Abstract
Purpose
There has recently been much interest in analysing the creation of personalised tourism services and studying their effect on organisations. However, there still needs to be more work in analysing their effect on happiness and the role that emotions play in these processes. This paper aims to analyse, in the context of personalised and innovative tourism services, which factors can encourage and improve managers' happiness.
Design/methodology/approach
A model of analysis is presented with five variables: tourism managers' happiness (TMH), innovative personalised tourism services, internal factors: emotions (IFE), organisational factors (OF) and personal factors (PF). Eight hypotheses are proposed and tested with a structural equation model.
Findings
The results allow the authors to affirm that personalised technological advances applied to tourism services not only contribute to improving the happiness of hotel managers but also in generating emotions that contribute to improving their attitude towards the company.
Research limitations/implications
This scientific work has some limitations. Firstly, this study was carried out exclusively in Spain due to the relevance of this country in the international tourism sector, according to the World Tourism Organisation. The results achieved in this research should be contrasted with other studies in other territories. Secondly, the interviews and surveys were carried out at specific time intervals. It has not led to problems of significant bias in the variance of the standard method. Therefore, it is desirable to undertake longitudinal or cross-sectional studies for future research. Thirdly, it is interesting to develop theoretical models that include other psycho-directive or leadership style constructs to determine whether they holistically enhance the subjective well-being of hospitality managers. Moreover, other types of factors of a social or strategic nature can be considered, which can positively or negatively impact the analysed variables. Finally, future research can deepen the empirical analysis of the relationship between managerial competencies and digital innovation from the perspective of happiness management. These findings would contribute to a greater cognitive understanding of the implications of personalised and innovative tourism services on hotel establishments' happiness and economic benefits.
Practical implications
This paper shows the fundamental role of a happy leadership style in creating responsible, green and innovative environments in today's digital society. Furthermore, the happiness of tourism managers can contribute to the generation of high quality and excellent services that are in line with the principles of sustainable development.
Social implications
Personalised technological advances applied to tourism services not only contribute to improving the happiness of hotel managers but also to generating emotions that contribute to improving their attitude towards the company. On the other hand, it has been observed that personalised and innovative tourism services generate positive effects at organisational, internal and personal levels. The following reflections are advanced: The development of internal factors such as the emotions of awe and gratitude or the generation of trust can enhance the happiness of tourism managers. The happiness of tourism business managers can be enhanced by developing OF such as smart-personalised tourism services and data protection. The happiness of tourism managers can be enhanced by the development of PF such as travellers' desires, expectations and needs, or other factors such as disposable income, health status or family situation.
Originality/value
This is the first empirical study that focuses on investigating how personalised and innovative tourism services affect managing happiness.
Keywords
Citation
Robina-Ramirez, R., Ortiz-de-Urbina-Criado, M. and Ravina-Ripoll, R. (2023), "How can tourism managers' happiness be generated through personal and innovative tourism services?", European Journal of Innovation Management, Vol. 26 No. 7, pp. 751-774. https://doi.org/10.1108/EJIM-07-2023-0594
Publisher
:Emerald Publishing Limited
Copyright © 2023, Rafael Robina-Ramirez, Marta Ortiz-de-Urbina-Criado and Rafael Ravina-Ripoll
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Innovation in the tourism sector has become a key aspect of its growth (Lyu et al., 2023). In recent years, several studies on innovation in tourism services have been developed because, among other things, they provide valuable data to better manage uncertainty (Robina-Ramirez et al., 2022). Through innovative methods, stimuli are generated in individuals and an emotional state is created that can influence their attitudes and behaviour (Moons and De Pelsmacker, 2012). According to Robina-Ramírez et al. (2022a, 2023a, b), tourism services can generate three emotions: awe, gratitude and compassion.
In this line, some works have analysed the impact of technology on personalised tourism services and the emotions generated. Neuhofer et al. (2014) studied the emotions generated by personalisation and privacy assurance in customers' responses to travel websites, while other studies have analysed the effort for product personalisation and tourist motivation (Aksenov et al., 2014) and its effect on the emotions generated (Mugge et al., 2009). Other authors recognise that these digital tools are essential to stimulate tourists' motivations and desires today (Pasquinelli et al., 2023; Panfiluk, 2023). Furthermore, some studies indicate that tourism establishments with modern, innovative and personalised tourism services improve service quality and customer satisfaction (Prima Lita et al., 2020; Tleuberdinova et al., 2022).
Personalised tourism services can help improve customer happiness in aspects such as obtaining information about the destination and experiencing tourism services (Ukpabiand Karjaluoto, 2016). Studying happiness in personalised tourism services requires coordinating several disciplines, such as psychology, technology, tourism or behavioural sciences, and finding the right strategy to unravel the psychological aspects of providing a personalised service that contributes to improving quality of life. However, despite the interest in this topic, there are still few studies that investigate how personalised and innovative tourism services influence quality, excellence and happiness (Galiano-Coronil et al., 2023; Robina-Ramírez et al., 2023a, b).
Therefore, an interesting research question is how personalised tourism services affect happiness management. To provide a possible answer to this question, the purpose of this paper is the analysis of the impact that the provision of innovative and personalised tourism services can have on happiness management. More specifically, this paper aims to identify a set of factors that can promote and enhance managerial happiness when innovative tourism services are provided. To achieve this goal, a model is proposed that examines the relationships between the following variables: personalised and innovative tourism services (PITS); internal, personal and organisational factors (IF, PF, OF); and tourism managers' happiness (TMH). Eight hypotheses are proposed and tested using structural equation modelling.
As Ravina-Ripoll et al. (2021a) comment, there is a need for more studies on the effect of innovation on happiness with application to the tourism sector. This is the first empirical study that focuses on investigating how personalised and innovative tourism services affect managing happiness. The study of happiness is complex because it is influenced by multiple psychological factors, such as emotions, internal and external factors (Robina-Ramírez et al., 2023a, b). Therefore, one contribution of this paper is to consider the importance of some factors generated in providing innovative tourism services in generating happiness. Another contribution is the proposal and empirical validation of a model of TMH. It is understood as an emotional state that is favoured by personalised and innovative tourism services. Furthermore, the proposed model shows a high explanatory power.
After this introduction, the next section describes the theoretical framework of the proposed theoretical model and its hypotheses. The third section presents the methodology used to test the hypotheses formulated. The following sections present and discuss the results obtained. Finally, the conclusions, theoretical and practical implications, limitations and future lines of research are presented.
2. Theoretical framework
To develop the theoretical framework, a literature review was carried out in four steps: (1) problem definition; (2) literature search in WoS and Scopus databases; (3) literature analysis; and (4) structure of the literature review. Regarding the problem definition, this paper starts from the relationship between two concepts: “happiness management” and “innovative tourism services”. A literature search was carried out in WoS and Scopus (17 September 2023) to see what has been studied on this topic. In Scopus, the search terms were TITLE-ABS-KEY and the results were “happiness management” and “innovative tourism service*” (0 results); “happiness management” and “tourism service*” and innovat* (0 results); “happiness management” and tourism* and “innovat* service*” (0 results); “happiness management” and tourism* and service* (0 results); “happiness management” and tourism* (2 results); “happiness management” and innov* (10 results). In the case of the WoS database, the search term was TOPIC: “happiness management” and “innovative tourism services*” (0 results); “happiness management” and services* and innov* (1 result); “happiness management” and services* (3 results); “happiness management” and innov* (10 results). As there is no specific study of this type of service and happiness management, previous studies on happiness management in general and its relationship with tourism services and innovation have been considered.
Happiness management can contribute to the development of passion for work and the promotion of innovation (Ravina-Ripoll et al., 2021b). Furthermore, Kim et al. (2015) and Schmiedeberg and Schröder (2017) find that the quality of innovative personalised services has a significant impact on the happiness of their users. Workplace happiness can be considered one of the intangible resources contributing most to organisational innovation performance (Ravina-Ripoll et al., 2023a; b). The literature shows that happy employees are characterised as a highly productive, intrapreneurial, creative and innovative group (Foncubierta-Rodríguez et al., 2020). To implement innovative activities, a collaborative leadership style can proactively stimulate the happiness of employees (Berraies, 2022; Ruiz-Rodríguez et al., 2023). Tourism managers can develop a culture based on the principles of corporate happiness to stimulate innovative performance (Aboramadan and Kundi, 2022; De-la-Gala-Velázquez et al., 2023). In this environment of subjective well-being, employees can increase their innovative capacity and motivation for the pursuit of ideas that will be future technological products for the tourism sector (Bibi et al., 2022).
Happiness can be subjective through the generation of positive emotions or psychological when it provides a sense of excellence, perfection, meaning and direction based on people's objective experience (Ravina-Ripoll et al., 2019b). In addition, PF such as status and level of responsibility can modify the sequence of emotions and the state of happiness within the organisation. However, the impact of innovation on happiness is not only determined by internal factors. It is also important to consider organisational aspects that can affect the happiness of managers and customers (Yousif, 2023). However, much remains to be done to analyse their impact on happiness and the role of emotions in these processes.
Taking these ideas into account, an analytical model (Figure 1) and eight hypotheses have been proposed in order to explore the factors related to innovative tourism services that can promote managers' happiness. These hypotheses are explained next.
2.1 Innovative personalised tourism service (IPTS)
The literature defines innovation in tourism as the generation, acceptance and application of new ideas, processes, products or services (Hall et al., 2008). In the same vein, Suder et al. (2022) define tourism innovation as a complex process that goes beyond being the result of the personal creativity of entrepreneurs. For this reason, some researchers argue that in tourism services, managing knowledge is fundamental to implementing innovative processes in organisations (Hjaleger, 2002). Following this line of reasoning, some recent studies indicate that tourism experience companies do not seem to design innovation processes intentionally. Rather, they seem to “innovate by innovating” or “innovate by doing” (Hall et al., 2008; Hoarau, 2016). In this way, tourism businesses can meet the current needs of tourists seeking new and unique experiences by developing personalised and innovative tourism services (Hu et al., 2009).
This would benefit from organisations with high levels of innovation and management models that promote teamwork, corporate happiness and altruistic knowledge transfer among all members (Finnegan and Willcoks, 2006; Hallin and Marnburg, 2008). Tidd et al. (2005) argue that sharing knowledge within firms contributes significantly to improving their competitive position in the current globalised market. Aboushouk et al. (2019) and Obrenovic and Qin (2014) classify knowledge sharing factors in tourism firms into three categories: organisational, social and personal.
OF influence knowledge sharing adoption (Obrenovic and Qin, 2014). These factors include organisational culture, incentive, reward and compensation systems, support from top management, supervisors and colleagues, leadership style, organisational structure, value congruence, openness and fairness, and employee commitment (Aboushouk et al., 2019).
Other studies agree that social factors positively influence adopting knowledge sharing (Obrenovic and Qin, 2014). Social factors include employee relationships such as trust, career advancement, reciprocity, social interactions and team collaboration, sense of community, social networks and diversity in the team context (Aboushouk et al., 2019).
In the case of PF, managers in tourism companies have been found to enhance and develop employee participation in knowledge sharing (Obrenovic and Qin, 2014; Cimbaljević et al., 2023). PF include aspects of self-efficacy, optimistic personal and work attitudes towards knowledge sharing, expected rewards, recognition and status enhancement, enjoyment of helping others, perceived loss of knowledge power, personal expectations, subjective norms, employee intentions beyond knowledge sharing with peers, employee personality and emotions, sense of self-esteem and feeling of being part of the organisation (Aboushouk et al., 2019).
Innovative tourism services enhance internal knowledge sharing, as well as personal and organisational knowledge sharing. This knowledge sharing facilitates the participation of different stakeholders in the tourism sector, especially employees, which improves the working environment and can contribute to increased well-being and happiness in the company (Robina-Ramírez et al., 2022a). It also affects value co-creation (Gao et al., 2022) and business performance (Tajeddini et al., 2020).
Thus, the interest in considering the impact of innovative personalised tourism service provision on internal, personal and OF has been highlighted (Hysa et al., 2023). In addition, according to Ravina-Ripoll and Robina-Ramírez (2023), these factors allow for a link between the variables of innovative personalised tourism services and the satisfaction of tourism managers.
2.2 Internal factors: emotions (IFE)
The term innovative personalised tourism services suggests that the use of digital tools allows people to enjoy valuable and useful information in real time when choosing the location of their future tourist destinations (Ajantha et al., 2017; Buhalis and Amaranggana, 2015). Such a circumstance generates several positive emotions that not only stimulate their propensity for new leisure trips but also increase their attachment or psychological connection to the area of their choice for holidays (Lee et al., 2018; Neuhofer et al., 2014; Kabadayi et al., 2019). Based on this fact, some scientific studies recognise that personalised tourism services generate positive emotions in their users when they guarantee high quality and excellent services, as well as easy accessibility and operability (Garud et al., 2013).
The Positive and Negative Affect Scale (PANAS) is widely used in the tourism sector to measure the satisfaction of hotel customers (Watson et al., 1988) and to determine the effects that personalised tourism services generate in their users (Papaiannidis and Davlembayeva, 2022). One of these effects is the generation of emotions such as awe, gratitude, achievement, compassion or enthusiasm (Keltner and Haildt, 2003; Büssing et al., 2018; Sheldon, 2020). Organisations can offer tourism services that provide positive emotions, self-confidence and subjective well-being to their customers (Kallou and Kikilia, 2021). Kurshwaha (2020) points out that tourism services are delivered effectively when personalised user content (UPC) is characterised by gratitude and affectivity. This finding shows that innovative personalised tourism services create value for users when their information systems promote their happiness by satisfying their wants and needs (Robina-Ramírez et al., 2022a).
For example, Kontogianni et al. (2022) suggest that innovative personalised tourism services become essential sources of sustainable competitive advantage when they exert a strong influence on customers' internal factors, especially their latent positive emotions (Baumgartner et al., 2008; Dane and George, 2014). In contrast, some researchers have focused on exploring the negative emotions generated during the innovation process from the perspective of stakeholders (Wood and Moreau, 2006; Yang and Hung, 2015). This is because negative emotions such as anger, sadness, hostility or guilt reduce the productive and economic performance of organisations (Staw et al., 1981). They also limit the creativity, disruptive thinking and technological innovation of employees and managers (Brown et al., 1999). Importantly, negative emotions are also a source of empathy (Goetz et al., 2010).
However, the emerging literature on happiness management teaches us that happy companies are characterised by management models that are open to digital innovation, intrapreneurship and gamification. Under these parameters, tourism companies that embrace the philosophy of happiness management can enjoy innovative personalised tourism services that generate positive emotions for their customers on the one hand, and happiness at work for their tourism managers on the other (Mu et al., 2023). In other words, the internal factor-emotion construct represents a transcendental link in the chain of happiness variables for managers of tourism services (Ravina-Ripoll et al., 2023a, b). As a result of the above, the following research hypotheses are formulated:
Internal factors: emotions (IFE) positively affect tourism managers' happiness (TMH).
Innovative personalised tourism service (IPTS) positively affects internal factors: emotions (IFE).
2.3 Personal factors (PF)
Following the COVID-19 pandemic, one of the strategic lines of action for companies in the tourism sector must be to create new, innovative, personalised tourism services that attract the attention of customers (Toubes et al., 2021). These companies need to have a wealth of real-time information about the internal and PF of their potential customers. This will allow them to understand their preferences for the next destination and their purchasing power, available leisure time, how they like to shop or cultural preferences (Buhalis and Amaranggana, 2015). This information is essential for tourism managers to implement advertising and marketing campaigns that increase customer loyalty (Paliwal et al., 2022). Consequently, the economic success of these organisations will lie, among other things, in offering innovative personalised tourism services that ensure the subjective well-being of individuals in order to achieve their loyalty to the companies (Bharwani and Mathews, 2016).
Today, innovative personalised tourism services can create memorable consumer experiences in terms of quality, trust and positive emotions (Camisón and Forés, 2015; Gezhi and Xiang, 2022). Therefore, the efforts of organisations should be directed towards the provision of innovative personalised services that are in line with the internal expectations of their customers (Buhalis and Amaranggana, 2015). This requires a workforce with PF that foster creative and innovative performance and coping skills to deal with problems that arise in their daily work (Sheldon, 2020).
Internal, employee-related factors, such as the ability to solve problems or provide quality service, have an impact on emotions (Faullant et al., 2011). Also, the emotions generated are often related to the previous experiences and personality of the tourist and the manager (Gezhi and Xiang, 2022). Personalised tourism services can contribute to the professional and personal development of people working in organisations, as they are more likely to face challenges and experience a sense of achievement and fulfilment. This generates enthusiasm and optimism in customers (Sheldon, 2020). This is the result of healthy self-awareness, leading to greater happiness and job satisfaction.
Openness to the experience of exploring innovative ideas and developing a collaborative personality fosters a culture of learning and innovation (Barnes et al., 2016). These PF increase managerial happiness and improve overall performance and team effectiveness (Li et al., 2022). They are also linked to positive attitudes. Managers who approach their work with enthusiasm, passion and positivity experience greater job satisfaction and happiness. Combined with these personality traits, other characteristics such as optimism, resilience and the ability to adapt to find joy in their professional role ultimately lead to greater happiness.
For Faullant et al. (2011), optimism, joy and happiness are fundamental to creating positive, meaningful and motivating emotional experiences for consumers. The results of this research show that the management models of tourism organisations should focus on the holistic pursuit of customer happiness. Previous studies confirm that one of the fundamental prerequisites to achieve this goal is modern, innovative and personalised tourism services, such as hospitality or smart destinations (Bharwani and Jauhari, 2013; Sanagustín-Fons et al., 2020). On the other hand, Faullant et al. (2011) point out that innovation strategies in tourism companies require a leadership style and human capital with creative, adaptive and innovative work behaviours. In this way, the top management of these organisations will be able to provide innovative and tailored tourism services that meet the expectations and needs of consumers (Barnes et al., 2016).
Therefore, one way to remain economically sustainable in the long term may be to cultivate corporate happiness ecosystems that leverage workers' PF towards the advancement of new digital technologies (Li et al., 2022). In this regard, some academic work highlights that the happiness of tourism managers plays a crucial role in encouraging employees to develop enthusiasm, passion and positivity (Ravina-Ripoll and Robina-Ramírez, 2023). These internal factors contribute to gaining competitive advantages by creating modern, innovative and personalised tourism services (Sheldon, 2020). On the other hand, they are also crucial in fostering positive internal emotions among consumers when they perceive first-hand their ease of use (Wu et al., 2023). The following research hypotheses are derived from these theoretical foundations:
Innovative personalised tourism service (IPTS) positively affects personal factors (PF).
Personal factors (PF) positively affect internal factors: emotions (IFE).
Personal factors (PF) positively affect tourism managers' happiness (TMH).
2.4 Organisational factors (OF)
In smart tourism, accurate recommendations are crucial for providing personalised customer experiences (Logesh et al., 2019). By incorporating user feedback and continuously improving their offerings based on customer input, organisations can demonstrate their commitment to meeting user needs (Bošnjak et al., 2017).
Organisations that prioritise service quality are more likely to attract and retain customers. Organisations that effectively tailor their offerings to individual needs can create positive emotional experiences and increase user engagement (Neuhofer et al., 2015). Organisations are also concerned about privacy and security. Prioritising and communicating strong data protection measures builds greater trust with users (Masseno and Santos, 2018). Emotional reassurance about the protection of personal data encourages people to feel more comfortable using these services (Kabadayi et al., 2019). Tourism managers need advanced systems and tools to collect, analyse and use reliable technology (Buhalis and O'Connor, 2005). Attention to these organisational aspects creates a positive organisational culture that enables the development of an incentive system to motivate and reward tourism managers in tourism (Bronzin et al., 2021).
In this sense, OF have been considered to refer to those psycho-managerial characteristics that become highly relevant in the daily life of organisations to design happy, creative, dynamic and collaborative ecosystems (Obrenovic and Qin, 2014). The literature on organisational innovation shows that in order to improve the delivery of tourism services to their users (Bošnjak et al., 2017; Logesh et al., 2019), firms have at their disposal management models that associate this term with the three Ps: prosperity, productivity and progress (Breznitz, 2021). All this can be achieved when companies promote internal knowledge sharing and innovative performance of their human resources (Um and Chung, 2021; Mariani et al., 2023; Norouzi et al., 2022).
In this sense, OF are observed to contribute to the development of technologies that motivate the innovative performance of both employees and tourism managers (Buhalis and O'Connor, 2005). Some studies confirm that companies increase the quality of innovative personalised tourism services when OF contribute significantly to increasing customers' trust and consumption expectations by promoting positive and enjoyable emotional experiences (Neuhofer et al., 2015; Masseno and Santos, 2018; Kabadayi et al., 2019).
According to self-determination theories, OF lead to employees' job satisfaction and customers' positive emotions (Vansteenkiste et al., 2010). Therefore, such factors are highly relevant for companies to produce modern and innovative digital tourism services in order to gain a sustainable and strong competitive advantage (Cimbaljević et al., 2023).
In this line, some studies show that the happiness of tourism managers is determined by OF that promote the innovative performance of employees from happiness management, intrapreneurship and technological innovation (Ahumada-Tello et al., 2022; Galván-Vela et al., 2021). Furthermore, OF may act as mediators between innovative personalised tourism services and the happiness of tourism managers. Based on these theoretical arguments, the following research hypotheses to be tested are justified:
Innovative personalised tourism service (IPTS) positively affects organisational factors (OF).
Organisational factors (OF) positively affect internal factors: emotions (IFE).
Organisational factors (OF) positively affect tourism managers' happiness (TMH).
3. Methodology
3.1 Variables and questionnaire
A list of 14,796 Spanish hotels with contact details was compiled and checked against statistics from the National Statistics Institute. From this list, 60 hotel managers from each Autonomous Community were selected. Data were collected from each manager to find out their opinions, behaviour or psychological characteristics. Hotel managers were chosen as the subject of the study because they have a holistic view of hotel operations, including the introduction and management of innovative services. Their insight can provide a comprehensive understanding of how these services affect the emotional experience of employees. In addition, they are responsible for the introduction and implementation of innovative services in their properties. Their responses can shed light on the strategic decisions behind these innovations and how they are likely to affect employees' emotions. They also have access to internal data, employee opinions and performance metrics. This access can facilitate the collection of objectives, quantitative data, increasing the rigour and reliability of the research. Finally, they bring their practical experience to help contextualise the findings.
Initial contacts were made via email and telephone in early June 2023, and they were invited to participate in several focus groups. The sample of hotels is shown in Figure 2. Of the total sample, 36 hotel managers agreed to participate in the study. A series of focus group meetings were organised (Sánchez-Oro and Robina-Ramírez, 2020) in which 12 and 10 hotel managers participated, respectively, and individual meetings were organised for the remaining 14. The objective was to analyse the variables that influence the generation of emotions and the search for customer happiness through personalised tourism services. Four validated measurement scales related to happiness (Ravina-Ripoll et al., 2020), emotion generation (Robina-Ramírez et al., 2022b), personal and organisational factors (Hilaly et al., 2019) and technology and innovation (Parasuraman, 2000) were used as a starting point. And a list of indicators was proposed to measure each construct. In the first session, 22 of the 70 proposed indicators were discarded because, according to the hotel managers, they did not fit well with the practical concept of personalised tourism services. For the remaining 48 indicators, each manager was asked to rate the level of interest from 1 (least important) to 5 (most important). Finally, those indicators were selected that scored an average of 4 on the criteria of clarity of presentation, applicability in the company and contribution to improving the customer's perception of the company, a total of 22 (Table 1).
Regarding the first construct “managerial happiness”, hotel managers discussed the development of an emotional culture and a collaborative leadership style to stimulate their happiness by fostering a positive work environment. Collaborative leadership creates a mutually reinforcing cycle of happiness and well-being that contributes to a healthier and more productive workplace. Managers who lead teams to successfully implement innovative services are likely to experience a sense of pride, achievement and accomplishment. This, in turn, contributes to their overall job satisfaction and happiness.
The second construct, internal factors such as “emotions”, plays a crucial role in the overall travel and tourism experience and significantly influences the traveller's perception of the quality of tourism services. Efficient and high-quality personalised services can evoke positive emotions and should be based on compassion, genuine care and empathy towards travellers, especially in difficult situations.
The third construct is innovative personalised tourism service, which provides knowledge to implement the company's innovation process and satisfy the tourist's desire for new experiences. Knowledge sharing behaviour helps organisations to identify opportunities, design unique experiences and remain competitive in the dynamic tourism sector. Innovation as part of organisational culture values creativity, risk-taking and collaboration within teamwork and social factors. This culture must be recognised in the incentive systems of the organisation.
Personal factors, as the fourth construct, combine personal expectations, including goals, aspirations and desire for self-improvement, pursuit of advancement opportunities, such as disposable income and health status. To develop resilience and adaptability to overcome obstacles, hotel managers need to acquire new knowledge and skills. The fifth construct is the organisational factor as the commitment to deliver exceptional customer experiences often requires organisational adaptations. Organisations can restructure to create customer-centric departments focused on personalised services and innovation. Reliable technology ensures consistent customer experiences and generates a sense of achievement and motivation, as technology streamlines processes and enables better service delivery.
3.2 Sample
The questionnaires were sent out during July 2023 and were approved through the “ethical clearance” process, informed by the University of Extremadura document 16-2023. The final sample is composed of 558 responses. Table 2 shows the study population and sample of hotels in each region. According to the data, considering a population of 14,796 hotels and a sample size of 558 hotel managers, the error margin is 3% for a confidence interval of 90%.
The socio-demographic data show hardly any gender variation between hotel employees and managers, slightly favouring men (52%) compared to women (48%). 55% are under 35, and 63% have more than a secondary education. 40% are married, neither separated nor divorced. Almost 50% earn less than €25,000.
3.3 Data processing
SEM-PLS has been chosen over covariance-based SEM techniques due to the complexity of the model and latent variables (Dash and Paul, 2021), especially the difficulty in determining the content of emotions derived from personalised tourism technology services. Covariance-based SEM techniques can be more sensitive to misspecification, leading to biased estimates (Reinartz et al., 2009). Reflective measurement models are widely used in social science research. These models assume that latent constructs cause the observed indicators, implying that a change in the construct leads to a change in the indicators. Researchers often use reflective models when they believe that the latent construct is the underlying cause of the observed variables. It involves a series of steps, including conceptualization, indicator selection, assessment of reliability and validity, internal and external consistency checks, and model assessment. Researchers must navigate these stages carefully to ensure that the model accurately represents the latent constructs and aligns with the theoretical framework.
4. Results
Evaluating a PLS-SEM reflective measurement model is a rigorous process that requires multiple analyses and tests to ensure the reliability and validity of the scales and internal and external consistency (Jannoo et al., 2014). External loadings refer to the correlations between latent variables and observed variables and are expected to be > 0.7 (Carmines and Richard, 1979). For all indicators presented in Table 1 meet this except for THM5 (0.558), IPTF4 (0.624) and PF2 (0.556).
Average variance extracted (AVE) and the R-squared (R2) values are considered to assess the quality of their measurement model in confirmatory factor analysis (CFA) within PLS-SEM. These values help evaluate the extent to which the latent factors account for the observed variance, providing information about the construct's reliability and validity in the model. Validity and reliability (0 to 1) were analysed (Hair et al., 2011) and all conditions met (Table 3).
Table 4 shows the values extracted from the Fornell-Larcker criterion by comparing the AVE and the correlations. The diagonal values are lower than the vertical and horizontal values; therefore, all conditions are fulfilled (Fornell and Larcker, 1981). The Fornell-Larcker criterion does not consider the possibility that a latent variable is related to variables not included in the model, which may affect discriminant validity. To do so, if the HTMT is lower than 0.90, discriminant validity between the two latent variables is considered to exist (Henseler et al., 2015).
The fit indices are the normalised root mean square residual SRMR, that is 0.079, indicating a better model fit if values are below 0.08. Lower values of d_ULS (1.086) and d_G (0.285) that indicate a better model fit. Chi-square (χ2), that is 1281.013, compares the observed covariance matrix with the covariance matrix implied by the model. The NFI, that is 0.726, shows a better fit if values are closer to 1 (Henseler et al., 2016).
In SEM-PLS, hypotheses express in terms of regression coefficients (beta). These indicate the strength and direction of the relationship between the variables in the model. According to Cepeda-Carrion et al. (2019), to assess the statistical significance of the regression coefficients, Student's t-test is used if significantly different from zero for a t-value greater than 1.96 and the p-value, if less than 0.05, indicates that the regression coefficient is significantly different from zero (Table 5).
The R2 coefficient assesses the model's ability to explain and predict the variables of interest. These results are aligned when analysing the explanatory power of the model. Based on R2, we can say that the amount of variance of THM is significantly explained by the predictor variables of the remaining endogenous constructs (IFE, OF, PF). It observes that the improvement of OF contributes to a greater extent to the happiness provided by the use of tourism services (TFM-OF, variance explained) and to a lesser extent by the emotions generated by the incorporation of these personalised services in customer management (TFM-OF, variance explained). If we analyse the factors contributing to generating positive emotions through personalised tourism services (IFE-OF, variance explained) (Table 6).
5. Discussion
Confirming all the hypotheses allows us to affirm that personalised technological advances applied to tourism services contribute to improving the happiness of hotel employees and managers and generating emotions that contribute to improving their attitude towards the company. The most used services in hotel management are personalised digital tourism services (Kushwaha, 2020), localisation techniques for tourism services (Ajantha et al., 2017) and the integration of public transport in personalised electronic tourist guides (García et al., 2013), among others.
Among the hypotheses, the high significance of hypothesis H4 stands out. IPTS positively affects OF as tourism managers seek to base their knowledge and algorithms on data to offer tailored suggestions based on smart-personalised tourism (Norouzi et al., 2022). These services affect the organisation's structure (Um and Chung, 2021) and the type of personalised customer experience (Logesh et al., 2019). It means a greater likelihood of attracting and retaining customers (Neuhofer et al., 2015).
Especially significant are also H7 and H3. OF positively affect internal factors such as emotions. Tailoring tourism offerings to individual needs can create positive emotional experiences and increase user engagement (Neuhofer et al., 2015; Lee et al., 2018). Personalised tourism services provide technological advances to manage information about the tourism destination in real-time (Buhalisand Amaranggana, 2015). However, they also generate emotions that affect tourism behaviour (Lu et al., 2019) of awe and gratitude that influence behaviour (Büssing et al., 2018), providing self-confidence to visitors (Kallou and Kikilia, 2021), trust (Gezhi and Xiang, 2022), awe (Magnini, 2017; Sheldon, 2020) and compassion in the face of harm caused when service delivery is inadequate (Goetz et al., 2010).
According to hypothesis 3, PF significantly affect personalised tourism services. In this case, PF such as travellers' desires, expectations and needs affect the mode of service delivery (PF1), the ability to solve problems or provide quality service (PF3), and the level of professional and personal development (PF4). In contrast, the content of the information provided by such services is unrelated to disposable income, family situation and previous experiences (PF2) (Buhalis and Amaranggana, 2015).
Moreover, the model's explanatory power justifies the importance of developing advanced systems and tools by tourism managers to collect, analyse and use reliable technology (Buhalis and O'Connor, 2005). In addition to offering personalised customer experiences (Logesh et al., 2019), a positive organisational culture can be created that allows for the development of an incentive scheme to motivate and reward employees of the tourism company (Bronzin et al., 2021).
6. Conclusion
This paper has proposed and empirically validated an explanatory model of happiness arising from providing innovative and personalised tourism services. The main academic contribution is that it is one of the first scientific studies to empirically examine the influence of innovation processes on the happiness of tourism managers.
Personalised technological advances applied to tourism services not only contribute to improving the happiness of hotel managers but also to generating emotions that contribute to improving their attitude towards the company. On the other hand, it has been observed that personalised and innovative tourism services generate positive effects at organisational, internal and personal levels. The following reflections are advanced:
The development of internal factors such as the emotions of awe and gratitude or the generation of trust can enhance the happiness of tourism managers.
The happiness of tourism business managers can be enhanced by developing OF such as smart-personalised tourism services and data protection.
The happiness of tourism managers can be enhanced by the development of PF such as travellers' desires, expectations and needs, or other factors such as disposable income, health status or family situation.
It also has several practical implications for strategic management, especially in the tourism sector. The results for the organisational, personal and internal factors can be used to offer some lines of action in companies. It is interesting to develop an emotional culture and collaborative leadership styles around happiness that encourage employee innovation. Stimulating employee innovation and happiness can increase productivity and economic efficiency. Stimulating employee happiness requires solid organisational support and implementing innovative services to achieve happy customers.
To achieve high levels of innovation, knowledge-sharing behaviours among employees must be reinforced. Personalised tourism services require knowledge sharing to satisfy the need to search for new experiences. There are organisational (culture, incentive systems …), social (trust, promotion …) and personal (positive attitudes …) factors that help knowledge sharing.
Organisations' ability to solve problems or provide quality service influences positive emotions and happiness. Moreover, if PF contribute to professional and personal development, it may be easier to face future challenges. Happy organisations are sources of prosperity, innovation and economic development. A leadership style can create a work environment where human capital is proactive, dynamic and intrapreneurial (Kaur and Kaur, 2023). This phenomenon may be the seed that will sprout innovative products and services in today's digital society (Deb et al., 2022). In the tourism sector, the ecosystem is characterised by corporate governance that feeds job insecurity, emotional exhaustion, absenteeism and turnover. This toxic environment degrades its employees' psychological health and propensity for digital innovation and change (Morgan and O'Connor, 2022).
The implementation of the happiness management philosophy offers tourism companies the possibility of implementing a human resources policy that allows them to bring out the creative talent and inner innovation of their internal customers in the era of Industry 5.0 (Ravina-Ripoll et al., 2022). To achieve this end, a sine qua no condition must be to encourage happy tourism managers who facilitate the ethical, sustainable and innovative development of all company members.
Companies in this sector can implement an organisational culture that stimulates emotional and PF in the innovation of their employees, and that fosters a working environment where happiness flourishes and management models that encourage digital progress, creativity or disruptive thinking are applied.
This paper has significant political and social implications. The first provides rich information for public administrations to develop policy actions to foster organisational innovation within tourism enterprises through corporate happiness. In this way, tourism enterprises can maximise their efficiency and competitiveness in the long run (Nuñez-Barriopedro et al., 2023). Second, the empirical results of this scientific study show the critical role of a happy leadership style in creating responsible, green and innovative environments in today's digital society (Li et al., 2023). Third, the happiness of tourism managers is fundamental, on the one hand, to contribute to the generation of high-quality services and excellence that comply with the principles of the Sustainable Development. On the other hand, to improve the exchange of knowledge between workers within companies. As a result, territories will be able to enjoy innovative and happy ecosystems where the general interest of citizens is cultivated (Ruiz-Rodríguez et al., 2023). Fourthly, innovative personalised tourism services can be considered beneficial instruments to satisfy people's general well-being, especially during leisure time (Rando-Cueto et al., 2023). Fifthly, public governments carry out action plans in the tourism industry that contemplate as a roadmap that organisational innovation and the happiness of its human capital are guarantors of economic and social success (Ravina-Ripoll et al., 2019a). Last but not least, to show social agents the need for policies in the tourism sector to consider that the culture of happiness management is the light of quality of life, general interest and sustainability (Jambrino-Maldonado et al., 2022).
This scientific work has some limitations. Firstly, this study was carried out exclusively in Spain due to the relevance of this country in the international tourism sector, according to the World Tourism Organisation. The results achieved in this research should be contrasted with other studies in other territories. Secondly, the interviews and surveys were carried out at specific time intervals. It has not led to problems of significant bias in the variance of the standard method. Therefore, it is desirable to undertake longitudinal or cross-sectional studies for future research. Thirdly, it is interesting to develop theoretical models that include other psycho-directive or leadership style constructs to determine whether they holistically enhance the subjective wellbeing of hospitality managers. Moreover, other types of factors of a social or strategic nature can be considered, which can positively or negatively impact the analysed variables. Additionally, future research can deepen the empirical analysis of the relationship between managerial competencies and digital innovation from the perspective of happiness management. These findings would contribute to a greater cognitive understanding of the implications of personalised and innovative tourism services on hotel establishments' happiness and economic benefits. Finally, future work could consider comparative studies to see if there are differences within the tourism sector depending on the type of activity carried out.
Figures
List of indicators and constructs
| Constructs | Indicators | Authors* |
|---|---|---|
| Tourism managers' happiness (TMH) | ||
| MH1 | Develop an emotional culture around happiness that encourages employee innovation | Aboramadan and Kundi (2022) |
| MH2 | Develop a collaborative leadership style that stimulates employee happiness | Peng et al. (2023), Ruiz-Rodríguez et al. (2023) |
| MH3 | Stimulate innovation and employee happiness to increase the company's productive output and economic efficiency | Galván-Vela et al. (2022) |
| MH4 | Stimulating employee happiness requires strong organisational support | Kuriakose et al. (2023) |
| MH5 | Implement innovative services to achieve happy customers | Dhiman and Kumar (2023) |
| Internal factors: emotions (IFE) | ||
| IFE1 | Personalised tourism services generate emotions of awe and gratitude that influence behaviour | Stellar et al. (2017), Büssing et al. (2018) |
| IFE2 | Improved quality of tourism services gives visitors self-confidence | Kallou and Kikilia (2021) |
| IFE3 | Trust arises when the customer creates memorable experiences and delivers exceptional service | Gezhi and Xiang (2022) |
| IFE4 | Efficient service delivery through personalised content unleashes emotions such as wonder | Magnini (2017), Sheldon (2020) |
| IFE5 | Compassion generates feelings of pity in the face of harm caused by inadequate service delivery | Goetz et al. (2010) |
| Innovative personalised tourism service (IPTS) | ||
| IPTS 1 | An innovative tourism service requires the necessary knowledge to implement innovation processes | Hall et al. (2008), Hoarau (2016) |
| IPTS 2 | Personalised tourism services require knowledge sharing to meet the needs of seeking new experiences | Hjalager (2002), Cavusgil et al. (2003), Hu et al. (2009) |
| IPTS 3 | To achieve high levels of innovation in the company, knowledge-sharing behaviours among employees must reinforce | Finnegan and Willcocks (2006) |
| IPTS 4 | Organisational factors (organisational culture, incentive systems …), social factors (trust, professional promotion …) and personal factors (positive individual and work attitudes …) allow knowledge to exchange | Obrenovic and Qin (2014), Aboushouk et al. (2019) |
| Personal factors (PF) | ||
| PF1 | Knowledge of customers' factors, such as wishes, expectations and needs of travellers, affects the way the service is provided | Buhalis and Amaranggana (2015) |
| PF2 | Personal factors, such as disposable income, health status and family situation, influence service provision | |
| PF3 | Personal factors such as the ability to solve problems or provide quality service influence positive emotions and happiness | Faullant et al. (2011) |
| PF4 | If personal factors contribute to professional and personal development, it is easier to meet the company's challenges | Sheldon (2020) |
| Organisational Factors (OF) | ||
| OF1 | The use of smart personalised innovative tourism services affects the structure of the organisation and the delivery of the service | Um and Chung (2021), Norouzi et al. (2022) |
| OF2 | Organisations show their commitment to the customer by incorporating personalised tourism services | Bošnjak et al. (2017), Logesh et al. (2019) |
| OF3 | Organisations that prioritise data protection instil confidence in users | Masseno and Santos (2018), Kabadayi et al. (2019) |
| OF4 | Developing reliable technology in the organisation motivates managers and employees | Buhalis and O'Connor (2005), Bronzin et al. (2021) |
Note(s): *The full references listed in this column can be obtained from the contact author
Source(s): Authors’ own creation
Population and sample
| Hotels | Rooms | Employees | Sample | |
|---|---|---|---|---|
| Andalucía | 2,565 | 271,761 | 38,054 | 102 |
| Aragón | 706 | 36,846 | 3,610 | 81 |
| Asturias, Principado de | 586 | 26,333 | 2,996 | 31 |
| Balears, Illes | 600 | 163,099 | 29,613 | 46 |
| Canarias | 577 | 256,116 | 51,221 | 87 |
| Cantabria | 390 | 18,209 | 2,215 | 46 |
| Castilla y León | 1,183 | 57,474 | 6,405 | 36 |
| Castilla - La Mancha | 730 | 32,249 | 2,836 | 21 |
| Cataluña | 2,201 | 261,624 | 33,967 | 20 |
| ComunitatValenciana | 1,086 | 138,645 | 17,179 | 16 |
| Extremadura | 355 | 18,458 | 2,419 | 14 |
| Galicia | 1,476 | 61,386 | 6,643 | 13 |
| Madrid, Comunidad de | 1,131 | 117,049 | 14,540 | 10 |
| Murcia, Región de | 170 | 19,091 | 2,234 | 10 |
| Navarra, ComunidadForal de | 272 | 11,945 | 1,419 | 9 |
| País Vasco | 606 | 33,924 | 4,207 | 7 |
| Rioja, La | 144 | 6,277 | 791 | 6 |
| Ceuta | 10 | 752 | 160 | 2 |
| Melilla | 8 | 809 | 139 | 1 |
| Total | 14,796 | 1,532,047 | 220,648 | 558 |
Source(s): Authors’ own creation
Reliability and validity
| Cronbach's alpha | Composite reliability (rho_a) | Composite reliability (rho_c) | Average Variance Extracted (AVE) | R-squared (R2) | |
|---|---|---|---|---|---|
| IFE | 0.840 | 0.843 | 0.886 | 0.609 | 0.336 |
| OF | 0.751 | 0.753 | 0.843 | 0.574 | 0.249 |
| PF | 0.774 | 0.850 | 0.866 | 0.686 | 0.139 |
| IPTS | 0.774 | 0.789 | 0.870 | 0.693 | – |
| TMH | 0.746 | 0.765 | 0.838 | 0.566 | 0.456 |
Source(s): Authors’ own creation
Fornell-Larcker criterion (FLC) and HTMT
| IFE | OF | PF | SD | TMH | |||||
|---|---|---|---|---|---|---|---|---|---|
| FLC | HTMT | FLC | HTMT | FLC | HTMT | FLC | HTMT | FLC | |
| IFE | 0.781 | ||||||||
| OF | 0.570 | 0.709 | 0.757 | ||||||
| PF | 0.368 | 0.434 | 0.361 | 0.456 | 0.828 | ||||
| IPTS | 0.408 | 0.510 | 0.499 | 0.651 | 0.373 | 0.442 | 0.832 | ||
| TMH | 0.534 | 0.673 | 0.629 | 0.819 | 0.379 | 0.479 | 0.354 | 0.440 | 0.752 |
Source(s): Authors’ own creation
Hypotheses
| Beta | 2.5% | 97.5% | Statistics (|O/STDEV|) | p-values | ||
|---|---|---|---|---|---|---|
| H1 | IFE→TMH | 0.228 | 0.152 | 0.301 | 5.932 | 0.000 |
| H2 | IPTS→IFE | 0.124 | 0.054 | 0.198 | 3.383 | 0.001 |
| H3 | IPTS→PF | 0.373 | 0.296 | 0.450 | 9.432 | 0.000 |
| H4 | IPTS→OF | 0.499 | 0.428 | 0.570 | 13.650 | 0.000 |
| H5 | FP→IFE | 0.159 | 0.086 | 0.231 | 4.326 | 0.000 |
| H6 | FP→TMH | 0.132 | 0.058 | 0.207 | 3.431 | 0.001 |
| H7 | OF→IFE | 0.451 | 0.357 | 0.539 | 9.631 | 0.000 |
| H8 | OF→TMH | 0.452 | 0.382 | 0.523 | 12.589 | 0.000 |
Source(s): Author's own creation
The explanatory capacity of the model
| Adjusted R2 | Direct effect | Correlation | Variance explained | |
|---|---|---|---|---|
| TMH | 0.456 | |||
| OF | 0.452 | 0.629 | 0.284 | |
| IFE | 0.228 | 0.534 | 0.122 | |
| PF | 0.132 | 0.379 | 0.050 | |
| IFE | 0.366 | 0.456 | ||
| PF | 0.159 | 0.368 | 0.059 | |
| OF | 0.451 | 0.570 | 0.257 | |
| IPTS | 0.124 | 0.408 | 0.051 | |
| OF | 0.249 | 0.366 | ||
| IPTS | 0.499 | 0.499 | 0.249 | |
| PF | 0.139 | |||
| IPTS | 0.373 | 0.373 | 0.139 |
Source(s): Authors’ own creation
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