Keywords

Home-stays, Tourism, Community based tourism, Environment preservation, Cultural landscape, Community participation, Home-stay choice.

Introduction

Community-Based Tourism (CBT) (Tosun, 2000; Manyara and Jones, 2007; Goodwin and Santilli, 2009) can build an economically powerful society and can conserve its cultural heritage and natural capital. Home-stay tourism is one approach to nurturing community-based tourism. This program can be implemented in rural areas with low start-up costs. They provide affordable lodging to tourists with sharing natural and cultural heritage. Home-stays can fulfil the rising lodging requirements of the Indian tourism sector (Gupta and Dutta, 2018) (Times, 2017). Rural home stays offer a unique cultural experience to tourists and a source of revenue for host communities (Acharya and Halpenny, 2013; Kontogeorgopoulos, Churyen and Duangsaeng, 2015).

Home-stays offer visitors a quick look of the local tradition , culture and life style also building it a smart alternative for home-stay owners financial gains (Ranasinghe, 2015). Consequently home-stays propose a chance for the traveller to reside with a host family and know the everyday deeds and culture (Jamaludin, Othman and Awang, 2012). The Homestay program is facilitating the tourist to discover about local culture, lifestyle, and nature.

Studies have addressed the tourist point of view related to the visitor satisfaction from different point of views like community, culture, natural attraction, home-stay service (Hussin and Kunjuraman, 2014; Biswakarma, 2015; Ogucha et al., 2015; Ismail et al., 2016) and perceptions of visitors (Jamal, Othman and Muhammad, 2011; Mura, 2015). Researchers have also disclosed inspirations of the visitors for home-stays selection (Gunasekaran and Anandkumar, 2012; Agyeiwaah, Akyeampong and Amenumey, 2013).

From a home-stay operator’s viewpoint, it is necessary to know visitors’ point of view of optional lodgings and influencing features. Therefore, this could help devise suitable marketing strategies (Gunasekaran and Anandkumar, 2012) based on the perceptive of tourist requirements and descriptions (Mtapuri, Giampiccoli and Jugmohan, 2015). Other researchers had also studied factors inspiring tourists to choose home-stays as a lodging alternative (Thapa, B. and Malini, 2017).

According to (Kala and Bagri, 2018) a higher level of community participation is required in Homestay tourism but research examining tourist point of view in enjoying authentic local experience and intermingling with community members are limited in Uttarakhand perspective. Study about Homestay tourism provides opportunity for learning new things from local culture and communities is also limited. In general hotel and resort based tourism development lowers the quality of environment. Limited research has been available on effects of Homestay tourism on local environment particularly in context of Uttarakhand, India. Government of Uttarakhand is promoting Homestay tourism under United Nations Sustainable Tourism Development Goals (UNSTDG) but the study investigating either Homestay tourism is providing value for money or not is limited.

This research paper investigates views and concern of tourists in community participation, local culture, food and lifestyle in Homestay Tourism. Consequently, examines the importance of community and cultural landscape in tourist Homestay choice. Himalayan local culture and local food served with regional ingredients will give authentic local experience to tourist. Subsequently, interaction with local folks, learning new things and understanding a new culture can help in promoting Homestay tourism in Uttarakhand, India. Study also looks into the role of Homestay tourism on environmental preservation and waste management. The research paper also investigates economic worth or value for money of the Homestay tourism from traveller’s point of view.

Literature Review

Community & Cultural Landscape (CCL)

Home-stay operations give socio-economical benefits to the local village community (Hussin and Kunjuraman, 2014). Apart from providing expected accommodation and food services to tourist home-stay also imparts long-term socio-cultural relationships (Kayat, 2010). In home-stay tourism, tourists are close with home-stay operator; share meals, and are treated as family guest (Gu and Wong, 2006; Kayat, 2010). As home stays are a rising accommodation trend, the need is to build a new framework with a focus on societal and hospitality factors that affects community involvement (Sood, Lynch and Anastasiadou, 2017). Socio-demographics affect the visitor inspiration for opting home-stay (Agyeiwaah, Akyeampong and Amenumey, 2013). Home-stay tourists’ perceptions are not only reliant on practical characteristics of value but also on experiential and emotional features. Home-stay operators should highlight tourists' outstanding experiences, local tradition-oriented activities, cultural performances, and friendly hosts (Jamal, Othman and Muhammad, 2011).

Local culture, food, and art can attract more visitors if utilized efficiently. These items have the power to facilitate many community benefits (Giampiccoli and Kalis, 2012). Home-stay should provide an opportunity for the visitor to choose what they would like to have from a food menu (Ogucha et al., 2015). The cultural landscape plays a considerable role in sustainable rural tourism. Home-stay uses cultural components in the tourism sector to exercise the cultural landscape in their everyday routine (Samsudin and Maliki, 2015). In home-stay tourism guest intermingles with the host family, improves local awareness, and easily practices, the culture and lifestyle of the home-stay operator family (Ibrahim and Rashid, 2010).

H₁: There exists a substantial relationship between the community & cultural landscape and home-stay choice

Economic Rewards (ER)

Home-stays have the potential to provide added income and employment within the community (Kamisan Pusiran and Xiao, 2013). Villagers consider home-stay programs can generate revenue for themselves and can improve the local community’s income and also can create job opportunities for villagers. It would be a reasonable method to provide monetary benefits to the local community members (Imran and Ngoc Thi Bich Nguyen, 2018). The home-stay operations give socio-economical benefits to the local village community (Hussin and Kunjuraman, 2014). Homestay program with community-based tourism generates employment prospects for local communities (Din, 1993; Kumar, Gill and Kunasekaran, 2012; Hussin and Kunjuraman, 2014; Hasan Miraz et al., 2015) and also increases the source of primary income and side incomes (Fauziah and Hamzah, 2012). Home-stay tourism boosts the socio-economic position of all operators and also of the local community involve (Chaiyatorn, 2010).

H₂: There exists a substantial relationship between economic rewards and home-stay choice.

Environmental Preservation (EP)

In general; tourism development lowers the quality of the environment. To ensure green growth; tourism growth policies should go with pollution abatement policies (Gupta and Dutta, 2018). Pleasant climatic conditions, beautiful surroundings, and cleanliness are vital characteristics of visitor satisfaction (Imran and Ngoc Thi Bich Nguyen, 2018). Homestay is considered beneficial in preserving the local rural environment, culture, and authentic heritage (Wang, 2007). Home-stay tourism conserves local culture and environment and provides economic rewards to the community(Laurie, Andolina and Radcliffe, 2005) . According to a research motivation and sustainability make a considerable relationship with home-stay operators (Mohamad et al., 2018). Community-based tourism emphasizes social and environmental sustainability (Intan Osman et al., 2014).

H₃: There exists a substantial relationship between environmental preservation and home-stay choice.

Research Methodology

Sampling and Collection of Data

The personality –managed survey questionnaire was utilized to gather data. A questionnaire is an effective tool in data collection as it leads to a more generalized and accurate statistical analysis (Rowley, 2014). The results of questionnaires are truthful and sincere since respondents were not influenced by researchers (Saunders, Lewis and Thornhill, 2008). To assess whether questions in the questionnaire could be easily understood by the respondents, as a pilot test, it was distributed among 30 WhatsApp users. In this pilot test, all variables were found supportive. Hence, the questionnaire used in the pilot test was used in the actual survey without any alteration. The sampling technique used was Convenience sampling. The questionnaire was prepared on Google Forms as it automatically records the responses of the respondents in a structured format in Google Drive. The survey was conducted from January 2021- to May 2021. The questionnaire was sent, using the hyperlink of Google Form, to social media users of India who were members of various social groups on the WhatsApp messaging platform. The intent public of this research was social media users. A total sample of 205 respondents was received, but only 193 were used while the rest were rejected because of wrongly filled forms. The minimum sample size for this study, comprising 18 independent variables, was determined to be 180 (Chin, Wynne, 1999; Jr.1, Patel3 and 1, 2014; Sarstedt, Ringle and Hair, 2017). As this study had a sample size of 193, it met the conditions of minimum sample size. Table 1 shows the respondents’ demographic profiles.

Table 1  Demographic Information
Gender n=193	Frequency	Percent
Male	106	54.9
Female	87	45.1
Age Group
16 to 24 Years	105	54.4
25 to 34 Years	34	17.6
35 to 44 Years	31	16.1
45 to 55 Years	21	10.9
Above 55 Years	2	1.0
Yearly Income
Up to 6 Lakh	48	24.9
6 to 10 Lakh	21	10.9
10 to 15 Lah	9	4.7
15 to 25 Lakh	5	2.6
Above 25 Lakh	11	5.7
Student	99	51.3
Education
12th	18	9.3
Graduate	41	21.2
Post Graduate	119	61.7
PhD	15	7.8

Measures:

A multidimensional scale that uses the existing standard scales of the core constructs was used to assess the hypothesized model. A Likert scale of five -point was used ranging from (5) strongly agrees to (1) strongly disagrees.

Items of the constructs Community & Cultural Landscape (CCL), Economic Rewards (ER), Environment Preservation (EP) and Home-stay Choice (HC) were adopted from previous studies as indicated in Table 2 and adjusted for the current study.

Table 2 Questionnaire
Community & Cultural Landscape (CCL)
CCL1	Homestay provides opportunity for interaction with local folks	(Agyeiwaah, Akyeampong and Amenumey, 2013)
CCL2	Homestay provides opportunity for enjoying authentic local experience
CCL3	Homestay provides opportunity for learning new things from local communities
CCL4	Homestay provides opportunity to understand a new culture
CCL5	Homestay provides opportunity for enjoying local foods
CCL6	Homestay provides opportunity for understanding local lifestyle
CCL7	Homestay is a way of giving back to locals
Economic Rewards (ER)
ER1	Homestay offers value for money	(Agyeiwaah, Akyeampong and Amenumey, 2013)
ER2	Homestay offers lower prices
Environment Preservation (EP)
EP1	Homestay promotes environmental preservation	(Agyeiwaah, Akyeampong and Amenumey, 2013)
EP2	Homestay reduces waste production
EP3	Homestay ensures clean environment
EP4	Home-stay preserving local environment
Home-stay Choice (HC)
HC1	often choose a home-stay for my accommodation when travelling	(Dey, Mathew and Chee-Hua, 2020), (Agyeiwaah, Akyeampong and Amenumey, 2013)
HC2	I prefer home-stay over other modes of accommodations
HC3	I really enjoy staying in a home-stay
HC4	I choose to visit a home-stay as it meets my all reasonable expectations
HC5	I choose to visit a home-stay as it satisfies my needs

Analytical Approach

AMOS 21 was applied for confirmatory factor analysis to the theoretical model. The goodness of fit was measured using the values of Chi-square statistics; CFI, SRMR, RMSEA and P close (Hu and Bentler, 1999). Structural Equation Modelling was used to test the hypotheses of the theoretical model. AMOS 21 was used for the SEM. Structural Equation Modelling is the best tool to assess multi-item latent variables and is widely used to examine mediating effects (Cheung, 2007). (Yadav and Singh, 2016) relevant paths are specified, and several measurement errors are controlled while testing hypotheses in SEM

Result

Table 3 shows the descriptive statistics that include mean and standard deviation with correlation. The mean of HC, CCL, ER and EP are 3.4808, 3.9267, 3.6606 and 3.7526 respectively with standard deviations of 0.7709, 0.7142, 0.8339 and 0.7672 respectively. Significant correlation is there among HC, CCL, ER and EP as shown in Table 3. The mean and standard deviations of the variables are in acceptable range. * denotes the p values are in the range less than 0.01.

Table 3  Descriptive Statistics
Statistics	HC	CCL	ER	EP
Mean	3.4808	3.9267	3.6606	3.7526
Std. Deviation	0.7709	0.7142	0.8339	0.7672
HC	1
CCL	0.475*	1
ER	0.463*	0.617*	1
EP	0.503*	0.488*	0.595*	1

Confirmatory Factor Analysis

According to (Hair et al., 2010) a good standardized factor loading value should be ideally 0.7 or above. As shown in Table 3, items (total =18) used to measure the theoretical model support both the reliability and validity. As given in Table 3, the factor loadings of all 18 items are greater than 0.7; the reliability of all the items is confirmed (Hair et al., 2010).

The Confirmatory factor analysis results show that the model fit measures are within the threshold limits, displays values. The value of CMIN/DF= 2.596; which is less than 3 and makes a modal acceptable fit (Marsh and Hocevar, 1985; Kline, 1998). CFI= 0.910, and is within an acceptable range (Fan, Thompson and Wang, 1999; West, Taylor and Wu, 2012). SRMR=0.0693, RMSEA= 0.091 and PCLOSE= 00 are also in acceptable range (MacCallum, Browne and Sugawara, 1996; Diamantopoulos and Siguaw, 2000).

Significant loadings and the high reliabilities of the constructs confirms convergent validity of the model. The values of AVE for all the items are above 0.5 and for all items, composite reliability is greater than its AVE, which confirms the convergent validity (Hair et al., 2010). Discriminating validity exists as all values of AVE are greater than MSV (Hair et al., 2010) and the values of inter-construct correlations are less than the values of the square root of AVE (Fornell and Larcker, 1981). Herman’s single factor Method was used to check the common method bias. All items were loaded into a single factor using SPSS. The total variance for this single factor is 40.478%. This indicates that the results are free from common method bias Tables 4 & 5.

Table 4   Fitness Measures
Measure	CMIN/DF	CFI	SRMR	RMSEA	P Close
Observed Value	2.596	0.910	0.0693	0.091	00

Table 5 Reliability & Validity Measures
	CR	AVE	MSV	HC	CCP	ER	EP
HC	0.890	0.619	0.253	0.787
CCL	0.924	0.636	0.381	0.475	0.797
ER	0.809	0.680	0.381	0.463	0.617	0.824
EP	0.887	0.662	0.354	0.503	0.488	0.595	0.814

Structural Equation Modelling

In the hypothesized model, Home-stay Choice (HC) is outcome variable; Community and Cultural Landscape (CCL), Economic Rewards (ER) and Environment Preservation (EP) is independent variables indicates that all SEM Model fit indices are within the acceptable range (Hooper et al., 2008), thereby support the model fit Figures 1 & 2.

Standardized impact of Environment Preservation (EP) on Home-Stay Choice (HC) (β = 0.331 at p ≤ 0.001) and Standardized impact of Community & Cultural Landscape (CCL) on Home-Stay Choice (HC) (β = 0.253 at p ≤ 0.001) are positive and significant (Tables 6 & 7). This supports the hypo-thesis H1 and H3 that is there exist a substantial relationship between community & cultural landscape and home-stay choice, and also a substantial relationship between environment preservation and home-stay choice. Standardized impact of Economic Rewards (ER) on Home-Stay Choice (HC) (β = 0.076 at p =.273) is not significant hence this does not supports the hypo-thesis H2; there is no relationship between economic rewards and home-stay choice in presence of community and cultural landscape (CCL) and environmental preservation (EP).

Table 6   Sem Fitness Measures
Fitness Indices	CFI	NFI	TLI	CMIN/DF	RMSEA	LO 90	HI 90
Observed Value	0.855	0.810	0.831	3.531	0.115	0.104	0.126

Discussion and Implications

This study has validated the considerable role of community participation, cultural landscape, and environmental preservation in home-stay tourism. This research work has revealed that the characteristics that inspire tourists to opt home-stay are to enjoy local and traditional cultures; this also validates the findings of the study motivations for rural home-stay choice (Dey, et al. 2020). Most of the visitors staying in home-stay put socio-cultural causes foremost, which validates (Wang, 2007) the report on the Naxi home-stay amenities in China. This study also validates findings of the research conducted on global travellers inspiration for opting home-stay in the Kumasi Metropolis of Ghana (Agyeiwaah, Akyeampong and Amenumey, 2013). The standardized impact of Economic Rewards (ER) on Home-Stay Choice (HC) is not significant hence this does not supports the hypothesis that there is a substantial relationship between economic rewards and home-stay choice. This low impact is due to influence of community and cultural landscape (CCL) and environmental preservation (EP).

Table 7  Regression Weights
			Estimate	S.E.	C.R.	P
HC	<---	ER	.076	.069	1.096	.273
HC	<---	EP	.331	.076	4.329	***
HC	<---	CCL	.253	.071	3.560	***

As shown in Table 7 cronbach alpha of community and cultural landscape (CCL) is 0.923 and for environmental preservation (EP) is 0.885 and loadings for all factors of CCL and EP are above 0.7, these values confirms high reliability and validity of both constructs (Hair et al., 2010) and supports many previous studies discussed above. The insights and results of this study would be worth full for policy designer trying to know why visitors prefer home-stay. The socio-environmental aspects basically needed much focus from the various stakeholders for more community-based tourism development and enhanced quality of life for the home-stay owners. Government and tourism agencies need to display culture and festivals of the different regions of the state in websites to promote home-stay tourism. They also need to find and promote ways to involve local community in rural tourism. The study also implies to protect and promote environment and also showcase it on tourism websites for marketing purpose.

Limitations & Future Scope

Limitation could be due to small sample size which can influence generalizability of the findings across diverse tourism practices. Since the scales for this research were taken for the community and cultural landscape based home-stay tourism practices, the findings cannot be generalized across other mode of tourism stuff. One more limitation has to do with the Asian cultural outlook from which the results were drawn. There may be challenges in generalizing these results to Western tourists. Furthermore, one concern that has not been considered in the present study is individual versus group travel. Future research may measure the differences in rural home-stay choice based on the composition of the travel group.

Low standardized impact of Economic Rewards (ER) may indicate low price sensitivity of home-stay tourism in presence of community and cultural landscape (CCL) and environmental preservation (EP). This can be a topic for future research. Home-stays are evolving as alternative mode of accommodation and fulfilling all reasonable expectations of the travellers. Furthermore, the association of home-stay services and natural beauty of Uttarakhand with home-stay choice can be areas of future research.

Conclusion

This study has validated the considerable role of community participation, cultural landscape, and environmental preservation in home-stay tourism. Community and cultural landscape are the primary basis for travellers in rural home-stay tourism to experience the way of life. This research work has revealed that the characteristics that inspire tourists to opt home-stay are to enjoy local and traditional cultures. Home-stay tourist believes in environmental preservation and waste management. In general; tourism development lowers the quality of the environment. Home-stay tourism conserves local culture and environment and provides economic rewards to the community. Knowledge and information on the local culture of the area or state should be displayed on an online platform with the help of experts to encourage cultural tourism. The rural home stay would be helpful in generating employment, especially in rural hilly areas, and protecting the environment in Uttarakhand.

References

Acharya, B. P. and Halpenny, E. A. (2013) ‘Homestays as an Alternative Tourism Product for Sustainable Community Development: A Case Study of Women-Managed Tourism Product in Rural Nepal’, Tourism Planning and Development.

Indexed at, Google Scholar, Cross Ref

Agyeiwaah, E., Akyeampong, O. and Amenumey, E. K. (2013) ‘International tourists’ motivations to choose homestay: Do their socio-demographics have any influence?’, Tourism and Hospitality Research.

Indexed at, Google Scholar, Cross Ref

Biswakarma, G. (2015) ‘On the Dimensionality of Measuring Tourist Satisfaction towards Homestay’, International Journal of Hospitality and Tourism Systems.

Indexed at, Google Scholar, Cross Ref

Chaiyatorn (2010) ‘The Developmental Model of Cultural Tourism-Homestay of the Lao Vieng and Lao Song Ethnic Groups in the Central Region of Thailand’, Journal of Social Sciences, 6(1).

Indexed at, Google Scholar, Cross Ref

Cheung, M. W. L. (2007) ‘Comparison of approaches to constructing confidence intervals for mediating effects using structural equation models’, Structural Equation Modeling.

Chin, Wynne, N. P. (1999) ‘Structural Equation Modeling Analysis with Small Samples Using Partial Least Square’, Statistical strategies for small sample research, 1(1).

Dey, B., Mathew, J. and Chee-Hua, C. (2020) ‘Influence of destination attractiveness factors and travel motivations on rural homestay choice: the moderating role of need for uniqueness’, International Journal of Culture, Tourism, and Hospitality Research, 14(4).

Indexed at, Google Scholar, Cross Ref

Diamantopoulos, A. and Siguaw, J. A. (2000) ‘Introducing LISREL: A guide for the uninitiated’, Journal of the Electrochemical Society, 129.

Din, K. H. (1993) ‘Dialogue with the hosts: an educational strategy towards sustainable tourism’, Tourism in South-East Asia.

Fan, X., Thompson, B. and Wang, L. (1999) ‘Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes’, Structural Equation Modeling, 6(1).

Fauziah, C. L. and Hamzah, M. R. (2012) ‘Homestay tourism and pro-poor tourism strategy in Banghuris Selangor , Malaysia’, Elixir Geoscience, 45.

Google Scholar

Fornell, C. and Larcker, D. F. (1981) ‘Evaluating Structural Equation Models with Unobservable Variables and Measurement Error’, Journal of Marketing Research.

Indexed at, Google Scholar

Giampiccoli, A. and Kalis, J. H. (2012) ‘Tourism, food, and culture: Community-based tourism, local food, and community development in mpondoland’, Culture, Agriculture, Food and Environment.

Indexed at, Google Scholar, Cross Ref

Goodwin, H. and Santilli, R. (2009) ‘Community-Based Tourism: a success??’, Tourism Management.

Gu, M., & Wong, P. P. (2006) ‘Residents’ perception of tourism impacts: A case study of homestay operators in Dachangshan Dao, North-East China’, Tourism Geographies, 8(3).

Indexed at, Google Scholar, Cross Ref

Gunasekaran, N. and Anandkumar, V. (2012) ‘Factors of Influence in Choosing Alternative Accommodation:A Study with Reference to Pondicherry, A Coastal Heritage Town’, Procedia - Social and Behavioral Sciences, 62.

Gupta, M. R. and Dutta, P. B. (2018) ‘Tourism development, environmental pollution and economic growth: A theoretical analysis’, Journal of International Trade and Economic Development.

Hair, J. F. et al. (2010) ‘Multivariate Data Analysis’, Vectors.

Hasan Miraz, M. et al. (2015) ‘A Study on Homestay Malaysia: ICT Applications’, Proceedings of International Conference on Networking and Computer Application.

Google Scholar

Hooper, D. et al. (2008) ‘Evaluating Model Fit?: a Synthesis of the Structural Equation Modelling Literature’, Electronic Journal of business Research Methods.

Google Scholar

Hu, L. T. and Bentler, P. M. (1999) ‘Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives’, Structural Equation Modeling.

Indexed at, Google Scholar

Hussin, R. and Kunjuraman, V. (2014) ‘Sustainable Community-Based Tourism ( Cbt ) Through Homestay Programme in Sabah , East Malaysia’, Proceeding of the Social Sciences Research ICSSR 2014 (e-ISBN 978-967-11768-7-0). 9-10 June 2014, Kota Kinabalu, Sabah, MALAYSIA.

Ibrahim, Y. and Rashid, A. (2010) ‘Homestay Program and Rural Community Development in Malaysia’, Journal of Ritsumeikan Social Sciences and Humanities, 1(2).

Imran, M. M. and Ngoc Thi Bich Nguyen (2018) ‘A Community Response to Tourism , Focusing on the Home-stay Program in K Village in Nainital ,Uttarakhand, India’, Journal of Urban and Regional Studies on Contemporary India.

Indexed at, Google Scholar

Intan Osman et al. (2014) ‘Understanding Motivation, Empowerment and Sustainability Outcomes of Women Homestay Entrepreneurs in West Malaysia. A Preliminary Analysis.’, International Journal of Gender and Entrepreneurship, 4(1).

Ismail, M. N. I. et al. (2016) ‘Community-based Homestay Service Quality, Visitor Satisfaction, and Behavioral Intention’, Procedia - Social and Behavioral Sciences.

Google Scholar

Jamal, S. A., Othman, N. and Muhammad, N. M. N. (2011) ‘Tourist perceived value in a community-based homestay visit: An investigation into the functional and experiential aspect of value’, Journal of Vacation Marketing.

Jamaludin, M., Othman, N. and Awang, A. R. (2012) ‘Community Based Homestay Programme: A Personal Experience’, Procedia - Social and Behavioral Sciences, 42.

Jr.1, J. F. H., Patel3, M. L. D. S. G. V. K. and 1 (2014) ‘AMOS COVARIANCE-BASED STRUCTURAL EQUATION MODELING (CB-SEM): GUIDELINES ON ITS APPLICATION AS A MARKETING RESEARCH TOOL’, Brazilian Journal of Marketing -BJM Revista Brasileira de Marketing – ReMark Edição Especial, 13(2).

Kala, D. and Bagri, S. C. (2018) ‘Barriers to local community participation in tourism development: Evidence from mountainous state Uttarakhand, India’, Tourism.

Indexed at, Google Scholar

Kamisan Pusiran, A. and Xiao, H. (2013) ‘Challenges and community development: A case study of Homestay in Malaysia’, Asian Social Science.

Google Scholar

Kayat, K. (2010) ‘The nature of cultural contribution of a community-based homestay programme’, Tourismos, 5(2).

Kline, R. B. (1998) ‘Software Review: Software Programs for Structural Equation Modeling: Amos, EQS, and LISREL’, Journal of Psychoeducational Assessment.

Kontogeorgopoulos, N., Churyen, A. and Duangsaeng, V. (2015) ‘Homestay Tourism and the Commercialization of the Rural Home in Thailand’, Asia Pacific Journal of Tourism Research.

Kumar, R., Gill, S. S. and Kunasekaran, P. (2012) ‘Tourism as a Poverty Eradication Tool for Rural Areas in Selangor, Malaysia’, Global Journal of Human Social Science, 12(7).

Laurie, N., Andolina, R. and Radcliffe, S. (2005) ‘Ethnodevelopment: Social movements, creating experts and professionalising indigenous knowledge in ecuador’, Antipode, 37(3).

MacCallum, R. C., Browne, M. W. and Sugawara, H. M. (1996) ‘Power analysis and determination of sample size for covariance structure modeling’, Psychological Methods, 1(2).

Google Scholar

Manyara, G. and Jones, E. (2007) ‘Community-based tourism enterprises development in Kenya: An exploration of their potential as avenues of poverty reduction’, Journal of Sustainable Tourism.

Indexed at, Google Scholar, Cross Ref

Marsh, H. W. and Hocevar, D. (1985) ‘Application of Confirmatory Factor Analysis to the Study of Self-Concept. First- and Higher Order Factor Models and Their Invariance Across Groups’, Psychological Bulletin, 97(3).

Mohamad, Z. et al. (2018) ‘Relationship between motivation and business sustainability: A study on homestay entrepreneurs in Malaysia’, Journal of Social Sciences Research, 4(12).

Mtapuri, O., Giampiccoli, A. and Jugmohan, S. (2015) ‘Community-based tourism affinity index: a visitor’s approach’, African Journal of Hospitality, Tourism and Leisure, 4(2).

Mura, P. (2015) ‘Perceptions of authenticity in a Malaysian homestay - A narrative analysis’, Tourism Management.

Ogucha, E. B. et al. (2015) ‘The influence of homestay facilities on tourist satisfaction in the Lake Victoria Kenya Tourism Circuit’, Journal of Ecotourism.

Indexed at, Google Scholar, Cross Ref

Ranasinghe, R. (2015) ‘Evaluation of homestay accommodation supply in Sri Lanka’, International Journal of Multidisciplinary Research and Development, 2(2).

Google Scholar

Rowley, J. (2014) ‘Designing and using research questionnaires’, Management Research Review.

Indexed at, Google Scholar, Cross Ref

Samsudin, P. Y. and Maliki, N. Z. (2015) ‘Preserving Cultural Landscape in Homestay Programme Towards Sustainable Tourism: Brief Critical Review Concept’, Procedia - Social and Behavioral Sciences.

Indexed at, Google Scholar, Cross Ref

Sarstedt, M., Ringle, C. M. and Hair, J. F. (2017) ‘Partial Last Square Structural Equation Modelling’, Springer International Publishing AG 2017.

Google Scholar

Saunders, M., Lewis, P. and Thornhill, A. (2008) Research Methods for Business Students 5th Ed, Research methods for business students.

Sood, J., Lynch, P. and Anastasiadou, C. (2017) ‘Community non-participation in homestays in Kullu, Himachal Pradesh, India’, Tourism Management.

Thapa, B. and Malini, D. H. (2017) ‘Guest reasons for choosing homestay accommodation: an overview of recent researchese’, Asia Pacific Journal of Research, Vol. 1(No. LV), pp. 169–175.

Times, H. (2017) ‘Tourism ministry policy to standardize homestays by october end’, Press Trust of India.

Tosun, C. (2000) ‘Limits to community participation in the tourism development process in developing countries’, Tourism Management.

Wang, Y. (2007) ‘Customized authenticity begins at home’, Annals of Tourism Research, 34(3).

Indexed at, Google Scholar, Cross Ref

West, S. G., Taylor, A. B. and Wu, W. (2012) ‘Model fit and model selection in structural equation modeling.’, Handbook of structural equation modeling.

Yadav, R. S. and Singh, M. (2016) ‘Winning the “trust” of the employees, ethically or strategically?’, International Journal of Business Governance and Ethics.

Google Scholar

Received: 21-Dec-2023, Manuscript No. AMSJ-23-13022; Editor assigned: 22-Dec-2023, PreQC No. AMSJ-23-13022(PQ); Reviewed: 21-Apr-2023, QC No. AMSJ-23-13022; Revised: 23-May-2023, Manuscript No. AMSJ-23-13022(R); Published: 10-Jun-2023