As we were. Interested in receiving. Responses from young populatio. Age of our target population was ranging from 18-45. Questions were. Asked in four sections.
In the first section
questions. Were. Asked. On whether Jerin Imel na B2B the respondent. Shopped online. At least. 10 times. In last one year. Or not.
This cut off point. Was. Taken. Presumably to. Ensure the reliability and trustworthiness of the consumers on online shopping.
It was. Found. That many. People engage in online. Shopping twice or thrice in a year. But do not rely on that.So, those who engaged. Online.Shopping at least ten times in last. One year have been. Considered real. Online shoppers in this study.
In the second and third sections, attitude towards online shopping. Using scale were collected using 1-7 scale. ranging from. Strongly disagree (1) to strongly agree (7) through 21 factors respectively.
In the last section, some demographic and socio. economic characteristics about the respondents were sought out.
Appropriateness of
Factor Tun daga farkon telegraph zuwa Analysis – Reliability of factor analysis depends on the appropriateness of data.
Without proper checking of the appropriateness of the data, the factor analysis can be misleading and inappropriate.
Soto test the
Appropriateness of the data, this study relied on Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy which is with different indexes ranging from 0 to 1. Hair et al. (2014) suggests that the KMO value should always be above 0.
5 to proceed with factor analysis.
In this study, factor analysis has been considered to find out a small set of motivational factors (mostly uncorrelated) from usb directory among a set of variables (extracted factors) which are of most importance in relation with online shopping which could be done with the help of exploratory factor analysis (EFA) or confirmatory factor analysis (CFA).
CFA, generally, tests theories related to latent process and typically used in structural equation modeling.
EFA, on the contrary, is used when there is no or a little pre-defined idea we have of the structure or how many dimensions are in a set of variables.
As the underlying
Structure for this exploratory study is not known, EFA was employed for this research.
Between two variants of EFA, this study relied on the principal component factor analysis to drive the minimum number of factors and to explain the maximum portion of variance in the original variables.
