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Kumar, Suneel
- Understanding the Dynamics of Length of Stay of Tourists in India through Interpretive Structure Modeling
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PDF Views:201
Authors
Affiliations
1 Department of Commerce, Delhi School of Economics, University of Delhi, Delhi, IN
2 Department of Commerce, Shaheed Bhagat Singh College (University of Delhi), Sheikh Sarai, New Delhi, IN
3 Non- Collegiate Women’s Education Board, University of Delhi, Delhi, IN
1 Department of Commerce, Delhi School of Economics, University of Delhi, Delhi, IN
2 Department of Commerce, Shaheed Bhagat Singh College (University of Delhi), Sheikh Sarai, New Delhi, IN
3 Non- Collegiate Women’s Education Board, University of Delhi, Delhi, IN
Source
Review of Professional Management- A Journal of New Delhi Institute of Management, Vol 16, No 2 (2018), Pagination: 14-24Abstract
The purpose of this research paper is to identify the different factors that affect the length of stay of tourists in India and developing a hierarchical relationship between those factors. The factors are grouped into different classifications which will help policymakers to focus on specially identified groups. Interpretive Structural Modeling (ISM) is used to develop the hierarchical relationship. MICMAC ( cross-impact matrix multiplication applied for classification) analysis will be conducted to determine the driving as well as dependence power of the factors involved and to classify them into Driving, Dependent, Autonomous and Linkage factors. Different factors involved are identified from literature and then a questionnaire is prepared to verify whether there exists any relationship between variables. The MICMAC analysis finds that Age of tourist, purpose of visit and budget of tourist are among the driving forces which affect of other variables involved in the system. Average daily expenditure and pre planning of visit are dependents and knowledge of destination is autonomous factors. An ISM model is then prepared on the basis of partition level of factors.
This paper has implications for researchers as well as policymakers. Researchers need to carry out the demographic study of tourists so that the tourists could be divided on the basis of age, nationality, education. Similarly, investigation should be carried out to identify the purpose of visit that impacts length of stay. The policymakers must concentrate on strategies on those groups who stay or can be made to stay for longer length of period.
Keywords
Length of Stay, ISM, MICMAC, Driving Factor, Dependent factor and Autonomous Factor.Full Text
References
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- Kumar, S., Shekhar, & Attri, K. (2018). The Economic Contribution of Tourism Industry in India: An Appraisal. International Journal of Applied Hospitality and Tourism Research, 10(1) 3-12.
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- Trend Analysis of Foreign Direct Investment in Tourism Industry in India:An Empirical Study
Abstract Views :250 |
PDF Views:169
Authors
Suneel Kumar
1,
Anjali Gupta
2
Affiliations
1 Assistant Professor, Department of Commerce, Shaheed Bhagat Singh College, University of Delhi, IN
2 Visiting Faculty, School of Open Learning, University of Delhi, IN
1 Assistant Professor, Department of Commerce, Shaheed Bhagat Singh College, University of Delhi, IN
2 Visiting Faculty, School of Open Learning, University of Delhi, IN
Source
Review of Professional Management- A Journal of New Delhi Institute of Management, Vol 17, No 1 (2019), Pagination: 70-83Abstract
This study attempts to investigate trends of foreign investment in India’s tourism industry on the basis of data on past trends and pattern of FDI flows in this sector. Research adopts both qualitative and quantitative approach on the basis of different secondary sources such as reports, articles, tourism and travel reports, tourism ministries publications to study trends in tourism industry. Then, Granger Causality test is used to study the causal relationship between India’s economic growth and FDI in tourism sector. Time series analysis techniques and Linear regression model are used to establish relation between FDI flows in Indian tourism and identify independent factors. For time series analysis, stationarity is tested by applying ADF unit ischolar_main test. Regression assumptions are also tested and appropriate regression model was fitted using Eviews statistical software. Factors impacting FDI inflows in tourism industry are studied by using regression analysis on the basis of identified independent variables. Results reveal that the Government individual spending and inflation have a key role in impacting FDI inflows positively. While other factors like total tourist visits, exchange rate, GDP contribution of Tourism and Per Capita GDP have an insignificant impact but cannot be altogether ignored and are of significance when taken together. The existing trend and inflows in tourism sector are not encouraging enough thus require much needed effort in direction of promoting India as an investment destination for foreign investors. Authors findings are interesting as they indicates the Govt’s spending are important contributors among other factors and hence, to encourage tourism should support through infrastructural development and strategic planning.Keywords
FDI, Trend Analysis, Stationarity, Heteroskedasticity.Full Text
References
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- Suneel, K., Shekhar, & Kamlesh, A. (2018). The Economic Contribution of Tourism Industry in India: An Appraisal. International Journal of Applied Hospitality and Tourism Research, 1-12.