Publication activity
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
Research across participating journals · All insights follow your collection filters.
Publication activity alongside incoming citations.
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Leading affiliations and themes in this collection.
Full distributions & methodology ↓Independent sources. Clear time scales.
Crossref and OpenAlex · separate totals for the same publication cohorts
Hover over a year or focus the chart and use arrow keys to inspect values.
Latest lifetime totals, grouped by the cited article’s year. These are not citations received in that year.
OpenAlex · incoming citation links grouped by citing-work year
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.
Articles by publication year
Latest lifetime totals · grouped by publication year
Latest lifetime totals · grouped by publication year
By year of the citing work · 2017–2026
2026 is year to date. Crossref and OpenAlex lifetime charts share a citation scale. Unknown observations appear as gaps; known zero stays zero. Annual receipts use available OpenAlex histories and may not sum to lifetime totals. 0 undated publications excluded from publication-year charts.
Crossref citation coverage: 8 / 8 publications (100.0%). Latest observation: 21 Oct 2026, 00:14 UTC. Means and percentages use records with known counts.
DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.
Observation range: 21 Oct 2026 00:14 UTC — 21 Oct 2026 00:14 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.
OpenAlex affiliations and primary-topic classification. Each publication counts once per institution or country; multi-affiliated publications appear in multiple groups, so percentages can sum above 100%. Countries describe author affiliations, not nationality. Topics use one primary topic per publication.
8 / 8 with data · 0 missing or unmatched. Percentages use all 8 selected publications.
8 / 8 with data · 0 missing or unmatched. Percentages use all 8 selected publications.
8 / 8 with data · 0 missing or unmatched. Percentages use all 8 selected publications.
Citations are the latest recorded totals for articles published in each year, not citations received during that year. Crossref and OpenAlex remain separate and share the same citation scale. 2026 is incomplete; newer articles have had less time to receive citations.
0 undated publications excluded. Unknown citation counts are shown as —, never as zero. Partial coverage can understate totals; expand each table for known / total records.
| Publication year | Journal / scope | Publications | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 15 | 3 | 3/3 | 3/3 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 23 | 3 | 3/3 | 3/3 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 2 | 2/2 | 2/2 |
Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.
The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.
Annual history available for 8 / 8 selected publications. Supported display window: 2017–2026; 2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Missing histories and years beyond a saved observation’s window remain unknown (—); partial coverage can understate totals.
Annual-history observations (UTC): 2026-10-21T00:14:27.759247+00:00 — 2026-10-21T00:14:35.686791+00:00. Older observations may be retained after failed or incomplete refreshes.
| Citation year | Journal / scope | OpenAlex · Citations received by year | Publications | Annual history known |
|---|---|---|---|---|
| 2017 | All selected publications | 0 | 8 | 8/8 |
| 2018 | All selected publications | 0 | 8 | 8/8 |
| 2019 | All selected publications | 0 | 8 | 8/8 |
| 2020 | All selected publications | 0 | 8 | 8/8 |
| 2021 | All selected publications | 0 | 8 | 8/8 |
| 2022 | All selected publications | 1 | 8 | 8/8 |
| 2023 | All selected publications | 5 | 8 | 8/8 |
| 2024 | All selected publications | 10 | 8 | 8/8 |
| 2025 | All selected publications | 6 | 8 | 8/8 |
| 2026 | All selected publications | 4 | 8 | 8/8 |
Counts represent citation links, not unique citing papers across a journal: one paper citing two selected articles contributes two links. Older citations outside this window are excluded, so annual sums need not equal lifetime totals. OpenAlex methodology ↗
Publications by publication year. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2021 | 1 |
| 2022 | 3 |
| 2024 | 1 |
| 2025 | 1 |
| 2026 | 2 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 8 | 17 | 26 | 8/8 | 2.12 | 0.5 | 50.0 | 8/8 · 100.0% |
* Percentage among publications with a known citation count.
Prior studies in Bangladesh examined how several non-demographic factors influenced consumers' online buying behavior. However, no specific research has been conducted to examine an association between consumers' demographic factors and the online shopping behavior of Bangladeshi buyers. Therefore, this study aimed to examine the association between online shopping behavior and the demographic characteristics of Bangladeshi buyers. The association between six consumers' demographic variables, such as age, gender, income, education, occupation, and marital status, and online shopping behavior, proxied by the frequency of online shopping, was examined. Primary data through a structured questionnaire was collected from the 547 respondents in urban and rural areas of seven divisions in Bangladesh through offline and online surveys. The chi-square test was used to examine the association between consumers' demographic characteristics and online shopping behavior. The study found that male and married consumers with a higher level of education and higher-category jobs have a higher propensity to shop online. However, consumers' age and income level do not significantly impact their online shopping behavior. The study's outcomes are expected to provide online retailers and merchants with critical information about buyer behavior. Keywords: Association, online shopping behavior, demographic characteristics, chi-square test, Cramér’s V, e-commerce. JEL Classification: M31, M39, and L81
This study aims to analyze and find out the effect of flash sales on purchase decisions moderated by product knowledge. This study is survey research with a questionnaire as the data collection tool. The population in this study is the Shopee marketplace users in Yogyakarta. The data used in this study are primary data obtained from the answers of 190 respondents with a purposive sampling method. The data analysis technique used in this study is Moderated Regression Analysis (MRA). The results of this study conclude that: (i) Flash sale has a positive and significant effect on purchase decision; I(i) Product knowledge is able to moderate the effect of a flash sale on purchase decision and has a positive and significant effect.
The aim of this study is to evaluate the convenience, promotion, and security factors associated with the use of Shopee Pay electronic currency by visitors in malls in the Central Jakarta region. The study sample comprises persons who frequent shopping malls in the Central Jakarta Region. This survey includes a group of 103 persons who use Shopee Pay electronic money in the mall area of Centra Jakarta. The sample selection was carried out using the method of incidental sampling. The data used in this study include primary data, especially questionnaires that were distributed to respondents. The study results suggest that the convenience and promotional activities have a positive influence on the decision to use Shopee Pay digital currency. This suggests that the choice to utilise electronic currency is impacted by factors such as convenience and promotional offers. Before proceeding, consumers will evaluate whether a system would streamline their activities, considering the wide array of attractive offers offered by the shopeepay site, as well as compelling marketing about available specials on the platform. Furthermore, security concerns negatively affect the willingness to use Shopee Pay as a digital payment option. This text explores the relationship between security and the choice to use electronic money. Before choosing the Electronic Money platform, customers must ensure that the funds saved in the electronic wallet will be protected and resistant to unauthorised access, therefore reducing the likelihood of unwanted events.
The development of the coffee industry in Indonesia is growing significantly, as it is driven by the number of coffee shops that are developing both in villages to urban areas as a balancer for people's lifestyles who like to drink coffee while enjoying activities outside the home. This phenomenon makes the level of competition for coffee brands in packaging very hypercompetitive. Consumer intentions in deciding to buy packaged coffee are strongly influenced by the perception of the quality of the coffee, so it is not surprising that currently there are many different flavors and brands. To market coffee products, many producers use celebrity endorsement services. However, as time goes by and the marketing strategy through endorsement has become massive, it is necessary to study whether this strategy is still effective in increasing the number of sales. It turns out that currently, endorsements do not really affect consumer purchasing decisions. From the results of the study, it can be concluded that: (1) perceived quality influences the intention to purchase packaged coffee, and perceived quality also influences brand loyalty in packaged coffee; (2) celebrity endorsement does not influence the intention to purchase packaged coffee, but celebrity endorsement influences the brand loyalty; and (3) brand loyalty influences the intention to purchase packaged coffee. So that in general brand loyalty is able to mediate the influence of perceived quality and celebrity endorsement on the intention to purchase packaged coffee.
This study investigated the factors influencing consumer repurchase intentions of beauty and haircare products on e-commerce platforms in South Africa. With the growing trend of online shopping, understanding the determinants of repurchase intention became essential for businesses looking to retain customers. The purpose of the study was to explore how various factors such as brand trust, security risk perception, ease of use, customer readiness, and loyalty impact consumer repurchase behaviour. A quantitative research design was employed, using an online questionnaire to collect data from 164 respondents who had previously purchased beauty and haircare products on an online shopping site for cosmetics in South Africa. The study utilised multiple regression analysis to assess the relationships among the identified factors and their influence on repurchase intentions. The findings revealed that brand trust, ease of use, and customer loyalty were significant positive predictors of repurchase intentions, while security risk perception had a negative impact. Readiness did not show a significant relationship with repurchase intentions. Based on these results, the study recommends that e-commerce businesses in the beauty sector focus on building trust, enhancing user-friendly interfaces, and fostering customer loyalty programs to encourage repeat purchases.
This study investigated the factors influencing consumer repurchase intentions of beauty and haircare products on e-commerce platforms in South Africa. With the growing trend of online shopping, understanding the determinants of repurchase intention became essential for businesses looking to retain customers. The purpose of the study was to explore how various factors such as brand trust, security risk perception, ease of use, customer readiness, and loyalty impact consumer repurchase behaviour. A quantitative research design was employed, using an online questionnaire to collect data from 164 respondents who had previously purchased beauty and haircare products on an online shopping site for cosmetics in South Africa. The study utilised multiple regression analysis to assess the relationships among the identified factors and their influence on repurchase intentions. The findings revealed that brand trust, ease of use, and customer loyalty were significant positive predictors of repurchase intentions, while security risk perception had a negative impact. Readiness did not show a significant relationship with repurchase intentions. Based on these results, the study recommends that e-commerce businesses in the beauty sector focus on building trust, enhancing user-friendly interfaces, and fostering customer loyalty programs to encourage repeat purchases.
This study provides a comprehensive analysis of the marketing mix strategies that influence customer acquisition at Spar in Durban. Utilizing a quantitative methodology, data were collected through structured questionnaires completed by 278 respondents. The findings indicate that Spar effectively employs digital marketing tools—including social media, WhatsApp, and loyalty programs—as key communication channels to engage customers. Reliability analysis confirmed the validity of the measurement instrument (Cronbach’s ? = 0.902; KMO = 0.899). The results demonstrate that younger consumers are more responsive to digital platforms, particularly social media and loyalty programs, while traditional methods such as printed flyers are less effective. No significant differences were observed in the perceived effectiveness of specific digital channels across different respondent groups, suggesting a consistent perception of Spar’s digital engagement. The study emphasizes the importance of integrating digital strategies with factors such as pricing, convenience, and product assortment to enhance customer acquisition in Durban’s competitive retail environment.
In the face of heightened global competition, micro and small enterprises (MSEs) in Durban, South Africa, face challenges such as limited resources and restricted market access, which hinder their ability to achieve sustained growth and profitability. This study aims to examine the influence of the 4Ps marketing mix on the performance of MSEs. A cross-sectional, descriptive study with a quantitative research design was employed. Data was collected from 217 MSEs using structured questionnaires, and the analysis was conducted with SPSS 29. Multiple regression analysis was used to examine the relationship between the 4Ps (product, price, promotion, place) and MSEs' performance. The findings show that pricing decisions are a significant determinant of performance, while product diversity does not necessarily enhance business outcomes, emphasizing the importance of strategic product management. Promotional efforts, while positive, were statistically insignificant, indicating complexities in their impact. The relationship between physical location (place) and performance was weak, suggesting a need for MSEs to optimise distribution channels through omnichannel strategies. In conclusion, MSEs can improve performance by refining promotional strategies, leveraging pricing and optimising distribution networks. Further research is suggested to explore the generalizability of these findings across different industries and additional factors influencing marketing strategies.
The aim of this study is to evaluate the convenience, promotion, and security factors associated with the use of Shopee Pay electronic currency by visitors in malls in the Central Jakarta region. The study sample comprises persons who frequent shopping malls in the Central Jakarta Region. This survey includes a group of 103 persons who use Shopee Pay electronic money in the mall area of Centra Jakarta. The sample selection was carried out using the method of incidental sampling. The data used in this study include primary data, especially questionnaires that were distributed to respondents. The study results suggest that the convenience and promotional activities have a positive influence on the decision to use Shopee Pay digital currency. This suggests that the choice to utilise electronic currency is impacted by factors such as convenience and promotional offers. Before proceeding, consumers will evaluate whether a system would streamline their activities, considering the wide array of attractive offers offered by the shopeepay site, as well as compelling marketing about available specials on the platform. Furthermore, security concerns negatively affect the willingness to use Shopee Pay as a digital payment option. This text explores the relationship between security and the choice to use electronic money. Before choosing the Electronic Money platform, customers must ensure that the funds saved in the electronic wallet will be protected and resistant to unauthorised access, therefore reducing the likelihood of unwanted events.
Prior studies in Bangladesh examined how several non-demographic factors influenced consumers' online buying behavior. However, no specific research has been conducted to examine an association between consumers' demographic factors and the online shopping behavior of Bangladeshi buyers. Therefore, this study aimed to examine the association between online shopping behavior and the demographic characteristics of Bangladeshi buyers. The association between six consumers' demographic variables, such as age, gender, income, education, occupation, and marital status, and online shopping behavior, proxied by the frequency of online shopping, was examined. Primary data through a structured questionnaire was collected from the 547 respondents in urban and rural areas of seven divisions in Bangladesh through offline and online surveys. The chi-square test was used to examine the association between consumers' demographic characteristics and online shopping behavior. The study found that male and married consumers with a higher level of education and higher-category jobs have a higher propensity to shop online. However, consumers' age and income level do not significantly impact their online shopping behavior. The study's outcomes are expected to provide online retailers and merchants with critical information about buyer behavior. Keywords: Association, online shopping behavior, demographic characteristics, chi-square test, Cramér’s V, e-commerce. JEL Classification: M31, M39, and L81
Source coverage refers to this result set; a publication may occur in several sources. Sync times refer to contributing journals.
Missing abstracts: 0 · Missing authors: 0 · Missing publication dates: 0 · Dates without day precision: 0
| Source | Most recent successful journal sync | Latest attempt |
|---|---|---|
| crossref | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |
| ojs-rest | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:02 UTC |
| oai-pmh | 20 Oct 2026 19:49 UTC · ijbes | complete · ijbes · 20 Oct 2026 19:48 UTC |
| openalex-enrichment | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |