ESIC Market

Esic Market Economics and Business Journal Vol. 52, Issue 3, September-December 2021, e5234

Tourists’ characteristics in relation to expectations, satisfaction and loyalty in hotel industry

Luna Santos Roldán *

Universidad de Córdoba, Departamento de Estadística, Econometría, Investigación Operativa, Organización de Empresas y Economía Aplicada, Facultad de Derecho y C.C.Económicas y Empresariales. Puerta Nueva s.n, 14071, Córdoba.

td1sarol@uco.es

Beatriz Palacios Florencio

University of Pablo de Olavide, Department of Business Organization and Marketing, Faculty of Business Studies, Carretera Utrera, Km.1, 41013, Seville.

bpalacios@upo.es

Peter Bolcha

Anglo-American University, School of Business Administration, Letenska 5, Prague, Czech Republic,

peter.bolcha@aauni.edu

Received: 08/04/2021; Accepted: 19/05/2021; Published: 13/09/2021

Abstract

Objective: This paper makes an effort in combining the hotel subsector with a specific geographic location and with three determined constructs.

Methods: This article uses a unique individual level dataset collected in Spain hotels and attempts to shed more light on three phases of consumer evaluation: expectations, satisfaction and loyalty. In order to relate the evaluation scores in these areas to sociodemographic characteristics of the consumers, we employ regression analysis.

Results: The results show that all dependent variables in hand are related to explanatory variables; often in directions assumed by theory or previous empirical studies. Specifically, we find that age, economic status and country of origin are statistically significantly related to consumer evaluation. One of the novelties of our study is inclusion of “exceeded expectations” variable that intends to measure positive or negative surprise with the service.

Conclusion: The knowledge of the existence of incidences of demographic variables on satisfaction, loyalty and expectations could not only, but should, lead to the formulation and implementation of differentiated strategies, segmented according to groups of individuals, focused on improving these indicators, adapting services to the demographic characteristics of the clients.

Keywords: Hotel, expectations, satisfaction, loyalty, exceeded expectations

JEL classification: D12, L83, M31

游客特征与酒店行业期望、满意度和忠诚度的关系

文章摘要

研究目标： 本文章将酒店行业子部门与特定的地理位置和三个特定的结构结合起来。

分析方法： 本文章使用从西班牙酒店收集的个人数据，并试图更多地阐明消费者评估的三个阶段：期望、满意度和忠诚度。 为了将这些领域的评估分数与消费者的社会人口学特征联系起来，我们使用了回归分析。

研究结果： 此研究的结果表明，我们计算的所有因变量都与自变量有关，通常是在理论或先前实证研究假设的方向上。具体地说，我们发现年龄、经济地位和民族与消费者评估有显著的统计关系。我们研究的一个新特点是包含了“超越期望” 变量，该变量试图衡量服务的惊喜程度，无论是正相关的还是负相关的。

研究结论： 了解人口统计学变量对满意度、忠诚度和期望的影响，通过了解制定和实施不同的战略，根据个人群体进行细分，并侧重于改善这些指标，根据客户的人口特征调整服务。

关键词： 酒店, 期望, 满意度, 忠诚度, 超越期望。

JEL 分类号: D12, L83, M31

Introduction

Tourism is one of the most studied areas in the Social Sciences and at the global pandemic this industry needs of specific research for ease to remain in business. A review of the literature reveals an increase in articles that focus on explaining – at both empirical and theoretical level – different aspects of tourist satisfaction and attributes around it, but it is also the case that every situation needs an individual approach under this context. Therefore, it can be stated that tourism industry is highly sensitive to significant shocks like the Covid-19 pandemic (Chang et al., 2020). In other words, tourism is particularly susceptible to measures to counter pandemics due to restricted mobility and social distancing. This leads to global travel restrictions (which are unprecedented) that, together with confinement, are causing the most severe disruption to the global economy in recent decades (Gössling et al., 2020). Regarding related researchers, they usually center on the specific elements that make up satisfaction/dissatisfaction construct. The theories of customer satisfaction have been developed around customer behaviors in the area of accommodation (Pjero and Orgeta, 2020; Brinci et al., 2018; Ekinci and Riley 1998; Barsky and Labagh 1992) in order to find out how customer satisfaction can be applied to the hospitality industry and tourism. There have been a number of studies examining the attributes that lead travelers to feel satisfied and based on them, the factors which are most decisive when it comes to customer satisfaction are: quality of the staff, location, cleanliness and comfort of the room as well as safety and security (Markovic et al. 2010). This paper makes an effort in combining the hotel subsector with a specific geographic location and with three determined constructs. By doing this individual study for types of tourism and destiny, it is possible determine more precisely the satisfaction of guests. This article presents firstly an analysis of the constructs considered and obtain the hypotheses, the methodology been applied is next and finally results are exposed.

Literature Review and Research Hypotheses

In this section, we present the main results obtained from the review of the literature concerning the topics expectations, satisfaction and the consumer loyalty and their relations with their personal, demographic and economic characteristics. Some studies identify a positive relationship between the variables expectation and satisfaction, which means that by raising tourists’ expectations, the level of perceived quality can be increased, which, in turn, leads to greater satisfaction (Song et al., 2012; Fornell et al., 2006). Another variable that can influence in tourist satisfaction is the number of times a tourist has visited the destination (Correia et al. 2008). An elevated level of tourist satisfaction will lead to positive behavior patterns in the future such as the intention to return to a destination, to improve its reputation and recommend a visit to others (Kandampulley and Suhartanto, 2000). Besides Castillo and Jimber (2018) stated in their study focused on Seville, that satisfied tourists have an important impact through their intentions to revisit and recommend, the management of tourist satisfaction is a vitally important aspect of destinations’ success.

Consumer Characteristics and Expectations

Otero et al., (2014) define the concept of expectation as anticipation of a future result of services provided by the destination. Tourists go to hotels and/or tourist destinations with a series of expectations about the quality of their service provisions. These expectations can be due to certain personal, demographic and cultural characteristics, such as sex, age, nationality, economic status and marital status. Different studies have addressed this problem in the area of hotel activity: Armstrong, Mok, Go and Chan (1997), Mok and Armstrong (1998), Ariffin and Maghzi (2012).

For their part, Armstrong et al. (1997), in a study carried out in three different hotels in Hong Kong, and with a final sample of 325 useful surveys, find that the expectations of service quality of Anglo-Saxon origin tourists were significantly higher than those of Asian customers, though not those of European-origin customers.

Mok and Armstrong’s (1998) study, where they use the same sample as the previous study but eliminate cultural subgroups with less than 30 respondents, points out that the English tourists score higher in their global expectations than North Americans, Australians, Taiwanese and Japanese.

Finally, Ariffin and Maghzi (2012) analyse the differences in expectations of customers of Malayan hotels, identifying between nationals and foreigners. The independent variables considered were sex, reason for stay, nationality, age, level of studies, level of incomes and private domain of hospitality. There were 101 useful questionnaires in the end and the results as to the variables of interest in our research were the following: a) the men show higher expectations than the women; b) significant age-based differences were not detected; c) the local customers have higher expectations than the foreigners; d) differences according to the customers’ level of income were not noted.

The results of the preceding studies lead us to propose the following hypotheses.

H1.1: male consumers present a higher relation with expectations than women consumers.

H1.2: national users score higher satisfaction expectations than foreign ones.

H1.3: significant age-based differences are not expected.

H1.4: the customers’ economic status is not a determinant of their expectations.

H1.5: the consumers’ marital status can affect their levels of expectations of hotel service.

Consumer Characteristics and Satisfaction

Li, Ye and Law (2013) identify in their literature review as determinant factors of customer satisfaction in the hotel area the following: the management of the physical product (Deng, 2008; Fu, 2011; Nam, Ekinci, and Whyatt, 2011; Ramanathan, 2012); the management process (Ramanathan, 2012); the value for money (Chand, 2010; Ramanathan, 2012); the staff’s service attitude (Deng, 2008; Wu and Liang, 2009; Zhang and Li, 2009; Nam, Ekinci, and Whyatt, 2011; Yang Jou and Cheng, 2011); the brand identification (Nam, Ekinci, and Whyatt, 2011); the lifestyle-congruence (Nam, Ekinci, and Whyatt, 2011); diverse aspects of the customer service, such as cleanliness, location, etc. (Wu and Liang, 2009; Kralj and Solnet, 2010; Mohsin and Lockyer, 2010; Han, Kim, and Hyun, 2011; Magnini, Crotts, and Zehrer, 2011; Yang Jou and Cheng, 2011); the quality of the service offered (Sanchez-Hernandez, Martinez-Tur, Peiro, and Moliner, 2010); and the interaction with other customers (Wu and Liang, 2009).

For their part, Sim, Mak and Jones (2006) do not find a significant relation between the consumers’ sex and their satisfaction. On the other hand, Choi and Chu (2001) indicate as determinant factors of customer satisfaction the quality of staff service, the quality of rooms, the perceived value, the security, other comforts, the business services and the telephone customer service. Jani and Han (2014) point out that consumers’ satisfaction in hotel services is conditioned by the users’ personality factors. Armstrong et al. (1997) establish that English and European consumers were more satisfied than Asian consumers with the services provided by 3 Hong Kong hotels.

All of this leads us to propose the following hypotheses:

H2.1: women will feel less satisfied than men with the hotel’s service provision.

H2.2: national users will feel less satisfied than foreigners.

H2.3: significant age-based differences are not expected.

H2.4: the customers’ economic status is not a determinant of their perceived satisfaction.

H2.5: the consumers’ marital status can affect their levels of satisfaction with the hotel.

Consumer Characteristics and Loyalty

Consumer loyalty towards a product, a brand, an establishment, etc., can be considered, according to Back and Parks (2003), from a double perspective: attitudinal and behavioural. Repeat purchase patterns can be included among the behavioural aspects of the loyalty concept. On the other hand, the attitudinal aspects incorporate issues such as commitment, involvement, motivation and other consumer affective and cognitive variables.

Combining the analysis of the variables which are determinants of the consumer’s loyalty in the area of tourist activity presented in Kandampully, Zhang and Bilgihan’s (2015) work, along with the study of other contributions not included in this review, the following main factors can be pointed out as determinants: corporate reputation (Chang, 2013); relational benefits (Dagger and Brien, 2010); perceived attractiveness (Um, Chon and Ro, 2006); perceived quality of service (Um et al., 2006; González, Comesaña and Brea, 2007; Kandampully and Hu, 2007; Clemes, Gan and Ren, 2010; Hyun, 2010; Gracia, Bakker and Grau, 2011; Kim, 2011; Prentice, 2013); perceived value for money (Um et al., 2006; Suh and Ahn, 2012); customer satisfaction (Bowen and Chen, 2001; Back and Parks, 2003; Kandampully and Suhartanto, 2003; González, Comesaña and Brea, 2007; Kandampully and Hu, 2007; Clemes, Gan and Ren, 2010; Nam, Ekinci, and Whyatt, 2011; Chi, 2012; Jani and Han, 2014; Kim, Vogt and Knutson, 2015); performance of hotels (Ramanathan and Ramanathan, 2011); web site designs (Sanchez-Franco and Rondan-Cataluña, 2010); relationship quality (Sanchez-Franco and Rondan-Cataluña, 2010); employee engagement (Salanova, Agut and Peiró, 2005); rewards programmes (Hu, Huang and Chen, 2010; Tanford, Raab and Kim, 2011); physical environment (Han, and Ryu, 2009); service orientation (Kim, 2011); termination costs (O’Mahony, Sophonsiri and Turner, 2013); special treatment benefits (O’Mahony, Sophonsiri and Turner, 2013); social benefits (O’Mahony, Sophonsiri and Turner, 2013); confidence benefits (O’Mahony, Sophonsiri and Turner, 2013); communication (O’Mahony, Sophonsiri and Turner, 2013); opportunistic behaviours (O’Mahony, Sophonsiri and Turner, 2013); food quality (Hyun, 2010); price (Hyun, 2010); location (Hyun, 2010); environment (Hyun, 2010); commitment (Tanford, Raab and Kim, 2011); brand identification (Nam, Ekinci, and Whyatt, 2011); and hotel image (Kandampully and Suhartanto, 2000; Kandampully and Suhartanto, 2003; Jani and Han, 2014).

Although we have not found any work which relates customer loyalty with the independent variables considered in our study, we propose the following hypotheses:

H3.1: men will be more loyal than women.

H3.2: foreign users’ loyalty will be greater than that of national customers.

H3.3: significant age-based differences are not expected.

H3.4: the customers’ economic status is not a determinant of their loyalty.

H3.5: the customers’ marital status can affect their loyalty towards the hotel.

Consumer Characteristics and Exceeded Expectations

In the opinion of the authors, the sole scientific work which has addressed the problem of the difference between consumers’ expectations and perceptions of satisfaction is Armstrong et al.’s (1997) article. According to these authors, English people and Europeans attain a level of excess concerning their expectations greater than Asians.

In this case, we propose the following set of hypotheses:

H4.1: differences in terms of exceeded expectations between men and women are expected.

H4.2: national users will show a lower exceeded expectations ratio than foreign users.

H4.3: significant age-based differences are not expected.

H4.4: the customers’ economic status is not a determinant of exceeded expectations.

H4.5: the consumers’ marital status can affect the exceeded expectations ratio.

Method

The purpose of this study is to examine the relation of hotel guests’ characteristics to their satisfaction and other key variables of interest. This section first describes the collection of the sample and data used to test the proposed model. Subsequently, the translation and measures of satisfaction, expectations and loyalty are presented.

Data Collection and Sample

In order to collect data, it was needed a useful tool compatible with the goal of the paper, so the authors built a closed questionnaire was the chosen for managing.

The designed measuring tool is organised in three main sections. The first one deals with the information related to guest stay in tourist hotel located in Spain with seven elements: (1) length of the visit (number of nights); (2) main reason for being in the hotel, (3) who was in charge of the payment, (4) if there is any discount or special offer, (5) who chose the hotel, (6) if they stayed at the hotel before and how many times, and (7) how the booking was done. The second section measures the different constructs of the model. A 5 point Likert scale was used from 1 = "strongly disagree to 5 = "strongly agree" where the value 3 is interpreted as point of indifference. The third section collects the personal information of the respondents: (1) gender, (2) age, (3) nationality, (4) activity to which it is dedicated, (5) marital status and (6) size of the household.

For the calculation of the sample size, a simple design was used for the proportion with finite population. Substituting each parameter for its value we obtained that the minimum sample to be made was of 384 tourists.

Fixed the number of questionnaires to be made, the next step was the planning of the fieldwork. The investigation was carried out from 9:00 a.m. - 12:00 a.m. in the hall of 4 international hotels, near the counter, where the tourists made their departure, receiving the permission of the Director of the hotel to carry out said study. We chose to carry out the study on tourists staying in 4-star hotels, since, according to INE data (INE, 2019), the number of travellers (both nationals and foreigners) who stay overnight in this category is higher than in other star categories.

The field work was carried out without incident, obtaining a total of 629 valid questionnaires, a number that in principle far exceeded the minimum required. There were no nonsense values in the questionnaire. The responses show values in reasonable ranges and expected distribution. The rate of missing response is low (on average 2% across the variables). Variables with logical meaning (yes/no) were transformed to dummy variables (0=no, 1=yes), in particular age (age groups, marital status, work status).

The city of Seville was selected for reputational reasons, as the capital of the Autonomous Community of Andalusia (Spain) and of Seville Province, which has the largest surface area and population within the Community. It borders on the provinces of Malaga and Cadiz to the south, Huelva to the east, Badajoz to the north, and Cordoba to the east. Tourism is one of the strategic economic development engines of this city, which is why it is considered an essential instrument for wealth-, job- and new company-creation. Seville’s strength as an internationally competitive first-class urban tourist destination is based on its competitiveness in a number of tourism segments: cultural, religious, leisure and festive, culinary, health, rural, sports and business tourism, mainly. As a representation of the strength of the industry, it could be pointed out that in August 2020, under the global pandemic context, Seville hosted around 80,000 tourists, despite the situation known by all. In Jover and Díaz-Parra (2020), Díaz-Parra and Jover (2021), Domínguez-Navarro and González-Rodríguez (2020), or Ríos et al., (2016) we can relate to other papers focused on the same city of Seville with a common touristic approach.

Since our data allow us to test the above-mentioned hypotheses statistically, we have employed corresponding methods. After inspecting descriptive statistics and introducing simple correlations, we have chosen to apply multiple regression models, that allow us to (1) test multiple hypotheses in one model, to (2) make statistical inference about the individual relationships between independent and dependent variables, including the magnitude of these relationships and to (3) inspect these relationships in a separate (ceteris paribus) lines of relation. The multiple regression model (referred below) thus allowed us to get best linear unbiased estimates of these relationships and to eliminate the cases of spurious correlations¹ which would not be possible in case of separate analyses employing single-factor models.

Measures

Items for measuring employees’ expectations are the same as in Díaz-Martín et al. (2000). The reason for this is its concordance in tourism industry, as they used them for measuring clients expectations in rural tourism.

expect_rate = sum of all expectation variables divided by possible maximum; gives us relative number 0-1….corresponding to 0-100%

The disconfirming approach is the most common measure among researchers for measuring satisfaction. So that, we selected the scale in Maloles (1997), which has been adapted to our study, hotel sector, instead of the financial one.

satisf_rate sum of all satisfaction variables divided by possible maximum; gives us relative number 0-1….corresponding to 0-100%

The cross-sectional nature of the research does not allow us to measure consumer behavior as would have been desirable. For this, it could not be done. Loyalty, therefore, will be through behavioral intentions.

To measure intentions, we have studied the escalation elaborated by Zeithaml et al. (1996), also in the work of Maloles (1997) and Barroso (2000), adapting it to the context of our study.

loyalty_rate= sum of all loyalty variables divided by possible maximum; gives us relative number 0-1….corresponding to 0-100%

To traditional outcome variables we add a new one called exceeded expectations. Exceeded expectations are defined as relative difference between satisfaction and expectations (the more positive, the more positively surprised customer was).

exceeded_expectations_rate = satisf_rate- expect_rate (difference of percentages above)

Models and Hypotheses to be Tested

In order to perform tests of the hypotheses about relationships between the consumer characteristics, we had created several multiple regression models. Each of them is focused on specific aspect of the consumer experience. Models are depicted on Figure 1 below.

Fig. 1. Overview of regression models used for hypothesis testing

Consumer experience starts with expectations that further co-determine his/her satisfaction. In Model 1 we measure statistical relationship between consumer characteristics and expectations. During stay in hotel, consumer reaches certain level of satisfaction and Model 2 focuses on statistical relationship between consumer characteristics and satisfaction. As satisfaction is co-determined by prior expectations, we include Model 4 that relates consumer characteristics to difference between satisfaction and expectations. Last Model 3 relates consumer characteristics to loyalty.

Results

Sample Characteristics

Among the 627 respondents, 341 respondents (54%) were women and 286 (46%) were men. All respondents were 18 years old or higher, most coming from the age groups 25-34 (28%) and 35-44 (29%). Most of the respondents were economically active, 50% working and 33% self-employed. Regarding marital status, 60% of the respondents indicated that they were married.

The strongest positive correlation can be found between exceeded expectations rate and satisfaction rate, which is an expected result since high satisfaction at given level of expectations gives us high exceeded expectations rate. From analogical reasons, we find strongest negative correlation between exceeded expectations rate and expectations rate. Rather surprisingly, there is no significant correlation between exceeded expectations rate and loyalty. As noted above, these correlations server rather as preliminary analysis and multiple regression model(s) will enable us to analyze the variables simultaneously.

Test of Hypotheses

As mentioned in section above, we employ multiple regression in order to test multiple hypotheses we articulate. Table 2 below reports all results and we offer comments in text that follows.

As our results show, gender has no significant statistical relationship with any of our dependent variables.

Foreign guests on average show similar expectations as Spanish guests, but report slightly higher satisfaction (and therefore also higher positive difference between satisfaction and expectation than Spanish guests). Loyalty seem show negative sign: this is probably because of higher fraction of guests that do not need or intend to return to same place in near future.

Age seems to matter across all our models. Since we have used dummy variable approach and divided customers according to age groups, omitted variable (age 35-44) serves as a benchmark in interpretation. Youngest respondents (18-24) report higher satisfaction and positive difference between satisfaction and expectation (in relation to benchmark group). On the opposite side, guests aged 55-64 report lower satisfaction and difference between satisfaction and expectation (seem to be relatively disappointed by the services) than our benchmark age 35-44. On the other hand, oldest respondents report relatively high satisfaction, but this result can be driven by low number of respondents in this group (10). In relation to loyalty, only slightly relatively less loyal group are aged 65+.

Next statistical relationships are between economic status and dependent variables of interest. Benchmark group in this case is “work”. The most apparent difference applies to students who consistently report lower expectations, but surprisingly also report lower satisfaction than the working guests. Part of this result can be driven by a fact that most of the students are aged 18-24 and their responses are already captured by variable age. Thus, the negative sign shows relative lower satisfaction across students vs. non-students in this age, which can show that students are might be more critical in evaluation than their non-student counterparts from the same age cohort.

Self-employed guests report lower satisfaction with similar expectation which results also into lower difference between satisfaction and expectation. Retired persons have on average lower expectations with similar level of satisfaction which leads to higher difference between satisfaction and expectation.

Marital status does not show strong statistical relationships with dependent variables of interest. Most apparent is case of unmarried guests who have lower expectations, but also lower satisfaction than married ones that serve as a benchmark.

In a separate equation (extended version of model 3), we had come to intuitive result that satisfaction seems to be a strong predictor of loyalty. Each increase of satisfaction by 1 percent is associated with increase of loyalty by 0,59% percent points.

On top of hypotheses listed above we have created a variable that puts into relation expectations and satisfaction, thus signaling how much mis-expectations (in both positive and negative direction) can we observe across the customers. In the last column of table 3 we report the determinants of exceeded expectations. We report positive coefficients at foreign meaning that foreign guests on average are more often positively surprised that domestic ones. Similar surprise seems to be experienced by two youngest cohorts. Middle cohorts seem to have approximately similar expectations, but getting to oldest cohort, we find guests slightly disappointed.

Discussion and Conclusion

Discussion

Following rich literature on relations between customer characteristics and expectations, satisfaction and loyalty, we use a unique data collected in the field. Unlike most of previous studies, we employ multiple regressions that allows us to separate possible relation with one characteristic from another one. While many of our findings go in line with previous literature, in many other instances we do not find statistically significant relationships. Contrary to most previous papers, we show some evidence that economic status has relation to expectations, age has relation to satisfaction and that economic and family status may have relation to loyalty.

In line with Sim, Mak and Jones (2006), our results did not confirm relationships between gender and variable and interest. On the other hand, this result partly opposes findings of Ariffin and Maghzi (2012). A separate gender related study should be performed in order to reveal possible relations more closely. We did not have subtle nationality division, but our results show that foreigners show higher satisfaction than domestic guests, which confirms findings of Ariffin and Maghzi (2012). In constrast to the same authors (Ariffin and Maghzi, 2012) we found number of significant relationships with the age, which is more in line with findings of Yang et al. (2017) and Yang and Mattila (2016). Intuitively, different age brings different expectations, as well as different prior about the level of services. Economic status seem to make difference in case of students (larger and random sample would be needed to evaluate this more systematically and to distinguish from age more precisely).

Our data do not allow us to make deeper analysis that would distil the causal relationships. We might for example infer that students are less loyal than working group as a result of price sensitivity (might have chosen the hotel as a result of discount, next time this can be different hotel) or for example their stay being part of Europe or worldwide exploratory travels (even if they liked the hotel/destination) they do not report to come back. As stated above, more comprehensive collection of data and corresponding models should be done in order to address this more precisely.

Inspired by Armstrong et al.’s (1997), we have extended usual approach in existing literature by investigating determinants of exceeded expectations. The clearest pattern that coefficients show is that positive surprise can be most frequently found among youngest cohorts, while middle cohorts are about the same ending up with slightly negative surprise with older ones. This suggests another avenue for future research.

Conclusion

- Theoretical implications

In this study we bring some more evidence on relationships between consumer characteristics and key variables of interest that are one of crucial managerial indicators of for hotel industry.

The results show that the effects of demographic variables on satisfaction, loyalty and expectations are diverse. The investigated hotels were from the same category and we can expect the quality of their service to be comparable (Shieh et al., 2014). In other studies it is considered a variety of star rate (Castro et al, 2016; Yang et al., 2017), however the results changed in terms of category, so that the importance of developing research for each specific star rate.

Thus, the differences of responses can be attributed mostly to observables used in our models (starting with socio-economic characteristics and ending up with nationality, meaning different historical and cultural contexts) as well as to number of factors we were not able to capture. As manifested in other investigations (Yang et al., 2017; Yang and Mattila, 2016), age, income and level of study can also be important determinants of consumer behavior, as well as gender. An example of this type of results, is found in the study carried out by Hagan (2015), in the hotel service, where the author recommends the inclusion of the variables level of education and occupation, in addition to gender, to improve the service, from the segmentation by group of guests. Lehto et al. (2004) also stated that travel purpose, travel style, age and gender were significant factors influencing travellers.

- Practical implications

This study offers practitioners important actionable implications. First, this study recognizes the influence of demographic variables in terms of expectations, satisfaction and loyalty. This provides a mapping of how consumers perceive different outputs that may be common in hotels with the same star rate. Based on this, hotels can design a whole portfolio of package adapted to each market segment, as well as consider this finding in their webpage and social media profiles. This study can help regulators, investors and other agents working in the tourism sector develop a long-term market vision. With the help of the information obtained in this study, areas for improvement can be identified and adequate procedures can be put into practice which will improve the tourist offer and adapt it more closely to the needs of the traveler, resulting, thus, in greater levels of satisfaction and loyalty in the tourists who visit the city of Seville. The knowledge of the existence of incidences of demographic variables on satisfaction, loyalty and expectations could not only, but should, lead to the formulation and implementation of differentiated strategies, segmented according to groups of individuals, focused on improving these indicators, adapting services to the demographic characteristics of the clients. This differentiation would help the development of market strategies based on demographic variables, whose data would come from the consultations made to customers and the quantitative treatment, under schemes that allow determining the relationships between structural variables, appropriate to the context. Examples of these activities include: content marketing, offering advice about the city where it is located and proposing places and activities adapted to each group of visitors; offering an incentive adapted to recommend or leave their opinion of the stay; the existence of an online Guest Experience. This is a person who is in charge of seeing all the messages or comments from consumers and managing them so that they do not go unanswered and so as to satisfy the needs of the customers. In short, to carry out personalised attraction marketing.

- Limitations and future lines

The main limitations of this study is the sample size (extension would cover all categories better), limited number of variables (full data from hotel booking engines might be connected to similar survey) and last, but not least the sampling problem where this study means rather a pilot study capturing only very partial sample of population. Another limitation is that the data collected refers to a geographical area and a single sector and category. Regarding the first issue, the study was carried out in Seville, and it was desirable to have done it at the national level, considering not only indoor hotels, but also coastal hotels and covering different categories for their subsequent comparative analysis. This is a serious limitation when generalizing the results, however we believe to have shed some light into particular service and regional context. Next to focusing on higher number of respondents, variables and sampling, the future studies might be extended to other service sectors, and not only to the hotelier. Future lines of research could focus on the intersection of information between tourism offer and demand, providing insight into how an appropriate balance can be achieved in specific markets in determined territories. Moreover, it can be focused on specific age range, gender and specific customer characteristics to compare differences. This methodology can also be applied to other types of tourism, producing useful comparisons and identifying critical points and ways to continuously improve customer satisfaction.

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* Corresponding author. Email: td1sarol@uco.es

1. For example when results regarding the factor "age" would be influenced by the fact that a sample would contain much more young men than women and vice versa.

Citation

Santos Roldán, L.; Palacios Florencio, B.; Bolcha, P., 2021, Tourists’ characteristics in relation to expectations, satisfaction and loyalty in hotel industry, Esic Market Economics and Business Journal, 52(3), e5234. DOI: 10.7200/esicm.168.0523.4
ISSN 0212-1867 / e-ISSN 1989-3574
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