A De-biased Direct Question Approach to Measuring Consumers' Willingness to Pay

Knowledge of consumers' willingness to pay (WTP) is a prerequisite to profitable price-setting. To gauge consumers' WTP, practitioners often rely on a direct single question approach in which consumers are asked to explicitly state their WTP for a product. Despite its popularity among practitioners, this approach has been found to suffer from hypothetical bias. In this paper, we propose a rigorous method that improves the accuracy of the direct single question approach. Specifically, we systematically assess the hypothetical biases associated with the direct single question approach and explore ways to de-bias it. Our results show that by using the de-biasing procedures we propose, we can generate a de-biased direct single question approach that is accu-rate enough to be useful for managerial decision-making. We validate this approach with two studies in this paper.Comment: Market Research, Pricing, Demand Estimation, Direct Estimation, Single Question Approach, Choice Experiments, Willingness to Pay, Hypothetical Bia

Factors affecting smartphone shopping.

In recent years, the telecommunication sector has seen its market-leaders change. Today, the market is headed by 11 manufacturers, even though two main companies hold 42% of the market-share (Samsung and Apple). Furthermore, hundreds of models incorporating new functionalities are launched every year. This research is one of the first attempts to investigate functional evaluation in shopping smartphones and to predict future context of this turbulent market. With the use of 264 surveys of real smartphone owners and users, collected online in the first fortnight of May 2015, and the use of Conjoint Analysis (CA), we highlight major attributes consumers take into consideration in buying smartphones. Results show that consumers who decide to buy a smartphone consider Price, Camera performance, Battery-life and Brand. De facto, we find that, in smartphone shopping, consumers brand awareness is less important than technical characteristics. Notwithstanding, running the CA on subgroups defined by the brand of the smartphone owned, we find different attributes’ relative importance. Results show that Apple owners have a stronger brand awareness than Samsung owners. Implications aim to help manufacturers in developing smartphone features rationalizing invested resources, interpreting preferences of customers and reinforcing competitive advantages

A Consumer Perspective on Mobile Service Platforms: A Conjoint Analysis Approach

Digital platforms need to attract both application developers and end users. Existing literature suggests various strategies related to openness, flexibility, and generativity to attract application developers. However, how consumers make decisions on adopting platforms has not been studied. This paper studies which characteristics of digital platforms consumers most prefer. We focus on mobile platforms where application stores, operator portals, and service provider platforms compete for the consumer’s attention. We conducted a conjoint analysis among 166 consumers to determine the most important characteristics of the mobile platforms. We found that application-related characteristics were most important, especially the number of available applications. Governance-related and technical characteristics were hardly important. Platform characteristics were considerably less important than the brand of the operating system linked to the platform. These findings were consistent between European and Chinese users, and between males and females. The study paves the way for IS scholars to integrate consumer perspectives in the provider-dominated discourse of digital platforms

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 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

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

Smart Shopping Carts to Increase Healthier Food Purchase: A Conjoint Experiment

Shopping carts, in general, should be suitable for carrying smart technology in the retail store environment. Also, a smart shopping cart can present verbal motivating stimuli to increase healthier food purchases. A conjoint experiment was used to test with a hypothetical purchasing task for young consumers (n=91) the potential of motivating stimulus on smart shopping carts to influence healthier purchases when buying frozen pizza. The results show a positive impact for all stimuli stemming from the smart shopping cart, three of which were health-based. This shows that stimuli revealing dynamic and personalized data through smart technology in a physical grocery retail setting have the potential to outperform traditional brand statements. Our conjoint experiment increased young consumers’ likelihood of choosing a healthier frozen pizza. This result demonstrates that verbal stimuli on smart shopping carts can function as motivating augmentals on young adult consumers’ healthier food purchases and are in line with the market positioning and customerservice focus of many retailers and brands today, emphasizing a social marketing standing

Smart Shopping Carts to Increase Healthier Food Purchase: A Conjoint Experiment

Shopping carts, in general, should be suitable for carrying smart technology in the retail store environment. Also, a smart shopping cart can present verbal motivating stimuli to increase healthier food purchases. A conjoint experiment was used to test with a hypothetical purchasing task for young consumers (n=91) the potential of motivating stimulus on smart shopping carts to influence healthier purchases when buying frozen pizza. The results show a positive impact for all stimuli stemming from the smart shopping cart, three of which were health-based. This shows that stimuli revealing dynamic and personalized data through smart technology in a physical grocery retail setting have the potential to outperform traditional brand statements. Our conjoint experiment increased young consumers’ likelihood of choosing a healthier frozen pizza. This result demonstrates that verbal stimuli on smart shopping carts can function as motivating augmentals on young adult consumers’ healthier food p urchases and are in line with the market positioning and customer-service focus of many retailers and brands today, emphasizing a social marketing standing.publishedVersio

Sport Psychology App lication: NCAA Coaches\u27 Preferences for a Mental Training Mobile App

This study utilized a consumer marketing approach to investigate National Collegiate Athletic Association (NCAA) head coaches\u27 preferences for a mental training mobile application (mobile map) using a conjoint market analysis. Head coaches\u27 preferences for a mental training mobile app were compared based on price, ability to track athlete use of the app, recommendation sources, the inclusion of daily functions, coaches\u27 awareness of the app being used by other teams, and the credibility of the mobile app content creators. Price and tracking athlete use were the two most important characteristics to coaches. Considering all characteristics, coaches preferred mobile apps that cost less than {dollar}200, provided comprehensive tracking of athlete use, came with an internal recommendation, included daily functions, were used by other teams, and were created by content creators who work with other successful programs. Based on market simulations, more than two-thirds of coaches would purchase a mental training mobile app with the characteristics presented in this study if given the chance. The present findings are evidence that the use of mental training at the NCAA level may rely more on the delivery method and cost of services than previously thought

UNDERSTANDING THE BENEFIT STRUCTURE OF CLOUD STORAGE AS A MEANS OF PERSONAL ARCHIVING - A CHOICE-BASED CONJOINT ANALYSIS

While cloud storage has seen an increasing rise in demand and diffusion, it is also becoming a commodity, which makes it more difficult for cloud storage providers to be competitive in the market. To be successful as a storage provider, it is crucial to understand customer preferences so that these can be addressed accordingly. In this paper, we investigate consumer cloud storage choice decisions by employing a conjoint analysis that is based on empirical data collected from 340 participants and analyzed by means of hierarchical Bayes estimation. Our findings indicate significant differences in consumer preferences for price, storage capacity, encryption mechanism and accessibility. Based on these differences, we derive three consumer clusters that also exhibit differences in, e.g., their privacy concerns and risk beliefs. Based on our findings, we highlight some practical implications that can aid cloud storage providers in service design and adjustment decisions. This study contributes to the literature by providing a better understanding of the benefit structure and trade-offs user make in the choice of storage services. As an alternative to commercial conjoint software packages, we further contribute a method that can be adopted by other scholars who seek to conduct conjoint analyses using free software