Keywords

Higher Education, Public Policy, Challenging Factors, Efficiency, Thailand

Introduction

In recent years, hospitality industry and its role players like hotels, market, and restaurants are playing their essential protagonist for domestic and international economic activities (Pine, Pine & Gilmore, 1999; Rimmington, Williams & Morrison, 2009; Lashley & Morrison, 2010; Madani, 2011; Davis, Lockwood, Alcott & Pantelidis, 2018; Saengchai, Thaiprayoon & Jermsittiparsert, 2019). Hospitality and restaurant sectors are observed among the fastest-growing segments both in developed and developing economies (Barros, Peypoch, & Solonandrasana, 2009; Chen, 2010; Choi, Olsen, Kwansa & Tse, 1999). Meanwhile, its role in social and economic development is widely accepted in the literature (Chang, 2003; Duncan, Scott & Baum, 2013; Higgins-Desbiolles, 2006; Kazlauskaite, Buciuniene & Turauskas, 2006). A common notion is that hospitality industry is providing significant employment to the economy (Junaedi & Jermsittiparsert, 2020; Saengchai & Jermsittiparsert, 2020). Various studies have suggested that in the coming time, hospitality industry like hotels and restaurants may provide more employment. With an effort to increase the employment options and fulfilling the demand for the educated and trained mangers for restaurant industry, there is an ongoing trend for getting higher education in restaurant sector (Jang, Zheng & Bosselman, 2017; Kamran & Omran, 2018; Kim & Jang, 2019; Lugosi & Jameson, 2017). This idea is getting space in various economies of the world. The number of enrollments of the students in hospitality and restaurant management fields has been increased substantially in various countries like Australia, China, Thailand, Singapore, and Malaysia as well (Calhoun, O’Neill & Douglas, 2018; Conwi, Cortez & Ramos, 2016; Fernandez-Chung & Gore, 2016; Giousmpasoglou, 2016; Hornsby & Scott-Halsell, 2015).

Besides, public policy, as reflected in hospitality education has provided significant support for the development of human resource (Kang, Gatling & Kim, 2015; Kuo, Chen & Tseng, 2017). The reason is that provision of education in restaurant and hospitality is of great need in any economy, specifically those having tourist’s attraction. However, to fulfill the industry requirements, various factors are playing their crucial role and known as critical factors (Hanaysha, 2016; Seo, Kim & Sharma, 2017; Xiao, Yang & Iqbal, 2019a, 2019b). Another significant issue in the higher education is that students who have done their studies in hospitality management do not enter in the industry to start their carrier (Norton, Cherastidtham & Mackey, 2016; Ravitch, 2016). In this regard, there is considerable debate regarding the long-term career building in the hospitality industry. Meanwhile, one of the significant issues in the hospitality sector is accusing the educational institution of providing poorly prepared graduates who are not capable of doing the job in a right way (Nachmias, Walmsley & Orphanidou, 2017; Ravitch, 2016).

On the other hand, educators have pointed out the issues like following the old-fashioned attitude in providing the education and related facilities to their students with little focus on latest trends. Such situation has created serious issues for the industry, economy and local communities too. A range of studies has covered higher education while taking the initial entry phase. However, minimal studies have provided empirical facts combing the relationship between the commitment of the students and higher education.

Variables and Methods

This study has considered public policy in terms of higher education for the hospitality and restaurant sector in Thailand. For this purpose, overall ten items have been extracted from the literature and added in the questionnaire (Details in results and discussion). For the measurement of critical factors as second independent variable, eight items are identified and considered. For the measurement of efficiency of the restaurants, five proxies under the title of process efficiency, marketing efficiency, asset’s efficiency, staff efficiency, and reputational efficiency are added in the questionnaire. After the development of questionnaire, it was distributed among the restaurant managers for collection of data. A final sample from 332 respondents is collected and found to be valid for the analyses purpose. For this purpose, both descriptive and regression analysis are conducted. Descriptive findings have helped to understand the nature of the responses through mean score, deviation from the mean and other measures. Whereas, regression analysis has helped to understand the nature of causal relationship between independent and dependent variable of the study.

Results and Discussion

Table 1 provides the descriptive findings of the study, covering the total observation of each item, mean score, deviation from the mean, and other details. For the measurement of public policy regarding hospitality higher education overall ten items have been considered, ranging from HE1 to HE10. It is observed that highest mean score is observed for the HE1 which is 4.98 with the deviation from the mean of 1.329 respectively. It shows that through HE2 average score is 4.61 and deviation from the mean is 1.187. In a similar trend mean score for other items of HE are presented with their relative value of standard deviation too.

Besides, critical factors ranging from CF1 to CF5 are also presented under Table 1 with their average response value and deviation from this mean score. It is found that highest deviation from the mean value is observed for CF4, followed by CF3. For operational efficiency, the trends in the mean score are observed for all the five items, entitled as OE1 to OE5. It is presented that for OE3, mean score is 3.80, followed by OE2 which is 3.73. Besides, Table 1 provides the minimum and maximum point of the responses, percentiles, skewness, and kurtosis respectively.

Table 1 Descriptive Statistics
Variables	Obs	Mean	Std.Dev	Min	Max	p1	p99	Skew.	Kurt.
HE1	332	4.898	1.329	1	5	1	5	.119	1.936
HE2	332	4.361	1.187	1	5	1	5	-.303	2.136
HE3	332	3.036	1.309	1	5	1	5	-.067	1.825
HE4	332	3.389	1.198	1	5	1	5	-.528	2.511
HE5	332	4.452	1.124	1	5	1	5	-.365	2.38
HE6	332	4.726	1.397	1	5	1	5	.236	1.794
HE7	332	3.033	1.294	1	5	1	5	-.095	1.978
HE8	332	3.127	1.276	1	5	1	5	-.22	1.941
HE9	332	4.289	1.227	1	5	1	5	-.23	2.092
HE10	332	3.081	1.24	1	5	1	5	-.116	2.076
CF1	332	3.244	1.203	1	5	1	5	-.341	2.224
CF2	332	3.277	1.306	1	5	1	5	-.327	1.944
CF3	332	3.003	1.381	1	5	1	5	-.026	1.837
CF4	332	2.895	1.407	1	5	1	5	.116	1.707
CF5	332	3.919	1.064	1	5	1	5	-1.058	3.737
CF6	332	3.904	1.078	1	5	1	5	-.952	3.304
CF7	332	3.726	1.194	1	5	1	5	-.664	2.509
CF8	332	3.916	1.054	1	5	1	5	-.809	2.999
OE1	332	3.654	1.203	1	5	1	5	-.52	2.283
OE2	332	3.732	1.07	1	5	1	5	-.695	2.956
OE3	332	3.807	1.107	1	5	1	5	-.818	3.043
OE4	332	3.756	1.095	1	5	1	5	-.68	2.772
OE5	332	3.762	1.069	1	5	1	5	-.735	2.918

Table 2 provides the outcome for the impact of public policy in terms of higher education on operational efficiency as measured through process efficiency. It is found that HE3 (promotion of HE will increase tourism revenue) has shown its significant and highly positive influence on OE1. The coefficient of HE3 is 0.197 with the standard error of 0.063. It means that more the government influence on public policy like higher education in hospitality sector like restaurant, more the positive return for the restaurant business in terms of process efficiency. Similarly, HE5 and HE10 have also shown their direct and significant impact on OE1 in the restaurant industry of Thailand. The value of F-test indicates that all the stated regression coefficients are presented under Table 2 are significantly different from zero, While overall explanatory power of R² is 18.8 percent respectively.

Table 2 Linear Regression Output (Impact of He on Process Efficiency)
Process Efficiency (DV1)	Coef.	St.Err	t-value	p-value		Sig.
HE1: higher education in Hospitality should be government priority	0.061	0.056	1.08	0.281
HE2: more focus by the government influence HE in hospitality have its positive outcomes in society	0.011	0.063	0.17	0.865
HE3: HE in hospitality increase employment chances	0.057	0.055	1.05	0.296
HE4: promotion of HE in hospitality will increase tourism revenue	0.197	0.063	3.14	0.002		***
HE5: government should establish a separate department to evaluate HE in Hospitality	0.162	0.062	2.60	0.010		**
HE6: there is significant gap in HE for hospitality and restaurant industry	-0.045	0.050	-0.90	0.370
HE7: public policy in terms of HE for hospitality can help the restaurants to promote them.	-0.071	0.064	-1.12	0.265
HE8: HE for hospitality helps to increase literary rate in the country	0.063	0.065	0.97	0.332
HE9: I am very satisfied while getting HE for hospitality	-0.060	0.067	-0.88	0.378
HE10: Government should need to focus on promotion of HE in hospitality management.	0.137	0.061	2.23	0.026		**
cons	2.798	0.289	9.67	0.000		***
Mean dependent var	3.654	SD dependent var			1.203
R-squared	0.188	Number of obs			332.000
F-test	3.083	Prob>F			0.001
Akaike crit. (AIC)	1055.540	Bayesian crit. (BIC)			1097.397
Indicates *** p<0.01, ** p<0.05, * p<0.1

Table 3 provides the impact of challenging factors on the operational efficiency in terms of process efficiency of restaurant sector. It is found that factors like financial constraints, not interested in getting HE for hospitality and restaurant, and high merit in getting HE related to hospitality and restaurant management showing their adverse impact on process efficiency of restaurant sector in Thailand. While the factor of social circle CF8 have shown its positive influence on the process efficiency. It means that although the factor of social circle is observed as challenge, but at the same time, it works as core opportunity with its positive influence on process efficiency of the restaurants.

Table 3 Linear Regression Output (Impact of CF on Process Efficiency)
Process Efficiency (DV1)	Coef.	St.Err	t-value	p-value		Sig.
CF1: Financial constraints	-0.088	0.052	-1.69	0.093		*
CF2: family issues	0.146	0.047	1.10	0.115
CF3: not interested in getting HE for hospitality and restaurant	-0.110	0.051	-2.15	0.032		**
CF4: lack of job opportunities	0.011	0.049	0.22	0.824
CF5: significant competition	0.056	0.086	0.65	0.514
CF6: high merit in getting admission	-0.285	0.089	-3.21	0.001		***
CF7: low/no cooperation from the society	0.010	0.074	0.14	0.890
CF8: Social circle	0.204	0.078	2.60	0.010		**
_cons	1.590	0.305	5.21	0.000		***
Mean dependent var	3.654	SD dependent var			1.203
R-squared	0.251	Number of obs			332.000
F-test	13.540	Prob>F			0.000
Akaike crit. (AIC)	985.976	Bayesian crit. (BIC)			1020.222
Indicates *** p<0.01, ** p<0.05, * p<0.1

Table 4 provides the output for the impact of public policy in terms of higher education HE in hospitality on marketing efficiency of the restaurant business. It is found that effect of HE3-HE5 on OE2 is positive and significant at 5 percent, 10 percent, and 1 percent respectively. It means that more the reflection of public policy for the HE in the hospitality industry can affect the marketing efforts of restaurant business in a positive direction. However, the rest of the indicators have shown no influence on OE2 in restaurant industry of Thailand. Also, the rest of the indicators of HE have shown their insignificant association with the OE2 of restaurant sector of Thailand. additionally, value of R2 under Table 4 is 17.4, providing the fact that all items under the title of HE have shown their low explanatory power for the OE2.

Table 4 Linear Regression Output (Impact of He on Marketing Efficiency)
Marketing Efficiency (DV2)	Coef.	St.Err	t-value	p-value		Sig.
HE1: higher education in Hospitality should be government priority	0.022	0.048	0.47	0.640
HE2: more focus by the government influence HE in hospitality have its positive outcomes in society	0.076	0.053	1.44	0.151
HE3: HE in hospitality increase employment chances	0.093	0.046	2.00	0.046		**
HE4: promotion of HE in hospitality will increase tourism revenue	0.093	0.053	1.76	0.080		*
HE5: government should establish a separate department to evaluate HE in Hospitality	0.277	0.053	5.25	0.000		***
HE6: there is significant gap in HE for hospitality and restaurant industry	-0.016	0.042	-0.37	0.709
HE7: public policy in terms of HE for hospitality can help the restaurants to promote them.	0.037	0.054	0.69	0.489
HE8: HE for hospitality helps to increase literary rate in the country	-0.041	0.055	-0.74	0.462
HE9: I am very satisfied while getting HE for hospitality	0.011	0.057	0.20	0.842
HE10: Government should need to focus on promotion of HE in hospitality management.	-0.040	0.052	-0.77	0.441
_cons	1.999	0.245	8.16	0.000		***
Mean dependent var	3.732	SD DV: OE2			1.070
R-squared	0.174	Number of obs			332.000
F-test	6.749	Prob>F			0.000
Akaike crit. (AIC)	944.898	Bayesian crit. (BIC)			986.755
Indicates *** p<0.01, ** p<0.05, * p<0.1

Table 5 indicates the causal relationship between the CF factors and marketing efficiency as second measure of operational efficiency in the restaurant sector. It is observed that there is a significant and positive influence from CF5, CF7, and CF8 on the value marketing efficiency in restaurant sector of Thailand. It means that factors like significant competition, higher merit in getting admission, low/ no cooperation from the society have their direct effect in dealing with marketing efficiency of the restaurant. This relationship reveals that although these factors are challenging in nature, at the same time boosting the marketing efficiency of the restaurants through their significant and positive influence.

Table 5 Linear Regression Output (Impact of CF on Marketing Efficiency)
Marketing Efficiency (DV2)	Coef.	St.Err	t-value	p-value		Sig.
CF1: Financial constraints	-0.042	0.035	-1.21	0.229
CF2: family issues	0.020	0.032	0.65	0.518
CF3: not interested in getting HE for hospitality and restaurant	0.044	0.034	1.26	0.207
CF4: lack of job opportunities	-0.018	0.033	-0.55	0.582
CF5: significant competition	0.318	0.058	5.48	0.000		***
CF6: high merit in getting admission	0.081	0.060	1.36	0.173
CF7: low/no cooperation from the society	0.195	0.050	3.89	0.000		***
CF8: Social circle	0.261	0.053	4.95	0.000		***
_cons	0.412	0.205	2.01	0.045		**
Mean dependent var	3.732	SD dependent var			1.070
R-squared	0.573	Number of obs			332.000
F-test	54.163	Prob>F			0.000
Akaike crit. (AIC)	721.795	Bayesian crit. (BIC)			756.041
Indicates *** p<0.01, ** p<0.05, * p<0.1

Table 6 shows the effect of HE factors on operational efficiency in terms of assets’ efficiency in restaurant industry of Thailand. It shows that HE2 has its significant and positive impact on OE3 with the coefficient of 0.111 and standard error of 0.057 respectively. Through HE4, the effect on OE3 is 0.113, with the standard error of 0.057, significant at 5 percent. Through HE5, the effect on OE3 is 0.226 and standard error of 0.056 respectively. It means that more the attention of government on public policy in terms of establishing a separate department to evaluate higher education in hospitality and restaurant management, more the positive effect on OE3.

Table 6 Linear Regression Output (Impact of He on Assets’ Efficiency)
Asset’s Efficiency (DV3)	Coef.	St.Err	t-value	p-value		Sig.
HE1: higher education in Hospitality should be government priority	0.018	0.051	0.36	0.719
HE2: more focus by the government influence HE in hospitality have its positive outcomes in society	0.111	0.057	1.96	0.051		*
HE3: HE in hospitality increase employment chances	-0.050	0.049	-1.02	0.309
HE4: promotion of HE in hospitality will increase tourism revenue	0.113	0.057	2.00	0.047		**
HE5: government should establish a separate department to evaluate HE in Hospitality	0.226	0.056	4.02	0.000		***
HE6: there is significant gap in HE for hospitality and restaurant industry	-0.005	0.045	-0.10	0.920
HE7: public policy in terms of HE for hospitality can help the restaurants to promote them.	0.077	0.057	1.34	0.183
HE8: HE for hospitality helps to increase literary rate in the country	-0.055	0.059	-0.94	0.348
HE9: I am very satisfied while getting HE for hospitality	-0.021	0.061	-0.35	0.726
HE10: Government should need to focus on promotion of HE in hospitality management.	-0.030	0.055	-0.54	0.590
_cons	2.486	0.261	9.53	0.000		***
Mean dependent var	3.807	SD DV			1.107
R-squared	0.124	Number of obs			332.000
F-test	4.533	Prob>F			0.000
Akaike crit. (AIC)	986.846	Bayesian crit.			1028.702
Indicates *** p<0.01, ** p<0.05, * p<0.1

Table 7 provides the output for the impact of CF on asset’s efficiency of the restaurant. It is found that the effect of lack of job opportunity or CF4 has shown its significant and negative influence on asset’s efficiency of the restaurants in Thailand. However, factors like significant competition, high merit in getting admission, low/no cooperation from the society have shown their positive and significant impact on the value of asset’s efficiency of restaurant sector of Thailand.

Table 7 Linear Regression Output (Impact of CF on Asset’s Efficiency)
Asset’s Efficiency (DV3)	Coef.	St.Err	t-value	p-value		Sig.
CF1: Financial constraints	0.027	0.041	0.66	0.512
CF2: family issues	-0.060	0.037	-1.60	0.110
CF3: not interested in getting HE for hospitality and restaurant	0.035	0.040	0.86	0.390
CF4: lack of job opportunities	-0.096	0.039	-2.47	0.014		**
CF5: significant competition	0.128	0.068	1.88	0.061		*
CF6: high merit in getting admission	0.222	0.070	3.16	0.002		***
CF7: low/no cooperation from the society	0.101	0.059	1.72	0.086		*
CF8: Social circle	0.349	0.062	5.62	0.000		***
_cons	0.974	0.241	4.04	0.000		***
Mean dependent var	3.807	SD dependent var			1.107
R-squared	0.448	Number of obs			332.000
F-test	32.734	Prob>F			0.000
Akaike crit. (AIC)	829.583	Bayesian crit. (BIC)			863.829
Indicates *** p<0.01, ** p<0.05, * p<0.1

Table 8 provides the regression coefficients, standard error, t-statistics and significance level for each of the items under HE. It is found that the effect of HE4 on staff efficiency or OE4 is 0.140, significant at 5 percent. It shows that more the promotion of HE in hospitality and restaurant more the tourism revenue, which ultimately increase the staff efficiency in restaurant industry. Similarly, with the establishment of separate department to more HE education in terms of hospitality and restaurant management, more the constructive influence on staff efficiency in restaurant sector of Thailand is examined. In addition, HE7 indicates a good effect on staff efficiency too.

Table 8 Linear Regression output (Impact of HE on Staff Efficiency)
Staff Efficiency (DV4)	Coef.	St.Err	t-value	p-value		Sig.
HE1: higher education in Hospitality should be government priority	0.010	0.049	0.21	0.832
HE2: more focus by the government influence HE in hospitality have its positive outcomes in society	0.038	0.055	0.70	0.487
HE3: HE in hospitality increase employment chances	0.022	0.048	0.46	0.649
HE4: promotion of HE in hospitality will increase tourism revenue	0.140	0.055	2.54	0.012		**
HE5: government should establish a separate department to evaluate HE in Hospitality	0.183	0.055	3.35	0.001		***
HE6: there is significant gap in HE for hospitality and restaurant industry	-0.027	0.044	-0.62	0.533
HE7: public policy in terms of HE for hospitality can help the restaurants to promote them.	0.131	0.056	2.35	0.019		**
HE8: HE for hospitality helps to increase literary rate in the country	-0.068	0.057	-1.19	0.235
HE9: I am very satisfied while getting HE for hospitality	0.028	0.059	0.47	0.640
HE10: Government should need to focus on promotion of HE in hospitality management.	0.029	0.054	0.54	0.589
_cons	2.131	0.254	8.38	0.000		***
Mean dependent var	3.756	SD dependent var			1.095
R-squared	0.151	Number of obs			332.000
F-test	5.707	Prob>F			0.000
Akaike crit. (AIC)	969.408	Bayesian crit. (BIC)			1011.264
Indicates *** p<0.01, ** p<0.05, * p<0.1

Table 9 provides the outcome for the CF and staff efficiency relationship. It is expressed that factors like significant competition, and lack of job opportunities have shown their adverse impact on the value of staff efficiency of restaurant sector. While the factors like high merit in getting admission, low/no cooperation from the society and social circle have shown their positive influence on staff efficiency of the restaurant industry in Thailand.

Table 9 Linear Regression Output (Impact of CF on Staff Efficiency)
Staff Efficiency (DV4)	Coef.	St.Err	t-value	p-value		Sig.
CF1: Financial constraints	0.027	0.038	0.71	0.479
CF2: family issues	0.028	0.034	0.83	0.408
CF3: not interested in getting HE for hospitality and restaurant	0.024	0.037	0.66	0.512
CF4: lack of job opportunities	-0.026	0.035	-0.73	0.468
CF5: significant competition	-0.177	0.062	-2.84	0.005		***
CF6: high merit in getting admission	-0.263	0.064	-4.11	0.000		***
CF7: low/no cooperation from the society	0.097	0.054	1.82	0.070		*
CF8: Social circle	0.307	0.056	5.44	0.000		***
_cons	0.298	0.219	1.36	0.176
Mean dependent var	3.756	SD dependent var			1.095
R-squared	0.534	Number of obs			332.000
F-test	46.190	Prob>F			0.000
Akaike crit. (AIC)	766.525	Bayesian crit. (BIC)			800.772
Indicates *** p<0.01, ** p<0.05, * p<0.1

Table 10 demonstrates the effect of HE indicators on OE5 in terms of reputation management in the restaurant industry of Thailand. through HE4 and HE5 highly significant and positive influence is observed with the coefficients of 0.119 and 0.169 respectively. It means that the factor of promotion of HE and establishing of separate department by the government to increase HE in hospitality have their positive influence on reputation management of restaurant industry of Thailand. Similarly, for HE6, effect on OE5 is 0.076, significant at 10 percent. Whereas, same influence is recorded from HE9 which specifies that with the more satisfaction from getting the education in terms of hospitality and restaurant, more the constructive influence on the reputation of the restaurants as well.

Table 10 Linear Regression Output (Impact of HE on Reputational Efficiency)
Reputational Efficiency (DV5)	Coef.	St.Err	t-value	p-value		Sig.
HE1: higher education in Hospitality should be government priority	0.059	0.048	1.22	0.225
HE2: more focus by the government influence HE in hospitality have its positive outcomes in society	0.071	0.054	1.33	0.186
HE3: HE in hospitality increase employment chances	0.062	0.047	1.32	0.187
HE4: promotion of HE in hospitality will increase tourism revenue	0.119	0.054	2.20	0.029		**
HE5: government should establish a separate department to evaluate HE in Hospitality	0.169	0.053	3.16	0.002		***
HE6: there is significant gap in HE for hospitality and restaurant industry	0.076	0.043	1.78	0.077		*
HE7: public policy in terms of HE for hospitality can help the restaurants to promote them.	-0.039	0.055	-0.72	0.470
HE8: HE for hospitality helps to increase literary rate in the country	0.081	0.056	1.45	0.148
HE9: I am very satisfied while getting HE for hospitality	0.108	0.058	1.87	0.063		*
HE10: Government should need to focus on promotion of HE in hospitality management.	0.022	0.053	0.41	0.682
_cons	2.124	0.249	8.55	0.000		***
Mean dependent var	3.762	SD OEV5			1.069
R-squared	0.148	Number of obs			332.000
F-test	5.563	Prob>F			0.000
Akaike crit. (AIC)	954.375	Bayesian crit.			996.232
Indicates *** p<0.01, ** p<0.05, * p<0.1

Table 11 indicates the significant contributor to define the reputation management of the restaurant sector are the CF5, CF6, and CF7. Whereas, all remaining factors have shown their insignificant impact on reputation management by restaurant sector of Thailand.

Table 11 Linear Regression Output (Impact of CF on Reputational Efficiency)
Reputation Management (DV5)	Coef.	St.Err	t-value	p-value		Sig.
CF1: Financial constraints	-0.052	0.037	-1.42	0.157
CF2: family issues	-0.008	0.033	-0.24	0.808
CF3: not interested in getting HE for hospitality and restaurant	-0.032	0.036	-0.90	0.371
CF4: lack of job opportunities	0.014	0.035	0.41	0.684
CF5: significant competition	0.287	0.061	4.72	0.000		***
CF6: high merit in getting admission	0.133	0.063	2.12	0.034		**
CF7: low/no cooperation from the society	0.036	0.052	0.68	0.496
CF8: Social circle	0.381	0.055	6.90	0.000		***
_cons	0.746	0.215	3.47	0.001		***
Mean dependent var	3.762	SD dependent var			1.069
R-squared	0.530	Number of obs			332.000
F-test	45.577	Prob>F			0.000
Akaike crit. (AIC)	752.581	Bayesian crit. (BIC)			786.827
Indicates *** p<0.01, ** p<0.05, * p<0.1

Conclusion and Recommendations

This study examines the public policy in terms of higher education, challenging factors and their impact on the efficiency of the restaurant industry of Thailand. A sample of 332 respondents in terms of restaurant managers from different areas of the local region is collected and examined for the descriptive and regression analysis. Findings through regression analysis provide sound output. Results show the fact that selected factors of public policy in terms of higher education have demonstrated their direct and positive influence on the selected indicators of restaurant efficiency.

Additionally, the results through CF factors and their influence on restaurant efficiency have shown a mixed finding. It is observed that significant factors to be considered in the policy development and strategic decision-making process are the higher competition, low/no cooperation from the society, tough merit, and lack of job opportunity. These factors are positively as well as negatively affecting the restaurant efficiency as observed through present outcomes. Besides, this study is highly recommended to restaurant managers, owners, and the student community who are currently enrolled in the HE for the hospitality and restaurant management. A good understanding could be developed with the review of relationship between public policy for higher education, challenging factors and efficiency in restaurant industry.

Acknowledgement

Dr.Samanan Rattanasirivilai is a lecturer of Doctor of Philosophy Program in Development Administration, Graduate School, Suan Sunandha Rajabhat University, Thailand. Her official e-mail address is samanan.ra@ssru.ac.th.

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