ABSTRACT: This paper aims to predict consumer acceptance of e-commerce by proposing a set of key drivers for engaging consumers in on-line transactions. The primary constructs for capturing consumer acceptance of e-commerce are intention to transact and on-line transaction behavior. Following the theory of reasoned action (TRA) as applied to a technology-driven environment, technology acceptance model (TAM) variables (perceived usefulness and ease of use) are posited as key drivers of e-commerce acceptance. The practical utility of TAM stems from the fact that e-commerce is technology-driven. The proposed model integrates trust and perceived risk, which are incorporated given the implicit uncertainty of the e-commerce environment. The proposed integration of the hypothesized independent variables is justified by placing all the variables under the nomological TRA structure and proposing their interrelationships. The resulting research model is tested using data from two empirical studies. The first, exploratory study comprises three experiential scenarios with 103 students. The second, confirmatory study uses a sample of 155 on-line consumers. Both studies strongly support the e-commerce acceptance model by validating the proposed hypotheses. The paper discusses the implications for e-commerce theory, research, and practice, and makes several suggestions for future research.

Despite the inherent risk arising from separating buyers and sellers, networked online marketplaces are proliferating. We describe how online auction marketplaces take advantage of institutional structures to build buyer trust in auction sellers, mitigate risk, increase satisfaction, and promote transaction intentions. It is hypothesized, based on institutional trust (Zucker 1986), that buyer trust in auction sellers can be increased, beyond past experience with sellers, through structural assurances, such as buyer-driven certification, auction house escrows, and credit card guarantees. We examined buyer transaction intentions, mediated by trusting beliefs, risk reduction, and satisfaction. The model is tested with 274 buyers in Amazon’s online auction marketplace. The results support the hypotheses, highlighting the importance of institution-based trust in online networks. Implications are discussed. Keywords: Institution-based trust, online auctions, institutional structures, certification, escrows, third-party guarantees

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The continued growth of the World Wide Web makes the retrieval of relevant information for a user’s query increasingly difficult. Current search engines provide the user with many web pages, but varying levels of relevancy. In response, the Semantic Web has been proposed to retrieve and use more semantic information from the web. Our prior research has developed a Semantic Retrieval System to automate the processing of a user’s query while taking into account the query’s context. The system uses WordNet and the DARPA Agent Markup Language (DAML) ontologies to act as surrogates for understanding the context of terms in a user’s query. Like other applications that use ontologies, our system relies on using ‘good’ ontologies. This research draws upon semiotic theory to develop a suite of metrics that assess the syntactic, semantic, pragmatic, and social aspects of ontology quality. We operationalize the metrics and implement them in a prototype tool called the “Ontology Auditor. ” An initial validation of the Ontology Auditor on the DAML library of domain ontologies indicates that the metrics are feasible and highlight the wide variations in quality among ontologies in the library.

ACKNOWLEDGEMENTS: We thank the senior editor on the manuscript, V. Sambamurthy, and the anonymous associate editor and reviewers for their many insightful suggestions on earlier

One result of the increasing sophistication and complexity of MIS theory and research is the number of studies hypothesizing and testing for 1 V. Sambamurthy was the accepting senior editor for this paper. Carte & Russell/Moderation Errors RESEARCH ESSAY moderation effects. A review of the MIS and broader management literatures suggests researchers investigating moderated relationships often commit one or more errors falling into three broad categories: inappropriate use or interpretation of statistics, misalignment of research design with phenomena of interest, and measurement or scaling issues. Examples of nine common errors are presented. Commission of these errors is expected to yield literatures characterized by mixed results at best, and thoroughly erroneous results at worse. Procedures representing examples of best practice and reporting guidelines are provided to help MIS investigators avoid or minimize these errors.

The Technology Acceptance Model (TAM) predicts whether users will ultimately use software applications based upon causal relationships among belief and attitudinal constructs that influence usage behavior. Electronic mail, or email, is a collaborative technology available to virtually all members of an organization, and typically, there are alternative email applications available for use. This study applies TAM to assess the user acceptance and voluntary usage of a particular email application, cc:mail, in two different organizations. The results largely validate TAM, although the findings suggest that certain external variables, namely length of time since first use, and level of education, directly affect email usage behavior apart from their influence as mediated through the perceived usefulness (PU) and perceived ease of use (PEOU) constructs. 1.

E-government is increasingly been used for government administrative reform. In fact, spending in e-government initiatives continues to rise and, among these projects, Internet-based applications are increasingly important. Using a nested research design, this study explores the complex relationships among the relative success of state websites and certain organizational, institutional, and contextual factors 1. Based on a PLS analysis involving all 50 states and two rich case studies, this paper identifies several generalizable relationships and case-specific differences. For instance, organizational factors such as size of the IT organization, budget structure, IT training, in-house development, outsourcing, and marketing strategy were found to significantly affect the functionality of state websites. However, some of these factors play different roles in different contexts, their relevance is affected by state-specific environmental conditions, and the reasons why they are important also differ from setting to setting.

This study provides insights on the trust-related factors that influence consumer intentions to use online banking. Specifically, the study examines the relationships between trustworthiness, trust, distrust, and user intentions to use online banking services. Over 500 college students located across two different universities completed a survey designed to examine the effects of trustworthiness perceptions on trust and distrust, and the downstream influence of trust and distrust on intention to use. As hypothesized, results indicate that trust and distrust are distinct constructs, and that the established nomological network between trustworthiness, trust, and intention hold in the current context. Also supported is the new contention that trustworthiness is negatively related to distrust, and that distrust has a negative effect on intention to use. Finally, our hypothesis examining the relative contribution of trust and distrust on user intentions was not supported. In the context of this study, trust overwhelmed distrust.

Computer skills are key to organizational performance, and past research indicates that behavior modeling is a highly effective form of computer skill training.The present research develops and tests a new theoretical model of the underlying observational learning processes by which modeling-based training interventions influence computer task performance.Observational learning processes are represented as a second-order construct with four dimensions (attention, retention, production, and motivation).New measures for these dimensions were developed and shown to have strong psychometric properties.The proposed model controls for two pretraining individual differences (motivation to learn and self-efficacy) and specifies the relationships among three training outcomes (declarative knowledge, post-training self-efficacy, and task performance).The model was tested using PLS on data from an experiment (N = 95) on computer spreadsheet training.As hypothesized, observational learning processes significantly influenced training outcomes. A representative modeling-based training intervention (retention enhancement) significantly improved task performance through its specific effects on the retention processes dimension of observational learning.The new model provides a more complete theoretical account of the mechanisms by which modeling-based interventions affect training outcomes, which should enable future research to systematically evaluate the effectiveness of a wide range of modeling-based training interventions.Further, the new instruments can be used by practitioners to refine ongoing training programs.