Business Dealing with Selling Cars Online - Assignment Example

Marketing Research Report Use SPSS do it Introduction Advancement in technology has reshaped and revamped the way business is being done. There is a shift towards using internet as a platform for firms to carryout business. The advantages associated with this technology has left almost all business firms whether big or small in size to consider adopting it with the notion that it will help them stay competitive and relevant in the current world of business. However, there is little knowledge these firms have with regards to both advantages and disadvantages of adopting e-commerce. E-commerce is one of the fastest growing industries worldwide and is one of the most rapidly evolving areas of national and international trade (Eisingerich & Kretschmer, 2008). Using internet to carryout business has been deemed to be the most current innovation in the world of business and offers an opportunity to businesses to carryout business through electronics. Firms have rushed to adopt e-commerce which entails making transaction online with the belief that it will help them gain competitive advantages and increase their market shares as well as revenue. Indeed there are numerous advantages associated with this concept such as capturing new markets by allowing firms to go global, 24/7 operation this has been shown to bring with it the advantage of reliability and convenience which allows potential customers who do not have time to buy products and services regardless of time. It is evident that e-commerce help firm cut the costs of doing business, for instance there will be less paper work which requires human resource, a flexible or telework arrangement can be put in place making working execute their tasks, duties and responsibilities not necessarily in the office among other advantages (Eisingerich & Kretschmer, 2008). However there is need to first analyze if it is viable for a firm to adopt this technology ad for those firms that have already adopted internet in doing business, there is need for them to constantly evaluate its relevance and areas that need improvement. In this paper, I will try to analyze a questionnaire distributed by a business dealing with selling cars online. The task include identifying the level of measurement of each question, performing a descriptive analysis of each question and finding if there is a relationship between gender and respondent buying a new car from the company’s website. Level of measurement It is worth noting that in any research, the data collected through survey falls in one of the four level of measurement, nominal, order, interval or ratio scale. Variables falling under this category are those that have value but with no mathematical interpretation and posses difference in quality but not in quantity. The major characteristic of this level of measurement is to name or label attributes. Data can only be put into groups and counted by frequency (Burns & Bush, 2010). Ordinal scale is where the data can be placed in a certain order either from the lowest to the largest or vice versa. The order is indicted but the different magnitude of a given attribute is not indicated. This can be exemplified by Likert scale. It is worth noting that interval scale data have a fixed measurement unit but lack the true zero characteristic. It is possible for one to interpret both the order of the scale score and the distance between them. An example is temperature. Ratio scale is deemed to be the highest level of measurement. It possesses the characteristics of an interval scale as well as having a fixed origin (true zero point). Variables in this category include height, weight as well as time (Burns & Bush, 2010). Level of measurement Questions Nominal 1,5,7 , 7a and 19 Ordinal 14, 16 and17, Interval 2, 3, 6, 7b, and 8 Ratio 4,9,10,11,12,13,15 and 18 Descriptive analysis Nominal scale questions This involved questions 1, 5, 7,7a, 14, 17 and 19. The only suitable statistics for this variable was a frequency distribution which shows counts and percentages. Table 1. Frequencies of nominal scale variables Category Percentage Category Percentage Visit the website 100% (1400) Buy vehicle online Yes (20.5%) Find out about Auto Online No (79.5%) Friend Yes (5.8%) No (94.2%) Good experience Yes (19.4%) Internet Banner Yes (16.9%) No (83.1%) No (1.1%) Search Engine Yes (66.4%) No (33.6%) Missing (79.5%) Theater Yes (3.7%) No (96.3%) Marital status Some other way Yes (2.6%) No (97.4%) Single 39.9% Billboard Yes (3.4%) No (96.6%) Married 41.5% Web surfing Yes (43.4%) No (56.6%) Widowed 0.6% Television Yes (32.3%) No (67.7%) Divorced 14.9% Newspaper Yes (5.3%) No (94.7%) Separated 3.2% Race Gender Caucasian 68.5% Black 15.5% Males 80.3% Asian 9.1% American Indian 0.1% Female 19.7% Hispanic 6.2% Other 0.6% From table 1it is evident that all the respondents (100.0%) visited the Auto Online website in the past 3 month. When the respondent were asked to state how they came to know about the Auto Online, 5.8% said through friends, 16.9% through internet banner, 66.4% through search engines, 3.7% through theater, 2.6 through some other ways, 3.4% through billboard, 43.4% through web surfing, 32.3% through television and only 5.3% through newspaper. It is worth noting that when asked about buying their new vehicle from Auto Online website, 20.5% said yes while 79.5% said no. when asked whether buying a new car online was a better experience than the traditional way, 19.4% said yes, 1.1% said no while there was 79.5 missing cases, this is attributed to a bigger percentage not buying their new car from the company’s website. Ordinal scale The race of the respondents were as follows, Caucasian were presented by 68.5%, Blacks were represented by 15.5%, Asian by 9.1%, American Indian by 0.1%, Hispanic 6.2% and others 0.6%. In terms of gender, males were 80.3% while females were represented by 19.7%. Concerning marital status, 39.9% were single, 41.5% married, 0.6% widowed, 14.9% divorced and 3.2% separated (Table 1). From table 2, it is evident that 10.7% had less than high school level of education, 16.4% had acquired high school education, 23.4% had some collage education, 21.1% possessed undergraduate degree, 16.8% were graduate degree holders while 11.6% had acquired other level of education. Table 2 level of education Frequency Percent Valid Percent Cumulative Percent Valid Less than high school 150 10.7 10.7 10.7 High school 229 16.4 16.4 27.1 Some college 328 23.4 23.4 50.5 Undergraduate degree 295 21.1 21.1 71.6 Graduate degree 235 16.8 16.8 88.4 Other 163 11.6 11.6 100.0 Total 1400 100.0 100.0 Interval scale In table 3 it is evident that when asked about how often the respondents make purchases through the internet, 19.9% said never, 23.6% said almost never, 23.0% said occasionally, 21.3% said often and only 12.1% said very often. There were missing cases. Table 3 How often do you make purchases through the Internet? Frequency Percent Valid Percent Cumulative Percent Valid Never 279 19.9 19.9 19.9 Almost never 331 23.6 23.6 43.6 Occasionally 322 23.0 23.0 66.6 Often 298 21.3 21.3 87.9 Very often 170 12.1 12.1 100.0 Total 1400 100.0 100.0 Figure 1I like using the internet The figure above shows the majority of the respondents were neutral about whether they like using the internet. Figure 2 using the internet to research purchases More individual were in agreement that they use the intent to carryout research on the purchases they make. Figure 3 Purchasing items from the internet is safe From figure 3, it is evident that majority of the respondents were skeptical about the safety of buying products through the internet. Figure 4 Internet being a good tool to use when researching an automobile purchase. From figure 4, it is evident that those who strongly disagree that the internet is a good tool to use when researching an automobile are more compared to those who strongly agreed with the statement. Figure 5 Internet should not be used to purchase vehicles It was interesting when the respondents were asked whether they agreed that the internet should not be used to buy vehicles majority of the respondents strongly agreed compared to those who strongly disagreed. Figure 6 Online dealership is another way of getting one into traditional dealership Most of the respondents disagreed that online dealership was another way of getting potential customers into the traditional dealership. Respondents believed that online dealership was exclusively a virtual environment of doing business. Figure 7 I like the process of buying a new car From figure 7 it is apparent that majority of the respondents did not like the new process of buying a new car. Figure 8 Don’t like to hassle with car salesmen In figure 8 it is depicted that majority of the respondents do not like to hassle with car salesmen. A few were strongly disagreeing with the stamen. The table below shows how the respondents gave their views with regards to how much better was the experience of buying a new car from the company’s website. It is evident that those who were of the view that it was a great deal better were represented by 8.4% while those who said it was just a buy better were represented by 1.8%. Table 4 If yes, indicate how much better. Frequency Percent Valid Percent Cumulative Percent Valid A great deal better 117 8.4 43.0 43.0 Much better 72 5.1 26.5 69.5 Somewhat better 58 4.1 21.3 90.8 Just a bit better 25 1.8 9.2 100.0 Total 272 19.4 100.0 Missing System 1128 80.6 Total 1400 100.0 Table 5 People want to test the performance of the vehicle before buying it. Frequency Percent Valid Percent Cumulative Percent Valid Disagree 8 .6 .6 .6 Neutral 113 8.1 8.1 8.6 Agree 451 32.2 32.2 40.9 Strongly Agree 828 59.1 59.1 100.0 Total 1400 100.0 100.0 Table 5 represents respondents’ views on whether they agree or not about testing the performance of the vehicle before buying it. 59.1 strongly agreed while only 0.6% disagreed. About the safety of the internet being a place for personal information, majority of the respondents, 28.8% felt that the internet was not a safe place for personal information (table 6). Table 7 People usually have trade-ins that are too complicated to deal with online. Frequency Percent Valid Percent Cumulative Percent Valid Strongly Disagree 378 27.0 27.0 27.0 Disagree 176 12.6 12.6 39.6 Neutral 184 13.1 13.1 52.7 Agree 196 14.0 14.0 66.7 Strongly Agree 466 33.3 33.3 100.0 Total 1400 100.0 100.0 When asked about whether people usually have trade-ins that are too complicate to veal with online, 33.3% strongly agreed while 27.0% strongly disagreed. Table 8 People want to see the vehicle before they buy it to check for imperfections. Frequency Percent Valid Percent Cumulative Percent Valid Strongly Disagree 802 57.3 57.3 57.3 Disagree 320 22.9 22.9 80.1 Neutral 185 13.2 13.2 93.4 Agree 71 5.1 5.1 98.4 Strongly Agree 22 1.6 1.6 100.0 Total 1400 100.0 100.0 When the respondents were asked whether they want to see the vehicle before they buy to check for imperfections, only 1.6% strongly agreed while 57.3% strongly disagreed (table 8). Table 9 People feel that the Internet is not a safe place for personal information. Frequency Percent Valid Percent Cumulative Percent Valid Strongly Disagree 274 19.6 19.6 19.6 Disagree 195 13.9 13.9 33.5 Neutral 257 18.4 18.4 51.9 Agree 271 19.4 19.4 71.2 Strongly Agree 403 28.8 28.8 100.0 Total 1400 100.0 100.0 From table 10, it is evident that majority of the respondents were strongly in agreement with the statement that people like to have hand on situation when buying different options for their vehicle. Table 10 People like to have a "hands on" situation when buying different options for their vehicle. Frequency Percent Valid Percent Cumulative Percent Valid Strongly Disagree 32 2.3 2.3 2.3 Disagree 92 6.6 6.6 8.9 Neutral 304 21.7 21.7 30.6 Agree 383 27.4 27.4 57.9 Strongly Agree 589 42.1 42.1 100.0 Total 1400 100.0 100.0 From table 11 it is shown that majority of the respondents, 35.8% strongly disagreed that one can negotiate a better price by talking with a sales representative while 28.1% were in strong agreement with the statement. Table 11 People feel they can negotiate a better price by talking with a sales representative in person. Frequency Percent Valid Percent Cumulative Percent Valid Strongly Disagree 501 35.8 35.8 35.8 Disagree 172 12.3 12.3 48.1 Neutral 185 13.2 13.2 61.3 Agree 148 10.6 10.6 71.9 Strongly Agree 394 28.1 28.1 100.0 Total 1400 100.0 100.0 Figure 9 The website was easy to use From figure 9 it is evident that majority of the respondents found it easy to use the company’s website. Figure 10 website was very helpful in my purchase Similarly figure 10 shows that majority of the respondents agreed that the website was very helpful to them when buying a new car. Figure 11 Having a positive experience using the website From the bar graph in figure 1 it is apparent that the respond nets were in agreement that they had positive experiences using the company’s website. Figure 12 Would use the website only for research When asked whether they will used the company’s website purely for research majority of the respondents disagreed, this meant that they will use it for other purposes. Figure 13 The website influenced me to buy my vehicle From figure 13 it is apparent that a bigger portion of the respondents agreed that the website indeed influenced their decision to buy a new vehicle. Figure 14 Feeling secure buying from the website Although it was shown elsewhere that the respondent felt that buying online is not safe, majority of them stated that they would feel secure if they buy vehicles from the company’s website. Ratio scale Table 12 Descriptive Statistics N Minimum Maximum Mean Std. Deviation About how many times before you bought your automobile did you visit the Auto Online web site? 1400 1 16 6.61 3.171 Valid N (listwise) 1400 Table 12 shows the average number of times they visited the internet before buying an auto mobile. It is apparent that the average time the respondent visited the website is 6.61 times, the median is 7.0 while the mode was 6, this means that majority of the respondents visited the site 6 times. The maximum number the respondents visited the website is 16 times while the lowest number of visits stands at 1. Table 13 Statistics For how many weeks were you actively searching for your vehicle? N Valid 1400 Missing 0 Mean 3.61 Median 3.00 Mode 1 Std. Deviation 2.351 Minimum 1 Maximum 12 Sum 5050 When asked about the number of weeks a respondents was actively searching for his or her car, it emerged that there was no missing cases and the average time was 3.61 weeks, the median was 3.0 and the mode stood at 1. Majority of the respondents were searching for his or her car for only a week. This being the minimum number of weeks while 12 being the maximum number of weeks one was actively searching for his vehicle. Table 14 summarizes questions 10, 11 and 12. When asked about the price of the car the respondents traded in it emerged that the minimum price was $1,000 while the maximum price was $31,000. The standard deviation was $5,331.39 meaning that majority of the respondent traded in a vehicle whose price ranged between $15,709.48 and $5,046.69. The mean was $10,378.09. The actual priced they paid for averagely was $13,181.43, the maximum price paid was $33,000 and the minimum was $5,000. The standard deviation was $5,017.90. The approximate sticker price for the respondents’ new vehicle mean was $15,496.43, the maximum and minimum sticker prices were $35,000 and $10,000 (table 14). Table 14 Descriptive Statistics N Minimum Maximum Mean Std. Deviation If you traded in a vehicle, approximately how much was it worth? 1296 $1,000 $31,000 $10,378.09 $5,331.392 What was the approximate actual price you paid for it? 1400 $5,000 $33,000 $13,181.43 $5,017.903 What was the approximate sticker price of your new vehicle? 1400 $10,000 $35,000 $15,496.43 $4,905.977 Valid N (listwise) 1296 Concerning the age of the respondents, table seven gives a summery. The oldest respondents were 66 years old wile the youngest was 21 years old. The average age of the respondents stood at 36.08 years while the standard deviation was 8.625 years. The same can be graphically represented as in figure 2. Table 15 Descriptive Statistics N Minimum Maximum Mean Std. Deviation What is your age? 1400 21 66 36.08 8.625 Valid N (listwise) 1400 When the respondents were asked about the number of children they were living with and who were below the age of 18 years, there were 842 valid responses while 558 were missing. Those with no child were 10.0%, with one child were 20.2%, those with 2 children were 20.4%, with 3 children were 7.9%, those with 4 children were represented by 1.5% while those living with 5 children were represented by 0.2%. Table 16 How many children under the age of 18 are living with you? Frequency Percent Valid Percent Cumulative Percent Valid 0 140 10.0 16.6 16.6 1 283 20.2 33.6 50.2 2 285 20.4 33.8 84.1 3 110 7.9 13.1 97.1 4 21 1.5 2.5 99.6 5 3 .2 .4 100.0 Total 842 60.1 100.0 Missing System 558 39.9 Total 1400 100.0 From figure 15 below, the families whose income before taxes were under $35,000 were represented by 9.4%, between $35,000-$50,000 were represented by 10.7%, between $50,000-$65,000 were 8.2%, 65,000-80,000 were 13.9%, $80,000-$95,000 were 21.5%, $95,000-$110,000 were 15.6% and those families earning over $110,000 were represented by 20.8%. Figure 15 Total household income before tax Figure 16 Histogram of age of the respondents Relationship between gender and buying a new car online To establish whether there was a relationship between gender and buying a new car online, a cross tabulation will be carried out. Ideally cross tabulation entail merging of the frequency distributions of two or more variables in a table. This method was chosen because it will help in examining the direction of the relationship as well as the level of significance; how one variable relates to another variable. Additionally the data type which is categorical variables meets the requirement of using this method (Burns & Bush, 2010). Table 17 Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Did you buy your new vehicle on the Auto Online web site? * Your gender is... 1400 100.0% 0 .0% 1400 100.0% From the table above, it is evident that there are no missing cases, this means that all the 1400 respondent answered the two questions, about their gender and buying a car online. Table 18 Did you buy your new vehicle on the Auto Online web site? * Your gender is... Crosstabulation Your gender is... Total Male Female Did you buy your new vehicle on the Auto Online web site? Yes Count 227 60 287 % within Your gender is... 20.2% 21.7% 20.5% No Count 897 216 1113 % within Your gender is... 79.8% 78.3% 79.5% Total Count 1124 276 1400 % within Your gender is... 100.0% 100.0% 100.0% This table, 18 shows the cross tabulation results. It is evident that a total of 287 respondent representing 20.5% bought their new car online while 1113 respondents did not buy their new car online representing 79.5%. It is also apparent that 227 males which represent 20.2% bought their new car online while 897 which represent 79.8%. On the other hand only 21.7% (60) of female admitted that they bought their new car online while 78.3% (216) did not buy their new car online. It is thus evident from the results that males were more likely to buy new car online compared to female (Coakes, Steed & Price, 2008). This can be clearly seen in the bar graph below Figure 17 Bar graph It was also of interest to establish if the relationship between gender and buying a new car online was significant. However, after carrying out a cross tabulation with chi square checked, it emerged that the relationship is not statistically significant 0.569 is greater than p value of 0.05. This means that the gender does not dictate whether or not one will buy a new car from the internet. This means that there must be another factor which dictates buying a new car online. It was also of interest to establish if there was a difference in gender and purchasing goods and services online. This will help the firm to come up with better strategies to encourage the gender which seemed adamant in using the internet to make purchases. To accomplish this task, a cross tabulation is carried out. From table 19 it is evident that the male respondents were more likely to buy to buy and not to buy or make purchases online compared to female. For instance 69.9% and 73.1% of males agreed that they never or almost never make purchases through the internet respectively while the percentages of the same for the females’ respondents stood at 30.1% and 26.9%. Additionally males indicated that they had a 85.6% chance to make often purchases through the internet while the females respondents’ had a 14.4% chance of making often purchases through the internet. All these can be seen visually in figure 18. Table 19 Your gender is... * How often do you make purchases through the Internet? Cross tabulation How often do you make purchases through the Internet? Total Never Almost never Occasionally Often Very often Your gender is... Male Count 195 242 262 255 170 1124 % within How often do you make purchases through the Internet? 69.9% 73.1% 81.4% 85.6% 100.0% 80.3% Female Count 84 89 60 43 0 276 % within How often do you make purchases through the Internet? 30.1% 26.9% 18.6% 14.4% .0% 19.7% Total Count 279 331 322 298 170 1400 % within How often do you make purchases through the Internet? 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Figure 18 Cross tabulation of gender and making purchases from the internet Table 20 Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 77.043a 4 .000 Likelihood Ratio 107.579 4 .000 Linear-by-Linear Association 71.799 1 .000 N of Valid Cases 1400 a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 33.51. From table 20 it is evident that a chi square was carried out to determine if there was a significant association between gender and making purchases from the internet. Results clearly shows that there was a weak positive statistically significance between the two variables, Cramers, V=0.235 χ2 (4) =77.043, p=0.000 Marketing implications From the above findings, it is evident that some respondents still shows skepticism about internet security and safely. On the same note, they have indicated that they will feel secure purchasing products from the company’s website. This calls the firm to incorporate better security measures in the website. Additionally it has been shown that most males engage in buying new vehicles, online. Although there was not statistical significance between gender and buying vehicles, online, it emerged that there was statistical significance between gender and making purchases on line; the firm needs to come up with better strategies that will make more females to buy new cars through the companies, website, this might include giving those who buy new cars online some incentives like prolonged after sale services among others. Conclusion The task has involved using SPSS to evaluate the use of internet marketing for Auto Online company. Issues addressed include categorizing the question into one of the four levels of measurement, carrying out a descriptive analysis of each question and establishing whether there was a relationship between genders and buying a new car online. References Burns, A. & Bush, R. (2010). Marketing Research. Upper Saddle River: Pearson Education, Coakes, J., Steed, L. & Price, J. (2008). SPSS: Analysis without Anguish: Version 15 for Windows, Milton, QLD: John Wiley & Sons Australia. Eisingerich, A. & Kretschmer, T. (2008). In E-Commerce, More is More. Harvard Business Review 86, 20–21. Read More