Extended Abstract
Introduction: As one of the fundamental determinants of economic growth, the business environment is shaped by a set of institutional, legal, infrastructural, and policy-related variables, and its quality plays a decisive role in attracting investment, fostering industrial development, and generating employment across various economic sectors. Despite its abundant natural and human resources, Kohgiluyeh and Boyer-Ahmad Province has persistently faced structural challenges in improving its business environment. The present study was conducted with the aim of investigating, identifying, and ranking the most significant barriers to the business environment in this province and offering policy recommendations.
Methods: This study is applied in purpose and descriptive–survey in nature, employing a quantitative approach. The statistical population comprised economic actors, investors, experts, managers associated with the business environment, and provincial residents. Stratified random sampling was applied, and the sample size was estimated at 384 based on Cochran’s formula. More than 450 questionnaires were distributed, 390 were returned, and after screening, 359 valid questionnaires formed the basis of the analysis. Content validity was assessed by ten experts across 62 items structured within seven factors, yielding a Content Validity Index (CVI) of 0.793. In the pilot study, Cronbach’s alpha was 0.705, based on data from 30 respondents. A Kaiser-Meyer-Olkin (KMO) index of 0.902 and a significant Bartlett’s test confirmed the adequacy of the data. Data analysis was performed using descriptive statistics, the Friedman test, multiple regression, and Partial Least Squares Structural Equation Modeling (PLS-SEM).
Findings: The Friedman test established the following perceived priority ranking of barriers: educational and health barriers (mean rank = 5.89), commercial and financial (5.62), macroeconomic (5.34), innovation and technology (5.08), institutional (4.41), provincial and regional (3.27), and infrastructural (2.39). In contrast, the PLS-SEM structural model revealed a different pattern; institutional barriers (β = 0.552) and provincial and regional barriers (β = 0.537) emerged as the strongest predictors, whereas the other dimensions exhibited more limited effects. Overall, the model explained 0.614 of the variance, indicating a “moderate-to-high” explanatory power.
Conclusion: The principal finding of this study is the gap between “perceived priority” and “actual structural effect”: institutional and provincial and regional barriers, which rank low in the perceptions of economic actors, are in practice the most decisive constraints on the business environment at the provincial level in Kohgiluyeh and Boyer-Ahmad. This gap can be explained by the gradual normalization and internalization of institutional barriers. Accordingly, the priority of policy reforms should focus on reconstructing inadequate institutional, provincial, and regional structures and strengthening provincial governance capacity, accompanied by awareness-raising programs for economic actors, in order to achieve sustainable improvement in the province’s business environment.
Keywords: Business Environment, Institutional Barriers, Provincial and Regional Barriers