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The coronavirus disease (COVID-19) pandemic generated a worldwide financial crisis by impacting several links of the supply chain, however companies can take advantage by quantitatively measuring the disruptive impacts.

This study sought to develop the failure mode and effect analysis and supply chain resilience (FMEA-SCR), a hybrid tool developed using a potential failure mode and effect analysis (FMEA) applied to supply chain resilience (SCR) and taking into account the capability factors and business processes.

In order to validate, the proposed model was applied into two different organizational study cases: an university and a cooperative managing urban solid wastes with recyclable potential (MSWRP). Through the procedures described here any organization can understand and assess in a simplified way the impacts over their supply chain generated by such a crisis.

This study synthesizes three different procedures into a single method called FMEA-SCR, allowing organizations to understand and assess in a simplified way, the impacts over their supply chain generated by COVID-19. To this end, it brought together the studies developed by Rajesh and Ravi (2015) and Curkovic et al. (2015), on possible causes of disruptions in SC, the capability factors of Pettit et al. (2010) used by organizations to mitigate the effects of disruptions, besides Lambert's and Croxton (2005) business processes, thus weaving a method that allows organizations to visualize, analyze and classify the pandemic impacts over their supply chain.

The sound leadership style can be indicative of organizational success and explanatory of quality performance. Besides this, there are various factors that can impact organizational performance. To this end, this study aims to investigate the effect of ethical leadership on organizational performance, with the mediating role of corporate social responsibility (CSR) and organizational culture.

The service sector in Jordan was targeted by this research, and data were collected from 371 middle-level and top-level managers working in service companies. These responses were analyzed by using analysis of a moment structure.

The result conveyed that ethical leadership does not only influence organizational performance, but it also, and positively so, affects the organizational culture and CSR. In addition, CSR and organizational culture significantly mediate the relationship between ethical leadership and organizational performance.

The findings of this study are a guide for managers and owners of service companies who are aiming to enhance organizational performance. If they follow the ethical leadership approach and emphasize CSR initiatives and organizational culture, they can attain, and naturally so, the maximum level of organizational performance.

To the best of the authors’ knowledge, this research paper is the first to analyze ethical leadership in the context of the service sector in Jordan and highlight its influence on organizational culture, CSR and ultimately organizational performance. Moreover, it examined the mediating effects of organizational culture and CSR between ethical leadership and organizational performance.

Optimization algorithms can differ in performance for a specific problem. Hybrid approaches, using this difference, might give a higher performance in many cases. This paper presents a hybrid approach of Genetic Algorithm (GA) and Ant Colony Optimization (ACO) specifically for the Integrated Process Planning and Scheduling (IPPS) problems. GA and ACO have given different performances in different cases of IPPS problems. In some cases, GA has outperformed, and so do ACO in other cases. This hybrid method can be constructed as (I) GA to improve ACO results or (II) ACO to improve GA results. Based on the performances of the algorithm pairs on the given problem scale. This proposed hybrid GA-ACO approach (hAG) runs both GA and ACO simultaneously, and the better performing one is selected as the primary algorithm in the hybrid approach. hAG also avoids convergence by resetting parameters which cause algorithms to converge local optimum points. Moreover, the algorithm can obtain more accurate solutions with avoidance strategy. The new hybrid optimization technique (hAG) merges a GA with a local search strategy based on the interior point method. The efficiency of hAG is demonstrated by solving a constrained multi-objective mathematical test-case. The benchmarking results of the experimental studies with AIS (Artificial Immune System), GA, and ACO indicate that the proposed model has outperformed other non-hybrid algorithms in different scenarios.