Evaluating and Developing Theories in the Information Systems Discipline

This paper articulates a framework and criteria that can be used to evaluate the quality of theories. While the framework and criteria have general applicability, my focus is the evaluation of theories within the information systems discipline. To illustrate the usefulness of the framework and criteria, I show how they can be employed to pinpoint the strengths and weaknesses of a theory which, based upon citation evidence, has had a significant impact on other researchers within the information systems discipline. Because the evaluation of existing theories often provides the basis for refining existing theories or building new theories, I also show how the framework and criteria can be used to inform the development of high-quality theory

The Link Between Data Modeling ApproachesAnd Philosophical Assumptions: A Critique

Hirschheim et al. (1995) argue that information system designers\u27 choice of a particular data modeling approach is inextricably linked to ontological, epistemological, social-contextual, and representational assumptions that they make about the worlds they seek to represent via their models. I argue, instead, that the link between different data modeling approaches and these four sets of assumptions is either weak or non-existent. I agree that there is some type of association between use of a particular data modeling approach and the ontological assumptions that designers make. The nature of the links, however, between different data modeling approaches and different epistemological, social-contextual, and representational assumptions is more problematical

The Other Reviewer: RoboReviewer

The peer review process is a mainstay for informing publication decisions at many journals and conferences. It has several strengths that are well-accepted, such as providing a signal about the quality of published papers. Nonetheless, it has several limitations that have been documented extensively, such as reviewer biases affecting paper appraisals. To date, attempts to mitigate these limitations have had limited success. Accordingly, I consider how developments in artificial intelligence technologies—in particular, pretrained large language models with downstream fine-tuning—might be used to automate peer reviews. I discuss several challenges that are likely to arise if these systems are built and deployed and some ways to address these challenges. If the systems are deemed successful, I describe some characteristics of a highly competitive, lucrative marketplace for these systems that is likely to emerge. I discuss some ramifications of such a marketplace for authors, reviewers, editors, conference chairs, conference program committees, publishers, and the peer review process

Reach and Grasp in the Debate over the IS Core: An Empty Hand?

Papers published about the need for a theoretical core in the information systems (IS) discipline can be characterized as either nature-of-the-discipline commentaries or logic-of-the-core commentaries. The former articulate the authors\u27 views on those phenomena that research in the IS discipline ought to investigate. The latter scrutinize some of the logic that underlies arguments made by those who either support or reject the need for a theoretical core. Unfortunately, nature-of-the-discipline commentaries are unlikely to help clarify or resolve fundamental issues that underpin the debate. Too often they are based on idiosyncratic views that are difficult to either justify or refute. Logic-of-the-core commentaries, however, lay bare the arguments made by the protagonists so they can be evaluated. In this paper, I examine the logic-of-the-core arguments made by Lyytinen and King (2004) and evaluate their validity

CONDITIONAL STATEMENTS AND PROGRAM CODING: AN EXPERIMENTAL EVALUATION

Information Systems Working Papers Serie

Optional Properties Versus Subtyping in Conceptual Modeling: A Theory and Empirical Test

An important feature of many conceptual modeling grammars is the set of constraints they provide to allow analysts to show that real-world things may or may not possess a particular property. In the entity-relationship model, for example, the fact that a thing may not possess a property (the property is optional) can be represented by showing the minimum cardinality of a relationship or an attribute is zero (Batini, Ceri and Navathe 1992). Whether this practice should be followed, however, is a contentious issue because it may obfuscate the semantics of the real-world domain that is being modeled. An alternative approach is to eliminate optional properties from conceptual schema diagrams by using subtypes that have only mandatory properties (Weber and Zhang 1996). A problem with this approach, however, is that it often leads to more complex conceptual schema diagrams because they include more elements to represent the additional subtypes needed

A UNIFIED MODEL OF SOMWARE AND DATA DECOMPOSITION

Decomposition is an important part of information systems analysis and design and is manifested as the breakdown of the system to elements such as subsystems, modules, activities, processes, entities, and objects. Good decomposition is considered a major requirement for a good system design. However, there is no comprehensive theory of information systems decomposition and no single dominant decomposition approach exists. Consequently, software decomposition relies on guidelines and designer\u27s experience. In this article, we propose a foundation for a theory of good decomposition based on two principles: 1) the decomposition of an information system should reflect the nature of the real world system represented by it, and 2) static and dynamic aspects of systems cannot be separated and hence good decomposition should be based on both. The model enables the analysis of concepts such as good software modules, normalized relations, objects, and entities as special cases of one generalized construct

Structured Tools and Condiitonal Logic: an Empirical Investigation

An important outcome of recent work on the psychology of programming has been the recognition that we have a poor understanding of how various programming practices-indenting, commenting, naming, etc.-facilitate or inhibit the programming process. After a fairly extensive series of studies, many results obtained are contradictory and counterintuitive. The major probem seems to be that we have poor theoretical bases to drive the empirical research. In particular, we have little knowledge of the psychological constructs that programmers bring to bear when they perform various programming tasks, and we have little knowledge of what is natural for programmers. This research tested the propositon that the effectiveness of a programming practice is a function of the extent to which it provides a close cognitive fit with a programmers\u27 problem solving strategy when he or she performs a programming task. The proposition was tested in the context of two psychological processes that appear to be used by programmers when they design and code conditional logic: (a) taxonomizing-identifying the conditions that evoke particular actions; and (b) sequencing-converting the taxa to a linear sequence of program code. Three structured tools-structured English, decision tables, and decision trees-were investigated in a laboratory setting to determine how they facilitated these two processes. It was hypothesized that decision tables and decision trees would facilitate the taxonomising process because they allow conditions and actions to be easily identified, and that structurd English would facilitate the sequencing process because it provides a linear representation of logic that can be mapped easily into programming code. To test the hypotheses, 124 volunteer information systems and computer science students undertook three experiments. In the first experiment they were given a narrative description of some conditional logic and asked to represent the logic using one of the three types of structured tools. In the second experiment they were given conditional logic already represented via one of the tools and asked to convert it into COBOL code. In the third experiment they were given a narrative description of some conditional logic and asked to convert it into COBOL code after having first represented the logic using one of the three types of structured tools. Their perfomance was assessed in terms of the number of syntactic errors they made, the number of semantic errors they made, and the time taken to perform the experimental tasks. In general, the results confirmed the propostions investigated. When the taxonomizing task had to be undertaken, decision trees outperformed strutured English, although surprisingly structured English outperformed decision tables. When the sequencing task had to be undertaken, structured English outperformed decision tables, but decision trees evoked the same level of performance as structured English. Across all tasks, decision tables evoked relatively poor levels of perfomance. On the other hand, decision trees evoked high levels of performance across all tasks. It appears that the graphical tree structure allows taxon information to be represented poignantly. At the same time it appears relatively easy to trace a branch to its leaf node to perform the sequencing task. The superiority of decision trees seems to confirm the desirablity of graphically revealing the structure inherent in processes rather than using symbolic languages. Moreover, the results suggest that the syntax of current programming languages may be unnecessarily restrictive. Perhaps programming languages should provide decision trees as part of their syntax instead of providing only unidimensional, linear syntax to represent conditional logic

AN ONTOLOGICAL ANALYSIS OF SOME FUNDAMENTAL INFORMATION SYSTEMS CONCEPTS

This paper describes how ontological concepts can be used to model information systems. We view an information system as an object that is independent of its use or its technology of implementation. The main premise of the model is that an information system is a representation of a real-world system, and as such it should possess certain characteristics, We show how the model can be used to define various concepts such as real-time, batch, data processing, management reporting, decision support, controls, and decomposition. Furthermore, we show how the model may serve as the foundation of a theory of systems analysis and design. In particular, it provides a formal definition of information systems specifications and a normative model of decomposition

TOWARD A THEORY OF THE DEEP STRUCTURE OF INFORMATION SYSTEMS

The deep structure of an information system comprises those properties that manifest the meaning of the real-world system that the information system is intended to model. In this paper we describe three models that we have developed of information systems decl}.structure properties. The first, the representational model, proposes a set of constructs that enable the ontological completeness of an information systems grammar to be evaluated. The second, the state-tracking model, proposes four requirements that information systems must satisfy if they are to faithfully track the real-world system they are intended to model. The third, the good-decomposition model, proposes a set of necessary conditions that an information system must meet if it is to be well decomposed. The three models facilitate the evaluation of grammars used to analyze, design, and implement information systems and specific scripts that represent implemented information systems