Reference-dependent preferences on smart phones in South Korea: Focusing on attributes with heterogeneous preference direction

Consumers observe reference-dependent comparative attribute levels rather than absolute attribute levels of a product in their actual purchasing process. As the reference-dependent effect is important, many consumer preference studies in psychology and behavioral economics have perceived the reference-dependence as a general assumption. Nonetheless, few studies utilize standard economic models such as the discrete choice model, which is useful for analyzing demand forecasting in the marketing sector, and have used a reference-dependence utility function. Moreover, these studies analyze attributes only with the identical consumer preference directions, such as time and cost. Therefore, this study proposes an advanced discrete choice model that analyzes asymmetry preferences for attributes with heterogeneous preference direction as well as reference-dependence effect. It also investigates empirically the usefulness of the model on the market for smart phones. Based on this approach, we find wide disparities in consumer asymmetry preferences and loss aversion parameters in accordance to the existence of market experience and product attributes.     

Econometric Effects of Utility Order-Preserving Transformations in Discrete Choice Models

In the random utility modelling context, choice probabilities are unaffected by increasing linear transformations of the systematic utility; hence its empirical specification is derived on the basis that only differences in utility matters and that the scale of utility is arbitrary. We argue that choice probabilities remain unchanged if these linear transformations are made under the deterministic perspective of a single individual choosing several times. But, in the random utility setting, parameter estimates might be significantly affected by these transformations. In particular we focus on the effect of two order-preserving transformations usually applied in the derivation of the representative utility from the conditional indirect utility function: adding a constant to the utility of all alternatives and multiplying each alternative utility by a constant. We concentrate on the two most popular specifications in transport mode choice: the “wage rate” (Train and McFadden Transport Res 12:349–353, 1978) and the “expenditure rate” (Jara-Díaz and Farah Transport Res 22B:159–171, 1987) specifications. Using a collection of synthetic datasets generated in a new fashion directly from the conditional indirect utility function, i.e. before applying any expansion or transformation, we demonstrate how taking this class of order-preserving transformations could lead to misinterpretation of the econometric results, such as detecting randomly distributed and correlated parameters and/or income and time effects which are in fact not present.     

非线性关系下的工程项目工期—成本—质量综合优化*

工期、成本和质量是工程项目管理的主要内容,三者相互依存、相互影响,需要综合考虑。将工程项目间接成本和提前投产效益的上下限平均分摊到各工程活动中,构建各工程活动综合成本与持续时间之间、工程活动质量与持续时间之间的非线性关系,利用多属性效用函数理论建立项目工期—成本—质量综合优化模型,并用遗传算法求解。最后通过案例说明本文的优化模型不仅有效缩短了项目工期,还降低了项目成本,提高了工程质量。     

On Confounding Preference Heterogeneity and Income Effect in Discrete Choice Models

A substantial part of the discrete choice model literature has been concerned with specifications accounting for preference heterogeneity. In contrast, only a few studies have been interested in the presence of income effect, and it is much rarer still to come across models trying to account for both effects simultaneously. In this paper we use a specification that accounts for income effect and preference heterogeneity, both of a systematic and of a random nature. Our results point out that care should be taken with conclusions drawn from studies that only consider these effects separately, since they can be confounding from an empirical point of view. In fact, we provide empirical evidence that a random cost parameter can account for the existence of income effect.     

A utility function model for optimal material choice for multifunctional performance

This paper presents a general solution technique for problems of multifactor optimization by a rationalised utility function model. Evaluation of the performance of materials and structures reflecting all the possible interplay of their components and attributes is rendered more realistic by this method as the individual utility for every function of the candidates is accurately computed from proper utility functions/curves which are constructed based on their respective functional behaviour. This is, perhaps, for the first time such rational utility curves are constructed and utilized. Evaluation by its very nature is subjective and this method is no exception but the decision is guided properly on rational lines reflecting the actual behaviour. The method is illustrated by an example problem on the choice of a particular material out of ten candidates for possible utilization as a compression panel of minimum weight, maximum stability, least cost and five other such desirable attributes. This model is the most appropriate for development of new materials (composites) and economic utilization of existing materials by effecting suitable trade offs, especially when mathematical programming methods are of no avail.     

Dynamic and Personalized Web Services Composition in E-Business

Building composite Web services can save significant time and cost for developing new applications and enhancing the interoperability and collaboration among E-business partners. This article proposes a framework for dynamic and personalized composition of Web services using an approach that integrates not only functional attributes of Web services, but also nonfunctional attributes such as service requirements, quality of service, and the preferences and constraints of individual service consumers. A prototype system based on the proposed framework and some implementation details are also presented.     

基于效用的个性化推荐方法

当前的推荐方法未能从个性化效用角度评价推荐项目,因此用户需按自己的偏好,在推荐结果中进行再次筛选。针对该情况,提出一种基于效用的个性化推荐方法。该方法采用逼近于理想值的排序法(TOPSIS)作为衡量推荐对象效用的基本方法。为克服TOPSIS中静态权重设置的不足,采用可变精度粗糙集发现用户对属性的偏好。实验结果表明,该方法能为用户提供更好的个性化效用及准确性的推荐服务。     

A computer based application of non-linear multiple objective optimization

Multiple Objective Optimization Theory (MOOT) techniques are receiving increasing attention due to their ability to incorporate salient non-commensurate and conflicting objectives of a situation into the choice making process. This effort describes the modeling and optimization of an application which utilizes computer aided MOOT for candidate policy evaluation prior to a production process. The specific application discussed is an airborne tactical missile where the pre-production decision depends on such attributes as reliability, cost, technical performance, and survivability. A modeling and analysis effort produced non-linear performance indicers of the aforementioned attributes, and a set of constraints. This vector optimization problem is solved by implementing a constraint optimization technique on a digital computer. The resulting non-dominated solution set provides the information needed to proceed to a production stage.     

Linear uncertain extensions of the minimum cost consensus model based on uncertain distance and consensus utility

Uncertainty theory adopts the belief degree and uncertainty distribution to ensure good alignment with a decision-maker’s uncertain preferences, making the final decisions obtained from the consensus-reaching process closer to the actual decision-making scenarios. Under the constraints of the uncertain distance measure and consensus utility, this article explores the minimum-cost consensus model under various linear uncertainty distribution-based preferences. First, the uncertain distance is used to measure the deviation between individual opinions and the consensus through uncertainty distributions. A nonlinear analytical formula is derived to avoid the computational complexity of integral and piecewise function operations, thus reducing the calculation cost of the uncertain distance measure. The consensus utility function defined in this article characterizes the adjustment value and degree of aggregation of individual opinions. Three new consensus models are constructed based on the consensus utility and linear uncertainty distribution. The results show that, in complex group decision-making contexts, the uncertain consensus models are more flexible than traditional minimum-cost consensus models: compared with the high volatility of the adjusted opinions in traditional deterministic consensus models with crisp number-based preferences, the variation trends of both individual adjusted opinions and the collective opinion with a linear uncertainty distribution are much smoother and the fitting range is closer to reality. The introduction of the consensus utility not only reflects the relative changes of individual opinions, but also accounts for individual psychological changes during the opinion-adjustment process. Most importantly, it reduces the cost per unit of consensus utility, facilitates the determination of the optimal threshold for the consensus utility, and improves the efficiency of resource allocation.     

An optimization framework for “build-or-buy” decisions in software architecture

Building a software architecture that meets functional requirements is a quite consolidated activity, whereas keeping high quality attributes is still an open challenge. In this paper we introduce an optimization framework that supports the decision whether to buy software components or to build them in-house upon designing a software architecture. We devise a non-linear cost/quality optimization model based on decision variables indicating the set of architectural components to buy and to build in order to minimize the software cost while keeping satisfactory values of quality attributes. From this point of view, our tool can be ideally embedded into a Cost Benefit Analysis Method to provide decision support to software architects. The novelty of our approach consists in building costs and quality attributes on a common set of decision variables related to software development. We start from a special case of the framework where the quality constraints are related to the delivery time and the product reliability, and the model solution also devises the amount of unit testing to be performed on built components. We generalize the framework formulation to represent a broader class of architectural cost-minimization problems under quality constraints, and discuss advantages and limitations of such approach.     

Advantages of an Ellipse when Modeling Leisure Utility

This paper characterizes a specification for the utility of leisure that is based on the general equation for an ellipse. We show that this functional form has multiple benefits. The elliptical utility function provides Inada conditions at both the upper-bound and lower-bound constraints on labor supply, which is not the case for the two most common alternative functions. The presence of these two Inada conditions in the elliptical utility of leisure specification speeds up the computation by a factor between three and six times. We further show that the elliptical utility of leisure function is a close approximation to the constant relative risk aversion and constant Frisch elasticity functions in terms of marginal utilities, microeconomic outcomes in a life cycle model, and macroeconomic outcomes in a simple real business cycle model.     

An optimum design selection approach for product customization development

Consumer preferences and information on product choice behavior can be of significant value in the development processes of innovative products. In this paper, product customization evaluation and selection model is introduced to support imprecision inherent of qualitative inputs from customers and designers in the decision making process. Focusing on customer utility generation, an optimum design selection approach based on fuzzy set decision-making is proposed, where design attributes priority is identified from customer preferences using an analytical hierarchy process. A multi-attribute analysis diagram is developed to visualize the preference of each attribute from the expert’s group decision. Conjoint analysis is used in the product customization to focus on customer utility generation in terms of multiple criteria. The use of the decision-making method is illustrated with a case example that highlights the utility of the proposed method.     

A public procurement combinatorial auction mechanism with quality assignment

This article focuses on mechanism design for quality assignment combinatorial procurement auctions. We model how the participants can maximize social surplus, the difference between gross utility and total cost in electronic procurement, while selecting appropriate quality standards for the procured items. In typical forward combinatorial auctions, the goal is to maximize the sum of all buyers' valuations. In our setting, however, to achieve high buyer utility with low supplier cost, the selected quality levels for the procured items from the suppliers must exceed some predetermined minimum threshold. So the identification of capable suppliers and the corresponding quality assignments are crucial, since buyer utility and supplier cost will be affected by the buyer's quality choice. We develop a novel mechanism to balance the interests of buyers and sellers. Our proposed quality assignment Vickrey-Groves-Clarke (QA-VCG) mechanism is incentive-compatible, provides constraints on partial participation, and is efficient in quasi-linear preferences. In consideration of the perspective of the buyer as a government auctioneer, we also propose a revised mechanism to implement the goal of achieving minimal procurement costs, and appropriate benefits for participating suppliers. We provide a numerical illustration of our QA-VCG mechanism, and an extension that addresses an iterative combinatorial auction mechanism design in our context.     

Optimal paths in probabilistic networks: A case with temporary preferences

The classical shortest route problem in networks assumes deterministic arc weights and a utility (or cost) function that is linear over path weights for route evaluation. When the environment is stochastic and the “traveler's” utility function for travel attributes is nonlinear, we define “optimal paths” that maximize the expected utility.We review the concepts of temporary and permanent preferences for comparing a traveler's preference for available subpaths. It has been shown before that when the utility function is linear or exponential, permanent preferences prevail and an efficient Dijkstra-type algorithm [3] is available that determines the optimal path.In this paper an exact procedure is developed for determining an optimal path when the utility function is quadratic—a case where permanent preferences do not always prevail. The algorithm uses subpath comparison rules to establish permanent preferences, when possible, among subpaths of the given network. Although in the worst case the algorithm implicitly enumerates all paths (the number of operations increasing exponentially with the size of the network), we find, from the computational experience reported, that the number of potentially optimal paths to evaluate is generally manageable.     

Making Web services tradable: A policy-based approach for specifying preferences on Web service properties

In service-oriented architectures, applications are developed by incorporating services which are often provided by different organizations. Since a service might be offered under different configurations by various different organizations, sophisticated service selection and negotiation algorithms are required. Policies capture the conditions under which services are offered or requested and thereby constrain the negotiation space. However, current policy languages are ill-suited to realize beneficial trade-offs within a negotiation, since they support only Boolean decisions and cannot capture all relevant service information.Therefore, we present a novel policy language in this work that provides two main contributions: (i) we enable the specification of constraints on functional as well as non-functional properties of Web services. The functional properties include data objects and the behaviour, whereas the non-functional properties include QoS attributes. (ii) Given such constraints, we show how the concept of utility function policies can be used to define cardinal preferences over functional as well as non-functional properties. This is required to rank Web service offers, define their prices, and consequently to realize automated negotiations between service providers and requesters.     

Multi-Dimensional,MultiStep Negotiation

We present a multi-dimensional, multi-step negotiation mechanism for task allocation among cooperative agents based on distributed search. This mechanism uses marginal utility gain and marginal utility cost to structure this search process, so as to find a solution that maximizes the agents’ combined utility. These two utility values together with temporal constraints summarize the agents’ local information and reduce the communication load. This mechanism is anytime in character: by investing more time, the agents increase the likelihood of getting a better solution. We also introduce a multiple attribute utility function into negotiations. This allows agents to negotiate over the multiple attributes of the commitment, which produces more options, making it more likely for agents to find a solution that increases the global utility. A set of protocols are constructed and the experimental result shows a phase transition phenomenon as the complexity of negotiation situation changes. A measure of negotiation complexity is developed that can be used by an agent to choose an appropriate protocol, allowing the agents to explicitly balance the gain from the negotiation and the resource usage of the negotiation.This revised version was published online in August 2005 with a corrected cover date.     

Towards a Possibilistic Logic Handling of Preferences

The classical way of encoding preferences in decision theory is by means of utility or value functions. However agents are not always able to deliver such a function directly. In this paper, we relate three different ways of specifying preferences, namely by means of a set of particular types of constraints on the utility function, by means of an ordered set of prioritized goals expressed by logical propositions, and by means of an ordered set of subsets of possible choices reaching the same level of satisfaction. These different expression modes can be handled in a weighted logical setting, here the one of possibilistic logic. The aggregation of preferences pertaining to different criteria can then be handled by fusing sets of prioritized goals. Apart from a better expressivity, the benefits of a logical representation of preferences are to put them in a suitable format for reasoning purposes, or for modifying them.     

On consensus models with utility preferences and limited budget

This paper mainly focuses on the consensus problem with utility preferences denoted by simple trapezoidal membership function. In group decision-making (GDM), for acquiring the best consensus opinion, not only the total cost required by achieving the consensus, but also the utility of all the decision-makers (DMs) should be considered. Ben-Arieh et al. propose a consensus model from the view of the minimized cost. Based on their models, a kind of optimization consensus model has been put forward under the constraints of limited budget and different kinds of utility, whose objective function aims to obtain the maximum utility level of the whole GDM process. From an economic point of view, results show that different utility preferences of all the individual DMs have impacts on the final optimal consensus opinion. Besides, the moderator has a dominant role in the development trends throughout the whole decision-making process to some extent. Numerical examples are given to deeply explain the proposed models.     

Influence of Social Networks on Latent Choice of Electric Cars: A Mixed Logit Specification Using Experimental Design Data

Electric cars can potentially make a substantial contribution to the reduction of pollution and noise. The size of this contribution depends on the acceptance of this new technology in the market. This paper reports on the design and results of an elaborate stated choice experiment to investigate the effects of vehicle attributes, contextual and social network attributes on the latent demand for electric cars. The study contributes to the existing literature primarily by explicitly modelling the effects of different elements of social networks on the latent demand for electric cars. Moreover, the number of attributes included in the study design exceeds the typical number of attributes used in previous research, making the model more sensitive to a larger spectrum of variables. Two different mixed logit models are estimated: one with random parameters for vehicle attributes and contextual attributes and fixed effects for the social network attributes; one with random effects for social network attributes and fixed effects for the remaining attributes. Results indicate substantive differences between these two models in terms of the shape of utility curves. Overall, vehicle attributes are most important in the choice of electric cars, followed by social influence attributes. The effects of social network are relatively small.     

Personalized video adaptation framework (PIAF): high-level semantic adaptation

Despite much work on Universal Multimedia Experience (UME), existing video adaptation approaches cannot yet be considered as truly user-centric, mostly due to their poor handling of semantic user preferences. Indeed, these works mainly concentrate on lower-level user preferences but do neither consider any fine-grained object-level adaptation nor evaluate different adaptation options based on predicted user expectations. Moreover, these works do not provide owners with property rights that enable them to place restrictions on the types of modifications to be made to the video content. To address these shortcomings, we propose the Personalized vIdeo Adaptation Framework (PIAF) for high-level semantic video adaptation. PIAF is a fully integrated framework providing all the requirements for a semantic video adaptation. It defines a video annotation model and a user profile model comprising semantic constraints that are delineated in a consistent way, based on the standards MPEG-7 and MPEG-21. At the heart of the framework, the Adaptation Decision Taking Engine (ADTE) computes utility values for different adaptation options, considering each shot separately. The corresponding utility function evaluates the possible choices by evaluating multiple parameters that capture different dimensions of a multimedia experience: amount of modified content, modifications to key objects and shots with respect to the semantic integrity of the original content, expected processing cost of the adaptation, and the anticipated visual and temporal quality of the adapted content. Furthermore, the ADTE can deal with intellectual property issues by selecting an adaptation plan of good quality that also satisfies constraints specified by the content owner. This paper places a significant emphasis on theoretical details of the utility function and the computation of the adaptation plan. It also presents the results and evaluation of the adaptation process both in simulation and user study.