Though recycled toilet paper (RTP) is more environmental friendly than toilet paper made of virgin fiber, they are also more expensive. The price difference has made manufacturers hesitate about marketing RTP in shops, because they assume that consumers are reluctant to buy it. However, no research has been done in Taiwan to explore consumers¡¦ willingness to pay (WTP) for RTP. This study is an attempt to do so by the use of two methods: contingent evaluation method (CVM) and conjoint analysis. Both methods were administered through a survey, which had a convenience sample of 192 female Kaohsiung citizens as respondents. Results based on CVM showed that the mean WTP for RTP was NT 151, which was a little higher than the price set by Homemaker¡¦s Union and Foundation¡Xan NGO which was the main channel selling RTP to the domestic sector in Taiwan. This suggests that manufacturers might have underestimated the market for RTP. To check the validities of the CVM and conjoint method, two criteria were measured: the respondents¡¦ past environmental behavior (PEB) and their willingness to make sacrifice for environmental causes (WTP3). The WTP as estimated by CVM, namely WTP1, was significantly related to both of these criteria (rs = .16, .32, ps < .05), showing that the CVM had a certain degree of validity. The importance that respondents attached to the eco-label of RTP was assessed by conjoint analysis. Validity of the importance scores thus obtained, however, was quite low: the correlation between these scores and WTP1, PEB and WTP3 were .05, .12 and .20 respectively, with only the last one significant. Results also suggest that environmental knowledge and health and safety concerns for products were not related to WTP1. Keywords: green consumption, contingent valuation method, conjoint analysis, environmental behavior, eco-label, green mark.

Thesis (doctoral)--Linköping University, 1996. / Includes abstract. Includes bibliographical references.

This paper presents the fully Bayesian analysis of the latent class model using a new approach towards MCMC estimation in the context of mixture models. The approach starts with estimating unidentified models for various numbers of classes. Exact Bayes' factors are computed by the bridge sampling estimator to compare different models and select the number of classes. Estimation of the unidentified model is carried out using the random permutation sampler. From the unidentified model estimates for model parameters that are not class specific are derived. Then, the exploration of the MCMC output from the unconstrained model yields suitable identifiability constraints. Finally, the constrained version of the permutation sampler is used to estimate group specific parameters. Conjoint data from the Austrian mineral water market serve to illustrate the method. (author's abstract) / Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

No description available.

Conjoint analysis is one of the most important tools to support product development, pricing and positioning decisions in management practice. For this purpose various models have been developed. It is widely accepted that models that take consumer heterogeneity into account, outperform aggregate models in terms of hold-out tasks. The aim of our study is to investigate empirically whether predictions of choice-based conjoint models which incorporate heterogeneity can successfully be generalized to a whole market. To date no studies exist that examine the real world performance of choice-based conjoint models by use of aggregate scanner panel data. Our analysis is based on four commercial choice-based conjoint pricing studies including a total of 43 stock keeping units (SKU) and the corresponding weekly scanning data for approximately two years. An aggregate model serves as a benchmark for the performance of two models that take heterogeneity into account, hierarchical Bayes and latent class. Our empirical analysis demonstrates that, in contrast to the performance using hold-out tasks, the real world performance of hierarchical Bayes and latent class is similar to the performance of the aggregate model. Our results indicate that heterogeneity cannot be generalized to a whole market and suggest that aggregate models are sufficient to predict market shares. (author's abstract) / Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

In many studies, choice based conjoint analysis is used to build a market simulator to develop marketing strategies; i.e., shares-of-preference are taken as market share forecasts. However, conjoint data are collected in interview situations, which may differ considerably from real shopping behavior. In this paper, we test the internal and external validity of four commercial choice based conjoint pricing studies including a total of 43 brands. We use conjoint and sales data to assess the relative performance of two modern approaches to estimate conjoint parameters: the segmentation based Latent Class model and the individual level Hierarchical Bayes approach. Our paper confirms previous results of the internal superiority of the Hierarchical Bayes approach. The main result of our investigation is that internal validity does not predict external validity and that Latent Class shows the same real world performance as Hierarchical Bayes. Both models show an average error of 4.2% in market share level prediction and a correlation of 69% between conjoint forecasts and real market shares. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

In this paper we head for a fully Bayesian analysis of the latent class model with a priori unknown number of classes. Estimation is carried out by means of Markov Chain Monte Carlo (MCMC) methods. We deal explicitely with the consequences the unidentifiability of this type of model has on MCMC estimation. Joint Bayesian estimation of all latent variables, model parameters, and parameters determining the probability law of the latent process is carried out by a new MCMC method called permutation sampling. In a first run we use the random permutation sampler to sample from the unconstrained posterior. We will demonstrate that a lot of important information, such as e.g. estimates of the subject-specific regression coefficients, is available from such an unidentified model. The MCMC output of the random permutation sampler is explored in order to find suitable identifiability constraints. In a second run we use the permutation sampler to sample from the constrained posterior by imposing identifiablity constraints. The unknown number of classes is determined by formal Bayesian model comparison through exact model likelihoods. We apply a new method of computing model likelihoods for latent class models which is based on the method of bridge sampling. The approach is applied to simulated data and to data from a metric conjoint analysis in the Austrian mineral water market. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

Thesis (Ph. D.)--University of Sydney, 2009. / Title from title screen (viewed May 1, 2009) Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Economics to the Faculty of Economics and Business, University of Sydney. Degree awarded 2009; thesis submitted 2008. Bibliography: leaves 93-97. Also available in print form.

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Choi, Seung-Kyum; Committee Member: Allen, Janet K.; Committee Member: Paredis, Chris. Part of the SMARTech Electronic Thesis and Dissertation Collection.

[pt] Dentre as ferramentas mais utilizadas para conquistar a fidelidade do consumidor, destacam-se os programas de fidelidade que, em sua maioria, dão recompensas pelo relacionamento dos clientes com as empresas. Na Internet não é diferente, dado que as empresas virtuais tiveram que se adaptar a nova realidade, na qual o lucro operacional é fundamental à saúde financeira. Nessa dissertação aplicase a teoria de análise conjunta, com o objetivo de apontar o conjunto de características consideradas desejáveis pela classe de consumidores pesquisada acerca de um programa de multi-fidelidade na Internet. O desenvolvimento do trabalho é composto de duas etapas básicas: escolha dos atributos a serem avaliados pelos respondentes e análise dessa avaliação. Para escolher o conjunto de atributos a serem julgados foi utilizada uma entrevista com um grupo de foco. A formação desse conjunto de estímulos foi desenvolvida utilizando-se o software SPSS, versão windows. Em seguida, realizou-se a coleta de dados por meio de questionários, os quais foram enviados por correio eletrônico, sendo que alguns foram entregues pessoalmente. Por fim, também com o auxílio do software SPSS versão windows, o estudo atingiu seu objetivo, identificando o conceito de produto considerado o mais adequado, fruto da combinação de estímulos que gerou maior nível de utilidade. / [en] Among the most common tools used to gain customer s loyalty, companies give a great importance to loyalty programs which, in most cases, give rewards for consumers expenses. It is no different in the internet, as virtual companies had to adapt themselves to a new reality, in which operational profits are essential to their economic health. In this research the conjoint analysis theory is used with the objective of showing the group of characteristics understood as desirable by the class of consumers researched about a multi-loyalty program in the internet. This work is composed of two main basic steps: the choice of the attributes to be evaluated by the respondents and the analysis of this evaluation. The group of stimulus to be evaluated was chosen based on the information collected through the focus group interview. The group of stimulus presentation was developed making use of the SPSS software, for windows. Right after, the data collection was implemented with the questionnaries, sent by e-mail. Some of them were handled personnally. In the last step, also using the SPSS software for windows, this study reached its objective, identifying the concept of product considered the most adequate, as a result of the stimulus combination which generated the highest utility level.