Adaptations of Models in Information Systems: How New Questions are Answered in Research Relying on Established Work

by Michael Curry


This essay provides a critical review of two papers in the field of management information systems (MIS) to provide examples of i) good management research in the MIS discipline ii) researchers using prior work to study new problems and iii) different approaches to research methodology.  I begin by studying a paper published in a top MIS journal on the Coping Model of User Adaptation (hereafter referred to as CMUA). Given the significance of this work, it is interesting to study the strengths and weaknesses of this paper as well as the qualitative research methods it employed. The second paper is new research recently published which applies and extends the CMUA. I selected this paper because I found it to be an interesting example of a researcher using an established model to identify answers to new questions in MIS and (in contrast to the first paper) because  it uses quantitative methods.

The Coping Model of User Adaptation

Management research should seek to be interesting, rigorous and relevant (Easterby-Smith, Thorpe et al. 2009, p. 8-9), which some argue is the purpose of modern social research (Pettigrew 2001; Starkey and Madan 2001) —to produce work which both practitioners and academics find engaging (Bartunek, Rynes et al. 2006). The selection of Beaudry and Pinsonneault’s 2005 paper, “Understanding User Responses to Information Technology: a Coping Model of User Adaptation” was made partly because it seems to satisfy these goals of management research. My critique will begin with an examination of the authors’ literature review and their identification of a research gap followed by an overview of the research methodology. I will conclude by briefly discussing the contribution made by CMUA to set a foundation for the subsequent review of a derivative paper.

Literature Review and Research Gap

The literature review in CMUA applies a framework of critical realism (Easterby-Smith, Thorpe et al. 2009, p. 62-63) in an attempt to re-interpret a wide selection of literature on user adoption of computer systems.  User adoption is a popular topic in management information systems since both academics and industry would like to better understand why users prefer one information technology system over another. For example, the Technology Acceptance Model (or TAM) is one effort (I am familiar with) that has demonstrated people are more likely to embrace systems which are user-friendly and satisfy their needs (Venkatesh, Morris et al. 2003).

CMUA reinterprets the body of prior work as attempts to “predict how users will react to new technology”, and identifies a gap in this research by neatly classifying the preceding work as principally focusing on either “antecedents” or “outcomes” (Beaudry and Pinsonneault 2005, p. 494-497). Each perspective, they argue, is incomplete because it does not also consider the other view. To fill this gap CMUA is an attempt to develop a unified theory of user adaptation to disruptive technology. Using coping theory, the authors argue that because CMUA integrates antecedents and outcomes it may better explain the complexity of how users respond to new technology (Beaudry and Pinsonneault 2005, p. 494-497).

The literature review does not include support to justify the authors’ re-classifications of previous research approaches into two distinct categories. . However the authors’ interpretation is most likely intended to highlight the absence of a model that unifies multiple perspectives and not an attempt to diminish the relevance of prior work.  The contrast does clearly indicate what gap this work is intended to fill, and prepares the reader for further presentation of relevant literature.

Most of the literature review covers coping theory which researchers in the field of MIS as less likely to be familiar with. The prior work of R. Lazarus and S. Folkman in the field of psychology is cited nine times to explain that coping response to stress can be modeled as a two stage process. The authors link coping theory with user responses to technology to argue encounters with new technology are stressful. However, only one reference is cited to support this assertion, and in reviewing this cited reference it is not entirely clear it adequately justifies the validity of the link proposed (Lyytinen and Rose 2003).  However, most of us have experienced new technology and are likely to agree it can be stressful so perhaps the authors did not feel more justification was required.

Qualitative Data Collection

The authors used case studies in two very similar organizations (banks) which introduced new IT systems and studied the cognitive adaption of individuals with similar roles (account executives) who were principally impacted by the new technology. A total of seventeen interviews lasting an average of two hours each were collected by the authors using mixed structure interviews. Initial open-ended interviews were conducted with senior management and IT staff to understand the scope of the new technology and the roles of account executives. Later structured interviews were conducted with account executives to assess their adaptation to the new technology. Additional interviews were conducted with employees who had knowledge of the account executives job performance to help triangulate the adaptation assessment (Beaudry and Pinsonneault 2005, p. 503-517).

Once the interviews were collected, the responses were coded into four broad categories by two researchers, who also verified each other’s work to eliminate coding differences. Then a finer grain analysis of the responses was conducted to indentify coding quotes (Beaudry and Pinsonneault 2005, p. 507-508). One interesting point is that the “main categories were developed a-priori”, but the sub classifications “for the coding framework came about in an emergent manner (Easterby-Smith, Thorpe et al. 2009, p. 187).”  The purpose of the codes was to create a chain of evidence to classify the adaption of each account executive (Beaudry and Pinsonneault 2005, p. 508) and provide quantitative validity for the qualitative work (Cassell, Buehring et al. 2005, p. 29-30).

Research Contribution

The papers most significant contribution is a model to better explain user response to technology. CMUA predicts user responses will result in one of four likely outcomes. The two dependent variables are whether the user feels the new technology is a threat or an opportunity and whether they feel they have any control over the situation or not. For example, users who see technology as an opportunity and feel they have control are expected to maximize the benefits. At the other extreme, users who perceive new technology as a threat and themselves having little control are expected to focus on self-preservation, e.g. finding a new job (Beaudry and Pinsonneault 2005, p. 498-503). To validate the model nine and one-half pages are devoted to descriptions and quotes providing examples of each behavior predicted by the different quadrants of the CMUA model.

As a researcher and someone who has experienced disruptive technology I appreciate the explanatory value of CMUA. However, I question whether this model is a complete representation or an over simplification of an incredibly complex dynamic. Technology is so pervasive in modern society and consequently there are many ways it can impact human adaptation that were likely not captured in a study of skilled, educated senior employees at two banks. Furthermore, there are a wide range of emotional responses across the spectrum of humanity with varying degrees of education and IT experience that seem to make it difficult to expect complete explanatory predictions from a simplistic 2x2 model. At a minimum, there is likely a significant issue with “interrelated influences between the variables (Easterby-Smith, Thorpe et al. 2009, p. 271-272)” meaning the model may have interdependencies not depicted. The authors briefly mention potential influences between variables, but go on to argue that a feedback loop in the model allows for multiple discrete responses so that the issue can be disregarded (Beaudry and Pinsonneault 2005, p. 494-497).

To be fair, the model’s simplicity was most likely a design choice to simplify data collection (a common practice in MIS and psychology research), though care should be taken to “ensure interrelated variables are as mutually independent as possible (Easterby-Smith, Thorpe et al. 2009, p. 272).” How serious of a problem variable interference is to the validity of CMUA is not discussed in the paper, though further investigation into the original work of  R. Lazarus and S. Folkman’s contribution to coping theory may uncover additional clarification which the authors omitted for the sake of brevity.

This article is continued. Continue reading part 2.

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