2,578 research outputs found
The role of badges to spur frequent travelers to write online reviews
Purpose: Online travel reviews platforms have become innovative information systems also due to the incorporation of sophisticated gamification elements such as visually appealing badges. This study aims to analyze three features of the review after leveling up a badge: review length (number of words), sentiment scoring, and period between two successive reviews (number of days until the next review is written).
Design/methodology/approach: A total of 77k online TripAdvisor reviews written by 100 frequent travelers and contributors are analyzed using a data mining approach. A data-based sensitivity analysis (DSA) is then conducted to provide an understanding of the data mining trained models.
Findings: The results show evidence that badges appealing for self-pride (âbadge passportâ) and for peer-recognition (âbadge helpfulâ) have significant influence across the lifespan of online review, whereas badges simply awarded by counting the contributions have little effect.
Originality: This study provides the first analysis of how an experienced traveler is influenced as the badges and points are being awarded. Intrinsic motivational factor to award badges for standard contributions scarcely influence user behavior. Badges need to be designed to reward accomplishments that are not so trivial to be achieved and that do not depend entirely on the user.info:eu-repo/semantics/acceptedVersio
The millennialization of the sale
This research project examined how the art of selling has been reinvented by three interrelated cultural changes that had a domino effect on each other: technology, globalization, and the millennial generation. In the last several decades, technology has evolved exponentially, and became the most significant catalyst for sprawling globalization. Together, technology and globalization evolved and bred the very unique, millennial generation. In order to better understanding of how businesses sell to this unique generation, the scope of this project was narrowed. A comparative case analysis and SWOT were conducted on four organizations with Wisconsin roots: Johnson Controls, Inc., GE Healthcare, Northwestern Mutual, and Kohlâs. Each company competes in different platforms, industries, and markets. However, they all need to uncover how to sell to the millennial generation in order to sustain in the future. Based on the research, recommendations to sell to this generation include: engage in technology, take a global approach, and assess using the triple bottom line
Semantic discovery and reuse of business process patterns
Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse
A Survey on Cross-domain Recommendation: Taxonomies, Methods, and Future Directions
Traditional recommendation systems are faced with two long-standing
obstacles, namely, data sparsity and cold-start problems, which promote the
emergence and development of Cross-Domain Recommendation (CDR). The core idea
of CDR is to leverage information collected from other domains to alleviate the
two problems in one domain. Over the last decade, many efforts have been
engaged for cross-domain recommendation. Recently, with the development of deep
learning and neural networks, a large number of methods have emerged. However,
there is a limited number of systematic surveys on CDR, especially regarding
the latest proposed methods as well as the recommendation scenarios and
recommendation tasks they address. In this survey paper, we first proposed a
two-level taxonomy of cross-domain recommendation which classifies different
recommendation scenarios and recommendation tasks. We then introduce and
summarize existing cross-domain recommendation approaches under different
recommendation scenarios in a structured manner. We also organize datasets
commonly used. We conclude this survey by providing several potential research
directions about this field
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Putting e-commerce to work: The Japanese convenience store case
Japanese convenience stores (CVS) are exploiting e- and m-commerce solutions different from, but relevant to, US practices. Seven-Eleven Japan, Lawson, and FamilyMart ĂąËâ three of the largest CVS ĂąËâ base their fundamental business models on increasing store traffic. Japanese reluctance to make credit card payments over the Internet or via telephones opened the way for CVS to provide third-party payment services, which required substantial IT infrastructure. Now they are leveraging this investment. In doing so, they are following a different e-commerce B2C model than is typical in the United States. Their approach incorporates heavy dependence on IT-based alliances (e-retsu), a range of services and products, and telematics (coupling detailed database management with the use of smart cell phones and sophisticated in-car communication and guidance systems) rather than PCs. This business-to-consumer (B2C) model is relevant to markets and market segments possessing similar characteristics
Privacy Enhancing Technologies for solving the privacy-personalization paradox : taxonomy and survey
Personal data are often collected and processed in a decentralized fashion, within
different contexts. For instance, with the emergence of distributed applications,
several providers are usually correlating their records, and providing personalized services to their clients. Collected data include geographical and indoor
positions of users, their movement patterns as well as sensor-acquired data that
may reveal usersâ physical conditions, habits and interests. Consequently, this
may lead to undesired consequences such as unsolicited advertisement and even
to discrimination and stalking. To mitigate privacy threats, several techniques
emerged, referred to as Privacy Enhancing Technologies, PETs for short.
On one hand, the increasing pressure on service providers to protect usersâ privacy resulted in PETs being adopted. One the other hand, service providers
have built their business model on personalized services, e.g. targeted ads and
news. The objective of the paper is then to identify which of the PETs have the
potential to satisfy both usually divergent - economical and ethical - purposes.
This paper identifies a taxonomy classifying eight categories of PETs into three
groups, and for better clarity, it considers three categories of personalized services. After defining and presenting the main features of PETs with illustrative
examples, the paper points out which PETs best fit each personalized service
category.
Then, it discusses some of the inter-disciplinary privacy challenges that may
slow down the adoption of these techniques, namely: technical, social, legal and
economic concerns. Finally, it provides recommendations and highlights several
research directions
UNDERSTANDING USER PERCEPTIONS AND PREFERENCES FOR MASS-MARKET INFORMATION SYSTEMS â 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 consumerâs preferences for multiple factors combing functional, non-functional and economic aspects. The results include a âFramework for Conjoint Analysis Studies in ISâ 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.
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Les technologies cloud et mobiles ont fait Ă©merger une nouvelle catĂ©gorie de produits informatiques qui sâadressent Ă des utilisateurs hĂ©tĂ©rogĂšnes par le biais de systĂšmes d'information (SI) distribuĂ©s. Les termes âSI de masseâ sont employĂ©s pour dĂ©signer ces nouveaux systĂšmes. Une conception rĂ©ussie de ceux-ci passe par une phase essentielle de comprĂ©hension des besoins et des facteurs d'adoption des utilisateurs. Pour ce faire, la recherche en SI suggĂšre plusieurs thĂ©ories et modĂšles tels que le âIS Success Modelâ et le âTechnology Acceptance Modelâ. Bien que ces approches contribuent Ă la comprĂ©hension thĂ©orique de l'adoption et de l'utilisation des SI de masse, elles sont critiquĂ©es pour ne pas ĂȘtre en mesure de fournir des informations exploitables sur la conception de SI car elles considĂšrent l'artefact informatique comme une boĂźte noire. En dâautres termes, ces approches ne traitent pas suffisamment des caractĂ©ristiques internes du systĂšme. Nous soutenons que la recherche en SI doit adopter des techniques d'Ă©tude de marchĂ© afin de mieux intĂ©grer les exigences du client (âVoice of Customerâ) dans un scĂ©nario de marchĂ© de masse. Plus prĂ©cisĂ©ment, l'analyse conjointe (AC), issue de la recherche sur les consommateurs, peut contribuer au dĂ©veloppement de systĂšme SI Ă forte valeur d'usage. Si lâAC a gagnĂ© en popularitĂ© au sein de la recherche en SI, des recommandations quant Ă son utilisation dans ce domaine restent rares. Nous entendons soutenir la conception de SI de masse en facilitant une identification fiable des prĂ©fĂ©rences des consommateurs sur de multiples facteurs combinant des aspects fonctionnels, non-fonctionnels et Ă©conomiques. Les rĂ©sultats comprennent un âCadre de rĂ©fĂ©rence pour les Ă©tudes d'analyse conjointe en SIâ et des recommandations mĂ©thodologiques pour l'application de lâAC. Nous avons utilisĂ© ces contributions pour concevoir un SI de masse particuliĂšrement sensible au respect de la vie privĂ©e des utilisateurs et nous avons Ă©valuĂ© lâimpact de nos recherches sur l'adoption de ce systĂšme par ses utilisateurs. Ainsi, notre travail contribue tant Ă la thĂ©orie quâĂ la pratique des SI. Pour le monde universitaire, nous contribuons en proposant une conceptualisation plus nuancĂ©e de l'artefact informatique (c'est-Ă -dire du systĂšme) Ă travers le prisme des fonctionnalitĂ©s et par une approche basĂ©e sur les prĂ©fĂ©rences utilisateurs. Par ailleurs, les chercheurs peuvent Ă©galement s'appuyer sur nos directives mĂ©thodologiques pour Ă©tudier les perceptions et les prĂ©fĂ©rences des utilisateurs pour diffĂ©rentes variations de conception et Ă©tendre cela Ă l'adoption. De plus, nos Ă©tudes empiriques sur la conception dâun SI de masse sensible au respect de la vie privĂ©e des utilisateurs contribuent Ă une meilleure comprĂ©hension de lâapplication des techniques CA dans ce domaine spĂ©cifique. Nos Ă©tudes incluent notamment une Ă©valuation nuancĂ©e des prĂ©fĂ©rences des utilisateurs sur des fonctionnalitĂ©s de protection de la vie privĂ©e. Pour les praticiens, nous proposons des lignes directrices qui permettent dâintĂ©grer les exigences des clients afin de concevoir un SI rĂ©ussi
Automated Negotiation Among Web Services
Software as a service is well accepted software deployment and distribution model that is grown exponentially in the last few years. One of the biggest benefits of SaaS is the automated composition of these services in a composite system. It allows users to automatically find and bind these services, as to maximize the productivity of their composed systems, meeting both functional and non-functional requirements. In this paper we present a framework for modeling the dependency relationship of different Quality of Service parameters of a component service. Our proposed approach considers the different invocation patterns of component services in the system and models the dependency relationship for optimum values of these QoS parameters. We present a service composition framework that models the dependency relations ship among component services and uses the global QoS for service selection
University catalog, 2016-2017
The catalog is a comprehensive reference for your academic studies. It includes a list of all degree programs offered at MU, including bachelors, masters, specialists, doctorates, minors, certificates, and emphasis areas. It details the university wide requirements, the curricular requirements for each program, and in some cases provides a sample plan of study. The catalog includes a complete listing and description of approved courses. It also provides information on academic policies, contact information for supporting offices, and a complete listing of faculty members. -- Page 3
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