Strategic Orientations, Dynamic Capabilities, and Firm Performance: an Analysis for Knowledge Intensive Business Services

The strategic orientations of a firm are considered crucial for enhancing firm performance and their impact can be even greater when associated with dynamic capabilities, particularly in complex and dynamic environments. This study empirically analyzes the relationship between market, entrepreneurial and learning orientations, dynamic capabilities, and performance using an integrative approach hitherto little explored. Using a sample of 209 knowledge intensive business service firms, this paper applies structural equation modeling to explore both direct effects of strategic orientations and the mediating role of dynamic capabilities on performance. The study demonstrates that learning orientation and one of the dimensions of entrepreneurial orientation have a direct positive effect on performance. On the other hand, dynamic capabilities mediate the relationships between some of the strategic orientations and firm performance. Overall, when dynamic capabilities are combined with the appropriate strategic orientations, they enhance firm performance. This paper contributes to a better understanding of the knowledge economy, given the important role knowledge intensive business services play in such a dynamic and pivotal sector.

A Case Based approach to assess Waiting Time Prediction at an Intensive Care Unity

Waiting time at an intensive care unity stands for a key feature in the assessment of healthcare quality. Nevertheless, its estimation is a difficult task, not only due to the different factors with intricate relations among them, but also with respect to the available data, which may be incomplete, self-contradictory or even unknown. However, its prediction not only improves the patients’ satisfaction but also enhance the quality of the healthcare being provided. To fulfill this goal, this work aims at the development of a decision support system that allows one to predict how long a patient should remain at an emergency unit, having into consideration all the remarks that were just stated above. It is built on top of a Logic Programming approach to knowledge representation and reasoning, complemented with a Case Base approach to computing.

Length of Stay in Intensive Care Units - A Case Base Evaluation

As a matter of fact, an Intensive Care Unit (ICU) stands for a hospital facility where patients require close observation and monitoring. Indeed, predicting Length-of-Stay (LoS) at ICUs is essential not only to provide them with improved Quality-of-Care, but also to help the hospital management to cope with hospital resources. Therefore, in this work one`s aim is to present an Artificial Intelligence based Decision Support System to assist on the prediction of LoS at ICUs, which will be centered on a formal framework based on a Logic Programming acquaintance for knowledge representation and reasoning, complemented with a Case Based approach to computing, and able to handle unknown, incomplete, or even contradictory data, information or knowledge.

Organizational Cooperation and Knowledge Management in Research and Development Organizations

Organizational Cooperation (OC) is a current concept that responds to the growing interdependence among individuals and teams. Likewise, Knowledge Management (KM) accompanies specialization in all sectors of human activity. Most KM processes are cooperation-intensive, and the way both constructs relate to each other is relevant in understanding organizations and promoting performance. The present paper focuses on that relationship. The Organizational Cooperation Questionnaire (ORCOQ) and the Short form of the Knowledge Management Questionnaire (KMQ-SF) were applied to 639 members of research and development (R&D) organizations (Universities and Research Institutes). Descriptive, correlational, linear multiple regression and multivariate multiple regression analyses were performed. Results showed significant positive relationships between the ORCOQ and all the KMQ-SF dimensions. The prediction of KMQ-SF showed a large effect size (R2 = 62%). These findings will impact on how KM and OC are seen, and will be a step forward in the development of this field.