Understanding the impact of online social networks on disruptive innovation


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Understanding the impact of online social networks on disruptive innovation

  1. 1. 21st European Conference on Information Systems 6-8 June 2013, Utrecht, The Netherlands UNDERSTANDING THE IMPACT OF ONLINE SOCIAL NETWORKS ON DISRUPTIVE INNOVATION Abstract In this paper we explore the state of current knowledge about online social networks (OSNs), and their role in precipitating changes in existing market structures. We do so by reviewing more than 30 recent papers from top-ranked journals in the relevant fields of study. We begin by providing a comprehensive explanation of OSN antecedents that lead to innovation and subsequently to change in market structure. We also provide a novel definition of market structure, and show that disruptive innovation can be regarded as the subset of the innovation space that leads to shifts in market structures. Next, we analyze the process in which innovation in the OSNs disrupt existing market structures. We also show that OSNinduced changes in the market structure usually fall within one of the four categories: changes in transaction costs, bargaining positions, appropriability, and incentives. Finally, we build a framework of a market disruption process and conclude with the delineation of interesting areas for future research. Keywords: Online Social Networks, Disruptive Innovation, Market Structure 1. Introduction The concept of online social networks (OSN) is relatively new, and the surge in its popularity coincides with advances and developments of internet technologies – typically referred to by the umbrella term Web 2.0 – that have taken place during the past decade. Despite their short history, OSNs have emerged as a force that shapes dynamics and the form of a variety of markets. OSNs have also led to the obsoleteness of business strategies that were profitable and that made economic sense for decades before. There are several ways in which OSNs may change the market structure, for example via online activism (Broek et al., 2012). However, this paper focuses on disruptive innovation spurred by OSNs. Consider the music industry. Since the mid-20th century until the late 1990s the business model in the industry was based on physical record sales. However, with the rise of OSNs, the nature of the underlying product – music – changed dramatically. Music suddenly became a digital entity that could be transferred between the OSN users at the click of a button, at negligible marginal cost (examples of such OSNs include Napster or KaZaA (Becker & Clement, 2006). The characteristics of music files, in contrast to the physical records, resemble those of non-rival and non-exclusive public goods. Dominant record labels and distributors such as EMI and HMV faced difficulties in protecting their property rights (Coyle, Gould, Gupta, & Gupta, 2009). Consequently, the innovation of OSNs changed the structure of the music industry profoundly (Madden, 2009). The aim of this paper is to understand the impact that the OSN-induced disruptive innovation has on the market structure of industries. We restrict our investigation to innovation realized by the selfcreated OSNs, rather than innovation spurred by OSNs directed by market incumbents. To this end we review more than 30 recent papers from the top-ranked journals in the relevant fields of studies. Our selection criteria for the reviewed papers include the relevant keywords, area of study, and citation counts. A key contribution of this paper is in the advancement of a theoretical framework that aids in categorizing the extant literature on OSNs. The framework shows that the changes in the market structure, induced by the OSNs, usually fall within one of the categories that include: changes in transaction costs, 1
  2. 2. 21st European Conference on Information Systems 6-8 June 2013, Utrecht, The Netherlands increase of customers bargaining positions, and a lower level of appropriability. We also provide a novel definition of market structure, which is more suitable for describing the observed dynamics in the Web 2.0 domain, than is the traditional market structure definition promoted by the literature on industrial organization. Third, we show that by expanding the scope of the market structure definition we find a clear link between the literature on OSNs and the literature on disruptive innovation. Fourth, the framework that emerges from the study of the literature on OSNs and the market structure highlights avenues for the future research. 2. Methodology The literature study described in this paper includes a systematic review of recent literature (Fogliatto, da Silveira, & Borenstein, 2012). We searched through the Web of Science Social database for peerreviewed articles on the basis of key concepts, including: Online Social Networks, disruptive innovation, and market change. Since an interest of this research is to form a bridge between different research domains, we included research from fields of innovation and technology management, management information systems, general management, organization studies and marketing. We analyzed papers that were published in the peer-reviewed journals between 2004 and 2012. We chose 2004 as the baseline date, because it coincides with the publishing date of Danneels (2004) which is widely viewed as a pioneering work that spun off the research on disruptive innovation (Yu & Hang, 2010). We devise the relevance factor that indicates the most influential papers. The relevance index multiplies the impact factor of the journal by the relative yearly number of citations. Formally: = # ∗ , where is the year the given paper has was published ( ∈ (2004,2011)). In the case that the year of publishing is 2012, we divide the citation number by 0.5. The impact factor is given by ISI Web of Knowledge, and measures relative impact of the journal on the field of economics and business research. We approve paper for a review if: ≥ 20. This step allowed us to narrow our literature review to the most relevant and influential papers. 3. Background We begin by defining OSNs, innovation, and market structure, in order to show that disruptive innovation – the increasingly popular concept in the current literature – can be neatly defined in terms of these three notions. 3.1. Online Social Networks (OSNs) We define online social networks (OSN) as communities of individuals who communicate via an application or a web site which provides advanced tools for the following two features: 1) sharing of digital objects (music, texts, pictures, etc.), which represents technological functionality (Cachia, Compañó, & Da Costa, 2007). 2) Communication between members, which represents a dimension of socialization (Cachia et al., 2007). From practical perspective, OSNs aid in expressing personal relationships and enable their members to traverse the network through the list of connections of their direct connections (Ellison, 2007). OSNs are diverse in their level of socialization, and the richness of a particular OSN can be measured by the degree of social presence it allows (Kaplan & Haenlein, 2010). OSNs may involve all types of non-commercial as well as commercial knowledge and information sharing activities. We concentrate only on the non-commercial types of OSNs, because this provides an interesting perspective 2
  3. 3. 21st European Conference on Information Systems 6-8 June 2013, Utrecht, The Netherlands on how individuals influence corporate structures. Accordingly, we analyze two out of three modes of computer-mediated non-commercial communication: one-to-many (e.g. blogs), and many-to-many (e.g. wikis) (Ellison, 2007). Reciprocity in the exchange between members of the OSN may not be a symmetric; some members of OSNs are relatively passive (net information consumers) while others are relatively active (net information producers) (Gneiser, Heidemann, Klier, Landherr & Probst, 2012). 3.2. Innovation and disruptive innovation theory Innovation is the creation of user value through satisfying the existing or prospective user needs in a novel way (Tidd & Bessant, 2011; Von Hippel, 2009). “Disruptive innovation is a powerful means of broadening and developing new markets and providing new functionality, which, in turn, may disrupt existing market linkages” (Yu & Hang, 2010). Govindarajan and Kopalle (2006) classify an innovation as disruptive if it satisfies the following conditions (compared to the product/service offered by an incumbent): 1. it is inferior on the attributes that are valued by the mainstream customers; 2. it offers a new value propositions that attracts a new customers segment (new market creation) or the more price sensitive mainstream market (low-end disruptiveness); 3. is sold at a lower price; and 4. it penetrates the market from niche to mainstream. Yu and Hang (2010) add that disruptive innovation is a relative phenomenon. What is more, disruptive innovation does not imply a complete destruction of an incumbent’s business model (Anderson & Tushman, 1990; Henderson & Clark, 1990; Christensen, Anthony & Roth, 2004), nor does it imply that the new entrant totally replaces an incumbent (Yu & Hang, 2010). Instead, a disruptive innovation disrupts the established competitive structure of a market (Lyytinen & Rose, 2003). This means that due to a disruptive innovation, an incumbent is either deprived of its dominant position in the respective market, or a new market is created altogether. 3.3. Market Structure We define market structure as an ensemble of consumer, producer, product, and legal features of the market. Each of these features influences the competitive landscape of the market in its own way, and the competitive dynamics in a market can be seen as the product of their interactions (Miller, 2006). At this point we only provide the most essential explanations of these features. First, consumer-related features of market structure comprise of any of the following: size of the consumer base, concentration of the consumer base (it relates to distribution of sizes of customers and is analogical to the concentration ratio of firms in the industry), consumer needs, and the consumer information set. Second, producer-related features of market structure consist of macro elements such as the number of competing firms, the concentration of firms in the industry (measured with e.g.: HerfindahlHirschman Index), and barriers to entry (market contestability), as well as of micro components, such as companies’ business strategies, which include their investment in innovation (Motta, 2004). Taken together, these components determine the degree of firms’ market power, which may lie anywhere in the spectrum between perfect competition and monopoly (Weerawardena, O'Cass, & Julian, 2006). Third, product-related features of market structure refer to the economic characteristics of the underlying product or a service traded in the markets (McGee, Thomas, & Pruett, 2005). The first such attribute is excludability. A product or a service is said to be excludable if the firm possesses the capacity 3
  4. 4. 21st European Conference on Information Systems 6-8 June 2013, Utrecht, The Netherlands to obtain the payment from all customers that use its product/service. For example, a book in a physical form is an excludable good, because only the paying customers can obtain it in his/her physical possession. The second characteristic is rivalry of the product. Rivalry is defined as the capacity of the product to be used only by a limited number of users in a given moment. To put differently, use of the product by a certain set of customers (usually one customer), prevents others outside of the set to use the product at the same time. The final component of our definition of market structure is the legal framework. We see the legal infrastructure as the environmental variable that constrains the space of business strategies, contractual relations, and transactions that can be conducted in the market (Markman, Gianiodis, & Phan, 2009). As such it also influences the trajectory of any changes in other components of market structure. 4. OSN Elements for Innovation In this section we review literature that studies the features that make OSNs relatively more conductive to innovation than the alternative forms of organizing resources at the market (Zammuto et al., 2007). Since we do not have enough of space to discuss all the elements, we focus on structure and decontextualization as central elements of OSNs. 4.1. Structure Structurally, OSNs can be seen as a constellation of users, who are the atomic parts of the network (Musiał & Kazienko, 2012). The users are linked by the means of social relationships. Literature looks at the links between users from both macro and micro perspective. At the macro perspective the focus is typically aimed at the clustering properties of the networks (e.g. Kumar, Novak & Tomkins, 2010; Musiał & Kazienko, 2012; Grabowicz, Ramasco, & Eguiluz, 2012). Clusters within networks are defined as subgroups of users whose members possess higher than average levels of connectedness, where connectedness of a user is typically thought of as a number of connections that the user has to others. Papers like Ferlie et al. (2005) and Centola (2010) link the clustering properties of OSNs to the incidence and dissemination of innovative activity. Centola (2010) observes that network structures characterized by high degree of clustering display significantly higher effectiveness in spreading the behavior of users than networks with low levels of clustering. Studies like Faraj, Jarvenpaa, & Majchrzak (2011), Palla, Barabasi, & Vicsek (2007), and Ferlie et al. (2005) emphasize the importance of controlling for the nature of clustering when evaluating its effect on disseminative properties of networks. In particular, they show that when clustering occurs along the professional backgrounds of the users - that is, when the users group along their areas of expertise – the effect of clustering on dissemination is positive, while it might be negative when clusters are multiprofessional; that is, when its members come from different professional backgrounds. Ferlie et al. (2005) conjectures that the difference stems from different learning processes that are developing in different types of clusters. 4.2. Decontextualization Another attribute of OSNs that has been found to bear strong positive correspondence with innovative output is decontextualization, also referred to as social disembodiment of ideas. As explained by Hughes, Lang, and Vragov (2008), as well as Faraj et al., (2011), decontextualization occurs when ideas become independent of their authors and the contexts in which they were originally shared. In other words, decontextualization allows the other users in the network to use and apply the existing ideas 4
  5. 5. 21st European Conference on Information Systems 6-8 June 2013, Utrecht, The Netherlands independently of their initial creators, or of the problems in which they appeared initially. The reason that decontextualization positively influences innovation is that independence from the initial context or creator allows for the parallelization of efforts; a given idea can be applied to multiple other projects, each of which has some propensity to result in new innovations and ideas. 5. How do OSNs Change the Market Structure? In this section we analyze the structural and social innovation-inducing processes that can be attributed to the decontextualization of the OSNs. Second, we link processes to the changes in the features of the market structure. Discussion of the impact of OSNs on the change in the structure of the market will be extended beyond the case of decontextualization in the full version of this paper. 5.1. Structural Processes Induced by Decontextualization of OSNs and their Effects on Market Structure De-duplicatization of efforts Decontextualization of ideas – an underlying feature of OSNs – leads to lower duplication of effort within OSNs than in the pre-OSN forms of organizations (Osimo, 2008). Access to the pool of ideas decreases costly replications (Casey & Evans, 2011). The second consequence of decontextualization of ideas is parallelizability of innovative activity; multiple groups of OSN users can work on the ideas disseminated through the network independently (Füller, Matzler, & Hoppe, 2008). Parallelizability implies economies of scope; a given idea disseminated through the OSN has a higher multiplier effect on the future innovation, than it would have had if it had been disseminated through the non-OSN structure (Kemppainen, 2011). This has put pressure on multiple pre-OSN world incumbents to modify their business strategies in order to stay afloat (Teece, 2010). Software industry is the case in point. Opensource software is increasingly showing its ability to out-innovate the proprietary solutions of incumbents. Proposition 1: De-duplicatization of efforts can decrease the cost of innovating. Transformation of the Nature of the Product With the onset of OSNs, leveraged by the growth in Web 2.0 technologies, multiple products have undergone a profound transformation of their core economic characteristics. In particular, products that used to be provided as excludable and rivalry goods or services in the pre-OSN world, became nonrivalry and non-excludable in the world permeated with online social communities (Fuchs & Schreier, 2011). Media production (e.g. news, music, and publishing) is a case in point. Transformation of the core economic nature of the product is typically highly disruptive to the pre-OSN market establishment, because it makes the rents that incumbent firms previously gained through the product sales, less appropriable (Dhar & Chang, 2009). As a result, the core business strategies usually become obsolete and unprofitable, and thus force the existing firms to fight for their existence by “exploring blue oceans” (Kim & Mauborgne, 2005), i.e. by exploring the ways to add value in the subspace of market place that is not catered by the OSNs. Proposition 2: Transformation of product economic characteristics, such as appropriability, can lower the profitability and viability of incumbent businesses. 5.2. Social Processes Induced by Decontextualization of OSNs and their Effects on Market Structure 5
  6. 6. 21st European Conference on Information Systems 6-8 June 2013, Utrecht, The Netherlands Mass Collaboration Mass collaboration refers to the particular case of collective action, in which multiple users of an OSN work on the same project independently (Bercovitz & Feldman, 2011). As such the concept is closely related to the idea of parallelizability discussed before. The crucial difference is that parallelizability in the context of decontextualization typically refers to the concurrent work of users of applying same idea to different projects (Faraj et al., 2011). The necessary condition for mass collaboration to be feasible is that the project is modular in nature; i.e. that it consists of parts – modules – that can be worked upon independently. In the final stage, the modules are merged into the final product or service (Van Den Bulte & Joshi, 2007). The typical example of mass collaboration are the open source projects, in which multiple users are working on different parts of software separately, but upon release offer the unified piece of software that consists of these modules. Modularity of the underlying product/service facilitates scalability of production effort, and mass collaboration can be seen as a process of such scaling. Mass collaboration has emerged as the formidable force that transforms the structure of many industries, in which the underlying product/services is modular (e.g. computer software). In these industries, the preOSN incumbents’ development teams need to compete with the wisdom of crowds (i.e. mass collaboration), which the growth of open source community is making increasingly difficult (Tapscott & Williams, 2008). Proposition 3: Mass collaboration may produce higher rate and higher quality of innovation then incumbent’s in-house development teams. Customer Empowerment OSNs have transformed customer base into a formidable market player (Fuchs & Schreier, 2011). This, in turn, has tilted the balance of power away from the pre-OSN incumbents (Zwass, 2010). The increase in customer bargaining position (also known as customer empowerment) can be traced to the increasing transparency facilitated by the OSNs. OSNs have become a platform for customers to share information about product quality (e.g. online reviews, blogs), and prices (e.g. web-aggregators), to name the most prominent. This has decreased customers’ search costs and switching costs (i.e. the forms of transaction costs), and thus decreased the monopolistic rents that incumbents had enjoyed in the pre-OSN world (Zammuto et al., 2007). Zwass (2010) found that the higher the level of separation between the idea and the person generating the idea, the higher the level of collaboration in the community. The argument is that decontextualization allows for sharing and elaborating knowledge with less no costs associated with transfer of knowledge from the idea generator. Nevertheless, in the long run, bureaucracy and adherence to the rules of collaboration such as the ones implemented in Wikipedia or Open-source software projects, are said to bust innovativeness of a collective (Zwass, 2010). Interestingly, adherence to the improvisational rules (best known from Wikipedia) is found to be very efficient in lowering the adverse effect of the lack of proprietary rights (which in essence should stimulate innovativeness). The consequence of decontextualization in the OSNs is the change in the organizational practices and in the ‘command and control’ (Zammuto et al., 2007). Proposition 4: Customer empowerment leads to the shift in the balance of power from producers to consumers. 6. Conclusions In this paper we explored the state of current knowledge about online social networks (OSNs), and their role in precipitating changes in existing market structures and dynamics. We did so by reviewing more 6
  7. 7. 21st European Conference on Information Systems 6-8 June 2013, Utrecht, The Netherlands than 30 recent papers from the top-ranked journals in the relevant fields of studies. We began by providing a comprehensive classification of OSN antecedents that lead to innovation and thereby to the change in market structure. We also provided a novel definition of market structure, and showed that disruptive innovation can be regarded as the subset of the innovation space that leads to shifts in market structures and market dynamics. Next, we provided a comprehensive treatment of the processes that explain how OSNs disturb existing market structures. This research is an initial step towards an integrated theory of disruptive innovation in the environment of online social networks. Our main contribution is the integration of a wide variety of research findings. This research should be valuable for both practitioners and academics. Integrated theory should spur a discourse across different research domains. From the other side, our research can illuminate members of OSNs on the potential of their collective to disrupt market structures. Interestingly, incumbents’ response to the encroachment by the OSNs has not yet been rigorously studied. Understanding the incumbents’ endogenous reactions is crucial for identifying the impact of OSN activity on the empirically observable market structure. Future research should empirically investigate how the pressures induced by OSNs and incumbents’ responses interact over time, and the dynamic evolutionary movements that such interactions entail. References Anderson, P., & Tushman, M. L. (1990). Technological discontinuities and dominant designs: A cyclical model of technological change. Administrative Science Quarterly, 35(4) , 604-633. Becker, J. U., & Clement, M. (2006). Dynamics of illegal participation in peer-to-peer networks—Why do people illegally share media files? Journal of Media Economics, 19(1), 7-32. Bercovitz, J., & Feldman, M. (2011). The mechanisms of collaboration in inventive teams: Composition, social networks, and geography. Research Policy, 40(1), 81-93. Broek, T. A., Ehrenhard, M. L., Langley, D. J., & Groen, A. J. (2012). Dotcauses for sustainability: Combining activism and entrepreneurship. Journal of Public Affairs, 12(3), 214-223. Cachia, R., Compañó, R., & Da Costa, O. (2007). Grasping the potential of online social networks for foresight. Technological Forecasting and Social Change, 74(8), 1179-1203. Casey, G., & Evans, T. (2011). Designing for learning: Online social networks as a classroom environment. The International Review of Research in Open and Distance Learning, 12(7), 1-26. Centola, D. (2010). The spread of behavior in online social network experiment. Science,329(5996), 11941197. Christensen, C. M., Anthony, S. D., & Roth, E. A. (2004). Seeing what's next: Using the theories of innovation to predict industry change Harvard Business Press. New York, USA. Coyle, J. R., Gould, S. J., Gupta, P., & Gupta, R. (2009). “To buy or to pirate”: The matrix of music consumers' acquisition-mode decision-making. Journal of Business Research, 62(10), 1031-1037. Danneels, E. (2004). Disruptive technology reconsidered: A critique and research agenda. Journal of Product Innovation Management, 21(4), 246-258. Dhar, V., & Chang, E. A. (2009). Does chatter matter? the impact of user-generated content on music sales. Journal of Interactive Marketing, 23(4), 300-307. Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer‐ Mediated Communication, 13(1), 210-230. Faraj, S., Jarvenpaa, S. L., & Majchrzak, A. (2011). Knowledge collaboration in online communities. Organization Science, 22(5), 1224-1239. Ferlie, E., Fitzgerald, L., Wood, M., & Hawkins, C. (2005). The nonspread of innovations: The mediating role of professionals. Academy of Management Journal, 48(1), 117-134. Fogliatto, F. S., da Silveira, G. J., & Borenstein, D. (2012). The mass customization decade: An updated review of the literature. International Journal of Production Economics, 14-25 Fuchs, C., & Schreier, M. (2011). Customer empowerment in new product development. Journal of Product Innovation Management, 28(1), 17-32. 7
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