Recent advances in social media have profound technical and economic implications for innovative design. This research is motivated to investigate social network effects on product design with a focus on the interface of engineering design, viral marketing, and social computing. This dissertation envisions a new paradigm of design, called viral product design for social network effects. The research problem is formulated as identification of both an optimal set of product configurations and an optimal set of seed customers so as to maximize product adoption via online social networks through equilibrium solutions to marketing-engineering coordination. Fundamental issues are investigated and a technical framework is proposed with integrated decision-based design methods. Results of case studies demonstrate that the proposed research is able to bridge the gaps between the domains of engineering design and viral marketing by incorporating social network effects. The proposed work is geared towards new design theory and decision models by integrating peer influence of social networks, which shed light on understanding the social aspect of design. The dissertation reveals the fundamental issues underlying viral product design, including the identification of viral attributes, customer preference modeling incorporating subjective experiences, the dynamics of the diffusion mechanism of online social networks, formulation of adoption maximization, and coordination between the marketing and engineering domains. In order to tackle the fundamental issues, a technical framework of viral product design for social network effects is proposed. Accordingly, mathematical and computational models are developed within the framework to support 1) latent customer needs elicitation for viral product attributes extraction, 2) customer preference modeling and quantification for product choice decision making, 3) social network modeling for product adoption prediction, and 4) viral product design evaluation by adoption maximization. These coherent models along the technical framework lay the theoretical foundation of this research, as described below. First, in order to extract potential viral product attributes, latent customer needs elicitation is emphasized. This is because latent customer needs can delight customers unexpectedly, and thus lead to potential product adoption to a large extent. We propose to elicit latent customer needs by use case analogical reasoning from sentiment analysis of online product reviews. A case study of Kindle Fire HD tablets shows the potential and feasibility of the proposed method. The extracted product attributes and attribute levels provide the choice set of viral product attributes. Second, based on the extracted product attributes, a customer preference model based on cumulative prospect theory is presented, accommodating subjective experiences in the product choice decision making process. Moreover, a hierarchical Bayesian model with Markov chain Monte Carlo is used to estimate parameters involved in the model. Based on the case study of aircraft cabin interior design, the model parameters under different experimental conditions show systematic influence of subjective experiences in choice decision making. Furthermore, a copula structure is used to construct a holistic product utility, showing customers' overall preferences to a product. This measure is crucial to product choice decision making in the context of social networks. Third, in order to predict product adoption incorporating peer influence of social networks, a linear threshold-hurdle model is proposed. It overcomes multiple drawbacks of traditional diffusion models by modeling activation thresholds, influence probability, adoption spread, holistic utility of the product, and hurdle utility of a customer in a holistic fashion. A case study of Kindle Fire HD tablets demonstrates both the predictive power of the proposed model and interesting results about customers' adoption behavior. This model paves the way for product adoption maximization in large social networks. Fourth, in order to coordinate between marketing-engineering concerns, I formulate a bi-level game theoretic optimization model for viral product design evaluation, in which the leader maximizes product adoption, while the follower optimizes product line performance. Through social network effects in terms of viral product attributes and viral influence attributes, the expected number of product adopters and the expected shared surplus, resulting from the identified product configurations and seed customers, are proved to be larger than those obtained from existing practice of viral marketing and product line design respectively, based on the case study of Kindle Fire HD tablets. Thus, the proposed paradigm of design extends the traditional boundaries among domains of engineering design, viral marketing, and social computing.

This thesis addresses designing Product Lines (PLs) of Graphical Editors (GEs). It provides a feasible top-down design approach specialized on such Graphical Editor Product Lines (GEPLs), which can be configured dynamically. Furthermore, the end product's features are implemented modular, which has numerous positive effects on the development and maintenance processes for the family. These effects reach from decreasing the complexity of big PLs, allowing to delegate split up development tasks onto multiple isolated working teams, easier debugging and flexibility to extend or specialize a family of products as well as being able to use functionalities developed by third-party vendors. While design methods avoiding monolithic architectures and implementations exist for many PL domains, there are none known for GEPLs. Yet, the domain of those offers many challenges as GEPLs are actually comprised of Software Product Lines (SPLs) and Language Product Lines (LPLs), which is a combination untackled by any modular design approach known to me. Additionally, products in the domain require to implement multiple distinct and specific concerns, leading to artifacts which differ significantly but have to be located and managed in a single component. Overall, this justifies the need for specialized design approaches for the GEPL domain. In regard to this need, this thesis gives an overview of the existing landscape of approaches to design PLs, analyzing solutions offered by other researchers. Furthermore, a requirement analysis for the GEPL domain is conducted. Its results are the foundation for the presentation of a top-down design approach for dynamically configurable GEPLs, which are implemented feature modularly. Finally, a case study documenting the development of such a family of GEs is providing a proof of its feasibility.:1 Introduction 1.1 Motivation 1.2 Problem Definition 1.3 Outline 1.4 Terminology 2 Survey on Software and Language Product Line Design 2.1 Classification Scheme 2.1.1 Domain 2.1.2 Configuration 2.1.3 Design Method 2.1.4 Modularity 2.2 Overview 2.3 Discussion 2.3.1 Evaluation 2.3.2 Results 3 Requirements of Graphical Editor Product Lines 32 3.1 Functional Requirements 3.1.1 Edit Concerns 3.1.2 Language Family Concerns 3.2 Non-Functional Requirements 3.2.1 User Requirements 3.2.2 Development Requirements 4 Design of Graphical Editor Product Lines 4.1 Characteristics 4.2 Design Approach 4.2.1 Edit Concerns 4.2.2 Language Family Concerns 4.3 Discussion 4.3.1 Techniques 4.3.2 Evaluation 5 Case study: Modularization of a Family of Graphical Editors 5.1 Background 5.1.1 Compartment Role Object Model 5.1.2 Full-fledged Role Modeling Editor 5.1.3 Reusable Technology 5.2 Realization 5.2.1 Edit Concerns 5.2.2 Language Family Concerns 5.3 Discussion 5.3.1 Requirements 5.3.2 Limitations of the Modularization 5.3.3 Results 6 Conclusion 6.1 Summary 6.1.1 Desired Properties 6.1.2 Feasibility 6.2 Contributions 6.3 Future Work 6.3.1 Bottom-Up Design Method 6.3.2 Requirements 6.3.3 Modularization

This dissertation studies important issues in supply chain management and marketing interface research: competition, product line design, and channel efficiency, at the presence of vertically differentiated products. Vertical differentiation as a means of price discrimination has been well-studied in both economics and marketing literature. However, less attention has been paid on how vertical differentiation has been operationalized. In this dissertation, we focus our study on two types of vertical differentiation: the one created by a product line which is produced by the same firm, and the one created by products from different firms. We especially are interested in the so-called private label products vs. the national brand products. Specifically, this dissertation explores how vertical differentiation can affect the interactions among the members of a supply chain in several different contexts. In the first piece of work, we use a game theoretic model to explore how the ability of a retailer to introduce a private label product affects its interaction with a manufacturer of a national brand. In the second essay, we are investigating how an original equipment manufacturer (OEM) will be affected by the entry of a competitor when there are strategic suppliers of a critical component. If these suppliers behave strategically, it is not clear that the entry of other players will necessarily be harmful to the incumbent. In the last work, we pay our attention to an emerging change happening in the industry: some retailers begin to sell their private labels through their competitors. We investigate the strategic role of a retailer selling her own private label products through another retailer. In summary, this dissertation illustrates how vertical differentiation play a crucial role in firms' supply chain as well as marketing strategies. Therefore, it is important for firms to recognize these strategic issues related to vertically differentiated products while making operations/marketing decisions. / text