INTRODUCTION
The trade-off between economic development and the environmental quality is a wellknown phenomenon. Till a nation become highly developed and learn how to manage environmental or critical natural resources while undertaking various developmental activities the growth process becomes unsustainable. Hence a debate has always been 1 Address correspondence to Utpal Kumar De: North Eastern Hill University, Shillong, 793022, India Email: utpalkde@gmail.com; de_u@yahoo.com
Utpal Kumar De
there between the Club of Rome2 (Meadow and Meadow, 1971) and the hardcore neoclassical market economists in regard to the sustainability of the growth process and preservation of natural resources and maintaining inter-generational and also intragenerational equity. It is found that the poorer especially the indigenous people, whose livelihood are highly dependent on the natural resource extraction are the worst victim of the natural resource degradation that are caused by the socio-economic activities undertaken by the state as well as the richer section of any society. There is thus a strong inter-linkage between socio-economic activities, sustainability of resource use and environmental quality (De, 2006).
In the context of aforesaid background, nature based tourism that has been one of the fastest growing economic activities in the world during past few decades can be a better option for the maintenance of sustainable welfare along with the preservation of natural wealth. Ecotourism has also become a buzzword of the time. In the state of Meghalaya within North-East India, nature based tourism has occupied the central place of tourism, where large number of visitors come every year just to enjoy the scenic beauty of the wettest place, Cherrapunjee, waterfalls, limestone caves, trekking through hilly jungles, forest biodiversity and indigenous cultural items. The visitors are willing to spend to a significant amount of money and time to enjoy such scenic beauty and also for the preservation of such scenic beauty (De and Devi, 2011). The rising population and various economic activities like extraction of minerals (coal, limestone, boulder etc), collection of timber and other forest resources for the survival and prosperity of individuals sometimes cause damage to the forest, water, cave and also scenic beauty of the area (Lyngkhoi, 2007). In this scenario, nature-based tourism here provides an alternative scope of development without damaging the natural resources for the poor indigenous population (De and Devi, 2010).
The indigenous people in these matrilineal societies, especially the women have been found to sell food items, a number of handicrafts products that has been prepared from the locally collected minor forest products, traditional handloom products. Women, through their engagement in various tourism related activities are supposed to enhance their empowerment level at least economically and socially.3 Moreover, the development of scope of employment and income in the growing hospitality sector and transport business with the growing demand by the nature loving tourists has created
2 Club of Rome is a global forum that deals with a variety of international political issues. It was founded in 1968 by Aurelio Peccei, an Italian Industrialist and Alexander King, a Scottish Scientist. Its members include current and former Heads of State, UN bureaucrats, high-level politicians and government officials, diplomats, scientists, economists, and business leaders from around the globe who are convinced that the future of humankind is not determined once and for all and that each human being can contribute to the improvement of our societies. The task of the club is to raise awareness about the environmental concerns and problem of future developmental prospects due to the damage of environment caused by various factors of which the primary factor is the population growth itself as mentioned in the Limits to Growth by Meadows, Meadows, Randers and Behrens.
3 Even though women in these matrilineal societies possess physical assets and are engaged in various socio-economic and religious activities, they are not found politically empowered (De and Ghosh, 2011).
an opportunity for sustainable environmental management at the regional level for the livelihood itself.
OBJECTIVE
The author of this paper tries to explore how a substantial section of indigenous population of North-East India especially the women earn their livelihood from the growing nature based tourism activities through the maintenance of the nature. Also the relative position of women in terms of generation of employment and income vis a vis men is examined. The level of social and economic empowerment of women through tourism is also analysed. It is examined on the basis of empirical observation through a primary survey conducted in three prime tourist sites and central city Shillong in Meghalaya.
Some Relevant Studies on Impacts of Tourism and Involvement and Empowerment of Women
Various studies have already pointed out how growth of tourism in any area generate both problems and opportunities for societies and its manifold impact - economic, sociocultural, environmental and political (Chopra, 1991). Notwithstanding the size of an area affected by tourism, its economic effects would be categorised into four groups: Income, Employment, Balance of Payments and Investment and Development (Holloway, 1985). Mechanism through which the people around the places of tourist importance especially the poorer can benefit from tourism are (a) employment in tourism enterprises, (b) opportunities to supply goods and services to tourism enterprises, (c) direct sales of goods and services to visitors, (d) establishment and operation of tourism enterprises, (e) tax or levy on tourism income or profits with proceeds benefiting the poor, (f) donations and support provided by tourism enterprises and tourists and (g) investments in infrastructure stimulated by tourism development benefiting the poor. Its economic (employment and income) impact is reflected across various sections of the society including women who remain engaged in various organised and unorganised activities related to tourism and surrounding nature.
The cultural and social impacts of tourism are not only dependent on the number of tourists visiting a region but also on the 'nature' of tourism provided by the area. For instance, a tourist whose primary motive is to learn about new cultures will fully accept and acclimatise to the foreign customs and traditions, and will also attempt to explore the region independently in order to be 'less visible' in the area. However, tourism operators today are increasingly 'packaging' recreational sites for wealthy tourists, who visit an area with specific expectations for facilities that they are accustomed to in everyday life. Since many recreational sites situated in remote areas do not normally have access to such facilities, the surrounding areas have to be permanently altered for meeting the visitors' requirements. This often involves displacing local indigenous people and interferes of their ordinary lives, which is often resented by them, and at times viewed as a new form of 'colonialism' by the richer sections of society (Holloway, op. cit.). However, the growth of tourism in an area also has positive social impacts, since it not only opens up new avenues for earning income for both gender, but also leads to a regeneration of awareness and pride in one's traditions and cultures. In many areas, tourism has led to the revival of interest in tribal culture and traditions, regeneration and growth of cottage industries catering to tourist needs and has also opened up new avenues for knowledge and learning. Here lies the role of women who being in a matrilineal
society have a dominant role in socio-economic milieu of the tribal society in North-East India.
In most tourist destinations of North-East India, the impacts of tourism in the form of jobs and wages are only a part of livelihood gains and often not the most significant ones. Tourism here generate four different types of local cash income, involving four distinct categories of people: (a) Wages from formal employment, (b) Earnings from selling goods, services, or casual labour (e.g. food, crafts, building materials, guide services), (c) Dividends and profits arising from locally-owned enterprises and (d) Collective income: this may include profits from a community-run enterprise, dividends from a private sector partnership and land rental paid by an investor. Wage employment here may lift a household from an insecure to a secure footing, but it may only be available to a minority of people, and not the poor. Casual earnings may be very small, but more widely spread, and may be enough, for instance, to cover school fees for one or more children. Women are found to be more interested in and affected by local cash income from the category (b) (De and Devi 2010).
Experience from Asia and also from Meghalaya suggest that with the development of destinations, accommodation for tourists become as simple as offering at the early stage, with lodges, guest houses and hotels replacing more basic options as tourism grow, and some of these even include foreign companies. Once luxury resorts started to develop, the scenario becomes more complex with investors from outside start playing much more dominant role. Thus local indigenous tribal women tend to have very limited role in such organised sector activities. Transport normally fall into a grey area between formal and informal sectors. Most destinations have taxis, jeeps or other motorised forms of transport, often driven by the owners or employed drivers. As things expanded organised associations of owners, operating on a rota system became more common. Women are remaining out of this sector in any way.
Ample evidences show that high-status jobs in resorts typically go to non-locals, expatriate staff or trained nationals from outside. However, there is almost no analysis of who is employed in middle and lower ranking jobs (Ashley et al., 2007). But some new hotels resorts have come up in recent years in remote newly tourist locations with the local ownership and visitors are showing increasing interest to stay overnight in those locations instead of centrally located luxury resorts in town. These resorts employ mostly the local people. Thus, potential for employment of local staff seems to improve as one move away from the luxury resorts into these newly established areas (Ashley et al., 2007).
The activities like vending, running stalls and collecting fuel wood for the tourist industry fall into informal category often provides an easy entry into the industry for the poor, especially for women. Many of the small food shops, local artisan shops in the tourist sites of Meghalaya are own and run by the women. The incomes can be substantial but unreliable as it is often reported a seasonal activity.
These informal sectors in many areas tend to get less attention of planners, and institutional interventions. But in some cases initiatives like flexible licensing systems, cooperatives and associations have helped these sectors. In Meghalaya many of those are controlled and regulated by the local Dorbars4 while some are still unregulated and run independently by the owners. In most cases, causal labour and self-employment provide major opportunities for local communities particularly to women to enhance their livelihood opportunities from tourism. Here, unlike the formal employment, selfemployment tends to highlight the entrepreneurial spirit of village communities. Significant gains also accrue from economic linkages between tourism and other economic sectors like agriculture, horticulture, animal husbandry and handicrafts (Shah and Gupta, 2000; De and Devi, 2010).
Though a number of studies examined the role of tourism in providing employment to semi-skilled and unskilled labourer (John, 1974; Attanayake, Samaranayake and Ratnapala, 1983), its contribution to economic development in various countries (Elkan, 1975, Farver, 1984; Wilkinson, 1989; Blake, 2000; Kweka 2004; McCatty and Serju, 2006; Ajala, 2008; Pratt, 2009; Marcouiller, 2007; Isserman 2001; OECD 1999; Power 1988; Deller, Tsai, Marcouiller and English 2001) and its distributional impact in the rural society (McGranahan, 1999; Marcouiller Kim and Deller (2004) only very few tried to explore its impact on women (UNED-UK, 1999), and also its effect on their social, moral and family life (Mings, 1978; Wilkinson, 1989). Riley and Szivas (2009) opined that the creation of new jobs by the development of tourism alone does not lead automatically to the creation of wealth for the indigenous population because new jobs may not provide an acceptable standard of living, which in turn leads to an abnormal extension of effort in terms of hours worked. From the micro-level study of unskilled labour they proved the downward slopping nature of labour supply function indicating the distress supply of labour in the tourism sector and thus raised doubt about the actual impact of tourism on removing poverty (Riley and Szivas, 2009). The returns to unskilled workers engaged in tourism related industries were found to be less than those to other tourism related occupations such as skilled workers or entrepreneurs, even in the expanding phase of the industry (Blake et al, 2008). In Meghalaya, majority of the vendors (food as well as handicraft or handloom items) around the tourist sites are owned by the local tribal women. Despite being small businesses under informal sector, majority of them run their shops from 10 to 25 years displaying their indigenous skills, foods, various other items and earning sustenance. As many of the products generated from the minor non-timber forest produces adverse impact on the local environment is at very low.
MATERIALS AND METHODS
In order to examine the involvement of women (here almost everybody is indigenous tribal except a very few unlike that of men) and the potential of tourism for the generation of income and employment for female and male both; a primary survey was conducted in Shillong, the capital city of Meghalaya where most of the tourists stay throughout the year and around some major sites viz Lady Hydari Park (situated within the city), Shillong Peak (the highest peak of the state at about 15Km away from the capital city) and Cherrapunjee area (the wettest place on the earth, about 55Km away). Data were collected from 256 individuals by simple random sampling, from those who have been engaged in different categories of tourism related activities and earn their livelihood in various capacities from the/vicinity of those selected sites and cater to the needs of the
4 Dorbar is local community based traditional institution (like local self government or panchayat in various states of India) whose members are mostly male and that takes care of local administration in regard to various social, economic and developmental activities.
tourists visiting Shillong in general and those sites in particular. Out of them 48 were hotel owners, 36 were the heads of various restaurants, 24 were heads of fast food stalls and 20 street food stalls in vicinity of the sites, 68 were the vendors in those sites and 40 and 20 numbers of tourist and local taxis. The numbers here were not in proportion to the total number of various units operating in all the tourist sites of Meghalaya. The data were collected over the span of year 2009-10 in order to obtain reliable income estimates from the respondents in the lean as well as peak season.
Though tourism activities vary across the seasons of the year (due to the official vacation in the regions of origin of tourists and variation in temperature and other climatic conditions in the tourist destinations) much variation was not occurred across the seasons. Throughout the year hotels in and around the capital city remain booked in Meghalaya except a few winter months. The peak season ranges from April to October and the lean season constitutes of the remaining five months. Though month-wise distribution of tourist arrivals in the state was not available from official records (it is now available for recent years only), from the records of the a few renowned hotels and the entry tickets sold at those three major spots in the previous year we came to the conclusion that about seventy per cent of the yearly visitors visit during those seven months while the other thirty per cent of the tourists visit during the remaining five months. The potential impact of tourism on the income and employment could be analysed through the computation of its multiplier impact reflected in the directly related activities such as tourist guide, park guards and monitors, vendors in the sites, food courts in the sites and the vehicles, hotels used by the tourists and the indirectly related activities such as artisans whose products reach the tourist sites via several hands, suppliers of vegetables, milk, meat etc and producers of those items, the producers of inputs used in the production of those items and so on. Similarly, employment and income generated in the producing units of inputs used by the transport vehicles etc. Thus it has a long chain of impacts. The data of which was very difficult to obtain. Most of the hotel and restaurant owners were also unwilling to share their information on investment and expenditures and response rates were below 50 per cent. But the response rates of the vendors, tourist vehicles owners were outstanding. Thus it was very difficult to estimate the multiplier impact of unit investment in tourism sector and neither the input-output analysis could be applied. Moreover, there is public investment in tourism sector like construction of road, park improvement that has direct influence on the visit rate.
Considering the above mentioned facts, the seasonal variation in income and employment of the major tourism related activities has been considered and compared with the variation in visit rate. The variation in visit rate during peak and lean months has direct impact on the hotel rents and earning of restaurants, rates of vehicles as well as the sale of the vendors. Thus, variation in income and employment generated from lean to peak season were estimated by taking into account the variation in number of visitors faced by those surveyed units. It was then used to infer about the changes in employment and income of both male and female run enterprises as well as for both male and female in general owing to changes in tourist arrival. It may be noted that the visitors faced by the respective surveyed categories were not the total number of visitors (as only a part of the individuals involved in each category were surveyed but all the vendors in those sites were surveyed), which was much more than that. Of course, one may estimate the total number of employment just by considering the total units operating in the state under each category. But various categories of people involved indirectly in tourism related activities and many of them also operate multiple activities, which was very difficult to consider. But, one may safely assert that the variation in number of tourists faced by the surveyed individuals of different categories is proportional to the variation in tourists visited the sites in lean and peak season and hence the generalization of variation in income and employment generated due to variation in arrival of tourists from the estimated results would not be an exaggeration. Due to the aforesaid problem in estimating total employment and also income generated, in the study employment and income elasticity with respect to visiting tourists and not the investment in tourism that would provide a clear idea about the impact of tourism in the state (De and Devi, 2010).
OBSERVATION AND ANALYSIS
Distribution of the Surveyed Respondents According to their Gender
Table-1 indicated that the larger portion of the vendors, fast food stalls were own by the females and they were all local tribal. Whereas, majority of hotels and restaurants have been running by the male and all the taxi drivers were men. In Meghalaya, presence of women is abundant in almost all the social and economic activities excepting the political field, taxi or bus driving occupation and in the hotel and restaurant business (De and Ghosh, 2011). Though some indigenous women owners of hotel and restaurant are there, those have been practically managed by the males. As per the gender-wise distribution of tourism related employment a clear glass ceiling was observed where the indigenous women were mostly engaged in comparatively inferior occupation in terms of job status and earning opportunity as evident from the later part of discussion.
Table-1: Distribution of the Surveyed Respondents According to their Gender
| Category | Male | Female | Total |
|---|---|---|---|
| Hotel | 42 (87.50) | 6 (12.50) | 48 |
| Restaurant | 30 (83.33) | 6 (16.67) | 36 |
| Fast Food stall | 8 (33.33) | 16 (66.67) | 24 |
| Street Food stall | 12 (60.00) | 8 (40.00) | 20 |
| Tourist Taxi | 40 (100) | 0 (00) | 40 |
| Local Taxi | 20 (100) | 0 (00) | 20 |
| Vendors | 10 (14.71) | 58 (85.29) | 68 |
| Total | 162 (63.28) | 94 (36.72) | 256 |
Source: Field Survey by the researcher during 2009–10. Note: Figures in the parentheses represent percentage to total.
Distribution of the Surveyed Respondents According to their Level of Education:
Table 2 revealed that about 41 per cent of the respondents were graduate or above. About 55 per cent (5a+6a) of the 162 male respondents were graduate or above while only 8 per cent (5b+6b) of the 94 female respondents were graduate or above. Over 41 per cent (20+22+17+8 = 67 in total) of male respondents, with graduates or above were engaged in hotel or restaurant businesses. On the other hand, only 4 (1+1+2+0) female respondents (4.26 per cent) with graduates or above were engaged in hotel and restaurant businesses. A few male respondents despite graduate were in transport business and most of them were owner and just manage the businesses engaging driver and other workers. Majority (14+37+35) of women respondents (91.5 per cent) were below graduate and mostly they were engaged in vending, fast food or street food business in various tourist sites.
Thus, majority of the highly educated people engaged in tourism and hospitality sector in Meghalaya were male and they were largely involved in hotel and restaurant business, though a few middle level or low educated male were in driving, fast food stalls and even in vending. Majority of the low educated people in the tourism and hospitality sector in Meghalaya were female and majority of them were in vending or various food stall businesses. Actually, a number of hotels and renowned restaurants in the capital city Shillong where several tourists stay at night after visiting various sites during day time are owned by the better educated non-tribal people either from Meghalaya or outside. Despites low educated the indigenous people especially the women are mostly functioning in the tourist sites and engaged in selling food staffs which are of indigenous in nature for their demand by tourists of various categories, and also sell locally made handicraft and hand loom items. The handicraft items were mostly prepared from the locally available non-timber forest products available in the commonly accessible forest and thus they have dominance in such activities due to their traditional knowledge and culture.
Table-2: Distribution of the Surveyed Respondents According to their Level of Education
| Below Secondary | Secondary but below HS | HS but below Graduate | Graduate & above | Professional | Category Total | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2a | 2b | 3a | 3b | 4a | 4b | 5a | 5b | 6a | 6b | 7a | 7b |
| Category | M | F | M | F | M | F | M | F | M | F | M | F |
| Hotel | 0 (00) | 0 | 0 (00) | 0 (00) | 0 | 4 | 20 | 1 | 22 | 1 | 42 | 6 |
| (00) | (00) | (66.6 | (47.6 | (16.6 | (52.38) | (16.6 | ||||||
| 7) | 2) | 7) | 7) | |||||||||
| Restaura | 0 (00) | 0 | 0 (00) | 2 | 5 | 2 | 17 | 2 | 8 | 0 | 30 | 6 |
| nt | (00) | (33.33) | (16.6 | (33.3 | (56.6 | (33.3 | (26.67) | (00) | ||||
| 7) | 3) | 7) | 3) | |||||||||
| Fast | 0 (00) | 2 | 2 | 6 | 4 | 6 | 2 | 2 | 0 (00) | 0 | 8 | 16 |
| Food | (16.6 | (25.0) | (37.5) | (50.0 | (37.5 | (25.0 | (16.6 | (00) | ||||
| stall | 7) | ) | ) | ) | 7) | |||||||
| Street | 3 | 4 | 5 | 4 | 4 | 0 | 0 | 0 | 0 (00) | 0 | 12 | 8 |
| Food | (25.0) | (50.0 | (41.67) | (50.0) | (33.3 | (00) | (00) | (00) | (00) | |||
| stall | ) | 3) | ||||||||||
| Tourist | 2 | 0 | 8 | 0 (00) | 16 | 0 | 14 | 0 | 0 (00) | 0 | 40 | 0 |
| Taxi | (5.0) | (00) | (20.0) | (40.0 | (00) | (35.0 | (00) | (00) | ||||
| ) | ) | |||||||||||
| Local | 4 | 0 | 6 | 0 (00) | 6 | 0 | 4 | 0 | 0 (00) | 0 | 20 | 0 |
| Taxi | (20.0) | (00) | (30.0) | (30.0 | (00) | (20.0 | (00) | (00) | ||||
| ) | ) | |||||||||||
| Vendors | 4 | 8 | 3 | 25 | 1 | 23 | 2 | 2 | 0 (00) | 0 | 10 | 58 |
| (40.0) | (13.8 | (30.0) | (43.1) | (10.0 | (39.6 | (20.0 | (3.45 | (00) | ||||
| 0) | ) | 6) | ) | ) | ||||||||
| Sex | 13 | 14 | 24 | 37(39. | 36 | 35 | 59 | 7 | 30 | 1 | 162 | 94 |
| Wise | (8.02) | (14.9 | (14.8) | 36) | (22.2 | (37.2 | (36.4 | (7.45 | (18.52) | (1.06 | ||
| Total | ) | 2) | 3) | 1) | ) | ) | ||||||
| Overall Total | 26 (10.16) | 60 (23.44) | 66 (25.78) | 68 (26.56) | 36 (14.06) | 256 |
Source: Field Survey by the researcher during 2009-10.
Note: Figures in the parentheses represent percentage to total of each category.
Distribution of Respondents According to the Total Number of their Employees in their Respective Businesses during Lean and Peak Seasons:
Since the respondents of both genders were mostly dependant on the tourist inflow to these areas for their activities, the number of employees/assistants that they hired in the different seasons of the year may indicate the nature of their economic gains from tourism in different seasons. Among the 94 female respondents, about 62 per cent were vendors engaged in various vendor stalls selling various local handicraft and handloom items, selling and renting indigenous dress to the visitors, food items of indigenous and imported varieties and catering various other needs of the tourists. About 17 per cent of them were in fast food stalls and very few were in hotel and restaurants businesses.
On the other hand, out of 162 male respondents, about 26 and 18.52 per cent were in hotel and restaurant businesses respectively. About 25 and 12 per cent were in transportation, i.e., running taxis of different types. Comparison of various categories revealed that most of hotel and restaurant as well as transport businesses were occupied by the males while majority of vending businesses and fast food stalls were dominated by the females who hailed from various local indigenous communities.
Comparison of Tables 3a and 3b reveals that frequencies of having larger number of employees increased significantly during the peak season in all the categories despite their differences in percentage of growth. In all the categories increased requirement of labour during peak season has been met by employing casual/daily labourer. Shifting of percentage of respondents from less employee category to higher category was observed mostly in case of Hotels and restaurants as well as vendors. Among them women who own and work as vendor were benefitted more than the other categories, while in the hotel and restaurant categories men were benefitted more. During lean season none of the respondents was found in the group of having employee 21 and above. But during peak season 9.52 and 23.81 per cent of the male owned hotels were having employees of 21-25 and 26 or more respectively and all of them were male. On the other hand, 44.83 and 51.72 per cent of the female vendors had employees 3 or less and 4-6 respectively during the lean seasons. Merely a few male respondents were in those two categories. However, during peak season 34.48, 46.55 and 18.97 per cent of female respondent vendors were observed in the employment size of 3 or less, 4-6 and 7-9 respectively. It was clear that in terms of employment females were highly benefitted in the category of informal sector and relatively inferior occupation; while men were mostly benefitted in relatively better occupation and organised sector.
In respect of income categories 28.57, 23.81 and 23.81 per cent of the 42 male hotel owners, belonged to the categories of monthly income group of 75,001-90,000 INR, 90,001-1,05,000 INR and more than 1,05,000 INR respectively during lean season. While 33.33 per cent of a few (6) female hotel respondents were each in the monthly income group of 45,001-60,000 INR, 60,001-75,000 INR and 75,001-90,000 INR categories respectively and none was in the higher earning group during lean season. In the peak season 9.52, 23.81 and 66.67 per cent of male respondents in the hotel category, were found in the monthly earning groups of 75,001-90,000, 90,001-1,05,000 and more than 1,05,000 INR; while percentage of female hotel owners were same 33.33 in just one level up from their lean season monthly earning (Tables 4a and 4b).5
In the females dominated vendor category, about 81.03 per cent of the 58 female vendors were in the below 15,000 INR during the lean season and only 10.34 per cent of them was in the 30,001-45,000 INR monthly earning group; where as many of them were shifted to the next higher income group during the peak season 20.69, 68.97 and 10.34 per cent of those female vender respondents were found in the monthly earning group of 15,001-30,000 INR, 30,001-45,000 INR and 45,001-60,000 INR. Very few male were
5 Here INR indicates Indian Rupees
Utpal Kumar De
there in every income category. Overall, about 28.40 per cent of the male enterprises had monthly earning over 60,000 INR during the lean season and that increased to 54.93 per cent during the peak season. On the other hand, in case of female enterprises; hardly 4.26 per cent had monthly earning of over 60,000 INR and that was increased to about 16 per cent during peak season.
Table-3a: Gender-wise Distribution of the Surveyed Respondents According to the Employee Size in their Respective Businesses during Lean Season
| Size Group | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 3 or less | 4-6 | 7-9 | 10-15 | 16-20 | Total | |||||||
| Category | M | F | M | F | M | F | M | F | M | F | M | F |
| Hotel | 0 (00) | 0 (00) | 2 (4.76 ) | 2 (33.33 ) | 16 (38. 10) | 2 (33. 33) | 16 (38. 10) | 2 (33. 33) | 8 (19. 05) | 0 (00) | 42 (25.9 2) | 6 (6.38) |
| Restaurant | 0 (00) | 0 (00) | 4 (13.3 3) | 3 (50.0) | 3 (10. 0) | 2 (33. 33) | 13 (43. 33) | 1 (16. 67) | 10 (33. 33 | 0 (00) | 30 (18.5 2) | 6 (6.38) |
| Fast Food stall | 5 (62. 50) | 12 (75. 0) | 3 (37.5 0) | 4 (25.0) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 8 (4.94) | 16 (17.0 2) |
| Street Food stall | 12 (10 0) | 8 (10 0) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 12 (7.41) | 8 (8.51) |
| Tourist Taxi | 40 (10 0) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 40(24 .69) | 0 (00) |
| Local Taxi | 20 (10 0) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 20 (12.3 5) | 0 (00) |
| Vendors | 7 (70. 0) | 26 (44. 83) | 2 (20.0 ) | 30 (51.72 ) | 1 (10. 0) | 2 (3.4 5) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 10 (6.17) | 58 (61.7 0) |
| Total | 84 (51. 85) | 46 (48. 94) | 11 (6.79 ) | 39 (41.49 ) | 20 (12. 35) | 6 (6.3 8) | 29 (17. 90) | 3 (3.1 9) | 18 (11. 11) | 0 (00) | 162 (100) | 94 (100) |
Source: Field Survey by the researcher during 2009–10. Note: Figures in the parentheses of size group represent percentage to grand total of that category for each sex. But the parentheses of total of last column show the proportion of male and female in each occupation to total male or female.
Table-3b: Gender-wise Distribution of the Surveyed Respondents According to the Employee Size in their Respective Businesses during Peak Season
| Size Group | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 3 or less | 4-6 | 7-9 | 10-15 | 16-20 | 21-25 | 26 & | Total | |||||||||
| above | ||||||||||||||||
| Cate | M | F | M | F | M | F | M | F | M | F | M | F | M | F | M | F |
| gory | ||||||||||||||||
| Hotel | 0 (00) | 0 (00) | 0 (00) | 0 (0 0) | 13 (30. 95) | 3 (5 0. 0) | 9 (21. 43) | 3 (50. 0) | 6 (14. 29) | 0 (00) | 4 (9.5 2) | 0 (00) | 10 (23. 81) | 0 (0 0) | 42 (25. 92) | 6 (6.3 8) |
| Resta urant | 0 (00) | 0 (00) | 0 (00) | 0 (0 0) | 3 (10. 0) | 3 (5 0. 0) | 4 (13. 33) | 2 (33. 33) | 5 (16. 67 | 1 (16. 67) | 6 (20. 0) | 0 (00) | 12 (40. 0) | 0 (0 0) | 30 (18. 52) | 6 (6.3 8) |
| Fast Food stall | 3 (37. 5) | 6 (37. 5) | 4 (50. 0) | 8 (5 0. 0) | 1 (12. 5) | 2 (1 2. 5) | 0 (00 ) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (0 0) | 8 (4.9 4) | 16 (17. 02) |
| Street Food stall | 12 (10 0) | 8 (10 0) | 0 (00) | 0 (0 0) | 0 (00 ) | 0 (0 0) | 0 (00 ) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (0 0) | 12 (7.4 1) | 8 (8.5 1) |
| Touri st Taxi | 40 (10 0) | 0 (00) | 0 (00) | 0 (0 0) | 0 (00 ) | 0 (0 0) | 0 (00 ) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (0 0) | 40 (24. 69) | 0 (00) |
| Local Taxi | 20 (10 0) | 0 (00) | 0 (00) | 0 (0 0) | 0 (00 ) | 0 (0 0) | 0 (00 ) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (0 0) | 20 (12. 35) | 0 (00) |
| Vend ors | 4 (40. 0) | 20 (34. 48) | 3 (30. 0) | 27 (4 6. 55 ) | 3 (30. 0) | 11 (1 8. 97 ) | 0 (00 ) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (0 0) | 10 (6.1 7) | 58 (61. 70) |
| Total | 79 (48. 77) | 34 (36. 17) | 7 (4.3 2) | 35 (3 7. 23 ) | 20 (12. 35) | 19 (2 0. 21 ) | 13 (8.0 2) | 5 (5.3 2) | 11 (6.7 9) | 1 (1.0 6) | 10 (6.1 7) | 0 (00) | 22 (23. 40) | 0 (0 0) | 162 (10 0) | 94 (10 0) |
| Source: | Same as table-3a. Note: | Same as table-3a. |
Table-4a: Gender-wise Distribution of the Surveyed Respondents According to their Net Monthly Income during Lean Season
| 500 | - | Mon | thly In | roup D | ason (in | INR) | /a | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Num ber | 1500 Le | 00000000 | 01 - 000 | 300 450 | 450 600 | 01- 000 | 01- 000 | 750 900 | 9000 1050 | 10 m | Mo tha 1050 | n | To | tal | ||||
| Categ | M | F | M | F | M | F | M | F | M | F | M | F | M | F | M | F | M | F |
| Hotel | 0 (00) | 0 (00) | (00) | 0 (00) | (00) | (00) | (9.5 2) | 2 (33. 33) | 6 (14. 29) | (33. 33) | 12 (28. 57) | (33 .33 | 10 (23. 81) | 0 (0 0) | 10 (23. 81) | 0 (0 (0) | 42 (25. 92) | 6 (6.3 8) |
| Resta urant | 0 (00) | 0 (00) | 5 (16. 67) | 3 (50. 0) | 7 (23. 33) | 3 (50. 0) | 10 (33. 33) | (00) | 6 (20. 0) | 0 (00) | 0 (00) | (00 | 1 (3.3 3) | 0 (0 0) | (3.3 | 0 (0 (0) | 30 (18. 52) | 6 (6.3 8) |
| Fast Food stall | 0 (00) | 0 (00) | (62. 5) | 11 (68. 75) | 1 (12. 5) | 3 (18. 75) | (25. 0) | 2 (12. 5) | 0 (00) | 0 (00) | 0 (00) | (00 | 0 (00) | 0 (0 0) | (00) | 0 (0 0) | (4.9 4) | 16 (17. 02) |
| Street Food stall | 11 (91. 67) | 7 (87. 5) | (8.3 3) | 1 (12. 5) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | (00 | 0 (00) | 0 (0 0) | 0 (00) | 0 (0 (0) | 12 (7.4 1) | (8.5 1) |
| Touri st Taxi | (10. 0) | 0 (00) | 18 (45. 0) | 0 (00) | 15 (37. 5) | 0 (00) | 3 (7.5 0) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | (00 | 0 (00) | 0 (0 0) | 0 (00) | 0 (0 0) | 40 (24. 69) | (00) |
| Local Taxi | 4 (20. 0) | (00) | 10 (50. 0) | 0 (00) | 4 (20) | (00) | 2 (10) | (00) | 0 (00) | 0 (00) | (00) | (00 | 0 (00) | 0 (0 0) | (00) | 0 0 0 | 20 (12. 35) | (00) |
| Vend ors | 7 (70. 0) | 47 (81. 03) | 3 (30. 0) | 5 (8.6 2) | 0 (00) | 6 (10. 34) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | 0 (00) | (00 | 0 (00) | 0 (0 0) | 0 (00) | 0 (0 0) | 10 (6.1 7) | 58 (61. 70) |
| Total | 26 (16. 05) | 54 (57. 45) | 42 (25. 93) | 20 (21. 28) | 27 (16. 67) | 12 (12. 77) | 21 (12. 96) | (4.2 (6) | 12 (7.4 1) | (2.1 (3) | 12 (7.4 1) | (2. 13) | 11 (6.7 9) | 0 (0 0) | 11 (6.7 9) | 0 (0 0) | 162 (10 0) | 94 (10 0) |
Source: Field Survey by the researcher during 2009–10. Note: Figures in the parentheses of rows represent percentage to grand total of category; while figures in the parentheses of the last column represent percentage of the column total.
Table-4b: Gender-wise Distribution of the Surveyed Respondents According to their Net Monthly Income during Peak Season
| Mont | hly In | come G | roup I | uring l | Peak S | eason (i | in INR) | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Num ber | 1500 Le | A 100 CO 1 | 001- 000 | 375 (2.6) | 001- 000 | 001- 000 | 538505 | 001- 000 | 001- 000 | 01 – 000 | Mo tha 1050 | n | To | tal | ||||
| Cate | М | F | М | F | M | F | M | F | M | F | М | F | M | F | M | F | M | F |
| Hotel | (00 (00 | (00 | (00 | 00) | 0 (00 ) | (00 | (00 | (00 | (00 | (33. 33) | 4 (9.5 2) | (33. 33) | 10 (23. 81) | (33. 33) | 28 (66. 67) | 0 (0 0) | 42 (25. 92) | (6.3 8) |
| Resta urant | (00 | (00 | (00 | (00 | (00 | (00 | (00 | (33. (33) | 4 (13. 33) | (66. 67) | 10 (33. 33) | (00 | 12 (40. 0) | (00 | (13. 33) | 0 (0 0) | 30 (18. 52) | 6 (6.3 8) |
| Fast Food stall | (00 | (00 | (00 | (00 | (25. 0) | 4 (25. 0) | 3 (37. 5) | 7 (43. 75) | 3 (37. 5) | 5 (31. 25) | (00 | (00 | (00 | (00 | (00 | 0 (0 0) | 8 (4.9 4) | 16 (17. 02) |
| Street Food stall | 2 (16. 67) | 4 (50 .0) | (33. 33) | (25. 0) | (33. 33) | (25. 0) | 2 (16. 67) | (00 | (00 | (00 | (00 | (00 | (00 | (00 | (00 | 0 (0 0) | 12 (7.4 1) | (8.5 1) |
| Touri st Taxi | (00 | (00 | (00 ) | (00 | (20. 0) | (00 | 20 (50. 0) | (00 | 12 (30. 0) | (00 | (00 ) | (00 | (00 ) | (00 | (00 | 0 (0 0) | 40 (24. 69) | (00 |
| Local Taxi | (00 ) | (00 | (20. 0) | (00 | (40. 0) | (00 | (30. (3) | (00 | (10. 0) | (00 | (00 | (00 | (00 | (00 | (00 | 0 (0 0) | 20 (12. 35) | (00 |
| Vend ors | (00 (00 | (00 | (40. (0) | 12 (20. 69) | 4 (40. 0) | 40 (68. 97) | (20. (0) | 6 (10. 34) | (00 | (00 | (00 | (00 | (00 | (00 | (00 | 0 (0 0) | 10 (6.1 7) | 58 (61. 70) |
| Total | (1.2 (3) | 4 (4. 26) | 12 (7.4 1) | 14 (14. 89) | 26 (16. 05) | 46 (48. 94) | 33 (20. 37) | 15 (15. 96) | 21 (12. 96) | 11 (11. 70) | 14 (8.6 4) | (2.1 (3) | 22 (13. 58) | (2.1 (3) | 32 (19. 75) | (O (O) | 162 (10 0) | 94 (10 0) |
Source: Field Survey by the researcher during 2009–10. Note: Figures in the parentheses of rows represent percentage to grand total of category; while figures in the parentheses of the last column represent percentage of the column total.
Around 79 per cent of all female enterprises have monthly income 30,000 INR or below and only about 13 per cent were in the monthly earning group of 30,001-60,000 INR during lean season. It was changed to about 7 per cent and 24 per cent respectively during peak season. But, in case of male enterprises, around 27 and 19 per cent of the respondents were in the monthly income group of below 30,001 and 30,001-60,000 INR during lean season and that changed to 5.47 and about 24 per cent respectively during peak season.
Thus, it appeared that the male enterprises were more benefitted in terms of increase in monthly earning through various rising organised tourism related activities due to arrival of more tourists during the peak season, which have been furthered with the lengthening of peak season due to the disturbances in other prominent tourist areas of the country and diversion of tourists towards Meghalaya.
Table-5 shows that there was an overall 47.53 per cent growth in employment from lean to peak tourist season of the year. The restaurants recorded the largest beneficiary in terms of employment generated (62.76 per cent) and followed by the vendors category with about 49 per cent increase in employment. The increased labour requirement in the peak season has been met by employing mostly temporary labourer. The least benefitted are the street food stalls where very less labour is required to run the businesses.
In the restaurant or food stalls categories as well as vendors in Meghalaya the female employment have been increased in more proportion than their male counterpart. Of course, in the restaurants or hotels whatever female employment was observed; were mostly the lower status jobs e.g., sweeper, vegetable processor, helper of cooks, and the like. Whereas the officials, managers, supervisors have been found to be all male. Thus, a clear cut glass ceiling of gender distribution in the tourism activities was observed where females were employed in low status, informal sector businesses and males were mostly in the organised and relatively higher status and higher paying jobs. Overall, in terms of number, employment of females increased marginally higher than that of males despite the fact that the employment in transport and communication were all male.
Table-6 reveals that in all categories of tourism related business per unit earning of the establishments run by male (where mostly males were employed) were much higher than that of females except the vendor categories in both the lean and peak season. But there was relatively larger growth of income from lean to peak season in case of females for fast food stall and vendor category, while in other categories like hotel and restaurants male run establishments were more benefitted. Overall, growth of income by about 64 per cent was recorded and the figure was about 97 per cent for the females and that was 55.54 in case of males (Table-6). Table-7 reveals that in the category of hotel and vendor categories employment growth from lean to peak season has been higher for females and it is reversed in other categories.
The estimated income and employment elasticity as shown in Table-8 indicate the growth of income and employment due to marginal change in tourist inflow as reported by the surveyed tourism related establishments. The overall income and employment elasticity were 0.37 and 0.27 respectively. Both the income and employment elasticity were significantly higher in case of females than that of males (Table-8) though per unit earning of the primary hospitality business (hotel and restaurant in both lean and peak season) was higher for males than that of females (last row of Table-6).
Table-5: Gender-wise Percentage Variation in Average Daily Employment of Various Establishments from Lean to Peak Season as Observed from the Sample Survey
| Category | Per Unit | t Employe | es in Lean | Per Un | it Employ | ees in | Percentage Variation | |||
|---|---|---|---|---|---|---|---|---|---|---|
| Season ( | (No) | Peak S | eason (No | ) | ||||||
| Male | Female | Over all | Male | Female | Over | Male | Fema | Over | ||
| all | le | all | ||||||||
| Hotel | 11.05 | 8.33 | 12.24 | 15.48 | 11.67 | 15.00 | 40.09 | 40.00 | 40.08 | |
| Restaurant | 12.83 | 7.00 | 11.86 | 20.80 | 11.83 | 19.31 | 62.08 | 69.05 | 62.76 | |
| Fast Food stall | 3.50 | 3.13 | 3.25 | 4.63 | 4.75 | 4.71 | 32.14 | 52.00 | 44.87 | |
| Street Food | 2.33 | 1.75 | 2.10 | 2.33 | 2.00 | 2.20 | 0.00 | 14.29 | 4.76 | |
| stall | ||||||||||
| Tourist Taxi | 1.20 | 00 | 1.20 | 1.70 | 00 | 1.70 | 41.67 | 00 | 41.67 | |
| Local Taxi | 1.40 | 00 | 1.40 | 1.70 | 00 | 1.70 | 21.43 | 00 | 21.43 | |
| Vendors | 3.40 | 3.53 | 3.51 | 5.00 | 5.28 | 5.24 | 47.06 | 49.27 | 48.95 | |
| Total | 6.27 | 3.84 | 5.38 | 9.20 | 5.73 | 7.93 | 46.90 | 49.31 | 47.53 | |
Note: Estimated from the field survey conducted during 2009-10. Total employment of each category is divided by number of units of that category under each sex.
Table-6: Gender-wise Percentage Variation in Average Monthly Income of Various Establishments from Lean to Peak Season as Observed from the Sample Survey
| Category | it Income Season (Rs | t Income in eason (Rs) | Percer | ntage Vari | ation | ||||
|---|---|---|---|---|---|---|---|---|---|
| Male | Female | Over all | Male | Female | Over all | Male | Female | Over all | |
| Hotel | 86,428 | 67,500. | 84,062. | 1,05,738. | 78,500. | 1,02,33 | 22.34 | 16.30 | 21.73 |
| .57 | 00 | 50 | 10 | 00 | 3.33 | 22.34 | 10.50 | 21.73 | |
| Restaurant | 50,250 | 30,000. | 46,875. | 94,733.3 | 55,000. | 88,111. | 88.52 | 83.33 | 87.97 |
| .00 | 00 | 00 | 3 | 00 | 11 | 00.32 | 05.55 | 01.91 | |
| Fast Food stall | 31,875 | 29,062. | 30,000. | 54,375.0 | 51,468. | 52,437. | 70.59 | 77.10 | 74.79 |
| .00 | 50 | 00 | 0 | 75 | 50 | 10.39 | 77.10 | 14.19 | |
| Street Food | 11,041 | 11,562. | 11,250. | 30,416.6 | 20,000. | 26,250. | 175.47 | 72.97 | 133.3 |
| stall | .67 | 50 | 00 | 7 | 00 | 00 | 173.47 | 12.91 | 3 |
| Tourist Taxi | 29,125 | Nil | 29,125. | 54,000.0 | Nil | 54,000. | 85.41 | Nil | 85.41 |
| .00 | INII | 00 | 0 | INII | 00 | 65.41 | INII | 65.41 | |
| Local Taxi | 26,000 | Nil | 26,000. | 42,000.0 | Nil | 42,000. | 61.54 | Nil | 61.54 |
| .00 | INII | 00 | 0 | INII | 00 | 01.34 | INII | 01.54 | |
| Vendors | 13,750 | 13,922. | 13,897. | 34,500.0 | 35,482. | 35,338. | 150.01 | 154.86 | 154.2 |
| .00 | 41 | 06 | 0 | 76 | 24 | 150.91 | 134.80 | 9 | |
| Total | 45,354 | 20,744. | 36,318. | 70,543.2 | 40,877. | 59,650. | 55.54 | 97.05 | 64.24 |
| .94 | 68 | 36 | 1 | 66 | 39 | 55.54 | 97.03 | 04.24 |
Note: Estimated from the field survey conducted during 2009-10. Total income of each category is divided by number of units of that category under each sex.
Table-7: Percentage Variation in Daily Average Number of Tourists Visiting Various Surveyed Establishments from Lean to Peak Season
| Estab | пэшиси | is moin LC | an to 1 ear | x ocason | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Category | Tourists i eason (No) | Tourists | s in Peak S (No) | Season | Percentage Variation | ||||||
| Male | Female | Over all | Male | Female | Over all | Male | Female | Over all | |||
| Hotel | 6 | 7 | 6 | 15 | 17 | 15 | 148.00 | 150.00 | 148.28 | ||
| Restaurant | 8 | 8 | 8 | 21 | 18 | 20 | 148.00 | 120.00 | 143.33 | ||
| Fast Food stall | 11 | 13 | 12 | 31 | 31 | 31 | 177.78 | 150.00 | 158.62 | ||
| Street Food stall | 5 | 6 | 6 | 14 | 12 | 13 | 183.33 | 96.00 | 143.64 | ||
| Tourist Taxi | 5 | 0 | 5 | 10 | 0 | 10 | 95.24 | 0 | 95.24 | ||
| Local Taxi | 4 | 0 | 4 | 9 | 0 | 9 | 125.00 | 0 | 125.00 | ||
| Vendors | 94 | 89 | 90 | 315 | 243 | 254 | 235.11 | 173.06 | 182.62 | ||
| Total | 12 | 59 | 29 | 33 | 158 | 79 | 187.23 | 170.87 | 175.04 | ||
Note: Estimated from the field survey conducted during 2009-10. Total number of visitors faced by each category is divided by number of units of that category under each sex.
Table-8: Income and Employer Multiplier of Tourism in Meghalaya
| Employr | nent Elastic | city | Income | Elasticity | |
|---|---|---|---|---|---|
| Male | Female | Total | Male | Female | Total |
| 0.27 | 0.27 | 0.27 | 0.15 | 0.11 | 0.15 |
| 0.42 | 0.58 | 0.44 | 0.60 | 0.69 | 0.61 |
| 0.18 | 0.28 | 0.24 | 0.40 | 0.41 | 0.40 |
| 0.00 | 0.15 | 0.03 | 0.96 | 0.76 | 0.93 |
| 0.44 | 0.00 | 0.44 | 0.90 | 0.00 | 0.90 |
| 0.17 | 0.00 | 0.17 | 0.49 | 0.00 | 0.49 |
| 0.20 | 0.28 | 0.27 | 0.64 | 0.89 | 0.84 |
| 0.25 | 0.29 | 0.27 | 0.30 | 0.57 | 0.37 |
| Male 0.27 0.42 0.18 0.00 0.44 0.17 0.20 | Male Female 0.27 0.27 0.42 0.58 0.18 0.28 0.00 0.15 0.44 0.00 0.17 0.00 0.20 0.28 | 0.27 0.27 0.27 0.42 0.58 0.44 0.18 0.28 0.24 0.00 0.15 0.03 0.44 0.00 0.44 0.17 0.00 0.17 0.20 0.28 0.27 | Male Female Total Male 0.27 0.27 0.27 0.15 0.42 0.58 0.44 0.60 0.18 0.28 0.24 0.40 0.00 0.15 0.03 0.96 0.44 0.00 0.44 0.90 0.17 0.00 0.17 0.49 0.20 0.28 0.27 0.64 | Male Female Total Male Female 0.27 0.27 0.27 0.15 0.11 0.42 0.58 0.44 0.60 0.69 0.18 0.28 0.24 0.40 0.41 0.00 0.15 0.03 0.96 0.76 0.44 0.00 0.44 0.90 0.00 0.17 0.00 0.17 0.49 0.00 0.20 0.28 0.27 0.64 0.89 |
The empowerment aspects:
Not only women are benefitted in terms of employment and income; they also become more empowered at home and in the society. Distribution of 94 sample women respondents of different employment category in terms of their response to improvement of social, economic and psychological indicators is presented in Table-9.
As a primary response to the direct interview reveals that, despite their involvement in relatively inferior occupations they are happy with their business activities and earning. Instead of sitting idle, they are contributing significantly to their total family earnings. However, the fact is that most of the women business owners expect institutional support for the better arrangement of their business establishments and financial support for the expansion of their activities.
| Table-9: Distribution of Women Respondents of Various Tourism Related Activities on |
|---|
| Various Questions Related to Their Empowerment |
| Pattern of | X1 | X2 | X3 | X4 | X5 | X6 | X7 | X8 | X9 |
|---|---|---|---|---|---|---|---|---|---|
| Response | |||||||||
| Strongly Agree | 85.11 | 42.55 | 44.68 | 45.74 | 30.85 | 14.89 | 48.94 | 28.00 | 16.00 |
| Agree | 12.77 | 32.98 | 24.47 | 28.72 | 47.87 | 25.53 | 17.02 | 33.00 | 28.50 |
| Neither Agree | |||||||||
| Nor Disagree | 2.13 | 21.28 | 21.28 | 19.15 | 12.77 | 18.09 | 12.77 | 22.00 | 32.60 |
| Disagree | 0.00 | 3.19 | 9.57 | 6.38 | 4.26 | 23.40 | 14.89 | 14.87 | 12.77 |
| Strongly Disagree | 0.00 | 0.00 | 0.00 | 0.00 | 4.26 | 18.09 | 6.38 | 2.13 | 10.13 |
X1= Spending own earned money by self,
X2= Contribute to children's educational expenses
X3= Activities accelerated the movement and increased freedom to do so without any help,
X4= Participation in various decision making including the way of spending, adoption of children's education, marriage, purchase of property,
X5= Activities increased participation in various social functions,
X6= Changes in adoption of healthcare services,
X7= Taking food whenever feel to take and get required nutrition,
X8= Feel to get more respect in the neighbourhood because of involvement in activities,
X9= Feel that self-decision making power has improved because of tourism activities.
At home, they can participate in the decision making process more, with the rising earning capability, about the running of families, children's education and marriage, have better nutritional intake and earn more respects in their family. Only, in case of taking decision on healthcare the response is mix as still now many of them particularly in interior villages follow the traditional medicines and practices for treatment. These provide the motivation for the engagement of women across all ages to be involved in such activities in accordance with their abilities.
Moreover, as the women can move freely and that is necessary to run their respective business with or without the help of their male counterpart of their family, they are also socially empowered. Thus, the participation in tourism related activities despite their status of works, the indigenous women who are also adept in local handloom and handicrafts and indigenous food products are much empowered socially, economically and psychologically.
A comparison with those who are not involved in such activities would make the proposition clearer. Moreover, the standard of activities and nature of job as well as empowerment level would improve further with the involvement of educated indigenous women and diversifying tourism activities.
Concluding Remarks
Women play an important role in the management of various tourism related activities in Meghalaya. Being an indigenous tribal society, which is matrilineal, women have been engaged in various social and economic activities and they are freer than any non-tribal patriarchal society. So their involvement in tourism and hospitality sector is not an exception. Observations however revealed that in category of employment generated educational status of women relatively lower than that of men and it has the parity with the status of job created for women.
They have been involved in relatively low paying inferior occupations as compared to men and due to very natural reason not involved in transport sector. Overall, comparison of lean and peak season suggests that expansion of nature based tourism without
damaging the natural environment in Meghalaya substantially help in growth of income and employment of indigenous women involved in various tourism related activities along with men. Despite low rate of per capita earning, prospect of women are found to be more in terms employment and income benefit from the growth of nature based tourism. The economic independence provides women better status and empower themselves economically, socially and also psychologically leading to improvement in their decision making capability. It thus suggests the policy requirement for promoting more nature based tourism to create better scope for them.