2018
DOI: 10.15208/beh.2018.36
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Determinants of Chinese demand for tourism in Malaysia

Abstract: Tourism sector in Malaysia has always been one of its focal service industries not only in the past, but in the future as well in which Malaysian government has been focusing on diverting its economic activities from a resource-based to a service-based economy in its new economic model. China, a strongly emerging economy has been ranked as the third main tourist generating country for Malaysia since 2012. Hence, this study empirically identifies the macroeconomic determinants affecting the tourism demand from … Show more

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Cited by 15 publications
(22 citation statements)
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References 26 publications
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“…This is likely because the tourism goods and services in developing countries can better satisfy tourists' demand in terms of price and quality. Puah et al (2014) reported that pricing strategy influences tourist expenditure behavior in Malaysia. In addition, Mbaiwa (2003) claimed that the establishment of tourism facilities, such as wholesale and retail industries, transportation, and camps, is influenced by the development of the tourism industry in the Okavango Delta.…”
Section: Literature Reviewmentioning
confidence: 99%
“…This is likely because the tourism goods and services in developing countries can better satisfy tourists' demand in terms of price and quality. Puah et al (2014) reported that pricing strategy influences tourist expenditure behavior in Malaysia. In addition, Mbaiwa (2003) claimed that the establishment of tourism facilities, such as wholesale and retail industries, transportation, and camps, is influenced by the development of the tourism industry in the Okavango Delta.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Saayman and Botha (2015) adopted the Seasonal Autoregressive Integrated Moving Average (SARIMA) model to forecast tourist arrivals that exhibit seasonality. Furthermore, Lin et al (2015) and Puah et al (2018a) employed an econometric approach and Autoregressive Distributed Lag (ARDL) approach, respectively, to predict China outbound tourism; China is regarded as the largest outbound tourism market that contributes significantly to the global tourism industry. Puah et al (2018b) also employed the Autoregressive Distributed Lag (ARDL) approach that validated the tourism-led-growth hypothesis.…”
Section: Introductionmentioning
confidence: 99%
“…Hence, some tourist travel in groups and the group with which the tourist is travelling affects the individual's spending patterns (Long-Yi & Chen, 2009). Moreover, Puah et al (2018) analysing the tourism determinants by achieving the Auto Regressive Distributed Lag (ARDL) test of co-integration to examine the dynamic association between tourism demand and its determinants. In addition, Puah et al, (2014) found that, there are negative association between tourism demand with both exchange rate and travelling costs whereas there the real income and trade openness had positively affect tourism demand.…”
Section: Significant Of Tourismmentioning
confidence: 99%
“…Moreover, Puah et al (2018) analysing the tourism determinants by achieving the Auto Regressive Distributed Lag (ARDL) test of co-integration to examine the dynamic association between tourism demand and its determinants. In addition, Puah et al, (2014) found that, there are negative association between tourism demand with both exchange rate and travelling costs whereas there the real income and trade openness had positively affect tourism demand. Study achieved by Albaladejo and González-Martínez (2018), using, the nonlinear dynamic econometric model and further advanced to form the standard dynamic equation in order to estimate the tourism demand and effects between previous tourists and quality of tourism services and congestion.…”
Section: Significant Of Tourismmentioning
confidence: 99%