Random Sampling Techniques - Case Study Example

Introduction The study adopted quantitative research methods, it is a situation where the researcher collects data and analyses done on the collected data using mathematical techniques. A sample of 70 respondents were randomly selected with the aid of four research assistants. Part III Analysis and Results Random Sampling techniques was used to come up with 70 respondents, this was done by selecting names from list of travelers at the arrivals location in the Airport. Respondents were selected randomly from these lists so as to come up with the sample. This was done with the help of the Airport assistants working in the Airports at the arrivals and departure zones of King Abdulaziz International Airport, is an Airport located about 20kilometres north of Jeddah. Data was collected from 8:00am to 5:00pm however, more data was reconciled with the already collected data when there is any notable change the next day. In table1below 51.3% was made of female respondents, the male respondents were 47.1% of the total sample of 70people. In reference to age of the respondents the largest portion was made of people who fall between the age of 20-30years-51.4%, this was followed closely by those who fell between the age of 31-40years at a high of 24.3%, the third group which was 41-50years came in at a low of 13.6%. Finally, we have 51years and above who are the least in numbers among the sample members at 5.7%. When respondents were asked about the highest education level that they have achieved, people with no high school diploma made up 4.3% of the total sample, those with high school diploma composed of 8.6% of the sample. The highest portion was made of bachelor’s degree holders who made 37.1% of the sample. Those with 1-3years of college were 31.4% and finally the people with master’s degree or higher education levels than masters were 17.1%. On the question of income bracket for the respondents, the largest portion of the respondents was made of people earning an income level of less than $20,000, this was 4.6%. 21.4% of the sample was the second largest who had an income of $20,000 to $34,999. 14.3% of the sample with an income level of $35,000 to $49,999. The third portion in the group had an income of $50,000 to $74,999, this was 7.1% of the sample. 4.3% made an income level of $75,000 to $99,999. 2.9% made $100,000 to $149,999. The last portion of the group is a small portion of the sample who made the highest income of $150,000 to $199,999 annually. On the issue of occupation most people among the respondents were employed full-time, this is 45.7%, followed closely by the group who said they were involved in other employments activities at 21.4%. 11.4% had a tie such that the people who were employed part-time were 11.4% as well as the portion of people who were unemployed. 10.0% of the respondents were self-employed. Respondent’s profile Table 1 Descriptive statistics In this section the descriptive statistics are presented a study to show the respondents take for every question. (table2) lists mean scores, standard deviations, and sample size of the total of twenty-two questions. A 7-Point Likert scale was used where 1= strongly disagree, 2 = Disagree, 3 = Slightly Disagree, 4 = Neutral, 5 = Slightly Agree, 6 = Agree and finally and 7= strongly agree. Table 2 Descriptive Statistics ITEM N Mean Std. Deviation 1).The selected homestay property’s room is clean. 70 5.3000 1.65372 2). The selected homestay property’s bed is comfortable 70 5.1571 1.69086 3). The temperature control in the selected home-stay property is good. 70 5.2143 1.72696 4).The quality of towels at the selected home-stay property was satisfactory. 70 4.9286 1.67956 5).The quality of mattresses at the selected home-stay property was up to the expected standards 70 5.1714 1.55080 6).A modern television was available at the selected home-stay property. 70 5.0000 1.80177 7).Furniture at the selected homestay property was in excellent condition. 70 5.1857 1.62671 8).The noise level of the building at the selected home-stay property was non-distractive. 70 5.1571 1.64745 9).The prices of additional amenities offered at the selected home-stay property (Wi-Fi, TV, free parking) were provided. 70 4.5000 2.04833 10).The price of the selected home-stay property was reasonable, taking into consideration the quality of services offered. 70 5.0571 1.59606 11).The arrangement for transportation at the selected home-stay property was considering for the money I paid. 69 4.4783 1.81180 12).The reputation of the selected home-stay property was favorable comparing to the price. 70 4.9286 1.71372 13).A comfortable ambiance at the selected home-stay property was worth the money I paid 70 5.2000 1.68196 14).Open fire exits at the selected home-stay property were present, visible, and well-labeled. 70 5.1857 1.62671 15).Building alarms were present and easily reachable at the selected home-stay property. 70 5.0857 1.63957 16).The selected home-stay property provided a safe for valuable possessions such as jewelry, money, and electronics upon request. 70 4.7714 1.72930 17).The surrounding area at the selected home-stay property was well secured and safe even at night. 70 5.2286 1.71246 18).I would consider the selected home-stay property as my first choice when I travel next time. 70 4.5143 1.99087 19).I would highly recommend the selected home-stay property to my friends and family. 70 4.8286 1.94840 20).I intend to revisit a home-stay again in a future trip to Jeddah. 70 4.5857 2.08162 21).Duration of Stay-which stay at selected homestay 70 2.3429 .67857 22). Home-stay price for the selected home-stay 70 2.7000 1.28931 Table 2 above shows the respondents perceptions and reaction concerning different questions on the questionnaire as used by the study. There is a positive relationship between room quality in the home stay property through Airbnb and customers’ repurchase intention with a mean ranging from 4.48 to 5.3. More over the relationship between value in the homestay property through Airbnb and customer re-purchase intention is also positive with a mean score ranging from 4.9 to 5.2. Finally, there is a positive relationship between security in the home-stay property through Airbnb and customers’ re-purchase intention. This has an evidence as is displayed in table two above such that the mean was from 3.514 Hypotheses H1: There is a relationship between room quality in the home-stay property through Airbnb and customers’ re-purchase intention. H2: There is a relationship between value in the home-stay property through Airbnb and customers’ re-purchase intention. H3: There is a relationship between security in the home-stay property through Airbnb and customers’ re-purchase intention. Regression Analysis The table below shows multiple regression analysis, the dependent variable is represented by use of three questions to evaluate this construct and thus i have calculated the summative scores with those three questions “I intend to revisit the stay-home property again on my future trip to Jeddah (re-purchase intention-). This variable was regressed against room quality-after I calculated the summative scores for all variables room quality, security, value, security and value of the home-stay property, the model shows that the R-squared has a coefficient of 55.5%. This coefficient shows that quality, security and value of the home-stay property explain 55.5% of the dependent variable while the rest 44.5 is explained by other factors in the model and the error term Wedd, Results of Regression Regression Dependent Variable: Re-purchase intention Sig. .294 Room Quality Value in the home stay property Security in the home-stay property Dependent Variable Intention .877 .001 .000 Re-purchase intention .001 Wedd, follow Tural’s format to report the results of hypotheses testing. The regression was applied to test the hypotheses by using summative scores of each construct. Summative scores were calculated by adding all the questions measuring the same concept and dividing them by the total number of the questions. For instance, adding all from P201 to P309 and dividing by six created the summative score for the information quality construct. After calculating summative scores for each construct, the regression Table above was completed to examine whether there is a significant relationship between room quality, room value and room security. Room quality, value and security were represented by a different question each on the questionnaires. The question of “comfortable ambiance at the selected home-stay property was worth the money I paid” represent the value attached to the room by the clients. The question “surrounding area at the selected home-stay property was well secured and safe even at night” represented the security of the room in the stay home property. Question of “the price of the selected home-stay property was reasonable, taking into consideration the quality of services offered” represented the quality of the room in the stay-home property. Regression Analysis Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .736a .541 .520 1.44184 a. Predictors: (Constant), The surrounding area at the selected home-stay property was well secured and safe even at night., The price of the selected home-stay property was reasonable, taking into consideration the quality of services offered., A comfortable ambiance at the selected home-stay property was worth the money I paid ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 161.778 3 53.926 25.939 .000b Residual 137.208 66 2.079 Total 298.986 69 a. Dependent Variable: I intend to revisit a home-stay again in a future trip to Jeddah. b. Predictors: (Constant), A comfortable ambiance at the selected home-stay property was worth the money I paid, The surrounding area at the selected home-stay property was well secured and safe even at night. The price of the selected home-stay property was reasonable, taking into consideration the quality of services offered. H1a was supported since the results indicate that room quality in the home-stay property through Airbnb influence the customers re-purchase intention (β = 0.685; t=1.058; ρ Read More