Tourism Sustainable Competitiveness Indicator in Malaysia: Construct and Forecasting Ability - Ann Ni, Soh (Universiti Malaysia Sarawak (UNIMAS), 2023)
This study constructed the Tourism Sustainable Competitiveness Indicator (TSCI) to assess the vulnerability of the tourism market in Malaysia and its forecasting ability. The study has been motivated by a growing importance of sustainable tourism practices and the need for accurate indicators to measure both sustainability and competitiveness. The constructed TSCI comprises five main dimensions including human capital, market conditions, policy environment and enabling conditions, physical environment, and technology and innovation. The core framework of the constructed TSCI was selected based on a rigorous variable importance assessment using random forest algorithm. Each dimension has an indicator to represent various aspects of sustainable competitiveness in tourism. A total of nine individual indicators with leading attributes was established with an overall accuracy of 81.65 percent in prediction. The selected indicators comprised employment in travel and tourism sector, new business, capital investments in travel and tourism sector, government debt, total natural resources rents, energy use per capita, carbon dioxide emissions, individuals using the internet and trademarks. Markov switching regression was done to establish the relationships between the identified variables and Malaysian tourism demand. Empirical estimation revealed that all nine selected variables were found to be statistically significant at a 5 percent significance level for both contraction and expansion regimes, proving that the selected indicators significantly impacted Malaysian tourism. The aggregation of the nine individual indicators was determined using two indicator construction approaches: the arithmetic-based approach and the dynamic approximate factor model (DAFM) approach. Both successfully dated more than ten tourism vulnerabilities within two decades since 2000 for the Malaysian tourism cycle, addressing economic crises, environmental crises, societal and political crises, health-related crises, and technological crises. The constructed TSCI was tested for its forecasting ability using actual tourism performance as benchmark, to assess the accuracy, sensitivity, and specificity of both the constructed TSCIs. Findings indicate than both are robust indicators to assess tourism sustainable competitiveness in Malaysia, with the DAFM approach achieving a higher accuracy rate of 82.94 percent compared to the arithmetic-based approach which scored 77.38 percent. The Multivariate Diebold-Mariano forecasting evaluation analysis was done to further evaluate and compare the forecasting ability of both TSCIs, before proceeding to the wavelet coherence analysis. The same finding was validated when five out of seven forecasting evaluation criteria, which had lower values, favoured the TSCI constructed using the DAFM approach. The wavelet coherence analysis revealed that the constructed TSCI plays a leading role towards tourism market and economic development in Malaysia. The findings contribute to the concept of sustainable competitiveness, offering valuable insights for decision-making and strategy formulation in the tourism sector. This can assist policymakers, tourism stakeholders and authorities to make informed decisions, formulate strategies, and monitor risks to enhance competitive and sustainable tourism practices.