ABSTRACT
This study used a panel cointegration approach to investigate the effect of retail infrastructure/facilities on tourism demand in the casino gaming destination, Macao, from 23 provinces (and municipalities) of mainland China. Numbers of retail outlets in general and retail establishments in integrated resorts (IRs) are used as proxies for retail infrastructure/facilities. Dynamic Ordinary Least Square (DOLS) estimations reveal that a positive long-run relationship exists between tourism demand and retail from both dimensions. Heterogeneous results on the individual province estimates suggest visitors from the emerging central and western regions of China respond more strongly to retail facilities than the more saturated southern and eastern regions. The bidirectional causality between retail infrastructure and tourism demand also validates a positive cycle in the long-term growth of the destination. The results suggest that casino gaming destinations should seek to diversify entertainment and capitalize on the competitive advantage of their non-gaming facilities to sustain long-term development.
摘要
本研究采用面板协整方法分析零售基础设施对中国大陆 23 个省 (市) 到博彩旅游目的地澳门的旅游需求之影响。研究以综合度假村 (IR) 内的零售店和一般的零售场所的数量作零售基础设施的代理变数。动态普通最小二乘法 (DOLS) 估计显示, 旅游需求和零售之间存在长期正向关系。各省的异质估计结果表明, 相对于市场成熟度较高的南部和东部地区, 来自新兴的中西部地区的旅客对零售设施的反应较为显著。此外, 零售基础设施和旅游需求之间的双向因果关系也验证了目的地长期增长的正向循环。结果表明, 博彩旅游目的地应寻求休闲娱乐多样化, 并利用其非博彩设施的竞争优势来维持长期发展。
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. In this paper, retail infrastructures / facilities refer to the establishments with physical stores selling non-F&B items. Market stalls and fixed stalls on the street are excluded.
2. The anti-graft campaign started in 2014 and the negative effect was pronounced during 2014-2016. After 2016Q2, Macao’s VIP gaming revenues started to rebound, showing that the negative impact of the policy became less significant.
3. The origin provinces and municipalities include Beijing (BJ), Tianjin (TJ), Hebei (HEB), Shanxi (SX), Inner Mongolia (IM), Liaoning (LN), Jilin (JL), Heilongjiang (HLJ), Shanghai (SH), Jiangsu (JS), Zhejiang (ZJ), Anhui (AH), Fujian (FJ), Jiangxi (JX), Shandong (SD), Henan (HEN), Hubei (HUB), Hunan (HUN), Guangdong (GD), Guangxi (GX), Chongqing (CQ), Sichuan (SC), and Shaanxi (SAX). Arrivals from these origins accounted for around 85% of total visitor arrivals from China in 2019.
4. The quarterly panel data are seasonally adjusted using the menu-driven X-12-ARIMA Seasonal Adjustment method provided in Stata.
Additional information
Notes on contributors
Joey Pek U Sou
Joey Pek U Sou is a lecturer in the Macao Institute for Tourism Studies (IFTM). She is also a Ph.D. candidate in the Department of Economics and Finance at the University of Macao. Her research interests include tourism demand modeling, development economics, and economic impact of tourism destination (E-mail: [email protected]).