Uniqueness: How it affects firm
performance and market share, and
implications for platform firms
Daniel Dijkstra
S2979284
MSc BA Strategic Innovation Management
University of Groningen
Faculty of Economics and Business
Supervisor: J. Oehmichen
Co-assessor: F. Noseleit
2 Abstract
In this study, I argue that in order to obtain superior firm performance, firms should not choose to pursue a unique strategy. I argue that rather than focusing on unique resources, firms should focus on core competencies and create dynamic capabilities. Thus I argue that uniqueness has a negative relationship on firm performance. Further, for platform firms, due to winner-take-all (WTA) dynamics and network effects, performance differs from traditional firms. Compared to traditional firms, unique platforms may have more opportunities in gaining market share, while obtaining lower firm performance than unique traditional firms. Based on panel data on 2,542 firms from 2008-2017, the results indicate that firm uniqueness appears to be negatively related to firm performance, but this is not empirically supported. Further, the findings show support for a negative relationship of uniqueness on market share. In addition, I find that for platform firms, uniqueness has less negative implications for market share compared to traditional firms. Yet, uniqueness could lead to even worse firm performance for platform firms compared to traditional firms.
3 Introduction
Firm uniqueness has been an important area of research within the field of strategic management. Existing research has contributed to why some firms pursue a different strategy compared to industry rivals. These firms may obtain resources that are viewed as unattractive by other firms in the industry. Thus, it is of importance to understand the effects of pursuing such a unique strategy and how it affects firm performance and its position in the market. Uniqueness in firms exist when firms pursue a strategy to create or acquire unique resources and combine these unique resources to create a unique combination of resources, to create superior firm performance (Litov et al, 2012; Lippman and Rumelt, 2003: 1084; Rumelt, 1984; Barney, 1986; Montgomery and Wernerfelt, 1988; Brandenburger and Stuart, 1996). Recently, a novel measure of uniqueness has been developed by Litov et al (2012), they have developed a measure based on industry segment data. This contribution to the field of strategic management may help further explain the relationship between firm uniqueness and firm performance. By using industry segment data from different industry segments, the measure of uniqueness by Litov et al (2012) may be able to explain the level of uniqueness in the resource portfolio of the firm.
The resource-based view (RBV) as proposed by Barney (1986) has been a central theory that describes how resources are fundamental to the firm and how these may lead to superior performance. The paper by Barney (1986) has laid out the groundwork for other major theorists, which have extended the RBV. Some studies argue that the RBV theory as developed by Barney (1986) has been static, as it addresses the possession of resources, yet, it fails to explain how these resources should be exploited to create sustained superior firm performance (Priem and Butler, 2001). The broad nature of RBV gave theorists opportunities to develop upon the RBV. The gap between resource possession and the successful exploitation of these resources has been explained through several theories.
Prahlahad and Hamel (1991) introduced the theory of core competencies, arguing the importance of competencies and complementary resources to the core competencies of the firm.
4 The research on platform firms has gained traction over the years. Platform firms operate differently compared to traditional firms, as these firms are characterized by network effects and operate in markets with few dominant platforms (Cennamo et al, 2018; Eisenmann, 2006; Katz and Shapiro, 1994). Platforms not only compete directly with each other, but they also face fierce competition for resources and complements. This can be a result of customers preferring to use a platform with more users, and thereby offering a higher variety of choice (indirect network effects) or because customers prefer to use a platform with more customers (direct network effects) (Eisenmann, 2006, Evans, 2003; Rochet and Tirole, 2003). In platform markets, network effects are strong and could decide which platform prevails over time. Therefore, the goal of many platform firms is to build a large user base. Existing research suggests that eventually one or few platforms prevail in most platform markets, where one platform dominates the market and can influence the market in its favor. Hence, existing research has defined this phenomenon as the winner-take-all (WTA) strategy (Caillaud and Jullien, 2003; Eisenmann, 2006; Katz and Shapiro, 1994; Shapiro and Varian, 1999). Further, in their strategy to gain the most users, platforms often discount or incentify users to join the platform (Cennamo et al, 2013; McIntyre and Subramaniam, 2009).
Yet, no consistent definition has been developed as to what accounts as a platform firm. At their core, platform firms, following the definition by Gawer & Cusumano (2014) have an innovative business ecosystem and operate in high-tech industries driven by information technology. Further, taken broadly, platforms may be distinguished as internal platforms and external platforms. Internal platforms are characterized as ''a set of assets organized in a common structure from which a company can efficiently develop and produce a stream of derivative products''(Gawer & Cusumano, 2014). For example, a car manufacturer may use the same vehicle frame across different cars. However, in this study, I define platforms firms based on external platforms. External platforms are characterized as ‘’products, services, or technologies that act as a foundation upon which external innovators, organized as an innovative business ecosystem, can develop their own complementary products, technologies, or services.’’(Gawer & Cusumano, 2014).
5 terms of pursuing a strategy that is characterized as unique. Therefore, it is interesting to research the differences in strategy between platform firms and traditional firms. As over the years, platform firms have become more prevalent in an increasing amount of industries, it is important for both management of traditional and of platform firms to find the optimal strategy in order to increase firm performance.
Overall, researching uniqueness on firm performance further contributes to existing RBV research and extends the knowledge on firm uniqueness. By distinguishing firms between traditional firms and platform firms, this research aims to contribute to the field of strategic management as well as contributing to the research on platform firms. No research so far has investigated how platform firms and traditional firms differ in terms of pursuing a unique strategy. Hence, this could be an important research gap within the field of strategic management. Investigating differences between platform firms and traditional firms, in terms of firm uniqueness, may help further explain the strategic differences between platform firms and traditional firms. Therefore, it is important to further research this area in order to contribute to the existing RBV and platform research and gain further insights. Having identified the research gap in the role of platform firms on the firm uniqueness and firm performance relationship, and having stated the importance of the subject, I have come up with the following research question:
RQ: What is the relationship between firm uniqueness and firm performance and how does the relationship differ
for platform firms?
Literature review
Theoretical background
6 only resources are important. Rather, resources can be exploited through competencies. The authors argue that especially core competencies are good antecedents for creating competitive advantages. Core competencies are defined as ''the collective learning within the corporation'' (Prahalad and Hamel, 1990). This relates to the firm's inimitable skills, technologies, and knowledge behind the exploitation of resources. Core competencies help explain why a strategy purely based on resources may not lead to superior performance. Further, another important
extension on the RBV is the theoretical development of dynamic capabilities. Dynamic capabilities may explain how ‘’resources and core competencies are developed, deployed, and protected’’(Teece et al, 1997). Dynamic capabilities are defined as ‘’the firm’s ability to integrate, build and reconfigure internal and external competences to address rapidly changing environments’’ (Teece et al, 1997). Essentially, dynamic capabilities are capabilities of a firm to adapt the firm’s routines and processes in such a manner that the firm can reconfigure its resources to changes in the environment. Dynamic capabilities explain why the processes and competencies behind resources are important to sustain performance over time. It explains why not only the possession of resources is important, and it addresses one of the main criticisms of the RBV by explaining firm performance over time. Through the
development of the RBV literature over the years, the RBV has become increasingly extensive in explaining sustained competitive advantages and has been important in the field of strategic management.
Hypothesis development
Uniqueness on firm performance
Congruent to the RBV, resources have to be both valuable and rare in order to create a competitive advantage (Barney, 1986). Firm uniqueness is characterized as attaining and possessing unique resources. Unique resources can be viewed to be essentially a resource that is a combination of both valuable and rare. Foremost, unique resources can be valuable. Valuable resources are resources that improve a firm's efficiency and effectiveness. Moreover, resources are defined to be rare when a large number of rivals choose not to pursue a similar resource (Barney, 1986). Further, rare resources are not easily obtainable or available by most rivals in the industry. Resources satisfying the valuable and rare characteristics may help the firm to be able to create a competitive advantage (Barney, 1986).
7 find a way to attain, substitute or imitate the combination of valuable and rare resources. Thereby diminishing the returns gained from the competitive advantage. Therefore, in addition, firms should find and implement resources that are not imitable or substitutable next to satisfying the valuable and rare conditions. Furthermore, these resources should be managed through capabilities to exploit these resources (Peteraf, 1993; Henderson and Cockburn, 1994). Therefore, it is important for firms to strategize in such a manner that the strategy is not to build a higher quantity of resources. Alternatively, firms should integrate and build certain resources and capabilities to address changes in the environment, and change its resource portfolio over time.
Moreover, by having a unique combination of unique resources, unique firms are likely to have their resources dispersed across different industries, resulting in an increase in complexity of the resource portfolio. Increased complexity in the resource portfolio typically requires the allocation of additional resources such as managerial resources (Zhou, 2011). Knowledge flows less effectively and less efficiently when it is highly dispersed. Consequently, adapting resources and processes in changing environments will be more challenging for firms with complex processes and routines. Therefore, firm uniqueness can be problematic to attain dynamic capabilities. In turn, this inability of unique firms to develop dynamic capabilities could make it harder to sustain a competitive advantage.
8 viewed as the most important technology. NEC devoted its resources to the knowledge, technology and learning behind the semiconductor technology. In turn, this core competency was exploited through its complementary resources, such as its computer and telephone division. Therefore, firms should not focus on following a unique strategy and expand its resource portfolio. Instead, firms should focus on the development of their core
competencies. Hence, it is expected that by focusing their strategy on core competencies and complementary resources instead of following a unique strategy with unique resources, firms will obtain higher performance.
Overall, following a unique strategy requires more additional resources such as managerial resources due to an expanded and complex portfolio, which can be problematic for attaining dynamic capabilities and sustained competitive advantages. The added complexity due to uniqueness hampers firm performance. Both the theories of core competencies and dynamic capabilities explain that knowledge should flow easily through the firm to create superior performance. In addition, the theory of core competencies indicates that following a unique strategy is not desired for attaining higher firm performance, as the firm should build its resources and capabilities around its core competencies. Therefore, when firms implement a strategy it may be better for firm performance not to focus on following a unique strategy. Thus, I hypothesize that uniqueness will negatively influence firm performance.
Hypothesis 1: There is a negative linear relationship between firm uniqueness and firm performance
The role of platform firms on the uniqueness to firm performance relationship
9 Previous literature has stated that in order to create a positive WTA outcome, platforms have to ''get-big-fast'' to attract users rapidly in emerging markets, lock those users in and simultaneously undermine rivals from doing the same (Lee et al., 2006). Firms with similar offerings attract similar users and, therefore, compete in attaining the same set of (unique) resources. This race for resources is likely to be costly for firms in platform markets with WTA dynamics, as platform firms have to (heavily) incentivize users and discount prices to attract users to choose their platform over others (Cennamo & Santalo, 2013). Once the dominant platform is established, the platform will be able to leverage the user base and monetize the platform accordingly. For platform firms, pursuing a more unique strategy is even riskier as one platform pursuing a mainstream strategy could gain a head start by the force of network effects and, in turn, outcompete rivals (Cennamo et al 2013; Hill, 1997; Katz and Shapiro, 1994). Furthermore, the one or few dominant mainstream platforms are able to keep rivals from emerging as often there are switching costs (users switch from one platform to another) and multi-homing costs (users use different platforms simultaneously) (Eisenmann, 2011; Noe and Parker, 2005). Due to these WTA dynamics, the user base can be seen as a core competency. Further, for platform firms, Eisenman (2011) discusses that the process of managing the development of the user base can be an important dynamic capability.
Following WTA theory, it is essential for firms to follow a strategy based on attaining a large user base. It can be viewed as the most important strategic asset for platform firms (Shankar and Bayus, 2003). Pursuing a unique strategy and not focusing on the user base will make obtaining this resource harder and the acquisition will be more expensive. As it is likely to be the most essential resource to a platform firm, a user base can be defined to be a VRIN resource according to the VRIN framework by Barney (1986), as users are valuable, rare, inimitable and non-substitutable. Users are valuable as the platform can derive significant value from the amount and variety of users on the platform. Moreover, users are a rare resource as users enter the market because of network effects and often choose to home one platform. Further, a user base is hard to substitute and imitate due to switching costs and multi-homing costs. Therefore, pursuing a unique strategy and not having a strategy based on the user base will make monetization harder compared to mainstream platforms, as the mainstream platforms will be able to set prices at more competitive prices due to their economies of scale.
10 entering. Platforms pursuing a WTA strategy are likely to be able to monetize their platform, as switching costs and multi-homing costs are high in these markets. WTA platform firms are able to grow their user bases at a higher pace due to user incentivizing and network effects. It is unlikely that a platform pursuing a unique strategy will be able to compete, as growth will be harder to attain (Cennamo et al 2013; Hill, 1997; Katz and Shapiro, 1994). Once mainstream platform firms are established, it will be even harder for rivals pursuing a unique strategy to attain this resource as this now will have to be acquired at a competitive price (Barney, 1986). Compared to traditional firms, platform firms operate in markets with WTA dynamics, scarce resources, and network effects, which likely negatively affect firm performance for unique firms operating in these markets. Therefore, as competition by large mainstream platforms pursuing a WTA strategy is fierce and attracting users when pursuing a unique strategy is even more expensive, I hypothesize that at increasing levels of uniqueness platforms have even lower firm performance compared to traditional firms. Thereby, platforms take a moderating role in the uniqueness to firm performance relationship.
Hypothesis 2: The negative relationship between firm uniqueness and firm performance will be more negative for platform firms
Uniqueness on market share
Next to measuring the effects of firm uniqueness on firm performance, it is interesting to investigate the influence of uniqueness on industry market share. It is likely that firms with a unique combination of resources have their unique resources in different industries. If a firm is pursuing a unique strategy and is capturing a high market share in doing so within the industry, the firm would have to either have a sustained competitive advantage derived from within the industry or subsequently have its sustained competitive advantage derived from synergies within the portfolio by utilizing resources from other industries. If a firm has derived its competitive advantage from resources accessible from within the industry, there is a high likelihood that non-unique rivals will obtain, substitute or imitate these unique resources. Therefore it is likely that the unique firm will pursue synergies within the portfolio by utilizing resources from other industries for its primary industry strategy.
11 competencies which then should be exploited through complementary resources. However, unique resources have a higher likelihood of conflicting one another rather than supplement one another compared to complementary resources. Moreover, specialized and unique resources can be used across industries, yet, these are often not transferable and are not necessary for creating core competencies (Prahalad & Hamel 1990).
Furthermore, it is unlikely that uniqueness will result in an increased market share compared to rivals when firms derive their uniqueness from human and managerial resources, as obtaining a sustained competitive advantage requires the inimitability and non-substitution of resources. Managerial resources can be regarded as being valuable. However, they are common and imitable and can be learned by competitors in the industries that the firm operates in (Montgomery, 1985). Furthermore, obtaining a high market share is harder for unique firms as a portfolio of resources that is high in complexity requires more additional managerial resources (Zhou, 2011). Therefore, it is unlikely that unique firms will derive synergies from their managerial resources to result in sustaining a competitive advantage in the primary industry.
To conclude, unique firms should be less likely to have a high market share, as for these firms it will be harder to attain sustainable competitive advantages needed to compete with non-unique firms in the primary industry. Unique firms will be less likely to create synergies that result in competitive advantages due to the dispersion of resources, and due to the cost of the additional managerial resources needed to manage this
complexity. Unique firms will be less likely to have synergies in their portfolio as their focus on unique resources fragments the resource portfolio, and in turn hampers the firm's competitiveness compared to industry rivals. Therefore, I expect uniqueness to have a negative relationship with the primary industry market share.
Hypothesis 3: There is a negative linear relationship between firm uniqueness and market share
The role of platform firms on the uniqueness to market share relationship
12 platform firm is unique and is capturing high market share, it would have to derive its value from synergies from resources across industries. Platform firms operate with few assets, as users can substitute assets (e.g. Airbnb not owning apartments), and do not need many human and managerial resources. Therefore, compared to traditional firms, the complexity of the resource portfolio will be lower. Due to lower complexity, platform firms are less likely to face challenges in creating dynamic capabilities.
Research suggests that there is an opportunity for platform firms to pursue a highly unique strategy due to specialized customer needs (Cennamo & Santalo, 2013). However, pursuing a unique strategy comes with
challenges. As mentioned previously, WTA platforms will often outcompete rivals and will attract the majority of users. Pursuing a unique strategy for platform firms may be more costly due to incentivizing, discount pricing, switching costs, and multi-homing costs and scarcity of the user base. Yet, some potential users might have specialized needs that the mainstream rivals are unable to meet. Subsequently, these users may only be attracted through a combination of resources that is unique to the platform market. Accordingly, some firms will choose to operate in these niches, due to demand. However, if the strategy is unique, the platform likely has to operate at competitive prices set by the dominant platform to attract a user base, which may be problematic to grow and maintain market share (Cennamo and Saltalo, 2013). By choosing not to pursue the mainstream strategy and not to possess a similar set of resources that the dominant platforms choose and instead focus on other resources, unique platforms can operate in a niche.
In conclusion, platform firms operate differently compared to traditional firms due to WTA dynamics and network effects. Therefore, few platforms are likely to prevail and capture the majority of users. Due to the platform market dynamics, I expect that a unique strategy will be more costly compared to unique firms operating in
traditional markets. However, compared to more traditional markets with higher competition, there are more opportunities in these markets for unique firms to operate in niches. As one or few mainstream platforms emerge, there will be more opportunities for unique firms focusing on specialized needs compared to firms operating in traditional markets. Therefore, I hypothesize that for platform firms, market share will be less negatively influenced at increasing levels of uniqueness than for traditional firms.
13 Conceptual model
From the theoretical perspective of the RBV, four hypotheses were developed. Figure 1 is a conceptual model that illustrates how these hypotheses relate.
Figure 1: Conceptual model
Methodology
Data gathering
14 Measurement
Dependent variables
Market share. Previous studies have stated the importance of market share as a measure of performance. For firms,
higher market share could lead to market power, which brings a competitive advantage to the firm (Montgomery et al., 1985). Market share is particularly relevant for platform firms, due to WTA dynamics (Cennamo et al., 2013). The measure is calculated by dividing the sales of the firm in the primary industry compared to the total sales of the industry.
Firm performance. The firm performance is measured by Tobin’s q, which is a widely used measure of firm
performance. Tobin’s q was measured in a previous uniqueness study by Litov et al. (2012). Tobin’s q is an
15 Independent variable
Uniqueness. For this study, I used a similar measure of uniqueness to the measure that was developed by Litov et al.
(2012). In order to measure the uniqueness of firm strategies, I used segment data, namely the SIC codes for the respective industries firms operate in, and the sales derived from the segment industries. The first step in calculating the uniqueness measure is defining the total sales for each firm in each of the SIC codes for each year. si,t = [sales 1,i,t … sales N, i,t]' where i= the industry and t is the year. Next, to normalize this value, it has to be divided by the total sales in all the industries for the given year (Σj salesj,it’), where j is the number of industries a firm operates in. This concludes the first half of the uniqueness measure, where the uniqueness is in part measured at the firm level. Next, to find the uniqueness measure, this value for each firm will be compared to the uniqueness of the primary industry. First, for each primary industry, I will calculate the centroid of sales per year. Sj*,t= [Σi sales1,j,t … Σi salesN,i,t], where j* is the primary industry and i consists of all the firms that have j* as their primary industry. Second, this value has to be divided by the total number of sales per primary industry, for each primary industry per year, in order to normalize it. Thus, calculating ΣNj=1 Σi sales j,i,t, , where N is the total number of industries and j is the number of firms per industry. Finally, when taken together and having squared the difference between the two vectors, the uniqueness measure is calculated. The formula, uniquenessi,t= (si,t –sj*,t)’ (si,t –sj*,t) is derived from the normalized total sales for each firm in each of the SIC codes for each year and the normalized total sales for each primary industry for each year.
16 observations were not more than 5% of the sample size, and help the accuracy of the uniqueness measure. Further, the final measure was standardized, while it is not necessary, it provides easier interpretation and comparison.
Next, to illustrate the uniqueness measure I use the example of Microsoft in the year 2008, illustrated in table 1. Its primary industry is SIC code 7372, prepackaged software. Notably, this firm follows the platform
definition. There are 34 firms in the sample with the same primary SIC for the given year. The sales for each of the 4 SIC codes minus by total sales from Microsoft result in the normalized sales from each firm in each SIC, 0.0536104. Further, Microsoft's sales for each SIC minus the industry average results in the industry level uniqueness,
0.0072541. After calculating and squaring the difference, the uniqueness measure is calculated, which results to 0.07730285848.
SIC Uniqueness industry level Uniqueness firm level Difference²
7372 0.7553799 0.5906324 0.02714173875 7373 0.039327 0.2199963 0.03264139596 7375 0.0117818 0.1357609 0.01537081723 7371 0.0072541 0.0536104 0.00214890654 Total firm uniqueness 0.07730285848
Table 1: Uniqueness measurement of Microsoft in the year 2008 (unstandardized)
Platform moderator
17 code starting with 737. The list of firms classified by the SIC codes starting with 737 includes Twitter, Facebook, Google, Airbnb, Dropbox, Snap Inc., Yelp, eBay, Microsoft, IBM, and Alibaba. The official definition of this classification is ''Computer Programming, Data Processing, and Other Computer Related Services'' (NAICS, 2019). As a result of using this measure, it is possible that some platform firms, using a different primary SIC code, are not identified. As digital platforms are largely reliant on the development of software and the processing of user data, this SIC code is a dependable predictor of platform firms conforming to the database and the platform definition. A dummy variable was generated where 1 is for firms following the 737 SIC code and 0 was given for firms that do not have the 737 SIC code. Furthermore, firms from the finance, insurance, and real estate sectors were not included, as these have large differences in financial results such as sales and assets compared to traditional and platform firms.
Control variables
For the control variables, I used several firm characteristics, following Barth et al. (2001), Bhushan (1989) and Litov et al. (2012). I included a log for sales growth (in the past three years), a log for the number of shares outstanding and a log for number of employees and common equity. Similar to Litov et al. (2012) and the Tobin's q variable, common equity was windorised at the 2.5% level to control for extreme outliers. Next, I included return on assets (ROA). ROA and return on equity gave similar results, hence the use of ROA. Furthermore, a measure of diversification was controlled for and was standardized like the uniqueness measure. This is calculated as the total number of SIC codes a firm operates in. In order to find out the marginal effects of uniqueness, it is important to include diversification into the model, as it could be that unique firms tend to be more diversified. The uniqueness measure, as proposed by Litov et al. (2012), is designed in such a way that it does not conflict with this
diversification measure.
Robustness checks
18 Further, in the sample, there are many firms with only one SIC code and are the only ones operating in that industry. There are 1,652 observations in the sample where this is the case. Similar to Litov et al. (2012), a dummy variable is created to check the influence of these 'monopolies' in the results. The results were similar, and the uniqueness measurement still holds.
Data analysis
19 Results
Variable N Minimum Maximum Mean
Standard Deviation
Tobin’s q 23764 0.76 5.98 1.81 1.14
Av. Market share 25500 0 1 0.17 0.31
Uniqueness std. 25613 -0.78 6.58 2.32 1
Diversification std. 25613 -0.90 5.81 -1.27 1
Av. Sales growth (past 3 years) 23057 -0.43 2.88 0.36 0.64
Return on assets 23966 -327.67 252.28 6.46 10.82
Log nr. of employees 21227 0 14.65 9.44 1.55
Log shares outstanding 24229 5.22 20.96 13.09 1.59
Log common equity 24272 10.5 17.27 14.46 1.37
Platform dummy 25613 0 1 0.05 0.22
Uniqueness std* platform
dummy 25613 -0.78 6.58 2.32 1
Table 2: Descriptive statistics
Variable 1 2 3 4 5 6 7 8 9
1.Tobin’s q 1
2.Av. Market share -0.02 1
3.Uniqueness std. -0.07 -0.34 1
4.Diversification std. -0.20 0.13 0.24 1 5.Av. Sales growth (past 3
years) 0.24 -0.01 -0.05 -0.11 1
6.Return on assets 0.35 0.01 -0.02 -0.06 0.01 1
7.Log nr. of employees -0.18 0.06 0.07 0.23 -0.02 0.02 1
8.Log shares outstanding -0.11 -0.08 0.01 0.11 0.04 0.02 0.25 1
9.Log common equity -0.35 -0.02 0.06 0.22 -0.01 -0.03 0.50 0.29 1
20 Table 2 gives an overview of the descriptive statistics. There are 25,613 observations for most variables and 4,92% of these observations are from firms identifying as platform firms conforming to the 737 SIC codes. Table 3 shows the Pearson correlation matrix. Uniqueness correlates slightly with diversification with a correlation of 0.24. Yet, no correlations are problematic, as no high significant correlations between the independent and control variables are found. No variables are associated with each other, as all of the correlations are closer to zero than to the extreme values.
Next, to test for multicollinearity, VIF values were calculated, as illustrated in table 4. None of the VIF values were lower than 1 or higher than 1.46. No presence of multicollinearity was detected, as VIF values should be between 1 and 10, where the higher the number the higher the likelihood of multicollinearity.
The regression results are shown in table 4. As shown in Model 1, the random-effects regression of uniqueness on firm performance, measured by Tobin’s q gives β =-0.007 and p=0.342 for the uniqueness relationship. Therefore, there is no empirical support for hypothesis 1. It does indicate a negative effect of uniqueness on firm performance, however, this is not significant.
21
Figure 2: Predictive margins of platform on the uniqueness to firm performance relationship (with a 95% confidence interval)
Furthermore, as shown in Model 3, the random-effects regression of uniqueness on market share, measured by sales shows β = -0.103 and p=0.000 for uniqueness on market share. Therefore, hypothesis 3 can be empirically supported. It does indicate a significant negative effect of uniqueness on market share, at the 1% confidence level.
22
23
Table 4: Random-effects regressions and VIF values
Model 1 (Tobin’s q) Model 2 (Tobin’s q) Model 3 (Market share) Model 4 (Market share)
24 Discussion
This study analyzes how uniqueness affects firm performance and market share respectively, and how these may differ for platform firms. First, I discuss the main findings and explain the implications of the main results. Next, I analyze the results with regards to previous studies within the area of research, followed by an example of the most unique platform firm in the dataset.
The results indicate a slight negative relationship between firm uniqueness and firm performance. Yet, this relationship is not significant. This could imply that, in general, pursuing a unique strategy can hamper firm
25 through their core competencies. An important condition for this would be that these unique resources are
complementary to the core competencies of the firm.
Furthermore, the data from hypothesis 2 suggests that uniqueness may be increasingly unfavorable to firm performance for platform firms. Yet insignificant, it may imply that the platforms do differ compared to traditional firms in terms of strategy implications. Platform firms operate in markets characterized by WTA dynamics and network effects. Deviating from the WTA strategy and pursuing a unique strategy instead may worsen firm
performance, as attracting a mainstream resource such as a user base is vital to firms with these market dynamics. I argue that platforms should create core competencies and complementary resources around the user base. Further, the processes behind the management of the user base may create dynamic capabilities (Eisenmann, 2011).
Arguably users are the most important resource in these markets and choosing instead to focus on a unique strategy may be costly. Nonetheless, as hypothesis 2 was not found to be significant, it may be that some platform firms are less affected in terms of firm performance than others. Platform firms operate in markets with strong WTA dynamics and strong network effects. Yet, the strength of these may differ across industries platforms operate in (Eisenmann, 2007). The added value from pursuing a unique strategy may be dependent on the environment in which the platform firm operates. It is plausible that when WTA dynamics and networking effects are stronger, more dominant mainstream platforms will prevail and are able to capitalize on their significant user base. Whereas it could be that in some markets WTA dynamics and network effects are weaker, as to which the environment may be less troublesome for platforms with a higher quantity of unique resources.
26 Interestingly, for platform firms, the negative relationship between uniqueness and market share seems to be increasingly less negative. This may imply that due to WTA dynamics and network effects in platform markets, the opportunity for firms to specialize by pursuing a unique strategy is seemingly less negative. In these WTA markets, few mainstream platform firms emerge and, hence, there are opportunities for firms to attribute unique resources to specialized customer needs. Therefore, it seems that when platform firms attain unique resources at increasing levels a phenomenon arises as in this study two measures of performance were used. On the one hand, uniqueness is seemingly causing an increasingly less negative effect on market share compared to traditional firms. While on the other hand, for platform firms uniqueness seems to be causing an increasingly more negative effect on firm performance compared to traditional firms. Hence, this phenomenon may be explained through the dynamics of the platform markets. Due to WTA dynamics and network effects, one or few mainstream platforms dominate the market and attract the majority of potential users. Therefore, there is a higher opportunity for a firm to pursue a unique strategy to cater to specialized user needs compared to firms operating in traditional markets. Yet, pursuing a unique strategy seemingly will result in increasingly negative firm performance. Compared to traditional markets, platform firms pursuing a unique strategy may have increased additional costs. Not focusing on attracting a user base and following the WTA strategy, and instead focusing on a unique strategy may be more costly, as it is essential for the firm to acquire a user base. Additionally, monetization of the platform might be more troublesome, as a platform operating in a niche has fewer market economies of scope compared to the mainstream platforms. Dominant and non-unique platform firms are able to capitalize on their market position effectively through their market power, economies of scope, and network effects.
This study contradicts the findings of Litov et al (2012). The authors introduced the measure of firm uniqueness and this has been the only study published with this measure so far. Though I followed a similar
27 form of speculation behind the acquisition of unique resources, as it may not always hold that these resources will become more valuable upon acquisition by the firm. Further, the authors have not stressed the cost and the added level of complexity to the resource portfolio by possessing unique resources, which can hinder the firm's strategy.
Furthermore, the main result, in that uniqueness is not always less beneficial to firm performance, is in line with the empirical findings of other studies focusing on the relationship between unique resources and firm
performance (de Carolis, 2003; Costa et al. 2013, Henderson and Cockburn, 1994; Powell and Dent-Micallef, 1997; Zahra and Nielsen, 2002). Overall, empirical research has had trouble relating resource strategies and resource combinations to firm performance, as in an assessment of the resource-based view, Newbert (2007) found only 37% of the hypotheses linking resources to firm performance were found to be supported. Some researchers suggest that these insignificances could be because resources are only contributing to performance when they are combined with complementary resources and organizational capabilities (Winter, 1995; Eisenhardt and Martin, 2000; Newbert, 2007). Interestingly, 71% of the hypotheses with an independent variable relating a specific capability and 67% relating to a core competency respectively, were found to be supported to competitive advantages and/or firm performance. Therefore, it may be that indeed core competencies and capabilities may be better to explain superior firm performance.
To better understand the implications of how uniqueness in platform firms relate to firm performance, I discuss the most unique platform firm in the dataset, which is the search platform Yahoo in the year 2015. Yahoo once was a strong player in the early stages of the search platform market and was one of the most valued firms on earth with a valuation of over 100$ billion, yet it was acquired in 2016 by Verizon for $4.8 billion (Desjardins, 2016). While Google has developed a core competency in search technology and has been successfully deploying this competency across its products, Yahoo outsourced its search engine to Microsoft, which developed and
28 Tumblr, as monetization was unsuccessful. Meanwhile, nothing was being done with the Alibaba share.
Furthermore, the firm did not adapt to changes in the IT environment, as in all markets firms were doing its services better. Google in search and in Email, Facebook messenger and Whatsapp in messaging and Facebook in providing news. Overall, I argue that Yahoo was pursuing a strategy too much focused on a unique strategy, instead of developing core competencies and developing dynamic capabilities. Instead of investing in its search engine and adding complementary resources to the search engine, Yahoo went with a strategy of acquiring resources that were largely unrelated to the core competence of the firm. Further, the platform was not able to create dynamic
capabilities, as Yahoo did not successfully adapt to changes in the environment.
Conclusion
By combining the RBV and platform market economics, this study contributes to both the field of strategic management research and the field of platform research, and provides further insights for both areas of research.
This study found important insights into the field of platform research. For platform firms, it appears that uniqueness has a stronger negative relationship to firm performance. Further, for unique platforms the findings indicate that, while they may perform worse, they may obtain a higher market share than unique traditional firms. This may be explained through the WTA dynamics in the platform markets. On the one hand, the prevalence of one or a few firms in these markets creates more of an opportunity for firms to pursue a unique strategy and capture market share. On the other hand, the unique platforms may have more trouble monetizing the platform, as the few dominant platforms, due to economies of scope, are better at leveraging network effects.
Furthermore, this study provides further insights into the field of strategic management. First, I found similar results to previous studies in that resource combinations alone fail to explain the relationship to superior firm performance. Following a unique strategy does not necessarily lead to worse firm performance. In addition, the development of core competencies and dynamic capabilities may be more important factors to explain firm performance rather than resource strategies. Furthermore, the results support that uniqueness could lead to lower market share, which contributes to explain uniqueness in strategy.
29 strategy. Instead, it may be better to focus on core competencies and develop competencies in areas where the firm provides the most value. Uniqueness may result in more complexity, which could impede the development of competencies and capabilities. Furthermore, the results stress the importance for platform managers to be aware of the WTA dynamics and network effects. The findings indicate that while uniqueness may provide more market share opportunities compared to traditional firms, firm performance may be lower compared to unique traditional firms. Following a unique strategy may be more costly due to high competition from mainstream platforms, increasing user base acquisition costs and hampering platform monetization opportunities. Instead, platform managers could strategize around the user base as the processes behind the development of the user base could be a core competency and may lead to dynamic capabilities.
Limitations and Further Research
Uniqueness has been studied in ample studies in the form of unique resources, yet no consistent definition has been given. In general, research indicates that firm uniqueness relates to possessing unique resources and follow a unique strategy by possessing a unique combination of resources. The overall definition has not been used and interpreted consistently across studies. Similar to this study, some studies implicate that unique resources should be valuable and rare (e.g. Litov et al. 2012). Other studies further define unique resources as resources that are also satisfying the inimitable and non-substitutable conditions of the VRIN-framework (e.g. Costa et al, 2013). It may be an opportunity for further research to come with a consistent definition of firm uniqueness. Through a shared definition and measurement, consistency may be enhanced across studies.
Moreover, defining and measuring platforms in a large dataset was difficult. Existing research has not come up with a concise definition of platforms thus far and platforms have been measured differently across studies. In this study, the platform moderator was measured using the SIC codes from platform firms following the platform definition. Not in all cases firms measured as platform firms were indeed platform firms and some platform firms were not in the measured SIC codes.
30 performance, it may be interesting to further research the role of capabilities and dynamic capabilities. This study found differences between platform firms and traditional firms. Hence uniqueness may differ across industries. Therefore, for further research, it may be interesting to take into account industry-specific factors, such as industry dynamism. Further, as this study was focused on the RBV it may be interesting for further research to use the uniqueness measure by Litov et al. (2012) through a different theoretical perspective, such as the transaction cost theory.
From a methodological stance, there were several limitations to this study. This study was heavily reliant on SIC codes in measuring uniqueness in several ways. First, the measure depends on the accuracy of the SIC codes. Yet, it may be that the SIC codes as reported in Thomas Reuters Eikon may differ from the actual SIC code from the year the firm operated in. In addition, there were cases of firms having different IDs than reported elsewhere and cases of negative assets and sales. Further, the SIC codes may not be accurate in reporting the specific industries a firm operates in. A firm may operate in more industries than in the reported SIC codes. For example, platform firms such as Facebook, Twitter and Amazon are reported as 7375 in Eikon, while elsewhere these firms are reported as 7374 (Siccode.com, 2019). For further research, it may be interesting to use the North American Industry
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