Ikigai and Career Choices in Hospitality and Tourism: A Study of Student Motivations Amidst Industry Disruptions

Abstract

This study explores the motivations of students pursuing a university degree in hospitality and tourism and their intention to build a career in the sector. The research focused on students and recent graduates (up to two years post-graduation) from two universities in Portugal’s largest cities, Lisbon and Oporto, offering Hotel/Tourism Management programs. A quantitative study was carried out, and out of 610 questionnaires distributed, 346 valid responses were analysed using the structural equation modelling technique. Findings indicate that personal motivations, as well as macro and micro perspectives, influence the decision to pursue a degree in hospitality and tourism. Younger individuals with no prior industry experience tend to have a more optimistic outlook compared to older students or those with work experience. A key challenge is sustaining this optimism throughout their careers, which can enhance job satisfaction and improve retention in a sector known for high turnover rates. Unlike previous studies, this research links students’ motivations to their “Ikigai”—the pursuit of purpose and fulfilment. The desire to create meaningful experiences for others adds another dimension to understanding students’ motivations, particularly when considering differences in age and work experience.

1. Introduction

Ikigai, a Japanese concept referring to one’s “reason for being”, has lately gained attractiveness in research related to career development and employee motivation (Liu-Lastres et al., 2023). Likewise, integrating Ikigai into hospitality and tourism studies offers significant academic value by providing new insights into career motivation in terms of intrinsic motivational factors (e.g., personal satisfaction), whilst allowing a more holistic perspective on career success besides extrinsic rewards (e.g., financial) (Liu-Lastres et al., 2023).

Previous studies on Ikigai in career contexts have mostly highlighted general employee motivation across varying sectors (Żegleń et al., 2022). Nonetheless, the literature on the hospitality and tourism industry has focused mostly on common motivational factors and hardly on intrinsic concepts like the Ikigai dimensions of deeper psychological motivators. In this way, most hospitality studies highlight procedures to reduce turnover, such as improving pay, rather than deeper personal fulfilment (Żegleń et al., 2022).

Hence, there is sparse literature linking Ikigai to hospitality and tourism employee career choices, with narrow geographical scope, mostly carried out in Asia, with little or no cross-cultural evidence (Wilkes et al., 2023). In spite of mounting academic interest, a noteworthy gap remains with respect to Ikigai’s integration into hospitality and tourism career literature. This study intends to originally fill this gap by exploring how Ikigai influences students’ career intentions on hospitality and tourism in the specific and resource shortage of the Portuguese context. It contributes by empirically investigating how Ikigai influences career decisions among hospitality students, addressing its interplay with industry talent retention and recruitment challenges.

Indeed, the tourism and hospitality industry has long been associated with low wages, long working hours, weekend shifts, and emotional labour, making it an often unattractive career choice for prospective employees (Liu-Lastres et al., 2023). However, this sector plays a key role in Portugal’s economy, having been the country’s leading export sector in recent years, stimulating not only economic growth but also the appreciation of territories and communities. Thus, attracting and retaining talent in industry has been a significant challenge.

According to the Portuguese Hospitality Association (AHP), the hotel industry faced a shortage of more than 15,000 workers in 2022—a challenge that reflects a broader global issue. Several factors contribute to this labour gap. Firstly, many Baby Boomers are reaching retirement age, reducing the available workforce. Additionally, the industry has become more complex and demanding, with increased health risks, particularly in the wake of the COVID-19 pandemic. Economic conditions also play a role, as low unemployment and the rapid growth of other industries make it harder to attract talent to hospitality. Furthermore, the sector is often associated with low wages and high turnover, making it less appealing to younger generations. As a result, fewer young people are pursuing careers in hospitality, further exacerbating the human resources shortage.

Accordingly, this study aims to understand the motivations behind individuals choosing to pursue a university degree in hospitality and tourism and their intentions to build a career in the sector, so important to the hospitality and tourism sector and to the economy in general in Portugal. Also, in light of the Ikigai concept, it examines these motivations from both macro and micro perspectives. The macro perspective includes global trends such as economic and regulatory factors, globalisation, technological advancements, socio-cultural influences, and environmental sustainability. Meanwhile, the micro perspective focuses on individual preferences, business operations (e.g., service quality), and financial performance (e.g., revenue management) (Żegleń et al., 2022).

Therefore, this study explored how motivations to work in hospitality also align with the concept of “Ikigai”—a Japanese philosophy that combines “iki” (life) and “gai” (worth), representing a meaningful and fulfilling life. Factors such as openness to new cultural experiences, professional growth opportunities, and environmental awareness are linked to “Ikigai”, highlighting its potential to enhance mental well-being (Wilkes et al., 2023; Konar et al., 2018). The main findings are discussed and conclusions are established.

This article includes the following: an introduction, literature review, methodology, results and analysis, key findings, conclusions, theoretical and practical implications, study limitations, and future research directions.

2. Literature Review

The hospitality industry, particularly within hotel and tourism sectors, is a rapidly evolving service domain driven by innovation and customer-centric experiences. Yet, despite its dynamic nature, this industry often encounters enduring challenges, including low wages, employment instability, and limited career progression opportunities, which significantly impact workforce motivation and satisfaction. This review explores the complex relationship between employee motivation and career choices within hospitality, delving into core theoretical frameworks such as Herzberg’s two-factor theory, the Japanese concept of Ikigai, and transformational leadership. Emphasis is placed on macro and micro motivational factors and the emerging influence of artificial intelligence (AI), thereby setting the stage for empirical research within the Portuguese context.

Leadership is a cornerstone of employee motivation and satisfaction, deeply rooted in Herzberg’s two-factor theory. This theory distinguishes between hygiene factors—elements such as salary, workplace conditions, and job security—which must be adequately managed to prevent dissatisfaction, and intrinsic motivators such as recognition, achievement, and responsibility, which actively enhance job satisfaction and engagement (Makrinova & Grigorieva, 2015; Valk & Yousif, 2023). For example, hospitality managers who provide fair salaries (a hygiene factor) and simultaneously acknowledge outstanding employee performance through recognition programs (an intrinsic motivator) create an environment conducive to motivation. Transformational leadership extends this concept by inspiring employees with vision, facilitating personal and professional growth and aligning organizational goals with individual values, thus closely mirroring the principles of Ikigai, which emphasizes purposeful work (Ntalakos et al., 2023; Zhou et al., 2024). Practical hospitality examples include hotel managers fostering open dialogue about career aspirations, mentoring staff for leadership roles, and publicly recognizing team achievements, thereby strengthening employee loyalty and performance, particularly during stressful transitions such as AI integration (Dartey-Baah & Addo, 2019).

Beyond leadership, fostering team collaboration and a supportive organizational climate significantly enhance employees’ sense of belonging and professional purpose. Macro-level motivational strategies, including structured training programs, professional development opportunities, and comprehensive recognition systems, intersect closely with micro-level dynamics such as peer relationships, teamwork, and daily interactions, substantially influencing employee motivation (Aboobaker & KA, 2023; Khuong & Linh, 2020). Hotels actively promoting peer mentorship and offering structured career paths exemplify Ikigai’s focus on achieving mastery and purpose through work that benefits others, thus cultivating environments of loyalty and resilience during periods of significant change, such as adopting international service standards or technological innovation (Norbu & Wetprasit, 2020; Teixeira, 2019). A practical example includes major hotel chains implementing robust training and peer support systems, leading to higher retention rates and employee satisfaction.

Although Herzberg classifies salary primarily as a hygiene factor, it frequently operates as a central motivator in practical contexts such as student or entry-level employment within hospitality (Zhou et al., 2024). Micro-level motivators, including equitable pay, flexible scheduling, and respectful workplace culture, play crucial roles in attracting and retaining young talent. These motivators support Ikigai’s foundational principle of achieving a balance between financial stability and personal fulfilment. For instance, hotels providing competitive compensation, flexible part-time positions, and a supportive atmosphere significantly enhance entry-level employee engagement and loyalty, contributing to a skilled, adaptable workforce (Bentalha, 2023).

Effective job design significantly enhances intrinsic motivation by incorporating elements such as autonomy, task identity, and regular, meaningful feedback (Zhao, 2016). Hospitality roles that promote creativity and personal ownership, such as event planning or customer experience development, exemplify these job design principles by enabling employees to directly see the outcomes and impacts of their efforts. Hotels that actively encourage innovation and solicit input from frontline employees for service improvements reinforce psychological ownership, aligning closely with Ikigai’s emphasis on passion-driven and purposeful work (González-González & García-Almeida, 2021; Bermúdez-González et al., 2023). Practical implementations include regular brainstorming sessions, feedback loops, and incentives for innovation, resulting in continuous service enhancements and heightened employee morale.

An effective motivational approach blends tangible incentives like competitive salaries and bonuses with intangible rewards, such as recognition and empowerment (Makrinova & Grigorieva, 2015; Burlea-Schiopoiu et al., 2022). Macro-level incentives, including clearly structured appraisal and promotion systems, are complemented by micro-level motivational practices like personalized employee recognition events, regular feedback sessions, and targeted personal development plans. During macro disruptions like the COVID-19 pandemic or AI integration phases, employees with clear personal missions and intrinsic motivations aligned with Ikigai demonstrate greater resilience and sustained performance (Hazra et al., 2014; Su et al., 2022). A practical hospitality industry example includes hotels introducing comprehensive support systems during COVID-19, providing both financial reassurance and emotional support, significantly enhancing employee motivation and resilience.

The adoption of AI technology carries dual motivational implications within hospitality. Positively, AI increases operational efficiency by automating routine tasks, allowing staff to engage in more meaningful and customer-oriented interactions. Negatively, it raises concerns regarding job security and the potential loss of personalized service delivery (Cesário et al., 2022; Gajić et al., 2024). Effective macro-level technological integration strategies, coupled with supportive micro-level practices such as transparent communication, inclusive decision-making processes, and targeted retraining programs, are essential for mitigating employee anxiety and enhancing morale. For example, implementing AI-assisted concierge services alongside clear retraining programs and regular staff briefings ensures employees understand their evolving roles, thereby maintaining motivation and job satisfaction across different cultural contexts (Wang et al., 2023; Cassel et al., 2017).

Organizational culture, characterized by openness, trust, and continuous learning, strongly correlates with employee satisfaction and performance (Bhardwaj et al., 2023; Dawson et al., 2023). Macro-level practices like succession planning and structured employee empowerment directly affect motivation, while micro-level managerial practices, including regular check-ins, personalized coaching sessions, and clear goal-setting procedures, foster psychological safety and productivity. Hospitality organizations integrating talent management strategies closely aligned with their cultural values experience a reinforcing cycle of motivation, retention, and overall organizational effectiveness (Sinclair-Maragh et al., 2017; Kim & Lucas, 2024; Barron et al., 2014).

Demographic factors, including gender and age, significantly influence motivational preferences. Research indicates that men frequently prioritize financial incentives, while women often value supportive and inclusive work environments (Hilman & Kaliappen, 2014). Thus, motivational approaches must be contextualized to account for demographic differences. Additionally, adapting motivational frameworks like Ikigai to non-Japanese contexts, such as Portugal, demands further exploration to ensure cultural resonance and applicability. Variations in generational aspirations and career stages further highlight the importance of tailored motivational strategies, especially in regions economically dependent on tourism (Andringa et al., 2016; Zhang et al., 2024; Harrington et al., 2014).

Ultimately, fostering motivation in hospitality demands a holistic approach that integrates psychological theories, cultural values, leadership practices, and technological preparedness. Ikigai offers valuable insights into intrinsic motivation. Herzberg’s theory provides guidance on balancing extrinsic and intrinsic factors, and transformational leadership ensures the practical application of these insights. Future research should explore longitudinal motivational changes, the cross-cultural applicability of Ikigai, and the impact of AI on hospitality roles, thereby creating sustainable and purpose-driven workforce practices.

3. Materials and Methods

3.1. Data Collection Procedure

This study was conducted within Lisbon (capital of Portugal) and Porto (second biggest city in Portugal) in two higher education institutes with degrees in hotel management (3 years). A questionnaire was discussed with a focus group of 20 students in the last year of their hotel management degree (academic year of 2023–2024) in Lisbon. A first version of the questionnaire was built and adjusted according to the feedback received and tested. Then, the questionnaire (final/tested version) was sent to the alumni students of the academic years (recent graduated students) of 2021–2022 and 2022–2023 and the current academic year students of 2023–2024 (three years). For these current students, the questionnaires were completed online in classrooms involving the teachers. One of the researchers was at the classroom to explain the survey objectives. For the alumni students, the questionnaire was sent by email. About 610 students were enrolled and 346 valid responses were received.

The questionnaire has an introductory part explaining the objectives of the study, explaining the confidentiality terms and sharing the main researcher contact. It includes two parts, one with descriptive statistics such as gender, age, studying/working, years of professional experience, and the second part was about the motivations to either study or work in the hospitality and tourism sector, after or during the hotel management studies (15 questions), using a 5 point Likert scale (1—strongly disagree, 2—disagree, 3—not agree or disagree, 4—agree, 5—strongly agree). Thus, answers below 3 were considered as disagreement statements, 3 as neutral statements, and above 3 as agreement statements. The subsequent sample characteristics (gender, age, occupation, sector and work experience) are detailed in

Table 1. Sample characteristics.

	Frequency	Valid Percentage
Gender
Male	211	61.0%
Female	134	38.7%
Other	1	0.3%
Age
18–30	248	71.7%
31–49	73	21.1%
50–67	25	7.2%
Occupation
Student	124	35.8%
Student and Worker	130	26.6%
Only Worker	92	37.6%
Sector
Hospitality/Food and Beverage	222	64.2%
Tourism	56	16.2%
Other	68	19.7%
Work Experience
No experience	67	19.4%
Only internship (<1 year)	34	9.8%
1 to 5 years	134	38.7%
6 to 15 years	55	15.9%
>15 years	56	16.2%

Source: own elaboration.

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3.2. Data Analysis and Results

Concerning part II, SPSS26 (Statistical Package for the Social Sciences) was used to analyse the data. Principal Components Analysis (statistic instrument) was used by transforming a large set of variables into a smaller one that nevertheless contains most of the information in the large set.

Kaiser–Meyer–Olkin testing obtained a KMO and Bartlett = 0.887, verifying the internal consistency of the components (George & Mallery, 2019). Using the Varimax method to rotate the principal components allowed for an easier interpretation to analyse principal components, obtaining four principal components. The consistency was tested using Cronbach’s Alpha, regardless of the type of study, whether it is exploratory research, applied research, or scale development research; a criterion of 0.7 is universally employed (Lance et al., 2006). Below, the Cronbach’s Alpha values were found to be higher or equal to 0.7 in all components.

Component number 1 is connected to the sector itself, connected with Macro Perspectives such employment, sector growth, international career opportunities, and sometimes also connected with government policies, initiatives, and incentives.

Component number 2 relates to the Japanese word “Ikigai”. “Ikigai” is a Japanese word made up of “iki” (live) and “gai” (reason), the purpose of living and connected with a happy long life, a life with objectives and a purpose worth living for.

Component number 3 relates to Micro Perspectives, that is, means connected with the company policies itself.

Component number 4 is connected to being inside the comfort zone, pleasing the family, work that is easy to do, and stability. The four components are detailed in

Table 2. Motivations for higher education students, studying and working in the hospitality and tourism sector.

Principal Components	Mean	Loading	% Variance Explained	Cronbach Alpha
Component 1: Macro Perspective (MA) Q1. Employment opportunities Q6. I love to deal with people Q10. International career opportunities Q11. Sector growth Q12. Multicultural environments	3.68 3.82 3.77 4.06 3.92	0.614 0.618 0.609 0.745 0.807	21.5%	0.837
Component 2: “Ikigai” (IKI) Q5. Objective of life Q13. A dream came true Q14. My first option Q15. I love to “serve” people, contributing to their happiness	3.29 3.18 3.07 3.54	0.760 0.754 0.767 0.637	18.5%	0.839
Component 3: Micro Perspective (MI) Q2. Better salaries Q3. Career growth Q4. Balance personal and professional life	2.90 3.55 2.61	0.752 0.672 0.719	15.6%	0.747
Component 4: Comfort Zone (COMF) Q7. Family influence Q8. Work easy to do Q9. Contractual stability	2.33 2.60 2.88	0.824 0.672 0.707	12.0%	0.648

Source: own elaboration.

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SPSS26 (Statistical Package for the Social Sciences) software was used for statistical analysis of the data, as well as performance components analysis. Structural Equation Modelling (SEM) was employed to conduct confirmatory factor analysis. These two data analysis methods were utilised to test the consistency and validity of the principal components model. SEM (Structural Equation Modelling) was chosen because it is a set of statistical techniques used to measure and analyse the relationships of observed and latent variables, allowing us to see the model in a very simple and graphic way. Some indicators are calculated in SEM to evaluate the model fit such as the following: RMSEA was calculated to measure model quality, AVE is the average variance extracted, and CR is the Composite Reliability that describes the ability of measured variables to present the latent factor. AVE measures the level of variance captured by a construct versus the level due to measurement error; values above 0.7 are considered very good, whereas the level of 0.5 is acceptable. CR is a less biased estimate of reliability than Cronbach’s Alpha; the acceptable value of CR is 0.7 and above. The GFI compares the discrepancy between the observed covariance matrix (which represents the actual relationships between variables) and the predicted covariance matrix (which represents the relationships predicted by the model). The CFI (Comparative Fit Index) compares the fit of a target model to the fit of an independent or null model, and the TLI (Tucker Lewis Index) also ranges between 0 and 1, with values greater than 0.90 indicating good fit.

Component 4 was removed by the model because this action improved model parsimony and reduced the complexity of the SEM model, and then the items that provided the most information about the latent construct were retained. Retaining the most informative items ensures that the construct is adequately represented.

The Average Variance Extracted (AVE) values above 0.5 and Composite Reliability (CR) values above 0.7 indicate acceptable convergent validity (Fornell & Larcker, 1981). AVE has the advantage of considering measurement error in variables (Bollen, 1989), while CR provides a more unbiased reliability estimate than Cronbach’s Alpha (Rosli et al., 2021). Component 4: Comfort Zone was excluded from the model due to a Cronbach’s value below 0.70, AVE below 0.5, and CR below 0.7. In fact, while using the Likert scale from 1 to 5 (1—strongly disagree, 2—disagree, 3—not agree nor disagree, 4—agree, 5—strongly agree), the ensuing mean within this component resulted below 3, working out, in average, a disagreement, in which those variables do not foster the motivation to study or work in the sector.

The following hypotheses were tested and explained at Figure 1:

H1: 

Motivations for Higher Education Students to study and work in the Hospitality and Tourism Sector in the future can be explained by the latent variable, Macro Perspectives (MA);

H2: 

Motivations for Higher Education Students to study and work in the Hospitality and Tourism Sector in the future can be explained by the latent variable, IKIGAI (IKI);

H3: 

Motivations for Higher Education Students to study and work in the Hospitality and Tourism Sector in the future can be explained by the latent variable, Micro Perspectives (MI).

The overall fit of the model is very good according to Marôco (2018); the regression weight for Motivations in the prediction of Macro, “Ikigai”, and Micro is significantly different from zero at the 0.001 level (two-tailed). Thus, all the components are significantly relevant concerning the motivations for higher education students’ study and in the future work in hospitality and tourism sector. The quality of the adjustment and model statistics are explained in

Table 3. Model statistics.

Model	χ²	df	χ²/df	GFI	TLI	CFI	RMSEA
	29.803	24	1.064	0.985	0.998	0.999	0.014
Quality of the Adjustment			Very good	Very good	Very good	Very good	Very good

Source: AMOS26 ou.put.

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Convergent validity was determined by examining (1) the Standardised Factor Loading (SFL); (2) the Average Variance Extracted (AVE) for each dimension; and (3) the Composite Reliability (Raykov, 1997). Relevant figures and confirmed AVE values equal/higher than 0.5 and CR equal/higher than 0.7 are summarised at

Table 4. Convergent validity.

PC	Variables	SFL	AVE	CR
Component 1: Macro Perspective (MA)			0.580	0.846
	Q1. Employment opportunities	0.694
	Q10. International career opportunities	0.842
	Q11. Sector growth	0.809
	Q12. Multicultural environments	0.689
Component 2: “Ikigai” (IKI)	Q5. Objective of life	0.828	0.596	0.797
	Q13. A dream came true	0.835
	Q14. My first option	0.640
	Q15. “Serve” people, contributing for their happiness	0.769
Component 3: Micro Perspective (MI)	Q2. Better salaries	0.692	0.506	0.693
	Q3. Career growth	0.913
	Q4. Balance personal and professional life	0.455

Note: PC = Principal Component; SFL = Standardised Factor Loading; AVE = Average Variance Extracted; CR = Composite Reliability.

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The square roots of the AVE data of every dimension were greater than the absolute values of their correlation coefficients with other dimensions, which denoted satisfactory discriminant validity, as detailed at

Table 5. Discriminant validity.

	MA	IKI	MI
MA	0.762
IKI	0.469	0.772
MI	0.398	0.446	0.712

Note: Bivariate Pearson correlation, one tail. 1: MA: Macro Perspective, IKI: Ikigai, MI: Micro Perspective. 2: The diagonal figures are the square roots of AVE data.

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The regression weights for Motivations in the prediction of the three components (Macro, “Ikigai”, and Micro) are significantly different from zero at the 0.001 level (two-tailed). The most important (more weighted) are the Macro Perspective (0.91), followed by the Micro Perspective (0.80), and finally “Ikigai” (0.78). Thus, all of the Motivations are relevant and significant for the student motivations to study/work in the sector.

In summary, concerning the three components, the following tendencies concerning motivation to study/work in the sector were found, as detailed in Figure 2.

Concerning age, there is an inflection (decrease) for all components at the age span of 31–49 with respect to the motivation to study/work in the sector. This should be the age where the work experience is higher. With the work experience the motivation decreases, excluding the “Ikigai”, which increases again in the most experienced students (more than 15 years). The most motivational sector is tourism, compared with hotels and restaurants and others. The motivational factors decrease if the students are also working.

In summary, through the Structural Equation Model output, we could conclude that all components are relevant to the model as the variables of each one, so Motivations for Higher Education Students to study and work in the Hospitality and Tourism Sector can be explained by the latent variables Macro Perspectives (MAs): Hypothesis 1, IKIGAI (IKI): Hypothesis 2, and Micro Perspectives (MIs): Hypothesis 3.

The variable weights above 0.8 concern the Macro perspective: International Career Opportunities and Sector Growth, so governmental policies through the Portuguese Tourism Office will be key to maintaining growth in the sector and consequently career opportunities through the multinational companies attracted to the Portuguese market.

Concerning the Micro Perspective (companies’ perspective), career growth (more than 0.9) is the focus, so companies trying to attract and retain students should offer career plans. For example, better salaries and work–life balance scored less than 0.7. Therefore, addressing the issues of low salaries and poor work–life balance due to scheduling should be the second priority, provided that students feel confident they will have opportunities for career advancement.

Concerning Ikigai, “Objective of life and “A dream came true” are the variables with more weight, confirming that this can be their purpose of life, the basis of the Japanese concept of “Ikigai”. With “Ikigai”, people can find happiness working or doing just a little thing that makes sense for them to keep enjoying life.

A crossover study was conducted to understand the differences and similarities within the components related to age, work activity, sector, and work experience.

Crossover Study

With respect to gender, after running Levene’s test (variances equality) and t-tests (means equality), no significant differences were found.

One-way ANOVA was performed to determine if there were significant differences in the groups per component related to age, work activity (student, worker and student, or worker and not a student), sector (hotels and restaurants, tourism, or other), and work experience. We tested the equality of population means and homogeneity of variances. Levene’s test is used to check the equality of variances in samples. For the post hoc tests, multiple comparisons were conducted using Sheffe’s test, which is a single-step multiple comparison procedure that applies to the set of estimates of all possible contracts among the factor level means, not just the pairwise differences Bonferroni’s test can also be used to assess whether the group sample sizes are equal. Similarly, Dunnett’s test may be applied when the assumption of equal population variances is violated, as seen in Component 1 (Macro Perspective) related to age and activity, while homogeneity of variances was confirmed for all other components (p-value > 0.05). In summary, the significant differences between the groups are summarised in

Table 6. Crossover study results.

		Homogeneity of Variances		ANOVA
Principal Components	Variable	Levene	p-Values	F	p-Values	Post Doc Tests	Types of Post Hoc Tests
MA	Age
(Macro Perspective)	1: 18–30	5.153	0.006	4.334	0.014	More Employment Opportunities	Scheffe/Dunett C.
	2: 31–49					1 > 2 (p-value = 0.025 **)
	3: 50–67		>0.05	7.701	0.001	More Opportunties of International Career	Scheffe
						1 > 2 (p-value = 0.002 **)
MI	1: 18–30		>0.05	8.707	0.000	Better Salaries	Scheffe
(Micro Prespective)	2: 31–49					1 > 2 (p-value = 0.004 **)
	3: 50–67					1 > 3 (p-value = 0.012 **)
		3.536	0.030	6.709	0.001	More Opportunites of career	Scheffe/Dunett C.
						1 > 2 (p-value = 0.002 **)
MA	Activity
(Macro Perspective)	1: Student		>0.05	9.328	0.000	More Employment Opportunities	Scheffe
	2: Worker and Student					1 > 3 (p-value = 0.000 **)
	3: Worker and not a Student					2 > 3 (p-value = 0.017 **)
		5.078	0.007	16.467	0.000	More Opportunties of International Career	Scheffe/Dunett C.
						1 > 3 (p-value = 0.000 **)
						2 > 3 (p-value = 0.009 **)
			>0.05	11.812	0.000	Sector on growing	Scheffe
						1 > 3 (p-value = 0.000 **)
MI
(Micro Prespective)	1: Student		>0.05	22.933	0.000	Better Salaries	Scheffe
	2: Worker and Student					1 > 3 (p-value = 0.000 **)
	3: Worker and not a Student					2 > 3 (p-value = 0.000 **)
			>0.05	17.010	0.000	Career Growth	Scheffe
						1 > 3 (p-value = 0.000 **)
						2 > 3 (p-value = 0.001 **)
			>0.05	17.068	0.000	Balance professional/personal life	Scheffe
						1 > 3 (p-value = 0.000 **)
						2 > 3 (p-value = 0.000 **)
MA	Sector
(Macro Perspective)	1: Hotels and Restaurants		>0.05	3.038	0.049	More Opportunties of International Career	Bonferroni
	2: Tourism					2 > 3 (p-value = 0.046 **)
	3: Other		>0.05	7.609	0.001	Sector growth	Scheffe
						1 > 3 (p-value = 0.015 **)
						2 > 3 (p-value = 0.001 **)
			>0.05	5.083	0.007	Multicultural Environments	Scheffe
						2 > 3 (p-value = 0.007 **)
IKI			>0.05	4.877	0.008	Objetive of life	Scheffe
(IKIGAI)	1: Hotels and Restaurants					2 > 3 (p-value = 0.008 **)
	2: Tourism		>0.05	6.257	0.002	A dream come true	Scheffe
	3: Other					2 > 1 (p-value = 0.0013 **)
						2 > 3 (p-value = 0.0003 **)
			>0.05	4.491	0.012	First Option	Scheffe
						2 > 3 (p-value = 0.0010 **)
	Work Experience
MI	1: Without Experience		>0.05	7.681	0.000	Better Salaries	Scheffe
(Micro Prespective)	2: 1 to 5 years					1 > 2 (p-value = 0.012 **)
	3: 6 to 15 years					1 > 3 (p-value = 0.000 **)
	4: >15 years					1 > 4 (p-value = 0.001**)
	5: Only internership (<1 year)		>0.05	6.640	0.000	Career Growth	Scheffe
						1 > 2 (p-value = 0.005 **)
						1 > 3 (p-value = 0.003 **)
						1 > 4 (p-value = 0.001 **)
			>0.05	7.735	0.000	Balance professional/personal life	Scheffe
						1 > 2 (p-value = 0.002 **)
						1 > 3 (p-value = 0.000 **)
						1 > 4 (p-value = 0.002 **)

Note: The comparatives values are based in the mean. ** Significant Difference at the 0.05 level.

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Age

Macro Perspective

The biggest mean difference is between the rating for the younger aged 18–30 (3.80) and the rating for those aged between 31 and 40 (3.45).

The younger aged 18–30 agree more strongly (3.93) that “Employment opportunities” and “International career opportunities” contribute to their choice to study and work in the sector in the future. The age range of 31–40 (3.40) is closer to the neither agree nor disagree rating.

Macro Perspective influences the youngest much more in their decision to study/work in the sector of hospitality and tourism.

“Ikigai”

Large differences were not detected within this component related to age; however, “Objective of life” and “I love to ‘serve’ people, contributing to their happiness” have higher means for the age range of 50–67 (3.46 and 3.63, respectively). “A dream came true” (3.26), and “My first option” (3.20) rated higher for the age range of 18–30. Again, the age range of 31–40 registered lower ratings and in opposition to the age range of 18–30 for “A dream came true” (2.95) and “My first option” (2.95).

Micro Perspective

The mean for “Better salaries” decreased with the age: 18–30 (3.02), 31–40 (2.59), and 41–67 (2.38). “Career growth” and “Balance of personal and professional life” had the highest means for the age range of 18–30 (3.70 and 2.69, respectively) and were lowest for the age range of 31–49 (3.23 and 2.36, respectively).

Activity

Macro Perspective

“Employment opportunities” and “International opportunities” decrease with the work activity (means—students: 3.93 and 4.17, respectively; worker and student: 3.80 and 3.85, respectively; and worker and not student: 3.43 and 3.38, respectively). “Sector growth” had the highest mean for students (4.38) and the lowest for worker and not student (3.80). For all variables of this component, the lowest means is for worker and not student.

“Ikigai”

For all variables of this component, the lowest mean is for worker and not student and the highest mean is for student.

Micro Perspective

“Better salaries”, “Career growth”, and “Balance personal and professional life” decrease with the work activity (means—students: 3.30, 3.10, and 2.44, respectively; worker and student: 3.89, 3.69, and 3.20, respectively; and worker and not student: 2.93, 2.82, and 2.17, respectively).

Sector

Macro Perspective

The highest means are for the tourism sector and the lowest are for other sectors for all the variables in this component, with the hotels and restaurants sector in the middle.

For “Employment opportunities”, “International opportunities” and “Multicultural environments”, the means are for tourism: 3.88, 4.38, and 4.23, respectively, and other sectors (not hotels, restaurants, or tourism): 3.55, 3.72 and 3.69, respectively.

“Ikigai”

The highest means are for the tourism sector and the lowest are for other sectors for all the variables in this component, with the hotels and restaurants sector in the middle.

For “Objective of life”, “A dream came true” and “My first option”, the means are tourism: 3.68, 3.66, and 3.50, respectively, and other sectors (not hotels, restaurants, or tourism): 3.03, 2.94, and 2.78, respectively.

Micro Perspective

The highest means are for the tourism sector and the lowest are for other sectors for all the variables in this component, excluding balance of professional and personal life—for this variable, the lowest mean is in the hotels and restaurants sector.

For “Better salaries”, “Career growth”, and “Balance personal and professional life”, the means are tourism: 3.07, 3.68, and 3.05, respectively; hotels and restaurants: 2.91, 3.60, and 2.46, respectively, and other sectors: 2.84, 3.39, and 2.76, respectively.

Work Experience

Macro Perspective

The highest means are in the range of no experience of working or only internship experience (less of one year). The lowest rates for “Employment opportunities” and “Sector growth” are between 6 and 15 years of work experience (means: 3.51 and 3.85, respectively) and increasing to 3.60 and 4.00, respectively, with more than 15 years of work experience.

“Ikigai”

The highest means are in the range of no experience of working or only internship experience (less of one year), becoming lower until 15 years of work experience. For more than the 15 years of experience, there is an inflection of the decrease, increasing a little bit.

Micro Perspective

The highest means are in the range of no experience of working or only internship experience (less of one year), becoming lower with the years of work experience.

For “Better salaries”, “Career growth”, and “Balance personal and professional life”, the means are no experience: 3.49, 4.08, and 3.25, respectively; 1 to 5 years: 2.90, 3.51, and 2.54, respectively; 6 to 15 years: 2.65 3.36, and 2.22, respectively; and more than 15 years: 2.49, 3.27, and 2.38, respectively).

4. Conclusions

According to the results of the studied sample, students consider Macro, Micro, and “Ikigai” factors when deciding to study and pursue a career in the hospitality and tourism sector. Macro factors relate to national and industry policies such as employment rates, sector growth, and international opportunities—hold the highest significance. This suggests that government policies and economic expansion play a crucial role in attracting individuals to the field; Micro factors, which include company policies like salary structures and work–life balance, tend to be discouraging aspects of the sector. However, career growth opportunities emerge as a strong motivating factor; “Ikigai”, which reflects personal aspirations, life goals, and the intrinsic desire to serve and contribute to others’ happiness, also ranks highly. Many students and professionals in this sector see their work as a meaningful mission.

Younger individuals in particular tend to be more optimistic about career prospects in hospitality and tourism, but this optimism tends to decline as they gain work experience. Despite this, the tourism sector remains highly attractive due to its growth and opportunities, followed closely by hospitality (hotels and restaurants), while other related industries appear less appealing.

Hospitality and tourism students generally express strong optimism about what the sector can offer, including employment prospects, career advancement, and the fulfilment of personal dreams and aspirations within the “Ikigai” framework. To sustain this optimism beyond graduation and into the workforce, the industry must nurture personal and professional growth.

To reduce employee turnover and create positive experiences for customers, businesses must invest in employee satisfaction and well-being. A motivated and fulfilled workforce is essential for delivering high-quality service and creating value in end-customer markets. Industry leaders and HR professionals should, therefore, focus on recognising and rewarding employees for their dedication and hard work; fostering a positive work environment to strengthen loyalty and reduce turnover; implementing responsible HRM policies, balancing extrinsic (salary, benefits) and intrinsic (fulfilment, growth) motivations; and addressing job insecurity, which negatively impacts employee retention.

The study also highlights a shift in “Ikigai”- driven motivation across different life stages: between ages 31 and 49, individuals tend to experience a decline in intrinsic motivation as they reach career maturity and evaluate new job opportunities; yet, between ages 50 and 67, personal purpose and fulfilment regain importance, suggesting a renewed appreciation for meaning in work.

Hence, a key challenge for the industry builds upon sustaining “Ikigai”- driven motivation throughout employees’ careers, ensuring that passion and purpose remain strong despite the realities of long-term work experience. Hospitality and tourism companies should therefore focus on developing people, offering career plans, better salaries, and scheduling, which provide ensuing life balance, as already posited in previous pieces of literature (Chen et al., 2021) whereas confirming the mediating effect of employability on the relationship between career intention and retention in the hospitality and tourism industry. Furthermore, it indicates that stakeholders should work aiming at building up students’ career planning and confidence, whilst cultivating interns’ positive work attitude.

Moreover, young people are giving more importance to life balance, pursuing their dreams (Ikigai). Passion for “serving” people is key to offering excellent hospitality service, and this was highlighted in the research results, depicted as a motivational factor to be part of the sector. Passion is a motivational force driving people toward success and satisfaction. Organisations could thus control certain antecedents to passion, which is related with, yet distinct from concepts such as employee engagement and organisational commitment (Crawford et al., 2024).

5. Implications

5.1. Theoretical Implications

The tourism and hospitality industry has long been characterised by low wages, long hours, weekend work, and emotional labour (Liu-Lastres et al., 2023). Despite these challenges, our study reveals through the “Ikigai” dimension that this sector remains a lifelong aspiration for many—viewed as a dream come true, a first-choice career, and a fulfilling opportunity to serve others and contribute to their happiness. Among the different sub-sectors, the tourism industry ranks highest in terms of “Ikigai” motivation, followed by hotels and restaurants, with other sectors ranking the lowest.

First, contrary to the findings of (Hilman & Kaliappen, 2014) that suggest men prioritise salary while women focus on work environment, our study did not identify significant motivational differences based on gender. However, age and career stage play a crucial role in shaping motivations: younger individuals (18–30 years old) prioritise career development, international opportunities, employment stability, and higher salaries. This aligns with the Career Construction Theory, which emphasises the integration of personal needs with career expectations (Wang et al., 2023; Mogi, 2017). Whereas older professionals (31+ years old), who are generally more established in their careers, place less emphasis on these factors, students show a stronger preference for sector growth and job opportunities, compared to alumni who completed their degrees one to two years ago and are currently working. This suggests that students have higher expectations about career prospects as they prepare to enter the job market.

Second, work–life balance is not a primary motivator for choosing a career in this sector, as indicated by mean scores below 3.0. However, perceptions of work– life balance vary across age groups: the 31–49 age group reports the lowest satisfaction with work–life balance; the 18–30 and 50–67 age groups also rate it low but slightly higher than the 31–49 group; finally, students without work experience are more optimistic about work– life balance, whereas this optimism declines with minimal exposure to the industry (e.g., internships).

Third, with regard to altruistic vs. ego-driven motivations, our findings partially align with (Raub et al., 2023), who highlight that millennials prioritise ego-driven work values such as career development, compensation, and work–life balance. However, for altruistic motivations (e.g., “I love to serve people and contribute to their happiness”), there were no significant generational differences.

Finally, the lowest agreement with this statement was observed among individuals aged 31–49 with 6–15 years of work experience (students working alongside their studies). Conversely, young individuals without work experience and older professionals (50+ years) with more than 15 years of experience showed the strongest agreement with the idea of serving others as a source of fulfilment.

One can conclude that while the tourism and hospitality sector remains attractive due to its growth, career opportunities, and alignment with personal aspirations, the challenge lies in maintaining optimism and intrinsic motivation as employees gain experience in the field. Strategies to enhance job satisfaction, support career progression, and foster a sense of purpose will be critical in retaining talent and reducing turnover.

5.2. Practical Implications

The Portuguese Tourism Office built the Tourism strategy for Portugal. At this moment, the strategy is in place until 2027; due to actual tourism growth, most of the goals have already been achieved in 2024. The pillars of the Portuguese Tourism Office are to ensure stability and commitment regarding strategic options for national tourism; promote integration of sectoral policies; generate continuous coordination between the various tourism agents; and act with a strategic sense in the present and in the short/medium term. In 2024, the tourism sector recorded positive developments, with increases of 4.0% in overnight stays, 5.2% in guests, and 8.8% in tourist revenue, strengthening and consolidating Portugal’s position as a competitive destination at an international level. There were 31.6 million guests, of which 19.4 million were foreigners, representing increases of 5.2% and 6.3%, respectively, compared to 2023 (Chen et al., 2021).

Both international career opportunities and sector growth are key motivations for higher education students to carry on studies and work in the hospitality and tourism sector; governmental policies through the Portuguese Tourism Office will be central to maintaining the growth in the sector and ensuing career opportunities through varying multinational companies operating in the Portuguese market. Career plans should therefore be a priority for hospitality and tourism companies to either attract or retain human resources in this area. Career optimism positively influences career adaptability and future career intentions (Crawford et al., 2024).

Students view a career in the hospitality and tourism sector as a life goal and a dream fulfilled. These intrinsic motivations and emotions should be preserved as they gain experience. However, the results show that between the ages of 31 and 49—typically the peak of their careers—many lose their desire to remain in the sector. This decline in motivation may be linked to a diminished sense of Ikigai, possibly because the career progression they once envisioned has not materialized. After the age of 50, Ikigai appears to rise again, perhaps because career advancement is no longer expected, and the simple pleasure of serving others becomes paramount. Ikigai, in this context, can be seen as finding happiness and fulfillment without expecting anything in return (Turismo de Portugal, 2025). Nevertheless, further research is needed to draw definitive conclusions.

6. Limitations and Future Directions

Further research is essential due to several limitations of the current study. Firstly, external factors such as parental expectations and economic pressures, including cost of living, may significantly impact career choices beyond the previously discussed industry-specific and individual factors. Secondly, social desirability bias might have influenced respondents, potentially causing them to adjust their responses to align with societal expectations rather than their genuine motivations. Moreover, while the current quantitative approach facilitates statistical analysis, it lacks generalisability to other regions and does not fully capture the nuanced personal aspirations and motivations that evolve over time. Therefore, a qualitative and longitudinal approach would provide richer insights into career motivation dynamics.

Additionally, the Ikigai concept, deeply embedded in Japanese philosophy, requires cultural validation within the context of Portuguese students. It is critical to examine potential variations or reinterpretations of Ikigai dimensions across different ages and stages of work experience. The relationship between Ikigai and age, in particular, warrants further in-depth exploration. Finally, extending research beyond national boundaries or conducting comparative analyses with other regions is highly recommended to assess the broader applicability of the findings.