Knowledge Space Theory (KST) links in several ways to Formal Concept Analysis (FCA). Recently, the probabilistic and statistical aspects of KST have been further developed by several authors. We review part of the recent results, and describe some of the open problems. The question of whether the outcomes can be useful in FCA remains to be investigated.

As many buying decision are made in retail stores, it is interesting to investigate which factors, such as noise, lighting, music, colour, layout or visual communication have a significant influence on customers’ behaviour in a supermarket. Since only a few studies have been conducted among customers in Sweden, this paper examined their behaviour in the supermarket. The purpose of this study was to examine the role of the various environmental factors in the supermarket as well as how the perceived servicescape influences customers’ behaviour in the store. The research approach used was that of a single case study, based on survey instrument (personal interviews and electronic collection) in order to collect data on facets in regards to the perceived servicescape and customers’ behaviour in the supermarket. A supermarket chain – the ICA group, precisely ICA MAXI in Jönköping was used for this purpose. The collected data was analysed with the means of factor analysis and multiple regression methods in order to obtain factors that can influence customers’ behaviour in the supermarket. The conducted study showed that lighting, noise, colours, signs and symbols as well as space/function conditions such as layout and equipment are the factors that create emotionally pleasant environment in the supermarket. Thus, these factors influence customers’ moods, attitudes or certain beliefs about the supermarket. Moreover, customers may feel happier, more satisfied or relaxed in the supermarket, which lead to arousal – stimulation or excitement. Furthermore, the environmental factors explain the approach behaviour such as exploring the supermarket, spending more time on browsing the products which, consequently, refer to an increased number of items bought.

This research aims at providing methods in analyzing and estimating the taxi times of aircraft at airports, which are expected to be an important element for reducing taxiing delay and consequent excess fuel consumption and environmental costs. The proposed model involves a set of regression equations to model the taxi-out and taxi-in times at airports. The estimated results can be used to calculate the nominal taxi times, which are essential measures for evaluating the taxiing delays at airports. Given the outcomes of the regression model, an iterative algorithm is developed to predict taxi times. A case study at LGA shows that the proposed algorithm demonstrates higher accuracy in comparison to other algorithms in existing literature.

This dissertation consists of three chapters. The first chapter titled ``U.S. Grass-fed Beef Price Premiums" examined monthly retail-level price premiums for grass-fed beef (relative to conventional grain-fed beef) in the U.S. from 2014 through 2021. We found that premiums were heterogeneous, with premium cuts (such as sirloin steak, tenderloin, ribeye, and filet mignon) enjoying the highest premiums. Premiums were not consistent with price levels, as the lowest premiums were observed for short ribs, skirt steak, and flank steak. Our findings suggest that grass-fed beef price premiums were negatively affected by the consumption of food away from home. Changes in income, increased information about taste, protein and minerals, fat, revocation of the USDA grass-fed certification program in 2016 and COVID-19 pandemic, also affected premiums for several individual cuts. Premiums were not sensitive to changes in information about climate change. The second chapter, ``Impact of Animal Disease Outbreaks on The U.S. Meat Demand'', examined the impact of the mad cow (BSE) and bird flu (AI) outbreaks on the demand for beef, pork, and broilers in the U.S from 1997 to 2019. Using time-varying elasticities obtained from a Rotterdam model with animal disease cases, we found that BSE outbreaks reduced beef consumption by 0.64 percent and increased pork consumption by 2.34 percent, on average. While BSE outbreaks reduced beef demand, these effects were short lived and did not extend beyond one quarter. On the other hand, broiler consumption decreased during the HPAI outbreaks while beef and broiler consumption increased after such outbreaks. Our time-varying cross-price elasticities indicated that substitution between beef and broilers and beef and pork strengthened after Quarter 4 of 2003. The third chapter is titled ``Impact of North American Mad Cow Disease Outbreaks on The U.S. Cattle Futures". Our study developed a distributional event response model (DERM) framework to show the duration and magnitude of market responses of the U.S. cattle futures market during episodes of mad cow disease (BSE) in North America between 2010 and 2019. Our results indicated that the 2017 U.S. BSE outbreak reduced the returns of live cattle futures. Additionally, the average duration of the BSE event response was about 8.5 days. / Doctor of Philosophy / This dissertation focused on the price analysis of the U.S. livestock market. The first chapter analysed the pattern of grass-fed beef price premiums measured as the difference between grass-fed beef price and conventional beef price. We mainly explored how the premiums were affected by consumers' income, food consumption away from home, and information on climate change, beef taste, and nutrition. We found that consumption of food away from home reduced the grass-fed beef price premiums. In addition, increased information about taste, protein and minerals, fat, and COVID-19 pandemic, could also affected the grass-fed premiums for several individual cuts. The second chapter explored how mad cow diseases and bird flu diseases affected the demand for beef, pork, and chicken. We particularly investigated how each disease outbreak affected the meat demand. My result showed that in the presence of mad cow diseases in the U.S., people bought more pork. This result that retailers should have higher pork demand when mad cow diseases are detected. The third chapter explored how mad cow diseases in North America affected the U.S. live cattle futures. We showed that the U.S. mad cow disease in 2017 reduced the returns of U.S. cattle futures and this impact lasted about 8.5 days. Simultaneously, we found that mad cow disease outbreaks in Canada did not significantly affect the U.S. cattle futures.

Testes Adaptativos Computadorizados (TAC) são aqueles que selecionam gradativamente as questões (itens) a serem apresentadas ao indivíduo de acordo com o seu nível de conhecimento (traco latente). Um TAC pode se basear em um modelo da Teoria da Resposta ao Item (TRI) para a estimação do traco latente e escolha do item a ser apresentado em cada passo do teste. Este trabalho apresenta modelos da TRI utilizados em TAC encontrados na literatura e descreve alguns métodos de calibração de itens para a formação e manutenção do banco de questões do teste sob o modelo de Samejima (1969), estimação do traço latente, seleção de itens com restrições utilizando a abordagem Shadow test e critérios de parada normalmente utilizados. Foram realizadas simulações com um banco grande (500 itens) e com um banco pequeno (21 itens) e avaliada a qualidade das estimativas dos traços latente (através do cálculos dos vícios e erros quadráticos médios) de TACs com diferentes números de itens. Foi aplicado o modelo de Samejima às respostas de estudantes do Exame ao proficiência em inglês (EPI) do ICMC - USP, que é aplicado semestralmente no formato lápis e papel, para a formação de um banco de itens e posterior construção de um TAC. Também foi aplicado o modelo às respostas de pacientes clínicos do Hospital das Clínicas da Medicina da USP, cedido pelo doutor Yuang-Pang Wang, ao Inventário de Depressão de Beck (BDI) para os mesmos propósitos. Comparações com a atual metodologia para avaliação da proficiência em língua inglesa do EPI (Medida de Probabilidade Admissível, MPA) e para o diagnóstico de depressão do BDI (critério sugerido por Kendall et al., 1987) foram realizadas demonstrando as vantagens e maior riqueza dos resultados obtidos com a TRI e com os TACs implementados. Adcionalmente foi desenvolvido um programa Same-CAT que armazena bancos de itens e possibilita a criação e aplicação de TACs com restrições, através da abordagem Shadow test / Computerized Adaptive Tests (CAT) are those that select questions (items) gradually to be presented to an individual according to their proficiency (latent trait level). A CAT can be based on an Item Response Theory (IRT) model for estimation of the latent trait and selection of the next item to be presented in each step of the test. This paper presents IRT models used in CATs found in literature and describes some methods of item calibration for creation and maintenance of a test items bank under the Samejima\'s model (Samejima; 1969), estimation of latent trait, item selection with constraints using the Shadow test approach and usuals stopping criteria. Simulations were conducted with a large bank (500 items) and a small bank (21 items) and the quality of the estimatives of latent traits were evaluated (through calculations of mean squared errors and bias) TACs with different item numbers. Samejima\'s model were applied for the responses of students to the English Proficiency Exam (EPE) of ICMC - USP, a test applied twice a year in paper and pencil format, to create an item bank and subsequent construction of a CAT. The model was also applied to the responses of clinical patients from the Hospital das Clnicas - USP, given by Dr. Yuang-Pang Wang, to the Beck Depression Inventory (BDI) for the same purposes. Comparisons using the current methodology to evaluate the English Language Proficiency of EPE (Measure of Probability Allowable, MPA) and the BDI (criterion suggested by Kendall et al., 1987) were performed, and the CATs provided better and richer results. Furthermore a program, Same-CAT, that stores item banks and allows CAT\'s applications with constraints was created

It is important for fashion companies to be active in e-commerce landscape as it is growing rapidly especially in the apparel sector. As shopping is considered being an experience, it is important for companies to make the shopping experience pleasant for consumers and create positive emotions that lead to positive response behaviors. In online environments, this can be created through using low and high task-relevant atmospheric cues on the website. The purpose of this study is to describe how low task-relevant atmospheric cues affect consumers' emotions and responses in the online retail environment. Furthermore the aim is to analyze which of the examined low task-relevant cues have the strongest impact on consumers’ emotions and responses. To fulfill the purpose, a qualitative research approach has been chosen. The qualitative data was collected through ten semi-structured interviews with fashion interested new or experienced female online consumers in the age between 20-30 years old. This research shows that emotions and response behaviors are strongly connected and influenced by low task-relevant atmospheric cues. A connection within the response categories was also found. Furthermore, when designing a website, certain elements such as layout, color, images together with sales and promotional signage can be designed to achieve desired emotions as these are have the strongest impact on consumers' emotions and responses. / Program: Master programme in Fashion Management

This research study examined the psychometric properties of the Student Risk Screening Scale for Internalizing and Externalizing Behaviors (SRSS-IE) using Item Response Theory (IRT) methods among a sample of 2,122 middle school students. The SRSS-IE is a recently revised screening instrument aimed at identifying students who are potentially at risk for emotional and behavioral disorders (EBD). There are two studies included in this research. Study 1 utilized the Nominal Response and Generalized Partial Credit models of IRT to evaluate items from the SRSS-IE in terms of the degree to which the response options for each item functioned as intended by the scale developers and how well those response options discriminated among students who exhibited varying levels of EBD risk. Results from this first study indicated that the four response option configurations of the items on the SRSS-IE may not adequately discriminate among the frequency of externalizing and internalizing behaviors demonstrated by middle school students. Recommendations for item response option revisions or scale scoring revisions are discussed in this study. In study 2, differential item functioning (DIF) and differential step functioning (DSF) methods were used to examine differences in item and response option functioning according to student gender variables. Additionally, test information functions (TIFs) were used to determine whether preliminary recommendations for cut scores differ by gender. Results of this second study indicate that two of the items on the SRSS-IE systematically favor males over females and one item systematically favors females over males. Additionally, examination of TIFs demonstrated different degrees of measurement precision at various levels of theta for males and females on both the externalizing and internalizing constructs. Implications of these results are discussed in relation to possible revisions of the SRSS-IE items, cut scores, or scale scoring procedures.

This dissertation identifies key determinants of outbound cross-border mergers and acquisitions (M&As) by emerging Asian acquirers during 2001-2012. Using a zero-inflated model that takes into account different mechanisms governing country pairs that never engage in cross-border M&As and country pairs that actively participate in cross-border M&As, I uncover unique patterns for emerging Asian acquirers. Emerging Asian acquirers originate from countries with lower corporate tax rates than those countries where their targets are located. Furthermore, the negative impact of an international double tax burden is significantly larger than that found in previous studies. While country governance differences and geographical and cultural differences are important determinants of international M&As, relative valuation effects are muted. Coefficients of these determinants vary substantially, depending on whether targets are located in developing or advanced nations. Also, determinants differ considerably between active and non-active players in cross-border M&As. Moreover, comparisons of empirical models illustrate that estimating a non-linear model and taking into account both the bounded nature and non-normal distributions of fractional response variables lead to different inferences from those drawn from a linear model estimated by the ordinary least squares method. Overall, emerging Asian acquirers approach the deals differently from patterns documented in developed markets. So, when evaluating foreign business combinations or devising policies, managers or policymakers should consider these differences.

Testes Adaptativos Computadorizados (TAC) são aqueles que selecionam gradativamente as questões (itens) a serem apresentadas ao indivíduo de acordo com o seu nível de conhecimento (traco latente). Um TAC pode se basear em um modelo da Teoria da Resposta ao Item (TRI) para a estimação do traco latente e escolha do item a ser apresentado em cada passo do teste. Este trabalho apresenta modelos da TRI utilizados em TAC encontrados na literatura e descreve alguns métodos de calibração de itens para a formação e manutenção do banco de questões do teste sob o modelo de Samejima (1969), estimação do traço latente, seleção de itens com restrições utilizando a abordagem Shadow test e critérios de parada normalmente utilizados. Foram realizadas simulações com um banco grande (500 itens) e com um banco pequeno (21 itens) e avaliada a qualidade das estimativas dos traços latente (através do cálculos dos vícios e erros quadráticos médios) de TACs com diferentes números de itens. Foi aplicado o modelo de Samejima às respostas de estudantes do Exame ao proficiência em inglês (EPI) do ICMC - USP, que é aplicado semestralmente no formato lápis e papel, para a formação de um banco de itens e posterior construção de um TAC. Também foi aplicado o modelo às respostas de pacientes clínicos do Hospital das Clínicas da Medicina da USP, cedido pelo doutor Yuang-Pang Wang, ao Inventário de Depressão de Beck (BDI) para os mesmos propósitos. Comparações com a atual metodologia para avaliação da proficiência em língua inglesa do EPI (Medida de Probabilidade Admissível, MPA) e para o diagnóstico de depressão do BDI (critério sugerido por Kendall et al., 1987) foram realizadas demonstrando as vantagens e maior riqueza dos resultados obtidos com a TRI e com os TACs implementados. Adcionalmente foi desenvolvido um programa Same-CAT que armazena bancos de itens e possibilita a criação e aplicação de TACs com restrições, através da abordagem Shadow test / Computerized Adaptive Tests (CAT) are those that select questions (items) gradually to be presented to an individual according to their proficiency (latent trait level). A CAT can be based on an Item Response Theory (IRT) model for estimation of the latent trait and selection of the next item to be presented in each step of the test. This paper presents IRT models used in CATs found in literature and describes some methods of item calibration for creation and maintenance of a test items bank under the Samejima\'s model (Samejima; 1969), estimation of latent trait, item selection with constraints using the Shadow test approach and usuals stopping criteria. Simulations were conducted with a large bank (500 items) and a small bank (21 items) and the quality of the estimatives of latent traits were evaluated (through calculations of mean squared errors and bias) TACs with different item numbers. Samejima\'s model were applied for the responses of students to the English Proficiency Exam (EPE) of ICMC - USP, a test applied twice a year in paper and pencil format, to create an item bank and subsequent construction of a CAT. The model was also applied to the responses of clinical patients from the Hospital das Clnicas - USP, given by Dr. Yuang-Pang Wang, to the Beck Depression Inventory (BDI) for the same purposes. Comparisons using the current methodology to evaluate the English Language Proficiency of EPE (Measure of Probability Allowable, MPA) and the BDI (criterion suggested by Kendall et al., 1987) were performed, and the CATs provided better and richer results. Furthermore a program, Same-CAT, that stores item banks and allows CAT\'s applications with constraints was created

Knowledge Space Theory (KST) links in several ways to Formal Concept Analysis (FCA). Recently, the probabilistic and statistical aspects of KST have been further developed by several authors. We review part of the recent results, and describe some of the open problems. The question of whether the outcomes can be useful in FCA remains to be investigated.