Monthly family income has a various distribution: 3 % ( 12 ) of respondents has income less than 1000 monthly, 12 % ( 48 ) has income $ 1000- $ 0200, 36 % ( 144 ) has income $ 2000- $ 3000, 35 % ( 140 ) has income $ 3000- $ 6000, and 15 % ( 56 ) has income above $ 6000 per month. ( Figure 2 )
Education degree of respondents showed undermentioned: approximately 8 % ( 32 ) of the respondents had below high school instruction ; 17.0 % ( 68 ) of respondents received a degree grammar school or high school instruction, 25 % ( 100 ) of respondents held some college instruction, 37 % ( 148 ) of respondents held a unmarried man grade and 13 % ( 52 ) of respondents held graduate students degree ( Figure3 ) .
Consequences specified that 9 % ( 30 ) of the respondents is retired, 19 % ( 76 ) of respondents worked in direction / executive places, professionals comprised of 23 % ( 92 ) of respondents, 16 % ( 64 ) of respondents worked in authorities construction, 13 % ( 52 ) of respondents is freelance, 18 % ( 72 ) of respondents worked in clerical or gross revenues workers and 2 % ( 8 ) were unemployed ( Figure 4 ) .
4.1.2 INTERNET Use IN LIFE
In collected study ( Table 2 ) , in day-to-day life cyberspace was used by 85 % ( 340 ) of respondents used, and 15 % ( 60 ) had no on-line experience or utilizing really seldom ( Figure5 ) .
Figure 5: On-line experience of respondents
Sing respondents of in the Internet group, 15 % ( 51 ) of respondents use Internet 1-2 times per hebdomad, 25 % ( 85 ) utilizing internet 3-4 times per hebdomad, 45 % ( 153 ) utilizing it more than 5 times hebdomadal ( Figure 6 ) .
Figure 6: Internet utilizing of respondents per hebdomad
Besides among to respondents with on-line experience, 3 % ( 10 ) of respondents utilizing Internet less than 6 months, 24 % ( 82 ) have utilizing Internet around 6 months and 1 twelvemonth, 21 % ( 71 ) of respondents have used Internet around 1 and 2 old ages and 52 % ( 106 ) of respondents have more than 2 old ages of experience of utilizing the Internet ( Figure7 ) .
Figure 7: Internet use history
By consequences of study was identified intent of utilizing Internet, so it shows that 20 % ( 68 ) of all respondents utilizing cyberspace in their work, 8 % ( 27 ) of respondents utilizing cyberspace to online instruction. Besides 10 % ( 34 ) of respondents utilizing cyberspace to online shopping, 26 % ( 89 ) , 20 % ( 68 ) , and 16 % ( 54 ) of all respondents the chief intent of utilizing cyberspace is email communicating, amusement and personal information ( Figure 8 ) .
4.1.3 BEHAVIORAL CHARACTERISTICS REGARDING ONLINE RESERVATION EXPERIENCE
Two hundred and 60s of all respondents ( 75 % ) ne’er had experience with on-line reserve. 35 % ( 140 ) of respondents purchased hotel services and merchandises via on-line reserve. 3 % ( 4 ) of respondents with on-line reserve did non do on-line reserves in last 12 months. Forty-two ( 30 % ) of respondents did online reserve merely 1 clip. Seventy ( 50 % ) of respondents made on-line reserve 2 to 3 times in last 12 months. Seventeen ( 12 % ) of respondents made on-line reserve 4 to 5 times. Seven of all respondents ( 5 % ) made on-line reserve more than 5 times. Sing respondents that did non hold any on-line reserve experience, 25 % ( 65 ) telephone reserve made straight with hotels, 40 % ( 104 ) arranged their hotel service and merchandise via travel agents and 35 % ( 91 ) by corporate aid ( Table 3 ) .
4.2 FACTOR ANALYSIS
Identifying of important implicit in dimension that have influence to Kuala Lumpur hotel pursuits ‘ online reserve purpose were conducted by explorative factor analysis utilizing chief constituents with varimax rotary motion. Consequences of factor analysis demonstrated in Table 4.
Table 4: Factor Analysis Results with Varimax Rotation of Underlying Dimensions Influencing Kuala Lumpur Hotel Customers ‘ Online Reservation Intentions
Five factors in varimax – rotated factor matrix with Eigen values more than 1 was eventually removed and the illustrated 63,5 % of overall discrepancy. Five factors that were taking were called: 1. information demands, 2. service public presentation and repute of hotels, 3. convenience and security, 4. technological disposition and 5. monetary value benefits. Reasonably higher burdens in appropriate factor with clean construction were created. Most of the variables inserted to a great extent to other factors and did n’t infix to a great extent in other factors. It was intending that were minimum coincide between these factors and besides intending that all factors were independently. In order to prove factors analysis were appropriate: Bartlett Test of Sphericity and Kaiser-Meyer-Olkin ( KMO ) conducted. Consequences showed that significance of correlativity matrix is 0,0 with Bartlett Test of Sphericity value of 2179,612. It was bespeaking that about multivariate normal and acceptable for factor analysis because informations do non make an identify matrix. Kaiser-Meyer-Olkin ( KMO ) was meritable because quantify of trying adequateness was 0,81. Variables shared common factors and were reasonably interrelated. In add-on, Cronbach ‘s alpha was calculated to prove internal consistence and dependability of all factors. Result demonstrated that alpha coefficients varied between 0,71 and 0,86 for all factors. Consequences of factor analysis in this research are showed really dependable or reasonably dependable, because the minimal value for accepting is 0,50.
Following is that five factors which underlying Kuala Lumpur hotel consumers ‘ online reserve purpose features:
1. Information demands
Information demands includes six objects and showed 28,36 % of discrepancy and Eigen value of 5,38. It included objects linked to information demands of hotel consumers during their on-line reserve processs, incorporating: practical experience of available comfortss, appropriate merchandise and service information, easiness of comparing hotels, assortment of product/brand pick, lucidity of product/service information and latest merchandise and service information.
2. Service public presentation and repute of hotels
Service public presentation and repute of hotels factors demonstrated 10.18 % of discrepancy and characteristic root of a square matrix is 1,93. This factor included three objects: trade name name, company repute and credibleness and merchandise quality.
3. Convenience & A ; security
Including three objects and value factor analysis showed 9.57 % of discrepancy and Eigen value of 1,82. Three objects are: safe payment process, easiness of puting and call offing orders and 24-hour handiness. Besides three objects were removed: security of sensitive information, easiness of geting information and freedom from fuss.
4. Technological disposition
This factor includes three objects and factor analysis showed 7,81 % of varianceand Eigen value of 1,48. This factor including objects such as: receptiveness to new engineering invention, old satisfaction with e-commerce and acquaintance with e-commerce.
5. Monetary value benefits
Price benefits includes two objects and shoeing 7,31 % of the discrepancy and Eigen value of 1,38. Include objects: reduced purchase-related costs and price reduction monetary value.
4.3 DEMOGRAPHIC PROFILE AND ONLINE RESERVATION INTENTION
In order to demo whether there a important difference between demographic groups and five factors means was executing by ANOVA. While analysing age, gender, educational degree, monthly income and business with five factors, there was no important. As a consequence, first hypothesis can non be acknowledging.
4.4 MULTIPLE REGRESSION ANALYSIS
4.4.1 DETERMINANTS OF THE GUESTS ‘ OVERALL SATISFACTION LEVELS
Two multiple arrested development analyses were conducted in order to analyze whether dependent variables ( Kuala Lumpur hotel invitees ‘ satisfaction with on-line reserve pattern and chance of doing on-line reserve by invitees without on-line reserve pattern ) have important influence to independent variables ( 5 factors ) . Input variables to this analysis were factors from factors analysis. Multiple correlativity coefficient R, coefficient of finding ( ) , and F ratio were considered to foretell unity of arrested development theoretical account. Five purchase purpose factors was justified by adjusted of 0,439 that indicate about 43.9 % of discrepancy in dependent variable. Guests that had positive and comparatively high satisfaction degrees with five factors demonstrated by R of independent variables in dependent variable ( invitees ‘ satisfaction with on-line reserve ) is 0,692. Consequences of the arrested development theoretical account could appeared by opportunity explained by F-ratio and showed a important at 0,0000 and value of 12,103. In this survey arrested development theoretical account that implemented might hold non occurred and it consider as important. t-statistic trial was used to prove that dependant variable ( satisfaction degree with on-line reserve contributed to the five independent variables. t-statistic trial demonstrated that four factors such as: trade name repute of hotels, convenience and security, technological disposition and information demands was important variable in this manner cubic decimeter ( p a‰¤,05 ) . On the other manus, Factor 5 was non important ( p = 0,08 ) . One could find influence of each variable on dependant variable, base to co of each independent variable. A«Information needsA» was the most of import deciding factor in understanding invitees ‘ satisfaction degree, which can be noted from Table 5. It showed highest T value and highest coefficient value 0,42 every bit good. By importance other variables showed following: A«technological inclinationA» ( b = 0,22 ) , A«Service public presentation and reputes of hotelsA» ( b = 0,37 ) and A«convenience and securityA» ( b= 0,15 ) . A«Price benefitsA» variables showed that are non important and coefficient of value is less importance. Satisfaction degree of invitees illustrated that it depends by following four variables.
As a consequence, it can be concluded that of import factors of invitees ‘ satisfaction were this four variables. In other word, guests satisfaction degree additions when there a higher degree of satisfaction to these dimensions.
4.4.2 DETERMINANTS OF THE GUESTS ‘ PROBABLITY OF MAKING ONLINE RESERVATION
In this subdivision demonstrates same analysis as showed in old subdivision, placing whether five factors comprised a important influence on chance of a invitees without on-line reserve pattern will do on-line reserve following clip by utilizing same arrested development theoretical account. Summated dimensions of the five dimensions ensuing from the factor analysis were regressed to invitees ‘ chance of doing on-line reserve. Consequences of invitees ‘ chance of doing on-line reserve in associating to regression analysis demoing in Table 5. Adjusted R2of 0,277 demoing to regression equation of “ chance of doing on-line reserve ” , it is about 27,7 % of fluctuation in “ chance of doing on-line reserve ” . F-ratio of 19.687 was important as consequences of the equation were barely holding occurred. t-statistic trial was utilizing to prove five independent variables contributed to dependent variable “ chance of doing on-line reserve ” . Analysis demonstrated that all five factors such as: technological disposition, information demands, perceptual experience of hotels, convenience and security and monetary value benefits had important variable. One could find influence of each variable on dependant variable, base to co of each independent variable.
Information demands were the most of import deciding factor in understanding invitees ‘ satisfaction degree with highest coefficient value 0,31 and highest t value every bit good, that demoing in Table 5. By importance other variables showed following: service public presentation and reputes of hotels ( b = 0,15 ) , technological disposition ( b =0,17 ) , convenience and security ( B = 0.12 ) and monetary value benefits ( b = 0.21 ) . Satisfaction degree of invitees illustrated that it depends by following all of five variables.
As a consequence, it can be concluded that deciding factors of invitees ‘ satisfaction with on-line reserve information on hotel web sites were this five variables. In other word, when invitees ‘ satisfaction degree additions there were higher degree of satisfaction to these dimensions.