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PurposeAmbidexterity refers to the tension between two different business models within the same organisation. This paper examines the significance of individuals' knowledge exploration and exploitation activities in an organisation's ambidexterity context, along with how they affect the creation of an affective commitment in the workforce. The study then investigates how an organisation's ambidexterity vision contributes to employees' affective commitment to learning.Design/methodology/approachThese relationships are examined through an empirical investigation of 219 employees in the financial sector, using structural equation modelling validated by factor analysis.FindingsThe results indicate that for a firm to successfully achieve ambidexterity, its managers need to explicitly work to nurture a context where explorative and exploitative activities take place simultaneously. Another relevant contribution of this study has been addressing the impact that explorative and exploitative activities may have on affective commitment. The results suggest that while the effect of the ambidexterity context on the affective commitment by way of explorative activities is statistically insignificant, the effects of exploitative activities on affective commitment are statistically significant.Originality/valueWhile the extant literature provides useful insights into the relationship between contextual ambidexterity and organisational performance, the relationship between ambidexterity and affective commitment has been less researched. This study has shown that an ambidexterity context is a key component in the process of combining knowledge structures in ways which are appropriate for both exploring value of that knowledge for the company and being effective in exploiting its memory.

La violencia contra las mujeres en el contexto de pareja constituye una grave problemática social de carácter estructural que se ha mantenido a través del tiempo y que implica profundas vulneraciones a los Derechos Humanos. Con el objetivo de develar las distintas formas en que se manifiestan las violencias dentro de las relaciones de pareja, se recolectaron 1.168 frases sobre las mismas en 41 baños de una institución universitaria. Estas manifestaciones se clasificaron cualitativamente según las diversas tipologías de violencia (física, psicológica, sexual, y económica) y, mediante un análisis crítico y hermenéutico desde los postulados de la Perspectiva de Género y la Perspectiva de Derechos, se logró hallar que la violencia de pareja se sustenta en estereotipos de género, se oculta tras diversas formas, se justifica mediante patrones culturales hetero-patriarcales y se encuentra profundamente arraigada y normalizada dentro de la cultura, a tal punto que vulneran Derechos Humanos expresamente protegidos por la ley.

AbstractWe investigate the relationship between entrepreneurial capacities and firm performance. More specifically, we investigate the effects of radical innovation and learning orientation on business performance. We test the effects of entrepreneurial orientation on learning orientation and radical innovation. The results suggest that radical product innovation and companies' orientation to learn have a positive effect on organizational performance. Additionally, we find that entrepreneurial orientation positively influences a firm's capability to learn and innovate. Our findings also show a direct effect of learning orientation on radical innovation, which means that companies with a higher proclivity to learn are more likely to create products and processes, representing a major departure from the state of current knowledge. Copyright © 2014 ASAC. Published by John Wiley & Sons, Ltd.

Automated decision making and predictive analytics through artificial intelligence, in combination with rapid progress in technologies such as sensor technology and robotics are likely to change the way individuals, communities, governments and private actors perceive and respond to climate and ecological change. Methods based on various forms of artificial intelligence are already today being applied in a number of research fields related to climate change and environmental monitoring. Investments into applications of these technologies in agriculture, forestry and the extraction of marine resources also seem to be increasing rapidly. Despite a growing interest in, and deployment of AI-technologies in domains critical for sustainability, few have explored possible systemic risks in depth. This article offers a global overview of the progress of such technologies in sectors with high impact potential for sustainability like farming, forestry and the extraction of marine resources. We also identify possible systemic risks in these domains including a) algorithmic bias and allocative harms; b) unequal access and benefits; c) cascading failures and external disruptions, and d) trade-offs between efficiency and resilience. We explore these emerging risks, identify critical questions, and discuss the limitations of current governance mechanisms in addressing AI sustainability risks in these sectors.