a framework for Business Processes Management based on the concept of "edge of chaos"

This study aims to present a comprehensive model of agility in business process management by using the concept of "edge of chaos, " which is attempted through interviews with 18 experts. The effective components in the framework of agile organizational process management were identified so that in a complex and dynamic environment, in order to achieve agility in process management, the balance between the internal order of process management and the disorder caused by environmental dynamics can be maintained. After analyzing the findings and extracting primary codes (273 open codes), central codes (17 codes), and five selective codes with a reliability coefficient of 77.77, a conceptual model modeled on Strauss and Corbin's paradigm was drawn.Introduction Today, concepts related to the science of complexity and the edge of chaos have become essential to modern management's vocabulary of theory and practice. The edge of chaos is a space where freedom of action and dynamism are combined with order and stability, the output of which will be accompanied by creativity and innovation. Therefore, the management of agile processes based on chaos theory can be considered a framework for managing organizational processes, which, in addition to maintaining the benefits of formalization and standardization of processes, also enables the adaptability of processes and their agility in general. This research seeks to model this new look and attitude in process-oriented organizations looking for agility in complex work environments.Materials and Methods This study is a type of developmental research that follows interpretative philosophical foundations and an analytical, inductive approach and seeks to model data through qualitative strategies and interviews with 18 experts, who were selected using a non-random method and a snowball technique and considering that the nature of the proposed model will be used to solve a problem in process organizations, its orientation is practical.Discussion and Results The Results showed that the causal conditions of the model include appropriate culture, process governance, competent human resources, technological infrastructure, and environmental understanding and recognition. Intervening factors include continuous control and monitoring of processes, leadership characteristics, and platforms, including Strategizing based on improvisation, structure and organization, creative stability on the border of chaos, dynamic adaptation, organizational learning and strategies required in the model, quality management of processes, integration of knowledge management with organization processes and efficiency of life cycle components include, their use will aim for the improvement of quantitative and qualitative performance indicators.ConclusionsAccording to the existing research gap, to deal with the concept of managing agile business processes in complex environments, there is a need for a comprehensive and systematic look at managing agile organizational processes to help organizations deal with complex issues in chaotic border environments. For this purpose, a framework can be designed: First, in order to achieve agility in the management of organizational processes (a central category), the existence of primary conditions, including suitable culture, process governance, competent human resources, technological infrastructure, and environmental understanding and Intervening factors include: continuous control and monitoring of processes and leadership, in contexts and conditions including strategy-making based on improvisation, structure and organization, creative stability on the border of chaos, dynamic adaptation, organizational learning and through management strategies The quality of the processes is the integration of knowledge management with the organization processes and the optimization of the life cycle components, which will ultimately lead to attention to these issues, the promotion and improvement of quantitative and qualitative performance indicators