Value chain model for Melaka UNESCO World Heritage area : assessing tourists expenditure and local economic benefit - Syakir Amir bin Ab. Rahman (Kulliyyah of Architecture and Environmental Design, International Islamic University Malaysia, 2016)
Tourism is one of the major contributors to the economies of various countries in the world. The sector is characterised, among others, by the influx of international tourists that positively drive the countries' gross domestic products (GDPs) upwards. Unfortunately, the sector has also caused significant negative consequences to host destinations, especially in terms of socio-cultural and environmental aspects. Tourism has been identified to be unsustainable as related activities had maximised the usage of depleting resources, created adverse effects to cultural and natural environment while had been the source of profit making exclusivity of certain elite groups. Researchers believe that a new form of tourism should be developed to promote sustainable use of resources, to protect local cultural and heritage values and to maximize the economic advantages of the local communities. The refocus of tourist development objectives from the mass tourism approach to one that is more sustainable needs to be emphasized. Given its original focus of benefiting the local community from tourism activities through tourists' expenditure, value chain model (VCM) has attracted a significant degree of academic attention. However, to date, there has been little discussion and evidence-based comprehensive studies on VCM of local economic benefits with regards to the Malaysian tourism sector. Therefore, this thesis aims at identifying the economic benefits gained by the local community from tourists' expenditure in Melaka UNESCO World Heritage areas and developing a VCM for this specific locality. A Diary Record Survey has been conducted involving three different groups of selected tourists' accommodation based on star ratings namely 5 and 4 star hotels; 3, 2 and 1 star hotels; and budget hotels. A total of 2100 survey diaries have been distributed, but only 1000 booklets were completed, collected and deemed suited for data analysis purposes. The Chi-squared Automatic Interaction Detection (CHAID) has been used to visually and mathematically model linkages of domestic and international tourists' expenditure (TEL) in five tourism sectors – accommodation, food and beverages, transportation, entertainment and shopping. Afterwards, cross tabulation analysis has been used to model the linkages of local economic (LEL) benefits. Finally, VCM was developed based on these two linkages. The model was subsequently validated by eight government officers and 20 tourism operators from five tourism sectors to assess its reliability and legitimacy. The results revealed that accommodation and shopping have contributed more than proportionately towards local economic benefits. The tourists spent the highest proportion of their ringgits on accommodation (RM50 – RM464) which contributed to 97.7% benefits to the local economy, and less for shopping purposes (RM0 – RM26.50) despite being able to contribute 85.6% to the local economic benefits. On the other hand, entertainment, transportation as well as food and beverages have contributed less towards the local economic benefits. The tourists spent lesser ringgits on transportation (RM22.50 and below) and the least on entertainment (RM0 – RM6.25) which contributed to only 9.2% and 0.2% to the local economy respectively. Relatively, the tourists spent more on food and beverages (RM16 – RM147.50) but further disaggregation has seen that these only contributed to about 9.1% (breakfast), 43.2% (lunch) and 37.1% (dinner) to the local economy. The VCM for Melaka UNESCO World Heritage area is slightly different from other global case studies. The study indicated that heritage attraction pulled different types of tourists with different ways of spending, leading to different degrees of economic impacts to the local community. The VCM is expected to assist the relevant authorities in identifying geographical visitation patterns, respective economic impacts and timely and appropriate decision making.