Influences on standards adoption in de facto standardization

Abstract

In the IT industry, de facto standards emerge from standards competition as firms offer incompatible technologies, and user choices determine the outcome of the competition. The standards literature suggests that strong network effects create a bias toward a standard with a large installed base, leading to a winner-take-all outcome. More recently, several researchers have revealed that the dynamics of standardization are much more complex than the explanation offered by the economic theory of networks. Markets do not always exhibit tipping behavior so there is not always a single winner in de facto standardization; and the size of an overall installed base does not always exert a strong influence on adoption decisions. In contrast, network effects drawn from local social influence may be more salient to user adoption decisions. We ask: (1) Do we always observe a winner-take-all outcome in de facto standards competition? (2) What are the different technology adoption patterns observed in de facto standards competition? (3) What are the implications of network effects, switching costs, pricing, and functionality enhancement strategies on the outcome of de facto standards competition in different user network structures? Drawing on the economic theory of networks, the complex network theory, and previous work in the standards literature, we examine the influence of network effects, switching costs, price, and technology functionality on user adoption decisions using agent-based simulation. We incorporate underlying user network structures frequently observed in the real world as an important determining factor of user adoption decisions. Our results suggest that de facto standardization process does not always follow a three-phased S-shaped pattern. Winner-take-all is not a necessary outcome of standards competition. User network structures have a significant impact on the dynamics and outcomes of standards competition.

Interaction between technology standardization and technology development: a coupling effect study

“…Technology standardization is a dynamic process that disseminates technologies and knowledge [16,32].…”

Evolution toward an open value system for smart mobility services

“…The dynamic system simulations build on the earlier conceptual studies on radio spectrum regulation impacting the system dynamics (Basaure, Casey & Hämmäinen 2012). Advanced ABM simulations are recently applied also to related areas such as influence of ICT standards on other interrelated industry sectors (Heinrich 2014) and as a crossover study to explore the influences of network structures on the adoption of de facto standards (Techatassanasoontorn & Suo 2011).…”

“…The connection between complex systems with attractors and network topologies has been seen, for instance, when comparing diffusion models of innovations to a model of complex adaptive systems (Rogers et al 2005), which can enhance our understanding of system use over and above predictors from individual-level adoption research (Sykes, Venkatesh & Gosain 2009). Such considerations have been applied, for instance, to study influencing in de facto standardization (Techatassanasoontorn & Suo 2011). In general, studies related to weak ties in the flow of information (Granovetter 1973) implicate that diffusion of innovations is different in differently organized value systems.…”

Usage of Agent-Based Modeling and Simulation in Marketing

“…Reference [53] is about pricing proposed an agent-based computational model of the B2C electronic auction marketplace. In Reference [54], authors examined the influence of local network effects, switching costs, pricing, functionality enhancement strategies, and user network structures to understand de facto standardization through user standards adoption. In Reference [55], author covered the pricing of financial innovations.…”

“…Over the years the usage of agent-based modeling in marketing increases. [11], [20], [24], [33], [36], [37], [38] 2011 9 17 [8], [15], [18], [29], [41], [45], [52], [54], [56] 2012 7 13 [9], [13], [39], [42], [47], [55], [ In 2008 the only one paper was published so this year can be an outlier. The most number of papers were published in the years of 2011 and 2012.…”