Information technology (IT) acceptance research has yielded many competing models, each with different sets of acceptance determinants. In this paper, we (1) review user acceptance literature and discuss eight prominent models, (2) empirically compare the eight models and their extensions, (3) formulate a unified model that integrates elements across the eight models, and (4) empirically validate the unified model. The eight models reviewed are the theory of reasoned action, the technology acceptance model, the motivational model, the theory of planned behavior, a model combining the technology acceptance model and the theory of planned behavior, the model of PC utilization, the innovation diffusion theory, and the social cognitive theory. Using data from four organizations over a six-month period with three points of measurement, the eight models explained between 17 percent and 53 percent of the variance in user intentions to use information technology. Next, a unified model, called the Unified Theory of Acceptance and Use of Technology (UTAUT), was formulated, with four core determinants of intention and usage, and up to four moderators of key relationships. UTAUT was then tested using the original data and found to outperform the eight individual models (adjusted R 2 of 69 percent). UTAUT was then confirmed with data from two new organizations with similar

Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of “word of mouth ” in the promotion of new products. Recently, motivated by the design of viral marketing strategies, Domingos and Richardson posed a fundamental algorithmic problem for such social network processes: if we can try to convince a subset of individuals to adopt a new product or innovation, and the goal is to trigger a large cascade of further adoptions, which set of individuals should we target? We consider this problem in several of the most widely studied models in social network analysis. The optimization problem of selecting the most influential nodes is NP-hard here, and we provide the first provable approximation guarantees for efficient algorithms. Using an analysis framework based on submodular functions, we show that a natural greedy strategy obtains a solution that is provably within 63 % of optimal for several classes of models; our framework suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks. We also provide computational experiments on large collaboration networks, showing that in addition to their provable guarantees, our approximation algorithms significantly out-perform nodeselection heuristics based on the well-studied notions of degree centrality and distance centrality from the field of social networks.

This paper presents the findings of an empirical study into two organizations' experiences with the adoption and use of CASE tools over time. Using a grounded theory research approach, the study characterizes the organizations' experiences in terms of processes of incremental or radical organizational change. These findings are used to develop a theoretical framework for conceptualizing the organizational issues around the adoption and use of these tools--issues that have been largely missing from contemporary discussions of CASE tools. The paper thus has important implications for research and practice. Specifically, the framework and findings suggest that in order to account for the experiences and outcomes associated with CASE tools, research- ers should consider the social context of systems development, the intentions and actions of key players, and the implementation process followed by the organization. Similarly, the paper suggests that practitioners will be better able to manage their organizations' experiences with CASE tools if they understand that such implementations involve a process of organizational change over time and not merely the installation of a new technology.

Acknowledgements: The development of NeBIC theory has benefited greatly from the detailed guidance of the editor, associate editor, and reviewers. I also wish to thank research associate Michael Williams and Arvin Sayam for their valuable assistance and healthy debate in maturing the ideas presented here. NeBIC: A Dynamic Capabilities Theory for Assessing Net-enablement We propose the Net-enabled Business Innovation Cycle as an applied dynamic capabilities theory for measuring, predicting, and understanding a firm’s ability to create customer value through the business use of digital networks. The theory incorporates both a variance and process view of netenabled business innovation. It identifies four sequenced constructs: Choosing new IT, Matching with Economic Opportunities, Executing Business Innovation for Growth, and Assessing Customer Value, along with the processes and events that inter-relate them as a cycle. The sequence of these theorized relationships for net-enablement asserts that choosing IT precedes rather than aligns with corporate strategy. The theory offers a logically consistent and falsifiable basis for grounding research programs on metrics of net-enabled business innovation. NeBIC Page 1 1

In most companies two factors play a crucial role: managing the knowledge that is necessary for doing business and managing the hardware and software infrastructure that supports the business processes. Usually, business processes and infrastructure are not optimally aligned. We investigate how principles from knowledge management can be applied to enable the creation, consolidation, conservation and continuous actualization of knowledge about valuable software systems ("software assets") that are part of the infrastructure. Our point of departure is a generic framework for knowledge creation proposed by Von Krogh, Ichijo and Nonaka. We investigate the explicit and tacit knowledge about software assets that may exist in an organization and specialize the framework to obtain a strategy for creating new knowledge about these software assets. By applying this strategy, one can optimize the quality and the flexibility of the software assets while reducing costs.

Social capital (networks, values, trust and commitment) facilitates learning and change in communities by ‘oiling ’ the processes of accessing and acquiring new knowledge, skills and values. The literature on social capital argues that high levels of social capital lead to strong economic performance (Putnam, 1993). Development and maintenance of a strong economy requires an ability and willingness to adapt in the light of external pressures and opportunities. This in turn requires businesses to make appropriate and successful changes to their practices. This paper considers how social capital is used by a group of small businesses as they make changes which improve business outcomes. The paper examines a learning community of farm businesses (a communityof-practice rather than a geographic community). It traces the way in which the community deliberately structures its activities so as to develop and accumulate social capital. The paper also examines the outcomes of the use of social capital in learning processes of members. Much of the literature on social capital focuses on

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The extent of organizational innovation with IT, an important construct in the IT innovation literature, has been measured in many different ways. Some measures are more narrowly focused while others aggregate innovative behaviors across a set of innovations or across stages in the assimilation lifecycle within organizations. There appear to be some significant tradeoffs involving aggregation. More aggregated measures can be more robust and generalizable and can promote stronger predictive validity, while less aggregated measures allow more context-specific investigations and can preserve clearer theoretical interpretations. This article begins with a conceptual analysis that identifies the circumstances when these tradeoffs are most likely to favor aggregated measures. It is found that aggregation should be favorable when: (1) the researcher's interest is in general innovation or a model that generalizes to a class of innovations, (2) antecedents have effects in the same direction in all assimilation stages, (3) characteristics of organizations can be treated as constant across the innovations in the study, (4) characteristics of innovations can not be treated as constant across organizations in the study, (5) the set of innovations being aggregated includes substitutes or moderate complements, and (6) sources of noise in the measurement of innovation may be present. The article then presents an empirical study using data on the adoption of software process technologies by 608 US based corporations. This study—which had circumstances quite favorable to aggregation—found that aggregating across three innovations within a technology class more than doubled the variance explained compared to single innovation models. Aggregating across assimilation stages had a slight positive effect on predictive validity. Taken together, these results provide initial confirmation of the conclusions from the conceptual analysis regarding the circumstances favoring aggregation.

Virtual communities have been the focus of research since the beginning of the Internet. A more recent phenomenon is the hybrid networked community: a physical community extended by a network infrastructure, seeking to enhance existing social interactions, storage and dissemination of knowledge using both online and offline channels of communication. This paper considers one specific form: grassroots initiated networked communities. These are communities of locality that have developed their own Internet and /or intranet infrastructure with minimal external support. They believe that establishing such a network will enhance communication and 'sense of community ' within their geographically defined boundaries. These initiatives may offer a viable and sustainable method for overcoming multiple digital inequalities, support the development of social capital, and provide insights into the impact of near-ubiquitous social computing. We review a case study of five such projects in the UK, identifying characteristics, methods of function, and long term aims. An outline of this work is presented and indications of likely future developments offered. 1.

One of the recent phenomena information systems (IS) practitioners are currently facing in their continuous process of adopting new technology is the utilization of Extensible Markup Language (XML). In this paper we propose an XML adoption framework, a corresponding adoption space model, and a probit model of technology diffusion to examine the decision of adopting XML-based applications in the context of electronic business. First, an XML adoption framework is proposed. The framework helps companies examine their current status in the electronic business environment from the perspective of three electronic business domains, namely enterprise intranets, value-chain extranets, and the global Internet. This framework also provides guidelines for companies seeking to understand the potential benefits of adopting XML technology, and then further suggests the appropriate path and proper applications. Second, we propose an XML adoption space model. Considering its current status of IT applications, a company can utilize this model to measure the efforts/costs that will be incurred by developing XML-enabled IT applications. Third, we use a probit model of technology diffusion to explore the feasibility of a company's adoption of XML technology. This probit model considers a company's specific characteristics and evaluates benefits and efforts/costs of its XML adoption decision. Keywords: E-Business, Decision Model, Framework, XML 1.