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10.12688/f1000research.146873.2
Research Article
Articles
Socio-demographic analysis of destination selection factors for Himalayan Hill destinations
[version 2; peer review: 2 approved]

Badoni Manish Conceptualization Visualization https://orcid.org/0000-0002-8284-9723
a1
Rawat Babita Methodology Supervision Writing – Review & Editing 2
Aggarwal Megha Data Curation Investigation Writing – Original Draft Preparation https://orcid.org/0000-0002-8267-8813
3
1 USHHM, Uttaranchal University, Dehradun, Uttarakhand, India
2 Uttaranchal Institute of Management, Uttaranchal University, Dehradun, Uttarakhand, India
3 Uttaranchal Institute of Management, Uttaranchal University, Dehradun, Uttarakhand, India
a manish.anusha11@gmail.com
No competing interests were disclosed.

3 9 2024
2024
13 26227 8 2024
Copyright: © 2024 Badoni M et al.
2024
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background

The towering peaks of the Himalayas lie in troves of captivating hill destinations, especially in India. Each destination aims to provide tourists with unique experiences and breath-taking landscapes. Understanding the tapestry of factors that weave the allure of these destinations and draw visitors from diverse backgrounds remains intriguing.

Method

This study delves into the socio-demographic tapestry of Himalayan hill destination selection, unraveling the complex interplay of demographic characteristics, social influences, and individual motivations that shape tourists’ choices.

Results

This study aims to answer why different tourists have different travel choices and what factors are the drivers behind such choices. The results show that destination selection factors are similar irrespective of respondents’ socio-demographic variabilities; however, for a few factors, the results are reversed.

Conclusion

The study has implications for policymakers and the limitations of the research discussed at the end.

Himalayan Hill Destinations
Socio-demographic variables
Destination selection factors
Gender
Age
Occupation level
Income level
The author(s) declared that no grants were involved in supporting this work.Revised Amendments from Version 1

In response to one reviewer's feedback, this paper has undergone minor revisions related to the rationale behind the sample area, hypothesis development, pilot testing information, and clarity on results with improvements on implications. In the earlier version focus on pilot testing and validity has not been mentioned. The hypothesis development is also updated related to its association with the previous studies which is also an important part of the research. act. Furthermore, results are also reorganized in the context to previous studies, facilitating a better understanding of the theme of the paper.
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pmcIntroduction

The Himalayan hill destinations of India have long captivated the imagination of travellers with their breathtaking landscapes, diverse cultures, and spiritual significance. The selection of factors that drive tourists to visit these destinations is crucial for both tourism practitioners and policymakers. Destination selection is a complex process influenced by a myriad of socio-demographic and travel motivation factors ( Kaushik et al., 2010). This socio-demographic analysis of tourists with respect to destination selection factors provides valuable insights for tourism industry stakeholders. By recognizing the diverse preferences of different demographic groups, tourism practitioners can tailor their offerings to cater to a broad spectrum of tourists. This new understanding ensures that Himalayan hill destinations continue to attract visitors, while maintaining a delicate balance between economic development and environmental conservation.

Younger travellers are more likely to visit adventurous destinations, ( Chauhan & Jishtu, 2022) or older travellers would choose to relax to familiar and nearby destinations ( Wijaya et al., 2018). The higher income level group tended to travel to luxurious destinations and the other income level group would visit nearby destinations. These socio-demographic changes help customize marketing strategies to attract every class of tourists and increase footfall for a particular destination. Destinations with aesthetic images rightly communicated to tourists would be able to achieve a competitive advantage with respect to similar participative destinations. Understanding the intersection of sociodemographic and destination selection factors is vital. Related parties, such as destination marketers, tour operators, and policymakers, develop promotional campaigns, infrastructure, and tourism services based on these insights to ensure a more targeted and satisfying experience for tourists, contributing to the sustainable growth of the tourism industry ( Ma et al., 2018).

This study aims to construct a relationship between socio-demographic variables and destination selection factors for various destinations in Uttarakhand and Himachal Pradesh. It intends to highlight the sociodemographic factors that are majorly relevant for selecting a destination that further helps the destination to compete other similar geographical conditions. By examining the preferences and driving forces behind destination selection across various age groups, gender variability, occupation status, and income levels, this study aims to examine the nuanced decision-making processes that guide journeys to these major mountain havens.

Literature review

The tourism industry is highly competitive, and the personal characteristics of individual tourists play an important role in destination selection. Even if destination attributes are unknown, certain individual traits motivate tourists to visit the place ( Suttikun et al., 2018). Motivation to visit a destination also plays a crucial role in shaping tourist behavior ( Baloglu & Uysal, 1996). Researchers have also identified push and pull factors as motivating factors for tourists to visit a destination, and pull factors serve as the basis for destination selection ( Josiam et al., 1999). Destination appeal is a major factor for tourists to visit the destination, whereas other factors such as infrastructure facilities, transportation availability, time, and cost involved in travel are secondary factors that enhance tourist flow ( Das et al., 2007). The study ( Hudson & Shephard, 1998) identified that not only adventure services but also travel information, accommodation, and tour operator services are selection factors for tourists. Other researchers ( Crompton, 1979; Dann, 1977, 1981) have also examined push and pull motivation factors in tourism. Push factors can be identified as knowledge of culture, status, personal development, relaxation, interpersonal relationships, and pleasure. On the other hand, pull factors could be atmosphere and climate at the destination, hygiene, built heritage, outdoor activities, and people’s characteristics ( Antara & Prameswari, 2018; Karamehmedović, 2018; Prayag & Ryan, 2011). Thus, the attributes or features of a destination are important factors for tourists.

Studies have been done in the past analyzed the relationship between the personal characteristics of tourists and their travel motivations and found that they are inter-related ( Chon, 1990; Court & Lupton, 1997; Joppe et al., 2001). The author ( Iyiola & Akintunde, 2011) examined whether tourist travel motivation to visit Nigeria is affected by sociodemographic variables. The motivation to select a destination can be determined by the age and income of tourists ( Ng et al., 2007; Yoon & Uysal, 2005). Travel motivating factors were also studied with respect to senior-age travellers, and the results are similar to those of previous studies with fewer pull factors, such as destination familiarity, value for money, and destination closeness ( Wijaya et al., 2018). Various authors ( Beerli & Martín, 2004; Um & Crompton, 1990; Walmsley & Jenkins, 1993) have studied the relationship between motivation to visit a destination and individual characteristics such as gender, age, education, occupation, and income as determinants of creating a destination image. Studies ( Gibson et al., 2008; Woodside & Lysonski, 1989) have also found similar results in that the perception of destinations is affected by tourist socio-demographic characteristics.

Tourist places are marketed according to the needs of potential tourists’ personal characteristics such as gender, age, education, occupation, and income ( Stabler, 2013; Um & Crompton, 1990). Sources such as advertising and word-of-mouth publicity provide travel inspiration to tourists, and past experiences play an important role in influencing future travel decisions for a potential destination ( Huang Songshan, 2006).

Various studies have analyzed the motivating factors and the influence of sociodemographic factors on creating destination image and tourist intention to visit. It is also possible that diverse visitors will have different levels of expectations with respect to different motivational factors and destinations. In this study, the influence of gender, age, occupation, and income on the expectation level of tourists pertaining to different tourist motivational factors, such as destination image, infrastructural facilities, beauty, culture, and heritage, is examined for selected destinations of Uttarakhand and Himachal Pradesh. The states of Uttarakhand and Himachal Pradesh have a lot of tourism potential, and both states are continuously putting a lot of marketing effort into creating an identity among tourists. Both the states in India have historical relevance in tourism and are attracting a lot of tourists towards different tourist destinations. The two states of India, Uttarakhand and Himachal Pradesh has been taken as study area because these states are comparable in terms of similar geography.

Research objectives and hypothesis development

Based on the above literature review, this study aims to fulfill the following objectives and examine the related hypotheses:

Objective 1 To identify the selection factors to visit Himalayan region destination ( Antara & Prameswari, 2018; Das et al., 2007; Karamehmedović, 2018; Prayag & Ryan, 2011).

Objective 2 To identify the relationship between sociodemographic variables and destination selection factors ( Beerli & Martín, 2004; Gibson et al., 2008; Um & Crompton, 1990; Walmsley & Jenkins, 1993; Woodside & Lysonski, 1989).

Objective 2 is analyzed and fulfilled with the help of following related Hypothesis- H1 Destination selection factors are significantly similar irrespective of the gender of the tourists

H2 Destination selection factors are significantly similar irrespective of the age of the tourists

H3 Destination selection factors are significantly similar irrespective of the occupation of the tourists

H4 Destination selection factors are significantly similar irrespective of the income of the tourists

Methods

A self-administered questionnaire, prepared with a five-point Likert scale ( Likert, 1932) with 49 items, was prepared and distributed to Himalayan hill destinations of Uttarakhand and Himachal Pradesh, that is, Mussoorie, Shimla, Nainital, and Kangra, selected on the basis of convenience as these destinations are in close proximity. Experts from Academia and Tourism industry were approached for validating the questionnaire. Further pilot testing was performed on 100 responses and the value of Cronbach alpha was found to 0.897.

A total of 800 tourists were then approached, 200 at each destination, between April 2023 and November 2023. Out of 800, only 748 were included in the final analysis because Indian female, married, respondents were reluctant to complete the survey due to their reserved behaviour, and the survey was performed by their spouses or other relatives. Hence, these surveys were excluded from the final analysis. Although tourists were reluctant to participate in the survey, help from local restaurant owners, tour operators, and Mall Road vendors have been taken.

Sociodemographic analysis

To fulfil the research objectives, responses collected from 748 tourists from selected Indian hill destinations were analyzed using a structured questionnaire. The respondents were selected based on their travel experience to a specific destination. Sociodemographic dimensions, such as gender, age, occupation, and income, were purposely included in the questionnaire to fulfil the research objectives. The distribution of the data is presented in Table 1.

Table 1. Respondents’ profile.

Age	n	%	Gender	n	%	Occupation	n	%	Income	n	%	
Below 25 years	175	23.4	Male	531	71.0	Student	69	9.2	Below Rs.20,000	68	9.1	
25-35 years	430	57.5	Female	217	29.0	Private sector	423	56.6	Rs.20,000 - Rs.50,000	423	56.6	
35-45 years	116	15.5				Public sector	168	22.5	Rs.50,000 - Rs.80,000	165	22.1	
Above 45 years	27	3.6				Business class	61	8.2	Rs.80,000 - Rs.1,00,000	65	8.7	
						Other	27	3.6	Above than Rs.1,00,000	27	3.6	
Total	748	100		748	100		748	100		748	100	
Source: Author’s compilation.

Respondents’ sociodemographic analysis represented 57.5% of the youth tourist age ranging from to 25-35 years followed by 23% of respondents aged below 25 years. This indicates that about 80% of tourists belong to the young age group, that is, not more than 35 years. The maximum number of tourists was 71%, and 56% of the respondents belonged to private sector jobs, with incomes ranging from 20,000 Rs. to 50,000 Rs. Only 29% of the respondents were female as they were reluctant to participate in the survey. This behavior shows that the motivation of Indian females to travel to a destination still depends on their counterparts, whether their husbands, fathers, brothers, or friends.

Inferential Analysis

To identify the destination attributes or destination selection factors, a reliability analysis was performed, and the Cronbach’s alpha value of 0.909 showed that the questionnaire achieved high internal consistency. Before verifying the hypotheses set out in this study, an exploratory factorial analysis was conducted. The factors extracted by this method are uncorrelated and arranged in the order of decreasing variance. Bartlett’s test of sphericity and the calculation of Kaiser-Meyer-Olkin statistics indicate whether data are suitable for identifying orthogonal factor dimensions. Variables with loading equal to or greater than 0.4 were included in a given factor to decrease the probability of misclassification ( Hair et al., 1995). Forty-nine items were loaded saliently, and any factor that emerged with eigenvalues greater than one was considered for further analysis. The final factor distribution was allocated to forty-three items, other items with values below the threshold limit were not used for the final analysis. The total variance explained by factor analysis was 60%. The results of Cronbach’s alpha coefficients, KMO, Bartlett’s test of sphericity, and factor analysis are shown in Table 2.

Table 2. Results of factor analysis and factor distribution.

Factors	Item in the questionnaire	Item description	Factor loading	Cronbach’s alpha	
Factor 1 (Destination Image & Attributes)	Q1	I try to cover the unique places of the destination	0.714	0.865	
Q3	I try to check with weather conditions before travel	0.604	
Q4	I try to cover the least crowded places at the time of travel	0.819	
Q5	I consider Local residents’ behaviour while selecting a place	0.739	
Q7	I try to cover maximum popular places of the destinations	0.561	
Q9	I look for places where telecommunication facilities are good	0.462	
Q10	I look for market availability for local craft for gifting and souvenirs	0.648	
Q11	I look for cleanliness at the destination while selecting	0.567	
Q18	I travel at some special occasions like marriage anniversary or birthdays or new Year etc.	0.617	
Q19	I look for language comfortability while selecting destinations	0.53	
Q24	I look for Environmental condition of the destination	0.421	
Factor 2 (Value for Money)	Q34	I try to explore all the places you travel in limited time	0.602	0.763	
Q35	I try to find reasonable price for recreational activities	0.599	
Q36	I look for travel time of the destination (3 days or 5 days or 7 days or more)	0.736	
Q37	I would like to have political stability in destination	0.6	
Q38	I seek for a place to relax with friends and family	0.73	
Q43	I try to explore local cuisine and communicate with local people every time	0.448	
Factor 3 (Infrastructure Facilities)	Q6	I try to find diversity for accommodation while selecting the place to travel (Hotel/Homestay/villa/apartment/tent houses etc.)	0.557	0.735	
Q8	I try to check for local transport availability	0.49	
Q13	I try to get accommodation with good view and space	0.688	
Q14	I try to get accommodation with luxury facilities (like bathtub, shower, TV, refrigerator etc.)	0.753	
Q20	I look for places where road administration is good	0.559	
Factor 4 (Beauty, Culture & Heritage)	Q26	Religious places play an important role while selecting the destination	0.701	0.770	
Q27	I try to cover all religious places of the destinations	0.625	
Q28	I love to travel the places with scenic beauty and surroundings	0.701	
Q29	I try to cover places with historic monuments	0.556	
Factor 5 (Tour & Travel Connections)	Q15	I rely on the information provided by tour operators	0.783	0.745	
Q16	I try to manage all your travel plans by your own	0.661	
Q17	I try to go with good tour operators for travel plans	0.69	
Factor 6 (Value Added Services)	Q30	I look for recreational activities at the destination every time you travel	0.652	0.700	
Q31	I try to get good adventure facilities at the destination	0.77	
Q32	I look for facilities like banks/ATMs while selecting a destination	0.47	
Q33	I look for places where digital payments are upgraded for ease of payments	0.726	
Factor 7 (Destination Brand Value)	Q12	I try to cover the destinations showcase in movies and dramas (like Shimla in 3 idiots and Manali in Jab we met)	0.57	0.575	
Q21	I look for new and famous destinations every time you travel	0.564	
Q25	I take feedback from your friends and colleagues who already travelled to the destination	0.63	
Q39	I wait for right season to travel the place	0.6	
Factor 8 (Satisfaction and intention to Revisit)	Q44	I always feel satisfied with the quality of experiences in destination	0.558	0.817	
Q45	I am satisfied with the touristic attractions of the destination	0.614	
Q46	I am satisfied with the infrastructure of the destination	0.787	
Q47	I am satisfied with entertainment/recreational activities of the destination	0.702	
Q48	I am satisfied with the culture/traditions of the destination	0.725	
Q49	Overall, I am satisfied with the destination as a whole and revisit the destination	0.653	
Cronbach’s alpha of the total scale		0.909	
Variance explained		60%	
KMO		0.888	
Bartlett		15095.16	
Significance		.000	
Source: Author’s compilation.

Table 2 shows the factors considered motivating and satisfactory for destination selection. Factors such as ‘Destination Image’, ‘Value for Money,’ ‘Infrastructure Facilities,’ ‘Beauty, Culture & Heritage’, ‘Tour & Travel Connections’, ‘Value added Services,’ Destination Brand Value’ are independent factors and able to create destination selection factor. The table also shows that the Cronbach alphas’ value reported on factor 7, i.e. ‘Destination Brand Value’ is low. This could be a consequence of this factor because the maximum number of respondents belonged to the income group of Rs. 20,000 to Rs. 50,000; for such respondents’ destinations, brand value would not be a motivating factor in selecting a destination. However, it was considered suitable to include this item because destination image would be helpful in creating destination brand value, and hence, becomes a motivating factor for the selection of a destination. The table also shows the dependent variable, destination satisfaction and intention to revisit.

The possible relationship between tourists’ socio-demographic characteristics and the selection factors of a destination was analyzed using ANOVA, checking its significance by means of the F statistic and p value (confidence level 95%).

The relationship between the sociodemographic variables of respondents and the factors of destination selection decisions of the respondents are shown in Table 3 with the help of ANOVA.

Table 3. Relationship between gender and destination selection factor.

Factors	Results	Sum of Squares	df	Mean Square	F	Sig.*	
DI	Between Groups	5.967	1	5.967	0.118	0.732	
Within Groups	37786.443	746	50.652			
Vm	Between Groups	0.042	1	0.042	0.002	0.960	
Within Groups	12674.219	746	16.990			
Infra	Between Groups	0.243	1	0.243	0.019	0.891	
Within Groups	9648.708	746	12.934			
BeuCulHer	Between Groups	0.299	1	0.299	0.030	0.863	
Within Groups	7472.699	746	10.017			
TTC	Between Groups	2.921	1	2.921	0.499	0.480	
Within Groups	4365.485	746	5.852			
VaS	Between Groups	51.059	1	51.059	5.209	0.023	
Within Groups	7312.690	746	9.803			
BrandV	Between Groups	0.968	1	0.968	0.142	0.707	
Within Groups	5095.438	746	6.830			
Source: Author’s compilation.

The results show that there is a significant similarity between gender and destination selection factors, except for one factor, Value-added Services (VaS). This result justifies the fact that women tend to assess the value-added services of a destination more favorably than men. For all other factors, DI, Vm, Infra, BCH, TTC, and DBV, there were no significant differences irrespective of the gender of the respondents. Therefore, we confirm hypothesis H1 that Destination selection factors are significantly similar irrespective of the gender of tourists.

Table 4 shows the relationship between the age of respondents and destination selection factors. The results show that there is a significant difference among the selection factors for different age groups of the respondents.

Table 4. Relationship between age and destination selection factor.

Factors	Results	Sum of Squares	df	Mean Square	F	Sig.*	
DI	Between Groups	3337.991	3	1112.664	24.027	0.000	
Within Groups	34454.419	744	46.310			
Vm	Between Groups	127.647	3	42.549	2.523	0.05	
Within Groups	12546.614	744	16.864			
Infra	Between Groups	58.686	3	19.562	1.518	0.209	
Within Groups	9590.266	744	12.890			
BeuCulHer	Between Groups	69.595	3	23.198	2.331	0.073	
Within Groups	7403.403	744	9.951			
TTC	Between Groups	145.140	3	48.380	8.523	0.000	
Within Groups	4223.267	744	5.676			
VaS	Between Groups	61.092	3	20.364	2.075	0.102	
Within Groups	7302.657	744	9.815			
BrandV	Between Groups	157.748	3	52.583	7.921	0.000	
Within Groups	4938.658	744	6.638			
Source: Author’s compilation.

Factors such as destination image, value for money, tour and travel connections, and destination brand value are considered differently by different age groups of tourists. For other factors, including infrastructure facilities, ‘Beauty, Culture and Heritage’, and ‘Value-added Services’, the results show no significant difference with the age of the respondents. Results implies that the selection factor ‘destination image’ or ‘Destination Brand Value’ are significantly different for different age categories of the tourists. Young tourists tend to be motivated by destinations with a grand brand value rather than older tourists. Similarly, a destination would have different age tourist footfall due to the difference in value for money. On the basis of these results, we partially confirm hypothesis H2 that Destination selection factors are significantly similar irrespective of the age of the tourists but only for factors ‘Infrastructure facilities’, ‘Beauty, Culture and Heritage,’ and ‘Value-added Services’.

Table 5 shows the result of occupation and reveals a significant difference between occupation and selection factors for destination, but only for the factors ‘Destination Image’, and ‘Value for Money’. The results reveal similarities among various occupation respondents and their selection factors for destinations, such as ‘Beauty, Culture & Heritage’, ‘Infrastructure facilities’, ‘tour & travel connections’, ‘value-added services’, and ‘destination brand value’. Results implies that the factor ‘Destination Image’ or ‘Value for money’ are significantly different for various occupational categories of the tourists. Tourists who are private sector employees motivate destinations that provide more value for money than other tourists. These results confirm hypothesis H3 that destination selection factors are significantly similar, irrespective of the occupation of the tourists.

Table 5. Relationship between occupation and destination selection factor.

Factors	Results	Sum of Squares	df	Mean Square	F	Sig.*	
DI	Between Groups	1226.309	4	306.577	6.229	0.000	
Within Groups	36566.101	743	49.214			
Vm	Between Groups	176.014	4	44.003	2.616	0.034	
Within Groups	12498.247	743	16.821			
Infra	Between Groups	58.271	4	14.568	1.129	0.342	
Within Groups	9590.681	743	12.908			
BeuCulHer	Between Groups	90.143	4	22.536	2.268	0.060	
Within Groups	7382.856	743	9.937			
TTC	Between Groups	38.859	4	9.715	1.667	0.156	
Within Groups	4329.547	743	5.827			
VaS	Between Groups	33.237	4	8.309	0.842	0.499	
Within Groups	7330.511	743	9.866			
BrandV	Between Groups	61.639	4	15.410	2.274	0.060	
Within Groups	5034.767	743	6.776			
Source: Author’s compilation.

The relationship between the income of the respondents and the selection factors of the destination is shown in Table 6. The result shows there is no similarity between income and selection factors for destination only for the factors ‘Destination Image,’ ‘Value for Money,’ ‘Beauty, Culture & Heritage’. For other factors, ‘Infrastructure facilities,’ ‘Tour-Travel Connections’, ‘Value-added Services,’ and ‘Destination Brand Value’ showed significant similarity with the diverse income of respondents. Results implies that the factor ‘destination image’ or ‘Value for money’ are significantly different for different income categories of the tourists. Tourists with middle-income levels motivate and select destinations that provide more value for money than do other tourists. Thus, tourists with various income groups look for value for money and varied destination images rather than other destination selection criteria. These results partially confirm hypothesis H4 Destination selection factors are significantly similar irrespective of tourists’ income.

Table 6. Relationship between income and destination selection factor.

Factors	Results	Sum of Squares	df	Mean Square	F	Sig.*	
DI	Between Groups	1282.551	4	320.638	6.525	0.000	
Within Groups	36509.859	743	49.138			
Vm	Between Groups	289.294	4	72.324	4.339	0.002	
Within Groups	12384.966	743	16.669			
Infra	Between Groups	45.355	4	11.339	0.877	0.477	
Within Groups	9603.597	743	12.925			
BeuCulHer	Between Groups	129.524	4	32.381	3.276	0.011	
Within Groups	7343.475	743	9.884			
TTC	Between Groups	43.114	4	10.779	1.852	0.117	
Within Groups	4325.292	743	5.821			
VaS	Between Groups	38.944	4	9.736	0.988	0.413	
Within Groups	7324.805	743	9.858			
BrandV	Between Groups	48.806	4	12.202	1.796	0.128	
Within Groups	5047.600	743	6.794			
Source: Author’s compilation.

Results and discussion

This research was undertaken to identify various destination selection factors and their relationship with socio-demographic variables of tourists for various Himalayan region destinations in Uttarakhand and Himachal Pradesh, India. Various destination factors have been identified with the help of factor analysis, such as ‘Destination Image’, ‘Value for Money’, ‘Infrastructure facilities’, ‘Beauty, Culture & Heritage’, ‘Tour & Travel connections’, ‘value-added services, and ‘destination brand value’. These results are similar to previous studies such as Ng et al., 2007; Wijaya et al., 2018; Yoon & Uysal, 2005. Among all the above factors, ‘Destination image’ is a key determinant for travelers to visit any destination ( Kala, 2021). The Cronbach’s alpha value was 0.9, and the variance explained by all factors was 60%, which is considerably good ( Aggarwal et al., 2024).

To further analyze the relationship between the factors and sociodemographic variables, one-way analysis of variance (ANOVA) was performed. The summary results of the ANOVA are presented in Table 7. The results are somewhat different as compare to previous studies in context to Indian destinations. The selection of destinations is independent with respect to socio‐demographic variables.Destination Image and Value for Money were found to be significantly different for different age groups, occupation status, and income levels. This implies that tourists of different age groups, occupation statuses, and income levels will have different choices for selecting a destination on the basis of ‘Destination image’ or ‘Value for money’. ‘Value added services’ was found dissimilar for socio-demographic variable ‘Gender’. This implies that the selection of a destination may change if value-added services are different for any destination. However, for other factors such as ‘destination image’ or ‘beauty, culture, and heritage’, the selection factor does not create any difference between male and female tourists.

Table 7. Comparative analysis of ANOVA results.

Sociodemographic factors/Motivational factors	Results	Destination image	Value for money	Infrastructure facilities	Beauty, Culture & Heritage	Tour & Travel Connections	Value added services	Destination brand value	
Gender	F	0.118	0.002	0.019	0.030	0.499	5.209	0.142	
Sig.*	0.732	0.960	0.891	0.863	0.480	0.023*	0.707	
Age	F	24.027	2.523	1.518	2.331	8.523	2.075	7.921	
Sig.*	0.000*	0.05*	0.209	0.073	0.000*	0.102	0.000*	
Occupation	F	6.229	2.616	1.129	2.268	1.667	0.842	2.274	
Sig.*	0.000*	0.034*	0.342	0.060	0.156	0.499	0.060	
Income	F	6.525	4.339	0.877	3.276	1.852	0.988	1.796	
Sig.*	0.000*	0.002*	0.477	0.011*	0.117	0.413	0.128	
Source: Author’s compilation.

Implications and Limitations

Destination selection factors are important for any destination to improve tourist footfall and gain a competitive advantage. Socio-demographic variables play an important role in such decisions and hence need to be taken care of by the DMOs. Destination marketing organizations should identify their tourists and their choices. Any tourist, if impacted by their socio-demographic variable, will try to select destination suits for their personality and pocket. In this study, results revealed that age and income are major contributing socio- demographic variables in case of destination selection for Indian destinations. ‘Destination Image’ and ‘Value for Money’ factors are impacted by different age group and income level of the tourist. Young tourists would love to visit Goa, whereas senior-aged tourists would like to travel to a destination with religious beliefs. Thus, destination marketing organizations should analyze their tourist choices and market their products according to the needs of tourists.

This research also has some limitations. The first and foremost limitation of this study is the selection of socio-demographic variables. This research used only four socio-demographic variables: Gender, Age, Occupation and Income. Other sociodemographic variables were beyond the scope of this study. The results may vary if other variables are included in future studies. The other limitation is the study area, which is related to the Himalayan region and included a few destinations of Uttarakhand and Himachal Pradesh with random selection. Future studies should include other destinations. A comparison between these destinations could also be performed with respect to sociodemographic variables. This study covers the Himalayan region, and other hill regions of India can also be studied with the help of similar analysis, and further comparisons can be drawn.

Ethical statement

This research was conducted in accordance with the guidelines of the Research Ethics Board (REB) of Uttaranchal University. The Research Ethics Board has given the approval on March 4, 2023, and the approval number is UU/DRI/EC/2023/002.

The questionnaire has been submitted to REB of the university, the board members and chairperson have identified the viability of the research topic. All the authors have presented their research objectives to the board then the questionnaire got approval to conduct the study.

Consent statement

The consent from all the participants involved in the study has been taken. A self-explanatory written statement was attached with the questionnaire for the participants and the similar questionnaire has been submitted to the university research board (REB).

Data availability

The underlying data related to the paper are available in figshare with the following citation and DOI.

Figshare. Aggarwal, Megha, Badoni, Manish, Rawat, Babita (2024). Sociodemographic Analysis of Destination Selection Factors for Himalayan Hill Destinations. Dataset, https://doi.org/10.6084/m9.figshare.24936471.v2 ( Badoni et al., 2024).

The data available were submitted by Megha Aggarwal licensed under CC BY 4.0. Complete details are-Socio-Demographic Analysis of Destination Selection Factors for Himalayan Hill Destinations © 2024 by Manish Badoni, Babita Rawat, and Megha Aggarwal licensed under CC BY 4.0. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

10.5256/f1000research.171022.r320065
Reviewer response for version 2
Dwivedi Sunita 1Referee https://orcid.org/0000-0001-5617-995X

1 Symbiosis Centre for Management Studies, Symbiosis International University, Pune, Maharashtra, India
4 9 2024 Copyright: © 2024 Dwivedi S
2024
https://creativecommons.org/licenses/by/4.0/ This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions.
Version 2recommendationapprove
Dear Editor

I here by approve the paper

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Marketing and Branding

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

10.5256/f1000research.171022.r320066
Reviewer response for version 2
Kala Devkant 1Referee https://orcid.org/0000-0003-4539-4608

1 School of Business, UPES, Dehradun, Uttarakhand, India
4 9 2024 Copyright: © 2024 Kala D
2024
https://creativecommons.org/licenses/by/4.0/ This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Version 2recommendationapprove
Thank you for incorporating the suggested changes in your revised manuscript.

The flow, structure, and quality of the manuscript have improved now.

There is only one comment:

Please remove references from the research objectives.

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

Partly

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Partly

Reviewer Expertise:

Tourism & Hospitality and Consumer Behaviour

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

10.5256/f1000research.161000.r267431
Reviewer response for version 1
Dwivedi Sunita 1Referee https://orcid.org/0000-0001-5617-995X

1 Symbiosis Centre for Management Studies, Symbiosis International University, Pune, Maharashtra, India
6 5 2024 Copyright: © 2024 Dwivedi S
2024
https://creativecommons.org/licenses/by/4.0/ This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Version 1recommendationapprove
Dear Team F1000 Research,

Thank you for providing this opportunity to review the paper. The theme is interesting and the study has used all novelty to the research area. My feedback is as below:

The purpose of this study was to ascertain the correlation between various factors related to destination selection and sociodemographic characteristics of tourists for various destinations in the Himalayan region of Uttarakhand and Himachal Pradesh, India. Many destination factors, such as "value for money," "destination image," "beauty, culture, and heritage," "tour & travel connections," "value-added services," and "destination brand value," have been identified with the use of factor analysis techniques.

Research has statistically validated the factors identified impacting young consumers destination selection preferences. The study concluded with the significant outcome for tour and travel industry to draw the marketing strategies for travelers. 

I concur with the results and implication drafted by the authors, and recommend the paper for publication

Thanks

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Marketing and Branding

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

10.5256/f1000research.161000.r267432
Reviewer response for version 1
Kala Devkant 1Referee https://orcid.org/0000-0003-4539-4608

1 School of Business, UPES, Dehradun, Uttarakhand, India
24 4 2024 Copyright: © 2024 Kala D
2024
https://creativecommons.org/licenses/by/4.0/ This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Version 1recommendationapprove-with-reservations
Thank you for the opportunity to read this interesting study. The study has some potential. However, certain issues need to be addressed. The detailed observations are given below for your response:

Abstract:

Refinement is needed, particularly in the methods and results sections.

Introduction:

The rationale of the study should be presented more effectively, with recent and relevant papers cited. It is noted that many cited studies are outdated; the author/s should include recent and relevant studies to build and present their arguments. Incorporating Indian studies would further strengthen and justify the arguments made. For example,[1]  https://dergipark.org.tr/en/pub/ahtr/issue/32311/359067

Hypotheses Development:

Hypotheses development is not sufficiently presented. Please provide relevant literature to support your hypotheses.

Methods:

The author/s should provide references for previous studies from which items were adopted.

Clear justification is needed for selecting Uttarakhand and Himachal Pradesh as study areas, as well as for choosing convenience sampling.

“……. because Indian female respondents were reluctant to complete the survey, and the survey was performed by their spouses or other relatives.” Please refine this statement.

What about the validity of the questionnaire?

What was the language?

Did you conduct a Pilot test before full-scale survey?

Results:

Table 2: Item Description: Replace ‘You’ with ‘I’.

Instead of ANOVA, I suggest the author/s use regression analysis between Factors 1-7 and Factor 8.

The author/s should compare the results of the study with previous studies.

The implications (Theoretical and managerial) are vague and need refinement.

“Not every study has been completed without limitations,” – Please delete this portion of the statement.

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

Partly

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Partly

Reviewer Expertise:

Tourism & Hospitality and Consumer Behaviour

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

Badoni Manish USHHM, Uttaranchal University, Dehradun, Uttarakhand, India

25 8 2024 Dear Reviewer, Thank you for your suggestions. We have incorporated the major part as you suggested. However, one suggestion related to regression analysis has not been incorporated as we are developing a new paper using a similar analysis.

Competing interests: No competing interests were disclosed.

Competing interests: No competing interests were disclosed.

Competing interests: No competing interests were disclosed.

Competing interests: No competing interests were disclosed.

Competing interests: No competing interests were found.
==== Refs
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