A CONJOINT STUDY OF THE RELATIONSHIP BETWEEN WEBSITE ATTRIBUTES AND CONSUMER PURCHASE INTENTIONS

This paper extends and modifies the Schaupp and Belanger model (2005) to develop and propose a model of on-line shopping intentions. Four on-line websites were designed as the test platforms. Respondents of this study were asked to visit these web-sites that represent differing shopping scenarios before they completed our on-line survey. Findings of this study are as follows. First, on-line contract signing mechanism was ranked as the most desired option in building trust in on-line shopping websites by all respondents. Second, respondents of this study were found able to be categorized into three groups according to the website factors they valued most. The three were logistic/security, security/trust, and convenience/trust. The specific attributes of on-line shopping websites valued most within each of the three groups are discussed in this paper. This study presents findings that support the use of many existing on-line technologies that have been found little used in on-line shopping websites such as digital certificate and on-line contracting. The inclusion of these technologies in on-line shopping websites may increase the cost of building and maintaining them and may create worries about user inconvenience. However, it is important that these technologies increase the attractiveness of the on-line shopping website and web surfers purchase intentions

Direct and mediated impacts of product and process characteristics on consumers’ choice of organic vs. conventional chicken

There is a lack of research into why consumers value process characteristics. In this study, we test the hypothesis that the impact of process characteristics such as organic and free-range on consumers’ choices of food products is at least partly mediated through expected eating quality or taste expectations. In other words, the process characteristics partly function as cues to (eating) quality. Using a traditional metric conjoint approach based on an additive model, four product characteristics (production method, price, size and information about farmer and rearing conditions) were varied in a fractional factorial conjoint design, creating nine profiles of whole chickens. 384 respondents rated the nine different chickens in terms of taste expectations and willingness to buy. Since the nine records for each respondent are not independent, we used linear mixed modelling for the mediation analysis, We find that, as expected, taste expectations are a strong predictor of willingness to buy. As hypothesized, the impact of both product and process characteristics on willingness to buy is at least partly mediated through taste expectations. Hence, the study shows that process characteristics are important for consumers, not only in and off themselves, but partly because consumers make inferences about eating quality from knowledge about such process characteristics

Please, talk about it! When hotel popularity boosts preferences

Many consumers post on-line reviews, affecting the average evaluation of products and services. Yet, little is known about the importance of the number of reviews for consumer decision making. We conducted an on-line experiment (n= 168) to assess the joint impact of the average evaluation, a measure of quality, and the number of reviews, a measure of popularity, on hotel preference. The results show that consumers' preference increases with the number of reviews, independently of the average evaluation being high or low. This is not what one would expect from an informational point of view, and review websites fail to take this pattern into account. This novel result is mediated by demographics: young people, and in particular young males, are less affected by popularity, relying more on quality. We suggest the adoption of appropriate ranking mechanisms to fit consumer preferences. © 2014 Elsevier Ltd

The Relative Importance of Search versus Credence Product Attributes: Organic and Locally Grown

Organic foods and local foods have come to the forefront of consumer issues, due to concerns about nutrition, health, sustainability, and food safety. A conjoint analysis experiment quantified the relative importance of, and trade-offs between, apple search and experience attributes (quality/blemishes, size, flavor), credence attributes (conventional vs. organic production method, local origin vs. product of USA vs. imported), and purchase price when buying apples. Quality is the most important apple attribute. Production method—organic versus conventional—had no significant impact on preferences.conjoint analysis, organic, locally grown, credence attributes, Consumer/Household Economics, Food Consumption/Nutrition/Food Safety, Marketing,

The Effect of Loyalty Program Attributes on Customer’s Booking Choice

A loyalty program is commonly observed in our real world to establish and maintain a customer relationship. However, there is limited research information on the effect of loyalty program schemes on customers\u27 choice in an online booking context. The current study summarized the awards currently offered by major hotels and online travel agencies (OTAs) and examined: 1) customers\u27 preference toward attributes of the loyalty program, 2) within reward attributes, which contributes to an increase in consumers\u27 booking choice, 3) which attributes make customers book on hotel websites rather than on OTA websites, and 4) the interaction between customer involvement and hotel loyalty programs\u27 attributes on booking preference. The results revealed that customers prefer rewards that are related to hotel booking and immediate point redemption. Changing the reward attribute level from unrelated rewards to related rewards increased customers\u27 probability of choice. However, timing of redemption did not affect the choice. Further, the effect of related rewards on increasing the chance of booking was stronger for consumers on a high reward program tier than those on a low reward program tier. However, no interaction was found between time and customers\u27 tier of the program. Results suggest that the effect of hotel and OTA\u27s loyalty program attributes on customers\u27 choice is different from other industries\u27 loyalty programs

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

UNDERSTANDING USER’S TRUST FORMATION ON MULTI-SIDED E-COMMERCE PLATFORMS

With the ever-growing popularity of online shopping, platform environments providing access to products by multiple sellers increasingly attract users. To reduce information asymmetry and enhance user trust, platform actors provide signals such as star reviews to demonstrate their trustworthiness. This work investigates the influence of trust signals from different sources (on the platform itself vs. on external third-party review sites) and for different targets (platform provider vs. seller) on users’ trust formation in multi-sided e-commerce platforms. We conduct a choice-based conjoint analysis based on data from 81 participants. Our results show that users weigh external signals stronger than internal ones when building trust. Also, trust signals for sellers have a higher impact on users’ trust than platform provider signals. Signal discrepancies between internal and external reviews are especially harmful to the platform provider. These insights extend prior knowledge on trust formation and its impacting factors on e-commerce platforms

A study of consumer preferences for e-retailers’ attributes: an application of conjoint analysis

The aim of this paper is to determine and analyse consumer preferences regarding the profiles of an e-retailer’s website. Two types of products are examined to test whether there are differences in the individuals’ preferences. We conduct an initial study, from which we identify the principal attributes valued by the participants in the survey. These attributes are then used to design the profiles for the conjoint analysis. The variables that are most relevant to the shopping task are those which receive a higher response frequency. There are differences in the relative importance assigned to the attributes, depending on the product type, but no significant differences are found in the participants’ preferences when these are analysed according to gender or previous experience of online shopping

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