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Quotes recent (1994) literature suggesting that workers receive more training and support in their local work area than from a centralized management information systems (MIS) group. Suggests that there is therefore little knowledge about how users learn the computing skills necessary for them to achieve their tasks. Explores the issues. Presents four case studies, two having a central MIS training and support functions and two having none. Observes that in four work groups members depended on locally emerging arrangements for training and support.

Cloud computing originated in central data centers that are connected to the backbone of the Internet. The network transport to and from a distant data center incurs long latencies that hinder modern low-latency applications. In order to flexibly support the computing demands of users, cloud computing is evolving toward a continuum of cloud computing resources that are distributed between the end users and a distant data center. The purpose of this review paper is to concisely summarize the state-of-the-art in the evolving cloud computing field and to outline research imperatives.

The authors identify two main dimensions (or axes) of development of cloud computing: the trend toward flexibility of scaling computing resources, which the authors denote as Flex-Cloud, and the trend toward ubiquitous cloud computing, which the authors denote as Ubi-Cloud. Along these two axes of Flex-Cloud and Ubi-Cloud, the authors review the existing research and development and identify pressing open problems.

The authors find that extensive research and development efforts have addressed some Ubi-Cloud and Flex-Cloud challenges resulting in exciting advances to date. However, a wide array of research challenges remains open, thus providing a fertile field for future research and development.

This review paper is the first to define the concept of the Ubi-Flex-Cloud as the two-dimensional research and design space for cloud computing research and development. The Ubi-Flex-Cloud concept can serve as a foundation and reference framework for planning and positioning future cloud computing research and development efforts.

Training is a critical factor in enabling users to make effective use of their computers. A variety of training methods have been proposed in the literature. These training methods will be considered within the framework of procedural and conceptual training, with special reference to their application in the training of novice end users in the use of applications software. The impact of learning styles and other user characteristics on the selection of training methods for use in this area is discussed. Finally, a current research programme to explore the effectiveness of training methods for novice end users is briefly described.

Selects two of the recent developments in information technology, and those expected in the near future, which suggest major advances in both human‐computer and computer‐computer communications. Explores the internal control and auditing issues which surround two such technologies – end‐user computing and electronic data interchange (one from each of these categories respectively). Notes the growth of end‐user computing, together with the need to balance control against the trust and creativity which it fosters. This implies the need for a less instrumental and more organizational approach to audit and control. Electronic data interchange provides the opportunity for the further development of paper‐minimal systems and the resulting legal, as well as audit and control, problems are discussed. Concludes by suggesting that there may be a need for a review of audit methodologies which, in principle, remain focused on the large bureaucratic paper‐based systems of the early 1950s.

The purpose of this paper is to provide empirical evidence of the relationship between end-user computing satisfaction (EUCS) and radical innovation, using organizational learning as an explanatory variable.

An empirical study was conducted in a population of 402 Spanish companies. A sample of 251 valid questionnaires was obtained. Structural equations were used to validate the proposed hypotheses.

Organizational learning capability fully mediates the relationship between EUCS and radical innovation.

The sample of companies is heterogeneous in terms of size, sector, age and market share. The study uses single informants.

Results highlight the need to implement adequate information systems to promote radical innovation. In addition, it is necessary to facilitate organizational contexts that encourage dialogue, experimentation, risk-taking, participative decision-making and openness to the external environment.

This research contributes to the study of alternative antecedents of radical innovation by highlighting the importance of EUCS.

Big data has raised challenges and opportunities for business, the information technology (IT) industry and research communities. Nowadays, small and medium-sized enterprises (SME) are dealing with big data using their limited resources. The purpose of this paper is to describe the synergistic relationship between big data and knowledge management (KM), analyze the challenges and IT solutions of big data for SME and derives a KM model of big data for SME based on the collected real-world business cases.

The study collects eight well-documented cases of successful big data analytics in SME and conducts a qualitative data analysis of these cases in the context of KM. The qualitative data analysis of the multiple cases reveals a KM model of big data for SME.

The proposed model portrays the synergistic relationship between big data and KM. It indicates that strategic use of data, knowledge guided big data project planning, IT solutions for SME and new knowledge products are the major constructs of KM of big data for SME. These constructs form a loop through the causal relationships between them.

The number of cases used for the derivation of the KM model is not large. The coding of these qualitative data could involve biases and errors. Consequently, the conceptual KM model proposed in this paper is subject to further verification and validation.

The proposed model can guide SME to exploit big data for business by placing emphasis on KM instead of sophisticated IT techniques or the magnitude of data.

The study contributes to the KM literature by developing a theoretical model of KM of big data for SME based on underlying dimensions of strategic use of data, knowledge guided big data project planning, IT solutions for SME and new knowledge products.

The information system downsizing trend has been on the increase during the last five years because of extreme pressures brought about by the slow economy and intense global competition. The major benefit of downsizing is cost saving or cost avoidance, though reports of downsizing show that not all companies have achieved projected cost savings; while some have gained the savings predicted, others have cut short their efforts to downsize, the project ending in total disenchantment. Reports on a survey which uses companies, ranked as the top 100 information users. These “best users” were selected as the basis for determining: the motivation for downsizing; how cost effective downsizing is; and the degree of satisfaction after downsizing was attempted. Results indicate that cost saving and effective information technology utilization are the principal motives for downsizing. Less than 50 per cent of respondents indicated cost‐reduction due to downsizing, while the rest indicated otherwise or were not sure. Discusses downsizing strategies and identifies research challenges.

Some of you will remember a search system called Leadermart which was developed at Lehigh University in the early 1970s under the direction of Don Hillman. Don viewed Leadermart as one of the few early systems designed for end users rather than information specialists. He attributed its lack of acceptance by information specialists to the marriage of librarians to Boolean searching and their unwillingness to try anything new. Leadermart, however, was not particularly popular with end users either. In my opinion Leadermart's lack of acceptance was primarily due to the quality of results it produced. Also this is important in evaluating current ‘expert systems’ approaches to searching. With Leadermart, if you didn't get good results you had no way of knowing how to change your request to improve the results. Some people pursuing the end user today feel simpler interfaces of the Leadermart type are the single answer to capturing this vast market. In what follows I hope to show that the problem is substantially more complex than suggested by this simple solution.

The MIS manager is offered a framework to help in the selection of methodologies for projects; the choice of analyst may be crucial.