Inclusion of Social Subsystem Issues in IT Investment Decisions : An Empirical Assessment

Inclusion of Social Subsystem Issues in IT Investment Decisions :An Empirical Assessment Sherry D. Ryan and Michael S. Gates, University of North Texas, USA Reporter：Tzu-Chieh Lin

About Author • Sherry D. Ryan • Michael S. Gates

OUTLINE • INTRODUCTION • THEORETICAL BACKGROUND AND RESEARCH HYPOTHESES • METHODOLOGY • RESULTS • DISCUSSION • LIMITATIONS AND FUTURE RESEACH • CONCLUSION

INTRODUCTION(1/2) • There are many factors that lead to high failure rates and cost overruns. • Nearly one third of the outlays for IT are wasted. • 31% of IT projects are canceled before they are completed. • 53% of IT project will cost nearly double the original estimates. • Both researchers and practitioners have suggested that traditional valuation analyses are inadequate. • Adding a strategic perspective to IT investment decisions. • Consistent with the terminology and principles of socio-technical systems (STS) theory, we define there issues originating from employees’ assessments, capabilities, decisions, and task interdependencies as social subsystem issues. • Social subsystem benefits and costs do accrue when an IT is acquired. However, without awareness or formal consideration of social subsystem issues.

INTRODUCTION(2/2) • Some prior research focusing on IT valuation has examined social subsystem issues. • It was motivated by two primary research questions： • RQ1：What weight does the decision maker place on social subsystem issues as compared with technological or financial factors? • RQ2：To what extent are social subsystem issues considered in an explicit manner, an implicit manner, or not at all? • They believe their findings extend prior research by： • Providing an empirical assessment of how social subsystem issues compare with other IT decision criteria given differing decision types. • Identifying which social subsystem issues are considered most important by decision makers, • Distinguishing the manner by which these social subsystem issues are considered.

THEORETICAL BACKGROUND(1/3) • STS theory provides a strong theoretical basis for investigating issues in the technological and human resource domains. • Human resource：skills, knowledge, abilities, interrelationships, ideas, attitudes, and needs they bring to work. • Technological：incorporates the tools, devices, and techniques used within the social subsystem to accomplish organizational tasks. • Each subsystem must be designed to fit the requirements of the other, so that superior results can be achieved. • STS provides a conceptual framework with which to consider the close interrelationship between the technological and social subsystems. • However, many social subsystem issues are never included in the evaluation process.

THEORETICAL BACKGROUND(2/3) • Only 3% of executives sampled ever mentioned considering such important employee-related concerns as morale or job dissatisfaction. • Dual-core model → Tri-core model • Type I (Information Core)：focus on the management and administrative support of IS work or the technical IS task itself. • Type II (Administrative Core)：support functions of the business such as payroll systems or e-mail • Type III (Technical Core)：are those embedded in the elemental technology for producing the organization’s goods and services.

THEORETICAL BACKGROUND(3/3) • Ryan and Harrison (2000) created a two-dimensional framework consisting of Swanson’s innovation types on one dimension and the degree of change induced by an IT decision (Orlikowski, 1993) on the other dimension.

RESEARCH HYPOTHESES • H1：Social subsystem issues will be considered less than (a) technical or (b) financial issues in decisions that will induce little disruption. • H2：Social subsystem issues will be considered more than technical issues in decisions that will induce great disruption. • H3：Social subsystem issues will be considered less than financial issues in decisions that will induce great disruption. • H4：Implicit consideration of social subsystem issues will be considered to a greater extent for both (a) decisions that induce little disruption and (b) decisions that induce great disruption.

METHODOLOGY (Conduct of the study) • Interviews • Thirty semi-structured interviews were performed to obtain insight on issues decision makers consider when making an It investment decision. • Pilot Study • The survey was refined through four stages. • Survey • Firms in diverse industries and regions with varying organizational sizes were selected for the mail survey.

METHODOLOGY (Measures) • Social Subsystem Issues • The social subsystem issues decision makers most frequently incorporate into their decisions are： productivity, quality, improved decision-making ability, labor savings, training, change management, communication with the employees about the new IT, and on-the-job learning curve. • Two items were created for each of these categories. One item represented implicit consideration of a specific social subsystem issue, and the other item represented explicit consideration of the same social subsystem issue.

METHODOLOGY (Measures) • Financial and Technical Issues • Based upon the exploratory interviews, five questions were developed to measure technical decision issues and three questions were developed to measure financial issues. • These questions were refined through the pilot process previously discussed. • The social subsystem, financial and technical issues scale used in this study were found to be internally consistent • The most common method of assessing the reliability of an instrument is through the use of Cronbach’s alpha.

METHODOLOGY (Measures) • Instrument Reliabilities Table

METHODOLOGY (Measures) • A important criterion for a well-developed survey includes validity, which is often discussed in terms of two distinguishable types：content and construct. • The content validity of the survey was established in two ways. • First, the items were derived from the exploratory interviews with IT executives. • Second, the field experts who participated in the pilot study gave written and oral feedback concerning the survey. • The construct validity determines whether the scale measures what it purports to measure. • Orthogonal rotation

METHODOLOGY (Measures) • Scenario 1

METHODOLOGY (Measures) • Scenario 2

METHODOLOGY (Measures) • Factor Analysis

METHODOLOGY (Demographic Profile) • Surveys were mailed to 1515 firms. • 1242 were deliverable • 200 firms replied (16% response rate) • Responses were received from firms in 37 states. • Median annual revenue of the firms was reported as $150 million. With a median annual IT budget of $1.7 million. • Median number of employees in these firms was 650 with a median of 17 IT workers. • 28% of the firms were non-profit organizations. • 125 responded service, 68 manufacturing, 7 save no response. • 2% of those who responded were presidents, 50% were vice presidents or directors of IS/IT, 34% held the title of CIO or IS/IT manager, 4% CFO or controllers, and 10% held some other title. • 78% of the respondents were male. • The executives’ average tenure in their current position was 7.2 years (median =5 years) and their average age was 47. • The average number of years the executives had made IT decisions was 13.2 years and 72% had spent as least half their career in information system.

RESULT • Means of Decision Issues by Type of Decision

RESULT • Means of Implicit Versus Explicit Social Subsystem Issues by Type of Decision

RESULT • Differences in the Means of Implicit Versus Explicit Social Subsystem Issues Low Disruption Decision.

RESULT • Implicit Versus Explicit Consideration----Low Process Disruption Decision

RESULT • Implicit Versus Explicit Consideration----High Process Disruption Decision

RESULT • Differences in the Means of Implicit Versus Explicit Social Subsystem Issues High Disruption Decision.

DISCUSSION • The predominance of financial consideration is congruent with prior research that indicates that organizations often require IT investments to be evaluated using traditional financial measures such as net present value and return on investment. • The technical issues were secondary to financial issues in both decision types. This is somewhat surprising. • There appears to be a need for procedures that consider the effect an IT will have on productivity, the end-users learning curve, and change management.

LIMITATIONS • First, this study is cross-sectional. Therefore, no long-term trends or causal inferences can be established. • Common method variance is another possible limitation of this study. Because all the data were obtained from one executive per organization, concerns might arise regarding potential respondent biases which might constitute systematic error.

CONCLUSION • The greater the disruption, the more effort and resources should be expended in evaluating the social subsystem implications.

Inclusion of Social Subsystem Issues in IT Investment Decisions : An Empirical Assessment