Effects of Thought Attitude and Motivation on Internet Consumer Behavior

¶ … online purchases?" using the two-part approach provided below.

Description of the Participants

Sampling procedures

In most cases, the more subjects that are surveyed, the more trustworthy the results, but there are some diminishing returns involved in qualitative analyses that limit the usefulness of increasingly larger sample sizes. In this regard, Neuman (2003) reports that, "One principle of sample size is the smaller the population, the bigger the sampling ratio has to be for an accurate sample. Larger populations permit smaller sampling ratios for equally good samples. This is because as the population size grows, the returns in accuracy for sample size shrink" (p. 232). Researchers who employ survey methods for data-gathering purposes may have a general idea about how many subjects they would like to recruit, but the harsh realities of recruiting sufficient numbers of subjects to participate in surveys means that sometimes researchers must simply accept what they get (Darlington & Scott, 2002). As Neuman (2003) points out, "Some researchers tend to use nonprobability or nonrandom samples. This means they rarely determine the sample size in advance and have limited knowledge of the larger group or population from which the sample is taken" (p. 211).

There are two ways of estimating the sample size needed to achieve trustworthy results. For instance, Neuman (2003) advises that, "The question of sample size can be addressed by making assumptions about the population and statistical equations about random sampling processes" (p. 232). According to the online sample-size calculator provided by Raosoft (2012), "The population size indicates how many people are there to choose your random sample from. The sample size doesn't change much for populations larger than 20,000" (Sample size calculator, 2012, para. 2). A sample size of 100, for example, will provide a 5% margin of error at the 95% confidence level based on a population size of a population of only 134 with a 50% response distribution; by contrast, a recommended sample size of just 377 is the minimum recommended number for a population of 20,000 (Sample size calculator, 2012). The second method is described by Neuman (2003) thusly: "Sample size can also be addressed by the more frequent rule-of-thumb method, a conventional or commonly accepted amount" (p. 232).

Sample size

For the purposes of this study, the recommended sample size of 377 will be targeted, but a pragmatic rule-of-thumb estimation that 100 subjects represents a valid sample size will be acceptable given the time constraints involved; however, the general rule that the more subjects the better will also be followed during the data-collection process and ongoing recruiting efforts will be made during the administration of the online survey (Neuman, 2003) which is described further below.

Part Two: Description of the Procedure

Experimental manipulations

The experimental manipulation used in this study will be limited to data management techniques that analyze the statistical data that emerge from the research in ways that will identify salient trends in online consumer behavior according to gender and age with respect to online purchase behaviors using the measurement approaches outlined below.

Measurement approaches

Online purchase behaviors will be measured according to gender and age as shown and presented in tabular form as shown in Table 1 below.

Table 1

Measurement categories for online consumer behaviors

Categories

Count

Percentage

Gender

Male

Female

Age

< 21 years

21-29 years

30-39 years

40-49 years

>50 years

This breakdown is congruent with the approach used by Shergill and Chen (2005) in their study of online consumer behaviors. These data will be presented in tabular form and depicted graphically as shown in Table 1 above. This approach is consistent with the guidance provided by Chaudron who recommends that, "Whenever creating surveys, decide how to analyze, chart and graph the data before subjects complete them. This approach avoids bias when there is no set procedure for analysis, and reduces last-minute panic when the data comes flooding in" (p. 6).The two-part proforma survey instrument is set forth in Table 2 below; the first part is designed to collect relevant data concerning age and gender and the second part consists of a series of questions concerning online purchase behaviors.

Table 2

Proforma survey instrument for measuring online consumer behaviors

Question

Options

Responses

What is your age?

< 21 years

21-29 years

30-39 years

40-49 years

>50 years

What is your sex?

Male

Female

Have you used Internet during the past 12 months?

Yes

No

From where did you access the Internet?

At home

Anywhere via mobile

Have you ever purchased product online?

Yes

No

If yes, how often do you purchase product online during the past 12 months?

1-2 times

3-5 times more than 5 times

If no, have you ever think that you want to buy online?