An Examination of Two Screen/Report Design Variables in an Information Recall Context*

Screen/report design for output organization is still very much a common sense-driven activity. This paper identifies a preliminary set of factors beyond display format for examination as screen/report design variables. A laboratory experiment was conducted to assess the influence of one of these factors, spatial layout of information, along with display format in an information recall context. Individual imagery orientation (verbalizer/visualizer) was used as a moderating variable in the experimental design. The findings indicate that spatial layout of information significantly influenced performance when the recall task involved pattern detection. In fact, a central location of data in a document was the most conducive to pattern recall performance. Further, terminal items facilitated pattern recall better than early input items. With respect to display format, the results support previous findings that a tabular display enhances performance for point-value recall tasks while graphs exhibit an edge over tables for pattern types of recall tasks. Overall, the verbalizers demonstrated a complete supremacy in performance. Interaction between individual imagery orientation and display format indicates that, while the verbalizers and the mixed type were immune to display format variations, the graphical stimulus enhanced the pattern recall performance of the visualizers.     

An Empirical Investigation of the Effects of Decision Aids on Problem-Solving Processes*

Despite the growing number of investigations examining decision support systems (DSS), relatively few empirical studies have evaluated the effects of DSS on problem-solving processes. This study uses protocol analysis to investigate the impact of a specific decision aid on problem-solving processes in a semi-structured problem. Results indicate that decision aids influence the problem-solving processes of decision makers. The effect of a decision aid is found to be contingent on familiarity with the decision aid, task familiarity, and the interaction of these two factors. Suggestions for incorporating interaction effects and problem-solving processes into future examinations are proposed.     

Rule-Based Expert Systems and Linear Models: An Empirical Comparison of Learning-By-Examples Methods*

Building models of expert decision-making behavior from examples of experts’ decisions continues to receive considerable research attention. In the 1960's and 70's, linear models derived by statistical methods were studied extensively. More recently, rule-based expert systems derived by induction algorithms have been the focus of attention. Few studies compare the two approaches. This paper reports on a study that compared linear models derived by logistic regression with rule-based systems produced by two induction algorithms—ID3 and the genetic algorithm. The techniques performed comparably in modeling the experts at one task, graduate admissions, but differed significantly at a second task, bidder selection.     

Interaction Between Concurrent Transactions in the Design of Distributed Databases

A distributed database system allows concurrent execution of transactions from multiple users at multiple locations. This paper presents a general scheme of including the effect of interaction between such transactions in the design process of distributed databases. This scheme allows the decision maker to choose the most appropriate design for a distributed database. The interaction effect is a consequence of concurrency control procedures and contention for system resources. Prior research has not included all components of the interaction effect in the design process. A separate module, called an interaction module, was built to measure the interaction effect using a comprehensive simulation model of a general purpose relational distributed database management system (DBMS). The interaction module can be interfaced with any distributed database design system as an add-on module so that the interaction effect can be included in the design process. A detailed example demonstrates the use of the interaction module in the decision-making process. Experiments conducted using the module show that the interaction effect can be significant and that it can affect the choice of the design. Experiments were also conducted to measure the sensitivity of design choices under changing input conditions.     

Feedback in DSS as a Source of Control: Experiments with the Timing of Feedback

Well-designed feedback can improve decision making but to date there has been no comprehensive study of feedback in decision support systems (DSS) that could guide developers in its design. This work examines the opportunities and means to enhance cognitive control in decision making by providing appropriate feedback with DSS. It concentrates on the timing of feedback, which has been shown to affect the use of feedback and also demonstrates the potential advantages of using information technology over and above manual decision environments. Two experiments test the effects of controlling the timing of cognitive feedback on the user's cognitive control. The first tests the effect of timing one source of cognitive feedback, and the second tests the effect of timing two sources of feedback. The findings suggest that the design of feedback should become a routine part of the development of DSS.     

The Effects of Group Attitudes Toward Alternative GDSS Designs on the Decision-making Performance of Computer-Supported Groups*

Empirical investigations of the effects of group decision support systems (GDSS) accord relatively little attention to the role of attitudes developed by groups toward the GDSS. This study draws upon the theory of social influence to examine the role played by group attitudes in mediating the impact of GDSS designs on group decision-making performance. We found that, in addition to capabilities of GDSS designs, group attitudes toward GDSS were influential in affecting group decision-making performance. The managerial implications of the study are: (1) effective GDSS designs for supporting groups in equivocal decision-making contexts should include structures for communication and consensus support and (2) attempts should be made to enhance user attitudes toward the GDSS through design features of the GDSS, training, and facilitation of positive social influences within the group. The study also provides encouraging evidence about the value of social theories, such as the social influence model and the adaptive structuration theory, in investigating GDSS effects. Further, this study illustrates the value of the partial least squares (PLS) analysis method for testing holistic structural models of GDSS effects.     

Impact of Information Technology Integration and Lean/Just‐In‐Time Practices on Lead‐Time Performance*

Managers seeking to improve lead‐time performance are challenged by how to balance resources and investments between process improvement achieved through lean/just‐in‐time (JIT) practices and information technology (IT) deployment. However, extant literature provides little guidance on this question. Motivated by both practical importance and lack of academic research, this article examines empirically the relationships among interfirm IT integration, intrafirm IT integration, lean/JIT practices, and lead‐time performance using data from IndustryWeek's Census of Manufacturers ( IndustryWeek, 2006 ). The results provide several new insights on the relationship between IT integration and lean/JIT practices. First, the study confirms that implementing lean/JIT practices significantly reduces lead time. Second, lean/JIT practices mediate the influence of IT integration on lead‐time performance. This suggests that process improvements that result from lean/JIT practices are important contributors to the success of IT integration. Even companies that have experienced success in reducing lead time through lean/JIT practices may benefit from IT integration practices such as those embodied in enterprise resource planning systems. The findings provide managers with empirical evidence and a theoretical framework on the balance between lean/JIT and IT for effecting improvement in lead‐time performance, thus offering practical guidance on this important question. Future research is needed to extend the lean/JIT practices in this study to supply chain practices and explore the relationship between supply chain practices and IT integration.     

The Design of a Knowledge-Based Decision Support System to Support the Information Analyst in Determining Requirements

Decision support system (DSS) researchers and designers continue to look for unstructured organizational tasks where there is a critical need for intelligent computer-based support. One such decision task is information requirements determination. Requirements determination is recognized as the most crucial phase of the systems development life cycle. Unfortunately, most methodologies and CASE tools focus only on how to specify the requirements once they are determined. There is very little computer support for the process of determining requirements. This paper discusses the conceptual design and development of a knowledge-based DSS to support information analysts in the critical decision task of determining requirements for the design of effective information systems. The expert modeling support system has the expertise to assist the analyst in studying the organization as a whole and in modeling the system under study in the context of the overall organization's goals and needs. The focus of the paper is on the problems associated with building the knowledge base component of the intelligent decision support system. A prototype implementation of the system is described.     

An Alternative FMEA Method for Simple and Accurate Ranking of Failure Modes

Failure modes and effects analysis (FMEA) is a methodology for prioritizing actions to mitigate the effects of failures in products and processes. Although originally used by product designers, FMEA is currently more widely used in industry in Six Sigma quality improvement efforts. Two prominent criticisms of the traditional application of FMEA are that the risk priority number (RPN) used to rank failure modes is an invalid measure according to measurement theory, and that the RPN does not weight the three decision criteria used in FMEA. Various methods have been proposed to mitigate these concerns, including many using fuzzy logic. We develop a new ranking method in this article using a data‐elicitation technique. Furthermore, we develop an efficient means of eliciting data to reduce the effort associated with the new method. Subsequently, we conduct an experimental study to evaluate that proposed method against the traditional method using RPN and against an approach using fuzzy logic.     

Order Management in the Customization‐Responsiveness Squeeze*

Make‐to‐order (MTO) products may be either customized or standard, and customization can occur either at the configuration or component level. Consequently, MTO production processes can be divided into three customization gestalts: non‐customizers, custom assemblers, and custom producers. In this article, we examine how the multilevel nature of customization affects order management in processes that produce complex MTO products. We first empirically validate the existence of the three customization gestalts and subsequently, analyze the order management challenges and solutions in each gestalt in a sample of 163 MTO production processes embedded in seven different supply chains. In the analyses, we follow a mixed‐methods approach, combining a quantitative survey with qualitative interview data. The results show that important contingencies make different order management practices effective in different gestalts. Further qualitative inquiry reveals that some seemingly old‐fashioned practices, such as available‐to‐promise verifications, are effective but commonly neglected in many organizations. The results also challenge some of the conventional wisdom about custom assembly (and indirectly, mass customization). For example, the systematic configuration management methods—conventionally associated with project business environments—appear to be equally important in custom assembly.     

Automated Discovery in Managerial Problem Formulation: Formation of Causal Hypotheses for Cognitive Mapping

Development of knowledge acquisition techniques known as automated discovery systems has occurred in deep and narrow domains of knowledge. Automated discovery is the generation of new knowledge by a computer system on its own, without the help of another knowledge source. This paper describes research and validation of an automated discovery system for a wide and shallow domain—business management. The system continues recent advances in expert systems research which have enhanced cognitive mapping, a problem formulation tool. The system perceives the behavior of distal variables in the environment through probabilistic cues-to-causality, and generates previously unknown hypotheses by aggregating the probabilities into a single criterion of causal relatedness. The system is validated against the source code of a simulated managerial environment, and causal relationships posited by decision makers experienced in the play of the gaming simulator.     

An Empirical Investigation into Factors Relating to the Adoption of Executive Information Systems: An Analysis of EIS for Collaboration and Decision Support*

This study focuses on the organizational adoption of Executive Information Systems (EIS). A distinction is made between two related, complementary EIS capabilities—EIS for collaboration support (EIS_c) and EIS for decision support (EIS_d). EIS_c is relatively standardized and replicable, while EIS_d has to be developed in situ given the specific characteristics of the user and task. The adoption process is conceptualized as an initial transition from a state of nonadoption to adoption (adoption status) and subsequent internal propagation of the technology (adoption level). Data collected from a national survey are used to test hypotheses between identified contextual variables and the adoption status and adoption level of EIS_c and EIS_d. Adopters and nonadopters of both EIS_c and EIS_d do not differ in their organization size, suggesting that the traditional paradigm of “EIS as a technology for large firms” is no longer true. Environmental uncertainty is found to promote the transition from a state of nonadoption to adoption of both EIS_c and EIS_d while continuing to catalyze the internal propagation of EIS_d. While no differences are observed in IS department size between adopters and nonadopters of EIS_c, our results suggest that larger IS departments provide the resource base to explore the less standardized of the two capabilities, EIS_d. IS support is also found to be critical for the subsequent internal propagation of EIS_d. Furthermore, the adoption level of both EIS_c and EIS_d are found to be promoted by top management support. Implications of these results are discussed for the organizational adoption of EIS.     

An Evaluation of the Role and Performance of a Decision Support System in Business Education*

With the rapid growth in end-user computing, there has been an increasing demand on business schools to train managers in the use of computers for effective decision support. While computer-aided instruction (CAI) has been in vogue for over a decade, there are very few studies that evaluate the impact of computers on decision-making skills in a business education context. The study makes use of a controlled experiment to evaluate the impact of computers on the accuracy and quality of decision making in a business decision support context. It also addresses the relationships between decision performance and various student characteristics such as aptitude, attitude, domain experience, domain expertise, gender, and system experience. The study revealed that computer support positively influenced both dimensions of decision performance.     

Decision Making in an Automated Environment: The Effects of Anonymity and Proximity with a Group Decision Support System*

Recent advances in information systems technology have made it possible to support the work of interacting groups using networked personal computers. A laboratory experiment was conducted using a group decision support system to evaluate effects of anonymity and proximity on group process in automated group problem solving. Twenty groups of four persons each performed an idea-generating task using an interactive electronic brainstorming program. This experiment's main findings were: (1) Group members working anonymously and apart generated more comments. (2) Working in the same room increased satisfaction. (3) Highest levels of perceived system effectiveness were reported under anonymity.     

Information Systems Project Continuation in Escalation Situations: A Real Options Model

Software project escalation has been shown to be a widespread phenomenon. With few exceptions, prior research has portrayed escalation as an irrational decision‐making process whereby additional resources are plowed into a failing project. In this article, we examine the possibility that in some cases managers escalate their commitment not because they are acting irrationally, but rather as a rational response to real options that may be embedded in a project. A project embeds real options when managers have the opportunity but not the obligation to adjust the future direction of the project in response to external or internal events. Examples include deferring the project, switching the project to serve a different purpose, changing the scale of the project, implementing it in incremental stages, abandoning the project, or using the project as a platform for future growth opportunities. Although real options can represent a substantial portion of a project's value, they rarely enter into a project's formal justification process in the traditional quantitative discounted cash‐flow‐based project valuation techniques. Using experimental data collected from managers in 123 firms, we demonstrate that managers recognize and value the presence of real options. We also assess the relative importance that managers ascribe to each type of real option, showing that growth options are more highly valued than operational options. Finally, we demonstrate that the influence of the options on project continuation decisions is largely mediated by the perceived value that they add. Implications for both theory and practice are discussed.     

Does IO Economics Really Make the Case for Investments in IT: Comment on West and Courtney

West and Courtney [18] rely on industrial organization economics in general, and the economics of uncertainty in particular, for insights into the benefits of overcoming information constraints through information systems (IS) and improved information technologies (IT). This Comment argues that the IS researcher who looks to the economics of uncertainty to make a case for improved IT will only find support from a selective reading of a constantly expanding literature whose aims and inferences are easily misunderstood.     

A Simulation of Partial Information Use in Decision Making: Implications for DSS Design

Information matrices are often the output produced by a decision support system. These matrices are a common method for expressing a decision situation under different decision-making scenarios. The decisions involved in designing a decision support system to generate the information matrix are important and involve several cost and benefit components. A designer needs guidance in making effective design decisions in this context. Such guidance can be provided by considering the relationships among specific design decisions, costs, and benefits. The general objective of this study is to provide a comprehensive framework for this purpose. This study is the first to develop and present a comprehensive cost-benefit framework for evaluating design decisions for a variety of scenarios. The specific objective of this research is to provide guidance regarding the number of available information dimensions to incorporate in a computer-based decision aid. Simulation experiments are conducted with a completely specified model based on the cost-benefit framework (including needed assumptions) to evaluate how many information dimensions to include for a specific information matrix size to achieve a balance between information use costs and decision quality. Based upon extensive simulation analyses for a hypothetical decision maker, the practical guideline found for designers is to include only the top half of the relevant information dimensions in any specific decision support system. Over a large number of repeating choice decisions, the savings in cognitive effort and information gathering costs clearly offset relatively minor losses in decision quality.     

Information Systems Adaptation and the Successful Implementation of Advanced Manufacturing Technologies*

Few plants have initial success with advanced manufacturing technologies (AMTs), and adaptations are commonly required after installing new technologies. We especially know little about the outcomes of adaptations that manufacturers regularly employ in the context of AMTs. Sociotechnical theory and the technology literature suggest that AMTs commonly require four types of adaptations including those to process technologies, human resources, operational structures, and information systems. This study investigates which of these four adaptations and their interactions lead to improved operational performance. Data were collected on 104 plants that implemented a single type of manufacturing AMT. Findings indicate that information systems (IS) adaptation during the course of AMT implementation was the most important action. Surprisingly, human resource and process technology adaptations were linked to lower performance, and no interactions had any clear effects. The results also show that practitioners underestimated the relevance of IS adaptations during contemporary or “second-generation” AMT implementation projects and overemphasized the need for shop floor changes.     

A Note on Input Consistency in the Application of AHP

This is a response to the points raised by Wu [3] concerning my paper on the quantitative evaluation of data bases [4].     

Examining the Antecedents and Consequences of CIO Strategic Decision‐Making Authority: An Empirical Study*

Despite the strategic importance of information technology (IT) to contemporary firms, chief information officers (CIO) often still have varying degrees of strategic decision‐making authority. In this study, we apply the theory of managerial discretion to define CIO strategic decision‐making authority and argue that the CIO's level of strategic decision‐making authority directly influences IT's contribution to organization performance. We also draw on the power and politics perspective in the strategic decision‐making literature to identify the direct antecedents to the CIO's strategic decision‐making authority. A theoretical model is presented and empirically tested using survey data collected from a cross‐industry sample of 174 matched pairs of CIOs and top business executives through structural equation modeling. The results suggest that organizational climate, organizational support for IT, the CIO's structural power, the CIO's level of strategic effectiveness, and a strong partnership between the CIO and top management team directly influence the CIO's level of strategic decision‐making authority within the organization. The results also suggest that the CIO's strategic decision‐making authority in the organization directly influences the contribution of IT to firm performance and that effective CIOs have a greater influence on IT's contribution when provided with strategic decision‐making authority.