Digital marketing strategy across cultures: Algorithmic bias, local media, MSME performance, Indonesia & Malaysia

Abstract

This study aims to produce a cross-cultural analysis of algorithm bias and local media in Indonesia and Malaysia as a marketing strategy for MSMEs to enhance marketing performance. It examines how algorithmic bias in digital marketing affects cultural relevance in Indonesia and Malaysia. Consumers are more likely to accept and share content with cultural relevance, such as the use of local languages and distinctive symbols. This study employed a quantitative approach and data collection techniques, including questionnaires, interviews, and documentation. Data analysis utilized SEM PLS on 200 MSME consumer respondents in Malaysia and Indonesia, using a simple random sampling technique. The results of this study indicate that marketing strategies that integrate cultural factors, such as local languages, symbols, and traditional values, can increase consumer engagement and the effectiveness of digital marketing. By understanding the local context in depth—including how local media and algorithm bias affect message distribution—marketers can design more adaptive strategies that are responsive to audiences' needs in the digital era. This research contributes theoretical insights and provides practical recommendations for MSMEs to develop more inclusive and culturally effective digital marketing strategies.