Decision support for selecting a shortlist of electricity-saving options: a modified SMAA approach

This paper describes an application providing decision support for generating a shortlist of promising electricity-saving options for households in South Africa. The decision problem is characterised by constraints on time and other resources, and by substantial uncertainty around the preferences for energy-related attributes and the performance of alternatives on those attributes. We use a stochastic multi-criteria acceptability analysis model to incorporate preferential uncertainties, and adapt this for use with quantiles and other "simplified" formats for representing uncertain attribute evaluations

Project management decisions with uncertain targets

Project management decisions with uncertain target

The Optimization Ordering Model for Intuitionistic Fuzzy Preference Relations with Utility Functions

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Intuitionistic fuzzy sets describe information from the three aspects of membership degree, non-membership degree and hesitation degree, which has more practical significance when uncertainty pervades qualitative decision problems. In this paper, we investigate the problem of ranking intuitionistic fuzzy preference relations (IFPRs) based on various non-linear utility functions. First, we transform IFPRs into their isomorphic interval-value fuzzy preference relations (IVFPRs), and utilise non-linear utility functions, such as parabolic, S-shaped, and hyperbolic absolute risk aversion, to fit the true value of a decision-maker's judgement. Ultimately, the optimization ordering models for the membership and non-membership of IVFPRs based on utility function are constructed, with objective function aiming at minimizing the distance deviation between the multiplicative consistency ideal judgment and the actual judgment, represented by utility function, subject to the decision-maker's utility constraints. The proposed models ensure that more factual and optimal ranking of alternative is acquired, avoiding information distortion caused by the operations of intervals. Second, by introducing a non-Archimedean infinitesimal, we establish the optimization ordering model for IFPRs with the priority of utility or deviation, which realises the goal of prioritising solutions under multi-objective programming. Subsequently, we verify that a close connection exists between the ranking for membership and non-membership degree IVFPRs. Comparison analyses with existing approaches are summarized to demonstrate that the proposed models have advantage in dealing with group decision making problems with IFPRs

Proposta de aprendizagem da metodologia Kansei Engineering no curso de Design de produto

Orientadora: Profª Viviane Gaspar Ribas El MarghaniDissertação (mestrado) - Universidade Federal do Parana, Setor de Artes, Comunicação e Design, Programa de Pós-Graduação em Comunicação. Defesa: Curitiba, 28/02/2014Inclui referênciasÁrea de concentração : Design gráfico e de produtoResumo: A metodologia Kansei Engineering (KE) foi desenvolvida como uma tecnologia orientada para o consumidor com a finalidade de aprimorar o desenvolvimento de novos produtos. É definida como "tecnologia que traduz os sentimentos do consumidor e a imagem de um produto em elementos de design". Essa metodologia, baseada principalmente em conceitos matemáticos, tem permeado as indústrias japonesas e é utilizada em indústrias automotivas, de eletrodomésticos, construção civil, e vestuário e tem se mostrado eficiente para o projeto, manipulando dados subjetivos de maneira quantitativa. No Brasil, muitas faculdades de design incluem em sua grade curricular o ensino de metodologias empíricas, principalmente por ser uma área voltada para humanas. Entretanto, é importante considerar que metodologias como o KE podem ampliar as taxas de retorno de um projeto de produto e minimizar os riscos de um produto "ruim" chegar ao consumidor. Nesse estudo realizou-se, através de pesquisas sobre a literatura disponível e com o auxílio de revisão bibliográfica sistemática, um levantamento de estudos KE. O objetivo, com o levantamento e análise de casos, é elaborar uma proposta de aprendizagem KE, permitindo que essa metodologia seja disseminada nas universidades. Como principal resultado o trabalho apresenta uma proposta de aprendizagem estruturada com um plano de aula passo a passo, oferecendo um material pronto para replicação. Além disso, o estudo apresenta um experimento que retrata a aplicação dessa proposta em um grupo de estudantes de design de produto do terceiro ano, o andamento e resultados obtidos. Desse modo foi possível propor um modelo e também testar sua eficácia. Palavras Chave: tecnologia orientada ao consumidor. design de produto. sentimento kansei. engenharia kansei. metodologia Kansei. gestão do designAbstract: The Kansei Engineering (KE) methodology was developed as an oriented technology for the costumer with the purpose of improve new products development. It is defined as "technology that represents the costumer feeling in images of a product design elements." This methodology, based mainly on mathematical concepts have permeated Japanese industries and is widely used in automotive industry, home appliances, construction, and clothing industry and has shown an efficient method to manipulate subjective data in a quantitative way. At Brazil, many design colleges do not include in curriculum the teaching of quantitative methodology, mainly because it is an area focused on human. However, it is important to consider that methodologies such as KE can increase as income from a product design and minimize the risk of a "bad" product reaches the consumer. This study was realized through the research about the literature available and with the aid of systematic literature review, a survey of KE studies. The objective with the survey and analysis of cases, is to elaborate a learning KE, by allowing the methodology to be disseminated in universities. As main result the study presents a class plan step by step, with the structured proposed approach and with potential for replication. Additionally, the study presents an experiment that shows the application of this proposal in a group of students of product design of the third year, the progress and results. In this way it was possible to propose an approach and to test its efficacy. Keywords: consumer-oriented technology, product design, Kansei feeling, Kansei Engineering, Kansei methodology, design management

Modeling and measurement of consumers' decision strategies

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2012.Cataloged from PDF version of thesis.Includes bibliographical references.This thesis consists of three related essays which explore new approaches to modeling and measurement of consumer decision strategies. The focus is on decision strategies that deviate from von Neumann-Morgenstern utility theory. Essays 1 and 2 explore decision rules that consumers use to form their consideration sets. Essay 1 proposes disjunctions-of-conjunctions (DOC) decision rules that generalize several well-studied decision models. Two methods are proposed for estimating the model. Consumers' consideration sets for global positioning systems are observed for both calibration and validation data. For the validation data, the cognitively simple DOC-based methods predict better than the ten benchmark methods on an information theoretic measure and on hit rates. The results are robust with respect to format by which consideration is measured, sample, and presentation of profiles. Essay 2 develops and tests an active-machine-learning method to select questions adaptively when consumers use heuristic decision rules. The method tailors priors to each consumer based on a "configurator." Subsequent questions maximize information about the decision heuristics (minimize expected posterior entropy). To update posteriors after each question the posterior is approximated with a variational distribution and uses belief-propagation. The method runs sufficiently fast to select new queries in under a second and provides significantly and substantially more information per question than existing methods based on random, market-based, or orthogonal questions. The algorithm is tested empirically in a web-based survey conducted by an American automotive manufacturer to study vehicle consideration. Adaptive questions outperform market-based questions when estimating heuristic decision rules. Heuristics decision rules predict validation decisions better than compensatory rules. Essay 3 proposes a model of product search when preferences are constructed during the process of search: consumers learn what they like and dislike as they examine products. Product recommendations, whether made by sales people or online recommendation systems, bring products to the consumer's attention and impact his/her preferences. Changing preferences changes the products the consumer will choose to search; at the same time, the products the consumer chooses to search will determine the future shifts in preferences. Accounting for this two-way relationship between products and preferences is critical in optimizing recommendations.by Daria Dzyabura.Ph.D

Developing strategic information system planning model in Libya organisations

This quantitative research study investigated the impact of organisational context on the process and success of strategic IS planning (SISP) in post-implementation information systems in Libyan organisations. A set of direct and indirect relationships were investigated in the research model. The organisational context presented as a contingent situational variable mediated by SISP process and predicted by SISP success (the criterion variable). The causality of the relationship set was developed from the contingency theory of information systems and supported by fit models in strategic management research. The study deployed multivariate analysis represented in the structural equation modelling (SEM) to develop robust construct measurements and analyse data collected from executives responsible for information systems planning in both public and private Libyan organisations. Multi-dimensional multi-items constructs were used in the path analysis model after they were extensively validated. The path analysis model represented as mediation model, where hypothesise suggest that SISP context has an impact SISP success, through the influence of the SISP process. In the model, four dimensions of the SISP context construct were found to have a significant impact on SISP success directly and indirectly through the SISP process. Two of these dimensions are components of the leadership orientation construct, namely “Creative and Controlling” leadership. The other two dimensions are “Organisation centralisation structure and the Riskiness of organisation strategies”. The environmental uncertainty and planning resource constructs were found to have no impact on SISP success in Libyan organisations. Furthermore, this study validated six out of seven dimensions of SISP process construct measurement; only five exhibited acceptable fit level in the path analysis model and all were affected by the SISP context. However, just three out of five SISP process constructs had an impact on SISP success namely “Comprehensiveness, Focus and Intuition planning process”. Different SISP processes were associated with different levels of SISP success, “Intuition” was the most effective SISP process approach. The second most effective SISP process approach was the “Focus on innovation”, followed by “Limited comprehensiveness”. The SISP success measured by the fulfilment of key objectives that has three measurements constructs namely “Analysis, Alignment, and Cooperation”. The research suggest that under the effect of organisation context the most successful SISP produced by (CIO, CEO, or top executives) who rely less on personal judgment, focus more on innovation rather than control and limit their comprehensiveness of information systems planning process

Foundations for Value-Driven Delegated Design with Human Decision Makers

Value-Driven Design is a paradigm that argues that the goal of the engineering design process is to create a system with maximum value. However, the design of large, complex systems undoubtedly requires the efforts of many individuals, and it is naive to think these individuals will act to maximize value if their own values are not maximized along the way. This research focuses on building the foundational knowledge for incentivizing the many individuals in large system design to make design decisions toward maximizing system value. Specifically, this dissertation uses the mathematical framework of normative decision making to formulate and evaluate incentives. We formulate two promising incentive structures: the Piece Rate–where a marginal increase in system value yields a marginal increase in reward an individual will receive– and the Variable Ratio–where a marginal increase in system value yields a marginal increase in the probability of a reward to the individual. These incentive structures are evaluated twofold: (1) by how well they motivate an engineer to provide effort to search for an optimal design solution and (2) by how well they motivate an engineer to collaborate with other engineers to yield an optimal system design solution. We derive mathematical models of effort and collaboration provision for incentive evaluation. Mathematical analysis suggests that which incentive structure motivates greater search effort or collaboration is contextual. The effectiveness of one incentive over the other for effort provision is dependent, in part, on the risk preferences of the engineer. The effectiveness of one incentive over the other for collaboration provision is dependent, in part, on how the incentive structures are scaled with respect to the feasible system alternative space. Therefore, the analysis in this dissertation suggests that the greater information a system-level manager has over the people in the design process and the general characteristics of the system design alternative space, the greater her ability for choose between the Piece Rate and Variable Ratio incentive structures to induce search effort and collaboration to maximize system value

Theoretical and experimental examinations of target-based decision making

Target based decision making occurs when a decision maker wishes to maximize the probability of attaining some output or performance level. The target may be set externally, for example, by an employer as part of an incentive system. Or, the target may simply be based on a decision maker’s individual goals and understanding of implicit expectations. Questions arise concerning the effects of these decisions on the performance of an organization. Further, if these decisions affect organizational value, how well can these decisions be characterized and predicted? This research explores these questions—and others—using both theoretical and experimental means. A value gap model is developed that facilitates simulation based insights to target optimality. The effect of a target is characterized in terms of a value gap that is defined as the difference in value between what was selected based on a target and what the organization would have preferred. A copula based method is used to simulate future decision situations and the expected value gap is calculated as a function of model parameters. Several trends in target optimality are observed that are robust to changes in the probability distributions over future decision alternatives. Specifically, the optimal target (i) decreases as the organization’s risk aversion increases, (ii) increases as the number of available alternatives increase, and (iii) the presence of an efficient frontier of decision alternatives reduces the consequences of setting targets higher than optimal. A behavioral experiment is conducted to compare target-based decision making to decisions in the absence of a target. The results show that while target based decision making can be well predicted based on the properties of the decision alternatives alone. Decisions in the absence of a target, however, cannot be predicted based on the alternatives alone. Information about individualized differences in risk preferences is required to identify trends in the decision making behavior. These results have strong implications for decisions about whether or not to used target based incentives within an organization. The research concludes with an application to engineering systems and a discussion of additional questions raised by the research that point to directions for new research