The influence of event attributes on sport tourism destinations in Peninsular Malaysia: a preliminary study

Sport tourism is widely recognised as an effective, low-cost method for marketing locations and cultures. Malaysia increased its position in this area in 2023 by hosting major sporting events, boosting its reputation as a sports tourist and holiday destination. However, research frequently fails to focus on the diverse and context-specific nature of event attributes, particularly in non-Western settings. This study fills that vacuum by investigating how event attributes influence tourist perceptions, visit intentions, and return likelihood in Peninsular Malaysia. To further understand these patterns, a literature review was conducted and observed from the perspective of Tourism Destination Competitiveness (TDC) Theory. This quantitative study uses a positivist research paradigm. The study's unit of analysis concentrates on spectators among sport tourists attending sporting events in Peninsular Malaysia, such as CMAS 1st Intercontinental Championship Asia/ Oceania Underwater Hockey, Beneunder Pickleball Championship and Le Tour de Langkawi (LTDL). To eliminate answer biases, data was collected using a standardised questionnaire divided into nine sections, with the majority of subjective items including 6-point Likert scale replies. A non-probability purposive sampling strategy was used to select respondents based on their relevant experiences. The sample size for the primary study was determined to be 129 respondents using G*Power analysis, which ensured adequate statistical power and precision. Prior to the main data gathering, a pilot test with 41 responders was held at the MotoGP Sepang Circuit in November 2024. The pilot test included reliability analyses using Cronbach's Alpha, which revealed good to excellent internal consistency for all measurement scales (Sport Tourism Destination, Event Promotion, Event Quality, Event Satisfaction, and Event Attachment), with values ranging from 0.836 to 0.929. This outcome demonstrates the instrument's dependability and high data quality. The data analysis for the pilot test was performed using IBM SPSS Statistics Version 30.0.