Regularized algorithms for ranking, and manifold learning for related tasks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (leaves 119-127).This thesis describes an investigation of regularized algorithms for ranking problems for user preferences and information retrieval problems. We utilize regularized manifold algorithms to appropriately incorporate data from related tasks. This investigation was inspired by personalization challenges in both user preference and information retrieval ranking problems. We formulate the ranking problem of related tasks as a special case of semi-supervised learning. We examine how to incorporate instances from related tasks, with the appropriate penalty in the loss function to optimize performance on the hold out sets. We present a regularized manifold approach that allows us to learn a distance metric for the different instances directly from the data. This approach allows incorporation of information from related task examples, without prior estimation of cross-task coefficient covariances. We also present applications of ranking problems in two text analysis problems: a) Supervise content-word learning, and b) Company Entity matching for record linkage problems.by Giorgos Zacharia.Ph.D

Archives of Data Science, Series A. Vol. 1,1: Special Issue: Selected Papers of the 3rd German-Polish Symposium on Data Analysis and Applications

The first volume of Archives of Data Science, Series A is a special issue of a selection of contributions which have been originally presented at the {\em 3rd Bilateral German-Polish Symposium on Data Analysis and Its Applications} (GPSDAA 2013). All selected papers fit into the emerging field of data science consisting of the mathematical sciences (computer science, mathematics, operations research, and statistics) and an application domain (e.g. marketing, biology, economics, engineering)

Factors influencing the spatial distribution of natural resource-based industries: the softwood lumber industry in the United States South

Expanding on the Theory of Location, New Economic Geography, and Porter\u27s Theory of Clusters this dissertation attempts to identify key factors influencing the location of firms in a resource-based industry. The softwood lumber industry in the United States is used as a case study to test several hypotheses concerning these theories. Two U.S. regions, the West and the South, were selected for analysis because they account for over 70 percent of U.S lumber manufacturing capacity. A multi-disciplinary research approach involved three-stages. First, self-reported preferences were analyzed using common factor and conjoint analyses for preferences for location attributes. Surveys were sent to all sawmill managers in the U.S. West and South regions. Respondents were identified through the Random Lengths\u27 Big Book (2006), the industry\u27s most comprehensive database. Survey procedures followed Dillman\u27s (2000) Tailored Design Method. Conjoint analysis provided information on the relative importance of selected site attributes using several econometric models to estimate coefficients, significance and marginal effects of site attributes. Second, a model for industry location behavior in the U.S. South was developed using a spatial econometric model. An exploratory analysis identified deviations from complete spatial randomness as first-hand evidence of clustering. The presence of sawmill enterprises was used as the dependent variable, aggregated at the county level. Spatial autoregressive and correlated error econometric models were used to correct for spatial correlation. The final model was used to identify counties where softwood lumber industry development could occur in the future with a high probability of success. Third, two cross-sections of data were analyzed using point density tools to explore spatial concentration in the softwood lumber industry over time. There is evidence of consolidation in the industry as the number of firms has declined while capacity has increased over time. The findings are congruent with spatial predictions drawn by Location Theory, New Economic Geography and to some extent the Theory of Clusters. Research methods used in this study have the ability to capture decision-makers preferences and to operationalize major theories of location, economic geography and cluster development. Results can provide industry and economic development professionals with a new decision-making tool

Price differentiation strategies

Both practitioners and academics agree about the importance of price and its direct influenceon consumers’ purchase decision as well as the company profit. In the reality, we rarely see a single price for a given product. One visit in a store already shows that consumers face many various prices. This strategy of differential prices allows to increase profit but also improves consumers’ situation and increases welfare. A wide range of various price differentiation mechanisms exists on the market which makes price differentiation a very interesting phenomenon. Additionally, market developments constantly allow for new price differentiation applications. In this work, I research a fascinating topic of price differentiation, its various forms and new application possibilities in changing market areas

ICT 기술을 적용한 에티오피아의 미래 수도 서비스에 대한 연구 -AHP 및 이산선택실험 분석-

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 협동과정 기술경영·경제·정책전공, 2018. 8. Jongsu Lee.청정 수도 공급 정책 및 계획에 있어 불소 안전 수돗물 공급자들의 문제점과 불소 안전 수도 서비스에 대한 대중의 선호를 이해하는 것이 중요하다. 본 연구의 목적은 열곡 지대 거주자들의 불소 안전 수도 서비스 속성에 대한 선호 구조, 지불의사액과 하수도 공급자의 제약들을 파악하는 것에 있다. 본 연구는 과량의 불소 농도 지역에서 불소 안전 수도 서비스 공급에 대한 학계와 정책 입안자 모두에게 통찰력을 제공한다. 본 연구는 열곡 지대 거주자들의 선호도를 파악함에 있어 직접 설문 방법과 간접 설문 방법을 모두 사용하였다. 무작위 효용 이론을 바탕으로 에티오피아의 중앙 열곡 지역인 Adama, Lume, Bora, Zuway dugda 및 Adami Tulu & Jido kombolcha woredas에서 표본을 추출하여 혼합 및 잠재 계층 로짓 모델을 사용하여 분석했다. 보상 잉여 힉스주의 이론을 사용한 censored Tobit 모델을 추정하여 평균 지불의사액을 산정하고 연구 지역의 불소 안전 수도 공급 프로젝트에 대한 비용 편익 분석을 수행하였다. 수집된 데이터는 3 가지 다른 방법론을 통해 분석되었다. 첫번째 부분에서는 불소 안전 수돗물 공급 업체들의 제약 조건들을 파악하기 위한 연구로 분석 계층 프로세스(AHP) 방법과 전문가 쌍방향 평가 데이터를 활용하였으며 제약 조건 유형 중에서 재무적 요인, 기술적 요인, 제도적 요인 순으로 중요하게 도출되었다. 또한, 불소 안전 수돗물 공급 업체들은 높은 초기 비용과 무관하게 온라인 기반 불소 함량 모니터링을 선호하는 것을 알 수 있었다. 두번째 부분에서는 미래 수도 서비스에 대한 소비자 선호를 파악하기 위해 혼합로짓모형을 적용하여 선호도의 이질성을 포착하였으며, 잠재계층로짓 모형을 사용하여 가구 단위 이질성을 포착하였다. 속성들로는 불소 함량 (WHO 표준을 기준인 1.5mg / l을 사용), 용수 중단 빈도, 중단 기간, 중단 사전 통지 일 수, 통지 방식과 서비스 개선을 위한 추가 비용을 사용하여 분석하였다. 두 모형의 결과는 각 속성과 영향의 방향이 일치하였는데, 중단 빈도, 중단 기간과 인터넷 기반 통지 시스템은 음의 한계 효용을 보였으며, 불소 함량, 사전 통지 일 수, 모바일 기반 통지 시스템은 양의 한계 효용을 보였다. 모형 별 상대 중요도는 다르게 나타났는데, 추가 서비스 비용을 제외하고 혼합로짓모형에서는 WHO 기준 이상의 불소 함량 수질이 가장 중요한 반면, 잠재 계층 로짓 모형에서는 WHO 수준의 불소 함량 수질이 가장 중요한 것으로 나타났다. 세번째 부분에서는 선호 특성의 경제성을 파악하기 위해 잠재 계층 로짓 모형을 활용하여 평균 지불의사액을 추정하고 토빗 모델을 사용한 조건부 가치 평가 방법을 사용하여 소비자의 불소 안전 수도 공급 서비스에 대한 지불의사액을 조사했다. 인근 에티오피아 정부의 수도 공급 비용을 연구 지역에 불소 안전 수도 공급 비용에 대한 대용 값으로 활용하여 비용 편익 분석을 수행하였다. 분석 결과, 가구들의 불소 안전 수돗물에 대한 지불의사액은 자신 수입의 3%에서 16%에 달하였다. 이에 따른 정책적 함의는 다음과 같다Table of Contents Chapter 1. Introduction 1 1.1. Overview 1 1.2. Research motivation and objective 6 Chapter 2. Research background and problem statement 14 2.1. Water supply and socioeconomic development in Ethiopia 14 2.1.1. Problem statement 14 2.2. Water supply situation in the Rift Valley region 16 2.2.1. Global and regional status of fluoride 17 2.2.2. National status of fluoride 18 2.3. Online technology adoption in the water service sector 22 2.3.1. The need for online technology adoption in the water supply sector in Ethiopia 24 2.4. Ethiopias water supply policy 26 2.4.1. Rural water supply 26 2.4.2. Urban water supply 27 Chapter 3. Literature review 30 3.1. Studies on online technology (IoT) adoption for water quality monitoring 30 3.2. Studies on demand for water service improvements 35 3.3. Review of empirical studies in the Ethiopian context 46 3.4. Summary of literature review 48 3.5. Contributions to academic literature 50 Chapter 4. Models and methodology 53 4.1. Foundations of the discrete choice analysis 53 4.1.1. The random utility model 55 4.1.2. The Mixed Logit Model 58 4.1.3. Bayesian Estimation 62 4.1.4. The latent class logit model 64 4.2. Willingness to pay (WTP) 68 4.2.1. Willingness to pay using contingent valuation (CV) methods 70 4.3. Model estimation 73 4.4. The Analytical Hierarchy process method (AHP) 77 Chapter 5. Experimental design and estimation results 83 5.1. Survey design and data collection 83 5.1.1. Conjoint survey 83 5.1.2. Attributes and their levels 85 5.2. Descriptive statistics 93 5.3. Empirical models and estimation results 105 5.3.1. Providers constraints in supplying fluoride safe water services in the Rift Valley region 106 5.3.1.1. Financial factors criteria 109 5.3.1.2. Environmental factors criteria 111 5.3.1.3. Policy and institutional factors criteria 112 5.3.1.4. Technical factors criteria 113 5.3.1.5. Technology preferences 114 5.3.2. Household preferences on future water services attributes 118 5.3.2.1. Estimation of the mixed logit model 119 5.3.2.2. Estimation of latent class logit model 128 5.3.3. Policy simulation: Quality vs reliability seekers perspectives 135 5.3.3.1. A comparison of the models 138 5.3.4. Households willingness to pay for fluoride safe water services: A comparison of CA and CVM 142 5.3.4.1. Estimation of the model 145 5.3.4.2. Comparison of WTP results by methods 155 5.3.5. Cost benefit analysis 157 Chapter 6. Conclusion and Policy Implications 163 6.1. Conclusion 163 6.2. Key findings and policy implications 165 6.3. Limitation and future research 174 References: 177 Appendix 191 Annex 1-map of Ethiopia with survey sites 191 Annex II- Household preference Survey Questionnaire 192 Annex III- Water providers expert judgement survey questionnaire 200 Docto

A Conjoint Analysis of Wetland-Based Recreation: A Case Study of Louisiana Waterfowl Hunting.

Conjoint analysis is a recent evolution in mathematical psychology that has been employed extensively in the marketing environment. The technique is concerned with measuring the joint effect of two or more independent variables on the ordering of a dependent variable. Conjoint analysis relates an individual\u27s preferences to a set of prespecified attributes. The objective of conjoint analysis is to decomposed a set of responses to factorially designed stimuli in which the utility of each stimuli attribute can be inferred from the respondents\u27 evaluations of the stimuli. In addition, conjoint analysis and its economic foundations are developed in the context of conventional related market and non-market valuation approaches. Given the multiattribute nature of wetland based activities such as waterfowl hunting, conjoint analysis becomes an attractive approach in estimating the benefits and values derived from wetland based activities. An empirical and economic analysis is presented in which waterfowl hunters\u27 willingness-to-pay for various hunting trip attributes is derived from a rank-ordered logit specification of the indirect utility function. The hunting trip vignettes are developed according to seven different attributes with each attribute varying across three levels using a fractional factorial experiment. The data for the analysis were derived from questionnaires mailed to 7,500 randomly selected individuals who purchased 1990 Louisiana duck stamps. The statistical estimation technique employed in this research was rank-ordered logit via weighted least squares. Weighted least squares was chosen due to the presence of heteroskedasticity and uncertainty regarding the properties of the error term which masks the efficiency of the ordinary least squares regression. A Box-Cox transformation was also employed to test for specification of the functional form. The results indicated that the length of the hunting season, the daily duck bag limit, and the rate of congestion were three significant factors influencing waterfowl hunters\u27 trip rating preferences. In addition, conjoint analysis appears to be a viable technique for analysis of resource based multiattribute activities

The short food supply chains’ phenomenon: a multidisciplinary approach to explore consumer behaviour and preferences

L’odierna sfiducia dei consumatori verso i sistemi agroalimentari industriali e la loro crescente riflessività o “quality turn”, hanno portato negli ultimi anni allo sviluppo delle filiere corte (FC), in alternativa ai mercati convenzionali. Le FC hanno la capacità di aumentare la sostenibilità dei sistemi convenzionali in termini sia di equità socio-economica sia di sviluppo ambientale e locale, incontrando le abitudini e le motivazioni di acquisto del consumatore post-moderno, le quali sono per definizione molto eterogenee. Viepiù, la nuova Politica Agricola Comunitaria 2014-2020 incoraggia oggi la promozione delle FC, attraverso specifici supporti finanziari previsti all’interno del secondo pilastro, al fine di favorire uno sviluppo sostenibile. Questa ricerca indaga, attraverso un approccio multidisciplinare, le preferenze e il comportamento del consumatore verso l’acquisto in questi canali di vendita alternativi. Sulla base di alcuni risultati preliminari di natura qualitativa, tale ricerca esplora più in dettaglio determinati fattori che influenzano il comportamento del consumatore (sostenibilità, fiducia, equità). L’obiettivo più ampio è quello di fornire nuova conoscenza sulle FC, focalizzando l’attenzione in particolar modo all’Italia, al fine di spiegarne il crescente appeal sul consumatore e il continuo sviluppo. Questa ricerca passa da un approccio socio-psicologico (Teoria del Comportamento Pianificato) alla teoria economia, applicando la tecnica dell’esperimento di scelta basato su un mercato ipotetico e relativo ai mercati dei contadini. È stato svolto anche un confronto tra Italia e Brasile e Italia e Germania. I risultati mostrano l’importante ruolo della sostenibilità e della fiducia nell’influenzare gli acquisti alimentari presso le FC, cosi come una rinnovata enfasi su alcuni fattori legati al marketing tradizionale (contatto diretto con il produttore) e la possibilità per i consumatori di contribuire al reddito degli agricoltori.In recent years, the erosion of consumers’ confidence in industrialized agro-food systems and their increasing reflexivity known as “quality turn” have led to the promotion of Short Food Supply Chains (SFSCs) as opposite to conventional markets. SFSCs have the potential to enhance the sustainability of conventional food systems in terms of socio-economic equity and environmental and local development, addressing post-modern consumer’s habits and purchasing motivations that are extremely heterogeneous in natures. In addition, the renewed EU Common Agricultural Policy 2014-2020 encourages the promotion of SFSCs for the first time through a specific financial support within its II pillar, providing a publicly funded stimulus for sustainable development. This research aims at contributing to the growing literature on SFSCs, investigating consumer preferences and behavior towards purchasing food in such alternative schemes through a multidisciplinary approach. Based on some preliminary qualitative findings, this research explores the importance of some major drivers in influencing consumers’ preferences and purchasing behavior (i.e., sustainability, trust, fairness) more in depth. The broader objective is to provide new knowledge around SFSCs’ growing appeal among consumers, focusing especially on Italy, to explain their recent increasing in number. From a socio-psychological approach, i.e. the Theory of Planned Behavior, the research turns to economic theory with a choice experiment (CE) based on an hypothetical market situation and focusing on farmers’ markets. Italian consumers have been also compared with Brazilian and German consumers. Generally speaking, findings show the important role of sustainability and trust in influencing food purchases at SFSCs, as well as consumers’ renewed emphasis on both some traditional marketing patterns (i.e., face-to-face interactions with the producer) and the possibility to contribute to farmers’ income

Strategic Supplier Dynamics and Decision-making in Supply Chain Management: Exploring Market Segmentation, Copycatting, and Encroachment

In this dissertation, we explore the intricate dynamics of supplier relationships and strategic decision-making within the realm of Operations Management, focusing on the critical aspects of supply chain management. The research consists of three papers, each offering unique insights into supplier dynamics and their implications for manufacturers and businesses. The first paper presents a robust framework for joint learning of consumer preferences and market segmentation. Leveraging ideas from machine learning and mathematical programming, this framework efficiently segments the customer base and accurately learns preferences without compromising consumer privacy. By optimizing assortment decisions, this approach maximizes profits and offers superior prediction accuracy, enhancing marketing strategies in dynamic market scenarios. The second paper delves into the pressing issue of supplier copycatting, where suppliers imitate original products, posing challenges to manufacturers and suppliers worldwide. Employing a game-theoretic approach, the research analyzes strategic responses of manufacturers and suppliers to cope with this emerging trend. The findings reveal the impacts of quality improvements and potential shifts in outsourcing decisions, providing valuable insights for managing supplier relationships and mitigating copycatting risks. The third paper investigates the ramifications of supplier encroachment, as upstream suppliers venture into direct sales and compete with manufacturers. Through a two-period game-theoretic model, the research examines optimal outsourcing strategies for manufacturers while considering the potential repercussions faced by encroaching suppliers. This comprehensive analysis sheds light on the dynamics of supplier- manufacturer collaborations, highlighting the importance of trust and commitment in maintaining successful partnerships. Overall, this dissertation contributes valuable and comprehensive insights to the field of Operations Management. Employing a multi-method approach, we delve into supplier dynamics and decision-making, offering robust strategies and solutions to enhance supply chain efficiency and competitiveness. By addressing challenges such as consumer preference learning, supplier copycatting, and supplier encroachment, this research contributes to the growing body of knowledge in Operations Management and provides actionable guidance for businesses to thrive in the dynamic supply chain environments