Validation and Design Science Research in Information Systems

Validation within design science research in Information Systems (DSRIS) is much debated. The relationship of validation to artifact evaluation is still not clear. This chapter aims at elucidating several components of DSRIS in relation to validation. The role of theory and theorizing are an important starting point, because there is no agreement as to what types of theory should be produced. Moreover, if there is a theoretical contribution, then there needs to be clear guidance as to how the designed artifact and its evaluation are related to the theory and its validation. The epistemological underpinnings of DSRIS are also open to different alternatives, including positivism, interpretivism, and pragmatism, which affect the way that the validation strategy is conceived, and later on, accepted or rejected. The type of reasoning guiding a DSRIS endeavor, whether deductive, inductive, or abductive, should also be considered as it determines the fundamental logic behind any research validation. Once those choices are in place, artifact evaluation may be carried out, depending on the type of artifact and the type of technique available. Finally, the theoretical contribution may be validated from a formative (process-oriented) or summative (product-oriented) perspective.

A Practical Approach to Theory Structuring and Analysis

A large proportion of students who enroll for postgraduate degrees never finish their studies, with non-completion rates yielding 30% for a sample size of 2000 students. A number of empirical studies have been conducted indicating the possible factors for the non-completion rate. This chapter briefly highlights such factors and proposes a possible solution to increase the number of successful studies using relevant philosophies and problem-solving to build insight in determining IS/IT solutions and innovations. A research methodology is suggested to enable data capturing aligned to research objectives and organise sub-problem solving effectively. The process of finding information, determining if it is relevant, and then relating it to existing keywords and topics can be facilitated by using a spreadsheet as a data generation method. The outcome may lead to a research proposal and study to investigate the problem identified, search for possible solutions, and prove/disprove the validity of the suggested solutions.

Postmodernism, Interpretivism, and Formal Ontologies

This chapter investigates the relationship between postmodernism, interpretivism, and formal ontologies, which are widely used in Information Systems (IS). Interpretivism has many postmodernist traits. It acknowledges that the world is diverse and that knowledge is contextual, ever-changing, and emergent. The acceptance of the idea of more than one reality and multiple understandings is part and parcel of postmodernism. Interpretivism is, therefore, characterized as a postmodern research philosophy. To demonstrate this philosophical premise more concretely, the creation of the logical structure of formal ontologies is sketched as an example of typical interpretivist and postmodernist activity in IS.

Process Theory

Because the IS field is grounded in its applications to organizations, the challenge is to develop a coherent theoretical body of scholarly research, while also remaining relevant to the needs of the practitioner community. In this effort, the purpose of this chapter is to provide scholars with a general understanding of process theories and a taxonomy to provide some direction about how to make contributions to the theoretical legacy, particularly through often-ignored process theories, which are also relevant to practice.

Visualization and Analysis of Frames in Collections of Messages

A step-by-step introduction is provided on how to generate a semantic map from a collection of messages (full texts, paragraphs, or statements) using freely available software and/or SPSS for the relevant statistics and the visualization. The techniques are discussed in the various theoretical contexts of (i) linguistics (e.g., Latent Semantic Analysis), (ii) sociocybernetics and social systems theory (e.g., the communication of meaning), and (iii) communication studies (e.g., framing and agenda-setting). The authors distinguish between the communication of information in the network space (social network analysis) and the communication of meaning in the vector space. The vector space can be considered a generated as an architecture by the network of relations in the network space; words are then not only related, but also positioned. These positions are expected rather than observed, and therefore one can communicate meaning. Knowledge can be generated when these meanings can recursively be communicated and therefore also further codified.

On IT and SwE Research Methodologies and Paradigms

In this chapter, the authors review the landscape of research methodologies and paradigms available for Information Technology (IT) and Software Engineering (SwE). The aims of the chapter are two-fold: (i) create awareness in current research communities in IT and SwE on the variety of research paradigms and methodologies, and (ii) provide an useful map for guiding new researchers on the selection of an IT or SwE research paradigm and methodology. To achieve this, the chapter reviews the core IT and SwE research methodological literature, and based on the findings, the authors illustrate an updated IT and SwE research framework that comprehensively integrates findings and best practices and provides a coherent systemic (holistic) view of this research landscape.

Practice vs. Possession

Organizational knowledge is at the center of the debate focused on the nature of knowledge, where the perspective of knowledge as possession opposes the perspective of knowledge as practice. These two views are rooted in the radical versions of realist and constructivist epistemology, respectively, according to which knowledge is an object or a practice. Far from being a Byzantine dispute, the adoption of one or the other has relevant and concrete consequences for the design and management of IS/IT, because as such, the two paradigms result incommensurable in both theoretical and methodological aspects. However, from a moderate and middle-ground version the following fruitful implications would stem: 1) the juxtaposition would dissolve, and a dual nature of knowledge as object and practice would emerge; 2) the epistemology of pragmatism would be able to account for all the concepts and methods employed by the two fronts, thus terminating a sterile “paradigm war”; 3) the theory of autopoiesis would become irrelevant and eventually even misleading; 4) standard scientific methodologies and simulation models would be acknowledged as useful and common tools for progressive confrontations among the supporters of both the paradigms; 5) the development of IS/IT studies and the design of knowledge management systems would substantially benefit.

Engineering Design as Research

Research is defined as an activity that creates new knowledge. This is often misunderstood in the engineering community as necessarily requiring a scientific contribution that advances the theory of some matter related to engineering materials or processes. Consequently, typical engineering research projects investigate physical phenomena thought likely to be interesting in potential applications or to describe the characteristics of processes used in engineering work. The results of such projects provide a fragmented, abstracted view of the phenomena investigated, which is difficult to use in engineering decision making related to contextualised situations. This chapter shows how the actual design of engineered artefacts is research because it provides knowledge of the impact of the integration of various elements of existing knowledge, which demonstrates the properties of the designs achieved through the design work and leads to discovery of solutions to the various challenges of integration discovered through the project which attempts to achieve the integration.

Selecting Strategies and Approaches in Systems Engineering

This chapter presents a method of applying the principles of the descriptive research method to studies aimed at ascertaining the data needed for making a recommendation in regard to what strategy or approach should be chosen in a certain development stage of future projects. The idea is to use data extracted from already-finished projects to make decisions related to similar projects in their early stages. First, the method is briefly described; next, two case studies that illustrate the method are presented. The method is based on isolating an independent variable, which can be development strategy, integration approach or any other strategy or approach, and deciding which attribute of the independent variable is preferable with respect to the dependent variable, project success, measured by the extent of meeting the requirements, planned budget, planned schedule, and customer satisfaction.

Project Contexts and the Possibilities for Mixing Software Development and Systems Approaches

It is widely agreed that no single approach for software or systems development addresses all problems and contexts. This chapter summarizes three software development and systems approaches that are often viewed as somewhat unrelated: soft system methodology (SSM), work system method (WSM), and agile development. Next it presents a framework linking stakeholder interests and problem contexts known as the System of Systems Methodologies (SOSM) from Jackson and Keys (1984) and frameworks from Bustard and Kennan (2005) and Alter and Browne (2005) for visualizing various Information Systems (IS) contexts. It uses SOSM to position and explore alternative sets of IS project contexts described by Bustard and Kennan (2005) and Alter and Browne (2005) using their own frameworks. Comparison of these contexts in relation to SOSM leads to observations about the suitability of SSM, WSM, and agile development in different project contexts. Contributions of this research include identifying and comparing alternative contexts for software and system development and identifying possibilities for including within one project combinations of methodologies that are often viewed as unrelated.