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Although most of the literature supports the existence of a substitutive relationship between exploration and exploitation, some authors suggest that this relationship is complementary (ambidexterity), and others argue that there is no relationship. This paper aims to introduce organizational innovation into the analysis and discusses which of these three relationships prevails.

Analyses were performed using data from Spanish Technological Innovation Panel for the period 2008-2013. It should be emphasized that the use of panel data is essential in the analysis of the interaction of exploration and exploitation, as exploration only makes sense in the long run. Econometric strategy uses a two-stage selection model, estimated using the Wooldridge’s (1995) consistent estimator for panel data with sample selection. To perform the test, the hypothesis uses the approach of complementarity.

The results show that the relationships exploration-organizational innovation and exploitation-organizational innovation are complementary, provided that the analysis is performed on companies that simultaneously carry out exploration and exploitation activities, respectively. This indicates that the achievement of ambidexterity is strongly conditioned by the simultaneous realization of organizational innovations.

Managers and policymakers should be aware that the simultaneous implementation of exploration and exploitation yields better results when the corresponding organizational innovations are also implemented.

This paper extends the empirical investigation of the relationship between exploration and exploitation, seen in conjunction with organizational innovation, and using the complementarity approach as a research tool.

The purpose of this study is to construct the first short-term financial distress prediction model for the Spanish banking sector.

The concept of financial distress covers a range of different types of financial problems, in addition to bankruptcy, which is not common in the sector. The methodology used to predict financial problems was artificial neural networks using traditional financial variables according to the capital, assets, management, earnings, liquidity and sensibility system, as well as a series of macroeconomic variables, the impact of which has been proven in a number of studies.

The results obtained show that artificial neural networks are a highly suitable method for studying financial distress in Spanish credit institutions and for predicting all cases in which an entity has short-term financial problems.

This is the first work that tries to build a model of artificial neural networks to predict the financial distress in the Spanish banking system, grouping under the concept of financial distress, apart from bankruptcy, other financial problems that affect the viability of these entities.

The main purpose of this review is to enhance the understanding of intellectual structure and outlook of management innovation research as an interesting and growing research field.

This systematic literature review examines the question, what is the relationship of management innovation with the performance of companies and with other types of innovation? The work also pursues to summarize theories, contexts, characteristics of the papers and methodologies with the purpose of facilitating further development and opportunities and priorities for future research.

The results suggest that management innovation is an interesting and growing research field; in its relation to different types of innovation and performance, it is a field explored with theoretical approaches, contexts and methodologies that begin to form a consolidated body of knowledge. However, through a critical analysis, this review highlights the gaps in the literature and provides suggestions for future studies to further explore the field. This revision contributes to the literature on management innovation summarizing the findings and contributions of research published in the field and its relationships with innovation and performance. It then identifies three comprehensive research streams, namely, future research on conceptualization, definitions and measurements; research on the level of analysis; and future research on management innovation drivers, antecedents and use as mediator/moderator variables.

Management innovation is an emerging research field that is characterized as a branch of research long ignored by more orthodox lines dedicated to technological innovation and topics in product and service development research.