Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2016-08-24T12:37:44Z No. of bitstreams: 1 Fábio Ricardo Becker_.pdf: 1664082 bytes, checksum: e43db272faaa68a87cb6e74ed1a428bc (MD5) / Made available in DSpace on 2016-08-24T12:37:45Z (GMT). No. of bitstreams: 1 Fábio Ricardo Becker_.pdf: 1664082 bytes, checksum: e43db272faaa68a87cb6e74ed1a428bc (MD5) Previous issue date: 2016-05-19 / Nenhuma / A redução dos níveis de produção e consumo tem sido um dos caminhos apontados para mitigação das mudanças climáticas, por consequência permite a redução do uso dos recursos naturais e a queima de combustíveis fósseis, além da redução de outros impactos ambientais e sociais. O presente trabalho aborda o comportamento do comprador organizacional, para isso avalia através de dois estudos experimentais a percepção do comprador para produtos desenvolvidos com atributos sustentáveis a partir de estratégias de ecodesign. O primeiro estudo contou com uma amostra de 139 estudantes e no segundo estudo a amostra foi de 52 gestores de compras. Os procedimentos e métodos utilizados seguiram a abordagem da análise conjunta (conjoint analysis) como estratégia de pesquisa. Os experimentos foram modelados considerando os atributos e seus níveis para a projeção dos estímulos (perfis do produto), além de considerar ainda a consciência ecológica e a intenção de compra do comprador organizacional. Os resultados mostram que, independente da preocupação ambiental e do preço, a durabilidade do produto e a sua eficiência no consumo de energia podem influenciar a decisão de compra, desde que sejam percebidas vantagens como redução de custos e melhor utilização dos recursos. / The reduction of consumption and production levels has been one of the highlighted ways to mitigate climate change, therefore allows reducing the use of natural resources and fossil fuels, as well as reduction of other environmental and social impacts. This paper addresses the organizational buyer behavior, for it evaluates through two experimental studies the perception of the buyer for products developed with sustainable attributes from ecodesign strategies. The first study involved a sample of 139 students and in the second study sample was 52 buyers. The procedures and methods used followed the approach of conjoint analysis as research methods. The experiments were modeled considering the attributes and their levels for the projection of the stimuli (product profiles), and also consider ecological awareness and purchase intention in organizational buyer. The results show that environmental concerns, price, product durability and its efficiency in energy consumption can influence the buying decision, since benefits are perceived as cost reduction and better use of resources.

Ability to measure value from the customer's point of view is central to the determination of market offerings: Customers will only buy the equivalent of perceived value, and companies can only offer benefits that cost less to provide than customers are willing to pay. Conjoint analysis is the most popular individual-level value measurement method to determine relative impact of product or service attributes on preferences and other dependent variables. This research focuses on how value measurement can be made more accurate and more reliable by measuring the relative influence of selected methodological variations on performance in prediction and on stability of value structure, and by grouping customers with similar value structure into segments which respond to product stimuli in a similar manner. Influences of the type of attributes included in the conjoint task, of the factorial design used to construct the product profiles, of the type and form of model, of the time of measurement, and of the type of cluster-based segmentation method, are evaluated. Data was gathered with a questionnaire that controlled for methodological variations, and with a notebook computer as the measurement object. One repeated measurement was taken. The study was conducted in two phases. In Phase I, influences of methodological variations on accuracy in prediction and on respective value structure were examined. In Phase II, different cluster-based segmentation methods--hierarchical clustering (HIC), non-hierarchical clustering (NHC), and fuzzy c-means clustering (FUC)--and according conjoint models were evaluated for their performance in prediction and in comparison with individual-level conjoint models. Results show the best models for a variety of design parameters are traditional individual-level, main-effects-only conjoint models. Neither modeling of interactions, nor segment-level conjoint models were able to improve on prediction. Best segment-level conjoint models were obtained with a fuzzy clustering method, worst models were obtained with k-means and the most fuzzy clustering approach. In conclusion, conjoint analysis reveals itself as a reliable method to measure individual customer value. It seems more rewarding for improvement of accuracy in prediction to apply repeated measures, or gather additional data about the respondent, than to attempt improvement on methodological variations with a single measurement.

Nutrition labeling research suggests consumers want nutrition information on the label; however, many do not comprehend it. The purpose of Phase I was to determine the effect of: 1. two levels of nutrition label formats; 2. three levels of nutrition information load on consumers' preference for product choice using adaptive conjoint analysis. A computer interactive interview was conducted on 252 consumers in Crossroads Mall, Salt Lake City, Utah. label alternatives were printed on soup cans to realistically portray the information. The conjoint analysis compared the attributes, nutrition information format, and nutrition information load in addition to brand and price and determined how the study participants ranked choices within each of these attributes and against the other attributes. There were significant differences (p < .000) among all three mean utility values± Standard Error of the Mean (SEM) of information load, most (.300 ± .03) , more (.154 ± .02), and some (-.231 ± .03). There was no difference between graphical (.093 ± .027) and traditional (.055 ± .020) formats (p = .298). For the other attributes, there were significant differences (p < .000) among all brands, Campbell's (.590 ± .03), Private label (-.007 ± .02) Generic (-.361 ± .03) and all prices, (p < .000), low (.431 ± .03), medium (.022 ± .02), and high (-.230 ± .03). Market simulations were performed and market share was shifted from the major brand when nutrition information was added to a Private label or Generic brand. The purpose of Phase II was to determine the effect of: 1. three levels of nutrition information content load; 2. two levels of nutrition information order; 3. three levels of nutrition information format; and 4. four levels of nutrition information expression on consumers' perceptions of label usefulness in purchase decisions. The methodology was the same as Phase I. There were significant differences (p < .000) among all three mean utility values ± SEM of information load, most (.327 ± .02), more (.091 ± .02) , and some (-.213 ± .03), and between the two mean utility values ± SEM of information order, rearranged (.157 ± .03) and traditional (-.02 ± .02). Consumers significantly preferred (p < .000) the graphical format (.148 ± .02) over the graphical nutrient density (.038 ± .02) and traditional (.018 ± .03) formats. Consumers significantly preferred (p < .000) nutrition information stated in absolute numbers and percentages (.296 ± .03), versus absolute numbers only (.028 ± .03), traditional (-.026 ± .03), and percentages only (-.025 ± .03) expressions. The most useful nutrition label in a purchase decision was one that contained the most information, in a rearranged order, with a graphical format, and an absolute number and percentages expression.

<p>Tendencies in product development of today make it likely that many future products will be functional equivalent and therefore hard to distinguish between for the customer. Customers will decide by highly subjective criteria which product to purchase. One task for product development in this context is to be able to capture the customer’s considerations and feelings of products and translate these emotional aspects into concrete product design.</p><p>Today a number of different methods, such as Quality Function Deployment (QFD), Semantical Environment Description (SMB), Conjoint Analysis and Kansei Engineering exist and are used in practical applications.</p><p>The purpose of this thesis is to understand and apply Kansei Engineering methodology and explore ways to integrate the methodology into an industrial product development process.</p><p>This was done by conducting a study on forklift trucks in different European countries and business areas and by exploring ways of integrating Kansei Engineering in product development processes.</p><p>The number of Kansei words collected was reduced based on the result of a pilot study using a combination of different tools. A computerized data collection method was used in combination with a modified VAS-scale in order to reduce the time for filling out the evaluation forms The results of the study in the visited Northern and Middle European companies make it evident that Kansei Engineering has to be adapted in several aspects to the circumstances in each situation. The data showed that there are differences in attitude towards reach trucks in the different European countries. These results were used in order to adapt the product requirements for each specific country. Starting at Cooper’s stage gate model Kansei Engineering was applied on a macro level, a micro level and for verifying purpose. Using QFD, Kansei Engineering helps to identify customer needs their importance and the technical responses as well as to conduct benchmarking and to connect the customer needs mathematically to the technical responses.</p><p>This study of Kansei Engineering revealed that there was no general model on the methodology available in English literature. Outgoing from a previous flowchart, a conceptual framework of Kansei Engineering was developed integrating the existing Kansei Engineering Types and future tools.</p> / ISRN/Report code: LiU-Tek-Lic 2002:19

This study will examine the importance of Country-of-Origin, Price, Quality and Expiration date, in the consumer decision making process for fresh meat. Country-of-Origin has earlier been investigated, however the research has been focusing on manipulating one single cue. With the recent scandals in the fresh meat industry, were animals being abused and expiration dates being changed, it is interesting to investigate how important the consumers find the four attributes; Country-of-Origin, price, quality and expiration date.In order to answer the research questions, and fulfil the purpose, the authors will use a mix of different data collection methods. Qualitative data will be gathered by performing interviews and quantitative data will be gathered by conducting a pilot study and an experiment. The data will be retrieved with the use of SPSS 17.0 and the conjoint analysis procedure. Country-of-origin has been found to be the most preferred attribute for consumers in their purchasing process for fresh meat, closely followed by expiration date. The consumer did find price and quality to be of importance, however the attributes were not found to be as important as Country-of-Origin and expiration date. As Country-of-Origin was found to be the most significant attribute for consumers in their decision making process, this indicates that the consumers are ethnocentric in their behaviour, i.e. they consider their own country and culture to be above others, which leads to a purchase of Swedish meat. It has also been found that the purchasing process of fresh meat is of great complexity, especially with the negative attention the fresh meat industry has induced.

Decision making is necessary to provide a synthesis scheme to design activities and identify the most preferred design alternative. There exist several methods that address modeling designer preferences in a graphical manner to aid the decision making process. For instance, the Conjoint Analysis has been proven effective for various multi-attribute design problems by utilizing a ranking- or rating-based approach along with the graphical representation of the designer preference. However, the ranking or rating of design alternatives can be inconsistent from different users and it is often difficult to get customer responses in a timely fashion. The high number of alternative comparisons required for complex engineering problems can be exhausting for the decision maker. In addition, many design objectives can have interdependencies that can increase complexity and uncertainty throughout the decision making process. The uncertainties apparent in the attainment of subjective data as well as with system models can reduce the reliability of decision analysis results. To address these issues, the use of a new technique, the Improved Conjoint Analysis, is proposed to enable the modeling of designer preferences and trade-offs under the consideration of uncertainty. Specifically, a simulation-based ranking scheme is implemented and incorporated into the traditional process of the Conjoint Analysis. The proposed ranking scheme can reduce user fatigue and provide a better schematic decision support process. In addition, the incorporation of uncertainty in the design process provides the capability of producing robust or reliable products. The efficacy and applicability of the proposed framework are demonstrated with the design of a cantilever beam, a power-generating shock absorber, and a mesostructured hydrogen storage tank.

<p>This study will examine the importance of Country-of-Origin, Price, Quality and Expiration date, in the consumer decision making process for fresh meat. Country-of-Origin has earlier been investigated, however the research has been focusing on manipulating one single cue. With the recent scandals in the fresh meat industry, were animals being abused and expiration dates being changed, it is interesting to investigate how important the consumers find the four attributes; Country-of-Origin, price, quality and expiration date.In order to answer the research questions, and fulfil the purpose, the authors will use a mix of different data collection methods. Qualitative data will be gathered by performing interviews and quantitative data will be gathered by conducting a pilot study and an experiment. The data will be retrieved with the use of SPSS 17.0 and the conjoint analysis procedure. Country-of-origin has been found to be the most preferred attribute for consumers in their purchasing process for fresh meat, closely followed by expiration date. The consumer did find price and quality to be of importance, however the attributes were not found to be as important as Country-of-Origin and expiration date.<strong> </strong>As Country-of-Origin was found to be the most significant attribute for consumers in their decision making process, this indicates that the consumers are ethnocentric in their behaviour, i.e. they consider their own country and culture to be above others, which leads to a purchase of Swedish meat. It has also been found that the purchasing process of fresh meat is of great complexity, especially with the negative attention the fresh meat industry has induced.</p>

Tourism as one of the biggest industries in the world has been changing continuously and rapidly. The publishing of the Brundtland Report in 1987 has accelerated the discussion about combining economic, social and environmental factors – the so-called triple-bottom line – in order to secure long-term sustainable living conditions on a finite planet for both business and society. This has lead to occurring pressure from different stakeholder groups as for example policy makers or non-governmental organizations (NGO’s) urging for more sustainable business practise within the industry whereas one important pressure group appears to be missing out in this context: the customers of mass tourism products and therefore the demand side within the economic equation. Tourists have been observed to be overall reluctant to pay price premiums for more sustainable travel alternatives and seem to “take vacation” from their everyday green behaviour. Hence at the current point of time eco-tourism appears to be a market niche in which mainly small-scale providers and NGO’s like Nature’s Best in Sweden operate. However integrating mass tourism into the consideration can be seen as a promising opportunity and from an environmental standpoint an urgent necessity as it can be argued that within an industry of this scale, even small improvements towards more sustainable behaviour bear the potential for a substantial impact. The purpose of this study therefore lies in researching the two marketing tools of brands and eco-labels and the influence they can have individually and in combination on the tourist’s decision making delimitated to the context of charter tourism in Sweden. Through the research of this study it was found that currently no directly applicable theory about the combination of brands and eco-labels seems to exist for marketing neither in general, nor for the tourism industry in particular. This strongly indicates the novelty of the topic of combining brands and eco-labels and points out research opportunities. In order to achieve this purpose, a mixed-method research design was used combining qualitative expert interviews from direct business representatives and a quantitative data collection utilizing the scholarly acknowledged marketing research method of conjoint analysis in one of its most up-to-date forms of an adaptive choice-based conjoint analysis. Theory from different fields of study as consumer behaviour and decision making, branding and eco-labelling as well as sustainability marketing was combined and translated into the new and emerging service category of sustainable tourism. From this a conceptual framework was developed combining the data collection results from the mixed-method approach. This leads to the identification of ways for improving current charter tourism companies’ marketing based on the customers’ current view on utilities within certain aspects of the tourism package. Overall this study therefore contributes to the discussion on how demand for sustainable products evolves and can likely be increased. This is seen as a valuable theoretical, practical and societal contribution as it helps improving tourism companies’ understanding of their customer base and supports offering products/services with an improved perceived individual and societal value for charter tourism companies that aim for a higher degree of sustainability in their objectives.

Model development decisions are an important feature of engineering design. The quality of simulation models often dictates the quality of design decisions, seeing as models guide decision makers (DM) in choosing design decisions. A quality model accurately represents the modeled system and is helpful for exploring what-if scenarios, optimizing design parameters, estimating design performance, and predicting the effect of design changes. However, obtaining a quality model comes at a cost in terms of model development--in experimentation, labor, model development time, and simulation time. Thus, DMs must make appropriate trade-offs when considering model development decisions. The primary challenge in model development is making decisions under significant uncertainty. This thesis addresses model development in the conceptual design phase where uncertainty levels are high. In the conceptual design phase, there are many information constraints which may include an incomplete requirements list, unclear design goals, and/or undefined resource constrains. During the embodiment design phase, the overall objective of the design is more clearly defined, and model development decisions can be made with respect to an overall objective function. For example, the objective may be to maximize profit, where the profit is a known function of the model output. In the conceptual design phase, this level of clarity is not always present, so the DM must make decisions under significant model uncertainty and objective uncertainty. In this thesis, conjoint analysis is employed to solicit the preferences of the decision maker for various model attributes, and the preferences are used to formulate a quasi-objective function during the conceptual design phase--where the overall design goals are vague. Epistemic uncertainty (i.e., imprecision) in model attributes is represented as intervals and propagated through the proposed model development framework. The model development framework is used to evaluate the best course of action (i.e., model development decision) for a real-world packaging design problem. The optimization of medical product packaging is assessed via mass spring damper models which predict contact forces experienced during shipping and handling. Novel testing techniques are employed to gather information from drop tests, and preliminary models are developed based on limited information. Imprecision in preliminary test results are quantified, and multiple model options are considered. Ultimately, this thesis presents a model development framework in which decision makers have systematic guidance for choosing optimal model development decisions.

Made available in DSpace on 2015-03-26T13:32:07Z (GMT). No. of bitstreams: 1 texto completo.pdf: 1363370 bytes, checksum: c1941f11abc68868beaef6fe7462af56 (MD5) Previous issue date: 2008-11-17 / Conjoint analysis is a regression analvsis that uses a model with dummy or indicator explanatory variables to study consumer preference for treatments that can be products or services, and are defined by combining levels of each attribute or factor. lt allows the estimation of the Relative Importance (RI ) of each factor that makes up the treatments. Such studies are important to help decide, based on RI estimates obtained from the CA, to which factors should be given more attention when developing the products and/or services. In this research work we conducted a simulation study in order to investigate the robustness of the RI sampling distribution to departures from normality for the distribution of the random error term (&#1108;) of the CA model. We simulated four alternative distributions for &#1108; and generated data (acceptance notes) that allowed estimation of RI for hypothetical factors A, B, C and D considered in our study. In addition to the normal distribution, we used a location and scale transformation of the beta density to generate three alternative distributions: right skewed, left skewed, and also an U-shape distribution. Each one of these four distributions was tested with two standard error values (&#963; = 2.8 and 0.5) which resulted in eight alternative scenarios. Our simulation study considered factors A and B with 3 levels and factors C and D with two levels, hence 36 treatments in a full factorial design. We set reference RI values of 44.25%, 25.66%, 26.55% and 3.54%, respectively for factor A, B, C and D, and simulated data such that each treatment was evaluated by 108 consumers. This data set with 3888 observations was simulated 100 times for each scenario and analyzed by CA which resulted in 100 RI estimates for each factor at every scenario. Results were investigated by 95% confidence intervals (Cl) using the usual normal approximation and also percentile intervals, histograms of RI values sampling distribution to check normality, and also we calculated relative mean errors of estimation (RME) with respect to the reference RI values It was observed that the confidence intervals included the values of RI´s taken as reference in all scenarios, with the exception of: (i) factors A and B, with the normal Cl using normal distribution and &#963; = 2.8; ( i i ) wi th normal Cl and &#963; = 0.5, (iia) for factors A and C with normal distribution, U shaped and left skewed; (iib) for factor B with U shaped model and (iic) for factor D with normal distribution and U shaped. In al l these cases were the Cl missed the RI reference value, we observed close miss left and miss right results. We observed RME < 5% in all scenarios except for normal distribution and factor D only, for which RME = 7.91%. We concluded that sampling distribution of the estimator of the RI of a factor is relatively robust to departures from the normal distribution. In fact, results showed that i t s sampl ing dist r ibut ion must be close to the normal, regardless of the distribution of the random error term of the CA model. / Conjoint analysis ou análise conjunta de fatores (ANCF) é uma análise de regressão que utiliza um modelo com variáveis explicativas indicadoras ou dumnmy, para se estudar a preferência de consumidores por tratamentos que podem ser servidos ou produtos, e que são definidos pela combinação de níveis de diversos atributos ou fatores. Com essa técnica estima-se a Importância Relativa (IR) de cada fator que compõe os tratamentos avaliados. Tais estudos são importantes por permitir decidir, com base nas estimativas das IR de cada fator, quais devem ser observados com maior atenção na definição do tratamento. No presente trabalho foi realizado um estudo por simulação para se investigar a robustez da distribuição amostral do estimador da IR de um fator, à variação na distribuição do erro aleatório do modelo de regressão empregado na ANCF. Foram gerados erros aleatórios com a distribuição normal e também três outras distribuições alternativas obtidas por uma transformação de locação e escala da beta: uma distribuição assimétrica à direita, outra assimétrica à esquerda e uma com forma U. Para cada distribuição, utilizou-se desvio-padrão &#963; = 2,8 e &#963; = 0,5, portanto para oito condições foram simulados 100 conjuntos de dados referentes a avaliações (notas de aceitação) de 108 consumidores para cada um dos 36 tratamentos formados pela combinação de 4 fatores (A, B, C e D) num esquema fatorial completo 32 x 22. Definiu-se com base em um modelo de regressão para ANCF, valores de referências para as IR's iguais a 44,25%, 25,66%, 26,55% e 3,54%, respectivamente para os fatores A, B. C e D. Na avaliação dos resultados com base em intervalos de confiança percentil e pela aproximação normal, ambos a 95%, verificou-se intervalos mais estreitos pela aproximação normal. Conforme esperado, verificou-se intervalos de confiança para as IR´s mais amplos quando &#963; = 2,8. Observou-se que todos os intervalos de confiança incluíram os valores das IR's tomados como referência, exceto para os seguintes casos: (i) intervalo de confiança pela aproximação normal para a simulação de erros com distribuição normal e &#963; = 2,8, para os fatores A e B; (ii) com intervalo pela aproximação normal e &#963; = 0,5, (iia) para os fatores A e C com distribuição normal, em forma de U e assimétrica à esquerda; (iib) para o fator B com distribuição em forma de U; e (iic) para o fator D com distribuição normal e em forma de U . Entretanto, neste casos de não inclusão do valor IR de referência nos intervalos, observou-se que o valor estava próximo ao limite do IC, tanto à esquerda quanto à direita. As estimativas de IR obtidas no estudo por simulação também foram avaliadas pelo Erro Médio Relativo (EMR) com relação aos respectivos valores de referência. Exceto para o fator D na simulação com erros normais e &#963; = 2,8, na qual se obteve EMR = 7,91%, em todas as demais situações simuladas obteve-se EMR < 5%. Adicionalmente, o teste de Kolmogorov-Smirnov indicou normalidade (p > 0,05) das distribuições amostrais em todos os casos. Concluiu-se que o estimador da IR pode ser considerado como robusto à não nor-malidade da distribuição do erro aleatório do modelo de regressão utilizado na ANCF. Adicionalmente, pode-se considerar que a distribuição amostral da IR seja normal e que portanto métodos inferenciais que requerem normalidade podem ser aplicados às estimativas de lR's obtidas na ANCF.