Career barriers of hospitality and tourism management students and the impacts on their career intention

Figures & data

Figure 1. Conceptual framework. Source: own elaboration.

Table 1. Descriptive statistical results of the measurement scales and items.

Constructs and items (source)	Mean	Standard deviation	Factor loading
Personal CB (McWhirter et al., 2007; Song & Chathoth, 2008)
PCB1. I'm not interested in H&T related jobs.	3.58	1.222	0.868
PCB2. My ability and strength don’t match the H&T industry.	3.68	1.031	0.760
PCB3. As not satisfied with the course on HTM major, I do not want to work in the H&T industry.	3.52	1.241	0.778
PCB4. In the learning process of HTM major, I can’t develop a sense of achievement.	3.71	1.251	0.752
PCB5. I have no confidence towards the targets of H&T industry.	3.62	1.190	0.798
PCB6. I don’t share the core values of work in H&T industry.	3.78	1.173	0.769
Social CB (Same as above)
SCB1. Senior schoolmates in H&T industry suggest me not to work in this occupation.	3.60	1.220	0.812
SCB2. Many of my classmates are not going to work in H&T industry.	3.58	1.321	0.780
SCB3. My parents and relatives don’t support the idea of a worker in H&T industry.	3.78	1.187	0.764
SCB4. My peers and friends advise me not to work in H&T industry.	3.48	1.172	0.798
SCB5. Working in the H&T industry is not recognised by others.	3.63	1.157	0.850
Interactional CB (Same as above)
ICB1. Sex discrimination exists in the H&T industry.	3.68	1.081	0.897
ICB2. Working conditions in the H&T industry is not good.	3.76	1.058	0.832
ICB3. Most jobs in H&T industry are in remote locations.	3.76	1.035	0.768
ICB4. The career development opportunities for workers are few.	3.78	1.018	0.717
Career Intention (Arnold et al., 2006; Chang & Tse, 2015)
CI1. I plan to be a H&T employee.	3.44	0.948	0.806
CI2. I would be happy to spent my career in H&T industry.	3.38	0.943	0.825
CI3. I will certainly join H&T industry after graduation.	3.41	0.924	0.728
CI4. Working for H&T industry always keeps in my mind.	3.39	1.086	0.728
Major satisfaction (Han & Yoon, 2015; Nauta, 2007)
MS1. Generally speaking, I am satisfied with my major.	3.60	1.186	0.781
MS2. I feel good about my choice of major.	3.54	1.123	0.739
MS3. I never consider changing my major.	3.62	1.228	0.863
MS4. My decision to choose HTM major is wise.	3.54	1.177	0.827
Professional Identity (Diemer & Blustein, 2007; Porfeli et al., 2011)
PI1. I would recommend H&T profession to others.	3.38	0.958	0.712
PI2. H&T profession will help me achieve my personal goals.	3.39	1.069	0.698
PI3. I think H&T profession allows me to remain true values.	3.22	1.030	0.673
PI4. I am sure that H&T profession is right for me.	3.36	1.086	0.768
PI5. I think H&T profession will make my dream come true.	3.59	1.041	0.770

Note: The model fit indices of CFA are as follows: NFI = 0.967, RFI = 0.961, IFI = 0.977, TLI = 0.973, CFI = 0.977, RMSEA = 0.051.

Source: own elaboration.

Table 2. Sociodemographic profile of participants.

Variables	Categories	Frequency	Percent (%)
Gender (n = 807)	Male	188	23.3
	Female	619	76.7
School level (n = 842)	First-class university	220	26.1
	General university	622	73.9
Grade (n = 837)	Freshman	142	17.0
	Sophomore	277	33.1
	Junior	387	46.2
	Senior	31	3.7
Major (n = 836)	Tourism management	620	74.2
	Hospitality management	216	25.8
	Exhibition management	0	0.0
Homeland of students (n = 831)	Eastern China	22	2.6
	Central China	783	94.2
	Western China	17	2.0
	Northeastern China	9	1.1

Note: First-class universities include Anhui University, and Anhui Normal University, while General universities include Hefei College, Chizhou College, and Huangshan College.

Source: own elaboration.

Table 3. Reliability and validity analysis.

	Cronbach’s α	CR	AVE	Fornell-Larcker criterion
				PCB	SCB	ICB	PI	MS	CI
PCB	0.907	0.908	0.622	0.789
SCB	0.898	0.899	0.642	0.562	0.801
ICB	0.880	0.881	0.650	0.628	0.458	0.806
PI	0.854	0.847	0.526	−0.121	−0.126	−0.172	0.725
MS	0.878	0.879	0.646	−0.374	−0.374	−0.391	0.221	0.804
CI	0.880	0.856	0.598	−0.572	−0.504	−0.544	0.331	0.525	0.773

Note: The values in bold mean the square root of the AVE values of each latent variable (bolded). They were greater than the value of their correlation coefficients with other constructs, indicating good discriminant validity.

Source: own elaboration.

Table 4. Results of the mediation effect and moderated direct effect.

	Model 1	Model 2	Model 3
	CI	PI	CI
PCB	−0.480***	−0.120***	−0.400***
SCB	−0.406***	−0.113**	−0.324***
ICB	−0.434***	−0.151***	−0.394***
PI			0.284***
PCB*MS	0.128
SCB*MS	0.802
ICB*MS	0.927
R^2	0.391	0.024	0.370
F	179.466***	20.846***	245.891***
VIF	1.167	1.000	1.025

Note: **p < 0.01, ***p < 0.001.

Source: own elaboration.

Table 5. Results of moderated indirect effects.

	Moderator (MS)	Estimate	95%CI
PCB→PI→CI	High	0.006	[−0.010; 0.020]
	Low	−0.04	[−0.069; −0.015]
SCB→PI→CI	High	0.01	[−0.007; 0.029]
	Low	−0.036	[−0.065; −0.015]
ICB→PI→CI	High	−0.005	[−0.026; 0.013]
	Low	−0.036	[−0.065; −0.014]

Note: The values in bold indicate that MS could moderate the relationships between PCB, SCB, ICB and PI significantly.

Source: own elaboration.

Figure 2. Interaction between PCB, SCB, ICB and MS in PI prediction. Source: own elaboration.

Figure 3. Results of the conceptual model.

Note: ** p < 0.01, *** p < 0.001. Source: own elaboration.

McWhirter, E. H., Torres, D. M., Salgado, S., & Valdez, M. (2007). Perceived barriers and postsecondary plans in Mexican American and white adolescents. Journal of Career Assessment, 15(1), 119–138. https://doi.org/10.1177/1069072706294537

 Web of Science ®Google Scholar

Song, Z., & Chathoth, P. K. (2008). Career choice goals: The contribution of vocational interests, contextual support, and contextual barrier. Journal of China Tourism Research, 4(1), 98–123. https://doi.org/10.1080/19388160802099923

 Google Scholar

Arnold, J., Loan-Clarke, J., Coombs, C., Wilkinson, A., Park, J., & Preston, D. (2006). How well can the theory of planned behavior account for occupational intentions? Journal of Vocational Behavior, 69(3), 374–390. https://doi.org/10.1016/j.jvb.2006.07.006

 Web of Science ®Google Scholar

Chang, S., & Tse, E. C. Y. (2015). Understanding the initial career decisions of hospitality graduates in Hong Kong: Quantitative and qualitative evidence. Journal of Hospitality & Tourism Research, 39(1), 57–74. https://doi.org/10.1177/1096348012461544

 Web of Science ®Google Scholar

Han, H., & Yoon, H. (2015). Driving forces in the decision to enroll in hospitality and tourism graduate program. Journal of Hospitality, Leisure, Sport & Tourism Education, 17, 14–27. https://doi.org/10.1016/j.jhlste.2015.07.001

 Web of Science ®Google Scholar

Nauta, M. M. (2007). Assessing college students’ satisfaction with their academic majors. Journal of Career Assessment, 15(4), 446–462. https://doi.org/10.1177/1069072707305762

 Web of Science ®Google Scholar

Diemer, M. A., & Blustein, D. L. (2007). Vocational hope and vocational identity: Urban adolescents’ career development. Journal of Career Assessment, 15(1), 98–118. https://doi.org/10.1177/1069072706294528

 Web of Science ®Google Scholar

Porfeli, E. J., Lee, B., Vondracek, F. W., & Weigold, I. K. (2011). A multi-dimensional measure of vocational identity status. Journal of Adolescence, 34 (5), 853–871. https://doi.org/10.1016/j.adolescence.2011.02.001

 PubMed Web of Science ®Google Scholar