Explaining the Interactive Relationships Between Internal Marketing, Organizational Intelligence, and Organizational Innovation in the National Tax Administration

Abstract

In the era of information and advanced technology, organizations must implement innovative and intelligent strategies to maintain competitiveness and enhance their performance. To achieve these objectives, understanding and analyzing the relationships among internal marketing, organizational intelligence, and innovation—as key factors in optimizing organizational performance—are of particular importance. Therefore, the present study aims to explain the interactive relationships between internal marketing, organizational intelligence, and organizational innovation in the National Tax Administration. From a methodological perspective, this study employs a mixed-methods (qualitative and quantitative) approach. The qualitative phase utilizes thematic analysis, while the quantitative phase applies fuzzy Delphi and structural equation modeling (SEM). The statistical population in the qualitative phase consists of university professors and managers of the National Tax Administration. In the quantitative phase, the population includes all employees of the National Tax Administration, employed under contractual, probationary, or permanent official status in various departments. In the quantitative phase, the fuzzy Delphi technique was conducted using a snowball sampling method, selecting 19 experts. To test the model using structural equation modeling, a convenience sampling method was employed. Given that the total statistical population comprises 20,000 individuals, based on Krejcie and Morgan’s table with a 0.05 precision level, a sample size of 377 participants was determined. The thematic analysis process was carried out in six stages following the approach proposed by Braun and Clarke (2006). The findings identified two sub-themes and 13 base themes for internal marketing, two sub-themes and 10 base themes for open innovation, and two sub-themes and 11 base themes for organizational intelligence. After identifying and screening the indicators of internal marketing, organizational innovation, and organizational intelligence, these factors were categorized into clusters. Structural equation modeling (SEM) was used to test and evaluate the validity and reliability of the relationships. Additionally, interpretive structural modeling (ISM) was employed to determine the interactive relationships among the variables.