Exploratory Approach to the use of Techniques of Regression Analysis and Pooled Analysis in Studies of Consumer Behavior

This paper is part of a large study to assess the adequacy of the use of multivariate statistical techniques in theses and dissertations of some higher education institutions in the area of marketing with theme of consumer behavior from 1997 to 2006. The regression and conjoint analysis are focused on in this paper, two techniques with great potential of use in marketing studies. The objective of this study was to analyze whether the employement of these techniques suits the needs of the research problem presented in as well as to evaluate the level of success in meeting their premisses. Overall, the results suggest the need for more involvement of researchers in the verification of all the theoretical precepts of application of the techniques classified in the category of investigation of dependence among variables.

Conjoint-analyysi tuotekonseptien suunnittelun tukena

Conjoint-analyysi on kvantitatiivinen menetelmä kuluttajien mieltymysten mittaamiseen. Sitä hyödynnetään yleisesti tuotekonseptien suunnitteluvaiheessa, jossa jatkokehitykseen otettavaa konseptia valittaessa asiakkaiden mieltymysten tiedostaminen on hyvin tärkeää tuotteen lopullisen menestyksen kannalta. Työn tavoitteena on esitellä lukijalle conjoint-analyysin toimintaperiaate ja selvittää millaista lisäarvoa conjoint-analyysin käyttö voi tuoda tuotekonseptien suunnitteluun. Työssä määritellään lyhyesti mitä tuotekonseptointi on ja kuinka se sijoittuu tuotekehityksen kenttään sekä esitellään sen syitä ja tavoitteita. Conjoint-analyysin suorittaminen käydään läpi vaihe vaiheelta ja esitellään siihen liittyviä yleisiä käytäntöjä. Lisäksi määritellään muutamia yleisiä tavoitteita, joita tyypillisesti halutaan conjoint-tutkimuksen avulla toteuttaa. Työn empiirisessä osassa teoriaosan sisältöä konkretisoidaan esittelemällä ja analysoimalla muutamia eri syistä toteutettuja conjoint-tutkimuksia ja niiden tarjoamia tuloksia.

Prioritization of Potential Mates' History of Sexual Fidelity During a Conjoint Ranking Task

This series of studies is the first to use conjoint analysis to examine how individuals make trade-offs during mate selection when provided information about a partner's history of sexual infidelity. Across three studies, participants ranked profiles of potential mates, with each profile varying across five attributes: financial stability, physical attractiveness, sexual fidelity, emotional investment, and similarity. They also rated each attribute separately for importance in an ideal mate. Overall, we found that for a long-term mate, participants prioritized a potential partner's history of sexual fidelity over other attributes when profiles were ranked conjointly. For a short-term mate, sexual fidelity, physical attractiveness, and financial stability were equally important, and each was more important than emotional investment and similarity. These patterns contrast with participants' self-reported importance ratings of each individual attribute. Our results are interpreted within the context of previous literature examining how making trade-offs affect mate selection.

A generalized adaptive mathematical morphological filter for LIDAR data

Airborne Light Detection and Ranging (LIDAR) technology has become the primary method to derive high-resolution Digital Terrain Models (DTMs), which are essential for studying Earth's surface processes, such as flooding and landslides. The critical step in generating a DTM is to separate ground and non-ground measurements in a voluminous point LIDAR dataset, using a filter, because the DTM is created by interpolating ground points. As one of widely used filtering methods, the progressive morphological (PM) filter has the advantages of classifying the LIDAR data at the point level, a linear computational complexity, and preserving the geometric shapes of terrain features. The filter works well in an urban setting with a gentle slope and a mixture of vegetation and buildings. However, the PM filter often removes ground measurements incorrectly at the topographic high area, along with large sizes of non-ground objects, because it uses a constant threshold slope, resulting in "cut-off" errors. A novel cluster analysis method was developed in this study and incorporated into the PM filter to prevent the removal of the ground measurements at topographic highs. Furthermore, to obtain the optimal filtering results for an area with undulating terrain, a trend analysis method was developed to adaptively estimate the slope-related thresholds of the PM filter based on changes of topographic slopes and the characteristics of non-terrain objects. The comparison of the PM and generalized adaptive PM (GAPM) filters for selected study areas indicates that the GAPM filter preserves the most "cut-off" points removed incorrectly by the PM filter. The application of the GAPM filter to seven ISPRS benchmark datasets shows that the GAPM filter reduces the filtering error by 20% on average, compared with the method used by the popular commercial software TerraScan. The combination of the cluster method, adaptive trend analysis, and the PM filter allows users without much experience in processing LIDAR data to effectively and efficiently identify ground measurements for the complex terrains in a large LIDAR data set. The GAPM filter is highly automatic and requires little human input. Therefore, it can significantly reduce the effort of manually processing voluminous LIDAR measurements.

Sparse time-frequency data analysis : a multi-scale approach

In this work, we further extend the recently developed adaptive data analysis method, the Sparse Time-Frequency Representation (STFR) method. This method is based on the assumption that many physical signals inherently contain AM-FM representations. We propose a sparse optimization method to extract the AM-FM representations of such signals. We prove the convergence of the method for periodic signals under certain assumptions and provide practical algorithms specifically for the non-periodic STFR, which extends the method to tackle problems that former STFR methods could not handle, including stability to noise and non-periodic data analysis. This is a significant improvement since many adaptive and non-adaptive signal processing methods are not fully capable of handling non-periodic signals. Moreover, we propose a new STFR algorithm to study intrawave signals with strong frequency modulation and analyze the convergence of this new algorithm for periodic signals. Such signals have previously remained a bottleneck for all signal processing methods. Furthermore, we propose a modified version of STFR that facilitates the extraction of intrawaves that have overlaping frequency content. We show that the STFR methods can be applied to the realm of dynamical systems and cardiovascular signals. In particular, we present a simplified and modified version of the STFR algorithm that is potentially useful for the diagnosis of some cardiovascular diseases. We further explain some preliminary work on the nature of Intrinsic Mode Functions (IMFs) and how they can have different representations in different phase coordinates. This analysis shows that the uncertainty principle is fundamental to all oscillating signals.

Socioeconomic Differences in Preferences and Willingness-to-Pay for Insulin Delivery Systems in Type 1 and Type 2 Diabetes

Background: An evaluation of patients' preferences is necessary to understand the demand for different insulin delivery systems. The aim of this study was to investigate the association between socioeconomic status (SES) and patients' preferences and willingness to pay (WTP) for various attributes of insulin administration for diabetes management. Methods: We conducted a discrete choice experiment (DCE) to determine patients' preferences and their WTP for hypothetical insulin treatments. Both self-reported annual household income and education completed were used to explore differences in treatment preferences and WTP for different attributes of treatment across different levels of SES. Results: The DCE questionnaire was successfully completed by 274 patients. Overall, glucose control was the most valued attribute by all socioeconomic groups, while route of insulin delivery was not as important. Patients with higher incomes were willing to pay significantly more for better glucose control and to avoid adverse events compared to lower income groups. In addition, they were willing to pay more for an oral short-acting insulin ($Can 71.65 [95% confidence interval, $40.68, $102.62]) compared to the low income group ($Can 9.85 [95% confidence interval, 14.86, 34.56; P < 0.01]). Conversely, there were no differences in preferences when the sample was stratified by level of education. Conclusions: This study revealed that preferences and WTP for insulin therapy are influenced by income but not by level of education. Specifically, the higher the income, the greater desire for an oral insulin delivery system, whereas an inhaled route becomes less important for patients.

Investigating the gap between citizens` sustainability attitudes and food purchasing behaviour: empirical evidence from Brazilian pork consumers

Consumers worldwide are increasingly concerned with sustainable production and consumption. Recently, a comprehensive study ranked 17 countries in regard to their environmentally friendly behaviour among consumers. Brazil was one of the top countries in the list. Yet, several studies highlight significant differences between consumers` intentions to consume ethically, and their actual purchase behaviour: the so-called `Attitude-Behaviour Gap`. In developing countries, few studies have been conducted on this issue. The objective of this study is therefore to investigate the gap between citizens` sustainability-related attitudes and food purchasing behaviour using empirical data from Brazil. To this end, Brazilian citizens` attitudes towards pig production systems were mapped through conjoint analysis and their coexistence with relevant pork product-related purchasing behaviour of consumers was investigated through cluster analysis. The conjoint experiment was carried Out with empirical data collected from 475 respondents surveyed in the South and Center-West regions of Brazil. The results of the conjoint analysis were used for a subsequent cluster analysis in order to identify clusters of Brazilian citizens with diversified attitudes towards pig production systems, using socio-demographics, attitudes towards sustainability-related themes that are expected to influence the way they evaluate pig production systems, and consumption frequency of various pork products as clusters` background information. Three clusters were identified as `indifferent`, `environmental conscious` and `sustainability-oriented` citizens. Although attitudes towards environment and nature had indeed an influence on citizens` specific attitudes towards pig farming at the cluster level, the relationship between `citizenship` and consumption behaviour was found to be weak. This finding is similar to previous research conducted with European consumers: what people (in their role of citizens) think about pig production systems does not appear to significantly influence their pork consumption choices. Improvements in the integrated management of this chain would better meet consumers` sustainability-related expectations towards pig production systems.

"Owned by...". Country of origin's new cue

This study identifies and explores a new country of origin (COO) cue, “owned by….” The importance of three extrinsic cues “owned by …,” “made in …” and price was examined using conjoint analysis. Data were collected from a sample of 268 undergraduate students familiar with color televisions. Segments were formed using cluster analysis and analyzed using multiple discriminant analysis. “Owned by …” was found to be important and distinct from the “made in …” cue. Segments based on the two COO cues were identified using importance weights and individual utilities. When segments were formed using individual utilities the individual difference construct, economic nationalism, provided discriminatory power while consumer ethnocentrism did not, supporting the hypothesis that economic nationalism and consumer ethnocentrism differ. Practitioners can now use “owned by …” knowing that it forms an important and distinct marketing tool. Limitations and future research are discussed.

Planning Considerations for Tourism in the Minho-Lima Region (Northwest Portugal)

In administering their territories, most local municipalities aim to preserve their natural, historical and ethnographical resources while simultaneously using them to increase revenue and employment. In order to efficiently promote the products and services available and attract tourists, decision makers, private and public, need to know and incorporate tourists’ preferences in their marketing strategies. In this chapter we illustrate the use of stated preferences as an instrument to identify national and foreign tourists’ preferences regarding the products and services that the touristic destination of the Minho-Lima region (Northwest Portugal) should offer. As a starting point, we have taken the three general groups of touristic resources mentioned above as attributes. We take Ponte de Lima, a municipality in this region that has a strong cultural tourism potential as an example to identify possible future tourism scenarios for this territory. We believe the previously identified methodology can be a valuable instrument in the identification of the strengths and weaknesses of the selected territory and, thus, support the decision making process behind its future tourist development and marketing strategies.

What do broadband consumers want? Design and execution of a questionnaire on demand for bundled services on the Portuguese telecomunications market

The report addresses the question of what are the preferences of broadband consumers on the Portuguese telecommunication market. A triple play bundle is being investigated. The discrete choice analysis, adopted in the study, base on 110 responses, mainly from NOVA students. The data for the analysis was collected via manually designed on-line survey. The results show that the price attribute is relatively the most important one while the television attribute is being overlooked in the decision making process. Main effects examined in the research are robust. In addition, "extras" components are being tested in terms of users' preferences.

Union Mediation and Adaptation to Reciprocal Loyalty Arrangements

This study assesses the industrial relations application of the „loyalty-exit-voice‟ proposition. The loyalty concept is linked to reciprocal employer-employee arrangements and examined as a job attribute in a vignette questionnaire distributed to low and medium-skilled employees. The responses provided by employees in three European countries indicate that reciprocal loyalty arrangements, which involve the exchange of higher effort for job security, are one of the most desirable job attributes. This attribute exerts a higher impact on the job evaluations provided by unionised workers, compared to their non-union counterparts. This pattern is robust to a number of methodological considerations. It appears to be an outcome of adaptation to union mediated cooperation. Overall the evidence suggests that the loyalty-job evaluation profiles of unionised workers are receptive to repeated interaction and negative shocks, such as unemployment experience. This is not the case for the non-union workers. Finally, unionised workers appear to „voice‟ a lower job satisfaction, but exhibit low „exit‟ intentions, compared to the non-unionised labour.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Product Launch in Industrial Markets – Financial Risks in New AMD Elevator Door Launch

Tuotekehitys ja uusien tuotteiden lanseeraus on teollisen yrityksen menestyksekkään liiketoiminnan elinehtoja tämän päivän kilpailussa. Teollisuusyrityksen tuotteiden innovaatioaikakausia on ollut lukuisia, samoin kuin uuden tuotteen lanseerauksen lähtökohtia. Aikakausista, jolloin tuotteita kehitettiin yrityksen omista lähtökohdista, kuten valmistuksellisista eduista, on edetty tilanteeseen, jossa markkinoiden tarpeita tulee ottaa yhä enemmän huomioon. Kuitenkin, teollisuudessa esitellään tuotteita yhä puhtaasti tuotantolähtöisesti, ja tutkimuksen tavoitteena on selvittää taloudellisia riskejä, joita liittyy puhtaasti teknologiavetoiseen tuotteiden kehitystyöhön, valmistukseen ja lanseeraukseen. Normatiivisena tutkimuksena työ pyrkii asiakastarpeita ja teollisuusyrityksen loppuasiakkaiden näkökulmia huomioon ottaen osoittamaan markkinoinnin keinojen merkityksen tuotantolähtöisen tuotelanseerauksen taloudellisten riskien minimoimiseksi. Uuden teollisen tuotteen asiakastarpeita on selvitetty kyselymuotoisen markkinointitutkimuksen menetelmiä hyväksikäyttäen. Tuotteen tärkeimpien ominaisuuksien, kuten turvallisuuden, kestävyyden ja hinnan merkitystä voidaan hyödyntää ennen tuotteen kaupallista esittelyä potentiaalisten asiakassegmenttien kartoitukseen ja menestyksellisen lanseerauksen edesauttamiseksi.

Avaliação da intenção de compra de couve minimamente processada

Vários fatores influenciam a percepção do produto pelo consumidor e, conseqüentemente, sua intenção de compra. Dentre tais fatores pode estar a expectativa criada pelas características da embalagem e do rótulo, pois representam o primeiro contato entre o indivíduo e o produto. O objetivo desse trabalho foi avaliar o efeito das características da embalagem na intenção de compra de couve minimamente processada, considerando as diferenças individuais dos consumidores para processar as informações. Cinco características da embalagem de couve minimamente processada (informação, tipo de produção, cor, preço e visibilidade do produto) foram manipuladas e 12 embalagens criadas seguindo delineamento fatorial incompleto. A intenção de compra para o produto foi avaliada por 144 consumidores baseada apenas na observação das referidas embalagens. Os dados foram analisados utilizando Conjoint e Cluster Analyses. Os resultados apontaram para um segmento único de consumidores, composto por indivíduos com percepção do produto bastante similar quanto à intenção de compra. Dentre as características da embalagem, a informação foi a que obteve maior importância relativa (77%), enfatizando seu papel na intenção de compra para esse grupo de consumidores. Em seguida, o tipo de produção, cor e preço também contribuíram significativamente (p<0,0001) na intenção de compra de couve minimamente processada, havendo maior intenção de compra para a embalagem com a característica "sem produtos químicos" e preço baixo.

Fatores da embalagem de café orgânico torrado e moído na intenção de compra do consumidor

O efeito de algumas características da embalagem de café orgânico sobre a intenção de compra do consumidor foi avaliado, utilizando-se a conjoint analysis. Quatro características, cada uma com dois níveis, foram manipuladas: preço do produto (alto e baixo), cor da embalagem (vermelha e verde), marca (conhecida e desconhecida) e informação sobre orgânicos (com e sem os dizeres "produto isento de agrotóxicos" e "não agride o meio ambiente"). Dezesseis embalagens hipotéticas foram criadas seguindo o delineamento fatorial completo e avaliadas por 144 consumidores, de acordo com a intenção de compra. O modelo clustering segmentation foi utilizado para a análise dos dados. A marca conhecida afetou positivamente a intenção de compra de 93% dos consumidores. Embalagens possuindo preço alto conferiram impacto negativo na intenção de compra de todos os participantes. A cor da embalagem teve pouco impacto na avaliação. As informações adicionais sobre orgânicos afetaram positivamente a intenção de compra de 79% dos participantes, demonstrando que consumidores gostam de encontrar informações sobre o produto descritas na embalagem.