Using Social Network Analysis to Study Value Configurations in Virtual Worlds

Contenido de la comunicación

1. Introduction

The increasing importance of digital economy and the concept of value are getting attention in literature – the digital economy is challenging conventional business models and different expressions for value creation such as adding value [Porter 1985] or creating value [Normann and Ramirez 1994] or extracting value [Rayport and Sviokla 1995], are getting popular. As a result, recent business literature is filled with description of new business models of the digital economy [e.g. Timmer 1998, Tapscott, Ticoll & Lowy 2000, Weill & Vitale 2001, Applegate 2001] and value creation mechanisms related to these business models. These new business models and value creation mechanisms are often described with minimal precision and especially the logic underlying them is sometimes fuzzy. Addressing this problem, Sweet [2001] offers four fundamental strategic value configuration logics that, according to him, have endured all the previous economic paradigm changes and should be taken into account when building a business model and tools for its realization.

While digital economy has introduced new value propositions, it hasn’t entirely replaced the old ones. However, the economic principles underlying many of these old and new propositions have evolved too from economies of scale, to economies of scope, and to network effects. As these business models of the digital age are rarely applied outside the application area in which they are developed, we need new descriptive models that enable us to analyse the changes the digital economy inflicts on variety of companies operating in different industries.

This paper is part of an ongoing research project called VinCo - Innovative Business and Collaboration in Virtual Environments. VinCo project explores the interfaces between virtual and traditional environments and investigates virtual worlds as centres for collaboration and business. Knowledge intensive value creation and virtual worlds has been chosen as the focus in this research as they incorporate the two most recent evolutionary economies – the knowledge economy and the digital economy. In this project I intent to identify the core sources of knowledge intensive value creation, using Sweet [2001] and Amit & Zott [2001] as a starting point, and generate a set of value configurations, similar to Stabell and Fjeldstad [1998], that can be used to analyze and formulate business strategies for the digital economy.

Since I have just started to collect data the aim of this paper is not to report the results of this project, but to describe the research method I’m using in this project to identify the mechanisms that knowledge intensive companies in virtual worlds use to create value to customer. As this research area is filled with ambiguous terms and concepts, I start with reflecting this work with existing literature and this way define the central concepts used in this paper. In chapter 3, I’ll describe a little bit of the virtual world Second Life and use examples from Second Life to further illustrate these concepts. After that I turn into the proposed research method and describe it in detail. I conclude with the expected results and the implications of these results to researchers and companies interested in knowledge intensive value creation.

2. Value creation and configuration in knowledge intensive business environment

Few concepts in business today are as widely discussed as the concept of business models. Many people attribute the success of companies like eBay, Dell, and Amazon to the ways they used new technologies in unprecedented ways and even created new business models altogether [Malone, et al. 2006]. This discourse rarely answer questions like whether these business models are changing over time or how individual companies can exploit the business models described in business books to improve their own performance.

One notable exception is the work of Stabell and Fjeldstad [1998], which builds on the principles of Porter’s [1985] value chain and expands Porter’s descriptive “toolbox” with two additional analytical models or value configurations. All these value configurations are intended to be generic models that companies can use to represent and analyze their firm-level value creation. The analytical power comes from the ability to describe value creation in different industries – while business models may be too case dependent to be really descriptive, these value configurations hold the promise to be somewhat common denominator to different kinds of firms. However, value configurations are only a part of the picture (or business model) as can be seen from the figure below (cf. Figure 1).

Figure 1 The Business Model Ontology [Osterwaldor 2004]

The value configurations of Stabell and Fjeldstad [1998] are used in this paper as an example of the concept: Based on Thompson’s [1967] typology of long-linked, intensive and mediating technologies, they explore the idea that the Porter’s [1985] value chain models the activities of a manufacturing firms utilizing typically long-linked technology. Following this typology, their “value shop” configuration models firms, where value is created by mobilizing resources and activities to resolve a particular customer problem (intensive technology), and “value network” configuration models firms that create value by facilitating a network relationship between their customers using a mediating technology. Hospitals, professional service firms, and educational institutions are examples of firms that rely on an intensive technology. Examples of companies that create value by facilitating exchange among their customers by mediating technology are telephone companies, transportation companies, insurance companies and banks.

According to Sweet [2001] these value configurations are not the core building blocks of the business model, but should be themselves based on different value configuration logics. He offers four of these fundamental strategic value configuration logics:

1. Value-extracting logic - Increasing output with diminishing amounts of input per unit.

2. Value-adding logic - This logic is a mirror image of the value extracting logic. If a new function, attribute, or aspect of a product or service adds value, and customers are willing to pay for it, then this value addition should be engineered into the product / service chain.

3. Value-capturing logic - Value capturing configuration logic is the logic of capturing information regarding processes, transactions, or customers, separating this information from the source or user, and converting it into value.

4. Value-creating logic - Value creation logic occurs when cumulative inputs of customers can be stored / frozen, aggregated and made available to other customers and contributors to a network. Value creating strategy requires the connectedness of networks of producers and customers such that increasing returns to scale emerge.

Combining the ideas of Stabell and Fjeldstad [1998] and Sweet [2001] we get Table 1 describing the central concepts with the help of the three example value configurations. In this table a typical business model and managed value element is listed for each configuration along with examples of typical business sectors for these value configurations. These are more of descriptive features of any given value configuration than truly differentiating properties – you can construct many different business models with these configurations and apply these configuration in different value systems or business sectors than listed in the table. Thompson’s [1967] primary technologies and the economic principles listed in the Table 1 are distinctive to our three example configurations. However, this is not the case with any additional value configurations and apart from economies of scale the economic principles frequently mentioned in business literature are not rigorously defined.

For these above mentioned reasons I will concentrate in this research on the primary interaction type that the company has with a customer and the value configuration logics of these different configurations. Value configuration logics are not distinctive to a single value configuration either, as can be seen from the table below (cf. Table 1). Each value configuration may use different value configuration logics depending on the business environment or market situation – for example value chain configuration may change from value adding logic to value extracting logic as time goes by. Compared to economic principles, these value configuration logics are clearly defined (cf. Sweet 2001, or Amit & Zott 2001 for another set of logics) and in addition they can used as poles in different continuums (for example value-extracting – value-adding) in which different configuration logics can be placed.

With these choices, I’m taking a different viewpoint on the Business Model Ontology presented by Osterwaldor [2004]. I concur with the ontology on the level of essential elements, but there is one essential link missing in Osterwaldor’s ontology – in many cases the customer interface is an important part of the company’s resources and capabilities that need to be matched with intended value proposition with the help of value configuration. For this reason I’m placing the value configuration in the middle in my research and introducing a link from customer interface mechanism to value configuration. The modified ontology is presented in the Figure 2.

Figure 2 Modified business model ontology used in this research

Turning into knowledge intenseness and existing business literature on knowledge intensive / digital age value configurations: Since the mid-1990s, business services based on expertise have been referred to with the term “knowledge-intensive business services” or KIBS. The term intensive in this context emphasizes that the knowledge functions concerned involve more than mere transfer of existing information (Miles et al 1995). There are several competing definitions of KIBS, and especially operationalization of the concept is especially hard to achieve due to the growing significance of knowledge in practically all branches today (Toivonen 2004). However it is this increasing importance of knowledge-related transactions in the whole economy that has increased research in this field and descriptions of value configurations suitable for various market situations and business strategies.

Looking into this literature, it becomes clear that the three basic value configurations presented above are not suitable for every situation and that more value configurations can be found in conjunction with knowledge intensive business and digital economy. For example, there have been a growing number of descriptions of knowledge intensive brokering [e.g. Tapscott, Ticoll & Lowy 2000, Brusoni & Prencipe 2001, Toivonen 2004], especially when dynamic and knowledge intensive capabilities are needed. In these cases, the interactive coordination of knowledge and networks is done by system integrator firms which ‘know more that they do’. These firms are situated between the “Shop” and “Network” configurations in a sense that they form virtual organizations, usually relevant only to the customer’s problem, and their value configuration logic is based on knowing what is relevant and where these relevant resources can be found. In essence, they incorporate value-adding logic when incorporating only relevant recourses to virtual organization and value-capturing logic when using existing solutions and network linkages for resolving a particular customer’s problem. I use the name Aggregator [Tapscott, Ticoll & Lowy 2000] for this value configuration.

In similar way, possible value configurations can be identified from existing business model taxonomies [Timmer 1998, Tapscott, Ticoll & Lowy 2000, Linder and Cantrell 2000, Weill & Vitale 2001, Applegate 2001, Malone, et al. 2006]. Most of these taxonomies are similar to Sweet’s [2001] approach in trying to find business types that have always existed to some degree, but they also try to recognize the more recent ones that have made sense only through that diminishing transaction cost, increasing returns, and network effects of the digital economy. Concerning this research, it is noteworthy that none of these competing taxonomies are tested by trying to classify existing companies according to these taxonomies. Set of most common value configurations are listed with examples from the virtual world Second Life in next chapter.

3. Second Life virtual world

Virtual worlds are subgroup of contemporary social media platforms. They typically look like video games, but are accessed through the Internet by potentially tens of thousands of concurrent users. Each user explores the virtual world using an avatar, a human or human-like character and take part in different kinds of social interactions, including economic ones. Despite the differences in the platform of interaction, the participants are human beings. The social, economic and psychological patterns of human interactions seem to translate to these new platforms of interaction [Castronova 2005] just as they have translated to other online services previously. So, from the viewpoint of economics the virtual worlds do not differ from the real world in a fundamental way – for example the valuations that the human beings place on virtual property resemble the valuations on real world object [Lehtiniemi 2008].

Every virtual world contains an in-world economy to some degree [Castronova 2005], since the time of the user is always a scarce resource. Most of the virtual worlds have a designed internal system of economic transactions and many virtual worlds have an internal currency that can be used as a mean of exchange. Initially, real-money trade was not the intention of the virtual world operators. Instead, it emerged as a spontaneous by-product between the users of massively multiplayer online role-playing games (‘MMORPG’) such as World of Warcraft [Lehdonvirta 2009]. Later on, some virtual worlds have actually been designed so that there are possibilities for producing virtual property for the purpose of being traded for real money [Ondrejka 2004] and today the estimate on the worldwide amount of real money spent on virtual items is about USD 1.5 billion [Linden Lab 2009].

The virtual world Second Life has perhaps the most versatile in-world economy – although it isn’t the biggest of these virtual economies. In Second Life the users can own virtual land, organize events, use or perform services, produce virtual goods and sell them in markets – just to name few possibilities. Much like with the knowledge intensive industries, traditional value chain analysis [Porter 1985] falls short in the analysis of the entire virtual markets, since value creation opportunities in virtual markets may result from totally new combinations of information, virtual products and services. Some of the more traditional value configurations found in Second Life are presented in the Table 2.

Table 2 Typical value configurations with examples from Second Life

4. Research setting

Virtual environments are currently used, among other things, for medical, political, educational, military, social, entertainment, and commercial purposes [Fairfield 2005]. In this paper, I propose a serious research application of virtual worlds: their use for experiments in social and economic sciences. Several unique features argue for this kind of use. First, virtual worlds allow experimentation and observation at the level of an entire world while still maintaining specific focus on the research questions (of course respecting the avatars’ rights). Second, research in virtual worlds is scalable – virtual worlds allow huge numbers of research subjects with automated scripts collecting the data. Third, the people who engage with one another inside virtual worlds seem to constitute a genuine society. For example, virtual worlds seem to develop internal markets, in which users of these virtual world trade virtual items with one another at what appear to be stable and robust prices [Castronova 2008].

During our research project, a business exercise is organized with several collaborating business courses. These courses from different (Finnish) universities are mainly master level courses focusing on entrepreneurship and business planning. In this exercise groups of students will be given a task to form a business plan suitable for Second Life and then implement this business plan within a given budget and timetable. The budget consist of venture capital given by researchers in stages and stipends received from Linden Lab (the operator of Second Life) and the total budget amounts to 20,000 L$ (Linden Dollars) – with a current exchange rate of 270 L$ / 1 US$ this amounts to only 74 US$ or about 50 Euros with current rates (6.9.2009). However, this budget is enough to set up a small business in Second Life with all the cost involved. The length of the exercise is negotiated with the course organizers. Usually the student groups are given 12 weeks to familiarize themselves with the platform and the market, plan their approach, test their ideas, do marketing and reach the customer interface. This budget and timeline won’t allow groups to implement the most capital intensive business models, but there is plenty of room to generate original business ideas and even change plans during the exercise. For example, while testing the research setting, the researchers in this project set up a full service (aggregate value configuration) funeral home within this budget and timeframe.

For data gathering this research uses a modified version of in-world tracking script originally made by Nick Yee [2006] that allows the researchers to form ego nets from all the social connections of a any given student group. In addition to social networks, we ask student groups to report their use of money during the exercise so that relevant ties from these social networks can be highlighted. By observing how these ego nets form during time, I will be able to identify the primary interaction type of the student group’s company and also the interaction type of all the suppliers these student groups collaborate with during the exercise. Follow-up interviews will be conducted when the value configuration logic is not clear from publicly available material. Combining the observations from the ego nets and interviews, a classification according to existing value configurations should be possible. However, this research approach leaves a possibility to find totally new value configurations as well.

5. Implications

The increasing importance of digital economy is getting attention in literature and as a result, recent business literature is filled with description of new business models of the digital economy. However, these new business models are rarely used to describe business logics outside their initial application area. Neither are they tested, for example by categorizing existing companies according to these academic models.

This research attempts to fill this theoretical gap. Instead of using sometimes elusive concept of business model as a unit of analysis, this research suggests a more detailed analysis of value creation. By identifying the core sources of knowledge intensive value creation and by generating a set of value configurations that are based on these sources of value, researchers and companies are better equipped to analyze the possibilities and challenges of the digital age.

This research uses value configuration logics presented by Sweet [2001] as a starting point and social network analysis to identify the value configurations that are built upon these logics. I have listed some of the more typical value configurations of the digital economy in this paper, but there may be also entirely new ways to address these problems and opportunities in this economy. In essence, market in virtual worlds is knowledge intensive and thus many of the same value creation elements of the knowledge intensive business apply in virtual markets as well. However, virtual markets also present a challenge to RBV theory and traditional knowledge based value creation. As information-based resources and capabilities, which have a higher degree of mobility than other types of resources and capabilities, become more common, also the sustainability of newly created value may be reduced. Most likely new value configurations are needed to explain the new opportunities of the virtual markets. With the research design presented in this paper, I’m aiming to test the validity of these existing theoretical models and also leave room for totally new ways of creating value for customers in virtual worlds.

This ongoing research is intended to offer new business analysing methods for knowledge intensive business, but equally possible outcomes could be guidelines for entering new markers with knowledge intensive products. During the exercise we will ask the student groups also to fill up financial reports and projections for their business plan. The students are required to report these things in the collaborating business courses, whether they participate in our exercise or not, so we don’t increase their workload in this respect. From these reports we will be able to study things like market entry strategies and rationality of business decisions. However, these research questions haven’t been covered in this paper.

Overall, we feel that we have generated a true win-win-win situation with the research setting described in this paper: The ability to fail quickly and learn from the possible failure has been the most interesting aspect for instructors in business courses, the students get concrete exercise in which to test their skills (in contrast to some Excel sheets), and we as researchers get truly motivated groups participating in our research. While the development of this research setting has been a long journey, we are pleased with the results and confident that as a result we get a set of value configurations for other researchers and companies to use in the analysis of knowledge intensive value creation.

Bibliografía/Referencias

Books

• Castronova E. (2005) Synthetic Worlds: The Business and Culture of Online Games. University of Chicago Press, Chicago.
• Lehtiniemi T. (2008) Macroeconomic Indicators in a Virtual Economy. Master's thesis, University of Helsinki, 2008.
• Linder, J. and S. Cantrell (2000). Changing Business Models: Surveying the Landscape. Accenture Institute for Strategic Change.
• Miles I., Kastrinos N., Flanagan K., Bilderbeek R., Hertog B., Huntink W. and Bouman M. (1995) "Knowledge-Intensive Business Services: Users, Carriers and Sources of Innovation". European Innovation Monitoring System (EIMS). EIMS Publication No. 15. Luxembourg.
• Normann R., Ramirez R. (1994) Designing Interactive Strategy: From Value Chain to Value Constellation. Wiley, Chichester-New York, 1994.
• Osterwaldor A. (2004) The business model ontology – a proposition in a design science approach. PhD Thesis, Ecole des Hautes Etudes Commerciales, Universite de Lausanne, 2004.
• Porter M.E. (1985) Competitive Advantage: Creating and Sustaining Superior Performance. Free Press, New York, 1985.
• Tapscott D., Lowi A, Ticoll D. (2000) Digital Capital - Harnessing the Power of Business Webs. Harvard Business School Press, Boston, 2000.
• Thompson J.D. (1967) Organization in Action: Social Science Bases of Administrative Theory. McGraw-Hill, New York, 1967.
• Toivonen M. (2004) Expertise as Business: Long-Term Development and Future Prospects of Knowledge-Intensive Business Services (KIBS). PhD Thesis, Department of Industrial Engineering and Management, Helsinki University of Technology, 2004.
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Book chapters

• Applegate L. M. (2001). "E-business Models: Making sense of the Internet business landscape". In: Dickson G., Gary W., DeSanctis G. (Eds.): Information Technology and the Future Enterprise: New Models for Managers. Prentice Hall, Upper Saddle River, 2001.

Journal articles

• Amit R., Zott C. (2001) "Value creation in e-business". Strategic Management Journal, Vol. 22, No. 6-7, 2001, p. 493-520.
• Brusoni S., Prencipe A. (2001) "Unpacking the Black Box of Modularity". Industrial and Corporate Change, Vol. 10, No. 1, 2001, p. 179-205.
• Lehdonvirta V. (2009) "Virtual item sales as a revenue model: identifying attributes that drive purchase decisions". Electronic Commerce Research, Vol. 9, No. 1-2, p. 97-113.
• Rayport J.F., Sviokla J.J. (1995) "Exploiting the Virtual Value Chain". Harvard Business Review, Vol. 73, No. 6, 1995, p. 75-85.
• Stabell C.B., Fjeldstad O.D. (1998) "Configuring Value for Competitive Advantage: On Chains, Shops, and Networks". Strategic Management Journal, Vol. 19, No. 5, 1998, p. 413-437.
• Sweet P. (2001) "Strategic Value Configuration Logics and the “New” Economy: A Service Economy Revolution?" International Journal of Service Industry Management, Vol. 12, No. 1, 2001, p. 70–83.
• Timmers P. (1998) Business Models for Electronic Markets. Journal on Electronic Markets, Vol. 8, No. 2, 1998, p. 3-8.
• Yee N., Bailenson J.N. (2008) "A Method for Longitudinal Behavioral Data Collection in Second Life". Presence, Vol. 17, No. 6, p. 594-596.

Online article

• Castronova E. (2008) A Test of the Law of Demand in a Virtual World: Exploring the Petri Dish Approach to Social Science. CESifo Working Paper No. 2355. Available online at: http://ssrn.com/abstract=1173642
• Fairfield J. (2005) Virtual Property. Research paper, Indiana university school of law – Bloomington, 2005. Available online at: http://ssrn.com/abstract=807966
• Linden Lab (2009) Linden Lab Goes Shopping, Buys Virtual Goods Marketplaces to Integrate Web Shopping with Second Life. Press Release, January 20, 2009. Available at: http://lindenlab.com/pressroom/releases/01_20_09
• Malone T.W., Weill P., Lai R.K., D'Urso V.T., Herman G., Apel T.G., Woerner S.L. Do some business models perform better than others? Working Paper, MIT-Sloan School of Management, 2006. Available online at: http://ssrn.com/abstract=920667
• Ondrejka C. (2004) Aviators, Moguls, Fashionistas and Barons: Economics and Ownership in Second Life. Working paper, University of Southern California - Annenberg School for Communication, 2004. Available online at: http://ssrn.com/abstract=614663