Recently, the concept of resilience has gained new momentum in organization studies. It is held to be a very promising concept to explain how organizations can survive and thrive amidst adversity or turbulence. However, findings from an earlier review about resilience in the organizational and business context show that, although empirical research on the concept has increased, there is still a need for more clarity in terms of its measurement. The aim of this paper is to present a systematic review of the organizational resilience construct that covers both conceptual and operational issues. We discuss why researchers criticize resilience for being fuzzy and move on to identify and analyse existing literature under the lens of construct development and taxonomies. With this study, we aim to point out conceptual problems for future researchers to address conceptual clarity and to develop a clearer, more parsimonious concept. We conclude with a suggestion about future measurement.
Managers play an important role in creating organizational resilience. In highly volatile and uncertain times they must employ long-term visioning, think in alternatives, and deal with complexity in order to promote organizational resilience capabilities. However, strategic management education has been criticized for not providing significant learning experiences that equip them with those capabilities adequately. It still teaches outdated frameworks that do not meet the needs of today's complex environment and that are not truly considering real problems of strategy. One way to confront these limitations could be a learning intervention that combines a future-oriented strategy framework with a subsequent experiential learning experience. We use a qualitative research design with an experimental character to contrast student groups that were part of a combined learning intervention (a lecture on scenario planning and a case study work) with student groups that only took part in the case study work. Our video-based analysis shows that the first are consistently superior in terms of the strategy process (structure and outcome), performance outcomes (accuracy, plausibility, creativity, and
The purpose of this paper is to investigate the influence of national culture on organizational resilience, the effects of which are analyzed for companies from the North American Free Trade Agreement (NAFTA) region. This paper utilizes an etic approach to study this relationship and has an empirical design with a sample of N = 464. The direct effect of national culture on organizational resilience is investigated. To measure national culture, this paper relies on the dimensions of Hofstede. A multiple regression analysis is applied to answer the hypotheses. Results show that the dimensions of power distance, individualism, uncertainty avoidance, and indulgence have a significant direct effect on an organization’s resilience. This paper confirms the necessity for reflecting upon the importance of national cultures to globally-working organizations. Organizations that are dedicated to proactive development in their organizational resilience must understand the cultural circumstances that might hinder resilience development. Indeed, cultural influences play a significant role in human resource trainings, choices of location, leadership styles, and managing stakeholders and external alliances to improve organizational resilience. This paper is the first to quantitatively study the relationship of national culture on organizational resilience.
Understanding the way stimulus properties are encoded in the nerve cell responses of sensory organs is one of the fundamental scientific questions in neurosciences. Different neuronal coding hypotheses can be compared by use of an inverse procedure called stimulus reconstruction. Here, based on different attributes of experimentally recorded neuronal responses, the values of certain stimulus properties are estimated by statistical classification methods. Comparison of stimulus reconstruction results then allows to draw conclusions about relative importance of covariate features. Since many stimulus properties have a natural order and can therefore be considered as ordinal, we introduce a bivariate ordinal probit model to obtain classifications for the combination of light intensity and velocity of a visual dot pattern based on different covariates extracted from recorded spike trains. For parameter estimation, we develop a Bayesian Gibbs sampler and incorporate penalized splines to model nonlinear effects. We compare the classification performance of different individual cell covariates and simple features of groups of neurons and find that the combination of at least two covariates increases the classification performance significantly. Furthermore, we obtain a non-linear effect for the first spike latency. The model is compared to a naïve Bayesian stimulus estimation method where it yields comparable misclassification rates for the given dataset. Hence, the bivariate ordinal probit model is shown to be a helpful tool for stimulus reconstruction particularly thanks to its flexibility with respect to the number of covariates as well as their scale and effect type.
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