The determinants of the quality of Sales-Marketing Interface in a Multinational Customer Brand Focused Company: The Latin American Branches

Customer evolution and changes in consumers, determine the fact that the quality of the interface between marketing and sales may represent a true competitive advantage for the firm. Building on multidimensional theoretical and empirical models developed in Europe and on social network analysis, the organizational interface between the marketing and sales departments of a multinational high-growth company with operations in Argentina, Uruguay and Paraguay is studied. Both, attitudinal and social network measures of information exchange are used to make operational the nature and quality of the interface and its impact on performance. Results show the existence of a positive relationship of formalization, joint planning, teamwork, trust and information transfer on interface quality, as well as a positive relationship between interface quality and business performance. We conclude that efficient design and organizational management of the exchange network are essential for the successful performance of consumer goods companies that seek to develop distinctive capabilities to adapt to markets that experience vertiginous change

Detecting Real-World Influence Through Twitter

In this paper, we investigate the issue of detecting the real-life influence of people based on their Twitter account. We propose an overview of common Twitter features used to characterize such accounts and their activity, and show that these are inefficient in this context. In particular, retweets and followers numbers, and Klout score are not relevant to our analysis. We thus propose several Machine Learning approaches based on Natural Language Processing and Social Network Analysis to label Twitter users as Influencers or not. We also rank them according to a predicted influence level. Our proposals are evaluated over the CLEF RepLab 2014 dataset, and outmatch state-of-the-art ranking methods.Comment: 2nd European Network Intelligence Conference (ENIC), Sep 2015, Karlskrona, Swede

WHY DO RESEARCHERS COLLABORATE WITH INDUSTRY? AN ANALYSIS OF THE WINE SECTOR IN CHILE, SOUTH AFRICA AND ITALY

This paper explores the determinants of the linkages between industry and research organizations – including universities. We present new evidence on three wine producing areas – Piedmont, a region of Italy, Chile, South Africa - that have successfully reacted to the recent structural changes experienced in the industry worldwide. Based on an original data-set, we carry out an econometric exercise to study the microeconomic determinants of researchers' collaborations with industry. The evidence reveals that individual researcher characteristics, such as embeddedness in the academic system, age and sex, matter more than their publishing record or formal degrees.University-Industry Linkages, Innovation System, Wine Sector, Emerging Economies

A review on trust propagation and opinion dynamics in social networks and group decision making frameworks

On-line platforms foster the communication capabilities of the Internet to develop large- scale influence networks in which the quality of the interactions can be evaluated based on trust and reputation. So far, this technology is well known for building trust and harness- ing cooperation in on-line marketplaces, such as Amazon (www.amazon.com) and eBay (www.ebay.es). However, these mechanisms are poised to have a broader impact on a wide range of scenarios, from large scale decision making procedures, such as the ones implied in e-democracy, to trust based recommendations on e-health context or influence and per- formance assessment in e-marketing and e-learning systems. This contribution surveys the progress in understanding the new possibilities and challenges that trust and reputation systems pose. To do so, it discusses trust, reputation and influence which are important measures in networked based communication mechanisms to support the worthiness of information, products, services opinions and recommendations. The existent mechanisms to estimate and propagate trust and reputation, in distributed networked scenarios, and how these measures can be integrated in decision making to reach consensus among the agents are analysed. Furthermore, it also provides an overview of the relevant work in opinion dynamics and influence assessment, as part of social networks. Finally, it identi- fies challenges and research opportunities on how the so called trust based network can be leveraged as an influence measure to foster decision making processes and recommen- dation mechanisms in complex social networks scenarios with uncertain knowledge, like the mentioned in e-health and e-marketing frameworks.The authors acknowledge the financial support from the EU project H2020-MSCA-IF-2016-DeciTrustNET-746398, FEDER funds provided in the National Spanish project TIN2016-75850-P , and the support of the RUDN University Program 5-100 (Russian Federation)

A Computational Model to Evaluate Honesty in Social Internet of Things

Trust in Social Internet of Things has allowed to open new horizons in collaborative networking, particularly by allowing objects to communicate with their service providers, based on their relationships analogy to human world. However, strengthening trust is a challenging task as it involves identifying several influential factors in each domain of social-cyber-physical systems in order to build a reliable system. In this paper, we address the issue of understanding and evaluating honesty that is an important trust metric in trustworthiness evaluation process in social networks. First, we identify and define several trust attributes, which affect directly to the honesty. Then, a subjective computational model is derived based on experiences of objects and opinions from friendly objects with respect to identified attributes. Based on the outputs of this model a final honest level is predicted using regression analysis. Finally, the effectiveness of our model is tested using simulations

A taxonomy of innovation networks

In this discussion paper we develop a theory-based typology of innovation networks with a special focus on public-private collaboration. This taxonomy is theoretically based on the concept of life cycles which is transferred to the context of innovation networks as well as on the mode of network formation which can occur either spontaneous or planned. The taxonomy distinguishes six different types of networks and incorporates two plausible alternative developments that eventually lead to a similar network structure of the two types of networks. From this, important conclusions and recommendations for network actors and policy makers are drawn. --

Network dynamics in regional clusters: The perspective of an emerging economy

Regional clusters are spatial agglomerations of firms operating in the same or connected industries, which enable innovation and economic performance for firms. A wealth of empirical literature shows that one of key elements of the success of regional clusters is that they facilitate the formation of local inter-organizational networks, which act as conduits of knowledge and innovation. While most studies analyze the benefits and characteristics of regional cluster networks and focus on advanced economies and high tech Ôhot spotsÕ, this paper advances with the existing literature by analyzing network dynamics and taking an emerging economyÕs perspective. Using longitudinal data of a wine cluster in Chile and stochastic actor-oriented models for network dynamics, this paper examines what micro-level effects influence the formation of new knowledge ties among wineries. It finds that the coexistence of cohesion effects (reciprocity and transitivity) and the presence of inter-firm knowledge base heterogeneity contribute to the stability of an informal hierarchical network structure over time. Empirical results have interesting implications for cluster competitiveness and network studies, and for the burgeoning literature on corporate behavior in emerging economies.Regional clusters, knowledge networks, network dynamics, wine industry, Chile