This thesis examines how to design a mathematical inventory model for a ”Fast Moving Consumer Goods”-company (FMCG-company), which determines the optimal reorder point and order quantity such that the average inventory cost is minimized. The thesis was made in collaboration with a ”Software as a Service”- company which provided the data containing information about the products and inventory management of one of their customers, a FMCG-company. The thesis first considers a basic EOQ-model, with constant demand rate, that suggests a reorder time and order quantity for the products. Since constant demand rate might be an unrealistic assumption for a FMCG-company, the thesis also considers a (R,Q)-model, where the demand was based on a forecast made by using the Holt-Winters model on previous sales history. The solutions were found by investigating the singular points and comparing them to the critical point. The thesis shows that the EOQ-model gives useful results for the most indemand products, while the reorder times for the less popular products are instead impractically high. The (R,Q)-model showed more stable solutions for all products and therefore proves to be a better inventory model for FMCG-companies, as expected. Simulations of the (R,Q)-model showed various inventory cases, where some showed a mismatch between the inventory level and the demand. The cases shows how demand planning can be applied for different products for when to consider changing inventory strategy or discontinuing products and how the orders can be made optimally. / Detta examensarbete undersöker hur en matematisk lagermodell kan utformas för ett ”Fast Moving Consumer Goods”-företag (FMCG-företag), som bestämmer den optimala beställningspunkten och orderkvantiteten så att den genomsnittliga lagerkostnaden minimeras. Examensarbetet gjordes i samarbete med ett ”Software as a Service”-företag som tillhandahöll data innehållandes information om produkter och lagerhantering hos en av deras kunder, ett FMCG-företag. Avhandlingen behandlar först en grundläggande EOQ-modell, med konstant efterfrågan, som föreslår en återbeställningstid och orderkvantitet för produkterna. Eftersom att en konstant efterfågan kan anses vara ett orealistiskt antagande för ett FMCG-företag, tar avhandlingen även upp en (R,Q)-modell, där efterfrågan baserades på en prognos gjord med hjälp av Holt-Winters-modellen på tidigare försäljningshistorik. Lösningarna hittades genom att undersöka de singulära punkterna och jämföra dem med den kritiska punkten. Avhandlingen visar att EOQ-modellen ger användbara resultat för de mest efterfrågade produkterna medan beställningstiderna för de mindre populära produkter är ofta opraktiskt höga. (R,Q)-modellen visade mer stabila lösningar för alla produkter och visar sig därmed vara en bättre lagermodell för FMCGföretag, som förväntat. Simuleringar av (R,Q)-modellen visade olika fall, där vissa visade en obalans mellan lagernivån och efterfrågan. De olika fallen visar hur efterfrågeplanering kan tillämpas för olika produkter för när man ska överväga att ändra lagerstrategi eller avveckla produkter och hur beställningarna kan göras optimalt

This diploma thesis deals with the causes of division of customer preferences towards individual retail units in the town of Blatná in order to recommend proposals for improvement for the consumer cooperative COOP. The theoretical overview provides basic information about food retailers in the Czech Republic, presents the formats of stores, attitudes of shoppers to food stores, individual elements of the retail mix or other factors influencing customer attitudes towards the store which can be influenced by retailers. The practical part relates to the food chains in Blatná and it is focused on identifying the respondents' favourite and main shopping place, the reasons for dividing customer preferences towards retail units, researching attitudes toward retail units and evaluating the retail mix of these stores. The practical part consists of two parts, a questionnaire survey focused on customers of food stores in Blatná, and research from these stores. Subsequently, it is possible to define respondents' attitudes towards food retailers in Blatná and their buying behavior. The survey in retail formats is used to identify and evaluate the core elements of the retail mix of individual stores. Thanks to these procedures it is possible to define improvement suggestions for COOP Tip in Blatná.

Abstract Authors: Mikael Forsberg and Sara-Maria Löfvenberg Tutor: Susanne Åberg Title: Socially Desirable Fast Moving Consumer Goods – A Literature Review on How To Decrease the Gap Between Intention & Purchase Behavior Through Marketing Keywords Branding, Consumer Behavior, Consumer Value Creation, Decision-making, Differentiation, Eco, Ecological, Environmentally Conscious Behavior, Fast Moving Consumer Goods (FMCG), Green Consumer, Green Marketing, In-store marketing, Marketing, Organic, Purchase decision, Socially Desirable, Value Creation. Background and Problem Consumers today are more environmentally conscious than ever. However, it has been found that there is a gap between the consumer’s intention and actual purchase when it comes to products that there is a social pressure to buy for environmental reasons. The potential for the socially desirable segment is estimated to have potential, but growth seems to be slow. It has been stated that until now, there is not enough research done that take a holistic perspective including several fields of marketing. There is a need to review and combine existing literature in various fields of marketing to investigate how the gap can be decreased and sales increased. Purpose The purpose of this thesis is to review and combine existing literature in the fields of consumer value creation, decision-making and in-store marketing. By doing so the authors of this thesis aim to present a theoretical model on how producers of socially desirable FMCG can decrease the gap between the consumers’ intention and actual purchase through marketing. Decreasing the gap refers to more fully exploit the potential size of the segment and generate more sales.   Method A completely theoretical method was chosen for this thesis. To the authors’ knowledge there has not been done enough specific research to match the purpose of this thesis. A literature review has therefore been conducted within three separate fields of marketing to get a broader understanding of how the gap between intention and actual purchase can be decreased. Based on the extensive literature review, the authors developed ten propositions that formed a model that can be used as the backbone for future theoretical and empirical research.   Final Discussion Some highlights of the theoretical discussions earlier in this thesis are presented in the final discussion. The authors suggest that purchase decisions of socially desirable FMCG initially are high-involvement decisions that often are formed outside the in-store-setting. This suggests that more long-term marketing efforts such as brand building in some cases can be more important than in-store marketing when it comes to FMCG that are socially desirable. Symbolic values should be highlighted in branding of socially desirable FMCG because the instrumental differences between FMCG and socially desirable FMCG is limited. It is therefore likely that it is more efficient to focus on consumers’ self-identity to convince them to purchase socially desirable FMCG. It is also important that producers of socially desirable FMCG provide consumers with clear product information in-store and that the products are easy to find. Based on the extensive literature review, the authors have developed eight propositions that form the model presented in this chapter.

Background and Problem: CSI is a topic with a limited amount of research despite it being a very relevant issue and that its counter pole CSR is one of today’s most popular subjects to study. In both areas there is a gap in the literature regarding the apparel industry where there CSI can be evident in many different aspects, especially in the production process. In the FMCG market, the demand for apparel that has been produced ethically has increased over the years. Still, the importance that the consumers place on ethical attributes in their purchase decisions is rather unknown. Purpose: The study's purpose is to investigate the young consumers’ emotions towards FMCG apparel corporations in order to see if CSI actions give them a negative attitude. It will further be explored to see if the attitude towards the corporations reflects in their intentional purchase behavior and their actual behavior. This will provide insight to the young consumers’ knowledge and interest for CSI, aiding corporations in their quest for excellence when it comes to consumer relationships. Method: This research is done through a deductive, qualitative research. A literature review is done to create a great understanding to the concepts of CSI, consumer attitudes and planned behavior. Four focus groups are conducted as a base for the empirical findings. Further, these two chapters are compared in an analysis to get an understanding about the young consumers’ attitudes towards corporations acting unethically and the affects it may have on their planned behavior. Conclusion: Based on the analysis, the study found clear evidence that the participants have a negative attitude towards corporations’ CSI activities. However, these attitudes did not, as theory suggests, have any effect on the participants’ intended and actual purchasing behavior. Instead it is shown that young consumers base their decisions on contextual factors, where the most significant one is price.

Na área de processamento de sinais biomédicos a extração de informação, baseada em um conjunto de medidas adquiridas no tempo, é considerada de suma importância. A qualidade desta informação extraída permite avaliar o funcionamento dos diversos órgãos. Objetivos: (1) propor o método de análise de componentes dependentes para auxiliar a extração de componentes de interesse, a partir de medidas multivariadas; (2) caraterizar as componentes extraídas através de representações em termos de tempo e freqüência, e espectro de potência; e, (3) aplicar o método e avaliar as componentes de interesse extraídas no contexto real MCGf, MGG e fMRI. A proposta para a extração fundamenta-se no método chamado de Análise de Componentes Dependentes ACD. As medidas a serem processadas são multivariadas a partir de sensores distribuídos, espacialmente, no corpo humano dando origem a um conjunto de dados correlacionados no tempo e/ou no espaço. Observa-se que os sinais de interesse raramente são registrados de forma isolada, e sim misturados com outros sinais superpostos, ruído e artefatos fisiológicos ou ambientais, onde a relação sinal-ruído é geralmente baixa. Nesse contexto, a estratégia a ser utilizada baseia-se na ACD, que permitirá extrair um pequeno número de fontes, de potencial interesse, com informações úteis. A estratégia ACD para extração de informação é aplicada em três importantes problemas, na área de processamento de sinais biomédicos: (1) detecção do sinal do feto em magnetocardiografia fetal (MCGf); (2) detecção da atividade de resposta elétrica do estômago em magnetogastrografia (MGG); e, (3) detecção de regiões ativas do cérebro em experimentos de imagens por ressonância magnética funcional (Functional Magnetic Resonance Imaging, fMRI). Os resultados, nos três casos estudados, mostraram que o método utilizado, como estratégia, é efetivo e computacionalmente eficiente para extração de sinais de interesse. Concluímos, baseados nas aplicações, que o método proposto é eficaz, mostrando seu potencial para futuras pesquisas clínicas._________________________________________________________________________________________ ABSTRACT: An important goal in biomedical signal processing is the extraction of information based on a set of physiological measurements made along time. Generally, biomedical signals are electromagnetic measurements. Those measurements (usually made with multichannel equipment) are registered using spatially distributed sensors around some areas of the human body, originating a set of time and/or space correlated data. The signals of interest are rarely registered alone, being usually observed as a mixture of other spurious, noisy signals (sometimes superimposed) and environmental or physiological artifacts. More over, the signal-to-noise ratio is generally low. In many applications, a big number of sensors are available, but just a few sources are of interest and the remainder can be considered noise. For such kind of applications, it is necessary to develop trustful, robust and effective learning algorithms that allow the extraction of only a few sources potentially of interest and that hold useful information. The strategy used here for extraction of sources is applied in three important problems in biomedical signal processing: (1) detection of the fetal magnetocardiogram signal (fMCG); (2) detection of the electrical activity of the stomach in magnetogastrograms (MGG); and (3) detection of active regions of the brain in experiments in functional Magnetic Resonance Imaging (fMRI). The results, within the three cases of study, showed that the DCA method used as strategy is effective and computationally efficient on extraction of desired signals.