Decision support systems unfrastructure: The root problems of the management of changing IT

doi:10.1016/j.dss.2008.02.003

Decision Support Systems

Volume 45, Issue 4, November 2008, Pages 833-844

https://doi.org/10.1016/j.dss.2008.02.003 Get rights and content

Abstract

Rapidly emerging IT underpins decision support systems, but research has yet to explain the IT management challenges of such rapid change. This study sought to understand the problems of rapid IT change and the interrelationships between them. It used structured interviews with 16 IT professionals and 246 useable responses from a survey of 1000 such professionals. After identifying five problem categories, it proposed and tested theory that Vendor Competitiveness leads to Poor Quality, Incompatibility, and Management Confusion, and these increase Training Demands. Besides the theory, the research contributes a survey instrument and focal points to help IT managers better provide the infrastructure for DSS.

Introduction

Information technology is increasing in capability and decreasing in cost. At the same time, organizations are deploying new IT at a greater rate [17] and applying new IT at the center of more areas of the business to improve management decision making [65]. This state of continuous IT change is not only producing ways to use new IT to compete [25], but also elevating the importance of IT infrastructures [124]. Emerging technologies, such as enterprise systems, provide significant decision support benefits [58]. As a result, how well the introduction of new IT is managed determines its strategic impact [110]. Success in this turbulent environment requires change-ready IT capability, i.e. the ability to deliver strategic IT solutions quickly [30], [91].

Because “the IT industry is complex, uncertain, and ever changing [102, p. 45],” the problems of managing IT today are growing more and more complicated. Moreover, complex interrelationships between IT management problems can exacerbate matters. Thus more needs to be known about the IT management problems that arise specifically from rapid IT change and the interrelationships between them [12].

At the same time, combined with a corporate culture more aware of, accepting of, and most importantly, dependent on IT, such change has propelled IT into an increasingly visible role in more and more organizations. This has heightened the importance of managing IT in these organizations, and thus of understanding the challenge of managing today's rapidly changing IT. An understanding of the challenge of managing today's rapidly changing IT might enable management to increase the value IT delivers, an established concern of IT executives [79].

Information technology as defined herein is any hardware or software used to build, operate, or maintain an organization's IS applications including decision support tools and technologies as well as the IT infrastructure of transaction processing systems, ERP systems, servers, networks, and B2C and B2B websites that enable those applications to function. IT thus comprises not only the decision support tools themselves, but also the tools for developing the underlying functional aspects of a DSS [18]. The study investigated the recent problems of the major IT projects in organizations.

The goals of this research were to better understand the problems of rapid IT change and the interrelationships between them in order to improve the acquisition and implementation of new IT that provides the infrastructure for decision support systems. The research employed qualitative and quantitative data collection in two separate phases. It used the qualitative data from the first to generate an instrument to gather the quantitative data in the second. It then applied both exploratory and confirmatory data analyses as well as structural equation modeling to the quantitative to generate and test new theory to explain the intricacies of the challenges of rapid IT change. In doing so, it attempted to answer two research questions:

What problems from rapid IT change affect IT management?
How are the problems from rapid IT change interrelated?

Section snippets

Practical basis of the research

“One of the greatest difficulties confronting IT managers is adapting to rapid change [47, p. 1].” The challenge is not new. In recent years, the world has been changing so rapidly that managing in a steady state is no longer possible. “The need to adapt and change continuously has become a given in managerial life. In no other domain has this observation been more relevant than the field of information technology [81, p. 109].” Such IT change is replete with “startling innovations and drastic,

Theoretical basis: uncertainty caused by environmental change

Studies have long documented the problems associated with an uncertain environment. As uncertainty increases, problems occur [46]. For example, the uncertainty of emerging technologies has disrupted organizations and industries [36]. Researchers have portrayed a changing environment as causing problems to which organizations adapt [23], [73], [95], [118], [126]. Organizations try to adapt by ameliorating the problems through the reduction of the uncertainty [46].

IT is a dimension of the

Overview of research approach

The research applied accepted techniques for generating grounded theory by collecting a vast number of qualitative facts to achieve generality and by using diverse data from interviews to make the theory representative of everyday realities [49]. The research thus began with structured interviews to identify the problems from rapid IT change [29]. The problems formed the basis of a postal survey. Exploratory factor analysis (EFA) reduced the number of items into a theoretically sound set of

Data analysis for question 1: What problems from rapid IT change affect it management?

The data analysis began with EFA to answer the first research question (What problems from rapid IT change affect IT management?). The answers to this first question would then be a set of constructs applied to resolve the second question (How are the problems resulting from rapid IT change interrelated?). Thirty-nine items were too many to make sense of, but a few categories could facilitate a clear understanding.

The EFA used the principle factor method with promax oblique rotation on the

Question 1 discussion: problem categories

The EFA produced five IT problem categories: Training Demands, Incompatibility, Poor Quality, Management Confusion, and Vendor Competitiveness. These empirically answer the first research question, What problems from rapid IT change affect IT management? Each category of problem can produce delays, cost overruns, and unexpected work in IT efforts. They provide a succinct basis for an explanation of IT management problems due to rapid IT change.

The problems have some foundation in prior research

A framework for question 2: How are the problems from rapid it change interrelated?

This research sought to understand the interrelationships among the problem categories under the presumption that some of them contribute to the severity of others, with the possibility of one or more as root causes. A closer look at the problems suggests a root problem and their potential relationships. The relationships are expressed as six propositions.

First, the rush to make products available may confuse the vendors' customers, namely IT managers [34]. The shear numbers of new IT increase

Model analysis

PLS Graph version 3.00 was applied to confirm the measurement model and test the path model. PLS Graph is a component-based, structured equation modeling tool that employs least squares estimation in contrast to the covariance-based approach used by such tools as LISREL, EQS, and AMOS. PLS is often used because it places fewer demands on sample size, scales, and data distribution assumptions [27], [44], [125].

The five problem categories, with their manifest variables loading on them in the EFA,

Question 2 discussion: problem category interrelationships

The data analysis confirmed the causal model and answered the second research question, How are the problems from rapid IT change interrelated? The results were thus consistent with the expectation that Vendor Competitiveness, as root problem, increases Management Confusion (P1), Incompatibility (P2), and Poor Quality (P3). The rush to move products rapidly into the market would seem to increase the complexity of IT management, reduce their ability to work together, and reduce the quality of

Implications for research

Implications for practice

This research identified five problem categories - Vendor Competitiveness, Poor Quality, Incompatibility, Management Confusion and Training Demands. These findings provide focal points for IT managers for examining their own organizational problems. Such managers should understand the extent to which they encounter them and how they respond to them. Such examination could help them avoid or reduce the impact of the problems.

In addition to the problem categories, the individual items provide the

Conclusion

This paper makes a variety of contributions to DSS research and practice. First, it raises researchers' and practitioners' awareness of the challenges of rapidly changing technology. It does so by identifying five categories of the problems of such change: Vendor Competitiveness,Poor Quality, Incompatibility, Management Confusion, and Training Demands.

The paper contributes by generating new theory, as well as by demonstrating how to combine qualitative and quantitative data collection efforts,

John “Skip” Benamati is an associate professor of MIS in the Farmer School of Business at Miami University, Oxford, OH. Dr. Benamati's research interests are changing IT, IT management/strategy, and electronic commerce. His work has appeared in the Journal of Management Information Systems, Journal of Organizational Computing and Electronic Commerce, Communications of the ACM, Information and Management, and elsewhere.

References (129)

R. Agarwal et al.
Targeting COBOL programmers for C training: the role of job insecurity and organizational tenure
Journal of Systems and Software
(1997)
F. Bergeron et al.
Ideal patterns of strategic alignment and business performance
Information and Management
(2004)
H.K. Bhargava et al.
Progress in Web-based decision support technologies
Decision Support Systems
(August 2007)
Bhattacherjee
Management of emerging technologies: experiences and lessons learned at US West
Information and Management
(1998)
F. Burstein et al.
Decision support in an uncertain and complex world
Decision Support Systems
(August 2007)
A. Gupta et al.
Digital signature: use and modification to achieve success in next generational e-business processes
Information and Management
(2004)
C.W. Holsapple et al.
ERP plans and decision-support benefits
Decision Support Systems
(2005)
S.A. Lippman et al.
Preemptive innovation
Journal of Economic Theory
(1993)
R. Montealegre
Managing information technology in modernizing 'against the odds': lessons from an organization in a less-developed country
Information and Management
(1998)
N. Mukherji et al.
A decision support model for optimal timing of investments in information technology upgrades
Decision Support Systems
(2006)

T. Nakashima et al.

Analysis of software bug causes and its prevention

Information and Software Technology

(1999)

D.A. Aaker et al.

The perils of high-growth markets

Strategic Management Review

(1986)

R. Agarwal et al.

Time flies when you're having fun: cognitive absorption and beliefs about information technology usage

MIS Quarterly

(2000)

T.J. Allen et al.

Information Technologies and the Corporation of the 1990's

(1994)

J.C. Anderson et al.

Structural equation modeling in practice: a review and recommended two-step approach

Psychological Bulletin

(1988)

Anonymous

CIOs still feel besieged

ComputerWorld

(August 14 1995)

Anonymous

The competition steams up

Journal of Accountancy

(1998)

Computer Weekly

(October 31 2002)

T. Burns et al.

The Management of Innovation

(1961)

C.G. Ceglieski et al.

Emerging information technologies: Developing a timely IT strategy

Communications of the ACM

(2005)

P.Y. Chen et al.

Can Vendors Influence Switching Costs and Compatibility in an Environment with Open Standards

MIS Quarterly

(August 2006)

W.W. Chin

(September 1 1997)

R.A. D'Aveni

Coping with hypercompetition: Utilizing the new 7S's framework

Academy of Management Executive

(Aug 1995)

G.B. Davis et al.

Auditing Advanced EP Systems: A Survey of Practice and Development of a Theory

(1983)

G.S. Day et al.

Avoiding the pitfalls of emerging technologies

California Management Review

(Winter 2000)

T. Deiderich

Top execs rate tech a priority

ComputerWorld

(April 13 1998)

D.A. De Vaus

Surveys in Social Research

(1986)

C. Dickerson

The top 20 IT mistakes

InfoWorld

(November 22 2004)

W.R. Dill

Environment as an influence on managerial autonomy

Administrative Science Quarterly

(1958)

F. Edelman

The management of information resources - a challenge for American business

MIS Quarterly

(1981)

F.E. Emery et al.

The causal texture of organizational environments

Human Relations

(1965)

R.G. Fichman et al.

Adoption of Software Engineering Process Innovations

Sloan Management Review

(1993)

C. Fornell et al.

Two structural equation models: LISREL and PLS applied to consumer exit-voice theory

Journal of Marketing Research

(1982)

Cited by (26)

Development and psychometric evaluation of the cloud computing acceptance questionnaire for academic libraries
2021, Journal of Academic Librarianship
Citation Excerpt :
Lack of necessary facilities and training makes the academic librarians reluctant to accept IT changes, which can hinder the development of the library (Islam & Islam, 2007). The use of IT to coordinate organizations in the face of environmental changes and gain flexibility is inevitable, necessary and desirable (Lederer, 2008). One of these technologies is cloud computing.
Cloud computing is a new technology that drives libraries to create and share knowledge, leading to the cost reduction, easy management, and unlimited data storage capacity. Given the importance of cloud computing technology and the lack of tools to investigate the factors affecting cloud computing acceptance in academic libraries; therefore, the aim of present study was to perform the development and psychometric evaluation of the cloud computing technology acceptance questionnaire for academic libraries. This study is a methodological research. After defining the concept of cloud computing acceptance, the initial version of the questionnaire consisting of 43 items and 11 components was designed. Then, face and content validity were used to assess validity, and Cronbach's alpha coefficient and intra-class correlation coefficient (ICC) were used to determine reliability. The results showed that the questionnaire has acceptable face validity (more than 1.5) and content validity (0.79). The Cronbach's alpha coefficient and the intra-class correlation coefficient were 0.77 and 0.92, respectively. In this study, for the first time, a tool was designed to evaluate the acceptance of cloud computing technology in academic libraries. Due to the fact that this tool has acceptable validity and reliability, it can be used in various studies and surveys.
Failure factors in the control of large-scale business intelligence systems development projects case study of an advanced engineering finn in Mexico
2019, IFAC-PapersOnLine
Failed automation systems engineering projects are difficult to study and there is a lack of case studies regarding these projects. The literature over-represents ERP projects in western countries and theories of antecedents of failure are derived from data collected on ERP projects in the West. Studies from Mexico are almost absent. Also, intelligent applications for businesses are now very topical but few cases focussing on failure factors in business intelligence (BI) projects have appeared. This is in spite of the importance of business intelligence applications for firms in less developed economies in an increasingly globalised economy. This paper presents a challenged project for a complex business intelligence solution in Mexico. It compares ranked failure factors based on academic literature to the Mexican case. Whilst the comparison reveals that similar factors are failure antecedents, their relative importance is different, opening possibilities for further investigations.
Evolutionary optimization of model specification searches between project management knowledge and construction engineering performance
2013, Expert Systems with Applications
Many studies have attempted to specify alternative model configurations as fitting empirical data with the aid of structural equation modeling (SEM) method. However, significant path searching between constructs has increased in difficulty and complexity. One way to enhance modeling efficiency is evolutionary optimization by genetic algorithm (GA). This study applies the project management (PM) knowledge possessed by construction personnel and uses techniques, tools, and skills (TTS) to explore the causal relationship between TTS usage and construction engineering project performance (PP). A questionnaire survey is used to empirically measure the effectiveness of PM TTS on PP. The research framework is first defined by hypotheses supported by the literature. The GA is then applied to the model fitting process to optimize the structural paths. Analytical results show that evolutionary optimization for singular and multiple goodness of fit effectively searches the SEM specifications. By using GA in SEM procedure, researchers can perform automated specification searches to find the best empirical model fit to the data.
A use of DEA-DA to measure importance of R&D expenditure in Japanese information technology industry
2013, Decision Support Systems
Citation Excerpt :
Information Technology (IT) heavily depends upon the development of telecommunications and consumer electronic devices that provides Internet and other various types of information system with global technology infrastructure by connecting computers and other communication systems in the world [2,5,7,24,33].
This study discusses a use of DEA–DA (Data Envelopment Analysis–Discriminant Analysis) to assess the corporate value of IT (Information Technology) firms and other manufacturing firms. It is widely known that Tobin's q is a ratio that serves as a measure of corporate value. This study explores a linkage between DEA–DA (as a methodology) and Tobin's q (as a theoretical basis for corporate performance) via the measurement of Altman's Z score (as a financial performance). The Z score provides us with aggregated information regarding financial ratios and other financial measures that investors usually examine in their investment decisions. This study applies the proposed approach to compare between Japanese IT and manufacturing firms. The empirical evidence obtained in this study indicates that R&D (Research and Development) expenditure enhances the corporate value of Japanese IT and manufacturing firms. However, the R&D expenditure of IT firms is important but not essential, compared with other manufacturing firms in Japan. The empirical result is inconsistent with the opinion of many corporate leaders and individuals who are associated with the IT industry. They believe that the R&D expenditure is essential for the Japanese IT industry to maintain its international competitiveness in the global market. In addition to the R&D expenditure, the empirical study indicates that IT leaders need to pay attention to the reduction of an R&D cycle time to enhance their competitiveness because a market cycle time of IT products is less than that of the other manufacturing products. The findings on Japanese IT and manufacturing industries are applicable to other industrial nations.
Critical factors and risk allocation for PPP policy: Comparison between HSR and general infrastructure projects
2012, Transport Policy
Citation Excerpt :
For the reliability test, Cronbach α coefficients are calculated. Moreover, to assess the fitness of the proposed measurement model, the criteria for validating the model fit are found, including χ2/dof (Hayduk, 1987), GFI (Scott, 1994), CFI (Bagozzi and Yi, 1988), and IFI (Benamati and Lederer, 2008). The most common analytical software systems are linear structural relationships (LISREL), analysis of moment structure (AMOS), and EQS (Chin, 1998).
This study compared the use of public–private partnership (PPP) policy between high speed rail (HSR) projects and general infrastructure projects. Based on extensive literature reviews, drivers for adopting PPP strategy, critical success factors, and preferred risk factor allocation were collected to design a structural questionnaire for professionals in Taiwan and to elicit their PPP project experience. Analytical findings reveal that most experience learnt from general infrastructure projects is applicable in HSR projects after proper modification. This study provides a valuable reference for stakeholders interested in executing HSR via PPP.
Development of a structural equation modeling-based decision tree methodology for the analysis of lung transplantations
2011, Decision Support Systems
Citation Excerpt :
These advantages make SEM more powerful than factor analysis and multiple linear regression. Therefore, it has been widely used in the information systems (IS), information technology (IT), and operations management (OM) areas [2,3,41,43,60], yet have not been very popular in the medical field as widely. Although abovementioned studies reveal very useful initial knowledge for the organ transplantation field based on the classical statistical assumptions adopted, they still have some limitations as follows: (1) They implicitly ignore the fact that the predictive variables may not necessarily be independent of each other.
Lung transplantation has a vital role among all organ transplant procedures since it is the only accepted treatment for the end-stage pulmonary failure. There have been several research attempts to model the performance of lung transplants. Yet, these early studies either lack model predictive capability by relying on strong statistical assumptions or provide adequate predictive capability but suffer from less interpretability to the medical professionals. The proposed method described in this paper is focused on overcoming these limitations by providing a structural equation modeling-based decision tree construction procedure for lung transplant performance evaluation. Specifically, partial least squares-based path modeling algorithm is used for the structural equation modeling part. The proposed method is validated through a US nation-wide dataset obtained from United Network for Organ Sharing (UNOS). The results are promising in terms of both prediction and interpretation capabilities, and are superior to the existing techniques. Hence, we assert that a decision support system, which is based on the proposed method, can bridge the knowledge-gap between the large amount of available data and betterment of the lung transplantation procedures.

View all citing articles on Scopus

Albert L. Lederer is a professor of MIS in the C. M. Gatton College Business and Economics at the University of Kentucky, Lexington, KY. His research focuses on information systems planning. His work has appeared in Decision Support Systems, Journal of Organizational Computing and Electronic Commerce, MIS Quarterly, Information Systems Research, Decision Sciences, IEEE Transactions, and elsewhere.

¹: Tel.: +1 859 257 2536; fax: +1 859 257 8031.

View full text

Decision support systems unfrastructure: The root problems of the management of changing IT

Abstract

Introduction

Section snippets

Practical basis of the research

Theoretical basis: uncertainty caused by environmental change

Overview of research approach

Data analysis for question 1: What problems from rapid IT change affect it management?

Question 1 discussion: problem categories

A framework for question 2: How are the problems from rapid it change interrelated?

Model analysis

Question 2 discussion: problem category interrelationships

Implications for research

Implications for practice

Conclusion

Journal of Systems and Software

Information and Management