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This study aims to investigate the impact of new technologies on parameters of organizational behavior and evaluate their determining role of technology maturity and readiness of staff in the digital readiness.

This study has obtained an integrated model of technology’s effect on staff’s organizational behavior considering digital readiness level by using system dynamics is developed. In this model, the effects of new technologies entry on organizational behavior variables are analyzed in different layers, and the result of this impact on the consequent of a bank organizational behavior and each indicator is examined separately in different scenarios. In determining the indicators and their significant coefficients, the viewpoints of banking experts and professionals in organizational behavior have been considered.

As a result of our surveys, five technology effects, without intermediaries, were obtained, which are automation, learning, streamlining repetitive jobs, addiction to technology and reducing face-to-face contact. Each of these factors would make a chain of side effects. In a way that, ultimately, their positive or negative effects on productivity and consequently on organization profits appear. The result indicates technology has effects on important behavioral factors such as stress, motivation, organization values and personal satisfaction. Indicators, which are formed by positive or negative factors, are being upgraded or downgraded. Therefore, managing negative cycles and developing positive cycles can be considered as one of the major banking concerns for controlling IT effects on its organizational behavior of human resources.

There is little academic remarkable literature on clarifying the effects of digitalization on employee's behavior in an organization, this research offers managers and organizations a model of influential factors that need to be taken into account by managers when they encounter new technologies. This study’s proposed analysis is useful to improve the efficiency and productivity of the organization, and alongside this, it is effective for the digital transformation process. This study fills previous research gaps in the academic context related to the practical studies that relied on digital maturity.

Resilience as a novel concept has attracted the most attention in the management of engineering systems. The main goal of engineering systems is production assurance and increasing customer satisfaction which depends on the suitable performance of mechanical equipment. “A resilient system is defined as a system that is resistant to disruption and failures and can recover itself and returns to the state before failure as soon as possible in the case of failure.” Estimate the value of the system’s resilience to increase its resilience by covering the weakness in the resilience indexes of the system.

In this article, a suitable approach to estimating resilience in complex engineering systems management in the field of mining has been presented. Accordingly, indexes of reliability, maintainability, supportability, efficiency index of prognostics and health management of the system, and ultimately the organization resilience index, have been used to evaluate the system resilience.

The results of applying this approach indicate the value of 80% resilience if the risk factor is considered and 98% if the mentioned factors are ignored. Also, the value of 58% resilience of this organization’s management group indicates the weakness of situational awareness and weakness in the vulnerable points of the organization.

To evaluate the resilience in this article, five indicators of reliability, maintainability, and supportability are used as performance indicators. Also, organization resilience and the prognostic and health management of the system (PHM) are used as management indicators. To achieve more favorable results, the environmental and operational variables governing the system have been used in performance indicators, and expert experts' opinions have been used in management indicators.