In this introduction to the special issue on the role of information and communication technologies (ICT) in socioeconomic development, we provide a conceptual framework that considers four dimensions that impact socioeconomic development: policy, business, technology, and society. This framework, which is systematically constructed from reviewing several earlier frameworks but more general in focus, is intended to provide context for the eight papers in this special issue, and also guidance for future-related research.

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PurposeThe purpose of this paper is to provide a comprehensive literature review of enterprise content management (ECM) research, a conceptual framework of areas of concern regarding ECM, and an agenda for future ECM research, based on the review and conceptual framework.Design/methodology/approachTo gain an understanding of the ECM literature, a structured research approach is adopted, consisting of two phases. The first phase consists of identifying the relevant ECM research papers. In the second phase, the analysis phase, the current ECM research is categorized based on three structural pillars: system component dimensions, system lifecycle, and strategic managerial aspects.FindingsAfter a review and classification of 91 ECM publications, it is found that ECM involves several sophisticated and interacting technical, social, organizational, and business aspects. The current ECM literature can be grouped around three main pillars: the first pillar consists of the four ECM component dimensions (tools, strategy, process, and people). The second pillar is the enterprise system lifecycle (adoption, acquisition, evolution, and evaluation). The final pillar is the strategic managerial aspect (change management, and management commitment). Based on the review and a proposed conceptual framework, an agenda for future research around the aforementioned three pillars is suggested.Originality/valueThere is a lack of ECM meta‐analysis research that explains the current state of the field. This paper contributes to information systems research by describing and classifying the published literature in ECM and by pointing out the gaps where further research is most needed. Furthermore, the paper provides a framework that may provide a conceptual structure for future studies.

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An important problem in financial investment is the classification of bonds based on the likelihood that the issuing company may default on the promised payments. Much effort has been invested into simulating the bond rating process using statistical tools. A weakness of these tools is the requirement of statistical assumptions which may not be appropriate for the bond rating problem. In this paper we present results of a study comparing an artificial neural network system, a rule-based expert system and statistical techniques applied to the bond rating problem. The bond rating process is simulated by using published financial data.