Scientific Programming

Scientific Programming / 2020 / Article
Special Issue

Scientific Programming Towards a Smart World 2020

View this Special Issue

Review Article | Open Access

Volume 2020 |Article ID 8877128 | https://doi.org/10.1155/2020/8877128

Chen Xue, Wuxu Tian, Xiaotao Zhao, "The Literature Review of Platform Economy", Scientific Programming, vol. 2020, Article ID 8877128, 7 pages, 2020. https://doi.org/10.1155/2020/8877128

The Literature Review of Platform Economy

Academic Editor: Chenxi Huang
Received19 Apr 2020
Revised24 May 2020
Accepted06 Jul 2020
Published01 Sep 2020

Abstract

Since the 1990s, the increasing development of digital-driven technologies such as the Internet, cloud computing, big data, and the Internet of Things and the popularization of computers and mobile electronic devices have accelerated the evolution of global business organizations, thus making a new form of business organization, platform economy. As the most important form of industrial organization in the new economic era, the development of the platform has received extensive attention from the academia. Through literature analysis and inductive deduction, this paper reviews the connotation of platform economy, the historical context of development, the competition and monopoly (differentiation) of multilateral platforms, the evaluation mechanism of platform, antimonopoly governance, and research methods, and provides theoretical references and new ideas for future research directions.

1. Introduction

What is the “platform economy?” Evans [1] defines platform economy as a study of the unique economic phenomena of specific two-sided markets in traditional market economics. The platform economy studied in this paper refers to a series of digital technologies driven by the Internet, cloud computing, big data, and the Internet of Things, with a large number of platform enterprises as the lead, designing and implementing a complete set of platforms, consumers, and service providers, and influencing upstream and downstream enterprises, to reduce transaction costs of organizational rules and services and to achieve a new type of economic integration in which resources are highly integrated with traditional industries. Since the 1990s, mass platforms applying digital-driven business models show around the world where Google, eBay, Alibaba, Baidu, Tencent, JD.com, and other enterprises have stood out on the Internet, leading the increasing development of various industries and gradually forming the platform economy model, which has profoundly affected all aspects of the national economy and reshaped the market structure and competitive behavior of different industries. Meanwhile, it brings cross-country and cross-region business models and accelerates the global economic integration. This rapid growth of platform enterprises has inspired vast in-depth research studies in academia.

2. The Historical Development of Platform Economy

McAfee and Brynjolfsson [2] regard the rise of the platform as one of the three iconic events of the “digital revolution.” Its rise has changed people’s production and life and has also changed the way of human thinking. Most successful enterprises now have platform attributes [3]. Platform is the intermediary to realize the exchange between other participants, and most major technology companies can be regarded as platform-based enterprises [4].

Liebowitz and Margolis [5] put forward the conjecture of network externality and call the “market regulation effect” as “(indirect) network effect.” Their conjecture is considered by academia to be the oldest openness issue in network economics. Subsequently, Rochet and Tirole [6], Armstrong [7], and Caillaud and Jullien [8] have pioneered platform research and guided the economics community's interest in platform research.

At the beginning of the 21st century, with the rapid development of information technology and the further refinement of the social division of labor, the market operation model based on buyers and sellers has become increasingly mature. The platform enterprises based on buyers and sellers have formed a new market relationship, that is, the two-sided markets in the production and operation market. Caillaud and Jullien [8], Rochet and Tirole [6], and Amstrong [9] believe that the increase of users on one side of the platform will cause the increase of users on the other side. The two-sided “cross-group network externality” is called two-sided markets. Armstrong [9], Evans [1], Evans and Schmalensee [10], and Filistrucchi et al. [11] believe that two-sided market should embody at least one side with “cross-group network externality.” Rochet and Tirole [12] believe that the definition of cross-group network externality in two-sided markets lacks inclusiveness and should be defined from the price structure. Parker and van Alstyne [13] study two-sided markets earlier. They believe that the matching market is two-sided because the matching “platform” (such as dating services) is more important. Hagiu and Wright [14] impose restrictions on two-sided markets: one is the direct trade between the sides of the market, and the other is that each side of the market is “affiliated” to the platform, with higher cost of leaving the platform. Evans [1, 15] divides two-sided markets into three types: market maker, audience maker, and demand coordinator.

There are two main reasons to trace the emergence of the platform. Firstly, the platform helps to match. In the sharing economy, the platform provides a new structure to quickly and effectively match with low search cost [16] and acts as an intermediary between the buyer and the seller [17]. In view of the matching background, many scholars have conducted a lot of in-depth research on the competition and pricing strategies in the platform business and gradually focused on the importance of indirect network effects [8, 1820] and [21]. Secondly, the platform has improved trade efficiency. The platform improves transaction frequency and efficiency by reducing search cost, low replication, and verification cost. Through zero cost replication, the platform enables application providers to quickly provide services for a large number of customers, with interoperability. Simcoe [22] emphasized platform interoperability and the strategic nature of standard decision-making [6, 23], Hanna and Yehezkel [24] tested whether market participants would “multiple” and use multiple platforms through empirical data.

Regarding the research of platform economy, from the perspective of two-sided markets, many scholars focus on market intermediary behavior, especially market pricing; from the perspective of network effects, scholars focus on user adoption and optimal network scale; from the perspective of industry focuses, the media, payment system, and matching market are highly paid attention to the research and literature of two-sided markets, focusing more on high-tech and telecommunication market about network effects.

3. The Competition Effect of Platform Economy

The theoretical economics literature on multisided platforms focuses on competition (differentiation) between antitrust and multisided platforms serving the same customer group. According to Evans and Noel [25], various platforms face a more complex competitive environment. The existence of the “cross-group network externality” of the platform has led to mutual reciprocity on both sides, and platform enterprises have grown up at an extremely rapid rate. Platform enterprises with “intragroup network externality” will be provided with entrance barriers as their scale grows, and it will be difficult for new enterprises to reenter, often causing winner-take-all issues [1, 8]. Meanwhile, after the platform gains market power, it will become a “modern antitrust” to a great extent [26]. Evans [27] conducts a research on the operating status of the world’s top platforms and finds that their industry rankings have changed greatly in recent years, and antitrust platforms are also facing various challenges.

Platform competition theory has been one of the most active areas in industrial organization research for the past decade [6, 8, 9, 12, 20, 28]. Jacqueline and Jonathan [29] believe that the network effect model is conducive to the competition between platforms. Spiegler [30] studies that there are positive externalities between the two agents. The platform extracts these externalities by using exclusive interactive contracts. If another agent signs a contract with the platform, the payment to one of the agents is accordingly reduced. Caillaud and Jullien [31] believe that there is a market for price competition between the two platforms, and there is no difference between the platforms. When the existing platform has the market power, another new entry platform is difficult to develop. If the platform does not charge transaction fees, even if there is no product differentiation, the platform that has already occupied the market can still obtain profits; with the transaction fee, both platforms can get profits. Rochet and Tirole [6] study the issues of “single destination” and “multiple destination” for multisided platforms. Armstrong [9] shows the importance of “multiple destination” for competition. Armstrong and Wright [32] put forward that if the multisided platforms of competition is regarded as homogeneous by members of one group but differentiated by members of another group, then the “competitive bottleneck” will be endogenous. Economides and Katsamakas [33] study the competition between common platforms and open source platforms and find that the property platform dominates open source platforms by having greater market share and higher profitability. Jullien [34] conducts multifaceted background research studies based on the market of vertical differentiated platforms and sequential games and finds the pricing strategy of competitive platforms. Weyl [35] analyzes the pricing strategy of the platform from the perspective of multifunctional platform and from the perspective of user heterogeneity and platform monopoly, establishes a general theory of network antitrust pricing, and lays the foundation for the platform economic theory. Tiwana [36] and Mukhopadhyay et al. [37] believe that the platform is a dynamic, purposeful, or internal interdependent network, and participants can jointly create value [38] and add complementary products, services, and technologies [39]; Annabelle and Cusumano [40]. Mcintyre and Srinivasan [41] believe that the value creation in the platform system is jointly participated by platform owners, suppliers, and final consumers. This is due to internal competition and cooperation between participants, which occurs in the interaction between independent participants and the evolutionary process. Reiley, Hall [42, 43] believe that the reduction of transaction costs will lead to more flexible platform pricing.

Brynjolfsson et al. [2] found that online prices are much lower than offline prices by comparing the products of four pure Internet retailers, four offline retailers, and four “hybrid” retailers with both online and offline stores. Orlov [44] found that the platform will increase the price dispersion within the enterprise, but it does not have a great impact on the price dispersion among enterprises. Instead, the search cost reduces the price dispersion [4547].

Regarding information asymmetry in platform competition, Damiano and Li [48], Ambrus and Argenziano [49], Peitz et al. [50], Weyl [20], and White and Weyl [51] focus on the research of ex-ante asymmetric information. Based on this issue in the two-sided markets, Hanna and Yaron [24] used multiple destinations to solve the market failure caused by information asymmetry and empirically studied the influence of ex-ante uncertainty of new technology value and ex-post asymmetric information on platform strategies and results.

The focus of the platform economy is to solve the problem of how platforms can price both sides of the market at the same time. Rochet and Tirole [12] focus on the price structure when defining two-sided platforms, which has the characteristics of using externality and member externality. Evans and Schmalensee [10] define two-sided platforms, grasping the key features of the platform business, namely, (a) having two or more customer groups, (b) to some extent need each other, (c) unable to obtain value from mutual attraction, and (d) the platform creates more value. Evans [52] believe that the pricing of one side of the market depends not only on the demand and costs brought by consumers but also on how their participation affects the other party and the profits derived from the participation. In one-sided market, the elasticity of demand and marginal cost can be used to describe price cost increase, but in two-sided markets, the pricing decision also needs to consider the flexibility of the other party’s response and the price increase charged to the other party. Rochet and Tirole [53] point out that if the services provided to consumers and merchants are completely competitive, then the exchange fee does not affect the profits of members but affects the terms and total transactions faced by merchants and consumers. Rochet and Tirole [6, 12] and Weyl [54] believe that prices on both sides of the market depend on the elasticity of demand and the marginal cost of each party. A platform acting as an intermediary is regarded as antitrust that has access to members who do not use other platforms. Enterprises using a single network compete fiercely in order to charge antitrust price to the other party trying to reach it [9].

An important issue of platform research is price discrimination in the case of heterogeneous demand. Weyl [35] has empirically found that, by manipulating the prices of participation and use, the platform can obtain more profits. Discrimination increases the value of one party, which causes the decreasing price of the other party. Caillaud and Jullien [8] empirically study how the new platform uses price discrimination to achieve success when market participants expect new entrants to fail.

Regarding the research on platform antitrust competition, Rochet and Tirole [6] and Armstrong [9] study antitrust pricing and price competition of platforms. Rochet and Tirole believe that the platform is priced based on transaction fees. Jullien [55] believes that there are more than two consumer subgroups and intragroup network externality on the platform, constructing a duopoly model. Evans [1] points out that, in many industries, enterprises act as catalysts to set prices below marginal costs, sometimes even zero, such as on some software platforms, advertising-supported media, exchanges, and payment systems.

Regarding the research on heterogeneity in platform competition, Ellison et al. [56] conduct a study on the competition between two auction websites and find that even if there is a lack of heterogeneity of products and agents, multiple platforms coexist. Damiano et al. [48, 57] [61] believe that consumers are heterogeneous in the platform economy, and different types of consumers can be distinguished through registration fees. Caillaud and Jullien impose monotonicity on the consumer demand, assuming that the full market coverage under equilibrium conditions is selected among equilibriums. Ambrus and Argenziano [58] study the conditions for the coexistence of multiple asymmetric networks in a bidirectional market with network externality from the perspective of consumer heterogeneity and find that one side of a network platform is cheaper and larger, the other side is even cheaper and larger. Weyl [54] believes that, in the case of heterogeneous demand, the platform can obtain more profits by operating participants and prices. Rochet and Tirole [6] put out that customers with prestige and influence will have significant direct or indirect externality.

4. The Governance Issues of Platform Economy

Platform governance is jointly constructed by the platform, its participants, and the government and revolves around three issues: “who sets the rules,” “how to allocate rights and obligations,” and “how to resolve disputes.” The idea of platform governance includes spontaneous organization of platform subjects, participation in governance, government-led regulation, and consumer supervision. Jin and Kato [59], through empirical research on eBay’s rating system, find that credibility is an effective means of identifying integrity platforms. Avery et al. [60] started the research on the recommendation system earlier and devoted to building the evaluation system. Jacqueline and Jonathan [29] conduct an empirical study on eBay, establishing a communication mechanism to encourage other users to evaluate the quality of sellers or products by setting up a communication mechanism that encourages and aggregates user feedback, thus building the evaluation system of a platform reputation. Dellarocas [61] has empirically found that sellers with higher feedback scores enjoy some benefits when prices and sales rates are higher.

Cabral and Hortacsu [62] and Saeedi et al. [63] find that the evaluation mechanism set up by the platform to increase the evaluation rate will breed strategic behavior of evaluation. The existence of strategic behavior will distort the reputation mechanism and affect its effectiveness. Rieder and Sire [64] have empirically found that if the platform’s search accepts advertising sponsorship, it may affect the objectivity of the platform’s search.

In the fields of economics, management, and strategic management, a large amount of literature on platform antitrust governance has appeared, especially because of the research on pricing issues in the field of platform economics, which provides an important reference for antitrust governance. Rochet and Tirole [53] find that if the antitrust law is not violated when setting the exchange fee, but the equilibrium result deviates from the social optimal value, the reasonable solution is price regulation. Evans [65] believes that, with the increasing revolution of the Internet, mobile devices, and information technology and the increasing emergence of global large-scale multisided platforms, antitrust will become a key link in governance issues.

Evans [52] studies how platforms develop governance systems to reduce platform participants’ undesirable behavior that may reduce the value of the platform. Hagiu [66] discusses the use of platform regulations to increase positive externality and reduce negative externality. Ruhmer [67] raises the issue of whether multisided platforms can increase profits by colluding to charge only part of the price. Evans and Schmalensee [15] believe that the fierce competition between the two platforms may eliminate the profitability of colluding with each other’s prices. Rysman [28] believes that predatory pricing and overpricing will lead to anticompetitive platforms.

5. The Method Research of Platform Economy

Rochet and Tirole [53], Jullien [55], Armstrong and Adendorff [68], and Parker and Van Alstyne [69] conduct empirical research on the entry, pricing, and other strategies of the platform industry, providing a research background for the emerging economic theory of platform. Rysman et al. [70] provides the empirical and policy [1] research for multisided platforms market. Rochet and Tirole [6] take the lead in constructing one of the two most basic models of two-sided platforms pricing. It is assumed that two-sided antitrust platforms have no member externality. Only by using externality and charging usage fees for each transaction while without charging, member fees can the cost bonus be lowered with the higher demand elasticity. Armstrong [9] proposes the second model, two-sided antitrust platforms do not use externality, only the externality of members, no user fees, only member fees, and the price of maximizing profits. Hagiu [66] modifies the Armstrong [9] model, and the size of the profit share of the antitrust platform comes from the consumer’s preference for varieties. Jacqueline and Jonathan [29] conduct empirical research on platform and platform competition and construct a platform competition model for analyzing platform pricing, competition, and market tilt issues. Rochet and Tirole [6] carry out empirical research on both sides of the platform, which finds that, from the perspective of maximizing profits or maximizing social welfare, the optimal price may cause the pricing to be lower than the marginal supply cost of one party and higher than the marginal supply cost of the other party.

Economists have developed various models to help analyze whether certain business practices may harm consumers by excluding competitors from the market, or benefit consumers by lowering prices or improving quality. Segal and Whinston [71] demonstrate that, under the condition of economies of scale, monopolistic enterprises can effectively prevent competitors from entering by signing exclusive transaction contracts. Armstrong and Wright [32] build a platform competition model, which is regarded as a differentiated platform by one customer group and a homogenized platform by another customer group. Exclusive transactions can be used to prevent the latter ‘s multihoming and exclude competitors, but antitrust equilibrium may be effective. Doganoglu and Wright [72] demonstrate the effectiveness of this strategy without economies of scale but with network effects. Leung and Lee [73] conduct empirical research on the video game industry, finding that exclusive contracts can facilitate entry rather than prevent entry. Rochet and Tirole [74] simulate the situation that tying increases social welfare and found that tying in a simple model helps to enhance welfare, but in a more complex model, the net effect of tying on welfare is ambiguous. Choi [75] proposes a theoretical model based on the influence of the combination of Microsoft Windows media player and Windows. Bundling as a means of price discrimination will reduce costs, and the network effect will make the price optimal. Then, Chao and Derdenger adopt video games to carry out empirical analysis of pricing and reach a conclusion consistent with the theoretical model. Amelio and Bruno [76] conduct a case study. Assuming the profit-maximizing price of a party is negative, it is not feasible to actually charge a negative price. It is found that tying can both make profits and increase welfare. Ruhmer [67] constructs a single-destination two-sided model. The indirect network effect increases the benefits of price reduction, making collusion difficult to maintain.

Hagiu [77] provides a duopoly model of two-sided platforms. Armstrong and Wright [32] establish a bottleneck model of two-sided competition, The empirical platform can charge the producers of the market for user fees. Spulber [78] proves the choice of buyers and sellers and finds that they should either search in a decentralized market or search through an intermediary. Hagiu [66] constructs a competitive model for platform pricing. By analyzing the economic and strategic factors in the optimal access pricing structure of the two-sided platforms connecting consumers and producers, the competition between producers is introduced.

Farrell and Klemperer [79] construct a network effect model based on three factors: the degree of substitution of competitive platforms, the intensity of positive network effects, and the degree to which production is characterized by economies of scale. Rysman [28] believes that the single destination preference, the scale and intensity of network effects, and the price elasticity system are all key parameters of the platform competition network effect model. Brown and Morgan [80] demonstrate the competition between eBay and Yahoo through auctions. Edelman [81] and Hal [42] give the modeling formula of auction market. Levin [82] studies a related model and show that there is a near-effective equilibrium of mixed strategies. Gawer and Cusumano [83] demonstrate the pricing strategies of Microsoft, Apple, IBM, Palm, and other operating system enterprises.

Baye and Morgan build a price competition model where consumers can search by price. Einav et al. [84] empirically study auction pricing and additional prices and find that fees and prices have no significant impact on consumers. Gentzkow and Shapiro [85] empirically study the personal consumption of online media and discover the long tail demand theory of platform economy. Roberts and Sweeting [86] construct a platform dynamic pricing model. Rysman [28] constructs a differentiated platform competition model to solve the platform antitrust issue.

Regarding the issue of dynamic competition, Doganoglu [87] and Mitchell and Skrzypacz [88] derive the Markov perfect equilibrium of the indefinite game where the consumer utility is a growth function of market share in the past. Markovich and Moenius [89] develop an industry computing model including “hardware” and “software” components, which assumes that consumers live for two periods and benefit from indirect network effects through the quality of existing products. Chen et al. [90] develop a computational dynamic model in which it is assumed that consumer benefits are a growing function of the size of the network at the time of purchase (consumers are not forward-looking). These assumptions assume that consumer behavior is relatively simple. Driskill [91] constructs a deterministic and continuous-time model where consumers are forward-looking. Cabral [92] builds a dynamic model of price competition based on balanced symmetry and network effects.

6. Research Outlook

As one of the three landmark events of the digital economic revolution [93], the platform economy will become the most important form of economic organization in the foreseeable future when the academia will not only be limited to the research of platform economy such as economics, management, econometrics, law, and sociology, but also possible to conduct cross-field and multifield research. One of the main focuses of two-sided markets economy is to solve the issue of how the platform can price both sides of the market at the same time. Platform opening, market access, pricing analysis, governance supervision, and antitrust are all significant directions for future research.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References

  1. D. S. Evans, “The antitrust economics of multi-sided platforms markets,” Yale Journal on Regulation, vol. 20, pp. 325–382, 2003. View at: Google Scholar
  2. Brynjolfsson, Erik, Smith et al., “Frictionless commerce? A comparison of internet and conventional retailers,” Management Science, vol. 46, no. 4, pp. 563–585, 2000. View at: Publisher Site | Google Scholar
  3. P. Evans and A. Gawer, The Rise of the Platform Enterprise: A Global Survey, The Center for Global Enterprise, New York, NY, USA, 2015.
  4. A. Cusumano and C. Tucker, “Digital economics,” Journal of Economic Literature, vol. 57, no. 1, pp. 3–43, 2019. View at: Publisher Site | Google Scholar
  5. S. J. Liebowitz and S. E. Margolis, “Network externality: an uncommon tragedy,” Journal of Economic Perspectives, vol. 8, no. 2, pp. 133–150, 1994. View at: Publisher Site | Google Scholar
  6. J.-C. Rochet and J. Tirole, “Platform competition in two-sided markets,” Journal of the European Economic Association, vol. 1, no. 4, pp. 990–1029, 2003. View at: Publisher Site | Google Scholar
  7. M. Armstrong, “Network interconnection with asymmetric networks and heterogeneous calling patterns,” Information Economics and Policy, vol. 16, no. 3, pp. 375–390, 2004. View at: Publisher Site | Google Scholar
  8. B. Caillaud and B. Jullien, “Chicken & egg: competition among intermediation service 49providers,” The RAND Journal of Economics, vol. 34, no. 2, pp. 309–328, 2003. View at: Publisher Site | Google Scholar
  9. M. Armstrong, “Competition in two-sided markets,” The RAND Journal of Economics, vol. 37, no. 3, pp. 668–691, 2006. View at: Publisher Site | Google Scholar
  10. D. S. Evans and R. Schmalensee, “The industrial organization of markets with two-sided platforms,” Tech. Rep., National Bureau of Economic Research, Cambridge, MA, USA, 2007, Working Paper No. 11603. View at: Google Scholar
  11. L. Filistrucchi, D. Geradin, and E. van Damme, “Market definition in two-sided marketss: theory and practice,” Journal of Competition Law and Economics, vol. 10, no. 2, pp. 293–339, 2013. View at: Google Scholar
  12. J.-C. Rochet and J. Tirole, “Two-sided markets: a progress report,” The RAND Journal of Economics, vol. 37, no. 3, pp. 645–667, 2006. View at: Publisher Site | Google Scholar
  13. G. Parker and M. G. van Alstyne, “Information compliments, substitutes, and strategic product design,” SSRN Electronic Journal, 2000. View at: Publisher Site | Google Scholar
  14. A. Hagiu and J. Wright., “Multi-sided platforms,” International Journal of Industrial Organization, vol. 43, pp. 162–174, 2015. View at: Publisher Site | Google Scholar
  15. D. S. Evans and R. Schmalensee, Catalyst Code: The Strategies behind the World's Most Dynamic Companies, Harvard Business School Press Books, Boston, MA, USA, 2007.
  16. B. Jullien, Two-sided B to B Platforms, Oxford University Press, New York, NY, USA, 2012.
  17. V. Nocke, M. Peitz, and K. Stahl, “Platform ownership,” Journal of the European Economic Association, vol. 5, no. 6, pp. 1130–1160, 2007. View at: Publisher Site | Google Scholar
  18. A. Hagiu and J. Bruno, “Why do intermediaries divert search?” The RAND Journal of Economics, vol. 42, no. 2, pp. 337–362, 2011. View at: Publisher Site | Google Scholar
  19. M. R. Baye, J. Morgan, and P. Scholten, “Temporal price dispersion: evidence from an online consumer electronics market,” Journal of Interactive Marketing, vol. 18, no. 4, pp. 101–115, 2010. View at: Publisher Site | Google Scholar
  20. E. G. Weyl, “A price theory of multi-sided platforms,” American Economic Review, vol. 100, no. 4, pp. 1642–1672, 2010. View at: Publisher Site | Google Scholar
  21. D. A. Corniere, “Search advertising,” American Economic Journal: Microeconomics, vol. 8, no. 3, pp. 156–188, 2016. View at: Publisher Site | Google Scholar
  22. T. Simcoe, “Standard setting committees: consensus governance for shared technology platforms,” American Economic Review, vol. 102, no. 1, pp. 305–336, 2012. View at: Publisher Site | Google Scholar
  23. M. Rysman, “An empirical analysis of payment card usage,” Journal of Industrial Economics, vol. 55, no. 1, pp. 1–36, 2007. View at: Google Scholar
  24. H. Hanna and Y. Yehezkel, “Platform competition under asymmetric information,” American Economic Journal Microeconomics, vol. 5, no. 3, pp. 22–68, 2013. View at: Publisher Site | Google Scholar
  25. D. S. Evans and M. D. Noel, “Analyzing market definition and power in multi-sided platform markets,” SSRN Electronic Journal, 2005. View at: Publisher Site | Google Scholar
  26. A. Moazed and L. Nicholas, Johnson. Modern Monopolies: What it Takes to Dominate the 21st Century Economy, St. Martin’s Press, New York, NY, USA, 2016.
  27. D. S. Evans, “Why the dynamics of competition for online platforms leads to sleepless nights but not sleepy monopolies,” Social Science Electronic Publishing, 2017. View at: Google Scholar
  28. M. Rysman, “The economics of two-sided markets,” Journal of Economic Perspectives, vol. 23, no. 3, pp. 125–143, 2009. View at: Publisher Site | Google Scholar
  29. H. Jacqueline and D. Jonathan, “Marketing in context -- the marketing authenticity of owner/entrepreneurs of small firms: case evidence from Welsh [uk] sme food and drink producers and retailers,” Small Enterprise Research, vol. 18, no. 1, pp. 33–50, 2011. View at: Publisher Site | Google Scholar
  30. I. Spiegler, “Knowledge management: a new idea or a recycled concept?” Communications of the Ais, vol. 3, 2000. View at: Publisher Site | Google Scholar
  31. B. Caillaud and B. Jullien, “Competing cybermediaries,” European Economic Review, vol. 45, no. 4–6, pp. 797–808, 2001. View at: Publisher Site | Google Scholar
  32. M. Armstrong and J. Wright, “Two-sided markets, competitive bottlenecks and exclusive contracts,” Economic Theory, vol. 32, no. 2, pp. 353–380, 2007. View at: Publisher Site | Google Scholar
  33. N. Economides and E. Katsamakas, “Linux vs. Windows: a comparison of application and platform innovation incentives for open source and proprietary software platforms,” in The Economics of Open Source Software Development, pp. 207–218, Elsevier, Amsterdam, Netherlands, 2006. View at: Publisher Site | Google Scholar
  34. B. Jullien, “Competition in multi-sided markets: divide and conquer,” American Economic Journal, Microeconomics, vol. 3, no. 4, pp. 186–220, 2011. View at: Publisher Site | Google Scholar
  35. E. G. Weyl, “Slutsky meets marschak: the first-order identification of multi-product production,” SSRN Electronic Journal, vol. 16, 2009. View at: Publisher Site | Google Scholar
  36. A. Tiwana, Platform Ecosystems: Aligning Architecture, Governance, and Strategy, Morgan Kaufmann Publishers Inc., Burlington, MA, USA, 2014.
  37. S. Mukhopadhyay, M. de Reuver, and H. Bouwman, “Effectiveness of control mechanisms in mobile platform ecosystem,” Telematics and Informatics, vol. 33, no. 3, pp. 848–859, 2016. View at: Publisher Site | Google Scholar
  38. R. Adner and R. Kapoor, “Value creation in innovation ecosystems: how the structure of technological interdependence affects firm performance in new technology generations,” Strategic Management Journal, vol. 31, no. 3, pp. 306–333, 2009. View at: Publisher Site | Google Scholar
  39. M. G. Jacobides, “Who does what and who takes what: benefiting from innovation,” 2006. View at: Google Scholar
  40. G. Annabelle and M. A. Cusumano, “Industry platforms and ecosystem innovation,” Journal of Product Innovation Management, vol. 31, no. 3, pp. 417–433, 2014. View at: Publisher Site | Google Scholar
  41. D. P. Mcintyre and A. Srinivasan, “Networks, platforms, and strategy: emerging views and next steps,” Strategic Management Journal, vol. 38, no. 1, pp. 141–160, 2017. View at: Publisher Site | Google Scholar
  42. R. V. Hal, “Position auctions,” International Journal of Industrial Organization, vol. 25, no. 6, pp. 1163–1178, 2007. View at: Publisher Site | Google Scholar
  43. R. E. Hall, Digital Dealing: How E-Markets Are Transforming the Economy, W. W. Norton, New York, NY, USA, 2002.
  44. E. Orlov, “How does the internet influence price dispersion? Evidence from the airline industry,” The Journal of Industrial Economics, vol. 59, no. 1, pp. 21–37, 2011. View at: Publisher Site | Google Scholar
  45. R. Jensen, “The digital provide: information (technology), market performance, and welfare in the South Indian fisheries sector,” The Quarterly Journal of Economics, vol. 122, no. 1, pp. 879–924, 2007. View at: Publisher Site | Google Scholar
  46. J. C. Aker, “Information from markets near and far: mobile phones and agricultural markets in Niger,” American Economic Journal: Applied Economics, vol. 2, no. 3, pp. 46–59, 2010. View at: Publisher Site | Google Scholar
  47. C. Parke, K. Ramdas, and N. Savva, “Is IT enough? Evidence from a natural experiment in India]s agriculture markets,” Management Science, vol. 62, no. 9, pp. 2481–2503, 2016. View at: Publisher Site | Google Scholar
  48. E. Damiano and L. Hao, “Competing matchmaking,” Journal of the European Economic Association, vol. 6, no. 4, pp. 789–818, 2008. View at: Publisher Site | Google Scholar
  49. A. Ambrus and R. Argenziano, “Asymmetric networks in two-sided markets,” American Economic Journal: Microeconomics, vol. 1, no. 1, pp. 17–52, 2009. View at: Publisher Site | Google Scholar
  50. M. Peitz, S. Rady, and P. Trepper, “Experimentation in two-sided markets,” Social Science Electronic Publishing, 2010. View at: Publisher Site | Google Scholar
  51. A. White and E. G. Weyl, “Imperfect platform competition: a general framework,” 2010. View at: Google Scholar
  52. D. S. Evans, “The Antitrust Analysis of Multi-Sided Platform Businesses,” National Bureau of Economic Research, Cambridge, MA, USA, 2013. View at: Google Scholar
  53. J.-C. Rochet and J. Tirole, “Cooperation among competitors: some economics of payment card associations,” The RAND Journal of Economics, vol. 33, no. 4, pp. 549–570, 2002. View at: Publisher Site | Google Scholar
  54. E. G. Weyl, “Monopoly, ramsey and lindahl in Rochet and Tirole (2003),” Economics Letters, vol. 103, no. 2, pp. 99-100, 2009. View at: Publisher Site | Google Scholar
  55. B. Jullien, “Competing with network externalities and price discrimination,” 2001. View at: Google Scholar
  56. G. Ellison, D. Fudenberg, and M. Möbius, “Competing auctions,” Journal of the European Economic Association, vol. 2, no. 1, pp. 30–66, 2004. View at: Publisher Site | Google Scholar
  57. E. Damiano, H. Li, and W. Suen, “Unravelling of dynamic sorting,” Review of Economic Studies, vol. 72, no. 4, pp. 1057–1076, 2005. View at: Publisher Site | Google Scholar
  58. A. Ambrus and R. Argenziano, “Network markets and consumers coordination,” Social Science Electronic Publishing, vol. 10, 2004. View at: Google Scholar
  59. G. Z. Jin and A. Kato, “Price, quality, and reputation: evidence from an online field experiment,” The RAND Journal of Economics, vol. 37, no. 4, pp. 983–1005, 2006. View at: Publisher Site | Google Scholar
  60. C. Avery, P. Resnick, and R. Zeckhauser, “The market for evaluations”, American Economics Review, vol. 89, no. 3, pp. 564–584, 1999.
  61. C. Dellarocas, “Strategic manipulation of internet opinion forums: implications for consumers and firms,” Management Science, vol. 52, no. 10, pp. 1577–1593, 2006. View at: Publisher Site | Google Scholar
  62. L. Cabral and A. Hortaçsu, “The dynamics of seller reputation: evidence from Ebay,” The Journal of Industrial Economics, vol. 58, no. 1, pp. 54–78, 2010. View at: Publisher Site | Google Scholar
  63. M. Saeedi, Z. Shen, and N. Sundaresan, “The value of feedback: an analysis of reputation system,” Social Science Electronic Publishing, vol. 16, p. 2005, 2014. View at: Google Scholar
  64. B. Rieder and G. Sire, “Conflicts of interest and incentives to bias: a microeconomic critique of Google’s tangled position on the Web,” New Media & Society, vol. 16, no. 2, pp. 195–211, 2013. View at: Publisher Site | Google Scholar
  65. D. S. Evans, “The economics of the online advertising industry,” Review of Network Economics, vol. 7, no. 3, 2008. View at: Publisher Site | Google Scholar
  66. A. Hagiu, “Quantity vs. Quality and Exclusion by Two-Sided Platforms,” SSRN Electronic Journal, Harvard Business School Strategy Unit, Boston, MA, USA, 2009. View at: Publisher Site | Google Scholar
  67. I. Ruhmer, Platform Collusion in Two-Sided Markets, University of Mannheim, Mannheim, Germany, 2011.
  68. M. Armstrong and M. Adendorff, “Data warehouse system” U.S. Patent Application 09/987,905, 2002.
  69. G. G. Parker and M. Van Alstyne, Unbundling in the Presence of Network Externalities, Mimeo, New York, NY, USA, 2002.
  70. M. Rysman, S. Engerman, L. Gallman et al., “The economics of network industries,” Journal of Economic Literature, vol. 40, no. 2, p. 556, 2002. View at: Google Scholar
  71. I. R. Segal and M. D. Whinston, “Exclusive contracts and protection of investments,” SSRN Electronic Journal, vol. 31, no. 4, pp. 603–633, 2000. View at: Publisher Site | Google Scholar
  72. T. Doganoglu and J. Wright, “Exclusive dealing with network effects,” International Journal of Industrial Organization, vol. 28, no. 2, pp. 145–154, 2010. View at: Publisher Site | Google Scholar
  73. L. Leung and P. S. N. Lee, “The influences of information literacy, internet addiction and parenting styles on internet risks,” New Media & Society, vol. 14, no. 1, pp. 117–136, 2012. View at: Publisher Site | Google Scholar
  74. J.-C. Rochet and T. Jean, “Competition policy in two-sided markets,” Handbook of Antitrust Economics, pp. 543–582, 2008. View at: Google Scholar
  75. J. P. Choi, “Tying in two-sided markets with multi-homing,” The Journal of Industrial Economics, vol. 58, no. 3, pp. 607–626, 2010. View at: Publisher Site | Google Scholar
  76. A. Amelio and B. Jullien, “Tying and freebies in two-sided markets,” International Journal of Industrial Organization, vol. 30, no. 5, pp. 436–446, 2012. View at: Publisher Site | Google Scholar
  77. A. Hagiu, “Pricing and commitment by two-sided platforms,” The RAND Journal of Economics, vol. 37, no. 3, pp. 720–737, 2006. View at: Publisher Site | Google Scholar
  78. D. L. Reiley and D. F. Spulber, “Business-to-business electronic commerce,” 2000, https://www.vanderbilt.edu/econ. View at: Google Scholar
  79. J. Farrell and P. Klemperer, “Chapter 31 coordination and lock-in: competition with switching costs and network effects,” Handbook of Industrial Organization, vol. 3, no. 6, pp. 1967–2072, 2007. View at: Publisher Site | Google Scholar
  80. J. Brown and J. Morgan, “How much is a dollar worth? Tipping versus equilibrium coexistence on competing online auction sites,” Journal of Political Economy, vol. 117, no. 4, pp. 668–700, 2009. View at: Publisher Site | Google Scholar
  81. B. O. Edelman, “Internet advertising and the generalized second-price auction: selling billions of dollars worth of keywords,” The American Economic Review, vol. 97, no. 1, pp. 242–259, 2007. View at: Publisher Site | Google Scholar
  82. B. J. Levin, “Matching and price competition matching,” American Economic Review, vol. 96, no. 3, pp. 652–668, 2006. View at: Google Scholar
  83. M. A. Cusumano and A. Gawer, “The elements of platform leadership,” IEEE Engineering Management Review, vol. 31, no. 1, p. 8, 2003. View at: Publisher Site | Google Scholar
  84. L. Einav, T. Kuchler, J. Levin et al., “Learning from Seller Experiements in Online Markets,” Tech. Rep., 2011, National Bureau of Economic Research, Cambridge, MA, USA. View at: Google Scholar
  85. M. Gentzkow and J. M. Shapiro, “What drives media slant? Evidence from U.S. daily newspapers,” Econometrica, vol. 78, no. 1, pp. 35–71, 2010. View at: Publisher Site | Google Scholar
  86. J. W. Roberts and A. Sweeting, “Competition versus auction design,” 2010. View at: Google Scholar
  87. T. Doganoglu, “Dynamic price competition with consumption externalities,” Netnomics, vol. 5, no. 1, pp. 43–69, 2003. View at: Publisher Site | Google Scholar
  88. M. F. Mitchell and A. Skrzypacz, “Network externalities and long-run market shares,” Economic Theory, vol. 29, no. 3, pp. 621–648, 2006. View at: Publisher Site | Google Scholar
  89. S. Markovich and J. Moenius, “Winning while losing: competition dynamics in the presence of indirect network effects,” International Journal of Industrial Organization, vol. 27, no. 3, pp. 346–357, 2009. View at: Publisher Site | Google Scholar
  90. J. Chen, U. Doraszelski, and J. E. Harrington Jr., “Avoiding market dominance: product compatibility in markets with network effects,” The RAND Journal of Economics, vol. 40, no. 3, pp. 455–485, 2007. View at: Publisher Site | Google Scholar
  91. R. Driskill, Monopoly and Oligopoly Supply of a Good with Dynamic Network Externalities, vol. 47, Vanderbilt University, Nashville, TN, USA, 2007.
  92. L. Cabral, “Dynamic price competition with network effects,” The Review of Economic Studies, vol. 78, no. 1, pp. 83–111, 2011. View at: Publisher Site | Google Scholar
  93. A. McAfee and E. Brynjolfsson, “Machine, platform, crowd: Harnessing our digital future,” WW Norton & Company, New York, NY, USA, 2017. View at: Google Scholar

Copyright © 2020 Chen Xue et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder
Views1832
Downloads673
Citations

Related articles

Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.