Peter B. Seddon

A Respecification and Extension of the DeLone and McLean Model of IS Success

DeLone and McLeans DeLone, W. H., E. R. McLean. 1992. Information systems success: The quest for the dependent variable. Inform. Systems Res.31 60--95. comprehensive review of different information system success measures concludes with a model of “temporal and causal” interdependencies between their six categories of IS Success. After working with this model for some years, it has become apparent that the inclusion of both variance and process interpretations in their model leads to so many potentially confusing meanings that the value of the model is diminished. Because of the confusion that this overloading of meanings can cause, this paper presents and justifies a respecified and slightly extended version of DeLone and McLeans model.

Assessing and managing the benefits of enterprise systems: the business manager's perspective

. This paper focuses on the benefits that organizations may achieve from their investment in enterprise systems (ES). It proposes an ES benefit framework for summarizing benefits in the years after ES implementation. Based on an analysis of the features of enterprise systems, on the literature on information technology (IT) value, on data from 233 enterprise systems vendor-reported stories published on the Web and on interviews with managers of 34 organizations using ES, the framework provides a detailed list of benefits that have reportedly been acquired through ES implementation. This list of benefits is consolidated into five benefits dimensions: operational, managerial, strategic, IT infrastructure and organizational, and illustrated using perceived net benefit flow (PNBF) graphs. In a detailed example, the paper shows how the framework has been applied to the identification of benefits in a longitudinal case study of four organizations.

Dimensions of information systems success

The value added by an organization’s IT assets is a critical concern to both research and practice. Not surprisingly, a large number of IS effectiveness measures can be found in the IS literature. What is not clear in the literature is what measures are appropriate in a particular context. In this paper we propose a two-dimensional matrix for classifying IS Effectiveness measures. The first dimension is the type of system studied. The second dimension is the stakeholder in whose interests the system is being evaluated. The matrix was tested by using it to classify IS effectiveness measures from 186 empirical papers in three major IS journals for the last nine years. The results indicate that the classifications are meaningful. Hence, the IS Effectiveness Matrix provides a useful guide for conceptualizing effectiveness measurement in IS research, and for choosing appropriate measures, both for research and practice.

A multi-project model of key factors affecting organizational benefits from enterprise systems

This paper develops a long-term, multi-project model of factors affecting organizational benefits from enterprise systems (ES), then reports a preliminary test of the model. In the shorter-term half of the model, it is hypothesized that once a system has gone live, two factors, namely functional fit and overcoming organizational inertia, drive organizational benefits flowing from each major ES improvement project. The importance of these factors may vary from project to project. In the long-term half of the model, it is hypothesized that four additional factors, namely integration, process optimization, improved access to information, and on-going major ES business improvement projects, drive organizational benefits from ES over the long term. Preliminary tests of the model were conducted using data from 126 customer presentations from SAPs 2003 and 2005 Sapphire U.S. conferences. All six factors were found to be important in explaining variance in organizational benefits from enterprise systems from the perspective of senior management.

Measuring organizational IS effectiveness: an overview and update of senior management perspectives

This paper reports the views of 80 senior IT managers about IT evaluation approaches, and the benefits that IT provides for their organizations. Their views were obtained through a survey mailed to medium to large organizations in both Europe and the US. The survey sought answers to three questions: How does the senior IT managers organization assess the value of its (1) overall IT investment portfolio? (2) individual IT projects and applications? (3) IT function? Questions for the survey were based on a thorough review of prior research into IT evaluation. The paper provides a summary of that prior work and compares current findings to prior research. Consistent with prior research, the paper concludes that many firms do not conduct rigorous evaluations of all their IT investments, and offers a tentative explanation of why it might be rational to skip formal evaluations in some circumstances. It also posits five push factors to explain occasions when more lasting improvements in IT evaluation practice have occurred.

Having expectations of information systems benefits that match received benefits: does it really matter?

A study was conducted to examine the effect of implementing a new system on its users, specifically, the relationship between pre-implementation expectations and their perceived benefits based on post-implementation experience. Disconfirmation theory was used as the theoretical basis; this predicts that unrealistically high expectations will result in lower levels of perceived benefit than those associated with realistic expectations (i.e. where expectations match experience). Support was found for this prediction, refuting the predictions of dissonance theory. In addition to examining expectations of system use generally, six expectation categories were examined to identify the critical categories where managers should keep expectations from becoming unrealistically high. Significant relationships were found for three expectation categories: system usefulness, ease of use, and information quality. The results indicate that creating and maintaining realistic expectations of future system benefits really does matter.

How Does Enterprise Architecture Add Value to Organisations

Enterprise architecture (EA) is the definition and representation of a high-level view of an enterprises business processes and IT systems, their interrelationships, and the extent to which these processes and systems are shared by different parts of the enterprise. EA aims to define a suitable operating platform to support an organisations future goals and the roadmap for moving towards this vision. Despite significant practitioner interest in the domain, understanding the value of EA remains a challenge. Although many studies make EA benefit claims, the explanations of why and how EA leads to these benefits are fragmented, incomplete, and not grounded in theory. This article aims to address this knowledge gap by focusing on the question: How does EA lead to organisational benefits? Through a careful review of EA literature, the paper consolidates the fragmented knowledge on EA benefits and presents the EA Benefits Model (EABM). The EABM proposes that EA leads to organisational benefits through its impact on four benefit enablers: Organisational Alignment, Information Availability, Resource Portfolio Optimisation, and Resource Complementarity. The article concludes with a discussion of a number of potential avenues for future research, which could build on the findings of this study.

IT outsourcing configuration: Research into defining and designing outsourcing arrangements

Abstract In this paper, we introduce the concept of information technology outsourcing (ITO) ‘configuration’, defined as: a high-level description of the set of choices the organization makes in crafting its IT outsourcing portfolio. From research into 49 ITO arrangements studied over time, we identify seven attributes—Scope Grouping, Supplier Grouping, Financial Scale, Duration, Pricing, Resource Ownership, and Commercial Relationship—as key descriptors of an organizations ITO configuration. Seven further cases tested the relevance of the attributes. The contribution of this paper is its articulation of the concept of configuration as a taxonomy of ITO structural characteristics, the key attributes, and demonstration that configuration is an important concept for understanding, comparing, and managing ITO arrangements. In particular, the paper details the rationales for 31 different options in outsourcing, the risks and management issues emerging for each, and how these play out in different combinations in selected, illustrative case studies.

Testing the Technology-to-Performance Chain Model

Goodhue and Thompson proposed the technology-to-performance chain (TPC) model in 1995 to help end users and organizations understand and make more effective use of information technology. The TPC model combines insights from research on user attitudes as predictors of utilization and insights from research on task-technology fit as a predictor of performance. In this article, the TPC model was tested in two settings voluntary use and mandatory use. In both settings, strong support was found for the impact of task-technology fit on performance, as well as on attitudes and beliefs about use. Social norms also had a significant impact on utilization in the mandatory use setting. Beliefs about use only had a significant impact on utilization in the voluntary use setting. Overall, the results found support for the predictive power of the TPC model; however, the results show that the relationships among the constructs in the model will vary depending on if the users have a choice to use the system or not.

Towards the improved treatment of generalization of knowledge claims in IS research: drawing general conclusions from samples

This paper presents a framework for justifying generalization in information systems (IS) research. First, using evidence from an analysis of two leading IS journals, we show that the treatment of generalization in many empirical papers in leading IS research journals is unsatisfactory. Many quantitative studies need clearer definition of populations and more discussion of the extent to which ‘significant’ statistics and use of non-probability sampling affect support for their knowledge claims. Many qualitative studies need more discussion of boundary conditions for their sample-based general knowledge claims. Second, the proposed new framework is presented. It defines eight alternative logical pathways for justifying generalizations in IS research. Three key concepts underpinning the framework are the need for researcher judgment when making any claim about the likely truth of sample-based knowledge claims in other settings; the importance of sample representativeness and its assessment in terms of the knowledge claim of interest; and the desirability of integrating a studys general knowledge claims with those from prior research. Finally, we show how the framework may be applied by researchers and reviewers. Observing the pathways in the framework has potential to improve both research rigour and practical relevance for IS research.