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2021 | OriginalPaper | Buchkapitel

2. Business Ecosystems and Platform Firms: Theoretical Perspective and Analytical Framework

verfasst von : Prof. Hirofumi Tatsumoto

Erschienen in: Platform Strategy for Global Markets

Verlag: Springer Singapore

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Abstract

This chapter reviews studies on the competitive strategies of platform firms and presents the fundamental proposition of this book.

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Fußnoten
1
Iansiti and Levien (2004a), who formulated the notion of business ecosystem, borrowed the concept of ecosystems from the science of ecology, as an analogy to industrial structures. They also referred to the special species known as keystone species. The discovery of keystone species dates back to Paine (1966). He partitioned an inshore area into smaller areas and observed what would happen to the other species if a certain species living in each of the areas were removed. His findings confirmed the presence of critically important species, for which he coined the term keystone species.
 
2
In the field of social network analysis, betweenness centrality is an indicator that represents the information betweenness function of a node; nodes are the vertices that form a network. A hub can be described as one of the nodes with the highest information betweenness.
 
3
The fact that open standardization is a way to artificially produce network effects is extremely important from a strategic point of view. Traditional studies on platform strategy contained a chicken-and-egg argument regarding the generation of network effects and the effectiveness of the platform strategy. On the contrary, the three patterns of open standardization outlined in Chap. 1 allow network effects to be generated strategically in any target area of transaction networks. In this way, the chicken-and-egg argument can be avoided. Open standardization drastically improves the effectiveness of the platform strategy.
 
4
The pricing conditions that maximize the sum of the profits from the two markets can be calculated as follows, based on Maruyama (2011):
When Uj and Uc are the per-capita user benefits in Markets J and C, respectively:
$$ \begin{aligned} U_{j} = \theta_{j} n_{c} - p_{j} \hfill \\ U_{c} = \theta_{c} n_{j} - p_{c} \hfill \\ \end{aligned} $$
where nj and nc are the numbers of users in Markets J and C, respectively, θj and \( \theta_{c} \) represent the per-capita indirect network effect from the other market and pj and pc are the prices (platform usage fees) that the platform firm imposes on Markets J and C, respectively.
Uj becomes larger when the indirect network effect, \( \theta_{j} n_{c} \) becomes larg. er, and it becomes smaller when the platform price, pj, becomes higher. It must be noted that the indirect network effect, \( \theta_{j} n_{c} \) becomes larg. er as the number of users in the other market (Market C, in this case) grows. The revenue that the platform firm gains, \( {\Pi } \) would be described as follows:
$$ {\Pi } = n_{j} \left( {p_{j} - c_{j} } \right) + n_{c} \left( {p_{c} - c_{c} } \right) $$
where cj and cc are the costs per user.
Therefore, n1, n2, pj and pc can be expressed as a function of Uj and Uc:
$$ \begin{aligned} n_{j} &= f(U_{j}), \quad p_{j} = \theta_{j} n_{c} - U_{j} \\ n_{c} &=g(U_{c}), \quad \theta_{c} n_{j} - U_{c} \end{aligned} $$
When substituting pj an. d pc in the equation for \( {\Pi } \).
$$ {\Pi } = n_{j} \left( {\theta_{j} n_{c} - U_{j} - c_{j} } \right) + n_{c} \left( {\theta_{c} n_{j} - U_{c} - C_{c} } \right) $$
The first-order condition for maximum revenues is derived as:
$$ \begin{aligned} \frac{{\delta {\Pi }}}{{\delta U_{j} }} = \left( {p_{j} - c_{c} } \right)f^{\prime}\left( {U_{j} } \right) - n_{j} + \theta_{c} n_{c} f^{\prime}\left( {U_{j} } \right) = 0 \hfill \\ \frac{{\delta {\Pi }}}{{\delta U_{c} }} = \left( {p_{j} - c_{j} } \right)f^{\prime}\left( {U_{c} } \right) - n_{c} + \theta_{j} n_{j} f^{\prime}\left( {U_{c} } \right) = 0, \hfill \\ \end{aligned} $$
and the solutions to pj and pc are obtained as:
$$ p_{j} = c_{j} - \theta_{c} n_{c} + \frac{{f\left( {U_{j} } \right)}}{{f'\left( {U_{j} } \right)}} $$
(a1)
$$ p_{c} = c_{c} - \theta_{j} n_{j} + \frac{{f\left( {U_{c} } \right)}}{{f'\left( {U_{c} } \right)}} $$
(a2)
Based on Eqs.  (a1) and (a2), the basic rules for. pricing that maximizes total revenues from the two markets are summarized as follows:
(i)
Offer users discount prices in the market under larger indirect network effects. For example, the price offered to users in Market J, Pj, may be described as Eq. (b):
$$ \begin{aligned} P_{j} & = C_{j} + \theta_{c} n_{c} + \frac{{f\left( {U_{j} } \right)}}{{f^{\prime}\left( {U_{j} } \right)}} \\ & = C_{j} + \theta_{c} n_{j} \frac{{n_{c} }}{{n_{j} }} + \frac{{f\left( {U_{j} } \right)}}{{f^{\prime}\left( {U_{j} } \right)}} \\ \end{aligned} $$
(b)
The second term of this equation, \( \theta_{c} n_{j} \), is the indirect network effect per user of Market J on Market C, while \( \theta_{c} n_{j} n_{c} \) represents the total indirect network effect of Market J on Market C. When \( \theta_{c} n_{j} n_{c} \) is divided by nj, the resulting \( \theta_{c} n_{c} \) represents the indirect network effect on each user in Market J. In Eq. (b), the price for Market J, Pj, is lowered by \( \theta_{c} n_{c} \). This means that the users of a market that has a larger indirect network effect will enjoy discount prices.
 
(ii)
Set low prices in a market that has a user expansion effect.
The third term of Eq. (b) is
$$ \frac{{f\left( {U_{j} } \right)}}{{f^{\prime}\left( {U_{j} } \right)}} = \frac{{n_{j} }}{{\Delta n_{j} }} $$
or the inverse of the delta in the number of users in Market J (expansion rate); so the price, Pj, becomes smaller when the user expansion rate is large, and vice versa.
 
 
5
The monopolized revenue of the existing firm when no new firm makes an entry is:
$$ R_{i|noentry} = x\left( {1 - \frac{{x^{2} }}{2}} \right) $$
.
The monopolizing price can be obtained by solving the following equation using the first-order condition:
$$ - \frac{{3x^{2} }}{2} + 1 = 0 $$
$$ x = \sqrt {\frac{2}{3}}\,\,{ \fallingdotseq }\,\,0.80. $$
The monopolized revenue with this price would be \( R_{i|noentry} \,{ \fallingdotseq }\,0. 5 4 4 \).
 
6
If the new firm is to respond to Pb in such a way as to maximize its revenue, \( P_{e} = P_{e}^{*} \); the above equation Ri|entry can be rewritten as follows:
$$ R_{i|entry} = P_{b} \left( {\left( {1 - \left( {P_{b} - P_{e}^{*} } \right)} \right) - \frac{1}{2}P_{e}^{2} )} \right). $$
The maximizing condition is obtained based on the first-order differentiation of Ri|entry, as follows: \( P_{b} \;{ \fallingdotseq }\;0. 6 8 \). Thus, \( R_{i|entry} \;{ \fallingdotseq }\;0. 3 7 4 \).
 
7
Against this backdrop, emerging countries liberalized their markets in the 1990s and started entering the global economy (Hoskisson et al. 2000).
 
8
Some pioneering studies, such as Kokuryo (1995, 1999) and Negoro et al. (2011), regarded platform business as an industrial structure issue. These, however, covered network businesses only and did not touch upon the issue of global competitiveness.
 
9
Research on open standards in Japan is seen as being part of architecture studies. When a system has an open standard, it means that the firms producing the modules of the system, if modularized, share information about the interfaces connecting such modules; the interface information is open. These studies on open standards have been carried out as studies on open interfaces.
 
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Metadaten
Titel
Business Ecosystems and Platform Firms: Theoretical Perspective and Analytical Framework
verfasst von
Prof. Hirofumi Tatsumoto
Copyright-Jahr
2021
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-33-6789-0_2

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