IT artifact bias: How exogenous predilections influence organizational information system paradigms

https://doi.org/10.1016/j.ijinfomgt.2014.02.005Get rights and content

Highlights

  • We theorize that how one perceives IT artifact affordances shapes their cognitive bias.

  • We develop a simple instrument to assess this phenomenon (IT artifact bias).

  • IT artifact bias is shown to shade perceptions of IT processes and IT quality.

  • Two predictors (job role and IT complexity) systematically impact IT artifact bias.

Abstract

Efforts in IS research have long sought to bridge the gap between the information technology (IT) function and strategic business interests. People perceive affordances (possibilities for action) in information technology artifacts differently as cognitive structures (schema) which bias individual focus. This study explores how an individual's tendency to perceive the ‘trees’ in an IT ‘forest’ (artifact preference) affects their assessment of efforts to achieve more effective IT outcomes. The effect is demonstrated using a relatively simple IT success model. Further, in a sample of 120 survey responses supported by ten semi-structured interviews, we demonstrate that job role and organizational IT complexity systematically impact artifact perception. A better understanding of IT artifact bias promises to help organizations better assess information systems.

Introduction

Efforts in IS research have long sought to bridge the gap between the information technology (IT) function and strategic business interests. The working philosophy behind these efforts is that less separation between the two will benefit the organization. While some have focused on defining the gap and quantifying its size (see for example, Bergeron et al., 2004, Chan and Reich, 2007, Henderson and Venkatraman, 1993), others are focused on systematically closing the gap (see for example, International Organization for Standardization, 2005, IT Governance Institute, 2008, Taylor et al., 2007). While assessing this ‘gap’ within an organization is important for IT management, it is also difficult because assessments are colored by the experience, understanding, and organizational role of personnel.

The work reported in this article explores how individual predispositions to focus on IT artifact affordances colors their assessment of information systems (IS) initiatives, IS success, and the antecedents of IS success. While IT artifacts may afford many possibilities for action (Leonardi, 2011), those “affordances” are perceived differently based, in part, on one's personal preference. These preferences may be shaped by prior experience, which serves as a guide to interpreting related perceptions. Put another way, one's preference for perceiving IT forms a cognitive bias, which we posit will shade various judgments about organizational IT processes.

One way to characterize cognitive bias as it relates to organizational information systems is to assess an individual's predilection to either distinguish the IT artifact affordances in an information system or else to view IT as an enabler of organizational IS processes. Affordances, as considered in this line of work, are defined as perceived information system potentialities for organizational effectiveness. For example, an ERP system has the potential to decrease transaction costs; but the mechanisms to accomplish this are complex and some employees may not perceive these affordances and therefore contribute less effectively to implementation initiatives.

In order to be perceived (and therefore included in a multifaceted decision processes), system potentialities must make it through an individual's cognitive filtering process. People are more likely to sense capabilities consistent with their personal schema (Crocker, Fiske, & Taylor, 1984). Schemas are cognitive structures representing knowledge about a typical sequence of occurrences in a given situation (Ashforth & Fried, 1988). These mental models can conserve cognitive resources by reducing the effort needed to interpret the perceived world (Johnson-Laird, 1983), but they can also limit perception of potentially useful stimuli. We will refer to the cumulative effect of schemas on an individual's tendency to perceive the affordances of IT artifacts as perception preference.

IT artifacts are structured IT applications, which enable business processes (Benbasat & Zmud, 2003) or, alternatively, purposeful innovations that enable information systems (Hevner, March, Park, & Ram, 2004). IT artifacts include information technology (IT) or machines that process, store, and disseminate information (Nevo & Wade, 2010), such as computer hardware and software. IT artifacts may also apply to information systems (IS), or the interaction between people, processes, data, and technology (Kroenke, 2011). Additionally, IT workers, IT governance frameworks, policies, procedures, and documentation also play an important role in coordinating the flow of information through machines (Leonardi & Barley, 2008). Therefore, our use of IT artifacts encompasses IT, IS, and also related people, policies, and practices.

To illustrate the impact of perception preference on affordances, we compare an organizational information system to a ‘forest’ composed of many IT artifact ‘trees.’ Artifact preference is being inclined to see the affordances of ‘trees’ in the ‘forest.’ Such a preference will afford more possibilities to cognitively connect IT components to organizational outcomes. Conversely, individuals with a process preference are inclined to perceive IT in a supporting role to business processes, or have a tendency to see affordances at the ‘forest’ level. We anticipate that a ‘forest-level’ preference may limit perception of connections between more detailed IT artifact affordances and organizational outcomes.

We theorize that differing perception preferences are a frequent and common source of organizational problems because they complicate communication and make it more difficult to narrow the gap between IT capabilities and strategic business interests. Those who prefer to view people and processes as accomplishing goals assisted by IT are more likely to assign different credit for IT's contribution than those with an artifact preference.

For example, IT best practice frameworks, such as ITIL, ISO/IEC 27001, and COBIT, advocate IT processes such as identifying and addressing sources of risk as well as using performance metrics to systematically improve IT (IT Governance Institute, 2007, Taylor et al., 2007). These practices have been well established as antecedents to higher quality organizational outcomes (see, for example Duffy and Denison, 2008, Grembergen et al., 2003, Haes and Grembergen, 2008, Ridley et al., 2004). However, our experience suggests that not everyone in the organization is inclined to consistently connect many IT best practice efforts to organizational effectiveness. Warnings about Internet threats, for example, are largely ignored because users rarely view their own activity as a security risk (Wu, Miller, & Garfinkel, 2006).

Because individual perceptions have been shown to predict IT system adoption (Davis et al., 1992, Venkatesh and Davis, 2000, Venkatesh et al., 2003), establishing a method to gauge IT artifact preference could help to identify perception differences associated with IT's contribution. Information system adoption has also been linked to user satisfaction and IT quality as a predictor of organizational impact (DeLone and McLean, 1992, DeLone and McLean, 2003). Consequently, examining the link between how employees’ preferences influence their perceptions of IT processes and IT quality may offer further benefits to organizations.

Therefore, the research question we seek to answer in this exploratory study is:

Research Question: how does IT artifact perception preference influence perceptions of IT processes and IT quality?

Our research question is particularly relevant for smaller organizations, which may have greater difficulty recognizing and correcting for variation in perception. Larger organizations may have a dedicated staff of IT professionals – employees with IT training or experience – who accept responsibility for delivering IT services. By contrast, small to medium enterprises (SMEs) are typically resource-constrained and have difficulty committing time, money, and effort to IT management (DeLone, 1988, Devos, 2007, Huang et al., 2010, Tagliavini et al., 2001). Because smaller organizations often have no IT professionals they transfer some responsibility to end users (Bayrak, 2013, Lee et al., 2007, Qiang et al., 2006). These users may innovate, attempt to troubleshoot issues, and initiate support requests. Greater participation in IT efforts by SME employees may influence user IT perceptions and, therefore, impact information system adoption, management, and governance initiatives.

We also anticipate that smaller organizations with informal management attitudes will be more open and transparent than larger organizations. We expect that such openness and transparency may help facilitate measurement of IT artifact perception preference.

This paper proceeds as follows: first, we describe the relevant literature and formulate our hypotheses. Next, we present our model for investigation, describe the study design, and present quotes from interviews to support our theory and classification of IT artifact perception preference. Finally, we statistically analyze our data and present the results. A discussion of the contributions, limitations, and proposed future work concludes the paper.

Section snippets

Hypotheses development

This section presents the foundation for our conceptualization of IT artifact bias and the development of hypotheses to answer our research question. We then present a research model for studying IT artifact bias in smaller organizations.

Methodology

The remainder of this article reports on results from 120 survey responses and ten semi-structured interviews. Study participants were recruited from the Austin Family Business Program (AFBP, 2012), which serves as a liaison between academic researchers and small family businesses in the Northwest United States. The study's purpose was described as an effort to understand the effect of IT attitudes in organizations. No compensation was offered, but the benefits of participation were described

Semi-Structured Interviews

The transcripts of ten semi-structured interviews were reviewed in light of our hypotheses. Table 5 connects excerpts from the transcripts to our theoretical expectations.

A number of respondent comments were thematically relevant to our hypothesis. For example, our H1b predicted senior managers to be less exogenous, and the two managers in cases 1 and 2 both displayed a preference to focus on the process outcomes (e.g., productivity and money) instead of on individual artifacts. The manager in

Discussion

This study aims to collect and evaluate evidence that the phenomenon of IT artifact bias impacts important perceptions of IT processes and IT quality. Further, at least two important predictors (job role and IT complexity) are shown to systematically impact IT artifact bias. As depicted in Fig. 1 above, our research model firstly anticipates that well-conceived IT efforts will lead to higher quality IT outcomes (H2), secondly projects that IT bias will influence perceptions related to the H2

Conclusions, limitations, and future work

Applying a socio-materiality/affordance perspective, this study explored both how perceptive tendencies impact IT assessment and how experience and context affect IT assessment perceptions. The notion of affordance perception bridges the promising notion of value-added capabilities of systems and that of organizational understanding of IT quality. IT professionals and managers often see the IT world differently. A manager wants to ask “what did the system do for us?” An IT professional might

Acknowledgements

We are grateful for the study participation of the Austin Family Business Program within the College of Business at Oregon State University. We also acknowledge the valuable contribution made by anonymous reviewers of our manuscript and thank them for their efforts.

Michael Curry is a Clinical Associate Professor of Information Systems and Entrepreneurship at Washington State University Vancouver's College of Business. He received a doctorate in business administration from Manchester Business School in 2014 in the field of Management Information Systems. His research explores the mechanisms that normative attitudes play in IT effectiveness efforts and how this can be used to adapt IT best practice frameworks to smaller organizations. Michael has over a

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  • Cited by (0)

    Michael Curry is a Clinical Associate Professor of Information Systems and Entrepreneurship at Washington State University Vancouver's College of Business. He received a doctorate in business administration from Manchester Business School in 2014 in the field of Management Information Systems. His research explores the mechanisms that normative attitudes play in IT effectiveness efforts and how this can be used to adapt IT best practice frameworks to smaller organizations. Michael has over a decade experience as an entrepreneur and IT innovation consultant.

    Byron Marshall is an Associate Professor of Information Management and Accounting at Oregon State University's College of Business. His research interests emphasize the re-use of organizational data in informal node-link knowledge representations to support analysis tasks. He received a Ph.D. in Management Information Systems from the University of Arizona in 2005. Byron has 13 years of dynamic industry experience designing, creating, and using computer systems in the cotton industry.

    Peter Kawalek is Professor of Information Systems and Strategy at Manchester Business School. He is also a Visiting Professor at Instituto de Empresa in Madrid and Letterkenny Institute of Technology in County Donegal. Peter's PhD is in Computer Science, and his research interests focus on innovation in the areas of cybernetics, enterprise systems, government, and start-ups. He works closely with Office an Taoiseach, Department of Communities and Local Government, the NHS, Leeds City Council, Tameside Council and Salford City Council.

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