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

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

A framework for innovative service design

Drawing on research from design science, marketing and service science, our paper provides an integrated framework for evaluating and directing innovative service design. The main goal of our review is to highlight the strengths of existing frameworks and to suggest how they can be enhanced in combination with design science principles. Based on our review, we propose a new framework for the design of innovative services that integrates several key paradigmatic approaches and identifies fundamental open research questions. Our approach is unique as it combines three service disciplines, namely services marketing, service science, and design science, and provides a new framework that describes step by step the procedure that needs to be taken and the conditions that need to be met for developing innovative services. We believe that providing such a framework is a valuable addition to the literature

Understanding How Farmers Evaluate and Value Services

Farm Management,

More Isn't Always Better – Measuring Customers' Preferences for Digital Process Transparency

Digital technologies have made the line of visibility more transparent, enabling customers to get deeper insights into an organization's core operations than ever before. This creates new challenges for organizations trying to consistently deliver high-quality customer experiences. In this paper we conduct an empirical analysis of customers’ preferences and their willingness-to-pay for different degrees of process transparency, using the example of digitally-enabled business-to-customer delivery services. Applying conjoint analysis, we quantify customers' preferences and willingness-to-pay for different service attributes and levels. Our contributions are two-fold: For research, we provide empirical measurements of customers’ preferences and their willingness-to-pay for process transparency, suggesting that more is not always better. Additionally, we provide a blueprint of how conjoint analysis can be applied to study design decisions regarding changing an organization's digital line of visibility. For practice, our findings enable service managers to make decisions about process transparency and establishing different levels of service quality

FACILITATING E-MOBILITY THROUGH DIGITAL TECHNOLOGIES – DEVELOPMENT AND EVALUATION OF A DYNAMIC BATTERY-LEASING BUSINESS MODEL

The electric mobility sector – an important pillar for counteracting climate change – is facing a sluggish market development. In this paper, we present a new dynamic battery-leasing business model that can play a key role in promoting the market introduction of electric mobility. Unlike medium- to long-term approaches for creating additional value from electric vehicles (e.g., demand response or vehicle-to-grid), the business model we propose can be applied in the short run as all necessary prerequisites are already fulfilled. To demonstrate, we proceed in two major steps. First, we design the digital technology–enabled business model that breaks with current business logics by actively involving users in the value generation process. The concept contributes to reducing battery degradation effects and thus increases the residual value of the batteries. Second, we test the underlying hypothesis of our business model – the user’s willingness to follow a certain charging guideline in order to extend battery lifetime – using a comprehensive conjoint analysis. Thus, our research demonstrates how information systems can be used to encourage green choices by consumers

Product design selection using online customer reviews

Product design selection is heavily constrained by its customer preference data acquisition process. Traditionally, the customer preference data is collected through survey-based methods such as conjoint; sometimes product prototypes are generated and evaluated by focused groups of customers. In this way, the data acquisition process can become costly and require a significant amount of time. The goal of this dissertation is to overcome the limitation of the traditional customer preference data acquisition process by making use of a new type of customer data - online customer reviews. Because online customer reviews are, to a large extent, freely available on the Internet copiously, using them for product design can significantly reduce the cost as well as the time. Of course, the data obtained from online reviews have some disadvantages too. For example, online reviews are freely expressed and can contain a lot of noise. In this dissertation, a new methodology is developed to extract useful data from online customer reviews from a single website, construct customer preference models and select a product design that provides a maximum expected profit. However, online customer reviews from a single website may not represent the market well. Furthermore, different websites may have their own procedures and formats to acquire customer reviews. A new approach is developed to systematically elicit customer data from multiple websites, construct customer preference models by considering website heterogeneity, and select a product design. The model from multiple websites is also extended to account for customer preference heterogeneity. The models obtained from the online customer reviews for single and multiple websites are compared and validated using a set of out-of-sample data. To demonstrate the applicability of the proposed models, a smartphone case study is used throughout the dissertation

Doctor of Philosophy

dissertationThis dissertation consists of three essays that investigate the general decision process of users' choices regarding information technology (IT) applications and products, focusing on placebo effects of software pricing, incorporating user perceptions and product attributes in modeling software product choices, and firms' practices of green IT. Taking a customer-centric approach to users' assessments of IT applications and products, I address the evaluative responses of individual consumers and organizations to market information including price, product attributes, and key contextual factors. The objective of the first essay is to understand the placebo-like effects invoked by the price of software products on consumers' satisfaction, problem-solving performance, and purchasing behavior. Built upon the response expectancy theory, a research framework and a series of hypotheses are proposed. I test the hypotheses with a controlled experiment, and the data supports most of the hypotheses. Specifically, a user's outcome expectancy, as activated by software price, affects not only his/her satisfaction, but also the problem-solving performance using the software product. Satisfaction and actual problem-solving performance in turn affects the user's willingness-to-pay. In order to better explain and predict consumers' preferential choices of software products, I propose in the second essay a model that incorporates product attributes and consumer perceptions to estimate users' software product selection. The influences of product attributes on users' perceptions of product characteristics are also examined. With a choice-based conjoint study, and the collection of additional data on users' perceived product characteristics, I demonstrate that the proposed model can better explain and predict users' software choices than the model with product attributes only, or with user perceptions only, in terms of the in-sample fit and the holdout prediction hit rate at the individual-level and the aggregate-level. The third essay examines important drivers of green IT practices by firms. I propose a framework premised on social contracts theory and institutional theory, and then use it to develop a model that explains firms' decisions. I test the model and the associated hypotheses with the survey data collected from 304 major firms in Taiwan. Overall, the results show global environmental awareness, industry norms, and key stakeholders' attitudes affect a firm's green IT practices directly. Competitors seem to play a limited role, as suggested by an insignificant impact on the firm's green IT practices