Gerardo Gabriel Alfaro Calderón

A fuzzy methodology for innovation management measurement

Purpose Innovation has been recognized as one of the main sources of competitive advantage for organizations and nations. The purpose of this study is to present an innovation management measurement approach by applying fuzzy techniques to small- and medium-sized manufacturing enterprises. Design/methodology/approach This study presents a survey focusing on seven innovation measurement areas: innovation strategy, knowledge management, project management, portfolio management, internal enablers, organization and structure and external enablers. A total of 91 small- and medium-sized enterprises (SMEs) located in the city of Morelia, Mexico, participated in the study. Furthermore, the data collected were analyzed under a multi-criteria decision-making approach using the theory of expertons and the induced generalized ordered weighted averaging operator. Findings The results show that the most valued areas are innovation strategy, organization and structure, knowledge management and project management. Furthermore, portfolio management, external drivers and internal drivers are the areas with the lowest valuations. Originality/value This paper presents an original methodological structure based on an expertise process designed to achieve well-founded results from uncertain and subjective opinions directly from the managers of the surveyed SMEs.

Hierarchization of Factors Involved in the Failure of Startups

In this research we determine the main factors by which start-ups or startups fail in a period of no more than five years in the city of Morelia Michoacan, using the methodology AHP (Analytical Hierarchical Process), which allows us to establish the level of priority of each of the factors identified in the business failure, a phenomenon that we live on a daily basis in the city, which can be seen worldwide.

A fuzzy approach to a municipality grouping model towards creation of synergies

In recent years, a trend for accelerating the economic, social and environmental development of cities through associations, organization and creation of synergies has been identified. Our investigation applies a grouping model in order to identify municipalities that could create optimal synergies towards the construction of competitive advantages. In order to achieve this task, we use tools of Fuzzy Logic to evaluate subjective and qualitative characteristic elements of different municipalities under Galois’ group theory. Results conclude on 32 different groups ordered in 7 different levels, relating 12 municipalities of a specific region according to 8 competitive variables. This work seeks to shed light in the conformation of groups under uncertain conditions and the deep examination of the characteristic competitive elements in a specific region for further policy and decision-making processes.

Innovation Capabilities Using Fuzzy Logic Systems

In recent decades, innovation has been recognized as one of the main sources of competitive advantage for organizations at an international level. Recently, numerous studies have been developed, mainly focused on the analyses of innovation processes in large companies, however, little has been done in the identification of innovative capabilities that allow small and medium-sized companies to compete in highly uncertain environments. This study presents the interpreted results of an innovation diagnosis utilizing the Experton method and the application of the generalized ordered weighted average operator (GOWA) for the treatment of information. The focus relies on seven organizational areas of small and medium-sized manufacturing companies. The applied questionnaire presents 32 exploration and 5 control questions applied to a total of 217 small and medium-sized companies in the Latin American city of Morelia, Mexico. The present work seeks to shed light in the diagnosis of innovation capabilities in manufacturing companies with the aim of fostering synergies and effectively allocate resources for the promotion of innovation management as a source of competitiveness and economic growth.

VARIABLES FOSTERING KNOWLEDGE MANAGEMENT CLASSICAL THEORY VS. UNCERTAINTY THEORY

There is a number of variables considered as fostering knowledge management. This set of variables includes organizational culture, leadership of the owner manager, relational assets, and structural assets. This article presents a comparison of the variables considered as fostering knowledge management using classical theory vs. Uncertainty theory, using the linguistic label approach.