Leveraging Market Research Techniques in IS – A Review of Conjoint Analysis in IS Research

With the increasing importance of mass-market information systems (IS), understanding individual user preferences for IS design and adoption is essential. However, this has been a challenging task due to the complexity of balancing functional, non-functional, and economic requirements. Conjoint analysis (CA), a marketing research technique, estimates user preferences by measuring tradeoffs between products attributes. Although the number of studies applying CA in IS has increased in the past years, we still lack fundamental discussion on its use in our discipline. We review the existing CA studies in IS with regard to the application areas and methodological choices along the CA procedure. Based on this review, we develop a reference framework for application areas in IS that serves as foundation for future studies. We argue that CA can be leveraged in requirements management, business model design, and systems evaluation. As future research opportunities, we see domain-specific adaptations e.g., user preference models

Leveraging Market Research Techniques in IS: A Review and Framework of Conjoint Analysis Studies in the IS Discipline

With cloud and mobile computing, information systems (IS) have evolved towards mass-market services. While IS success requires user involvement, the IS discipline lacks methods that allow organizations to integrate the “voice of the customer” into mass-market services with individual and dispersed users. Conjoint analysis (CA), from marketing research, provides insights into user preferences and measures user trade-offs for multiple product features simultaneously. While CA has gained popularity in the IS domain, existing studies have mostly been one-time efforts, which has resulted in little knowledge accumulation about CA’s applications in IS. We argue that CA could have a significant impact on IS research (and practice) if this method was further developed and adopted for IS application areas. From reviewing 70 CA studies published between 1999 and 2019 in the IS discipline, we found that CA supports in initially conceptualizing, iteratively designing, and evaluating IS and their business models. We critically assess the methodological choices along the CA procedure to provide recommendations and guidance on “how” to leverage CA techniques in future IS research. We then synthesize our findings into a framework for conjoint analysis studies in IS that outlines “where” researchers and practitioners can apply CA along the IS lifecycle

Bayesian learning approach on benefit scale parameter

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 협동과정 기술경영·경제·정책전공, 2021. 2. 이종수.본 연구는 혜택기반모형에 혜택 척도 모수를 도입한 혜택척도모형을 제안한다. 혜택척도모형은 정보가 희소한 이산선택실험에서 데이터를 보다 효과적으로 사용할 수 있다는 장점이 있는데, 본 연구에서는 베이지안 학습 방법에 기반하여 의사결정 중요도 정보를 추출하여 모형 추정에 활용하고 구현하는 방법을 보였다. 제안한 혜택척도모형은 표준 다항로짓과 혜택기반모형보다 우수한 모형 적합도를 보였고, 우수한 예측력을 제공하였으며, 우수한 혜택 할당 확률의 수렴을 보였으며, 다른 해석을 제공하였다. 혜택척도모형을 확장한 색인혜택척도모형은 모형 적합도 수준에서 표준 다항로짓에서 개선이 없는 수준이었는데, 이는 속성을 혜택으로 할당되는 방식을 연구자가 가정하는 것에는 신중한 접근이 필요하며, 개인이 속성을 혜택으로 할당하는 방식이 실제로 이질적이라는 증거로 판단된다. 또한, 혜택척도모형에서 척도 모수에 인구통계변수를 포함하여 혜택 차원의 이질성을 포착할 수 있는 가능성을 확인하였다. 본 연구에서는 또한, 한계효용체감의 범위가 혜택 단위 뿐 아니라 전체 효용 단위로도 발생할 수 있음을 보였다.This study proposes a benefit-scale model that introduces the scale parameter to the benefit-based model. The benefit-scale model has the advantage of being able to use data more effectively in discrete choice experiments when information is sparse. In this study, we show a method of extracting and implementing decision importance information based on the Bayesian learning method. The proposed benefit scale model shows better model fit, predictive power, and convergence in assignment probabilities than the standard multinomial logit and benefit-based model and provides different interpretations. The indexed benefit-scale model, which is an applied model of the benefit-scale approach, showed no improvement in model fit compared to the standard model. This indicates that a careful approach is required when the researcher assumes that attributes are assigned to benefits, and that assignment probability is indeed heterogeneous. In addition, the possibility of capturing the heterogeneity in scale was tested and confirmed by including demographic variables in the scale parameter. It was also shown in this study that satiation can take place in both benefit level and utility-as-a-whole level. For empirical validation of the model, Over-the-top(OTT) service data and alternative fuel vehicle data were used. This study provides service planning implications for IPTV or cable TV service operators and product planning implications for electric vehicle manufacturers.Abstract v Contents vii List of Tables xi List of Figures xiv Chapter 1. Introduction 1 1.1 Research background 1 1.2 Research objective 3 1.3 Research outline 3 Chapter 2. Literature Review 4 2.1 Choice Theories and Models 4 2.1.1 Valuation Rules 8 2.1.2 Integration Rules 10 2.1.3 Choice Rules 16 2.2 Satiation 21 2.3 Factor Approach 23 2.4 Research Motivation 26 Chapter 3. Model 28 3.1 Benefit-based Model 28 3.1.1 Overview of the Model 28 3.1.2 Model Specification 29 3.1.3 Schematic illustration of the Model 32 3.1.4 Estimation procedure 36 3.2 Satiation in utility level model 37 3.2.1 Model specification 37 3.2.2 Estimation procedure 38 3.3 Benefit-scale Model 39 3.3.1 Overview of the Model 39 3.3.2 Model specification 41 3.3.3 Estimation Procedure 42 3.4 Indexed Benefit-scale model 44 3.4.1 Overview of the Model 44 3.4.2 Estimation Procedure 44 3.5 Demographic Indexed Benefit-scale Model 47 3.5.1 Model Specification 47 3.5.2 Estimation Procedure 47 Chapter 4. Empirical Studies 50 4.1 The Study on OTT services 50 4.1.1 Introduction 50 4.1.2 Data 51 4.1.3 MNL & Benefit-based(BB) Model: Estimation Results 55 4.1.4 Satiation in Utility(SU) Model: Estimation Results 62 4.1.5 Benefit-scale(BS) Model: Estimation Results 65 4.1.6 Indexed Benefit-scale(IBS) Model: Estimation Results 74 4.1.7 Demographic Indexed Benefit-scale(DIBS) Model: Results 77 4.1.8 Conclusion and Implications 80 4.2 The Study on Alternative Fuel Vehicle 85 4.2.1 Introduction 85 4.2.2 Data 86 4.2.3 MNL & Benefit-based Model: Estimation Results 92 4.2.4 Satiation in Utility Model: Estimation Results 96 4.2.5 Benefit-scale Model: Estimation Results 99 4.2.6 Indexed Benefit-scale Model: Estimation Results 106 4.2.7 Demographic Indexed Benefit-scale Model: Results 109 4.2.8 Conclusion and Implications 112 Chapter 5. Summary and Conclusion 116 5.1 Concluding Remarks and Contributions 116 5.2 Limitations and Future Studies 117 Bibliography 118 Appendix 1: Improvement in convergence of assignment probability 133 Appendix 2: Discussion on existence of local solutions 134 Appendix 3: Discussion on sensitivity of scale parameters prior 135 Appendix 4: Discrete Choice Experiment questionnaire: OTT service 137 Appendix 5: Discrete Choice Experiment questionnaire: Alternative Fuel Vehicle 141 Abstract (Korean) 145Docto

소비자의 현재보유제품에 대한 이질성을 고려한 신제품 수용 행태 분석

학위논문 (박사)-- 서울대학교 대학원 : 협동과정 기술경영·경제·정책전공, 2012. 8. 이종수.본 연구의 목적은 소비자가 현재 보유한 제품 (status quo)이 새로운 제품 선택에 미치는 영향을 고려하여 주기적으로 구매되는 준내구재 제품에 대한 소비자의 선호를 분석하는 것이다. 소비자들은 일반적으로 새로운 제품을 구매할 때 그들이 현재 보유한 제품의 상태와 이로부터 얻은 경험 등에 크게 영향을 받기 때문에, 새로운 제품들의 비교만으로는 소비자 선호를 정확히 예측하는 것이 힘들기 때문이다. 특히, 본 연구에서는 보유한 제품의 진부화 정도나 새로 구매하고자 하는 제품과의 유사성 등을 현재 보유한 제품이 미치는 주된 영향으로 고려하고 분석하였다. 이와 같은 현재 보유한 제품의 상태를 고려한 선택 모형은 동일한 카테고리 내의 제품 선택뿐만 아니라, 상호 영향을 줄 수 있는 다른 카테고리 제품의 경우에 대해서도 확장이 가능하다. 실증 분석은 세 개의 스마트 기기인 스마트폰, 스마트패드, 스마트TV에 대해서 수행되었다. 우선 계층적 베이지안 (hierarchical Bayesian)을 이용한 다항로짓모형 (multinomial logit model)을 이용하여, 현재 보유한 제품이 새로운 선택에 어떤 영향을 미치는지를 분석하였다. 분석 결과, 새로운 제품을 선택함에 있어서 해당 제품 속성 수준 자체만큼이나 기존에 보유했던 제품의 특성이 선택에 미치는 영향이 큰 것으로 나타났고, 새로운 대안들의 선택확률을 계산함에 있어 현재 보유한 대안을 고려하는 경우와 그렇지 않은 경우에 큰 차이가 있음을 알 수 있었다. 시간에 따른 대안의 선택확률 변화는 진부화 효과가 미치는 영향이 추정되면 시뮬레이션 해 볼 수 있다. 이처럼 시계열 데이터 없이도 시간에 따른 선택확률의 변화를 분석할 수 있는 것은 본 연구의 장점 중 하나이다. 이 외에도, 보다 정밀한 수요 예측을 위한 함의들이 도출되었다. 다양한 카테고리 제품간의 상호 연계성의 관점에서, 현재 보유한 제품이 다른 카테고리의 제품 선택에 미치는 효과를 이변량 다항프로빗 모형 (bivariate multinomial probit model)을 이용하여 분석할 수 있다. 본 연구에서는 이변량 다항프로빗 모형을 이용하여 응답자가 어떤 스마트폰을 선택했는지에 따라서 새로운 스마트패드나 스마트TV의 선택이 어떻게 달라지게 되는지를 분석하였다. 그 차이는 모수 추정 결과를 분포 밀도 (kernel density) 그래프를 통해서 쉽게 식별할 수 있게 하였고, 분산-공분산 행렬을 통해 다른 카테고리의 제품간의 상관관계까지 고려할 수 있도록 하였다. 정리하면, 본 연구는 왜 우리가 선택 모형에서 소비자가 현재 보유한 제품이 새로운 제품의 선택에 미치는 영향을 고려해야 하는 이유를 제시하고, 이를 실증적으로 어떻게 고려하여 분석할 것인지에 대한 분석틀을 제공하는 것에 의의가 있고, 이를 통해 더 정확한 수요 예측 모형을 개발하는데 기여할 것으로 보인다.The purpose of this study is to analyze consumer preference for semi-durable products that are purchased regularly, in consideration of the effect of the consumers currently owned products on the selection of new products. When consumers purchase new products, they are likely to be affected greatly by the condition of their currently owned products and their experiences with those productstherefore, it is difficult to forecast accurately the preference of consumers merely from a comparison of new products. In particular, this study analyzes factors involving the level of obsolescence of consumer-owned products and any similarities they share with the products to be purchased. Such a choice model that considers the condition of currently owned products can be used to select products in the same categoryit can also be extended to products in other categories that may be mutually influential. Empirical analysis is conducted with three smart devices: smart phones, smart pads, and smart TVs. By using a hierarchical Bayesian multinomial logit, the status-quo effect on new choices is analyzed. It is found that the relative importance of the status-quo effect is considerable, and that choice probabilities that consider status-quo alternatives are significantly different from those that do not. The change in choice probabilities over time can be simulated if the magnitude of the obsolescence effect can be estimated. Analyzing the change in choice probabilities over time, even in the absence of time-series data, is one of the remarkable advantages of this studys methodology. From the perspective of interaction between multi-product categories, the choice model that incorporates the status quo can be extended by using a bivariate multinomial probit model. Through the use of this model, the current study analyzes how consumer preference for a smart pad or TV differs from each other, as a function of having selected a smart phone. Kernel-density plots highlight this difference, and the variance–covariance matrix shows the correlation among alternatives. Obviously, the status-quo effect of a smart phone on choosing a new smart pad or TV can be analyzed. In summary, this study explains why a choice model should consider the status-quo effect, and it offers an empirical analysis method that incorporates this effect.Abstract v Contents vii List of Tables ix List of Figures xi Chapter 1. Introduction 1 1.1 Research Background 1 1.2 Research Objectives 3 1.3 Research Framework 10 1.4 Research Outline 15 Chapter 2. Literature Review and Research Purpose 16 2.1 Discrete Choice Models that Consider Consumer Heterogeneity 16 2.1.1 Multinomial Logit Choice Model 17 2.1.2 Mixed Logit and Generalized Multinomial Logit Models 20 2.1.3 Discrete Choice Models that Incorporate the Status-Quo Alternative 23 2.2 New-Product Adoption Process at the Individual Level 26 2.3 Research Purpose 30 Chapter 3. Model Specification 33 3.1 Modeling for Single-Product Category Case 35 3.1.1 Modeling Utility Function of the Status-Quo Alternative 35 3.1.2 Modeling Utility Function of the New Alternatives 37 3.1.3 Discrete Choice Models that Incorporate a Status-Quo Alternative 40 3.1.4 Hierarchical Bayesian Multinomial Logit Choice Model that Incorporates a Status-Quo Alternative 43 3.2 Modeling for the Multi-Product Category Case 47 Chapter 4. Empirical Analysis 53 4.1 Survey Design and Data Description 53 4.1.1 Single-Product Category Case 55 4.1.2 Multi-Product Category Case 65 4.2 Estimation Results 66 4.2.1 Single-Product Category Case 66 4.2.2 Multi-Product Category Case 89 Chapter 5. Conclusion 106 Bibliography 109 Appendix A: Descriptions of Attributes and Attribute Levels from the Smart Phone Conjoint Survey 119 Appendix B: Descriptions of Attributes and Attribute Levels from the Smart Pad Conjoint Survey 121 Appendix C: Descriptions of Attributes and Attribute Levels from the Smart TV Conjoint Survey 123 Abstract (Korean) 125Docto

UNDERSTANDING USER PERCEPTIONS AND PREFERENCES FOR MASS-MARKET INFORMATION SYSTEMS – LEVERAGING MARKET RESEARCH TECHNIQUES AND EXAMPLES IN PRIVACY-AWARE DESIGN

With cloud and mobile computing, a new category of software products emerges as mass-market information systems (IS) that addresses distributed and heterogeneous end-users. Understanding user requirements and the factors that drive user adoption are crucial for successful design of such systems. IS research has suggested several theories and models to explain user adoption and intentions to use, among them the IS Success Model and the Technology Acceptance Model (TAM). Although these approaches contribute to theoretical understanding of the adoption and use of IS in mass-markets, they are criticized for not being able to drive actionable insights on IS design as they consider the IT artifact as a black-box (i.e., they do not sufficiently address the system internal characteristics). We argue that IS needs to embrace market research techniques to understand and empirically assess user preferences and perceptions in order to integrate the "voice of the customer" in a mass-market scenario. More specifically, conjoint analysis (CA), from market research, can add user preference measurements for designing high-utility IS. CA has gained popularity in IS research, however little guidance is provided for its application in the domain. We aim at supporting the design of mass-market IS by establishing a reliable understanding of consumer’s preferences for multiple factors combing functional, non-functional and economic aspects. The results include a “Framework for Conjoint Analysis Studies in IS” and methodological guidance for applying CA. We apply our findings to the privacy-aware design of mass-market IS and evaluate their implications on user adoption. We contribute to both academia and practice. For academia, we contribute to a more nuanced conceptualization of the IT artifact (i.e., system) through a feature-oriented lens and a preference-based approach. We provide methodological guidelines that support researchers in studying user perceptions and preferences for design variations and extending that to adoption. Moreover, the empirical studies for privacy- aware design contribute to a better understanding of the domain specific applications of CA for IS design and evaluation with a nuanced assessment of user preferences for privacy-preserving features. For practice, we propose guidelines for integrating the voice of the customer for successful IS design. -- Les technologies cloud et mobiles ont fait émerger une nouvelle catégorie de produits informatiques qui s’adressent à des utilisateurs hétérogènes par le biais de systèmes d'information (SI) distribués. Les termes “SI de masse” sont employés pour désigner ces nouveaux systèmes. Une conception réussie de ceux-ci passe par une phase essentielle de compréhension des besoins et des facteurs d'adoption des utilisateurs. Pour ce faire, la recherche en SI suggère plusieurs théories et modèles tels que le “IS Success Model” et le “Technology Acceptance Model”. Bien que ces approches contribuent à la compréhension théorique de l'adoption et de l'utilisation des SI de masse, elles sont critiquées pour ne pas être en mesure de fournir des informations exploitables sur la conception de SI car elles considèrent l'artefact informatique comme une boîte noire. En d’autres termes, ces approches ne traitent pas suffisamment des caractéristiques internes du système. Nous soutenons que la recherche en SI doit adopter des techniques d'étude de marché afin de mieux intégrer les exigences du client (“Voice of Customer”) dans un scénario de marché de masse. Plus précisément, l'analyse conjointe (AC), issue de la recherche sur les consommateurs, peut contribuer au développement de système SI à forte valeur d'usage. Si l’AC a gagné en popularité au sein de la recherche en SI, des recommandations quant à son utilisation dans ce domaine restent rares. Nous entendons soutenir la conception de SI de masse en facilitant une identification fiable des préférences des consommateurs sur de multiples facteurs combinant des aspects fonctionnels, non-fonctionnels et économiques. Les résultats comprennent un “Cadre de référence pour les études d'analyse conjointe en SI” et des recommandations méthodologiques pour l'application de l’AC. Nous avons utilisé ces contributions pour concevoir un SI de masse particulièrement sensible au respect de la vie privée des utilisateurs et nous avons évalué l’impact de nos recherches sur l'adoption de ce système par ses utilisateurs. Ainsi, notre travail contribue tant à la théorie qu’à la pratique des SI. Pour le monde universitaire, nous contribuons en proposant une conceptualisation plus nuancée de l'artefact informatique (c'est-à-dire du système) à travers le prisme des fonctionnalités et par une approche basée sur les préférences utilisateurs. Par ailleurs, les chercheurs peuvent également s'appuyer sur nos directives méthodologiques pour étudier les perceptions et les préférences des utilisateurs pour différentes variations de conception et étendre cela à l'adoption. De plus, nos études empiriques sur la conception d’un SI de masse sensible au respect de la vie privée des utilisateurs contribuent à une meilleure compréhension de l’application des techniques CA dans ce domaine spécifique. Nos études incluent notamment une évaluation nuancée des préférences des utilisateurs sur des fonctionnalités de protection de la vie privée. Pour les praticiens, nous proposons des lignes directrices qui permettent d’intégrer les exigences des clients afin de concevoir un SI réussi

소비자의 이질성을 반영한 사회기반 시설의 선호 분석: 한국의 송전선로 건설을 중심으로

학위논문 (석사)-- 서울대학교 대학원 공과대학 협동과정 기술경영·경제·정책전공, 2017. 8. 이종수.There are two primary methods of transmitting electricity: building transmission towers on mountainsides and/or in big fields, or installing high voltage transmission cables and distribution lines underground. Evidently, the growing demand for electricity and the difficulty of developing new electricity sources have augmented the need for transmission capabilities, which is best achieved by transmission at very high voltages. The benefit of grounding wires is that transmission towers – which are huge and hateful at sight – become unnecessary, and the surrounding landscape and the city scenery becomes more likable. However, the cost is much higher than for tower installation due to the necessity of having to construct and manage concrete tunnels underground for the wires to run through. Consequently, underground work has primarily been concentrated in large cities with high population density, leaving rural cities, especially those with budget constraints, relatively neglected. This disparity has yielded arguments that when pursuing governmental projects that can lead to controversies, they must be promoted and implemented in ways that can minimize the imbalance between conflicting stakes and regional conditions. In this paper, citizens preference for power transmission cable installations in South Korea are analyzed, with a focus on individuals innate and residential heterogeneity. In doing so, discrete choice models are utilizedspecifically, the mixed logit model and the latent class model. Attributes such as the number of transmission towers, the electromagnetic field exposure, the number of blackouts, the duration of each blackout, and the additional electricity costs are considered in the choice experiment to identify residents varying preference structures. The factors that represent individuals innate heterogeneity, such as their perceived needs for the project, their attitude with regard to risk, and their city of residence, are also considered to enable further segmentation of consumers. The results of this paper are expected to contribute in identifying the heterogeneous preferences of subjects for governmental projects, which may eventually help regional governments gain a greater understanding of target consumers specific needs.Chapter 1. Introduction Chapter 2. Literature Review 2.1 Electric Power Transmission 2.1.1 Current State 2.1.2 Milyang Conflict 2.2 Existing Studies on Power Transmission Cable Installation Chapter 3. Research Model and Methodology 3.1 Research Framework 3.1.1 Mixed Logit Model 3.1.2 Latent Class Model 3.2 Composition of Data 3.3 Empirical Models 3.3.1 Mixed Logit Model 3.3.2 Latent Class Model Chapter 4. Empirical Studies 4.1 Descriptive Statistics 4.2 Mixed Logit Model Estimation Results 4.2.1 Analysis of Preference Structure 4.2.2 Sensitivity Analysis 4.3 Latent Class Model Estimation Results 4.3.1 Summary of Results 4.3.2 Sensitivity Analysis Chapter 5. Discussion and Conclusion Bibliography Appendix 1: Survey Questionnaire Abstract (Korean)Maste

Models for Individual Responses: Explaining and predicting individual behavior

In this thesis, I develop approaches to explain individual outcomes. These approaches focus on accurately estimating and predicting individual responses: how do individuals react (e.g. with their purchase behavior) to changes in explanatory variables (e.g. price)? The approaches contribute to the literature by allowing for more realistic individual behavior, especially when the dataset contains little information per individual

Quantifying Public Acceptance of Innovation Policy: A Demand-Oriented Analysis for Renewable Energy Policy

학위논문 (박사)-- 서울대학교 대학원 : 협동과정 기술경영·경제·정책전공, 2014. 8. 이종수.Innovation policies are considered as key to encouraging innovative activity, which may serve as essential and valid means to survive and adapt to our current fast-changing society. To date, innovation policies have mostly focused on supply-side measures by creating and diffusing new technologies. However, since demand also plays a crucial role by being one of the primary sources of innovation, the importance of demand-oriented innovation policies has received much attention recently. Public acceptance is a very important consideration from the perspective of demand-oriented innovation policies, because innovation policies may face social resistance despite their obvious advantages and usefulness. The purpose of this dissertation is twofold. The first is to quantitatively analyze public preferences for an innovation policy and to forecast the level of public acceptance according to variations in policy attribute levels. To achieve this, stated preference data obtained from choice experiments are analyzed using a mixed logit model, one of the discrete choice models (DCMs). The second is to suggest an integrated approach to simultaneously analyze public preferences for multiple policies in a policy category. It is often necessary to understand public preference structure for a certain policy category in order to design overall policy direction. To achieve this, a data classification method is developed to classify various policy alternatives. The multivariate probit (MVP) model, which is also a DCM, is used to analyze these classified data. Empirical analyses are conducted for three renewable energy policies: the Renewable Portfolio Standard (RPS), Renewable Fuel Standard (RFS), and two different types of Renewable Heat Obligations (RHOs), namely RHO schemes aimed at either heat suppliers or building owners. The selected policies represent a strong regulatory component and serve as quantitative policies in the electric power, transport, and heating sectors, respectively. The results of the mixed logit model show that the public assigns great importance to the price attribute, which is critical to maintain relatively high public acceptance. In the case of the RPS, public acceptance will be maintained at above 89.5% if the increase in electricity bills is limited to under 6%. Public acceptance of the RFS varies from 91.2-48.8% when the price of transportation fuels is increased by 0-45%. In case of the RHO for heat suppliers, an increase of 0-30% in heating expenses decreases public acceptance from 99.9-60.3%. Other important attributes having substantial influence on public acceptance of renewable energy policies are new job creation in the RPS, stability of the heat supply in the RHO for heat suppliers, and government subsidy in the RHO for building owners. In the case of the RFS, attributes other than increased fuel price have little effect on public acceptance. The results of the MVP model show that the public is sensitive to increased energy prices in general, because they assign great importance to the price attribute. Moreover, the publics average preferences for renewable energy policies can change according to the type of RHO. While the publics level of knowledge about renewable energy policies has a positive effect on their choice of eco-friendly policies, their attitude toward environmental protection has no bearing on the same. Thus, in order to ease public resistance incurred by possible increases in energy prices, governments should map out efficient strategies to improve the publics knowledge of renewable energy policies. In conclusion, the proposed methodology in this dissertation allows one to not only analyze public acceptance of an innovation policy more quantitatively but also to analyze public preferences for a superordinate policy category simultaneously. The framework of this research can be generally applied to any public innovation policy. Notably, the proposed integrated data classification method can be applied to any category of policies/products having common attributes.Abstract iii Contents vii List of Tables ix List of Figures x Chapter 1. Introduction 1 1.1 Overview: Toward a Demand-Oriented Innovation Policy 1 1.2 Objectives of this Dissertation 6 1.3 Outline of this Dissertation 8 Chapter 2. Literature Review 12 2.1 Public Acceptance of New Technology and Policy 12 2.2 Research on Renewable Energy Policies 21 Chapter 3. Methodology 29 3.1 Stated Preference Technique: Discrete Choice Experiment 29 3.2 Mixed Logit Model 34 3.3 Multivariate Probit Model 38 Chapter 4. Quantifying Public Acceptance of Renewable Energy Policies 43 4.1 Renewable Portfolio Standard: Analysis in the Electric Power Sector 43 4.1.1 Research Background 43 4.1.2 Data: Design of Choice Experiment 46 4.1.3 Results and Discussion 51 4.1.4 Section Summary 62 4.2 Renewable Fuel Standard: Analysis in the Transport Sector 63 4.2.1 Research Background 63 4.2.2 Data: Design of Choice Experiment 66 4.2.3 Results and Discussion 73 4.2.4 Section Summary 81 4.3 Renewable Heat Obligation: Analysis in the Heating Sector 83 4.3.1 Research Background 83 4.3.2 Data: Design of Choice Experiment 87 4.3.3 Results and Discussion 94 4.3.4 Section Summary 106 Chapter 5. An Integrated Approach to Analyze Public Preferences for a Policy Category 110 5.1 Research Background 110 5.2 Data: Classifying innovation policies into types 112 5.3 Results and Discussion 120 Chapter 6. Conclusion 131 Bibliography 137 Appendix: Survey questionnaires 158 Abstract (Korean) 179Docto

A Statistical Approach to the Alignment of fMRI Data

Multi-subject functional Magnetic Resonance Image studies are critical. The anatomical and functional structure varies across subjects, so the image alignment is necessary. We define a probabilistic model to describe functional alignment. Imposing a prior distribution, as the matrix Fisher Von Mises distribution, of the orthogonal transformation parameter, the anatomical information is embedded in the estimation of the parameters, i.e., penalizing the combination of spatially distant voxels. Real applications show an improvement in the classification and interpretability of the results compared to various functional alignment methods