Vector Consensus Model

Vector Consensus Model

José M. Monguet (Universitat Politécnica de Catalunya, Spain), Alfredo Gutiérrez (Universitat Politécnica de Catalunya, Spain), Marco Ferruzca (Autonomous Metropolitan University, Spain), Yadira Alatriste (Universitat Politécnica de Catalunya, Spain), Claudia Martínez (Universitat Politécnica de Catalunya, Spain), Carlos Córdoba (Universitat Politécnica de Catalunya, Spain), Joaquín Fernández (Universitat Politécnica de Catalunya, Spain), Teresa Sanguino (Universitat Politécnica de Catalunya, Spain), José Aguilá (Universitat Politécnica de Catalunya, Spain) and Miguel Ramírez (Universitat Politécnica de Catalunya, Spain)
DOI: 10.4018/978-1-4666-1764-3.ch017
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Abstract

Two case studies are presented; the first one is focused on the prioritization of the drivers that motivate a researcher in an innovative group, and the second is dedicated to the assessment of the drivers for the future internet.
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Introduction

To examine the context for taking better decisions is an important task for any kind of organization (Choo, 1996). Overall today when it is more difficult to keep a competitive advantage on the basis of common knowledge and new business models. The aim of a decision process is to reach an agreement by sharing ideas with the intention to take the best decision, and thus to achieve some advantage for an organization.

The decision-making process should include a representative number of members in the organization and its stakeholders, generally if an environmental change is being planned (Lozada & Calantone, 1996).

The aim of this chapter is to present a model of consensus decision making, denominated Vector Consensus1, for helping organizations to manage a consensus decision-making process based on a diagnosis and discussion approach of current, and idealized future scenario of a specific topic of interest. The model incorporates a mechanism that allows comparing the personal opinion to the average group’s opinion.

The Consensus Process may focus on different aspects of the topic of study. Once identified the drivers or aspects that are going to be evaluated, the attention may be put in many different matters, from how well the things go today, to which is the risks in the future for a particular item, of not to be considered properly.

In the first case the focus is dedicated to prioritize the topics evaluated with the aim of taking decisions about where to start actions. The model is presented within the dynamic context of an innovation community, so group of participants are the researchers of that community. A prototype of such consensus support system in which members provide their opinion in relation to some drivers that support and encourage their organization has been implemented. In such a way, we provide a new consensus framework which can be applied to support web-based consensus and decision processes in different drivers: motivation, cooperation, collaboration, etc.

The second case study is applied to the evaluation of future internet by a representative group of experts of the internet community. The drivers that influence the evolution of internet in the future are put under the assessment of the experts, with the intention of determining a shared scenario for the internet of the future. The goal is to get an agreement about the relevance of a selected group of “drivers” and to agree about the existing risk that these drivers are not correctly managed by the internet community.

Sometimes there are decisions situations in which the members’ ideas cannot be put in common and thus the uses of a consensus decision-making approach is necessary (Pérez, Cabrerizo, & Herrera-Viedma, 2011). But, even when the consensus idea is popular as a way to take decisions, sometimes it is hard for organizations to build a consistent and efficient consensus model (Butler & Rothstein, 2001).

A good consensus process can support the elements that drive effective decisions (Yeager & Sommer, 2010). For example:

  • By helping members to clarify themselves about their position in the organization they belong to.

  • To clarify the role that each member must play in his or her job.

  • To build a common language.

  • To build a shared decision-making process.

On the other hand, we believe that in many domains the activities of an organization are already open and distributed and those who can stimulate and support this kind of collaboration to leverage their local and dispersed resources will have more chances to succeed (Hansen & Nohria 2004). This is the case of collaborative innovation communities like: research groups, living labs or multinational organizations.

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