Images of Information Systems in the Early 21st Century

As we enter the 21st Century, we are confronted by waves of new technology and pressured by competitive forces to find the most effective and efficient uses of information systems (IS)in organizations. Periodically, it is useful to stand back and take a look at the IS field from a variety of perspectives. These perspectives create images of IS that offer the potential of generating new insights into the field as it moves forward. These images are created through the lens of metaphors. Metaphors have been used in IS to help explain many of its central concepts from systems development methodologies to human-computer interaction. This paper describes five metaphors for the field of IS itself. From these metaphors a set of challenges for IS researchers and practitioners is proposed

Recognizing Good Ideas: An Essential Skill of a Doctoral Student Advisor

Ideas are the driving force behind a doctoral thesis. It is the ideas inherent in a thesis that determine the impact that the thesis will have on research and practice. It is a doctoral student\u27s role to generate these ideas about thesis topics, about scope, and about methodology, but it is the advisor\u27s role to recognize the good ideas from the not so good ideas, and to help the student develop and complete a doctoral thesis. This paper explores the advisor\u27s role in recognizing good thesis ideas. One of Gary Dickson\u27s greatest skills is his ability to identify and encourage thesis ideas that are of high quality and high potential impact

Aligning business and information systems thinking: a cognitive approach

Business-information systems (IS) alignment has become an important strategic imperative for organizations competing in the global economy. Recent research (Reich and Benbasat [56]) indicates that building a shared understanding between business and IS executives is one way of strengthening this alignment. This paper describes a study that examines the cognitive basis of shared understanding between business and IS executives. Using Personal Construct Theory (Kelly [36]), this study uses cognitive mapping techniques to explore the commonal-ities and individualities in the cognition between these executives. Eighty business and IS executives in six companies participated in this study. The results indicate that a higher level of cognitive commonality is positively related to a higher level of business-IS alignment. This is supported by findings that greater diversity in cognitive structure and cognitive content of business and IS executives coincide with a lower level of alignment. Implications for practitioners and researchers are discussed

Assimilation of Flexible Information Technologies

This research focuses on the process of how flexible information technologies assimilate into work processes and become routinized in an organization’s activities. The success of this post-implementation phase is essential if organizations are to reap the benefits of their investments in these technologies. However, many organizations struggle to integrate them with their processes and consequently, do not fully realize the benefits and value of those technologies. We attempt to study IS assimilation using the grounded theory approach to respond to the call for researchers to take the sociomaterial nature of the IS phenomenon into account. To develop a better understanding of the sociomaterial findings of this research, we view these findings through the lens of the Imbrication concept in order to better explain how technology assimilates into organizational practices through gradual interactions of technological and social elements. Several implications for research and practice are discussed

POST-ADOPTION OF SOCIAL NETWORK SITES: A LITERATURE REVIEW AND A PROCESS FRAMEWORK

This article provides a comprehensive literature review about the post-adoption stage of social network sites (SNS) usage with the special focus on habitual use and terminating stages. The extant research has examined this topic mainly from two perspectives: namely, intentional and habitual. Findings from each of these two perspectives are synthesized and used to build a process model to better understand how different intentions and behaviors of users manifest in different stages of SNS post-adoption phase. The process model suggests that disturbances such as technical glitches and privacy leaks trigger users’ awareness of the ‘dark sides’ of habitual SNS use. In addition, the awareness of negative impacts of addictive use, which are perceived as threats, motivates people to switch from or quit SNS. This paper contributes to SNS research by synthesizing fragmented theoretical explanations and providing a visual tool that helps researchers to develop a deeper understanding of the dynamics in the SNS post-adoption phase. Practitioners will gain insights into how to retain existing users and better manage processes related to users who wish to quit

Strategic IT Experiments and Organizational Renewal: Getting There Faster By Taking Smaller Steps

The purpose of this paper is to develop practical theory for predicting whether different categories of strategic IT experiments – trials of innovative information technologies within established organizations – lead to varying degrees of organizational renewal. A new framework of categories of strategic IT experiments is developed. We propose that the most innovative strategic IT experiments may have theleast influence on organizational renewal while less innovative experiments have a greater influence. Longitudinal case studies of three organizations illustrate the framework

IT Industry Analysts: A Review and Two Research Agendas

The firms involved in analyzing the information technology industry (IT), such as Gartner, Forrester, and IDC, are reputed to have a major impact on both IT vendors and IT adopters through their influence over how IT actually is acquired and used. The purpose of this article is to take stock of the nascent stream of research on industry analysts that has developed in recent years in order to shed some light on the IT analysis industry―to analyze the IT industry analysts, if you will. Using an organizational field-level lens, we look at the business models of the firms that operate in this industry. We examine the main institutional work that the analysts in these firms perform as status arbiters, institutional carriers, network brokers, IT fashion setters, and knowledge entrepreneurs. We examine the competitive and institutional pressures faced by analysts in these firms. Finally, we propose two research agendas: (1) to study the impact that this industry has had, and could continue to have, on the IT industry as a whole, and (2) to study how the relationship between the academic information systems community and the IT analysis industry might co-evolve

Environmental Scanning and Business Insight Capability:_x000D_ The Role of Business Analytics and Knowledge Integration

Environmental scanning is an important process that helps organizations sense what is happening in their environments. However, environmental scanning has been found to be less effective than its proponents had hoped for. The problem appears to be that environmental scanning does not lead to the business insights that managers need to order to help their organizations survive and grow (LaValle et al., 2011). This paper reports a study into the role of data analytics and knowledge integration on environmental scanning and business insight capability. Fifteen in-depth interviews were conducted with data analytics professionals to get a deeper understanding of how what they do impacts the results of environmental scanning processes and the generation of business insights. The results indicate data analytics and knowledge integration need to play a bigger role in the environmental scanning process if greater business insights are to be generated

THE IMPACT OF COMPUTER-BASED SUPPORT ON THE PROCESS AND OUTCOMES OF GROUP DECISION MAKING

Interactive computer-based systems to support group decision making (group decision support systems or GDSS) have received increased attention from researchers and practitioners in recent years. Huber (1984) argues that as organizational environments become more turbulent and complex, decisions will be required to be made in less time and with greater information exchange within decision making groups. Thus, it is imperative that studies be undertaken to determine the types and characteristics of group decision tasks most appropriate for support by a GDSS and to determine the features of a GDSS that will support those tasks. A number of prominent researchers in the field of group decision making (Shaw, 1973, 1981; Hackman and Morris, 1975; Fisher, 1974) agree that the decision task itself is probably the most important factor in determining group decision making effectiveness. The characteristics of group decision tasks are many and varied, but according to Shaw (1973) the level of difficulty/complexity of the decision is a fundamental factor in influencing the performance of the group. Some decisions are characterized by information that is clear, concise, easily communicable, and where relationships between important factors in the decision are easily understood. In short, these decisions require relatively little effort to make and are therefore called easy decisions. Decision tasks where the information to be considered in making the decision is incomplete, difficult to understand, and where complex relationships exist within the information available are called complex or difficult decisions. The role of decision task difficulty in the effective use of GDSS is considered ih this study. This research is an initial experimental study, exploratory in nature, that aims to get a first-level understanding of the impact of a computer-based DSS on group decision making. The group decision support system that is used in this study has only those features that specifically support group decision making (alternatives generation and communication, preference ranking and voting support). The reason for this approach is to start a program of research with a simple system in order to determine the particular impact of these features on, not only the outcomes of group decision making (such as decision quality), but on the process of group decision making as well. A controlled 2 x 2 factorial experiment was used to compare the decisions made by groups which had GDSS support with those groups that had no GDSS support and those with a high difficulty task to those with a low difficulty task. Figure 1 shows the relationship among the main variables in the study. The experimental task was a marketing business case in which the company was experiencing declining profits. Each group was asked to find the problem which was causing the declining profits. Difficulty was manipulated by modifying the data in the case. The setting for this experiment was a decision room designed and set up to accommodate face-to-face group interaction. The GDSS treatment entailed the use of one computer terminal per group member so that the GDSS could be used to support group decision making. Each group member in the GDSS treatment also had the use of a pencil, paper, a hand calculator, and a blackboard. For the non GDSS treatment, the terminals were removed and the group used just pencils, paper, hand calculators, and a blackboard to assist in making the decision. The computer hardware consisted of a DEC VAX 11/780 timesharing system using the VMS operating system, and DEC VT-102 terminals. The terminals were connected to the VAX 11/780 using 2400 baud direct lines. The GDSS called Decision Aid for Groups (DECAID) was designed, coded, and tested to make sure that it worked in the experimental setting. The approach to design was to implement the features, and then to refine the system through testing to make those features work as efficiently as possible. The GDSS software performed the basic functions of recording and storing and displaying alternatives that were entered by group members, aggregating and displaying preference rankings that had been entered for those alternatives, and recording votes (either publicly or anonymously) for the various alternatives generated. The system was easy to use and menu driven. Eighty four senior undergraduate business administration students participated in the study. These subjects had taken at least one course each in management science/decision analysis techniques, marketing, management theory/organizational behavior, and all had exposure to case analysis techniques. All subjects had been given training in the use of the GDSS. Measures were taken of decision outcomes (decision quality, decision time, decision confidence, satisfaction with group process, and amount of GDSS usage), and decision process variables (number of issues considered, number of alternatives generated, and participation in the decision making). Decision quality was measured along two dimensions: (1) decision content - how close did the group\u27s decision come to that made by a panel of experts; and (2) decision reasoning -- how similar the group\u27s reasoning in arriving at their decision was to the reasoning of the experts. Decision time was defined as the length of time it took the group to reach a consensus decision. Decision confidence and satisfaction with the group process were measured by individual responses to a post- test questionnaire. The individual responses were then aggregated to give a group value. The amount of GDSS usage was measured by examining the computer logs that were kept during the GDSS sessions. Decision issues were defined as factors that were important in the analysis of the case. Decision alternatives were defined as those issues in the case that the group analyzed as being the possible major problems in the case and hence, possible solutions to the decision task. Participation was measured by counting the number of task related comments made by each individual group member. Issues, alternatives and participation were determined by analysis of the video and audio tapes that were made of the experimental sessions. The major findings of the study are: 1. Decision quality is enhanced when decision making is supported by a GDSS, particularly for high dificulty tasks. 2. Decision time is not affected by use of a GDSS. 3. Confidence in the group decision and satisfaction with the decision making process are reduced when a GDSS is used, irrespective of task difficulty. 4. The number of alternatives considered is increased when a GDSS is used to support group decision making. 5. Participation in the group decision making process is unaffected by GDSS support or by decision task difficulty. The paper concludes by suggesting directions for future research into GDSS. Work is needed to determine the effectiveness of additional features of a GDSS (such as other communication features, modeling features, etc.), to understand the impact of GDSS on the different phases of decision making, and to examine the effect of repeated use of a GDSS on the quality of group decision making

Information Systems Control: A Review and Framework for Emerging Information Systems Processes

A major stream of information systems (IS) research examines the topic of control, which focuses on attempts to affect employee behavior as a means to achieve organizational objectives. Despite a rich history of IS control research, approximately 90 percent of the publications focus on only three IS processes: managing information systems development, managing IS outsourcing, and managing security. However, the emergence of new IS processes and technologies with distinct control challenges, such as managing enterprise architecture and managing innovation, highlights a need to consider the wider applicability of past control insights. In this paper, we first integrate existing IS control constructs and relationships into a comprehensive IS control model. Second, we apply this model to emerging IS processes to guide future research and practice. We review 65 influential IS control-related journal papers and identify five control dimensions. We then consolidate these dimensions into a single, integrated model to apply past IS control findings to the challenges of emerging information systems by posing a series of related propositions. With this paper, we position current IS control research to be increasingly applicable and relevant to tomorrow’s emerging IS opportunities and challenges