INTRODUCTION:

Today, tourism is a most important source of revenue for many countries, and affects the economy of both the source and host countries, in some cases being of vital significance.

Internet has brought revolt in every globe of life. It has given trade (whether big or small) an equal occasion to enlarge by attainment out to a wide range of clients throughout the world. By increasing this world wide exposure, it has raised the competitiveness of the firms who have become more creative and competitive in providing new and better services to the customers. Be it a manufacturing sector or service sector; Information and Communication Technology (ICT) is getting key component of every industry and Tourism Industry is not an exception to it. E-Tourism describes a new way of doing business.

It communicates earlier and access global markets with negligible costs for new businesses. Buhalis suggests that e-tourism reflects the digitization of all processes and value chains in the tourism, travel, hospitality and catering industries.

NEED FOR THE STUDY:

The online booking phenomenon is a relatively new subject area that has been the focus of research investigations in marketing field. However, there is little descriptive research in the travel and tourism field, which has focused on online booking.

The purpose of this research is to examine a single online travel community in order to conduct an in depth analysis of the influence of factors of online booking on travel decisions. The results of this study can help tourism marketers among travel consumers. Also it creates a new venue to promote their products.

SCOPE OF THE STUDY:

The study is very useful for the e-tourism companies to understand the factors responsible for creating trust in travel websites. It is very helpful in designing the strategies for retaining the existing customers with the company. It is useful for the researchers to give them insight into the concept of consumer trust while booking online. Since, it is an emerging concept in India, it gives a movement to the building of a more advanced and convenient mode of booking.

OBJECTIVES OF THE STUDY:

· To examine the gender difference towards the factors of online booking.

· To examine the internet access, frequent travel, travel websites group difference towards the factor of online booking.

REVIEW OF LITERATURE OF ONLINE BOOKING:

Mpinganjira (2014) he talks about the act of purchase is the main target for a profit driven by the organization. All marketing and business plans have as their main goal to increase the purchases of products or services and as a result to increase the profits of a company.

Green and Lomanno (2012) says about the price transparency of online channels that adds more pressure to travellers online booking rates and thereby forces travel agents to keep rate parity in all channels and keeps online rates as low as possible or provide “low price guarantees” on travel websites.

Jiang (2003) and Punj (2012) Online customers tend to utilize the internet as a major information search tool to help them make a quality decision and generate different search strategies, such as using third-party websites or search engines as facilitated tools to match consumers’ needs and reduce search efforts.

Wen (2012) Dash and Saji (2008) Kim and Stoel (2004) purchase intention and recommend to purchase is an outcome of a number of factors. The trust of the customers to the web page is a major factor that can affect the customer's willingness to buy a product or service and several studies have shown this positive relationship.

Peterson (2011) describes about understanding consumers’ perceptions regarding product value and how consumers evaluate discounted products may prove valuable information to online travel service providers. However, most service providers still focus on how to slash prices as their main promotional marketing strategies instead of understanding consumer deal-searching behavior.

Dunn, Baloglu, Brewer and Qu (2009) researchers have suggested that travel service providers should take advantage of using the internet to build effective customer relationships and increase their customer loyalty.

Tejada and Linan (2009) in their study, explored the main worldwide factor that have an crash on the services of order and deliver of the tourism industry. They enlisted Internet and decreased cost of air travel in affecting the supply side of this industry. And on the other hand, increasing income, changing lifestyles and development of newer tourist sites have been evaluated as factors leading to higher demand.

RESEARCH METHODOLOGY:

Sampling means selecting a sample from a population. There are five steps in sampling design which are defining the population, determine the sampling frame, select sampling techniques, determine the sample size and execute the sampling process. Through these steps, it helps to identify the qualified target respondents to participate in the survey (Kuul, 1984).

In order to address the research aim the participants are selected using a non-probability sampling method. For the purpose of the study, customers of online travel agencies in Coimbatore are selected as population.

Sampling procedure:

The sampling procedure used is convenience sampling. The sampling is selected on the basis of convenience in and around Coimbatore which served as main factor for the selection of the sampling procedures. Hence the sampling method applied is convenient sampling. Convenience sampling is non-probability sampling technique, where subjects are selected because of their c convenience and closeness to the researchers.

TO ANALYSIS THE GENDER DIFFERENCES OF THE RESPONDENTS TOWARDS THE FACTORS OF ONLINE BOOKING:

H_o: Respondents with different gender have same opinion towards the factors based on online booking.

Factor	Gender	N	Mean	Df	Sig. (2-tailed)	Sig	Null hypothesis
Useful	Male	85	4.4706	248	.001	.023**	Rejected **
Useful	Female	165	4.2788	151.957	.001	.023**	Rejected **
Aesthetics	Male	85	15.6353	248	.776	.585	Accepted
Aesthetics	Female	165	15.7636	161.806	.780	.585	Accepted
Ease to use	Male	85	15.5529	248	.920	.448	Accepted
Ease to use	Female	165	15.5091	160.846	.922	.448	Accepted
Intention to purchase	Male	85	19.1647	248	.814	.562	Accepted
Intention to purchase	Female	165	19.3333	223.940	.793	.562	Accepted
Intention to recommend	Male	85	19.5412	248	.830	.840	Accepted
Intention to recommend	Female	165	19.6545	169.511	.830	.840	Accepted

Note: *Significance level is at 5%

From the above table (4.10) it is inferred that there is significant difference in opinion exists among male and female for the factor usefulness. Hence the null hypothesis is rejected. There is no significant difference in opinion exists among male and female for the factors aesthetics, ease to use, intention to purchase and intention to recommend. Hence the null hypothesis is accepted.

TO FIND THE MARITAL STATUS OF RESPONDENTS TOWARDS THE FACTORS OF ONLINE BOOKING

H_o: Respondents with different marital status have same opinion towards the factors based on online booking.

TABLE 4.11:

Factor	Gender	N	Mean	Df	Sig. (2-tailed)	Sig	Null hypothesis
Useful	Married	96	5.3958	248	.849	.998	Accepted
Useful	Unmarried	154	5.3117	204.602	.848	.998	Accepted
Aesthetics	Married	96	5.8854	248	.541	.771	Accepted
Aesthetics	Unmarried	154	5.6169	202.336	.541	.771	Accepted
Ease to use	Married	96	5.6875	248	.534	.930	Accepted
Ease to use	Unmarried	154	5.4221	194.534	.539	.930	Accepted
Intention to purchase	Married	96	9.6250	248	.416	.047**	Rejected**
Intention to purchase	Unmarried	154	9.0584	143.085	.462	.047**	Rejected**
Intention to recommend	Married	96	9.9375	248	.309	.120	Accepted
Intention to recommend	Unmarried	154	9.4156	213.236	.300	.120	Accepted

Note: *Significance level is at 5%

From the above table (4.11) it is inferred that there is significance difference exists among married and unmarried for the factor intention to purchase. Hence the null hypothesis is rejected. But for the factors like usefulness, aesthetics ease to use and intention to recommend it has no significance. Hence the null hypothesis is accepted.

TO EXAMINE THE DIFFERENT AGE GROUP OF THE RESPONDENTS TOWARDS THE FACTORS OF ONLINE BOOKING

H_o: Different age group of respondents has the same opinion towards the online booking.

TABLE 4.12:

		Df	Mean Square	F	Sig.	Null hypothesis
Usefulness	Between Groups	5	6.935	.4426	.043**	Rejected **
	Within Groups	244	11.548
	Total	249
Aesthetics/visual appeal	Between Groups	5	22.469	2.016	.077	Accepted
	Within Groups	244	11.148
	Total	249
Ease to use	Between Groups	5	15.087	1.416	.219	Accepted
	Within Groups	244	10.651
	Total	249
Intention to purchase	Between Groups	5	3.089	.106	.991	Accepted
	Within Groups	244	29.084
	Total	249
Intention to recommend	Between Groups	5	18.164	1.177	.321	Accepted
	Within Groups	244	15.436
	Total	249

From the above table (4.12) it is inferred that there is significant difference exists among different groups for the factor usefulness. Hence the null hypothesis is rejected. But for the factors like aesthetics, ease to use, intention to purchase and intention to recommend it has no significance. Hence the null hypothesis is accepted.

TO EXAMINE THE DIFFERENCE OF FREQUENT TRAVEL OF THE RESPONDENTS TOWARDS THE FACTORS OF ONLINE BOOKING

H_o: Different frequent travel of respondents has the same opinion towards the online booking.

		df	Mean Square	F	Sig.	Null hypothesis
Usefulness	Between Groups	3	45.605	4.131	.007**	Rejected**
	Within Groups	246	11.039
	Total	249
Aesthetics/visual appeal	Between Groups	3	8.606	.754	.521	Accepted
	Within Groups	246	11.409
	Total	249
Ease to use	Between Groups	3	8.741	.812	.488	Accepted
	Within Groups	246	10.765
	Total	249
Intention to purchase	Between Groups	3	14.959	.521	.668	Accepted
	Within Groups	246	28.728
	Total	249
Intention to recommend	Between Groups	3	24.014	1.561	.200	Accepted
	Within Groups	246	15.387
	Total	249

Note: *Significance level is at 5%

From the above table (4.17) it is inferred that there is significance difference exists among different groups for the factor usefulness. Hence the null hypothesis is rejected. But for the factors like aesthetics, ease to use, intention to purchase and intention to recommend it has no significance. Hence the null hypothesis is accepted.

FINDINGS, SUGGESTION AND CONCLUSION:

FINDINGS:

The socio demographic profile of respondents shows that 66.4 percent of respondents are female, and the majority of 44.8 percent of the age of the respondents was 25 to 35 years,46.8 percent of the respondents have completed post graduation 61.6 percent of the respondents are unmarried,34.4 percent of the respondents earn an income above 40,000 per month, 37.2 percent of the respondents are private as their occupation,38.0 percent of respondents are accessing internet 4-6 years, 31.2 percent of the respondents often travel 6 months once and 42.8 percent of respondents mostly use makemytrip.com travel websites for online booking.

By the help of Z-test, shows the male and female respondents have different opinion towards the factor usefulness, but they have same opinion for aesthetics, ease to use, intention to purchase and intention to recommend.

By the help of Z-test, shows the married and unmarried respondents have different opinion towards the factor of intention to purchase, but they have same opinion for usefulness, aesthetics, ease to use and intention to recommend.

By using ANOVA, it is observed that the null hypothesis (0.05) is rejected for the factor usefulness. But for the factors like aesthetics, ease to use, intention to purchase and intention to recommend the different age group has the same opinion.

By applying ANOVA, it is observed that different frequent travel group have the difference opinion for the factor of usefulness. But the respondents have the same opinion for the factors like aesthetics, ease to use and intention to purchase and intention to recommend.

SUGGESTION:

· The different types of customers require different type of information and have different target of websites. They generally make a booking decision based on the travel website presented on the webpage.

· Thus, the presentation of website choices on the webpage should be designed by considering the multidimensional preference of customers and the position effect of the choices on the website. Travel websites failing to meet the minimum acceptable review score should be positioned lower in the list or even cut out from the available choice to help customers search faster. Also, the sale conditions (e.g. cancellation policy, special deal) have important effect that inspire or stop the booking decision.

CONCLUSION:

In current scenario, there is growth of online booking is increasing in all the regions of world. Hence, the study offers a beginning point especially to understand the customer’s attitude and behavior in travel industry.

The online travel booking behavior is dependent on an individual’s traits and characteristics. In online booking, customers may feel skeptical about the website’s reliability and authenticity. In increasing countries, the unavailability of legal communications support for e-commerce websites exacerbates the lack of trust. Customers may be uninformed about the technicalities and procedures of transaction and the outcomes of online booking.

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WEBSITES:

1. https://en.wikipedia.org/wiki/Internet_booking_engine

2. https://en.wikipedia.org/wiki/Yatra_(company)

3. https://en.wikipedia.org/wiki/MakeMyTrip

4. https://en.wikipedia.org/wiki/Ibibo

5. https://en.wikipedia.org/wiki/TripAdvisor

6. http://www.travelucd.com/research/pdf/hotel_booking_process

7. https://en.wikipedia.org/wiki/Booking.com

8. https://cashbackoffer.in/best-online-travel-sites-india/

9. https://en.wikipedia.org/wiki/Travel_agency

Received on 25.03.2020 Modified on 17.04.2020

Asian Journal of Management. 2020;11(3):304-308.

DOI: 10.5958/2321-5763.2020.00047.5