Multiattribute Data

The present studies show that preferences change systematically depending on the global context and the measurement task Subjects evaluated apartments described by monthly rent and distance to campus using two different tasks (choices and attractiveness ratings) in two different global contexts (one with a narrow range of rents and a wide range of distances, and the other with a wide range of rents and a narrow range of distances) With the task held constant, preference orders for the same pair of apartments reversed in the two different contexts Similarly, with the context held constant, preference orders for the same pair of apartments reversed in the two tasks Taken together, the effects are startling Out of 25 apartments common to all four conditions, the preference rank of the apartment that was most expensive and closest to campus ranged from the 28th percentile to the 80th percentile We argue that, in the present experiments, the global context influences the scale values (or...

With all of the attention that examinations of bundle evaluations have garnered in the literature, it is surprising that no research has investigated how consumers process contextual information when the context, target, or both are composed of bundles. The ...

The study examines the relative merits of a noncompatibility and a restructuring explanation of the recurrent empirical finding that a prominent attribute looms larger in choices than in judgments. Pairs of equally attractive options were presented to 72 undergraduates who were assigned to six conditions in which they performed (1) only preference judgments or choices, (2) preference judgments or choices preceded by judgments of attractiveness of attribute levels, or (3) preference judgments or choices accompanied by think-aloud reports. The results replicated the prominence effect for choices, but a prominence effect was also found for preference judgments. In accordance with the restructuring explanation, the think-aloud protocols indicated that options were more often restructured in choices than in preference judgments. However, restructuring could not explain the prominence effect observed for preference judgments. A modified compatibility hypothesis is offered as an alternative explanation. Several studies of decision making have demonstrated that preference judgments o r judgments of the attractiveness of options, on the one hand, and choices between options, on the other hand, are not in perfect agreement (e.g. Slovic er al., 1990; Slovic and Lichtenstein, 1983; see Payne et al., 1991, for a review). Thus, an option judged to be the most attractive is not necessarily chosen. The discrepancy between judgment and choice also applies to the decision maker's information processing. F o r instance, Billings and Scherer (1988) and Westenberg and Koele (1990, 1992) demonstrated more intra-attribute information processing in choices than in judgments. In addition, Lindberg et al. (1989) found more selective processing. Recently, Slovic et al. (1990) and Tversky et al. (1988) offered a n explanation of the judgment-choice discrepancy in the simple case when two options are described on two attributes. They reported

Artigo recebido 01/06/2011. Aprovado em 13/08/2013. RESUMO O desempenho das organizações depende da qualidade de seus recursos humanos (NAQVI, 2009). Dessa forma, a preocupação com os modelos mentais e as competências da equipe demonstra ser uma atividade essencial para alavancar um melhor desempenho organizacional. A partir de um estudo exploratório com 294 gestores de organizações privadas de diversos segmentos de negócio na região serrana do Rio Grande do Sul, este estudo objetiva identificar como os gestores configuram seus modelos mentais sobre o conceito de Gestor e entender melhor quais competências estão mais presentes nestes gestores. Sendo os modelos mentais uma construção sistêmica, podendo ser configurada a partir de um sortimento de elementos sensoriais, simbólicos, cognitivos, emocionais e axiomáticos (DE TONI, 2005; SCHULER et al., 2009), identificou-se que para os gestores analisados há uma ênfase maior à dimensão racional e menor na dimensão emocional. Sendo que as competências profissionais que prevalecem em seus modelos mentais são as gerenciais e técnicas ou funcionais. Observou-se também que as competências humanas, tais como a ética, a iniciativa, a consciência da qualidade no trabalho, a criatividade, a abertura às mudanças e o aprendizado são as competências mais incentivadas e valorizadas pelos gestores na sua equipe. Os modelos mentais e as competências são fatores que influenciam o comportamento dos gestores e consequentemente no desempenho organizacional. Palavras-chave: Modelos mentais. Competência. Habilidade. Esta obra está licenciada sob uma Licença Creative Commons Attribution 3.0.

Artigo recebido 01/06/2011. Aprovado em 13/08/2013. RESUMO O desempenho das organizações depende da qualidade de seus recursos humanos (NAQVI, 2009). Dessa forma, a preocupação com os modelos mentais e as competências da equipe demonstra ser uma atividade essencial para alavancar um melhor desempenho organizacional. A partir de um estudo exploratório com 294 gestores de organizações privadas de diversos segmentos de negócio na região serrana do Rio Grande do Sul, este estudo objetiva identificar como os gestores configuram seus modelos mentais sobre o conceito de Gestor e entender melhor quais competências estão mais presentes nestes gestores. Sendo os modelos mentais uma construção sistêmica, podendo ser configurada a partir de um sortimento de elementos sensoriais, simbólicos, cognitivos, emocionais e axiomáticos (DE TONI, 2005; SCHULER et al., 2009), identificou-se que para os gestores analisados há uma ênfase maior à dimensão racional e menor na dimensão emocional. Sendo que as competências profissionais que prevalecem em seus modelos mentais são as gerenciais e técnicas ou funcionais. Observou-se também que as competências humanas, tais como a ética, a iniciativa, a consciência da qualidade no trabalho, a criatividade, a abertura às mudanças e o aprendizado são as competências mais incentivadas e valorizadas pelos gestores na sua equipe. Os modelos mentais e as competências são fatores que influenciam o comportamento dos gestores e consequentemente no desempenho organizacional. Palavras-chave: Modelos mentais. Competência. Habilidade. Esta obra está licenciada sob uma Licença Creative Commons Attribution 3.0.

A inovação deixou de configurar uma opção para as organizações passando a ser um requisito obrigatório institucional e legitimador. O debate está centrado na questão da forma de inovar e de pesquisar, em virtude do expressivo custo de realizar as atividades de P&D. Destarte surge a necessidade de realizar uma análise compreensiva do processo decisório que visa definir o modo de realizar P&D-interna ou externa, ou seja, "Fazer ou Comprar?" as atividades de P&D, considerando-se os limites de racionalidade do gestor com base em aspectos cognitivos, mentais e perceptivos, além do estilo de gestão pré-construído da liderança organizacional.

Extant literature in decision theory suggests that online auction buyers depend on signals for mitigating uncertainty that influence bidder behavior at multiple points. However, the depth and breadth of the use of signals has only been partially explored. Using data from 242 online auction users, we show that eight emergent factors influence decisions of auction selection and initial bid in different ways. We further find that two ethical perspectives impact the evaluation of seller uncertainty in unique ways, although neither perspective predominates within our sample. These results enable sellers and online auction marketplaces to better design and implement auction systems that provide signals that buyers most desire.

Este estudo teve por objetivo desenvolver e testar um modelo adaptavel de analise economico-estrategico para apoio a decisao de externalizacao em logistica de transporte. Para tanto, foi realizado em quatro etapas, iniciando-se com a revisao bibliografica. Nas etapas seguintes desenvolve-se o modelo e o estudo de caso. Evidenciou-se o tipo de pesquisa metodologica como um estudo de caso aplicado de abordagem qualitativa/quantitativa, realizada a partir de multiplas fontes de coleta de dados. Os atributos utilizados no estudo de caso e na aplicacao do modelo – regularidade, confiabilidade, qualidade dos servicos, infraestrutura, custo – foram selecionados na literatura atinente e nas entrevistas com os gestores da organizacao, envolvidos com a decisao do processo de externalizacao. Pelos resultados obtidos, indica-se a externalizacao da frota com opcao pelo fornecedor A. Desta forma, conclui-se que o modelo proposto pode ser um importante instrumento de apoio aos gestores na tomada d...

Mobile ad hoc networks (MANETs) present similarities with Peer to Peer (P2P) systems in terms of decentralization, equality and autonomy. This results in the rise of new collaborative and spontaneous P2P applications over MANETs such as P2P auctions. The deployment of auctions over MANETS should provide new opportunities to the important marketplace created by mobile communities and may be a game changer in local markets when the mobile infrastructures are very pervasive. This business scenario implies multiple advantages such as ubiquity, availability, affordability, opportunity and spontaneity. Nevertheless, it faces various challenges such as fairness and security. In this paper we present a fully distributed architecture and a process designed to support P2P auctions over MANETs. The major goal of this paper is threefold: i) to propose an estimation model of a fair round duration called Tfair (the bids collection duration) to fulfill fairness, ii) to propose a new scheme for access control and no replay that takes into consideration the unique constraints imposed by the crossing of MANETs, P2P and auctions, and iii) to validate the proposals by simulations. We prove the effectiveness of the proposed Tfair estimation model. We also show that the overhead of the proposed security solution is acceptable for the studied scenarios.

Aim of this paper is to underline the main contributions in the context of Factorial Conjoint Analysis. The integration of Conjoint Analysis with the exploratory tools of Multidimensional Data Analysis is the basis of different research strategies, proposed by the authors, combining the common estimation method with its geometrical representation. Here we present a systematic and unitary review of some of these methodologies by taking into account their contribution to several open ended problems.

Aim of this paper is to underline the main contributions in the context of Factorial Conjoint Analysis. The integration of Conjoint Analysis with the exploratory tools of Multidimensional Data Analysis is the basis of different research strategies, proposed by the authors, combining the common estimation method with its geometrical representation. Here we present a systematic and unitary review of some of these methodologies by taking into account their contribution to several open ended problems.

We study a model of procurement auctions in which information policies can be used to treat two heterogeneous suppliers asymmetrically. The buyer is shown to be better off revealing information about her preferences to the weak supplier only, when there is a sufficient cost difference between the weak and the strong. Conversely, when the two competitors have similar cost structures, for the buyer it is best to disclose her preferences publicly.

Online auctions are a popular and convenient way to engage in ecommerce. However, the amount of auction fraud has increased with the rapid surge of users participating in online auctions. Shill bidding is the most prominent type of auction fraud where a seller submits bids to inflate the price of the item without the intention of winning. Mechanisms have been proposed to detect shill bidding once an auction has finished. However, if the shill bidder is not detected during the auction, an innocent bidder can potentially be cheated by the end of the auction. Therefore, it is essential to detect and verify shill bidding in a running auction and take necessary intervention steps accordingly. This paper proposes a run-time statistical algorithm, referred to as the Live Shill Score, for detecting shill bidding in online auctions and takes appropriate actions towards the suspected shill bidders (e.g., issue a warning message, suspend the auction, etc.). The Live Shill Score algorithm also uses a Post-Filtering Process to avoid misclassification of innocent bidders. Experimental results using both simulated and commercial auction data show that our proposed algorithm can potentially detect shill bidding attempts before an auction ends.

Context: Business process reengineering (BPR) is identified as one of the most important solutions for organizational improvements in all performance measures of business processes. However, high failure rates 70% is reported about using it the most important reason that caused the failure is the focus on the process itself; regardless of the surrounding environment, and the knowledge of the organization. The other reasons are due to the lack of tools to determine the causes of the inconsistencies and inefficiencies. Objective: This paper proposes Process Reengineering Ontology-based knowledge Map Methodology (PROM) to reduce the failure ratio, solve BPR problems, and overcome their difficulties. Method: using an organizational ontology to show the structure and environment surrounding to organization's processes, using knowledge maps as an inference that succeeds to identify and find out the causes that lead to contradictions and inefficiencies, and using Analytical hierarchy processing to identify and prioritize processes of the business to be redesigned . Results: through the proposed methodology all organizational processes are completely analyzed. Moreover, Analytical Hierarchy Processing technique is used to show the most important processes with high priority to be reengineered first then it is easy to discover any errors occurred during reengineering process through knowledge map so BPR is done successfully. Conclusion: Apply the proposed methodology to inventory management shows how processes reengineering are done successfully and helping the organization to achieve its objectives.

In this paper, a brief outline of the evolution of the statistical techniques for the measurement of quality is firstly sketched. At the same time, the need for multivariate procedures is justified from both methodological and application points of view and a proposal of non parametric control charts is shown. The attention is then focused on visualising and monitoring quality. The peculiar features of Non Symmetrical Data Analysis methods are shown to fit the demands arising when monitoring quality of multivariate industrial processes. Some research perspectives are finally enhanced.

Aim of this paper is to underline the main contributions in the context of Factorial Conjoint Analysis. The integration of Conjoint Analysis with the exploratory tools of Multidimensional Data Analysis is the basis of different research strategies, proposed by the authors, combining the common estimation method with its geometrical representation. Here we present a systematic and unitary review of some of these methodologies by taking into account their contribution to several open ended problems.

A user-centered approach in the development lifecycle of e-commerce websites is nowadays a crucial factor in the success of any on-line business. The purpose of this paper is twofold: a) to identify the factors that affect e-commerce website usability and b) to analyze the role of those factors in increasing the effectiveness of ecommerce web sites. Furthermore, it presents the application of a Multicriteria Satisfaction Analysis (MUSA) method to rank usability attributes in websites based on their competitiveness importance. A case study in eight e-tourism web-sites is presented as a demonstration of this work, the outcome of which will help usability specialists and e-commerce website developers to determine specific usability attributes that are more crucial to the overall usability and user satisfaction of a website. The results of the proposed approach suggest that for each e-commerce website certain usability attributes are likely to be more crucial to the success of the ecommerce website than others. Therefore, identifying the relevant usability attributes in advance through customers' feedback can be a great advantage to website developers if they want to have an edge over other competitors.

Any automated decision support software must tailor its actions or recommendations to the preferences of different users. Thus it requires some representation of user preferences as well as a means of eliciting or otherwise learning the preferences of the specific user on whose behalf it is acting. While additive preference models offer a compact representation of multiattribute utility functions, and ease of elicitation, they are often overly restrictive. The more flexible generalized additive independence (GAI) model maintains much of the intuitive nature of additive models, but comes at the cost of much more complex elicitation. In this article, we summarize the key contributions of our earlier paper (UAI 2005): (a) the first elaboration of the semantic foundations of GAI

Any automated decision support software must tailor its actions or recommendations to the preferences of different users. Thus it requires some representation of user preferences as well as a means of eliciting or otherwise learning the preferences of the specific user on whose behalf it is acting. While additive preference models offer a compact representation of multiattribute utility functions, and ease of elicitation, they are often overly restrictive. The more flexible generalized additive independence (GAI) model maintains much of the intuitive nature of additive models, but comes at the cost of much more complex elicitation. In this article, we summarize the key contributions of our earlier paper (UAI 2005): (a) the first elaboration of the semantic foundations of GAI models that allows one to engage in preference elicitation using local queries over small subsets of attributes rather than global queries over full outcomes; and (b) specific procedures for Bayesian preference ...

Online shopping has increasingly replaced traditional retail shopping, as a large number of consumers have adopted it on a global scale. However, while it is well established in developed countries, e-commerce is still at an early stage in emerging markets, hence there is a need to unveil which factors contributes to its adoption. The main objective of this study is to integrate the theory of planned behavior, the theory of reasoned action, and the technology acceptance model using a Bayesian approach to determine the key predictors of online purchase intention among internet users in Colombia. The results demonstrate the pertinence of the theory of reasoned action and technology acceptance model, models to explain online purchase intention, confirming that the intention to purchase online is mostly determined by the attitudes to e-commerce which, in turn, are explained by perceived usefulness, perceived ease of use, and the subjective norm related to online shopping.

The natural generalization of the (two-dimensional) Yang-Baxter equations to three dimensions is known as the Zamolodchikov's tetrahedron equations. We consider a simplified version of these equations which still ensures the commutativity of the transfer matrices with different spectral parameters and we present a family of free fermionic solutions.

This paper presents a methodology for the strategic management of enterprise performance. The methodology uses and integrates tools and methods for performance management found in literature and practice. The paper first presents an introduction to performance management systems and their requirements. It then reviews approaches to performance management. The paper concludes with a description of the Enterprise Performance Management Methodology, a methodology developed to address many of the shortcomings of current performance management systems.

Utility companies can organize e-auctions to procure electricity from other suppliers during peak load periods. For this purpose, we develop an efficient Combinatorial Reverse Auction (CRA) to purchase power from diverse sources, residents and plants. Our auction is different from what has been implemented in the electricity markets. In our CRA, which is subject to trading constraints, an item denotes a time slot that has two conflicting attributes, energy volume and its price. To ensure the security of energy, we design our auction with two bidding rounds: the first one is for variable-energy suppliers and the second one for other sources, like controllable load and renewable energy. Determining the winner of CRAs is a computational hard problem. We view this problem as an optimization of resource allocation that we solve with multi-objective genetic algorithms to find the best solution. The latter represents the best combination of suppliers that lowers the price and increases the energy.

seminal work on directionality in judgments of similarity demonstrated that people may not judge the similarity of A to B to be equal to the similarity of B to A. In a series of studies, we investigated comparison asymmetries. In Experiment 1, our aim was to extend Tversky's findings to a heterogeneous stimulus set, but no reliable asymmetries were observed. Experiment 2 employed a variety of comparison judgments, and, although some of these measures showed asymmetries, we still failed to observe asymmetries in rated similarity.A fmal attempt to obtain asymmetries used direction as a within-subjects factor, and for the first time, rating asymmetries were observed. Our data reinforce the idea of comparison asymmetries but suggest that similarity rating asymmetries are only observed under quite circumscribed conditions. Much ofmodem theorizing on similarity has focused on similarity structure and has used geometric scaling models that represent similarity relations as distances in some psychological space (see . The shorter the distance between two points, the more similar are the two items being compared. Multidimensional scaling (MDS) approaches have not, however, paid much attention to the processing side of similarity comparisons (see Nosofsky, 1992, for notable exceptions). Tversky (1977) demonstrated the flexibility of comparison processes within the framework of a featural-theoretical approach to the analysis of similarity, known as the contrast model. argued that metric models are not sufficient for representing similarity data and showed that similarity judgments violate axioms that must be satisfied by all distance models-most notably, for present purposes, symmetry. Symmetry is the assumption that the distance between two items is the same regardless of the direction ofthe comparison. However, people's judgments seem to show asymmetries. For example, Tversky reported that people rate the similarity ofNorth Korea to Red China to be greater than the similarity of Red China to North Korea. In general, asymmetries ofjudgment raise serious problems for geometric models (but see N osofsky, 1991,

In this paper we propose an alternative approach to conjoint analysis (CA) based on the principal component analysis onto a reference sub-space (PCAR). Following this technique, the results of a CA are considerably enriched by some graphical interpretation tools and optimal synthesis of the individual estimated part-worth coe$cients are also obtained with respect to hierarchized judges sub-populations.

Auctioning multi-dimensional items is a key challenge, which requires rigorous tools. This study proposes a multi-round, first-score, semi-sealed multi-attribute reverse auction system. A fundamental concern in multi-attribute auctions is acquiring a useful description of the buyers’ individuated requirements: hard constraints and qualitative preferences. To consider real requirements, we express dependencies among attributes. Indeed, our system enables buyers eliciting conditional constraints as well as conditional preferences. However, determining the winner with diverse criteria may be very time consuming. Therefore, it is more useful for our auction to process quantitative data. A challenge here is to satisfy buyers with more facilities, and at the same time keep the auctions efficient. To meet this challenge, our system maps the qualitative preferences into a multi-criteria decision rule. It also completely automates the winner determination since it is a very difficult task for buyers to estimate quantitatively the attribute weights and define attributes value functions. Our procurement auction looks for the outcome that satisfies all the constraints and best matches the preferences. We demonstrate the feasibility and measure the time performance of the proposed system through a 10-attribute auction. Finally, we assess the user acceptance of our requirements specification and winner selection tool.

Contextual effects due to attribute range were examined in single-attribute and multiattribute
judgments. The effect of a given attribute difference was greater when presented in a narrow range
than a wide range. Stretching and shrinking the range of attributes altered the rank orders of
judgments assigned to the same stimuli in different ranges. Trade-offs between time and money,
one measure of ability and another, and achievement and motivation depended on attribute range.
Although changes in trade-offs can result from changes in weights, data were consistent with the
hypothesis that attribute range influences scale values. Scale values for common levels of an
attribute spanned a wider interval when the attribute range was narrow than when the attribute
range was wide.

The present studies show that preferences change
systematically depending on the global context and the measurement
task. Subjects evaluated apartments described by
monthly rent and distance to campus using two different tasks
(choices and attractiveness ratings) in two different global contexts
(one with a narrow range of rents and a wide range of
distances, and the other with a wide range of rents and a narrow
range of distances). With the task held constant, preference
orders for the same pair of apartments reversed in the two
different contexts. Similarly, with the context held constant,
preference orders for the same pair of apartments reversed in
the two tasks. Taken together, the effects are startling. Out of
25 apartments common to all four conditions, the preference
rank of the apartment that was most expensive and closest to
campus ranged from the 28th percentile to the 80th percentile.
We argue that, in the present experiments, the global context
influences the scale values (or the perceptions of the attributes),
and the task influences the weights {or the psychological
importance) ofthe attributes.

The concept of sustainability has become increasingly important for organizations and has permeated a number of managerial and organizational decisions. Sustainability, as defined by its 'triple-bottom line' factors of economic, environmental, and social dimensions, is the underlying framework we use to develop and apply a strategic justification tool for project evaluation with sustainability implications. An activity-based management methodological framework is used as a vehicle to frame decisions using corporate sustainability. An illustrative application of this technique demonstrates how an organization could select between two competing reverse logistics providers. This process requires that we introduce issues relevant to three major sustainability factors (and their sub factors) and how they are influenced by a reverse logistics provider decision. The dual contribution of this paper includes investigating the design and development of the strategic sustainability evaluation framework and introducing the relationships of reverse logistics to economic, environmental and social sustainability dimensions.

Abstract Two problems may arise when an intelligent (recommender) system elicits users' preferences. First, there may be a mismatch between the quantitative preference representations in most preference models and the users' mental preference models. Giving exact numbers, eg, such as “I like 30 days of vacation 2.5 times better than 28 days” is difficult for people.

ABSTRACT Agility is increasingly being seen as a prerequisite for continued competitiveness in the changing global marketplace. However, many of the technological and organizational changes required in making the migration to agility are radical and strategic in nature. Attempting to justify many of these pervasive changes is difficult using currently available techniques, especially those which focus solely on traditional economic criteria.

The evolution from a focus on product design to one on process and product design in improving organizational competitiveness has included the development of a field of study called business process reengineering (BPR). BPR is a organizational development tool that requires a number of stages of analysis, design and implementation. The literature in the past few years has provided a number of tools and techniques to aid in BPR efforts. One area in this relatively new organizational change philosophy that has not received much attention is the selection or prioritization of a set of candidate business processes or projects that should undergo reengineering. Since business processes by definition are elements of a broader strategic system, the candidate evaluation and selection process must be strategically oriented. To aid in this evaluation process a strategic multiattribute evaluation and justification framework and methodology is presented. The methodology includes an activity based analysis and linkage of traditional (financial) and strategic considerations. The evaluation methodology may also have implications for post-implementation evaluation of BPR projects and other phases of BPR.

In this paper we propose an alternative approach to conjoint analysis (CA) based on the principal component analysis onto a reference sub-space (PCAR). Following this technique, the results of a CA are considerably enriched by some graphical interpretation tools and optimal synthesis of the individual estimated part-worth coe$cients are also obtained with respect to hierarchized judges sub-populations.

Any automated decision support software must tailor its actions or recommendations to the preferences of different users. Thus it requires some representation of user preferences as well as a means of eliciting or otherwise learning the preferences of the specific user on whose behalf it is acting. While additive preference models offer a compact representation of multiattribute utility functions, and ease of elicitation, they are often overly restrictive. The more flexible generalized additive independence (GAI) model maintains much of the intuitive nature of additive models, but comes at the cost of much more complex elicitation. In this article, we summarize the key contributions of our earlier paper (UAI 2005): (a) the first elaboration of the semantic foundations of GAI models that allows one to engage in preference elicitation using local queries over small subsets of attributes rather than global queries over full outcomes; and (b) specific procedures for Bayesian preference elicitation of the parameters of a GAI model using such local queries.