Knowledge that Transforms

Online spaces that enable shared public interpersonal communications are of significant social, organizational, and economic importance. In this paper, a theoretical model and associated unobtrusive method are proposed for researching the relationship between online spaces and the behavior they host. The model focuses on the collective impact that individual information-overload coping strategies have on the dynamics of open, interactive public online group discourse. Empirical research was undertaken to assess the validity of both the method and the model, based on the analysis of over 2.65 million postings to 600 Usenet newsgroups over a 6-month period. Our findings support the assertion that individual strategies for coping with “information overload” have an observable impact on large-scale online group discourse. Evidence was found for the hypotheses that: (1) users are more likely to respond to simpler messages in overloaded mass interaction; (2) users are more likely to end active participation as the overloading of mass interaction increases; and (3) users are more likely to generate simpler responses as the overloading of mass interaction grows. The theoretical model outlined offers insight into aspects of computer-mediated communication tool usability, technology design, and provides a road map for future empirical research.

The decision processes surrounding investments in innovative information technology (IT) platforms are complicated by uncertainty about expected payoffs and irreversibilities in the costs of implementation. When uncertainty and irreversibility are high, concepts from real options should be used to properly structure the evaluation and management of investment opportunities, and thereby capture the value of managerial flexibility. However, while innovation researchers have posited that option value can influence the motivations of early adopters, and options researchers have identified emerging IT as a promising area for application of options valuation techniques, there has yet to be a systematic theoretical integration of work on IT innovation and real options. This paper seeks to fill this gap by developing a model of the determinants of option value associated with investments in innovative IT platforms. In so doing, the model addresses a central question in the innovation field: When should a firm take a lead role in innovation with emerging technologies? The analysis begins with an explanation of real options analysis and how it differs from conventional approaches for evaluating new technologies. Then a set of 12 factors—drawn from 4 complementary perspectives on organizational innovation (technology strategy, organizational learning, innovation bandwagons, and technology adaptation)—is synthesized into a model of the option value of IT platform investments. Rationales are provided to explain the direct effects of these factors on option value, and selected interactions among the factors are also considered. Finally, the implications of the model are presented in three areas: predicting IT platform initiation and adoption, valuing IT platform options, and managing IT platform implementation.

The lack of consumer confidence in information privacy has been identified as a major problem hampering the growth of e-commerce. Despite the importance of understanding the nature of online consumers' concerns for information privacy, this topic has received little attention in the information systems community. To fill the gap in the literature, this article focuses on three distinct, yet closely related, issues. First, drawing on social contract theory, we offer a theoretical framework on the dimensionality of Internet users' information privacy concerns (IUIPC). Second, we attempt to operationalize the multidimensional notion of IUIPC using a second-order construct, and we develop a scale for it. Third, we propose and test a causal model on the relationship between IUIPC and behavioral intention toward releasing personal information at the request of a marketer. We conducted two separate field surveys and collected data from 742 household respondents in one-on-one, face-to-face interviews. The results of this study indicate that the second-order IUIPC factor, which consists of three first-order dimensions—namely, collection, control, and awareness—exhibited desirable psychometric properties in the context of online privacy. In addition, we found that the causal model centering on IUIPC fits the data satisfactorily and explains a large amount of variance in behavioral intention, suggesting that the proposed model will serve as a useful tool for analyzing online consumers' reactions to various privacy threats on the Internet.

Internet fraud has been on the rise in online consumer-to-consumer (C2C) auction markets, posing serious challenges to people's trust in electronic markets. Among various remedies to promote trust and reduce trader's risk, online escrow service has been proposed as a trusted third party to protect online transactions from Internet fraud. However, whether an escrow service constitutes a viable business model for a trusted third party to effectively block Internet fraud remains an open question. This research proposes a dynamic game model for online traders and a profit maximization model for the escrow service provider. Through the investigation of the optimal strategies of online traders, we explore the relationships among traders' decision making, escrow service fee rates, and adoption rates. We reveal the demand for escrow services and establish the optimal pricing rule for the escrow service provider. A numerical study based on the theoretical analysis is conducted to provide detailed guidelines of the model application for an escrow service provider and to explore if the escrow service is a viable business model in C2C auction markets.

Institution-based trust is a buyer’s perception that effective third-party institutional mechanisms are in place to facilitate transaction success. This paper integrates sociological and economic theories about institution-based trust to propose that the perceived effectiveness of three IT-enabled institutional mechanisms–specifically feedback mechanisms, third-party escrow services, and credit card guarantees–engender buyer trust in the community of online auction sellers. Trust in the marketplace intermediary that provides the overarching institutional context also builds buyer’s trust in the community of sellers. In addition, buyers’ trust in the community of sellers (as a group) facilitates online transactions by reducing perceived risk. Data collected from 274 buyers in Amazon’s online auction marketplace provide support for the proposed structural model. Longitudinal data collected a year later show that transaction intentions are correlated with actual and self-reported buyer behavior. The study shows that the perceived effectiveness of institutional mechanisms encompasses both “weak” (market-driven) and “strong” (legally binding) mechanisms. These mechanisms engender trust, not only in a few reputable sellers, but also in the entire community of sellers, which contributes to an effective online marketplace. The results thus help explain why, despite the inherent uncertainty that arises when buyers and sellers are separated in time and in space, online marketplaces are proliferating. Implications for theory are discussed, and suggestions for future research on improving IT-enabled trust-building mechanisms are suggested.