Relational Capital and Open Innovation： Two Cases of Successful Italian Companies

Praxis and doctrine agree on the importance of innovation for the competitiveness and profitability of the firm. Innovation is considered as a leverage to start a virtuous circle that improves company performance and, consequently, reduce financial constraints for its development. Being creative is definitely the first mechanism that leads to innovation. Creativity spreads from both the individuals that work in the firm and from the social processes and contextual factors that characterize individual relationships within the company. Relational capital is the second mechanism that brings innovation. Relationships with clients, suppliers, competitors, producers of complementary products, public and private research institutions provide creative elements that, once screened, give rise to innovation. The first mechanism requires the firm to be creative on its own as innovations come directly from within the organization （＂closed innovation＂ model）. In the second, the firm must get in touch with potentially innovative idea~ coming from outside （＂open innovation＂ model）. Doctrine and praxis point out that firms, which do not stop at the first mechanism of innovation, turn out to be more innovative. The paper is structured as follows. In the first part, a theoretical framework is provided, describing the main findings, in the literature, in terms of relationships among innovation, creativity and relational capital. The second part is based on the analysis of two case studies. The first case （Coswell）, the very different degree of success （in terms of generated income） of its products seems to be tightly related on how much ＂relational capital＂ is ＂inside＂ the innovation. In the second case （Pastificio Rana） shows that innovation resulting from relational capital allows the company to excel against its far bigger and financially superior competitors.

Evaluation of employee profiles using a hybrid clustering and optimization model Practical study

Purpose-The purpose of this paper is to introduce an evaluation methodology for employee profiles that will provide feedback to the training decision makers.Employee profiles play a crucial role in the evaluation process to improve the training process performance.This paper focuses on the clustering of the employees based on their profiles into specific categories that represent the employees’characteristics.The employees are classified into following categories:necessary training,required training,and no training.The work may answer the question of how to spend the budget of training for the employees.This investigation presents the use of fuzzy optimization and clustering hybrid model(data mining approaches)as a fuzzy imperialistic competitive algorithm(FICA)and k-means to find the employees’categories and predict their training requirements.Design/methodology/approach-Prior research that served as an impetus for this paper is discussed.The approach is to apply evolutionary algorithms and clustering hybrid model to improve the training decision system directions.Findings-This paper focuses on how to find a good model for the evaluation of employee profiles.The paper introduces the use of artificial intelligence methods(fuzzy optimization(FICA)and clustering techniques(K-means))in management.The suggestion and the recommendations were constructed based on the clustering results that represent the employee profiles and reflect their requirements during the training courses.Finally,the paper proved the ability of fuzzy optimization technique and clustering hybrid model in predicting the employee’s training requirements.Originality/value-This paper evaluates employee profiles based on new directions and expands the implication of clustering view in solving organizational challenges(in TCT for the first time).