The seamlessly integrated digital marketing through mouse-click ensures the customers’ needs with the door-step delivery. The COVID-19 pandemic experiences entrust the need for digital buying. It is essential to understand digital user and platform experiences to know buyer trust and emotional rapport of digital customer
The Positive CRM upsurge customer satisfaction and retention rate as well as employee satisfaction, consequently business performance. There is a requirement for understanding the speed of decision making by digital buyers
The structured questionnaire consists of four sections, the first section on the demographic information, second section on Digital Buying Behaviour (DBB), third section on Risk Factors (RF) associated with digital buying and fourth section on Customer Relationship Management (CRM). The designed instrument (Likert Scale) was validated with the help of an exploratory factor analysis and confirmed the items by confirmatory factor analysis and the model fitness is verified by measuring fit indexes using AMOS
Data Analysis is carried out in three stages viz., scale validation is done for DBB, RF and CRM. Further, mediating role of CRM in association amid DBB and RF is established. Accordingly, the results are discussed in the section below.
The Kaiser-Meyer-Olkin (KMO) test value is 0.784, which is more than 0.6
The Kaiser-Meyer-Olkin (KMO) test value is 0.827, which is more than 0.6
The Kaiser-Meyer-Olkin (KMO) test value is 0.817, which is more than 0.6
The present study was proposed to test the hypothesis; Digital Buying Behaviour (DBB) has a positive impact on Risk Factors of Digital Buying (RF) (H1), Customer Relationship Management (CRM) has a positive impact on Risk Factors (RF)(H2), Digital Buying Behaviour (DBB)has a positive impact on Customer Relationship Management (CRM) (H3) and DBB has a direct mediating effect through Customer Relationship Management (CRM) on Risk Factors (RF), (H4). The DBB is significant and positively associated with Risk Factors of Digital Buying (RF) (β = 0.952, p < 0.001), CRM is directly associated with RF (β = 0.471, p < .001) and DBB is noteworthy and directly related to CRM (β =.779, p<.001).
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|
|
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Step A |
0.890 |
0.070 |
0.952 |
10.992 |
0.000 |
Step B |
0.886 |
0.098 |
0.741 |
7.036 |
0.000 |
Step C |
0.708 |
0.062 |
0.779 |
7.003 |
0.000 |
Step D |
0.802 |
0.075 |
0.702 |
08.99 |
0.000 |
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Type of Mediation |
Z |
Effects |
Level of Significance |
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Score |
Direct |
Indirect |
Total |
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Partial |
3.09 |
0.603 |
0.250 |
0.852 |
0.000 |
* Controlled variable (DBB), predicted variable (RF), Mediating variable (CRM)
The multiple regression analysis indicates that; the first 3 steps of the mediation investigation were satisfied-reinforced. It also explored that after removal of mediating variables (CRM), β weight of the DBB is reduced from 0.952 to 0.703. Hence, CRM act as a partial mediator in relationship amid DBB and RF. In addition, Sobel test is steered to confirm the significance of the mediation effect of CRM, test statistic (z= 3.09, p <.001) reveals that there exist no proof to reject the pre-stated null hypothesis. Thus, CRM will mediate the relationship between DBB and RF. The DBB is significant and directly connected with RF (β = 0.952, p < .001), CRM is significant and positively allied with RF (β = 0.471, p < .001). DBB is significant and positively related to CRM (β = 0.779, p < 0.001). Thus, results may be summarized as; The RF has a positive impact on DBB(H1), CRM has a positive impact on DBB significantly (H2), DBB has a positive impact on CRM significantly(H3) and DBB has a direct mediating effect through CRM on RF(H4).The results of the multiple regression analysis explored that the first 3 steps of the mediation investigation were satisfied and reinforced, it also explored that after removal of mediating variables (CRM), the β weight of the DBB is reduced from 0.952 to 0.703 which is significant. Hence, CRM act as a partial mediator in relationship amid DBB and RF.
The CRM act as a partial mediator amid DBB and RF similar to the findings of
As CRM the β weight of the DBB is reduced from 0.952 to 0.703 which is also significant. Hence, CRM act as a partial mediator in relationship amid DBB and RF. Sobel test confirm the significance of the mediation effect of CRM (z= 3.09, p <.001). The DBB is significant and directly connected with RF (β = 0.952, p < .001), CRM is significant and positively allied with RF (β = 0.471, p < .001). DBB is significant and positively related to CRM (β = 0.779, p < 0.001). Thus, The RF has a positive impact on DBB(H1), CRM has a positive impact on DBB significantly (H2), DBB has a positive impact on CRM significantly(H3) and DBB has a direct mediating effect through CRM on RF(H4). A strong CRM system must deliver to potential digital buyers the value proposition of product and services buying process and management. DBB has a positive impact on CRM significantly (H3) and DBB has a direct mediating effect through CRM on RF, this indicates that a combination of high levels of examination and implementation of CRM is positively related to digital buying behaviour. The present study findings indicate that DBB process should embrace effective CRM driven by digital storekeepers.
Thus, it is decisive to hold effective CRM system in order to stimulate DBB towards buying intention. The study has important theoretical and managerial implications for further research in DBB, RF and CRM. Digital marketing professionals need to work out right permutation and combination of these three factors to achieve right mix of marketing. The present study findings indicate that DBB process should embrace RF which is driven by CRM. Finally, Digital marketing professionals may consider these variabilities to design Integrated Digital marketing Management Process. This study has certain limitations which may be explored by future researchers. First, data were obtained from Digital Buyers of Bangalore city, India which may also affect the accuracy of the universal judgment at the national level. Second, current study adopted purely quantitative approach. Therefore, considering these limitations into account, we call future researchers to explore on Qualitative Research in the marketing mix directions.