Academic researchers access commercial web sites to collect research data. This research practice is likely to increase. Is this appropriate? Is this legal? Such commercial web sites are maintained to achieve business objectives; research access uses site resources for other purposes. Web site administrators may, therefore, deem academic data collection inappropriate. Is there a process to make research access more open and acceptable to web site owners and administrators? These are significant issues. This article clarifies the problems and suggests possible approaches to handle the issues with sensitivity and openness. Research access to commercial web sites may be manual (using a standard web browser) or automated (using automated data collection agents). These approaches have different effects on web sites. Researchers using manual access tend to make a limited number of page requests because manual access is costly to perform. Researchers using automated access methods can request large numbers of pages at a low cost. Therefore, web site administrators tend to view manual access and automated access very differently. Because of the number of accesses and the nonbusiness purpose, automated research requests for data are sometimes blocked by site administration using a variety of means (both technological and legal). This paper details the pertinent legal issues including trespass, copyright violation, and breech of contract. It also explains the nature of express and implied consent by site administration for research access. Based on the issues presented, guidelines for researchers are proposed to reduce objections to research activities, to facilitate communication with web site administration, and to achieve express or implied consent. These include notification to web site administration of intended automated research activity, description of the research project posted as a web page, and clear identification of automated requests for web pages. In order to encourage good research practices with respect to automated data collection, suggestions are made with respect to disclosing methods used in research papers and for self regulation by academic associations
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[sup 2] of 69 percent). UTAUT was then confirmed with data from two new organizations with similar results (adjusted R[sup 2] of 70 percent). UTAUT thus provides a useful tool for managers needing to assess the likelihood of success for new technology introductions and helps them understand the drivers of acceptance in order to proactively design interventions (including training, marketing, etc.) targeted at populations of users that may be less inclined to adopt and use new systems. The paper also makes several recommendations for future research including developing a deeper understanding of the dynamic influences studied here, refining measurement of the core constructs used in UTAUT, and understanding the organizational outcomes associated with new technology use.
This study investigates the media selection behavior of directors (executives) and managers through the use of multiple methods. The findings indicate the directors were more 'self' oriented in their media choices, more often choosing media based on access/ease of use criteria, while the managers were more 'other' oriented, more often making choices based on media richness/social presence criteria. These differences have implications in the interpretation of communication from directors and managers to the rest of the organization and suggest a model for understanding the use of 'rich' and 'lean' communication media. The literature review of the study makes a major contribution by fitting together the multiple theories applied to the area and showing how conflicting results from all the established media selection theories make sense in different circumstances.
Increases in employee autonomy and the formation of teams often result from reengineering and process innovation efforts, as do moves to "downsize" or "flatten" organizations. Information systems departments have not been insulated from these trends. In spite of the rising interest in these initiatives, little is known about their impact on the systems development process. Past research in blue-collar contexts suggests that teams produce improvements in performance, while anecdotal evidence in the IS industry suggests that such improvements may never materialize. This paper reports on research conducted with 231 IS professionals from 27 systems development teams across 13 organizations. The results indicate that, while autonomy may lead to increased levels of satisfaction and motivation, the level of team development and an organization's learning capacity may be more important in achieving improved work outcomes.
There is strong evidence that data items stored in organizational databases have a significant rate of errors. If undetected in uses those errors in stored data may significantly affect business outcomes. Published research suggests that users of information systems tend to be ineffective in detecting data errors. However, in this paper it is argued that, rather than accepting poor human error detection performance, MIS researchers need to develop better theories of human error detection and to improve their understanding of the conditions for improving performance. This paper applies several theory bases (primarily signal detection theory but also a theory of individual task performance, theories of effort and accuracy in decision making, and theories of goals and incentives) to develop a set of propositions about successful human error detection. These propositions are tested in a laboratory setting. The results present a strong challenge to earlier assertions that humans are poor detectors of data errors. The findings of the two laboratory experiments show that explicit error detection goals and incentives can modify error detection performance. These findings provide an improved understanding of conditions under which users detect data errors. They indicate it is possible to influence detection behavior in organizational settings through managerial directives, training, and incentives.
This paper provides an overview report of the first joint curriculum development effort for undergraduate programs in information systems. The curriculum recommendations am a collaborative effort of the following organizations: ACM, AIS, DPMA, and ICIS. After a summary of the objectives and rationale for the curriculum, the curriculum model is described. Input and output attributes of graduates are delineated. Resource requirements for effective IS programs are then identified. Lastly, there is a proposal for maintaining currency of the curriculum through electronic media.