Using Slutsky equation to find the hotel growth model in the destination life cycle: an empirical study in Myrtle Beach
Purpose – The purpose of this paper is to examine the hotel growth model including hotel brand, culture and life cycle phases of the Myrtle Beach, South Carolina, the fastest growing tourism destination in the United States. Design/methodology/approach – Culture reflecting consuming behaviour of low...
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Emerald Publishing
2024-06-01
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| Series: | International Hospitality Review |
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| Online Access: | https://www.emerald.com/insight/content/doi/10.1108/IHR-10-2022-0042/full/pdf |
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| author | Xuan V. Tran |
| author_facet | Xuan V. Tran |
| author_sort | Xuan V. Tran |
| collection | DOAJ |
| description | Purpose – The purpose of this paper is to examine the hotel growth model including hotel brand, culture and life cycle phases of the Myrtle Beach, South Carolina, the fastest growing tourism destination in the United States. Design/methodology/approach – Culture reflecting consuming behaviour of low-context innovators and high-context imitators is measured by the price elasticity of demand (PED). Hotel brand reflecting guests’ hotel class is measured by the income elasticity of demand. Autoregressive distributed lag has been conducted on the Smith Travel Research data in 33 years (1989–2022) to determine the relationship among hotel brand, culture and life cycles. Findings – Skilled labour is the key to make hotels grow. Therefore, increase room rates when hotels possess skilled professionals and decrease room rates when hotels have no skilled professionals. During the rejuvenation in Myrtle Beach (1999–2003), hoteliers increased room rates for innovators due to skilled professionals to increase revenue. Otherwise, a decrease in room rates due to lack of skilled professionals would lead to increase revenue. Research limitations/implications – (1) Although Myrtle Beach is one of the fastest growing tourism destinations in the US, it has a relatively small geographic area relative to the country. (2) Data cover over one tourist life cycle, so the time span is relatively short. Hoteliers can forecast the number of guests in different culture by changing room rates. Practical implications – To optimize revenue, hoteliers can select skilled labour in professional design hotel brands which could make an increase in demand for leisure transient guests no matter what room rates increase after COVID-19 pandemic. Social implications – The study has considered the applied ethical processes regarding revenue management that would maximize both revenue and customer satisfaction when it set up an increase in room rates to compensate for professional hotel room design or it decreases room rates for low-income imitators in exploration and development. Originality/value – This research highlights that (1) skilled design in the luxury hotel brand is the key for the hotel growth and (2) there is a steady state of the growth model in the destination life cycle. |
| format | Article |
| id | doaj-art-3e742b75a26f4b43b2d42c8e1f9e1a22 |
| institution | DOAJ |
| issn | 2516-8142 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Emerald Publishing |
| record_format | Article |
| series | International Hospitality Review |
| spelling | doaj-art-3e742b75a26f4b43b2d42c8e1f9e1a222025-08-20T02:51:14ZengEmerald PublishingInternational Hospitality Review2516-81422024-06-0138220522010.1108/IHR-10-2022-0042Using Slutsky equation to find the hotel growth model in the destination life cycle: an empirical study in Myrtle BeachXuan V. Tran0Department of Commerce, University of West Florida, Pensacola, Florida, USAPurpose – The purpose of this paper is to examine the hotel growth model including hotel brand, culture and life cycle phases of the Myrtle Beach, South Carolina, the fastest growing tourism destination in the United States. Design/methodology/approach – Culture reflecting consuming behaviour of low-context innovators and high-context imitators is measured by the price elasticity of demand (PED). Hotel brand reflecting guests’ hotel class is measured by the income elasticity of demand. Autoregressive distributed lag has been conducted on the Smith Travel Research data in 33 years (1989–2022) to determine the relationship among hotel brand, culture and life cycles. Findings – Skilled labour is the key to make hotels grow. Therefore, increase room rates when hotels possess skilled professionals and decrease room rates when hotels have no skilled professionals. During the rejuvenation in Myrtle Beach (1999–2003), hoteliers increased room rates for innovators due to skilled professionals to increase revenue. Otherwise, a decrease in room rates due to lack of skilled professionals would lead to increase revenue. Research limitations/implications – (1) Although Myrtle Beach is one of the fastest growing tourism destinations in the US, it has a relatively small geographic area relative to the country. (2) Data cover over one tourist life cycle, so the time span is relatively short. Hoteliers can forecast the number of guests in different culture by changing room rates. Practical implications – To optimize revenue, hoteliers can select skilled labour in professional design hotel brands which could make an increase in demand for leisure transient guests no matter what room rates increase after COVID-19 pandemic. Social implications – The study has considered the applied ethical processes regarding revenue management that would maximize both revenue and customer satisfaction when it set up an increase in room rates to compensate for professional hotel room design or it decreases room rates for low-income imitators in exploration and development. Originality/value – This research highlights that (1) skilled design in the luxury hotel brand is the key for the hotel growth and (2) there is a steady state of the growth model in the destination life cycle.https://www.emerald.com/insight/content/doi/10.1108/IHR-10-2022-0042/full/pdfDestination life cycleLow-contextHigh-contextMyrtle Beach |
| spellingShingle | Xuan V. Tran Using Slutsky equation to find the hotel growth model in the destination life cycle: an empirical study in Myrtle Beach International Hospitality Review Destination life cycle Low-context High-context Myrtle Beach |
| title | Using Slutsky equation to find the hotel growth model in the destination life cycle: an empirical study in Myrtle Beach |
| title_full | Using Slutsky equation to find the hotel growth model in the destination life cycle: an empirical study in Myrtle Beach |
| title_fullStr | Using Slutsky equation to find the hotel growth model in the destination life cycle: an empirical study in Myrtle Beach |
| title_full_unstemmed | Using Slutsky equation to find the hotel growth model in the destination life cycle: an empirical study in Myrtle Beach |
| title_short | Using Slutsky equation to find the hotel growth model in the destination life cycle: an empirical study in Myrtle Beach |
| title_sort | using slutsky equation to find the hotel growth model in the destination life cycle an empirical study in myrtle beach |
| topic | Destination life cycle Low-context High-context Myrtle Beach |
| url | https://www.emerald.com/insight/content/doi/10.1108/IHR-10-2022-0042/full/pdf |
| work_keys_str_mv | AT xuanvtran usingslutskyequationtofindthehotelgrowthmodelinthedestinationlifecycleanempiricalstudyinmyrtlebeach |