Exploring Common Mistakes in Marketing Research Using Interpretive Structural Modeling (ISM)

This study aims to identify and analyze common mistakes in marketing research and provide a comprehensive framework to improve research processes. Common mistakes can significantly affect the quality of research outcomes and ultimately influence managerial decision-making. The research is applied in purpose and descriptive in nature, employing a survey method with a questionnaire as the data collection tool. A three-stage mixed approach was used: first, a systematic review of reputable scientific sources was conducted to identify the main components of common mistakes in marketing research. Next, semi-structured interviews with experts in marketing management and research were conducted to validate and refine these components. Finally, the relationships between the components and their levels of influence were analyzed using interpretive structural modeling (ISM). The findings indicate that ambiguity in problem definition is the most significant factor leading to errors in marketing research. Other factors include errors in selecting the research approach, weaknesses in questionnaire design, failure to conduct pilot studies, and human and non-human errors in data analysis. The final model illustrates the interactions between these components and provides a precise ranking of their impact and dependencies. This study offers a useful tool for researchers and marketing managers to enhance research quality by identifying and preventing common mistakes. Using this model in future projects can lead to better solutions and more reliable results in marketing research.