75 | International JournalofofInformatics Informatics Information System Computer Engineering .
International Journal Information System Computer Engineering 4.
International Journal of Informatics.
Information System and Computer Engineering A Computational Bibliometric Analysis of E-Groceries Analysis Using VOSviewer Rudhi Lesmana*.
M Ihsan Rifaldi Departemen Manajemen.
Universitas Komputer Indonesia.
Indonesia *Corresponding Email: Rudhi.
21221230@mahasiswa.
ABSTRACTS
ARTICLE INFO
Article History:
The purpose of the research is to combine mapping analysis with VOSviewer as well as Publish or Perish software to do a computerized bibliometric analysis of the topic "E-Groceries Analysis.
" The method used descriptive-quantitative approach in conjunction with bibliometric analysis in which the data were retrieved from Google Scholar.
Based on the results.
E-Groceries Analysis research decreases every year, proven by the fact that 2018 have 25 articles and increased to 32 articles in 2019, 49 articles in 2020, and 98 articles in 2021.
Based on further findings of this research, it can be concluded that there are several understudied sectors in EGroceries Analysis that may be examined further to increase the efficacy of E-Groceries analysis.
This research is also anticipated to serve as a reference for future research in defining and assessing the research subject, as well as a reference for field to be studied in E-Groceries analysis.
DOI: https://doi.
org/10.
34010/injiiscom.
p-ISSN 2810-0670 e-ISSN 2775-5584
Submitted/Received 01 Oct 2022
First Revised 15 Jan 2023
Accepted 03 Mar 2023
First Available Online 14 Apr 2023
Publication Date 01 Jun 2023
Aug 2018
__________________
Keywords:
Bibliometrics.
E-Groceries Analysis.
Data Analysis.
VOSviewer Rudhi & M.
Ihsan.
A Computational Bibliometric Analysis of E-Groceries.
| 76
INTRODUCTION
The customary sequences that were once employed when completing daily tasks, including shopping, have been disturbed and re-combined, both in time and place, as a result of the Internet today (Couclelis.
Online shopping does certainly allow customers to buy goods or services from a seller over the Internet, fundamentally changing the procedures involved in information gathering, comparison, and use, as well as purchase and delivery.
People who use e-commerce can purchase products using their mobile devices while, for instance, traveling to work or waiting at the train station without having to adhere to the store's precise opening and closing hours.
Consumer behavior is significantly altered by the evolution of shopping, and this behavior is closely related to transportation (Suel.
, & Polak.
With grocery shopping being the most popular and regular form of retail therapy, it has a particularly negative impact on the environment and urban However, depending on customer behaviour and last mile delivery strategies, switching from in-store to online purchasing can have both good and bad effects on In greater detail, it is evident that when customers order groceries online and want home delivery, the burden of the freight travels is transferred from the customer to the Instead, the final effect on urban freight transportation is unpredictable because it relies on the kind of product, how often people shop, why they purchase, whether trips are chained together, and how DOI: https://doi.
org/10.
34010/injiiscom.
p-ISSN 2810-0670 e-ISSN 2775-5584 quickly efficiency must be achieved (Mokhtarian.
Therefore, this study aims to conduct a bibliometric analysis on the topic of purchasing decisions in using the EGroceries service.
This method uses a mixed method with a literature review.
Publish or Perish to collect data and Vosviewer to visualize the relationship between terms as well as other things such as research trends throughout the It is hoped that this research will contribute to finding the fields proposed in the topic of E-Groceries Analysis.
EGroceries analysis is a business model that applies information technology to establish communication relationships and conduct transactions with customers products, services and distribution systems through internet media (Muhammad.
, et al 2.
Previous study regarding E-Groceries analysis have been conducted.
Ayudhia et al.
conducted a study regarding EGroceries analysis of business model.
Pico and Barcelo also conducted a study regarding E-Groceries study, which focuses on organic matter and According to Pico and Barcelo.
Py-GC-MS is a valuable technique for E-Groceries analysis specially to cover crucial E-Groceries aspects (Pico.
, & Barcelo.
Besides, plenty of bibliometric analysis research on various fields, such as Computer Science (Al Husaeni.
, &
Nandiyanto.
Educational Research (Al Husaeni.
, et al 2.
High school (Al Husaeni.
, &
Nandiyanto.
TechnoEconomic Education (Ragadhita.
, &
Nandiyanto.
Materials Research (Nandiyanto.
, et al 2.
Vocational School (Al Husaeni.
77 | International Journal of Informatics Information System and Computer Engineering 4.
75-88 , & Nandiyanto.
Digital Learning (Al Husaeni.
, &
Nandiyanto.
Scientific Publications (Mulyawati.
, &
Ramadhan.
Bioenergy Management (Soegoto.
, et al.
, 2.
Chemical Engineering (Nandiyanto.
et al 2.
Special Needs Education (Al Husaeni.
, et al.
, 2.
, and Covid-19 (Hamidah.
Sriyono.
, & Hudha.
However, there have not been a bibliometric analysis regarding EGroceries analysis.
Therefore, this research aims to conduct a bibliometric analysis on the topic of EGroceries analysis.
The method used mixed method with literature review.
Publish or Perish 8 to gather the data and Vosviewer to visualize the connection between terms as well as other things such as research trend along the year.
It is hoped that this research would contribute to discover the understudied fields in the topic of E-Groceries Analysis.
METHOD
Descriptive-quantitative were applied in this study.
In addition.
Literature review were conducted to gain insights based on previous researches on Bibliometric analysis as well as the topic of E-Groceries analysis.
We collected the articles from journals indexed by Google Scholar, due to its accessibility.
Publish or perish was chosen to gather the bibliometric data from Google Scholar (Al Husaeni.
, & Nandiyanto.
Then, the bibliometric data were saved in *.
ris, and *.
csv format to be used in VOSviewer software and to be converted into *.
xlsx to be analyzed The software version that is used DOI: https://doi.
org/10.
34010/injiiscom.
p-ISSN 2810-0670 e-ISSN 2775-5584 in this research is Publish or Perish 8 and VOSviewer 1.
In this research, we sifted through facts and used relevant facts to make arguments under the topic E-Groceries Analysis.
We retrieve the data from Google Scholar by entering the keyword "E-Groceries Analysis" for to the title, keyword, and abstract requirements in the Publish or Perish software.
obtained 993 articles on E-Groceries Analysis research published between 2017 and 2021.
The collected articles are then saved in *.
ris format to be visualized in VOSviewer software in the form of visualization map, and to analyze the research trend in the form of bibliometric Before creating the map, irrelevant terms were filtered in the visualization map (Allan.
, et al.
, 1.
The visualization map is classified into three types: Network visualization.
Overlay visualization, and Density visualization.
RESULTS AND DISCUSSION
Research developments in the field of E-Groceries Analysis Research on climate development in the field of E-Groceries Analysis.
Describes the development of research in the field of E-Groceries Analysis from 2018 to 2021 in Fig.
Figure 1 shows that the research on EGroceries Analysis decreases every year.
This can be proven by the fact that there are 25 articles in 2018, 32 articles in 2019, 49 articles in 2020, and lastly 98 articles in Based on the search results in the Publish or Perish, there are 263 articles that match the research topic.
16 articles with the most citations from 16 different publishers were shown in Table 1.
Rudhi & M.
Ihsan.
A Computational Bibliometric Analysis of E-Groceries.
| 78
Fig.
Level of research development on E-Groceries Analysis Table 1.
Article Data in the Field of E-Groceries Analysis Authors OA E-groceries:
Wiley Hjelkre Sustainable last Online , et al.
mile distribution Library in city planning C Fikar Ekren.
et al.
Title Publisher decision westminst support system erresearch.
investigate westminst food losses in eer.
Lateral inventory sharebased for IoT-enabled E-commerce sustainable food Year Cites (Bjyrgen, , et al.
(Fikar.
University of Jaffna DOI: https://doi.
org/10.
34010/injiiscom.
p-ISSN 2810-0670 e-ISSN 2775-5584 Refs (Ekren.
, et al.
79 | International Journal of Informatics Information System and Computer Engineering 4.
75-88 Table 1 (Continu.
Article Data in the Field of E-Groceries Analysis Authors Title Publisher Logistieke Thommi uitdagingen e-groceries Fernand Vazque zNoguer Modeling and optimization of the supply chain in e-groceries M Mees.
E-groceries: The Effects Simulated Sensory Information and Freshness Guarantee Information on Consumer Uncertainty.
Berggre , & S Wikstry Barriers Online:
Exploring Consumers' Resistance to Egroceries DOI: https://doi.
org/10.
34010/injiiscom.
p-ISSN 2810-0670 e-ISSN 2775-5584 Refs (Thommis, (Mees.
Modeling and thesis.
optimization of the supply chain in e-groceries Cites (Fernande z V.
AI Pujol Digital nudging turcomat.
behaviours in egroceries MFV Noguer Year (Berggren.
Wikstrym, (Pujol.
(Noguerol.
Rudhi & M.
Ihsan.
A Computational Bibliometric Analysis of E-Groceries.
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Table 1 (Continu.
Article Data in the Field of E-Groceries Analysis Authors Title Publisher Meijboo
Waste reduction e-groceries center: A case
study at Picnic
Gunawa
& PIN
Fernand Does Customer tesi.
Trust Mediate the Impact of eService Quality Dimensions? Lessons during COVID-19
Pandemic Gunawa
& PIN
Fernand Does customer iopscience.
trust impact on e-service quality during covid-19
Gunawa
& PIN
Fernand Assessing the Cambridge Mediation Role University of the Customer Press Trust On EService Quality:
Lessons During Covid-19 Pandemic KUSNA DI.
, & G
PAN
Developing sneonline business journal.
with university DOI: https://doi.
org/10.
34010/injiiscom.
p-ISSN 2810-0670 e-ISSN 2775-5584 Year Cites Refs (Meijboom .
(Gunawar dana.
Fernando, (Gunawar dana.
Fernando, (Gunawar dana.
Fernando, (Kusnadi, , & PAN, 81 | International Journal of Informatics Information System and Computer Engineering 4.
75-88 Table 1 (Continu.
Article Data in the Field of E-Groceries Analysis Authors Title Echrler.
et al.
Challenges and sljmuok.
perspectives for electric vehicles for last mile ecommerceAe Findings from case studies in Germany Waitz.
et al.
support system for efficient lastmile distribution of fresh fruits and vegetables as part of egrocery Publisher Year Cites (Ehrler.
, et al.
In Table 1 there are 16 articles that match the criteria research.
Of the 16 selected articles, showing that highest quote related to E-Groceries Analysis research is 255, while with the lowest citation is 13.
That in Table 1, it shows that in 2018 and 2021, each has articles with quotes In 2018-2021, the most articles quoted is 255 articles.
Temporary that, in 2018, a lot of articles quoted are 63 Year with quote the most is in 2021 as many as 255 articles.
Visualization E-Groceries Analysis topic area using VOSviewer Visualization map of E-Groceries Analysis topic was created using VOSviewer software.
According to Al Husaeni and Nandiyanto, two terms set DOI: https://doi.
org/10.
34010/injiiscom.
p-ISSN 2810-0670 e-ISSN 2775-5584 Refs (Waitz.
Mild.
, &
Fikar, relationships when creating map using VOSviewer software (Peters.
The generated map has 10 items .
with a total of 3 clusters, 18 links, and total link strength of 166 (See Fig.
Cluster 1 is indicated by red.
Cluster 2 is shown in green.
Cluster 3 is shown in dark blue.
Figure 2 is the Network Visualization map generated by VOSviewer based on the terms present in collected data.
The collected articles have a total of 10 terms .
n the form of item.
and were categorized into 3 clusters.
In addition, it has the total link strength of 166 and total links of 18.
The item categorization is determined based on the connection Rudhi & M.
Ihsan.
A Computational Bibliometric Analysis of E-Groceries.
| 82
strength of the terms with each other, further detail of each cluster is shown in Figs.
3 - 7.
Items on each cluster are as .
Cluster 1 .
Cluster 2 .
Feature.
Main Content Skip.
Skip .
Cluster 3 .
Covid.
Pandemic.
Role Customer.
E-Grocery.
Home delivery.
Supply chain Fig.
Network Visualization map of E-Groceries Analysis Fig.
Cluster 1 Visualization E-Groceries Analysis Network.
DOI: https://doi.
org/10.
34010/injiiscom.
p-ISSN 2810-0670 e-ISSN 2775-5584 83 | International Journal of Informatics Information System and Computer Engineering 4.
75-88 The main node in Cluster 1 is the term AoEGroceriesAo, this node linked to several other nodes in cluster 1 namely.
Aosupply chainAo.
AocostumerAo, and Aohome deliveryAo.
In addition, it also linked to the nodes in the other cluster, such as The main node in Cluster 2 is the term.
EGroceries Feature, this node linked to several other nodes in cluster 2 namely.
AoskipAo, and AoMain content SkipAo.
addition, it also linked to the nodes in the other cluster, such as A 'supply chain', 'costumer', and 'home delivery' in Cluster 1 A 'supply chain', 'costumer', and 'home delivery' in Cluster 1 A 'Feature', 'Main Content Skip', and 'Skip' in Cluster 2 A 'Feature', 'Main Content Skip', and 'Skip' in Cluster 2 A 'Covid', 'Pandemic', and 'Role' in Cluster 3 A ' Covid', 'Pandemic', and 'Role' in Cluster 3 Fig.
Cluster 2 Visualization E-Groceries Analysis network.
DOI: https://doi.
org/10.
34010/injiiscom.
p-ISSN 2810-0670 e-ISSN 2775-5584 Rudhi & M.
Ihsan.
A Computational Bibliometric Analysis of E-Groceries.
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Fig 5.
Cluster 3 Visualization E-Groceries Analysis network.
Overlay Visualization map of EGroceries Analysis Density Visualization of E-Groceries Analysis Overlay Visualization map visualize the research trend of keywords in each year.
Different coloration indicates the year in which terms are commonly used.
Darker color indicates that the keyword is commonly appear on older years while bright color indicates that the keyword commonly appears on recent year.
Density Visualization aims to show the frequency of occurrence of terms in the collected data.
Color intensity and size is the primary indicator of density, so an item that have a large and bright coloration means that the keyword appears frequently in the collected data and vice versa.
The density visualization is shown in Fig.
In Fig.
6, the majority of keywords seems to be popular on older years.
However, there are recently emerging keywords in the collected data such as AocovidAo.
AoEGroceryAo.
AocustomerAo.
AofeatureAo.
These keywords can be linked to recent situations such as the Covid-19 pandemic and the effort to minimize carbon footprint and green energy development in the name of saving the environment.
DOI: https://doi.
org/10.
34010/injiiscom.
p-ISSN 2810-0670 e-ISSN 2775-5584 Visualization density about climate EGroceries Analysis research is in the picture above, which means that on the map density showing results analysis use all article regarding E-Groceries Analysis in 2018-2022.
In Fig.
7, it is depicted that there are some color terms that is there is color yellow with a fairly large diameter.
These terms called evidence.
E-Grocery, covud, customer, and feature.
85 | International Journal of Informatics Information System and Computer Engineering 4.
75-88 Fig.
Overlay E-Groceries Analysis visualization Fig.
Density Visualization map of E-Groceries Analysis CONCLUSION The conclusion in this study is that there are many topics that are poorly explored in the field of E-Groceries analysis for example, cluster 1 is "E-Groceriey".
Cluster 2 "feature".
Cluster 3 "covid".
It is hoped that this research will contribute to finding the field studied in the topic of EGroceries Analysis REFERENCES