market valuation, locking in the best customer relationships, ability to influence the industry, increasing the market share, a lead in e-business knowledge and experience, and the retention of core human resources. However, in many instances, being a first mover may not provide an advantage, or may even be a disadvantage (Carow et al., 2004).

Fig. 1. Trade-off model and Sand Cone model. Source: http://www.ifm.eng.cam.ac.uk/dstools/paradigm/trade.html.

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2.4.1. Focus Focus strategy is defined as a firm’s concentration of its efforts on a specific market segment (Porter, 1980). The niche strategy focuses on penetrating into a small but specialized market where other competitors cannot easily enter. Firms choosing this strategy focus on specific groups of buyers, product lines, or geographic areas. Within their more limited market scope, they emphasize either low costs or differentiated products and services. The new entrants will logically choose this strategy to compete against large, established firms by focusing on a particular market niche (Kim et al., 2004b). According to Porter (1985), the benefits of concentrating a firm’s strategy on a particular target segment (focus) cannot be gained if it is simultaneously serving a broad range of segments (cost leadership or differentiation). In the electronic markets, early followers are divided into two types. One is incumbents in the traditional markets, characterized by being well positioned with their resources and having solid core competencies. According to the literature, incumbents initially ignore new entrants with major technological innovations, but tend to compete against them with their product dimensions rather than marketing instruments (Kuester, Homburg, & Robertson, 1999). Leveraging their resources and capabilities, they wait and see how the pioneers test the market, then implement their own unique business model focusing on their products. The other type of early movers includes late pure online entrants in the electronic market. Kim et al. (2004a) argued that focus is a “necessary condition” for a successful e-business competitive strategy. The strategy of focus is more of a “competitive imperative” than a “competitive option” for e-business firms. To illustrate the interrelationship between early followers and their strategic choice under Korea perspective, we take Gmarket as our case. Gmarket Inc., is a retail e-commerce marketplace in Korea. It offers buyers a selection of products and sellers with a flexible sales solution. Their 4Q 2008 gross merchandise value (GMV) increased by 14% to 1106.6 billion won from 970.0 billion won in 4Q 2007. In 4Q 2008, total revenues increased to 77.0 billion won, representing 15% year-over-year growth. By December 31, 2008, they had over 15.6 million registered users. In June 2006, Yahoo! Inc. made a strategic investment in their Company. They argued that their key successes are their unique business model and effective targeting of the broadest seller segment, resulting in a tremendous selection of products available to their buyers. Their business focus has always been somewhat different from existing players in the market. Instead of focusing on large businesses or occasional sellers, they have focused on the needs of small to medium-sized businesses (Gmarket, 2009). Because of their strategy, eBay has lost considerable market share to Gmarket since 68% of the Korean population is Internet users, the highest percentage in the world (Koo, Lee, & Nam, 2003). Hence Hypothesis 1 is developed as follows: Hypothesis 1. Followers tend to concentrate more on focus strategy than early movers. 2.4.2. Differentiation The strategy of differentiation aims to create a product or service that is seen as unique by customers. Porter (1980, 1985, 1996) argued that by creating customer loyalty and price inelasticity, this strategy erects competitive barriers to entry, provides higher margins, and reduces the power of buyers because they feel that they lack substitute products. Kotler (1997) defined differentiation as “the subdividing of a market into homogeneous subsets of customers, where any subset may conceivably be selected as a market target to be reached with a distinct marketing mix.” There are many kinds of differentiation strategies which can be built on many factors, including design, brand image, reputation, tech-

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nology, product features, networks, and so forth. In addition, true differentiated strategy is difficult to be imitated (Kim et al., 2004a). In this study, we adopt Miller’s (1986, 1988) variant of differentiation. Miller posited two types of differentiation to make up for the restricted vision of innovation behaviors suggested by Porter’s framework: innovative differentiation and product/market differentiation. In this paper, we adapt Miller’s (1986, 1988) work and focus on innovative differentiation and market differentiation. Market differentiation is defined as the difference in product quality, service quality, design, and service scope. Mazzeo (2002) suggested that the lower price strategy would not seriously affect business performance when the competitor has a full range of products in the cyber or traditional market, and also insisted that differentiation strategy is influenced by the market entrance order. These two strategies contribute to oligopoly market structures. Porter (2001) suggested that, since the cyber market has emerged, competitiveness through the web is to execute different market positioning strategies. Timmers (1999) explained that differentiated products/services provide unique characteristics and help firms charge a high price to maintain a high margin. That is, firms are rewarded through premium prices based on market differentiation. Innovative differentiation is based on innovation and is akin to Miles and Snow’s (1978) prospectors. They defined prospectors as organizations that continually search for market opportunities and regularly experiment with potential responses to emerging environmental trends. Thus, these organizations are often the creators of change and uncertainty to which their competitors must respond. Miller (1988,1989) suggested that innovative differentiation is most likely to result in success. As successful design and implementation of complex innovative strategies require comprehensive understanding of engineering, marketing, production and environmental factors, a tremendous amount of information processing would be needed. One interestingly real case in terms of differentiation strategies is competition between Microsoft and Netscape. Microsoft declared war after Netscape rejected Microsoft’s proposal of designing Navigator with the Internet-related application programming interfaces (APIs) in Windows 95. Microsoft then withheld crucial technical information that Netscape needed to complete Navigator for Windows 95 as a means to delay the release of the newer version of Navigator. At the same time, Internet Explorer (IE) was developed by Microsoft to compete against Navigator. Thus, Microsoft implemented other strategies in order to diminish the popularity of Navigator. First, IE was free to all. Second, Microsoft bound IE to its popular Windows products (i.e., Internet Explorer 1.0 with Windows 95) based on technical reasons, according to Microsoft. The company also bound its browser to Internet access provider (IAPs) and Internet service provider (ISPs) Internet sign-up programs. IAPs or ISPs were encouraged to promote Internet Explorer and restrict the distribution of its competing browsers. In return, their access programs were included into Windows as effective promotional tools. Based on a survey by AdKnowledge, the share of IE and Netscape were 20% and 77%, respectively, in January 1997 and 49% and 48%, respectively, in August 1998. Three years from the release of IE 1.0, Microsoft was the winner in the war. During 1997 and 1998, though Netscape was the market leader throughout the time, its market share changed dramatically. Specifically, it was the time when Navigator’s share dropped almost by half while IE share jumped almost double (Chiaravutthi, 2006). The Microsoft’s innovation differentiation strategies has led Microsoft became the winner in software industry. In the relation to the influence of competitive tactics upon the moment of entry, for the early entrant, most literature points out that the competitive tactic that has the greater influence on performance is orientation differentiation (Hill, 1988). This is because, by means of these tactics, these companies will be able to take

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advantage of the differentiation benefits that stem from their entry as pioneers to the market, and thus to achieve a superior performance to other competitors. In dynamic sectors the importance of the differentiation orientation for the early entrant is emphasized (Ruiz-Ortega & Garcia-Villaverde, 2008). According to Shepherd (2000), a few early movers in each market that support e-business processes will have an opportunity to build innovative processes at their competitors’ expense. Kerin, Varadarajan, and Peterson (1992) also proposed that, all else being equal, an early mover’s differentiation advantages are greater than a follower’s (Koo et al., 2003). Hence we propose Hypothesis 2: Hypothesis 2. H2a: Early movers implement market differentiation more aggressively than followers. H2b: Early movers implement innovative differentiation more aggressively than followers. 2.4.3. Cost leadership If a product or service is not perceived as acceptable by buyers, a cost leader will be forced to discount prices well below the competitors’ in order to gain sales (Porter, 1980). Cost leadership involves pursuing a position of being the lowest-cost producer through economies of scale and benefiting from experience curve effects in order to build and increase market share (Timmers, 1999). Cost leadership is a possible strategic choice in the Digital Age. Lower price has been a key selling point of e-business firms such as the Internet bookstore Yes 24 in South Korea (Kim et al., 2004a). One study conducted in Korea (Kim et al., 2004a), indicated that 71% of 500 first times online shoppers claimed that price was their most important consideration. Early movers in e-business expect that deployment of an ebusiness strategy would enhance brand loyalty and create a strong eyeball effect, and ultimately provide sustainable profitability. The application of the Internet works toward achieving a sustainable competitive advantage through operating at a lower cost, commanding a premium price, or doing both (Porter, 2001). Although lower cost does not guarantee lower prices, lower prices have been a key selling point for e-business firms (Kim et al., 2004b). For instance, gmarket.com adopts this strategy as one online store in Korea, at least to gain market share through online competition. If the website requires the lowest prices, firms may conclude that they have no choice but to pursue cost leadership (Kim et al., 2004a). Many e-retailers have no choice but to adopt price competition in order to attract customers. Thus, they tend to adopt a cost strategy to survive (Hoffman, Novak, & Peralta, 1999). Early mover strategies are easily imitated and entry barriers are much lower than the traditional market. As a result, the lower cost can be an effective strategy to compete against competitors, since firms can be profitable even in the face of fierce competition if their costs are low enough. Competitive pricing often offers the easiest and the most effective way to retain existing customers (Kim et al., 2004a; Koo et al., 2003). Hence Hypothesis 3 is: Hypothesis 3. Early movers implement cost efficiency strategy more aggressively than followers. 2.4.4. Performance Traditionally, market entrance order is divided into pioneers, early movers, and followers. If a pioneer has success, it will be a bonanza. But, the probability of success is very low. On the other hand, if a follower imitates the early mover’s business activities before the early mover firmly occupies the market, it will have better performance than the early mover (Mitchell, 1989, 1991). Mitchell also argued that the effect of market entrance order is affected by external factors such as market maturity and degree of imitation. Yet, Min and Wolfinbarger (2005) indicated that if first movers use their early entry to determine customer needs and then

successfully fulfill promises to those customers, then first movers can enjoy the benefits of customer loyalty. The timing of entry into a new market is an important issue for firms. Entering the market at the right time can often be critical factor of success (Li et al., 2003). In terms of organizational learning, first movers are more likely than their followers to have more extensive learning and thus have better access to opportunities. They can often initiate the build-up of experiential raw material so that they develop the most advanced insights, associations and causal maps within a specified context (Li et al., 2003). In an empirical test of small and medium size firms, Durand and Coeuderoy (2001) stated that the early mover’s process differentiation and innovation differentiation produce better performance than the follower’s imitation strategy. However, Shankar et al. (1998) insisted that an innovative follower may create excellent performance through a high market potential and repurchase rate. In contrast, a non-innovative follower confronts the early mover’s market entrance barrier. In the following year (1999), they released an interesting research on the same pharmacy industry. This research showed that in the growth stage the follower has better performance than the early mover, and in the mature stage, the follower cannot rise to the early mover’s performance level. In this paper, we will test recent conflicting results of Durand and Coeurderoy (2001) and Shankar et al. (1998), Shankar, Carpenter, & Krishnamurthi (1999) by examining an explosive cyber market. Hence, like in traditional markets, early mover performance is assumed to be better than the follower’s (Koo et al., 2003). Our fourth hypothesis is as follows: Hypothesis 4. follower.

The early mover has better performance than the

2.4.5. Cumulative causal relationships among strategic capabilities Gonsalves, Lederer, Mahaney, and Newkik (1999) examined Porter’s three generic strategies for websites. They found that managers’ greatest expectation from their websites was that they would help in marketing to specialized customer segments (focus strategy). Their second expectation was that the site would help differentiate their products and services from those of their competitors (differentiation strategy). Their least important expectation was to use the Web for cost leadership (cost efficiency strategy). Managers sought cost leadership considerably less than focus and differentiation. Gonsalves et al. suggested that when managers expected the website to help customers acquire their products, managers thought it would also help their organizations carry out all three generic strategies. Consequently, the website was expected to reduce the organization’s costs and to serve as a very powerful competitive tool. Durand and Coeurderoy (2001) clarified that a firm’s performance depends on the firm’s market entry order and strategic orientations (cost leadership and differentiation), and the firm’s age partially drives its financial and organizational performance. In addition, Noble, Sinha, and Kumar (2002) suggested that focus and market differentiation have a positive impact on firms’ performance. According to Levit (1983), the technology trend has pushed market toward global commonality. This commonality has led inescapably to the standardization of products, manufacturing, and the institutions of trade and commerce. Success in a competitive world depends on efficiency in production, distribution, marketing, management, and inevitably becomes focused on price. Superior quality and reliability are embedded into their cost structure. They compete on the basis of appropriate value, with the best combination of price, quality, reliability, and delivery for products that are globally identical with respect to design, function, and so forth. Hence, we assume that strategic capabilities have a critical

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Fig. 2. Research framework based on the Sand Cone model.

path as shown in Fig. 2. Our final set of hypotheses can be postulated concerning the four competitive strategies and performance: Hypothesis 5. H5a: Performance is affected by four strategic capabilities. H5b: Market differentiation and innovative differentiation strategies enhance cost leadership strategy. H5c: Focus strategy enhances market differentiation, innovative differentiation and cost leadership strategies. 3. Research method and analyses For the purpose of this study, we conducted a survey-based study in South Korea. While the growth of online business in the USA has somewhat stabilized, European and Asian markets have witnessed an explosive growth in electronic commerce. Among these nations, Korea presents a unique opportunity to study the electronic commerce phenomenon for several reasons: (1) The number of .kr domain has increased significantly every year, multiplying by 112 times, from 8045 in 1997 to 906,116 domains in 2007. Data from NIDA reports that the highest rate of increase were in 1998–1999, approximately 691%. Research conducted by NIDA with 10.000 household samples in 2006 showed that ownership of desktop computers exceeds 70% (NIDA, 2008). (2) Widespread use of the best high-speed Internet technology in the world. Household with Internet access in 2006 was around 74.8%, increased around 4% from 2005. The Internet population was estimated approximately 34.120 millions (NIDA, 2008). (3) The high level of willingness to experiment with and minimal resistance to new technologies on the part of Koreans — since Koreans have gained self-efficacy from the successes of e-transformation and the can-do spirit nurtured through overcoming countless hardships, Koreans have new found confidence to adopt modern ICT (Lee, 2003). This country is also called “the world most wired country,” over 20 million people are connected to super fast broadband connectivity and has made using Internet part of their daily life (Chon, Park, Kang, & Lee, 2005). 3.1. Data collection The sample firms examined in this study comprised of online and hybrid (on/offline) firms in Korea. The questionnaire measured the Porter’s topology of strategy as perceived by managers. Questions were derived from Porter’s generic strategies literature (Durand & Coeurderoy, 2001; Spanos & Lioukas, 2001). A pilot test was conducted with the founders of 13 Internet venture firms in

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Korea to improve the clarity and relevance of the questionnaire. In developing the questionnaires, the items for generic strategies are based on Durand and Coeurderoy’s (2001) study in cost leadership: positioning of prices and production/service costs of competitors. The items for differentiation and focus are based on the works of Dess and Davis (1984) and Miller (1987). We adapted and developed four questions to distinguish the degree of effort from competitors. Secondly, we defined market differentiation as the degree of difference in product quality, design, service quality, and breadth of products/services from competitors. Innovative differentiation is referred as innovative products/services, processes, and technology compared to competitors. Focus strategy consists of the degree of focus on the price, process innovation, cost reduction, and refinement of existing products/services in the niche market. Finally, the organization’s performance can be measured in two different ways: quantitative performance such as profitability and market share, and qualitative performance such as customer satisfaction and employee satisfaction. In this paper, we used quantitative performance based on the studies by Lee and Miller (1996). In measuring organizational performance, we adopted managerial self-reports method. For this purpose, six indicators are used: the average margin for two years, total profit, rate of increase in employee number, rate of increase in assets, earning per share, and the rate of growth in sales. Woodside, Sullivan, Trappey, and Randolph (1999) noted that managerial self-reports of organizational performance have been found to be consistent with objective performance measures internal to the organization (Dess & Robinson, 1984) as well as secondary published data external to the organization (Conant, Mokwa, & Vadarajan, 1990). A sample of 1000 firms was randomly selected from an ecommerce directory published by Korea National Statistical Office. The directory classifies each firm as either online or brick and click. We initially conducted the survey by mail and followed up with emails, phone calls and personal visits. The survey took four months to complete from August though December in 2001. According to Ministry of commerce, Industry and Energy (MOCIE) (2003) of South Korea, e-Business initiative in Korea as an authorized regulation was established in 2001. Moreover, an Organization of Economic Cooperation and Development (OEDC) report dated October 2001 stated that Korea is the most advanced country in the world in terms of broadband Internet network connection. Also, both general and specialty retailers were involved in ecommerce operations, with most specialized in retail sales (84.8%) in 2001. In 2000, the fact recorded that Korean e-commerce was in development phrase. For instance, in this year, Samsung Group, SK Group, Lotte Group, Kolon Group, and Cheil Jedang became the pioneer of Internet business in Korea. Many offline companies joined forces to establish e-commerce entities like Asia BtoB Ventures, GTWeb Korea, and eNtoB to create the foundation for cooperation in the online environment. Likewise, US also reported the same trend during this stage. E-commerce outperformed total economic activity in manufacturing shipments, merchant wholesale trade sales, and retail trade sales sectors measured between 2000 and 2001 (US Department of Commerce, 2003). Thus, even we used the dataset collected in 2001, it is interesting to know that in this phase, e-commerce trend may represent the importance of theory development and analysis conducted in our research. We received a total of 135 responses in the study for a response rate of 13.5%, out of which 32 we discarded for rigorous analysis. To determine the presence of response bias, we classified the responses into two groups. Forty-eight responses received during the first two months were classified as early returns and 87 received during the last two months as late returns. We compared the two groups for any significant difference in responses using the

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chi-square test of independences. We found no significant differences between the two groups. After discarding 32 unusable returns, we finally utilized 103 responses for our study. This study tests the hypotheses with 103 usable returned questionnaires. The return rate was ultimately 10.3%. The demographic characteristics of the respondents are as follows: CEOs (10.7%), top managers (14.6%), middle managers (16.5%), and department level managers (58.3%). The types of business that the responding firms belong to are: e-shopping (37.9%), information brokerage (12.6%), virtual third party marketplace (10.7%), business community (7.8%), financial services (7.8%), value chain service (4.5%), e-procurement (1.9%), pharmacy (1.0%), and others (15.57%). The distribution of business types of the responding firms was similar to that of the original 1000 firms selected for the study. We classified the sample into two groups; the early mover group and the follower group, based on Rogers’ (1995) classification scheme. Rogers classified adopters as innovators (2.5%), early adopters (13.5%), early majority (34%), late majority (34%) and laggards (16%). In this study, we defined early movers (42.4%) as being first or second entrants in their own e-business marketplace, and followers (57.6%) as being third or later entrants. 3.2. Validity Content validity refers to the extent to which the instrument measures what it is supposed to measure. Most of the measures used in the study were adopted from previous studies on the topics. While basing the study on the established literature provides a considerable level of validity to further improve the validity of the study, we conducted a pilot test with a panel of experts that consists of two academic researchers and five practitioners. To ensure that the meaning and nuance of the instrument are not distorted during the translation process, we independently translated the instrument from English to Korean then from Korean back to English. The instrument was revised to remedy any discrepancies. In addition, we performed factor analysis to confirm the construct validity of the instrument. The results of the analyses are shown in Table 2 for the independent variables (Porter’s strategies) and Table 3 for the dependent variables (business performance). The results supported the constructs of our research model. All items used in the instrument to measure the four independent variables were cleanly loaded into the four factors and all six items used to assess the dependent variable were loaded into a single factor with high loading scores.

3.3. Reliability We examined the reliability of the instrument with composite reliability estimates using coefficient alpha statistics (see the last column in Tables 2 and 3). All coefficients exceeded Nunnally’s (1978) recommended 0.70 level of internal consistency. In the case of strategic topology constructs, the four factors identified accounted for 74.019% of the observed variance. Factor analysis was conducted to assess the construct validity of the measures and to determine the underlying factors influencing organizational performance. For factor analysis, we used principal components analysis to extract the data with the varimax rotation technique. Without specifying the number of factors, four factors with eigenvalues above 1 were found. The loading of each of the 13 measures on its respective factor is well over 0.70. For organizational performance, one factor explained 74.445% of the observed variance and the factor loadings are higher than 0.70 with an eigenvalue of 4.467. Nunnally (1978) recommended that in order to assess the fit between the items and their construct, all of the primary factor loadings should be greater than 0.5. For this test, all factor loadings satisfied this requirement, which demonstrates a good match between each factor and related items. The results of exploratory factor analysis indicate that the measures chosen are true constructs, because there are relatively high correlations between measures of the same construct using different methods and low correlations between measures of construct that are expected to differ. After testing discriminant and convergent validity of each multi-item scale, we summed the value of each construct and then conducted a one-way ANOVA to detect strategic differences between early movers and followers. The measurement model was assessed through confirmatory factor analysis, using maximum likelihood estimation on the covariance matrix (Jöreskog & Sörbom, 1993). The model tested for the casual relationship included five latent variables: focus, market differentiation, innovative differentiation, cost leadership and performance. Table 4 presents the standardized factor loading (lambda) and t-values (p < 0.05) for the measurement portion of the path analysis. As is apparent in Table 4, all the variables loaded significantly on the factors as hypothesized. A p value greater than 50% implies that the variance captured by trait was exceeded by error components. Finally, the squared multiple correlations of the individual items give an indication of the lower bound of the measures’ reliability. Most of the measures are above 0.40, indicating a moderate level of construct validity.

Table 2 Exploratory factors analysis of independent variables. Variables

Focus

Product differentiation

Innovation differentiation

Cost leadership

Cronbach alpha

Focus on price in the niche market Focus on process innovation in the niche market Focus on cost reduction in the niche market Focus on refining existing products/services in the niche market

0.859 0.848 0.778 0.748

0.169 0.198 0.082 0.159

0.088 0.071 −0.026 0.015

0.089 0.024 0.060 0.088

0.839

Differentiation of quality from competitors Differentiation of design from competitors Differentiation of service quality from competitors Differentiation of breadth of products/services

0.167 0.059 0.289 0.179

0.818 0.788 0.784 0.729

0.169 0.225 0.153 0.123

0.009 −0.064 0.172 0.166

0.833

Innovative products/services over competitors Innovative process over competitors Innovative technology over competitors

0.006 0.045 0.064

0.209 0.218 0.151

0.886 0.886 0.845

0.057 0.100 0.105

0.893

Positioning of prices over competitors Positioning of production/service cost from competitors

0.069 0.128

0.084 0.081

0.058 0.163

0.910 0.885

0.827

Eigenvalue Percentage of variance explained

4.581 35.230

2.270 17.462

1.541 11.858

1.231 9.469

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Table 3 Results of factor analysis and reliability test in organization performance. Construct

Variables

Loading values

Alpha (˛)

Organizational performance

Average margin for two years Rate of growth in sales Earnings per share Total profit Rate of increase in assets Rate of increase in employees

0.897 0.889 0.886 0.879 0.879 0.737

0.931

Eigenvalue Percentage of variance explained (%)

4.4467 74.445

Table 4 Confirmative factor loading and t-value. Constructs and indicators

Lambda

t-value

Squared multiple correlation

Focus on price in the niche market Focus on process innovation in the niche market Focus on cost reduction in the niche market Focus on refining existing products/services in the niche market

1.00 1.27 1.24 1.01

7.21 7.11 6.04

0.46 0.73 0.70 0.46

Differentiation of quality from competitors Differentiation of design from competitors Differentiation of service quality from competitors Differentiation of breadth of products/services

1.00 1.18 1.32 1.06

6.44 6.84 5.93

0.43 0.60 0.75 0.48

Innovative products/services over competitors Innovative process over competitors Innovative technology over competitors

1.00 1.04 0.87

10.77 8.97

0.76 0.83 0.58

Positioning of prices over competitors Positioning of production/service cost from competitors

1.00 0.67

2.93

0.80 0.41

Average margin for two years Rate of growth in sales Earnings per share Total profit Rate of increase in assets Rate of increase in employees

1.00 1.01 1.00 0.99 1.02 0.78

11.54 11.37 11.18 11.76 7.62

0.74 0.75 0.74 0.72 0.76 0.44

4. Results In general, the survey results demonstrate that early movers are positively related to market differentiation, innovative differentiation, and cost efficiency. However, there was no difference in focus between early movers and followers even though we hypothesized that followers would implement a focus strategy more aggressively than early movers did (see Table 5). Table 6 shows the difference between early movers and followers in terms of performance. As hypothesized, early movers have significantly better performance than followers. The hypothesized paths in the research model were tested by the means of LISREL8.53 (Jöreskog & Sörbom, 1993). Fig. 3 presents the standardized path coefficients in the research model and summarizes the result of path hypothesis testing among strategic capabilities. Bold lines in Fig. 3 indicates the significant paths among latent constructs and thin lines represent non-significant paths. The measures of overall goodness-of-fit for the entire model are good as shown in Table 7. To assess the model, multiple fit indices (chi-square statistic – 2 , Normed Fit Indices – NFI; Non-Normed Fit Index – NNFI; Goodness of Fit Index – GFI; Adjusted Goodness of Fit index – AGFI; Root Mean Square of Error Approximation – RMSEA) are presented. The overall model showed an acceptable fit: 2 = 150.63; chi-square/df = 1.0533; NFI = 0.87; NNFI = 0.97; GFI = 0.87; AGFI = 0.82; RMSEA = 0.023 (Jöreskog & Sörbom, 1993). RMSEA takes into account parsimony as well as fit by examining discrepancy per degree of freedom. The RMSEA value (0.023) of our research model is equal to the recommended value of reasonable fit (Browne & Cudeck, 1992; Taylor & Todd, 1995).

Table 5 Results of a one-way ANO VA between early mover and follower in strategy topology. Constructs

Sum of squares df

Focus Between groups Within groups Total Market differentiation Between groups Within groups Total Innovation differentiation Between groups Within groups Total Cost leadership Between groups Within groups Total

0.237 1 969.117 97

Mean square F

Sig.

0.237 9.991

0.024

0.878

24.669 6.168

3.999

0.048

21.303 5.772

3.691

0.058

8.786 2.676

3.284

0.073

969.354 98

24.669 1 598.321 97 622.990 98

21.303 1 559.868 97 581.172 98

8.786 1 259.538 97 268.323 98

Note. In this paper, we used significant levels of 0.05 and 0.1 because the subjects are organizations. We believe that the significant level of organization subjects should be more liberal than that of individual subjects.

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Fig. 3. Path coefficients for the research model.

Table 6 Results of a one-way ANOVA between early mover and follower in performance. Constructs Performance Between groups Within groups Total

Sum of squares

df

Mean square

390.082 1895.938

1 97

2286.020

98

390.082 19.546

F

Sig.

19.957

0.000

Table 7 Measures of model fit. Fit measure

Recommended value

Fitness measure

Chi-square Chi-square/df NFI NNFI GFI AGFI RMSEA

≤3.0 ≥0.80 ≥0.90 ≥0.90 ≥0.80 ≤0.08

150.63 1.0533 0.87 0.97 0.87 0.82 0.023

5. Discussion The results of ANOVA indicate that early movers tend to implement market differentiation, innovative differentiation, and cost efficiency more than followers; even though focus strategy is not statistically significant, early movers show a higher level than followers (see Tables 5 and 6). How can we explain these results? The early mover effect is crucial in the cyber market even though followers can make inroads in the market through an imitation strategy. That is, e-customers generally prefer the early mover over the follower because the early mover is seen as offering more secure and trustworthy transactions. Likewise, a study by Varadarajan et al. (2008) concluded that first movers in the digital environment need to focus on achieving superior positions in resources that would lead them to get close to the customer fast, create switching costs, and retain them through ongoing investments in multi-faceted innovations. Specific to the electronic market, the early movers appear to respond quickly to changing electronic market conditions. Miles

and Snow (1978) argued that there are significant differences in marketing orientation, marketing strategy, and marketing-related behavior between defenders and prospectors in the traditional industry. Defenders are more likely to rely on more traditional products in their industry rather than search for new technology or product types. Conversely, the electronic market is very turbulent and new marketing strategies need to be implemented aggressively to defend and expand market positions. It is important that a company understands how e-commerce fits into the broader context of the business and its strategy. By focusing on a specific customer segment, they are able to target specific groups of customers (Quader, 2006). Although followers are oriented toward marketing strategies on the basis of new opportunities, early movers have a higher level of adaptive marketing strategies than followers. Another explanation for the results would be that although there are few costs associated with switching in the cyber market (Porter, 2001), e-customers highly value brand loyalty because they prefer a highly recognizable and trusted brand name (Mellahi & Johnson, 2000). Thus, it is not surprising that the online firms spend approximately 40% of their revenue on brand building (Margolis, 1999). This reason is supported by Chang’s study (1997). He found that customers of an Internet bookstore in Korea saw brand as a more important aspect of their buying criteria than price. We found that the early mover’s strategic capability is higher than the follower’s in market differentiation, innovative differentiation and cost leadership. The path analysis involving strategic capabilities shows some interesting results. With regard to performance, market differentiation (t = 2.16), innovative differentiation (t = 2.61), and cost leadership (t = 1.74) constructs appear to be significant predictors, while focus does not directly influence performance. However, focus affects cost leadership (t = 1.67), market differentiation (t = 3.87) and innovative differentiation (t = 1.73). Interestingly, the results indicate that innovative differentiation affects performance more than market differentiation and cost leadership, while focus affects performance channeled through cost leadership, market differentiation and innovative differentiation. Magretta (2002), claimed that “It was precisely this kind of competition – destructive competition, to use Michael Porter’s term – that did in many Internet retailers, whether they were selling pet

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supplies, drugs, or toys. Too many fledgling companies rushed to market with identical business models and no strategies to differentiate themselves in terms of which customers and markets to serve, what products and services to offer, and what kinds of value to create.” Hence, differentiation strategies will be associated with higher performance than generic strategy of cost leadership (Kim et al., 2004b). Moreover, they argued that firms that pursue narrowly focused strategies are unlikely to be as successful as firms pursuing either cost leadership or differentiation strategies because those firms can take advantage of the infinite scalability of Internet technologies to reach simultaneously both broad and narrow customer segments (Kim et al., 2004b). The empirical results also indicate that Ferdows and De Mayer’s (1990) accumulative relationship among the strategic is supported. The Sand Cone model can better explain relationships in strategic capabilities. They defined “sand” in the Sand Cone model as a standin for management effort and resources. To obtain a Sand Cone, a market entrant, regardless of whether it is an early mover or a follower, first creates a stable foundation of focus in a niche market. Pouring more sand, the entrant enlarges the focus foundation while also beginning to tackle differentiation strategy against its competitors. To build a taller Sand Cone, by enhancing the foundation layers of focus and differentiation, the market entrant can start building a stable and well-founded cost strategy. However, unlike Hypotheses H5b, there is no significant causal relationship between cost and market differentiation, and between cost and innovative differentiation. As previously mentioned, the impact of strategic orientations (cost leadership and differentiation) of a firm on performance is affected by the firm’s order of entry into the market (Durand & Coeurderoy, 2001; Lee, Park, & Lee, 2003; Yan & Ghose, 2009). While nearly all firms can benefit from e-business processes and techniques, the earliest movers into online markets will reap the greatest rewards. Most traditional companies take a cautious approach to e-business. They initiate studies, analyze requirements, build ROI models, and approve pilot programs when they need to act to develop their online markets. 6. Conclusion In sum, this empirical study investigates the differences in strategic choices of online firms based on their strategic capabilities and performance. Specifically, this study reviews early mover advantages and disadvantages based on Porter’s strategic topology, as well as strategic capabilities based on the Sand Cone model. The results show that early movers have more cumulative strategic capabilities than followers do in market differentiation, innovative differentiation, and cost leadership. Limitations and implications Certain limitations should be recognized when interpreting the findings. Firstly, one possible limitation is that the sample size of this research is relatively small, even though we did our best to collect data from several sources. Secondly, this survey was conducted in South Korea in 2001, with the possibility of different indication under different and current market environment. Thus, researchers should be careful in generalizing the results of this study without proper explanations. In future research, the effect of entry order in a long-term basis, rather than a snap shot analysis, should be performed to truly see the real advantages of early mover and followers. Another possible limitation of this study is, we concentrate our analysis on the companies conducting transaction on the Internet. A comparison study to evaluate the difference between brick and click and brick and mortar, or both is needed to enhance our hypotheses. Moreover, the other issues such as product charac-

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teristics, brand image, companies’ size might influence the firms’ strategies under online environment. However, this paper does not discuss the link between various sources of these competitive advantages and the strategies that can be adopted by the companies in detail. Thus, we call for further research to test these variables by employing our model empirically. Upon the limitations, our empirical research has a sum of theoretical contributions. First, by adopting Porter’s generic strategies and Sand Cone model as complementary tools, we have successfully investigated the reliability of these topologies in an online environment. In addition, our empirical results showed that early movers tend to implement market differentiation, innovative differentiation, and cost efficiency more than followers. Second, we explored the differences in strategic capabilities and organizational performance between early movers and followers in the cyber market. While prior researchers have investigated the relationship between organizational performance and strategy choices in traditional industry (e.g. Dess & Davis, 1984; Hambrick, 1983; McFarlan, 1983; Parsons, 1983; Porter, 1980, 1985), our empirical study proved it in an Internet environment. This paper makes two important contributions for practice. Firstly, we suggest that since bricks and mortar companies have long understood the early mover advantages, now online companies need to learn to apply the same principles. In e-commerce, first movers’ sustainability of their advantages is determined by the immutability of the resources and configuration on which they depend (Mellahi & Johnson, 2000). Early movers provided critical resources in the e-commerce industry that result in competitive advantage based on largely intangible assets and capabilities, such as innovativeness, technical expertise and knowledge. Innovation literature indicates that innovation, knowledge assets, and capability may continue to give high returns for early movers (Varadarajan et al., 2008). However, followers are likely to quickly adopt similar innovation (Dos Santos & Peffers, 1995). Investment in the cyber market should be viewed strategically, as plans will probably have to be altered or replaced in a matter of months. However, despite this fluid environment, companies must commit themselves now. Businesses that delay in the conversion to e-business will be at a significant, and perhaps fatal, disadvantage over the long term (Christensen, Rayner, & Verlinden, 2001). The emergence of e-commerce has created a novel marketplace (Chang, Jackson, & Groven, 2003), hence within it, customer needs and expectations when shopping online often have not been well understood, especially by early entrants (Min & Wolfinbarger, 2005). Secondly, most of traditional managerial approaches to improving business performance were based on trade-off theory. This study shows that trade-off theory does not apply in all cases. Through the empirical results, we are suggesting that every layer of capabilities requires continuous attention; one never leaves the necessity of investing in the basics of performance. In fact, the higher and fancier the capability sought, the more enhanced form the bottom layer of capability is required. To build cumulative and lasting strategic capabilities in e-business, management attention and resources should be concentrated first on enhancing focus, and then while the efforts to enhance focus are further expanded, attention should be paid to improving differentiation, then while efforts on the previous two are further enhanced, attention should be directed to cost efficiency. However, depending on a unique situation the firm is in, the accumulating order of strategic capability may be varied. As Kim et al. (2004b) claimed, under e-business context, focus strategies may be more attractive than cost leadership strategies. Accordingly, it seems that turbulent environments (Kim & McIntosh, 1999) and global environment (Chan & Wong, 1999) require flexible combinations of strategies. This study provides a modest step in this circumstance, advises the companies for the importance of e-

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commerce strategies in gaining the competitive advantages and winning the market. Acknowledgements The authors thank anonymous reviewers of this journal. We especially thank Dr. Sang M. Lee for his substantive suggestions and thank Yulia Wati for assisting our revision. We acknowledge that

this paper adopts data set on our paper “the differences of strategic choice and performance between early mover and followers on cyber market” and develops new strategic model “cumulative strategic capability model”. Appendix A. Survey on organization strategy of online and offline firms

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S.-G. Lee et al. / International Journal of Information Management 30 (2010) 239–255 Woodside, Sullivan, Arch G., Trappey, Daniel P., III, & Randolph, J. (1999). Assessing relationships among strategic types, distinctive marketing competencies, and organizational performance. Journal of Business Research, 45, 135–146. Wright, P. A. (1987). Refinement of Porter’s generic strategies. Strategic Management Journal, 8(1), 93–101. Yan, R., & Ghose, S. (2009). Forecast information and traditional retailer performance in a dual-channel competitive market. Journal of Business Research, doi:10.1016/j.jbusres.2009.02.017 Sang-Gun Lee is an associate professor in Ajou University, Korea. He received a PhD in management information systems from University of Nebraska-Lincoln, USA. His research area is on technology diffusion, ERP, Metaverse and e-commerce. He is a specialist at statistical and analytical analyses using SPSS, SAS, Clementine, AMOS and LISREL and is also interested in simulation methodology using ithink software and WITNESS program. He has published more then 40 papers including International Journal of Production Research, Information and Management, International Journal of Information Management, Small Business Economics, Industrial Management & Data Systems, Journal of Internet Commerce, and International Journal of Management Science. He is now teaching several classes such as Introduction of e-Biz, SAP MM module, telecommunication in undergraduate and research methodology and simulation in graduate. Chulmo Koo is an assistant professor in Chosun University, Korea. He received a PhD in management information systems from Sogang University, Korea. His

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research area is on Electronic Commerce Strategy and Performance, Green IT Management, Technostress, and Social Network Technologies Usage. His papers have been appeared in the International Journal of Electronic Commerce, International Journal of Information Management, Journal of Internet Commerce, Industrial Management & Data Systems, and Information Systems Frontiers. Currently he does actively research on Green IT Practices and publish in AMCIS 2009 and HICCSS 2010. Kichan Nam is a professor in the Department of Service Systems Management and Engineering, the School of Management at Sogang University, Seoul, Korea. He received his PhD in management information systems from the State University of New York at Buffalo in 1995. His major research topics are IT outsourcing, service Level agreement, IT service management, IT strategy, IT performance evaluation, service science, etc. His publications are found in Information Systems Research, Communications of the ACM, Decision Support Systems, Journal of Information Management, European Journal of Operational Research, Information Systems Frontier, International Journal of Information and Management, International Journal of Electronic Commerce, Expert Systems with Applications, and major IS journals in Korea. Also he actively works with Korean major IT companies in the area of outsourcing and serves as a member of IT-related committees for the Korean government. Currently, he is a Chairman of itSMF Korea.