An empirical taxonomy of IS decision-making processes

Decisions to invest in information systems (IS) are made by many organisations on a very regular basis. Such decisions can vary from quickly identifying the problem, screening options and choosing a solution in a very straightforward way, to very extensive and repeated search, screen, design and negotiation activities which can take many years. There has been little explicit research into the process by which managers and organisations decide to develop IS applications. This research addresses this by analyzing 20 IS decision-making processes, using a phase-based as well as an attribute-based approach. Mintzbergs typology is used to characterize seven types of IS decisions from a phase-based or process-based perspective. For the attribute approach, the decisions have been analyzed on the basis of subjective/objective and offensive/defensive contrasts and placed in one of four categories: innovative, rational, necessary or political. The paper concludes by identifying five factors that result in major differences in IS decision-making processes. These issues are: (1) whether there is scope to design a solution, (2) whether distinct alternatives have to be searched for, (3) the degree of urgency and necessity from the perspective of the decision-makers, (4) whether the decision can be subdivided in order to follow a gradual process path (planned versus incremental) and (5) the number and power of stakeholders involved in the process and the extent that their interests vary and contrast. The paper suggests that managers deciding on IS applications should be aware of these factors in order to design a process that fits best with the specific circumstances: no single process should be considered universally applicable. This conclusion is in contrast with many decision-making models rooted in the MIS-field, which suggest to use prescriptive and rational approaches to organise IS decision-making processes.

Interpretative perspectives on the acceptance of an optional information system

Understanding the factors that contribute to the acceptance and use of information systems is a central concern in the field of information systems. Especially in cases where users are relatively free to use an information system (a so called optional information system) it is important for implementers to understand which factors determine acceptance in order to develop an effective design and implementation plan. In order to identify factors that determine acceptance, this report describes and analyses the implementation of a therapy expert system for general practitioners (GPs) in the Netherlands. The Netherlands Ministry of Health decided to implement this system with the objective to promote cost effectiveness, consistency and quality of therapies and drug prescriptions of general practitioners. This paper uses an interpretive perspective to analyze the limited acceptance of the system. While the promotion campaign focused on the system, GPs based their decision on wider contextual factors. The case demonstrates pitfalls, which come up during the implementation of such a system, and shows which factors may play a role in the decision of possible users to accept or reject such an optional information system. Different issues arise from this case. One is that users seem to differ from non-users and that perceptions about the system itself but also about non-system features affect the decision to accept. The paper uses the evidence of the case by suggesting to extend the technology acceptance model (TAM) with relevant contextual factors. It concludes by outlining its implications for implementers of optional information systems in general.

Analyzing inter-organizational systems from a power and interest perspective

Inter-organizational systems (IOS) are ICT-based systems that enable organizations to share information and to electronically conduct business across organizational boundaries. Especially since the increasing availability of the Internet, there have been less technological barriers to implement IOS. However, that does not imply that IOS-possibilities are implemented successfully in all occasions: other barriers may remain. Innovation is not only a technical process of ?solving problems?, it also involves economic and political processes in which interests are articulated, alliances are built and outcomes are struggled over. To explore this observation, this paper presents a model that helps to describe and analyze IOS from a power and interest perspective of multiple parties. To illustrate this model, eight case studies of IOS are discussed, of which two in more depth. After that, we will put the findings of the analysis in a broader perspective. The paper concludes with the assertion that the scope for the design of an effective IOS depends on a combination of technical, economic and social

Influence of artificial intelligence on the work design of emergency department clinicians:a systematic literature review

Objective: This systematic literature review aims to demonstrate how Artificial Intelligence (AI) is currently used in emergency departments (ED) and how it alters the work design of ED clinicians. AI is still new and unknown to many healthcare professionals in emergency care, leading to unfamiliarity with its capabilities. Method: Various criteria were used to establish the suitability of the articles to answer the research question. This study was based on 34 selected peer-reviewed papers on the use of Artificial Intelligence (AI) in the Emergency Department (ED), published in the last five years. Drawing on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, all articles were scanned, read full-text, and analyzed afterward. Results: The majority of the AI applications consisted of AI-based tools to aid with clinical decisions and to relieve overcrowded EDs of their burden. AI support was mostly offered during triage, the moment that sets the patient trajectory. There is ample evidence that AI-based applications could improve the clinical decision-making process. Conclusion: The use of AI in EDs is still in its nascent stages. Many studies focus on the question of whether AI has clinical utility, such as decision support, improving resource allocation, reducing diagnostic errors, and promoting proactivity. Some studies suggest that AI-based tools essentially have the ability to outperform human skills. However, it is evident from the literature that current technology does not have the aims or power to do so. Nevertheless, AI-based tools can impact clinician work design in the ED by providing support with clinical decisions, which could ultimately help alleviate a portion of the increasing clinical burden

The influence of cultural values on Enterprise System adoption, towards a culture – Enterprise System alignment theory

During the last decades, organizations worldwide have replaced their fragmented and home-grown information systems with standardized Enterprise Systems that span the entire organization. The logics embedded in Enterprise Systems, such as a centralized and integrated view on the firm, standardized organization-wide working processes, and data sharing, may or may not be congruent with the cultural context of the user organization. Especially in case of a limited alignment, the adoption and full use of the Enterprise System will require specific attention from implementers. By developing a theoretical explanation of how responses to Enterprise Systems are influenced by cultural values, we contribute to the development of a cultural alignment theory of Enterprise Systems. Drawing on Hofstede’s cultural values framework, we analysed 85 published cases from firms operating in different cultural contexts, which resulted in the modelling of two contrasting archetypical cultural profiles: one that is more, and one that is less, receptive to the logics embedded in Enterprise Systems. Our model provides implementers with the necessary insights to develop implementation strategies that take the cultural context into account

Tailoring the implementation of digital business: A diagnostic framework

This chapter proposes a diagnostic framework that guides managers to develop a situationally appropriate and tailored implementation strategy for digital business. We distance ourselves from the view that there is one way of implementing digital business that will be effective in all circumstances. Rather, we clarify how an implementation strategy for digital business depends on the characteristics of the digital technology, the stakeholders involved, and the organizational context in which the digital business system is implemented. Based on this insight, we propose a diagnostic framework for the implementation of digital business. The framework helps managers reflect on the complexity and risks involved from four domains of the digital business project and guides them in consciously developing a suitable implementation strategy. The framework suggests four generic types of digital business projects (uniform, pluriform, unfolding, and ambiguous) and proposes implementation strategies that match these types. The framework supports an open dialogue with primary stakeholders to develop a shared understanding of project characteristics and align them with an appropriate strategy. It will help managers develop a deeper understanding of their project early on and during the project, resulting in more tailored and flexible implementation trajectories