Efficient choice set designs for estimating availability cross-effects models

Batsell and Polking proposed a discrete choice model which incorporates the availability (presence or absence) of competing brands into the utility of each brand under study. The information on relative impacts of adding or deleting brands is of strategic interest, and models that do not incorporate such effects may be misleading. The designs suggested by Batsell and Polking have 2^m–m–1 choice sets. Even with as few as 10=m brands, this requires over 1000 choice sets. In this paper we provide a catalog of designs for estimating cross effects models in as few as 2m–1 choice sets. This will make cross effects modelling practical in a wide range of academic and commercial settings.     

Models and optimal designs for conjoint choice experiments including a no-choice option

In a classical conjoint choice experiment, respondents choose one profile from each choice set that has to be evaluated. However, in real life, the respondent does not always make a choice: often he/she does not prefer any of the options offered. Therefore, including a no-choice option in a choice set makes a conjoint choice experiment more realistic. In the literature, three different models are used to analyze the results of a conjoint choice experiment with a no-choice option: the no-choice multinomial logit model, the extended no-choice multinomial logit model, and the nested no-choice multinomial logit model. We develop optimal designs for the two most appealing of these models using the D-optimality criterion and the modified Fedorov algorithm and compare these optimal designs with a reference design, which is constructed while ignoring the no-choice option, in terms of estimation and prediction accuracy. We conclude that taking into account the no-choice option when designing a no-choice experiment only has a marginal effect on the estimation and prediction accuracy as long as the model used for estimation matches the data-generating model.     

Attribute Range Effects in Binary Response Tasks

This paper investigates attribute range effects in binary response conjoint analysis tasks. We investigate a long-standing conjecture that the regression estimates of attributes in choice tasks are influenced by a researcher's selected range of attribute levels across choice sets. Specifically, we examine the effect(s) of varying attribute ranges systematically over two ranges of levels (1=wide range, 2=levels in the middle of the wide range) in a public bus choice context. A master 2³ design is used to vary the range (i.e., wide, middle) of three numerical attributes (fare, service and time). In each of the eight master range conditions a 2³ factorial creates bus profiles, and a ninth condition is added to test for response non-linearity. Our results suggest that attribute range impacts attribute main effects to a small degree, yet exhibit substantial and systematic effects on attribute interactions and model goodness-of-fit. Implications of these results for practical design of academic and commercial choice-based conjoint analysis tasks are discussed.     

融合智能算法和代理模型的天线快速优化平台设计

电磁仿真软件作为天线设计的主要工具，针对其内置的优化器在优化效率、支持优化类型以及优化结果可用性上的问题，提出建立一种天线快速优化平台的解决方案。该平台采用Ansoft HFSS和Matlab联合仿真，并基于天线优化流程提供友好的图形化操作界面；融合前沿的智能优化算法和代理模型方法,用于处理天线多目标优化问题并生成Pareto最优解集；同时为其他复杂天线执行性能优化提供参考。小型多频段平面单极子天线设计实例表明，该平台能够实现多参数天线结构的快速优化，提高天线设计的效率。     

Conducting Dyadic Multiple Issue Negotiation Experiments: Methodological Recommendations

We take a critical, yet constructive look at the literature that focuses on multiple issue negotiation experiments. Our purpose is to offer suggestions for improvement when conducting such experiments. We focus on experiments, which are conducted using an externally imposed value point structure for the negotiators across issues together with background context information. Negotiator performance in such experiments is generally poor in the sense that Pareto inferior settlements are typically generated. A possible explanation is that negotiators sometimes follow the externally imposed value points and sometimes their own values pertaining to the context. Hence we conclude that it would be better if multiple issue negotiation experiments would not be based on an apriori given value point structure - unless we have compelling reasons for it - particularly if no agents are used. The common argument against doing this is that we cannot then identify Pareto optimal or Pareto preferred settlements for the subjects. Recent research integrating the fields of Multiple Criteria Decision Making (MCDM) together with negotiation analysis, however, provides a possible solution to this problem. An experiment conducted by the authors is used to illustrate our methodological recommendations.     

Sequential sampling models of choice: Some recent advances

Choice models in marketing and economics are generally derived without specifying the underlying cognitive process of decision making. This approach has been successfully used to predict choice behavior. However, it has not much to say about such aspects of decision making as deliberation, attention, conflict, and cognitive limitations and how these influence choices. In contrast, sequential sampling models developed in cognitive psychology explain observed choices based on assumptions about cognitive processes that return the observed choice as the terminal state. We illustrate three advantages of this perspective. First, making explicit assumptions about underlying cognitive processes results in measures of deliberation, attention, conflict, and cognitive limitation. Second, the mathematical representations of underlying cognitive processes imply well documented departures from Luce’s Choice Axiom such as the similarity, compromise, and attraction effects. Third, the process perspective predicts response time and thus allows for inference based on observed choices and response times. Finally, we briefly discuss the relationship between these cognitive models and rules for statistically optimal decisions in sequential designs.     

Sequential choice designs to estimate the heterogeneity distribution of willingness-to-pay

Two prominent approaches exist nowadays for estimating the distribution of willingness-to-pay (WTP) based on choice experiments. One is to work in the usual preference space in which the random utility model is expressed in terms of partworths. These partworths or utility coefficients are estimated together with their distribution. The WTP and the corresponding heterogeneity distribution of WTP is derived from these results. The other approach reformulates the utility in terms of WTP (called WTP-space) and estimates the WTP and the heterogeneity distribution of WTP directly. Though often used, working in preference space has severe drawbacks as it often leads to WTP-distributions with long flat tails, infinite moments and therefore many extreme values. By moving to WTP-space, authors have tried to improve the estimation of WTP and its distribution from a modeling perspective. In this paper we will further improve the estimation of individual level WTP and corresponding heterogeneity distribution by designing the choice sets more efficiently. We will generate individual sequential choice designs in WTP space. The use of this sequential approach is motivated by findings of Yu et al. (2011) who show that this approach allows for superior estimation of the utility coefficients and their distribution. The key feature of this approach is that it uses Bayesian methods to generate individually optimized choice sets sequentially based on prior information of each individual which is further updated after each choice made. Based on a simulation study in which we compare the efficiency of this sequential design procedure with several non-sequential choice designs, we can conclude that the sequential approach improves the estimation results substantially.     

Brand inequalities in the loyalty-effects of purchases

Choice models in marketing have generally included the effects of loyalty on individual choice behavior.Loyalty has been typically measured as proportion of purchases or as an exponentially smoothed index of past purchases. An underlying assumption of both measures is that all brands gain the same increase in loyalty with a purchase. However, such an assumption may not hold when the competing brands are not comparable. We propose a new exponential smoothing measure which incorporates brand-specific parameters for the loyalty effects of purchases. A choice model, calibrated on individual level data for the detergent category, is used to compare the proposed measure with its traditional version. This comparison reveals that the new approach improves both the fit and predictive performance of the choice model. The results also suggest that the loyalty effects of purchases are likely to be lower for brands which are purchased on price promotions and higher for expensive brands.     

Using stated response choice data to enrich revealed preference discrete choice models

There is growing interest in exploring the view that both revealed preference (RP) and stated preference (SP) data have useful information and that their integration will enrich the overall explanatory power of RP choice models. These two types of data have been independently used in the estimation of a wide variety of discrete choice applications in marketing. In order to combine the two data sources, each with independent choice outcomes, allowance must be made for their different scaling properties. The approach uses a full information maximum likelihood estimation procedure of the hierarchical logit form to obtain suitable scaling parameters to make one or more data sets comparable. We illustrate the advantages of the dual data strategy by comparing the results with those obtained from models estimated independently with RP and SP data. Data collected as part of a study of high speed rail is used to estimate a set of illustrative mode choice models.     

Female,married and endorsing: integrating celebrity marital status,role congruence and credibility

In this study, we investigate the effect of marital status and perceived role congruence (RCN) of a female celebrity endorser on consumer attitudes incorporating the role of credibility in the Indian context. The research hypotheses were tested using a series of experimental designs. The main study had a 4 (Celebrity: Unmarried/Just Married/Married but Endorsing/Married and Comeback) × 2 (Product: Role Congruent/Role Incongruent) full factorial design. Non-student samples were used in this study. Major findings implied a significant effect of celebrity marital status, RCN and the interaction term on consumer attitudes. The three source credibility dimensions were found to have differential effects on consumer attitudes when they were included as moderators. This study finds evidence in support of diminishing effectiveness of female celebrities over time/marriage. In this study, we explored a new dimension of congruence (RCN) and found the same to influence consumer attitudes favourably towards the endorsed product.     

Enhancing Consumer Choice: Are We Making Appropriate Recommendations?

To reduce information search costs, consumers often use choice-making aids. If these aids are to help consumers make choices consistent with their own preferences, as well as reduce search effort, they must be based on choke models consistent with consumers' true preference sets. This study used conjoint analysis to identify these ideal choice models. Thirty-six percent of the subjects were found to use compensatory choice models and 64 percent noncompensatory models. The results suggest a need to base choice-making aids on ideal choice models if the aid is to lead consumers to decisions consistent with true preferences.     

The Pareto rule for frequently purchased packaged goods: an empirical generalization

Many markets have historically been dominated by a small number of best-selling products. The Pareto principle, also known as the 80/20 rule, describes this common pattern of sales concentration. Several papers have provided empirical evidence to explain the Pareto rule, although with limited data. This article provides a comprehensive empirical investigation on the extent to which the Pareto rule holds for mass-produced and distributed brands in the consumer-packaged goods (CPG) industry. We used a rich consumer panel dataset from A.C. Nielsen with 6 years of purchase histories from over 100,000 households. Our analysis utilizes a large number of potential factors such as brand attributes, category attributes, and consumer purchase behavior to explain variation in the Pareto ratio at the brand level across products. Our main conclusion is that the Pareto principle generally holds across a wide variety of CPG categories with the mean Pareto ratio at the brand level across product categories of .73. Several variables related to consumer purchase behavior (e.g., purchase frequency and purchase expenditure) are found to be positively correlated with the Pareto ratio. In addition, niche brands are more likely to have a higher Pareto ratio. Finally, brand/category size, promotion variables, change-of-pace brands, and market competition variables are negatively correlated with the Pareto ratio.     

Estimating choice models in data-sparse environments: Taking advantage of perceived similarity

Research suggests that choice models conditioned on correctly identified consideration sets outperform choice models conditioned on the awareness set (Hauser, 1978; Roberts and Lattin, 1991). However, in data-sparse environments, where purchase history information is not available or not relevant, choice models conditioned on the consideration set often yield nonunique or nonsignificant solutions. In these environments, we propose the use of similarity information to improve the performance of choice models. Support for this position is found in an empirical application involving automobiles.     

Modeling Methods for Discrete Choice Analysis

This paper introduces new forms, sampling and estimation approaches fordiscrete choice models. The new models include behavioral specifications oflatent class choice models, multinomial probit, hybrid logit, andnon-parametric methods. Recent contributions also include new specializedchoice based sample designs that permit greater efficiency in datacollection. Finally, the paper describes recent developments in the use ofsimulation methods for model estimation. These developments are designed toallow the applications of discrete choice models to a wider variety ofdiscrete choice problems.     

Quick and easy choice sets: Constructing optimal and nearly optimal stated choice experiments

In this paper we compare a number of common strategies for constructing discrete choice experiments. Two of the strategies, including one based on theoretical constructions for optimal discrete choice experiments, produce designs that are better than those that come about from random grouping and from using the L^MA construction. A simple account of this theoretical construction is given.     

完全信息条件下企业内部知识共享激励机制研究

基于委托代理理论和企业内部知识共享过程中所呈现的完全信息特征,构建了完全信息条件下企业内部知识共享多阶段激励机制模型。通过最优化一阶条件分别求解员工风险中性与风险规避时的最优激励机制,并分析最优激励机制的特点。研究结果表明:在完全信息条件下的企业内部知识共享过程中企业设计强制合同,帕累托最优合同可以实现,当员工为风险中性时,员工承担全部风险;当员工为风险规避时,员工不承担风险。     

OVERLAPPING SETS OF PRIORS AND THE EXISTENCE OF EFFICIENT ALLOCATIONS AND EQUILIBRIA FOR RISK MEASURES

The overlapping expectations and the collective absence of arbitrage conditions introduced in the economic literature to insure existence of Pareto optima and equilibria with short‐selling when investors have a single belief about future returns, is reconsidered. Investors use measures of risk. The overlapping sets of priors and the Pareto equilibrium conditions introduced by Heath and Ku for coherent risk measures are respectively reinterpreted as a weak no‐arbitrage and a weak collective absence of arbitrage conditions and shown to imply existence of Pareto optima and Arrow–Debreu equilibria.     

A reappraisal of strategic trade policies with the endogenous mode of competition under vertical structures

This paper examines the endogenous choice of competition mode with strategic export policies in vertically related markets when each upstream firm located in each country determines the terms of the two-part tariff contract by maximizing generalized Nash bargaining. We show that (i) choosing Cournot (Bertrand) competition is the dominant strategy for both downstream firms when goods are substitutes (complements), which leads Pareto superior regardless of the nature of goods under the optimal trade policies; (ii) irrespective of rival’s competition mode, the optimal trade policy is an export subsidy under Cournot competition and an export tax under Bertrand competition; and (iii) trade liberalization may give rise to changes of competition mode and increase of social welfare.     

税收监管的会计管理新模式探析——基于临安市会计管理的考察

会计管理模式的选择,直接关系到会计信息的质量和会计管理工作的效果。本文在评析现有会计管理模式的基础上,根据临安市会计管理的相关实践,提出了税收监管的会计管理新模式,剖析了该模式的主要特点,从法学、管理学、经济学视角论证了其可行性。     

LINKED RECURSIVE PREFERENCES AND OPTIMALITY

We study a class of optimization problems involving linked recursive preferences in a continuous‐time Brownian setting. Such links can arise when preferences depend directly on the level or volatility of wealth, in principal–agent (optimal compensation) problems with moral hazard, and when the impact of social influences on preferences is modeled via utility (and utility diffusion) externalities. We characterize the necessary first‐order conditions, which are also sufficient under additional conditions ensuring concavity. We also examine applications to optimal consumption and portfolio choice, and applications to Pareto optimal allocations.