We investigate the use of dimensionality reduction to improve performance for a new class of data analysis software called “recommender systems”. Recommender systems apply knowledge discovery techniques to the problem of making product recommendations during a live customer interaction. These systems are achieving widespread success in E-commerce nowadays, especially with the advent of the Inte...

This study analyzes the value created by so-called ‘‘toolkits for user innovation and design,’’ a new method of integrating customers into new product development and design. Toolkits allow customers to create their own product, which in turn is produced by the manufacturer. In the present study, questions asked were (1) if customers actually make use of the solution space offered by toolkits, ...

Advanced personalized e-applications require comprehensive knowledge about their user’s likes and dislikes in order to provide individual product recommendations, personal customer advice and custom-tailored product offers. In our approach we model such preferences as strict partial orders with “A is better than B” semantics, which has been proven to be very suitable in various e-applications. ...

Today, workforce scheduling programs are being implemented in many production and service centers. These sectors can provide better quality products and/or services to their customers, taking into account employees’ desires and preferences in order to increase sector productivity. In this study, an employee shift scheduling problem in the service sector is discussed. In the problem, the aim is ...

INTRODUCTION: Many online services use data-sharing nudges to solicit personal data from their customers for personalized services. OBJECTIVES: This study aims people’s privacy preferences in sharing different types of under nudging conditions, how digital nudgi

• Design an innovative user-based relocation policy to solve the vehicle problem in oneway car-sharing systems. Integrate a Markovian prediction method forecast future demand losses due imbalances. Propose adaptive that determines optimal incentive based on customers’ value of time. Illustrate benefits and performance compared staff-based terms service level, cost sustainability. Describe hybri...

the paper presents a factorization-based approach to make predictions in recommender systems. these systems are widely used in electronic commerce to help customers find products according to their preferences. taking into account the customer’s ratings of some products available in the system, the recommender system tries to predict the ratings the customer would give to other products in the ...

We consider cheap talk by a biased expert comparing multiple issues, e.g., discussion of different spending proposals by an industry lobbyist, evaluation of different stocks by a sell-side analyst, or analysis of different topics by a biased newspaper. When the expert’s motives are sufficiently transparent, we find that cheap talk is credible and influential even when the expert strongly favors...

In this paper, we introduce a notion of epistemic equivalence between hierarchies of conditional beliefs and hierarchies of lexicographic beliefs, thus extending the standard equivalence results of Halpern (2010) and Brandenburger et al. (2007) to an interactive setting, and we show that there is a Borel surjective function, mapping each conditional belief hierarchy to its epistemically equival...

We study the problem of elicitation of subjective beliefs of an agent when the beliefs are ambiguous (the set of beliefs is a non-singleton set) and the agent’s preference exhibits ambiguity aversion; in particular, as represented by α-maxmin preferences. We construct a direct revelation mechanism such that truthful reporting of beliefs is the agent’s unique best response. The mechanism uses kn...