Software as a Service (SaaS) delivers a bundle of applications and services through the Web. Its on-demand feature allows users to enjoy full scalability and to handle possible demand fluctuations at no risk. In recent years, SaaS has become an appealing alternative to purchasing, installing, and maintaining modifiable off-the-shelf (MOTS) software packages. We present a game-theoretical model to study the competitive dynamics between the SaaS provider, who charges a variable per-transaction fee, and the traditional MOTS provider. We characterize the equilibrium conditions under which the two coexist in a competitive market and those under which each provider will fail and exit the market. Decreasing the lack-of-fit (or the cross-application data integration) costs of SaaS results in four structural regimes in the market. These are MOTS Dominance ? Segmented Market ? Competitive Market ? SaaS Dominance. Based on our findings, we recommend distinct competitive strategies for each provider. We suggest that the SaaS provider should invest in reducing both its lack-of-fit costs and its per-transaction price so that it can offer increasing economies of scale. The MOTS provider, by contrast, should not resort to a price-cutting strategy; rather, it should enhance software functionality and features to deliver superior value. We further examine this problem from the software life-cycle perspective, with multiple stages over which users can depreciate the fixed costs of installing and customizing their MOTS solutions on site. We then present an analysis that characterizes the competitive outcomes when future technological developments could change the relative levels of the lack-of-fit costs. Specifically, we explain why the SaaS provider will always use a forward-looking pricing strategy: When lack-of-fit costs are expected to decrease (increase) in the future, the SaaS provider should reduce (increase) its current price. This is in contrast with the MOTS provider, who will use the forward-looking pricing strategy only when lack-of-fit costs are expected to increase. Surprisingly, when such costs are expected to decrease, the MOTS provider should ignore this expectation and use the same pricing strategy as in the benchmark with invariant lack-of-fit costs.
Really simple syndication (RSS) technology enables an alternative delivery mechanism for online content. Instead of waiting passively for users to pull online content out, websites can push it to potential users through RSS. This is expected to significantly affect user behavior, website profitability, and market equilibrium. This research uses an economic model to study the impact of RSS adoption and examine whether it increases a website's profit and competitive advantage. The findings are intriguing: they demonstrate that RSS can either increase or decrease website profit. In a competitive context, RSS adoption can actually be a disadvantage; in some cases, it hurts the adopter but benefits the competitor. Moreover, under certain conditions, the first mover will be worse off when the competitor mimics its adoption decision, which discourages the earlier adoption and thus creates an obstacle to using RSS. Derivation of the adoption equilibria in sequential and simultaneous games shows that multiple market outcomes may result. Finally, regardless of whether or not a website operator adopts RSS, it will still benefit by increasing user awareness of RSS technology, but only up to a certain level. Once this critical awareness level has been reached, websites will not gain by continuing to promote RSS to users. As a whole, these results show how technology adoption will have an impact on firm performance and market outcome, and illustrate the complexity of technology adoption strategy in a competitive setting. > >
Information technology (IT) innovations follow a diverse set of diffusion patterns. Early diffusion models explaining technology diffusion patterns assumed that there is a single homogeneous segment of potential adopters. It was later shown that a two-segment model considering two groups of adopters explains variations in diffusion patterns better than the existing one-segment models. While the two-segment model considers a group of adopters promoting adoption by exerting a positive influence on prospective adopters, it does not consider the members of society who aim to inhibit the adoption process by exerting a negative influence on prospective adopters. In fact, most IT innovations face opposition. Yet it is not clear how opposition affects the diffusion process. In this paper, we model the diffusion of an IT innovation through its target population with three types of actors: influentials, who are autonomous in adopting new technology and promote its adoption; opponents, who are opposed to the technology and inhibit its adoption; and imitators, who are information seekers, thus affected by both influentials and opponents. We show that opponents play a crucial role in determining the diffusion path of an innovation. The empirical tests using real as well as simulated data sets demonstrate the ability of our model to fit the data better and to identify the segments of adopters correctly.