应对经济衰退的营销策略

帮助豪华酒店品牌提供建议和指导

 

 

Help provide advice and guidance to luxury hotel brands

 

"What marketing strategies should luxury hotels in the UK use to counteract the effects of a recession on their business?"

 

This question is being asked, and the research is being done, to take advantage of the recent recession in the UK, and use it to help provide advice and guidance to luxury hotel brands on how to mitigate the impacts of future recessions. An economic recession implies a shrinking of levels of consumer and business demand (Begg et al, 2003, p. 56). As a result, there will be a reduced demand for services such as hotel rooms, particularly in the luxury market where individuals can easily downgrade to a cheaper hotel option. This implies that luxury hotel operators need to understand how best to market their hotels in order to maintain their market share and the success of their business in the face of a shrinking market and reduced demand. In addition to this, the travel and tourism operators that are affiliated to them need to be able to market these hotels to their customers in order to maintain their affiliation; hence they also have an interest in the marketing strategies of luxury hotels in the UK.

 

An appropriate qualitative research design that will fully answer the research question will need to be based on a valid and accepted academic framework. This research design will use the '7Ps' extended marketing mix as a conceptual framework around which the qualitative research can be based. The 7Ps are based on the 4Ps of product marketing introduced by McCarthy (1960, p. 43) but supplemented by an additional three factors that Booms and Bitners argued were relevant to service marketing (Kotler and Keller, 2006, p. 89). This creates a model of seven distinct factors: Product, Price, Promotion, Place, People, Processes and Physical Layout that make up a model of the services marketing mix.

 

This framework will be used to construct a series of qualitative questionnaires which look at how luxury hotels have adjusted their marketing mixes during the recession. These questionnaires will be presented to a wide range of luxury hotels throughout the UK. Once the relevant marketing mixes for the hotels have been determined, they will be compared to industry measures of the success of the hotels, including their industry ratings; the reviews of guests and industry bodies; and the extent to which the hotels have maintained their revenues, numbers of guests and revenue per room over the course of the recession. The questionnaires will also be followed up by a series of semi structured interviews with managers of the hotels which have performed the best during the recent recession. These semi structured interviews will allow the managers to provide more detail on the use of marketing to prepare for the recession; how well the hotel performed during the recession; and the extent to which the 7Ps model guided the marketing decisions and strategy of the hotel.

 

The main strength of this research design is that it combined both academic and practical research and discussion into a single conceptual framework, and tests that framework in a contemporary context. As a result, this will mean that the results of any research carried out using the design will have both academic and practical relevance. This will help to maximise their reliability and validity (Saunders et al, 2007, p. 130). The design does not have any significant conceptual weaknesses; however it is overly reliant on the most recent UK recession as a source of data. As a result, it is possible that the data will not be generalisable, and hence will not be relevant to hotel managers and tour operators looking to deal with future recession which may be of a different nature. This implies that the results of the research should be compared to other studies that have taken place in previous recessions, to determine if these recessions had different outcomes and implications. The practical aspects of the design are mainly focuses on the collection of data from hotels. As most hotels are usually very busy, it may be difficult to get data from them. This may necessitate a significant investment of time and effort. The data may also not be fully complete or accurate, as hotels may not have time to obtain and verify all the necessary data.#p#分页标题#e#

 

Evaluate the application of multivariate regression analysis for hospitality and tourism demand for forecasting purposes.

 

The use of multivariate regression analysis for hospitality and tourism demand for forecasting purposes has an advantage over the use of standard regression analysis, in that it can consider multiple potential causal factors. As Frechtling (2001, p. 154) notes, tourism demand is usually influenced by a large number of factors, including both push and pull factors. As such, it is impossible to accurately forecast future hospitality and tourism demand without taking at least some of these factors into account. A multivariate regression analysis will not only show which factors influence the level of demand, but will also demonstrate how significant the impact of each of these factors is, hence better indicating how demand may change as these factors vary in future.

 

Unfortunately, the consideration of multiple factors does not avoid the potential issue that these factors may not be independent of each other. In other words, there may be significant cross correlation between the different predictive factors, indicating that these factors actually have a causal relationship with each other (Frechtling, 2001, p. 165), If this is the case, then a multivariate regression analysis may indicate that one factor has a strong influence on tourism demand, when that factor is actually being influenced by another factor, which is actually the factor influencing the demand level. This can lead to factors being wrongly believed to be predictors of demand, when in fact they are not, and hence the model being inaccurate. In addition to this, the multivariate model may not provide information on factors which may be lagging indicators, and this could introduce further inaccuracies into the model (Frechtling, 2001, p. 171).

 

An appropriate qualitative research design that will fully answer the research question will need to be based on a valid and accepted academic framework. This research design will use the '7Ps' extended marketing mix as a conceptual framework around which the qualitative research can be based. The 7Ps are based on the 4Ps of product marketing introduced by McCarthy (1960, p. 43) but supplemented by an additional three factors that Booms and Bitners argued were relevant to service marketing (Kotler and Keller, 2006, p. 89). This creates a model of seven distinct factors: Product, Price, Promotion, Place, People, Processes and Physical Layout that make up a model of the services marketing mix.

 

This framework will be used to construct a series of qualitative questionnaires which look at how luxury hotels have adjusted their marketing mixes during the recession. These questionnaires will be presented to a wide range of luxury hotels throughout the UK. Once the relevant marketing mixes for the hotels have been determined, they will be compared to industry measures of the success of the hotels, including their industry ratings; the reviews of guests and industry bodies; and the extent to which the hotels have maintained their revenues, numbers of guests and revenue per room over the course of the recession. The questionnaires will also be followed up by a series of semi structured interviews with managers of the hotels which have performed the best during the recent recession. These semi structured interviews will allow the managers to provide more detail on the use of marketing to prepare for the recession; how well the hotel performed during the recession; and the extent to which the 7Ps model guided the marketing decisions and strategy of the hotel.#p#分页标题#e#

 

The main strength of this research design is that it combined both academic and practical research and discussion into a single conceptual framework, and tests that framework in a contemporary context. As a result, this will mean that the results of any research carried out using the design will have both academic and practical relevance. This will help to maximise their reliability and validity (Saunders et al, 2007, p. 130). The design does not have any significant conceptual weaknesses; however it is overly reliant on the most recent UK recession as a source of data. As a result, it is possible that the data will not be generalisable, and hence will not be relevant to hotel managers and tour operators looking to deal with future recession which may be of a different nature. This implies that the results of the research should be compared to other studies that have taken place in previous recessions, to determine if these recessions had different outcomes and implications. The practical aspects of the design are mainly focuses on the collection of data from hotels. As most hotels are usually very busy, it may be difficult to get data from them. This may necessitate a significant investment of time and effort. The data may also not be fully complete or accurate, as hotels may not have time to obtain and verify all the necessary data.

 

Evaluate the application of multivariate regression analysis for hospitality and tourism demand for forecasting purposes.

 

The use of multivariate regression analysis for hospitality and tourism demand for forecasting purposes has an advantage over the use of standard regression analysis, in that it can consider multiple potential causal factors. As Frechtling (2001, p. 154) notes, tourism demand is usually influenced by a large number of factors, including both push and pull factors. As such, it is impossible to accurately forecast future hospitality and tourism demand without taking at least some of these factors into account. A multivariate regression analysis will not only show which factors influence the level of demand, but will also demonstrate how significant the impact of each of these factors is, hence better indicating how demand may change as these factors vary in future.

 

Unfortunately, the consideration of multiple factors does not avoid the potential issue that these factors may not be independent of each other. In other words, there may be significant cross correlation between the different predictive factors, indicating that these factors actually have a causal relationship with each other (Frechtling, 2001, p. 165), If this is the case, then a multivariate regression analysis may indicate that one factor has a strong influence on tourism demand, when that factor is actually being influenced by another factor, which is actually the factor influencing the demand level. This can lead to factors being wrongly believed to be predictors of demand, when in fact they are not, and hence the model being inaccurate. In addition to this, the multivariate model may not provide information on factors which may be lagging indicators, and this could introduce further inaccuracies into the model (Frechtling, 2001, p. 171).#p#分页标题#e#