This study seeks to assess the impact of collaborative technologies on innovation at the firm level. Collaborative technologies’ influence on innovation is considered here as a multi-stage process that starts at adoption and extends to use. Thus, the effect of collaborative technologies on innovation is examined not only directly, the simple presence of collaborative technologies, but also base...

Dr. Stitt stated he felt that Dr. Mitchell's generalization, that large animals such as sheep did not produce fevers in response to intracerebral injections of PGE, was inaccurate, since there were at least two reports in the literature by Bligh and Milton and by Hales that documented such fevers. Dr. Mitchell acknowledged this fact, but added that these injections of PGE were given intracerebr...

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model cou...

Recommender system is currently widely used in many e-commerce systems, such as Amazon, eBay, and so on. It aims to help users to find items which they may be interested in. In literature, neighborhood-based collaborative filtering and matrix factorization are two common methods used in recommender systems. In this paper, we combine these two methods with personalized weights on them. Rather th...

Electronic commerce (EC) has become an important support for business and is regarded as an efficient system that connects suppliers with online users. Among the applications of EC, the recommender system is undoubtedly a popular issue to make the best recommendation to the users. Even if tremendous approaches have been proposed to perfect the recommendation, a comprehensive module comprising o...

Recommender systems are used by E-commerce sites to suggest products to their customers and to provide consumers with information to help them determine which products to purchase. Collaborative filtering algorithm is the most extensive personalized recommendation used in recommender systems. Since not being considering the dependence between predicted item and historical item, typical collabor...

In this paper we propose a conceptual model for e-procurement solutions for industrial services. Product-related services are of particular interest of companies and should be supported through an appropriate network strategy. However, in the service field, e-business solutions and current standards are still not or only partially considering specifications and related variables of services. We...

Providing experience-oriented offerings through e-commerce is an issue increasing critical in the growing commoditization of e-commercial services. The high accuracy of predictions rendered by Recommendation System (RS) technologies has strengthened the opportunities for experience-oriented offerings, making RS application an effective way of assisting consumers in online decision-making. This ...

One of the modern pillars of collaborative filtering and recommender systems is collection and exploitation of ratings from users. Likert scale is a psychometric quantifier of ratings popular among the electronic commerce sites. In this paper, we consider the tasks of collecting Likert scale ratings of items and of finding the n-k best-rated items, i.e., the n items that are most likely to be t...

Collaborative ontology engineering enables the creation of large complex ontologies. However, few projects successfully perform such multi-user ontology modeling. This paper gives an overview of ten different ontology engineering projects’ infrastructure, architecture and workflows. It especially focuses on issues regarding collaborative ontology modeling. The survey leads on to a discussion of...