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Background In recent years, online pharmacies have been accepted by increasingly more consumers, and the prospects for online pharmacies are optimistic. This article explores the consumers’ satisfaction factors addressed in Business to Customer (B2C) online pharmacy reviews and analyzes the sentiments expressed in the reviews. The goal of this work is to help B2C online pharmacy enterprises identify consumers’ concerns, continuously improve the health services level.
Methods This article was based on the Latent Dirichlet Allocation (LDA) topic model. From a third-party platform-based B2C online pharmacy and a proprietary B2C online pharmacy (JD Pharmacy and J1.COM, respectively), 136,630 pieces of over-the-counter (OTC) drug review data posted from January 1, 2015 to December 31, 2018 were selected as samples and used to explore the satisfaction factors of B2C online pharmacy consumers regarding the entire drug purchasing process. Then, the sentiments expressed in the drug reviews were analyzed with SnowNLP.
Result Categorization of the 12 factors identified by LDA showed that 5 factors were related to logistics; these 5 factors, which also included the most drug reviews, made up 38.5% of the reviews. The number of factors related to drug prices was second, with 3 factors, and reviews of drug prices made up 25.5% of the reviews. Customer service and drug effects each had two related factors, and a smaller percentage of these reviews (13.95%) were related to drug effects. Consumers still maintain positive opinions of JD Pharmacy and J1.COM. However, some opinions on logistics and drug prices are expressed.
Conclusion The most important task for online pharmacies is to improve logistics. It is better to develop self-built logistics. Both types of B2C online pharmacies can improve consumer viscosity by implementing marketing strategies. With regard to customer service, focusing on improving employees' service attitudes is necessary.
Keywords
B2C, mail-order pharmacy, online review, topic mining, sentiment analysis
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CURRENT STATUS: Published
View the published article at BMC Medical Informatics and Decision Making.
No community comments so far
Submission checks complete
On 12 Aug, 2020
Editorial decision: Accept
On 12 Aug, 2020
Version 2
Posted 08 Jul, 2020
No comments provided
Editorial decision: Minor revision
On 06 Aug, 2020
Review #1 received
Received 03 Aug, 2020
Reviewer #1 agreed
On 23 Jul, 2020
Reviewers invited
Invitations sent on 14 Jul, 2020
Editor assigned
On 02 Jul, 2020
Submission checks complete
On 01 Jul, 2020
Editor invited
On 01 Jul, 2020
No comments provided
Editorial decision: Major revision
On 05 Jun, 2020
Review #2 received
Received 27 May, 2020
Reviewer #2 agreed
On 18 May, 2020
Review #1 received
Received 22 Feb, 2020
Reviewer #1 agreed
On 07 Feb, 2020
Reviewers invited
Invitations sent on 04 Feb, 2020
Editor assigned
On 06 Dec, 2019
Submission checks complete
On 05 Dec, 2019
Editor invited
On 05 Dec, 2019
First submitted
On 04 Dec, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Medical Informatics
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See the published version of this preprint at BMC Medical Informatics and Decision Making.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Medical Informatics and Decision Making.
No community comments so far
Submission checks complete
On 12 Aug, 2020
Editorial decision: Accept
On 12 Aug, 2020
Version 2
Posted 08 Jul, 2020
No comments provided
Editorial decision: Minor revision
On 06 Aug, 2020
Review #1 received
Received 03 Aug, 2020
Reviewer #1 agreed
On 23 Jul, 2020
Reviewers invited
Invitations sent on 14 Jul, 2020
Editor assigned
On 02 Jul, 2020
Submission checks complete
On 01 Jul, 2020
Editor invited
On 01 Jul, 2020
No comments provided
Editorial decision: Major revision
On 05 Jun, 2020
Review #2 received
Received 27 May, 2020
Reviewer #2 agreed
On 18 May, 2020
Review #1 received
Received 22 Feb, 2020
Reviewer #1 agreed
On 07 Feb, 2020
Reviewers invited
Invitations sent on 04 Feb, 2020
Editor assigned
On 06 Dec, 2019
Submission checks complete
On 05 Dec, 2019
Editor invited
On 05 Dec, 2019
First submitted
On 04 Dec, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Medical Informatics
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Medical Informatics and Decision Making.
Background In recent years, online pharmacies have been accepted by increasingly more consumers, and the prospects for online pharmacies are optimistic. This article explores the consumers’ satisfaction factors addressed in Business to Customer (B2C) online pharmacy reviews and analyzes the sentiments expressed in the reviews. The goal of this work is to help B2C online pharmacy enterprises identify consumers’ concerns, continuously improve the health services level.
Methods This article was based on the Latent Dirichlet Allocation (LDA) topic model. From a third-party platform-based B2C online pharmacy and a proprietary B2C online pharmacy (JD Pharmacy and J1.COM, respectively), 136,630 pieces of over-the-counter (OTC) drug review data posted from January 1, 2015 to December 31, 2018 were selected as samples and used to explore the satisfaction factors of B2C online pharmacy consumers regarding the entire drug purchasing process. Then, the sentiments expressed in the drug reviews were analyzed with SnowNLP.
Result Categorization of the 12 factors identified by LDA showed that 5 factors were related to logistics; these 5 factors, which also included the most drug reviews, made up 38.5% of the reviews. The number of factors related to drug prices was second, with 3 factors, and reviews of drug prices made up 25.5% of the reviews. Customer service and drug effects each had two related factors, and a smaller percentage of these reviews (13.95%) were related to drug effects. Consumers still maintain positive opinions of JD Pharmacy and J1.COM. However, some opinions on logistics and drug prices are expressed.
Conclusion The most important task for online pharmacies is to improve logistics. It is better to develop self-built logistics. Both types of B2C online pharmacies can improve consumer viscosity by implementing marketing strategies. With regard to customer service, focusing on improving employees' service attitudes is necessary.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
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