A Model of Customer knowledge sharing behavior in electronic businesses: case study of Digikala

Introduction: Customers' acceptance of e-shopping has provided an unprecedented opportunity to obtain knowledge from customers with the aim of improving electronic businesses. Numerous researches has been conducted on the identification of factors affecting knowledge sharing by customers, however, literature review showed that not enough attention has been paid to the issue of identifying the order and importance of customer behavior formation factors for knowledge sharing. The purpose of this research is to identify the customer knowledge sharing behavior model in e-businesses with an emphasis on identifying the prerequisite relationships between the model variables. The three main questions in this article are: 1- What is the behavioral model of customer knowledge sharing in electronic businesses? 2- What variables are effective as drivers in the behavior of customers to share knowledge in electronic businesses? 3- What are the relationships between the influencing variables in the behavior of customers to share knowledge? For this purpose, based on the "Think-Feel-Do "model, "Event-Evaluate-Feel-Do" model was built as a conceptual model.
 Methodology: This research is practical in terms of purpose and descriptive-survey in terms of methodology. The statistical population of the study is the consumers of Digikala. The Cochran formula is used to estimate the sample size. Using the data collected by a questionnaire from 436 customers with a knowledge sharing experience in one of the country's electronic businesses, analysis of structural equation modeling was performed. The data were collected, tested and analyzed by the SmartPls3 software programs.
 Results and Discussion: Considering that all factor loadings of the model are greater than 0.50 and also Cronbach's alpha value of the combined reliability of the variables is greater than 0.70 and the positive common values ​​for all variables, the reliability of the measurement model was confirmed. The greater value of the average variance index extracted for all variables than 0.50 and the positive results of Fronel-Larker analysis confirm the convergent validity and divergent validity of the measurement model. The fact that the value of t statistic for all paths of the model is higher than the absolute value of 1.96, the coefficient of determination of all variables is higher than 0.50, the redundancy index and Q2 are positive for all variables, show that the structural fit of the model can be confirmed. The overall fit of the model was also confirmed using the goodness of fit criterion equal to 0.54.
Conclusion: The results showed that the starting point in sharing of customer knowledge is, respectively, event observation with a user origin, vendor origin, or internal origin. The customer then evaluates the action to share knowledge, based on four factors, in order of importance, "security consequences", "cost and benefits of knowledge sharing", "user experience from the knowledge registration process in the seller's portal" and "effectiveness of knowledge sharing". Based on the evaluation result, a feeling is evoked in the customer, which is mostly based on the feeling of sympathy and belonging, under the feeling of sadness and discomfort as well as the feeling of pleasure. Based on this feeling, the customer's decision for sharing knowledge is made, which the results revealed that among the three types of "blind", "open" and "unknown" knowledge, customers tend to share "Blind knowledge" more. Designing tools and applications based on the most important factors identified in the process of customer decision formation for knowledge sharing is a suitable field for future research. The customization of this model in future research based on the type and product of electronic businesses and the characteristics of customers, including age, gender, ethnicity and education level, can create more practical results for businesses. This research is the result of the analysis of data and information that is limited to the case study of this research. Meanwhile, if the same research method is analyzed in several statistical communities, the results will be more reliable and its generalizability will increase. Another limitation of this research was the limitation of access to online customer journeys data in the studied e-business portal. This caused the researchers to base their analysis on the information and data collected from the questionnaire instead of first-hand data at the time of the customer's action to share knowledge.