Interdependencies between people and information systems in organizations

This article argues that while people and information systems (ISs) represent the two single largest areas of investment for many organizations and are increasingly interconnected resources, there has been very little research on the nature of their interdependencies and how these interdependencies affect their functioning and complementarity. It discusses how a better understanding of the dynamics of interdependencies between people and ISs can help researchers study organizations and help organizations improve the interoperation of their human and technological assets, and thus returns on investments in them. The article begins by reviewing the concept of capital and its application to people - human capital - and information systems: ISs capital. Next, it surveys past literature on interdependencies and recent literature relating to interdependencies between people and information systems. Based on the analysis, the article proposes an agenda for future research aiming to conceptualize interdependencies between people and ISs in a richer fashion

What have we learned from the Smart Machine?

Zuboff's (1988) book In the Age of the Smart Machine: The Future of Work and Power is one of the most celebrated texts among Information Systems researchers. Despite its significant influence, I suggest that it may have a richer story to tell than has been told to date. Motivated by this potential, my essay has two aims: to explicate the theory developed in Zuboff's text, and to determine how fully it has been used and extended by Information Systems researchers, through an analysis of papers citing her text. My findings show that the theory developed in Zuboff's text has been used in a fairly limited and piecemeal fashion. I discuss how this presents a significant opportunity for research because the theory appears to be just as relevant now as it was when the text was published

New Perspectives on the System Usage Construct

Information systems are designed to support human and organizational purposes. To achieve their ends, information systems must be used. Although this may seem to be self-evident, there are many aspects of systems usage that are not so, and yet, in spite of this, there has been little intense conceptual scrutiny of this construct in past research. The objective of this thesis, therefore, is to develop new in-depth perspectives for studying system usage. Drawing on critical realist assumptions and studies of research diversity, I explain how epistemological factors enable while ontological factors constrain the diversity of meanings of system usage, and I build on this reasoning to advance a systematic approach for conceptualizing and measuring system usage in an appropriate way for a given research context. To demonstrate the approach and judge its usefulness, I carry out three empirical studies to test whether measures of system usage that are selected according to the proposed approach provide more explanatory power and lead to more coherent results in specific research contexts than other measures of system usage. Exploring the relationship between system usage and user task performance among 804 users of spreadsheet software, the experiments reveal support for the usefulness of the approach and demonstrate how it can enable researchers to conceptualize and measure system usage in an appropriate manner for a given research context. Together, the conceptual approach and empirical studies contribute by: (1) providing a systematic way to conceptualize and measure system usage for a given study context, (2) revealing rich new directions for research on the nature of system usage, its antecedents, and its consequences, and (3) suggesting a new approach for construct development and investigation in IS research

The Milky Way Heart: Investigating molecular gas and gamma-ray morphologies in the Central Molecular Zone

Since the discovery of a broad distribution of very high energy (VHE; >0.1 TeV) gamma-rays in the Central Molecular Zone (CMZ) of the Galaxy in 2006 by the HESS collaboration, the correlation of this emission with the integrated intensity of the CS(1-0) molecular line emission has inferred a hadronic origin for the gamma-rays. Here we describe the beginning of our investigation into the strength of this correlation utilising new multi-line millimeter data from the Mopra CMZ and HOP surveys and multi-wavelength GBT radio continuum observations towards the CMZ and compare these in detail with the diffuse TeV gamma-ray emission from HESS. The benefit of these new data is that they allow us to simultaneously observe and analyse correlations using a large number (>10) of molecular species, some of which contain their isotopologue pairs. The use of isotopologue pairs is especially powerful, since it allows one to analyse the optical depth of a number of different molecular species, thus investigating the nature of the correlation over a range of different physical conditions. Here we begin by comparing the integrated line emission and continuum radio emission with the diffuse gamma-ray emission, and, by using isotopologue pairs such as HCN/H$^{13}$CN, obtain optical depths throughout the CMZ corresponding to regions of both strong and weak gamma-ray emission. We find that the radio continuum better matches the peak of the gamma-ray emission, which corresponds to the more compact -- compared to the relatively coarse resolution of the gamma-ray images -- sources in the CMZ. Using the isotopologue pairs, we find that the optical depth at all positions and velocities within the CMZ are about 2--4. This is similar to that found for the CS(1--0) line and would underestimate the mass of the CMZ, potentially explaining why molecular line emission peaks appear offset from the gamma-ray peaks.Comment: 8 pages, 5 figures. Accepted to the Proceedings of the 25th Texas Symposium on Relativistic Astrophysics (Heidelberg, 2010

Using information systems effectively: A representational perspective

Although there has been a great deal of research on why individuals adopt and use information systems, there is little research on what it takes for individuals to use information systems effectively. Motivated by the view that much of the impacts of information systems stem from how they are used, we propose a model to explain the nature and drivers of effective system usage. The model is designed to explain effective system usage in the context of an individual user employing any individual information system. In this context, we build on a theory of information systems known as representation theory to propose that effective system usage requires a user to engage in three activities: adaptation activities (adapting the system so that it provides better representations), learning activities (learning how to access the representations offered by the system), and verification activities (verifying the representations in the system as well as the real world domain being represented). The model suggests a set of factors that drive these activities, specifies how these activities drive effective usage, and proposes a link between effective usage and users task performance. After specifying the model, we provide examples of how it could be used to explain the effective use of several types of information systems and we discuss how the model could be expanded to explain other contexts of use (e.g., multiple systems and multiple users) and to incorporate process forms of theorizing as well as variance forms of theorizing

How Good Are These UML Diagrams? An Empirical Test of the Wand and Weber Good Decomposition Model

In 1989, Wand and Weber proposed a formal model of systems decomposition based on ontology. Chidamber and Kemerer (1994) soon applied this model to develop complexity metrics for object-oriented design (OOD). Chidamber and Kemererís OOD metrics suite continues to receive interest in software engineering (Bansiya and Davis 2002; Basili et al. 1996). To date, however, Wand and Weberís good decomposition model has received almost no application in information systems (IS). For three reasons, we believe the theory might assist IS researchers. First, object-oriented analysis (OOA) has not been as successful in practice as OOD or OO programming (Chuang and Yadav 2000). The good decomposition model may help IS researchers investigate improvements to OOA. Second, Johnson (2002) recently lamented how few OOA studies employ any theory. Wand and Weberís theory may, therefore, be a useful approach. Third, many believe OOA is a revolutionary step away from traditional approaches (Sircar et al. 2001). Practicing analysts could benefit from theory-based principles to guide their use of this ìrevolutionaryî technique. In this study, we report an experiment to determine the utility of the good decomposition model in OOA. We operationalized each condition of Wand and Weberís model in a set of UML diagrams and tested participantsí understanding of the diagrams across three levels. Our results lend support to Wand and Weberís theory, but only across dependent variables that tested participantsí actual understanding. The impact on participantsí perceptions of their understanding remained equivocal

Understanding Digital Platform Generativity from a Sociomaterial Perspective

Research on digital platform generativity has predominantly taken a substantivist view, considering digital platforms as relatively static, self-contained entities separated from their human actors. We argue this view, while intuitive and common sensical, also has a downside – biasing researchers and practitioners from understanding the dynamic and processual nature of digital platform constituted through generativity in the flow of time. We offer a sociomaterial view to consider digital platforms as an assemblage of enacted sociomaterial practices, enabling researchers to move from studying platforms to platform becoming, and from generativity to generating. We illustrate these ideas via a preliminary empirical study of how generativity is constituted by the performativity of a digital platform, as it is enacted by the human agencies entailed in its design and management. Ultimately, our study aims to take steps towards a sociomaterial theory of digital platform generativity that can contributes to the digital platform literature

The Effects of Decomposition Quality and Multiple Forms of Information on Novices’ Understanding of a Domain from a Conceptual Model

Individuals can often use conceptual models to learn about the business domain to be supported by an information system. We investigate the extent to which such models can help novices (i.e., individuals who lack knowledge in the business domain and in conceptual modeling) to obtain an understanding of the domain codified in the model. We focus on two factors that we predict will influence novices’ understanding: (1) decomposition quality: whether the conceptual model manifests a good decomposition of the domain, and (2) multiple forms of information: whether the conceptual model is accompanied by information in another form (e.g., a textual narrative). We hypothesize that both factors will have positive effects on understanding and that these effects depend on whether the individual seeks a surface or deep understanding. Our results are largely in line with our predictions. Moreover, our results suggest that while novices are generally aware that having multiple forms of information affects their understanding, they are unaware that decomposition quality affects their understanding. Based on these results, we recommend that practitioners include complementary forms of information (such as a textual narrative) along with conceptual models and be careful to ensure that their conceptual models manifest a good decomposition of the domain

Understanding Relationships with Attributes in Entity-Relationship Diagrams

Conceptual modeling is an important task undertaken during the systems development process to build a representation of those features of an application domain that are important to stakeholders. In spite of its importance, however, substantial evidence exists to show that it is not done well. Designers often provide incomplete, inaccurate, or inconsistent representations of domain features in the conceptual models they prepare. Users often have difficulty understanding the meaning inherent in a conceptual model. In this paper, we investigate the proposition that part of the difficulties that stakeholders experience with conceptual modeling arises when a conceptual modeling grammar or a representation produced using the grammar lacks ontological clarity. Lack of ontological clarity arises when a one-one mapping does not exist between conceptual modeling constructs and real-world constructs. For example, the grammatical construct of an entity is used to represent both things and events in the real world. Specifically, we focus on the grammatical construct of a relationship with attributes, which is often used in entity-relationship modeling. We argue that use of this construct produces ontologically unclear representations of a domain. We also report results from an experiment we undertook where we investigated the impact of using relationships with attributes in conceptual modeling representations on the problem-solving performance of users of these representations. Consistent with our predictions, we found that using relationships with attributes undermined problem-solving performance in unfamiliar domains. Contrary to our predictions, however, their use did not undermine problem-solving performance in familiar domains