Designing an Interpretive Structural Model (ISM) of Digital Transformation Culture Drivers with a Contextual Approach in the Water and Wastewater Company of Tehran Province

Abstract

Today, digital transformation is described as a modern struggle for survival against the threat of digital disruption. Digital transformation is a process through which an organization evolves by experimenting with new technologies, revising its current approaches to problem-solving, and modifying its operational routines. To realize a digital transformation culture, it is essential to thoroughly examine and address the drivers, challenges, and barriers associated with digital disruption, the integration of emerging technologies, and the transformation of traditional work environments, as overcoming these obstacles is necessary for a successful digital transformation. The objective of this study is to design an interpretive structural model (ISM) of digital transformation culture drivers with a contextual approach in the Water and Wastewater Company of Tehran Province. This research is applied in terms of its objective and employs an exploratory mixed-method approach. In the qualitative phase, thematic analysis was utilized, while the quantitative phase employed interpretive structural modeling (ISM). The qualitative research population consisted of 14 experts, who were purposefully selected until data saturation was achieved. In the quantitative phase, a sample of 234 managers was randomly selected. Data collection in the qualitative phase was conducted through semi-structured in-depth interviews, while in the quantitative phase, a researcher-developed questionnaire was used. In the quantitative stage, data analysis was performed using descriptive statistics, confirmatory factor analysis, and interpretive structural modeling (ISM) based on the opinions of 12 experts. After identifying the themes, the model of digital transformation culture drivers was developed, and the relationships between factors were determined using interpretive structural modeling (ISM). Additionally, the factors were analyzed based on their impact and dependency using the MICMAC (Matrice d'Impacts Croisés Multiplication Appliquée à un Classement) diagram. The results indicate that digital competency and digital openness, with the highest influence power, serve as the primary drivers and key barriers to the formation of a digital transformation culture. The linking factors, including inadequate interactions and decision-making, act as inhibiting elements in the system due to their prevalence. The factor of insufficient maturity is located in the autonomous quadrant, while change management is influenced by other factors within the system. Consequently, to establish and enhance a digital transformation culture, it is necessary to review, modify, or eliminate these major barriers, as overcoming them is crucial for successful digital transformation.