Designing IS service strategy: an information acceleration approach

Information technology-based innovation involves considerable risk that requires insight and foresight. Yet, our understanding of how managers develop the insight to support new breakthrough applications is limited and remains obscured by high levels of technical and market uncertainty. This paper applies a new experimental method based on “discrete choice analysis” and “information acceleration” to directly examine how decisions are made in a way that is behaviourally sound. The method is highly applicable to information systems researchers because it provides relative importance measures on a common scale, greater control over alternate explanations and stronger evidence of causality. The practical implications are that information acceleration reduces the levels of uncertainty and generates a more accurate rationale for IS service strategy decisions

Traveller Behaviour: Decision making in an unpredictable world

This paper discusses the nature and consequences of uncertainty in transport systems. Drawing on work from a number of fields, it addresses travellers’ abilities to predict variable phenomena, their perception of uncertainty, their attitude to risk and the various strategies they might adopt in response to uncertainty. It is argued that despite the increased interest in the representation of uncertainty in transport systems, most models treat uncertainty as a purely statistical issue and ignore the psychological aspects of response to uncertainty. The principle theories and models currently used to predict travellers’ response to uncertainty are presented and number of alternative modelling approaches are outlined. It is argued that the current generation of predictive models do not provide an adequate basis for forecasting response to changes in the degree of uncertainty or for predicting the likely effect of providing additional information. A number of alternative modelling approaches are identified to deal with travellers’ acquisition of information, the definition of their choice set and their choice between the available options. The use of heuristic approaches is recommended as an alternative to more conventional probabilistic methods

Integrating multicriteria decision analysis and scenario planning : review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of "metacriteria" (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country

Simplified models for multi-criteria decision analysis under uncertainty

Includes abstract.Includes bibliographical references.When facilitating decisions in which some performance evaluations are uncertain, a decision must be taken about how this uncertainty is to be modelled. This involves, in part, choosing an uncertainty format {a way of representing the possible outcomes that may occur. It seems reasonable to suggest {and is an aim of the thesis to show {that the choice of how uncertain quantities are represented will exert some influence over the decision-making process and the final decision taken. Many models exist for multi-criteria decision analysis (MCDA) under conditions of uncertainty; perhaps the most well-known are those based on multi-attribute utility theory [MAUT, e.g. 147], which uses probability distributions to represent uncertainty. The great strength of MAUT is its axiomatic foundation, but even in its simplest form its practical implementation is formidable, and although there are several practical applications of MAUT reported in the literature [e.g. 39, 270] the number is small relative to its theoretical standing. Practical applications often use simpler decision models to aid decision making under uncertainty, based on uncertainty formats that `simplify' the full probability distributions (e.g. using expected values, variances, quantiles, etc). The aim of this thesis is to identify decision models associated with these `simplified' uncertainty formats and to evaluate the potential usefulness of these models as decision aids for problems involving uncertainty. It is hoped that doing so provides some guidance to practitioners about the types of models that may be used for uncertain decision making. The performance of simplified models is evaluated using three distinct methodological approaches {computer simulation, `laboratory' choice experiments, and real-world applications of decision analysis {in the hope of providing an integrated assessment. Chapter 3 generates a number of hypothetical decision problems by simulation, and within each problem simulates the hypothetical application of MAUT and various simplified decision models. The findings allow one to assess how the simplification of MAUT models might impact results, but do not provide any general conclusions because they are based on hypothetical decision problems and cannot evaluate practical issues like ease-of-use or the ability to generate insight that are critical to good decision aid. Chapter 4 addresses some of these limitations by reporting an experimental study consisting of choice tasks presented to numerate but unfacilitated participants. Tasks involved subjects selecting one from a set of five alternatives with uncertain attribute evaluations, with the format used to represent uncertainty and the number of objectives for the choice varied as part of the experimental design. The study is limited by the focus on descriptive rather than real prescriptive decision making, but has implications for prescriptive decision making practice in that natural tendencies are identified which may need to be overcome in the course of a prescriptive analysis

Aligning Perspectives and Methods for Value-Driven Design

Recent years have seen a push to use explicit consideration of “value” in order to drive design. This paper conveys the need to explicitly align perspectives on “value” with the method used to quantify “value.” Various concepts of value are introduced in the context of its evolution within economics in order to propose a holistic definition of value. Operationalization of value is discussed, including possible assumption violations in the aerospace domain. A series of prominent Value-Centric Design Methodologies for valuation are introduced, including Net Present Value, Multi-Attribute Utility Theory, and Cost-Benefit Analysis. These methods are compared in terms of the assumptions they make with regard to operationalizing value. It is shown that no method is fully complete in capturing the definition of value, but selecting the most appropriate one involves matching the particular system application being valued with acceptable assumptions for valuation. Two case studies, a telecommunications mission and a deep-space observation mission, are used to illustrate application of the three prior mentioned valuation methods. The results of the studies show that depending on method used for valuation, very different conclusions and insights will be derived, therefore an explicit consideration of the appropriate definition of value is necessary in order to align a chosen method with desired valuation insights.Massachusetts Institute of Technology. Systems Engineering Advancement Research Initiativ

INVESTIGATION OF INDUSTRY 5.0 HURDLES AND THEIR MITIGATION TACTICS IN EMERGING ECONOMIES BY TODIM ARITHMETIC AND GEOMETRIC AGGREGATION OPERATORS IN SINGLE VALUE NEUTROSOPHIC ENVIRONMENT

Industry 5.0 acceptance is accelerating, but research is still in its infancy, and existing research covers a small subset of context-specific obstacles. This study aims to enumerate all potential obstacles, quantitatively rank them, and assess interdependencies at the organizational level for Industry 5.0 adoption. To achieve this, we thoroughly review the literature, identify obstacles, and investigate causal relationships using a multi-criteria decision-making approach called single value Neutrosophic TODIM. Single-valued Neutrosophic sets (SVNS) ensembles are employed in a real-world setting to deal with uncertainty and indeterminacy. The suggested strategy enables the experts to conduct group decision-making by focusing on ranking the smaller collection of criterion values and the comparison with the decision-making trial and evaluation laboratory method (DEMATEL). According to the findings, the most significant hurdles are expenses and the funding system, capacity scalability, upskilling, and reskilling of human labor. As a result, a comfortable atmosphere is produced for decision-making, enabling the experts to handle an acceptable amount of data while still making choices

Applications of Adaptive Decision Making Under Risk in Health Contexts

Research in multi-attribute decision making and how people adapt strategy selection to changes in information suggest an influence of the task environment such as increases in task complexity, time pressure, or difficulty. Decisions made within a health context provide similar scenarios in which the environment can affect multi-attribute decision making strategies. This study sought to understand the influence of the seriousness and prevalence of a disease on decision outcomes and decision-making processes within the context of vaccination. Twenty-nine participants viewed eight hypothetical scenarios involving illnesses reported in the local area or associated with travel. In the scenarios, four illnesses were described that were either low or high in terms of the seriousness of the illness as indicated by the symptoms associated with them, and the scenarios either described an instance where there was a high or low prevalence of the illness in the area. Participants then used this information to evaluate a matrix displaying four possible vaccines as decision alternatives, each with four attributes that could be used to determine the benefits of the vaccine or the costs associated with them. A mixed-model analysis was used to examine the effects of seriousness and prevalence on choice and decision strategy. The hypothesis that high seriousness and prevalence would result in decisions favoring a more effective (and thus, more expensive) vaccine was supported. Additionally, the hypothesis that high seriousness and prevalence would lead to participants using strategies that focus on the beneficial attributes was also supported. However, this effect of prevalence was larger than predicted compared to seriousness

Advancing the determinants of risky decision behaviour using conjoint and multi-level moderated mediation analysis

Investment decision-making is an everyday activity within society. When these decisions involve innovation and require a willingness to innovate, additional complexities arise concerning uncertainty and decision irreversibility. This thesis investigates to what extent predictions of investment decision-making behaviour may be made based upon how varying levels of uncertainty and irreversibility affect perceptions of risk, how this may affect decision behaviour and how the strength of this effect may vary depending upon decision-maker risk propensity. In doing so, this thesis addresses important gaps found to exist at an intersection of the theory of innovation diffusion, the basic theory of irreversible investment under uncertainty and prospect theory. The research methodology employed for this purpose comprises full-profile conjoint value analysis and multi-level moderated mediation analysis. An online survey comprising ten conjoint tasks enables the conjoint analysis and provides the means to measure both perceptions of risk and risk propensity. The online survey itself relies upon an established case study titled ‘Carter Racing’. The results of this research find that a comprehensive set of relationships exist among the variables in question, from which valid and useful predictions may be made. Where a risk-averse relationship is shown to exist between decision-making behaviour and measures of uncertainty and irreversibility, it can also be shown that these relationships are exerted through and explained by perceptions of risk, with decision-maker risk propensity serving to influence the strength of the effects. In these cases, a significant positive correlation is observed between perceptions of risk and both uncertainty and irreversibility. A significant negative correlation is also observed between perceptions of risk and a willingness to innovate, this being the means through which innovativeness is measured. However, where a risk-seeking relationship is shown to exist, no significant correlations or effects are observed. These findings have important implications for theory and practice