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An Analysis of Customer Behavior in Online Shopping of Electronic Products 

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Research scopelocation scope of this research was south Tehran branch of Islamic azad university. Time scope of this research was all of students tested at winter 2018.Theme scope of this research was identification and prioritization of factors influencing costumer behavior in online purchase of electronic products.

Information collecting toolsIn this study we used two questionnaires to collect needed data. The first questionnaire was designed using Delphi method that its purpose was to identify effective indicators on costumer behavior in online purchase of electronic products. For this purpose, 14 of 20 indicators (table 1) extracted from past studies were rendered to elites using semi – open questionnaire and after thee times screening, final indicators were specified.

Next step of data collection was performed using even – comparison questionnaire. Goal of even – comparison questionnaire was to rank and determine weights of research indices applying hierarchy analysis. This questionnaire was designed after specifying results of previous step. Indices in this questionnaire were compared in binary manner. Given the method of this research that was descriptive – dependency, the first questionnaire included two parts:First part, demographic questions: in this part, questions such as education level, age, gender, employment state, marriage status were included. Second part, questions related to studied variables: in this pat, the questions were posed in order to measure and investigate costumer behavior in online purchase of electronic products. This part of questionnaire consisted of 14 items with five-score Likert scale. Table 2 shows mentioned likert scale


To determine justifiability of content of research tools, judicative method was used. To do so, questionnaire was designed and distributed among 4 university professors and 4 internet marketing experts and then analyzed and after several times modification and variation of questions, their justifiability was confirmed.


Perpetuity of first questionnaireThe most important method for order scales is Cronbach’s method or vision-meter. Given that minimum perpetuity coefficient for research questionnaires is 0.7, it is observed that obtained Cronbach’s alpha coefficient is higher than this threshold value and so is appropriate. After that, with general distribution of questionnaires, Cronbach’s alpha coefficient for total questionnaires quietly completed and investigatable, was accounted 0.868 using SPSS software.

Perpetuity of even – comparison questionnaireIn order to final evaluate second questionnaire, incompatibility rate was used. Incompatibility rate of even – comparison matrices by super decision was 0.008 (less than 0.1), consequently compatibility of matrices was acceptable.

Data analysis

To investigate questions of present research, statistic tests and decision techniques have been applied. In the following and after offering demographics findings of studied sample, results of tests have also been presented.

Demographics findingsFollowing demographics findings show information related to studied statistic sample in questionnaire designing step via likert spectrum. In this questionnaire, indicators such as gender, marital status, education and employment background were analyzed.

Description of sample members based on genderTable 3. demonstrates gender combination (abundance) of sample members. Table 3. abundance combination of sample members based on genderAs obviously seen, 55 percent of sample volume was assigned to marrieds while 45 percent to unmarried. According to demographics analysis, majority of internet buyers were youth with education level higher than undergraduate.

Results of questionnaire analysis using SPSS softwareIn this part of research, mean and standard deviation of data (14 indicators influencing costumer behavior in online purchase of electronic products) were calculated applying information achieved from the questionnaire completed by students and inputting data in statistic SPSS software. According to students (online consumers), obtained results are priority index that based on table 7, is less and more the same in experts opinion.

Prioritization of indicators affecting costumer behavior in online purchase of electronic productsHere, we involve prioritization of indicators affecting costumer behavior in online purchase of electronic products. According to categorization of factors in this research, final prioritization was presented. Resultant graph shows hierarchy structure of making decisions. The firs level is the same target level. In this research, goal of hierarchy analysis was to prioritize indicators affecting costumer behavior in online purchase of electronic products that was second level.APH technique was used to prioritize.

Prioritization of indicesIn this part, even – comparison of indicators and outputs of super decision software related to prioritization of effective indicators in costumer behavior in online purchase of electronic products were expressed. firstly, Unity even – comparison matrix was formed via geometry mean based on 3 experts opinions and then sum of values of all three rows was calculated and resultant values were normalized. Table 8 demonstrates mean of experts opinions rounded as integer numbers to even – compare 14 factors.

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