International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 Analysis of Online and Offline Travel AgentsAo Contribution to Room Occupancy Ni Kadek Masita Hardiani1.
Budi Susanto2.
I Ketut Astawa3.
Nyoman Mastiani Nadra4.
Made Sudiarta5.
Ni Made Sudarmini6 1,2,3,4,5,6The Wing Hotel.
Indonesia email: kd.
masita@gmail.
com, 2susanto@pnb.
id, 3ketutastawa@pnb.
4mastianinadra@pnb.
id, 5sudiarta@pnb.
id, 6madesudarmini@pnb.
Received on 05 January 2022
Revised on 06 March 2022
Accepted on 11 April 2022
ABSTRACT
Purpose: The aims of this study are to know the contribution of Online Travel Agents and Offline Travel Agents to room occupancy at a hotel in Denpasar.
Bali.
Indonesia, and to find out the comparison of contribution from Online Travel Agents and Offline Travel Agents to room occupancy at the hotel.
Research methods: Data collection methods used are observation, interview, and study documentation.
The analysis technique used is quantitative analysis, qualitative analysis, and descriptive statistics from secondary data.
The stages of the data analysis technique start from the classical assumption test, multiple regression analysis, hypothesis testing using SPSS 21 program, and descriptive statistical techniques.
Results and discussion: The results of this study indicate that the t count value of the online travel agent contribution is greater than the t table .
280> 1.
Meanwhile, the t count value of the contribution of the offline travel agent also has a greater value than the t table .
,280> 1,.
Based on the data obtained, the contribution of the Online Travel Agent and Offline Travel agents from 2017 to 2019 has fluctuated every year.
Implication: The contribution to the development of the Online Travel Agents has increased every year, while the contribution of Offline Travel Agents has decreased in 2019.
However, the largest contribution still comes from the Offline Travel Agent.
In an effort to increase room occupancy, the hotel should further expand the collaboration networking with Online Travel Agents to increase the contribution that can be generated by Online Travel Agents.
Keywords: online, offline, travel agent, room occupancy.
INTRODUCTION
The rapid development of information and technology at this time makes many things accessed easily and quickly.
Because of the rapid development of information and technology, it also makes more and more variations of the reservation process.
Reservation is a guest's request to get a room according to his Reservations were made in advance through several sources with various reservation methods aimed at ensuring that later the guest will get a room when they will stay (Aprillia et al.
, 2.
Reservations can be categorized into two types, namely online reservations and offline reservations (Wachyuni et al.
International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 However, currently there are many ways to make room reservations which will have a direct impact on the contribution generated by room reservation sources which will later affect the room occupancy rate.
Room occupancy rate or better known as hotel room occupancy is a condition that how far the number of rooms sold, when compared to the number of rooms that can be sold (Hendriyati.
The ratio of occupancy can be used as a measure of the success of the hotel in selling its main product, namely rooms (Sugiarto, 2.
Figure 1.
Contribution of room reservation sources [Source: Quest San Hotel Denpasar, 2.
At this time, there are many hotels that have a variety of ways in the room reservations process.
One hotel that applies variations in the room reservations process is Quest San Hotel Denpasar.
Quest San Hotel Denpasar is a 3-star that under Archipelago International hotel management and located on Jalan Mahendradatta.
Quest San Hotel Denpasar has several sources of room reservations such as: email, hotel sales, hotel websites, live chat, online travel agents, offline travel agents, other sources, phone calls, faxes, direct guests, and whatsapp business.
Each reservation sources makes a different contribution to International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 room occupancy.
The contribution of room reservation sources at Quest San Hotel Denpasar in 2017-2019 can be seen in Figure 1.
Based on figure 1, shows that the source of room reservations at Quest San Hotel Denpasar fluctuates every year, and two sources of reservations that seem dominant in contributing are online travel agents and offline travel agents.
online travel agent is a travel agent that carries out promotional activities and online sales through a website(Istikhomah & Darma, 2.
Reservations through online travel agents are carried out by many tourists because the reservation process does not require much time and can be done anywhere (Sagitarini, 2.
While offline travel agents are the opposite of online travel agents.
Offline travel agents are travel agents that their sales are not made through an online system but through brochures or banners (Yoety, 2.
However over time, offline travel agents also use promotional media through websites, but the difference with online travel agents are in their sales.
Where offline travel agents sell tour packages that include lodging, while online travel agents only sell accommodation (Sambodo, 2.
Based on the background described above, there are several problem that will be discussed in this research such as: how is the contribution of online travel agents to the room occupancy at Quest San Hotel Denpasar, how to contribute offline travel agents to the occupancy at Quest San Hotel Denpasar and how is the contribution of offline travel agents to the occupancy at Quest San Hotel Denpasar and and how are comparition between online travel agent and offline travel agent.
The objectives to be achieved from this research, are: to determine the contribution of online travel agents to room occupancy at Quest San Hotel Denpasar, to determine the contribution of offline travel agents to room occupancy at Quest San Hotel Denpasar and to find out the comparison between online travel agents and offline travel agents.
and how are comparition between online travel agent and offline travel agent.
The previous studies used as references in this study are: .
Opening the online marketplace: An examination of hotel pricing and travel agency on-line distribution of rooms by Liuyi Ling.
Xiaolong Guo and Chenchen Yang, in 2014.
This journal uses numerical studies and sensitivity analysis of parameter models in this study.
The results of this study indicate that the optimal unit commission increases with the number of hotel rooms or the number of hotels cooperating with OTA and decreases with the number of t-tourists or the number of potential OTA customers.
The similarities between the research above and this research are that they both discuss the Online Travel Agent (OTA) in increasing room While the difference are in the data analysis technique, time and location of the research.
Hotel booking through online travel agency: Optimal Stackelberg strategies under customer-centric payment service by Guang Xin.
Gao and Jian Wu Bib in 2021.
This journal uses the Stackelberg game model in this research.
The results of this study indicate that the optimal decision of the hotel and customer are related to the length of stay of the customer.
beside that, the interaction between hotel operations and customer payment decisions regarding differences in customer length of stay is also analyzed.
The similarities between the research above and this study are that they both discuss room reservations through Online Travel Agents (OTA).
While the difference lies in the International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 data analysis technique, time and location of the research.
Online Distribution Channels (ODS) on Hotel Revenue by Suci Sandi Wachyuni et al in 2018.
The research method used is a quantitative method.
The results of this study indicate that OTA is very effective in increasing sales at Hotel Dreamtel Jakarta, which is the income from OTA for 3 years compared to guests has a significant difference.
The similarities between the research above and this study are that they both discuss room reservations through Online Travel Agents (OTA).
While the difference are in the data analysis technique, the time and location of the The Effect of Online Travel Agents on Room Bookings at the Mutiara Malioboro Hotel Yogyakarta by Lutfi Hendriyanti in 2019.
This study uses a qualitative descriptive method.
The results of this study indicate that the sale of rooms through OTA is proven to increase room occupancy so the participation and support of the hotel from both employees and management must be The similarities between the research above and this research are they both discuss about the Online Travel Agent (OTA).
While the difference lies in the data analysis technique, time and location of the research.
Online Travel Agent Commission to Improve Room Occupancy at The-Ritz-Carlton Bali by Made Ayu Krismasari in 2020.
The research methods used are quantitative and descriptive qualitative methods to examine information data through words.
The results of this study indicate that the commission for Online Travel Agents (OTA) contributes to room occupancy and has a positive and partially significant effect.
The similarities between the research above and this study are that they both discuss the Online Travel Agent (OTA) in increasing room occupancy and using quantitative methods.
While the difference lies in the type of regression used, the time and location of the study.
The Contribution of Offline and Online Travel Agents to Room Occupancy at Four Points By Sheraton Bali Seminyak Hotel by Putu Septiawan in 2018.
The research method used is descriptive statistics which is the processing uses Microsoft Excel.
The results of this study indicate that the contribution of offline and online travel agents is dominated by Expedia with a total contribution is 61.
78% and Coorendon with a total contribution is 37.
71% in The similarities between the research above and this study are that they both use descriptive statistical methods and discuss online and offline travel agents in improving rooms, while the difference lies in the time and location of the RESEARCH METHODS This research was conducted at Quest Hotel San Denpasar, especially in Front Office Department.
This hotel is located at Mahendradatta Street No.
Denpasar.
Bali.
Indonesia.
The object of research were the contribution online travel agents and offline travel agents to room occupancy at Quest San Hotel Denpasar.
The data collection method used is observation, interviews and documentation studies.
Observation is data collection that used to collect research data by doing observation and sensing as the main tool (Sugiyono, 2.
, interviews are used as a data collection technique if you want to conduct a preliminary study to find problems that must be reserch.
Interviews are also conducted if researchers want to know the things from respondents in more depth and the number of respondents is small (Sugiyono, 2.
and documentation studies are a International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 type of data collection which are researchers obtain information from various written sources or from documents that already exist from the informant.
Which is the document can be in the form of cultural heritage (Aan.
Komariah dan DjamaAoan.
The types of data used in this research are quantitative data and qualitative data.
Which are quantitative data is data in the form of numbers that can be calculated (Sugiyono, 2.
While data Qualitative data is data in the form of words, sentences, schemes, and pictures (Sugiyono, 2.
In this research, there are two sources of data used, namely primary data and secondary data.
Primary data is a data source that directly provides data to data collectors (Sugiyono, 2.
While secondary data is data that has been compiled in the form of documents obtained from the company, and the data secondary can be in the form of facts, tables, figures and others (Sugiyono, 2.
Analysis of the data in this research using quantitative analysis.
Quantitative analysis is a process to gain knowledge, which uses data in the form of numbers as a tool to analyze information about what you want to know (Nasrudin, 2.
Quantitative analysis was performed by using multiple regression with secondary data and processing data is using application of IBM SPSS 21.
Besides using quantitative analysis, this study also use qualitative analysis to support the results of quantitative analysis.
This qualitative analysis is carried out by concluding and providing an explanation regarding the results of quantitative analysis.
The last method used in this research is descriptive statistics.
Descriptive statistics is a method of data processing that carried out with the aim to describing or providing an overview regerding the research object through sample or population data (Sujarweni.
RESULTS AND DISCUSSION There are several Online Travel Agents that dominantly contribute to the room occupancy at Quest San Hotel Denpasar.
Online Travel Agents that are dominantly contributing are: Traveloka.
Booking.
Agoda.
Expedia.
Tiket.
The online travel agents that have dominant contributed in 2017-2019 can be seen in table 1.
Table 1.
The online travel agents that dominant contributed in 2017-2019 Online Travel Agent (Nigh.
Years (Nigh.
(Nigh.
Traveloka Booking.
Agoda Expedia Tiket.
Based on Table 1, shows that the contribution of the five online travel agents fluctuates every year.
Which are.
Agoda is the most online travel agent that contributed in 2017.
Traveloka is the most contributed in 2018 and Tiket.
com is the most contributed in 2019.
International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 While for offline travel agents, there are also several Offline Travel Agents who dominantly contribute to the room occupancy at Quest San Hotel Denpasar.
Offline Travel Agents that are dominantly contributing are: Bali Oke Wisata T&T.
Eka Jaya Bali Wisata.
Jetwings Bali Tour & Travel.
Global Holiday Partners (Statistic.
Aji Tour & Travel.
The offline travel that have dominant contributed in 2017-2019 can be seen in Table 2.
Table 2.
The offline travel agents that dominantly contribute in 2017-2019 Offline Travel Agent Tahun (Nigh.
(Nigh.
(Nigh.
Bali Oke Wisata T & T Eka Jaya Bali Wisata Jetwings Bali Tour & Travel Mitra Global Holiday (Statisti.
Aji Tour &Travel Based on Table 2, shows that the contribution of the five offline travel agents fluctuates every year.
Which are.
Jetwings Bali Tour & Travel is offline travel agent that contributed the most in 2017.
Mitra Global Holiday (Statistic.
contributed the most in 2018 and Eka Jaya Bali Wisata contributed the most in Overall, every contribution that made by online travel agents and offline travel agents who dominant and less dominant will have a direct impact on the room occupancy at Quest San Hotel Denpasar.
Therefore in this research, the data used are the overall contribution of online travel agents and offline travel agents on the room occupancy rate at Quest San Hotel Denpasar.
To find out the contribution of online travel agents and offline travel agents to the room occupancy rate at Quest San Hotel Denpasar, so several tests will be carried out first.
Considering that this research uses secondary data for the processing data, then the first test that carried out is the classical assumption test, followed by multiple linear regression analysis, and hypothesis testing .
to answer the problem of formulation.
The results of the classical assumption test that have been carried out are:
Normality Test Based on the normality test that conducted with the One Sample Kolmogorov Smirnov Test method, shows that the value of Sig.
Asymp Significance .
-taile.
498, which is greater than the significance value 05 .
498 > 0.
From these results, it mean that the data used in this research were normally distributed.
Linearity Test Based on the linearity test on the online travel agent variable, it shows that the Sig Deviation from Linearity value is 0.
834 which is greater than 0.
834 > 0.
From these results, it mean there is a significant linear International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 relationship between the Online Travel Agent variable (X.
and the Room Occupancy variable (Y).
While, for the linearity test on the offline travel agent variable, it shows that the Sig Deviation from Linearity value is 0.
548 greater than 0.
From these results, it mean there is a significant linear relationship between the Offline Travel Agent variable (X.
and the Room Occupancy variable (Y).
Heterescedasticity Test Based on the heteroscedasticity test that conducted with glejser test, shows that the significance value (Sig.
) for the Online Travel Agent variable (X.
is 067 and the significance value (Sig.
) for the Offline Travel Agent variable (X.
Because the significance value of the two independent variables is greater than 0.
05, it mean there is no symptom of heteroscedasticity in this research.
Multicollinearity Test In this research, the multicollinearity test was carried out by looking at the VIF (Variance Inflation Factor.
Based on the results of data processing, shows that the VIF value for the Online Travel Agent variable (X.
and the Offline Travel Agent variable (X.
This result is smaller than 10 .
018 < .
While the tolerance value for the Online Travel Agent (X.
variable and the Offline Travel Agent (X.
variable is 0.
where this value is greater than 0.
982 > 0.
With the value of VIF and tolerance above, it mean there are no symptoms of multicollinearity.
Autocorrelation Test Based on the results of data processing, shows the Durbin Watson value is 1,599.
Then, this value will be compared with the value of the Durbin Watson table with c = 0.
As for the value on the durbin watson table is 1.
The condition that there is no autocorrelation is done by comparing:
- Dw < 4 Ae Du = 1.
599 < 4 Ae 1.
= 1.
599 < 2.
- Dw value > Du = 1.
599 > 1.
Based on the calculations above, it can be concluded that there is no autocorrelation problem in this research.
The results of multiple linear regression analysis can be seen in table 3.
Table 3.
Multiple linear regression analysis Coefficientsa Unstandardized CoStandardefficients ized Coefficients Std.
Error Beta (Constan.
X1_Online TA X2_Offline TA Dependent Variable: Y_Tingkat Hunian Kamar Model Sig.
International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 Based on the results of data processing above, the constant value is 61,964, the Online Travel Agent regression coefficient is 0.
009 and the Offline Travel Agent regression coefficient is 0.
The level of confidence that used in multiple linear regression is 95% or with an error rate is 5% .
From these results, the regression equation can be formulated as follows:
= c b1X1 b2X2 e = 61.
009 X1 0.
005 X2
The explanation of the regression equation above, are:
The constant .
is 61,964 states that, if there are no Online Travel Agent (X.
and Offline Travel Agent (X.
variables, the Room Occupancy (Y) is 61,964.
The regression coefficient value of the online travel agent variable (X.
is 009, which means that if the online travel agent increases by 1%, it will increase the room occupancy at 0.
The regression coefficient value for the offline travel agent variable (X.
is 005, which means that if the offline travel agent increases by 1%, the room occupancy will increase at 0.
To find out the contribution of online travel agents to room occupancy, then t-test will be carried out.
The results of the t-test that carried out on the online travel agent variable can be seen in the table 4.
Table 4.
T-test Model (Constan.
X1_Online Travel Agent X2_Offline Travel Agent Coefficientsa Unstandardized Coefficients Std.
Error Standardized Coefficients Beta Sig.
Dependent Variable: Y_Tingkat Hunian Kamar To find the t-table value, the formula used is:
= n-k
= 36-3 = 33
t table = 1.
Based on table 4, show that the t-value of online travel agents is 4,280 > t-table 1,692 .
,280 > 1,.
Then.
Ha is accepted and it mean that there is a positive and significant influence from the online travel agent contribution to the room Same as contribution of online travel agent, to find out the International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 contribution of offline travel agents to room occupancy, then t-test will be carried The results of the t-test that carried out on the online travel agent variable can be seen in Table 4.
To find the t-table value, the formula used is:
= n-k
= 36-3 = 33
t table = 1,692 Based on table 4, the t-count value for the offline travel agent variable is 4.
t-table 1.
431> 1.
Then.
Ha is accepted and this mean that there is a positive and significant influence on the contribution of Offline Travel Agent (OTA) to the room occupancy.
F Test (Simultaneous Tes.
This test is carried out with the aim to knowing are the independent variables together .
can affect the dependent variable or not.
The results of the F-test can be seen in the table 5.
Table 5.
F-test Model ANOVAa Sum of Mean Squares Square Regression Residual Total Dependent Variable: Y_Tingkat Hunian Kamar Predictors: (Constan.
X2_Offline Travel Agent.
X1_Online Travel Agent Sig.
To find the value of Degree of Freedom with significant level of = 5%, the formula used are:
Df numerator = k-1
= 3-1
Df Denominator = n-k
= 36-3
= 33
Then the value of F table = 3.
Based on Table 5, the calculated F value is 21,920 > F table 3.
,920 > 3.
Ha is accepted and it mean that there is a simultaneous positive and significant influence between online travel agents (OTA) and offline travel agents to the room occupancy.
The coefficient of determination is carried out to know how big the contribution of independent variable that influence dependent variable.
The coefficient of determination also has another meaning that is the magnitude of the value/ability of all independent variables in explaining the varians of the dependent variable.
The results coefficient of determination can be seen in the table 6 .
International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 Table 6.
Coefficient of determination test Model Summaryb Model R Square Adjusted R Square Std.
Error of the Estimate Predictors: (Constan.
X2_Offline Travel Agent.
X1_Online Travel Agent Dependent Variable: Y_Tingkat Hunian Kamar To find the value coefficient of determination, the formula used is:
KD = R2 x 100% = 0.
571 x 100% = 57.
The formula given above shows that the value coefficient of determination This means that online travel agents and offline travel agents can explain the room occupancy rate of 57.
1% and the rest is influenced by the outside variable model.
To find out the results of the comparison between contribution of online travel agents and offline travel agents to room occupancy then the average of online travel agent contribution and offline travel agent contribution should be find out first.
The average contribution of online travel agents and offline travel agents in 2017-2019 can be seen in table 7 .
Table 7.
Average contribution of online travel agents and offline travel agents in OTA
OFFTA
OCC
After founding the average contribution of online travel agents and offline travel agentsto room occupancy at Quest San Hotel Denpasar, then the development average will be graphed.
The figure of the development contribution between online travel agents and offline travel agents to room occupancy rates at Quest San Hotel Denpasar can be seen in figure 2 .
International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95
e-ISSN 2828-2590
p-ISSN 2828-5093
OTA
OFFTA
OCC
Figure 2.
Development contribution between online travel agents and offline travel agents [Source: Data Processed, 2.
Based on Figure 2, it shows that the average contribution of online travel agents and offline travel agents to the room occupancy at Quest San Hotel Denpasar for the last 3 years fluctuated every year.
However, if seen at the average, the contribution of Online Travel Agents has increased every year, while the average contribution of Offline Travel Agents has decreased in 2019.
Beside that.
Figure 2 shows that the average contribution of Online Travel Agents to the room occupancy rate at Quest San Hotel Denpasar in 2017 was 247 rooms or Then in 2018 it increased to 494 room nights or 11.
In 2019, it increased to 1003 room nights or 21.
While the average contribution of Offline Travel Agents, that obtained in 2017 was 2,484 room nights or 61.
Then in 2018 it increased to 3,268 room nights or 75.
Finally, in 2019 the average contribution decreased to 3,257 room nights or 69.
The contribution of Online Travel Agents has increased every year.
While the contribution of Offline Travel Agents, it had decreased in 2019.
If compared between the contribution of Online Travel Agents and the contribution of Offline Travel Agents to the room occupancy at Quest San Hotel Denpasar, so the Offline Travel Agent is greater than the Online Travel Agent.
CONCLUSION
Based on the results of data analysis and discussion that has been written in the previous chapter,the conclusion are: The contribution of Online Travel International Journal of Travel.
Hospitality and Events Volume 1 Number 2 Year 2022 Pages 83-95 e-ISSN 2828-2590 p-ISSN 2828-5093 Agents in the 2017-2019 has a positive and significant influence to the room occupancy at Quest San Hotel Denpasar.
Beside contribution of the Online Travel Agent, the contribution of the Offline Travel Agent is also has a positive and significant influence to the room occupancy at Quest San Hotel Denpasar.
It can be seen in the t-test results of all independent variables, where the value obtained is greater than the t-table value.
Based on the data processed, that can be seen the average contribution of online travel agents and offline travel agents fluctuates every year which is the development average of Online Travel Agents contribution has increased, while the average contribution of Offline Travel Agents had once decreased.
However while compared, the contribution of Offline Travel Agent is greater and faster increase than the contribution of Online Travel Agent Suggestions that can be given for Quest San Hotel Denpasar related to this research are as follows: Expand the network of cooperation with Online Travel Agents in order to increase the contribution that can be made by Online Travel Agents to room occupancy at Quest San Hotel Denpasar.
Give rewards to Online Travel Agents and Offline Travel Agents who have dominantly contributed to the room occupancy at Quest San Hotel Denpasar.
This reward is given as a form of appreciation and gratefull to Online Travel Agents and Offline Travel Agents.
Last Sugesstion is continue to maintain the well-established cooperation with Online Travel Agents (OTA) and Offline Travel Agents.
ACKNOWLEDGEMENT
The authors give great thanks to this journal (International Journal of Travel.
Hospitality, and Events/IJOTHE) for publishing this result of research.
REFERENCES