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: 76 / 76 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 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 07:23 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.
73 / 76 with data · 3 missing or unmatched. Percentages use all 76 selected publications.
73 / 76 with data · 3 missing or unmatched. Percentages use all 76 selected publications.
76 / 76 with data · 0 missing or unmatched. Percentages use all 76 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 |
|---|---|---|---|---|---|
| 2016 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2018 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 8 | 8 | 8/8 | 8/8 |
| 2020 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2021 | All selected publications | 8 | 8 | 8/8 | 8/8 |
| 2022 | All selected publications | 19 | 19 | 19/19 | 19/19 |
| 2023 | All selected publications | 13 | 13 | 13/13 | 13/13 |
| 2024 | All selected publications | 10 | 10 | 10/10 | 10/10 |
| 2025 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2026 | All selected publications | 7 | 7 | 7/7 | 7/7 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2016 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 4 | 2 | 2/2 | 2/2 |
| 2018 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 54 | 8 | 8/8 | 8/8 |
| 2020 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2021 | All selected publications | 38 | 8 | 8/8 | 8/8 |
| 2022 | All selected publications | 33 | 19 | 19/19 | 19/19 |
| 2023 | All selected publications | 37 | 13 | 13/13 | 13/13 |
| 2024 | All selected publications | 16 | 10 | 10/10 | 10/10 |
| 2025 | All selected publications | 4 | 3 | 3/3 | 3/3 |
| 2026 | All selected publications | 0 | 7 | 7/7 | 7/7 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2016 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 11 | 2 | 2/2 | 2/2 |
| 2018 | All selected publications | 9 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 125 | 8 | 8/8 | 8/8 |
| 2020 | All selected publications | 11 | 4 | 4/4 | 4/4 |
| 2021 | All selected publications | 78 | 8 | 8/8 | 8/8 |
| 2022 | All selected publications | 62 | 19 | 19/19 | 19/19 |
| 2023 | All selected publications | 50 | 13 | 13/13 | 13/13 |
| 2024 | All selected publications | 17 | 10 | 10/10 | 10/10 |
| 2025 | All selected publications | 4 | 3 | 3/3 | 3/3 |
| 2026 | All selected publications | 0 | 7 | 7/7 | 7/7 |
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 76 / 76 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): 2026-10-21T00:14:27.789096+00:00 — 2026-10-21T07:23:09.647639+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 | 1 | 76 | 76/76 |
| 2018 | All selected publications | 0 | 76 | 76/76 |
| 2019 | All selected publications | 5 | 76 | 76/76 |
| 2020 | All selected publications | 2 | 76 | 76/76 |
| 2021 | All selected publications | 20 | 76 | 76/76 |
| 2022 | All selected publications | 30 | 76 | 76/76 |
| 2023 | All selected publications | 79 | 76 | 76/76 |
| 2024 | All selected publications | 114 | 76 | 76/76 |
| 2025 | All selected publications | 78 | 76 | 76/76 |
| 2026 | All selected publications | 38 | 76 | 76/76 |
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 |
|---|---|
| 2016 | 1 |
| 2017 | 2 |
| 2018 | 1 |
| 2019 | 8 |
| 2020 | 4 |
| 2021 | 8 |
| 2022 | 19 |
| 2023 | 13 |
| 2024 | 10 |
| 2025 | 3 |
| 2026 | 7 |
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 | 10 | 15 | 20 | 10/10 | 1.5 | 0.0 | 40.0 | 10/10 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 3 | 3 | 8 | 3/3 | 1.0 | 1 | 66.7 | 3/3 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 63 | 175 | 339 | 63/63 | 2.78 | 2 | 71.4 | 63/63 · 100.0% |
* Percentage among publications with a known citation count.
The aim of this research is to examine the effect of the customer loyalty program on customer satisfaction and its impact on customer loyalty. This program is developed by the company in order to increase customer satisfaction. Optimal customer satisfaction will be able to create customer loyalty. For a company, customer loyalty will guarantee the company’s income to be constantly optimal. The research is conducted using the survey method involving 110 customers and 100 feasible data used. The sampling technique used is judgment sampling and data collected through the questionnaire. It uses SEM in examining hypotheses assisted by software AMOS version 20.0. Member card significantly affects customer satisfaction, while discount promo has no significant effect on customer satisfaction and it also doesn’t affect customer loyalty. Member cards and discount promo have a direct effect on customer loyalty. In general, it can be understood that the customer loyalty program applied by Alfamart either member card or discount promo affects customer satisfaction and has an impact on customer loyalty. This research gives input to retail business managers in managing customer satisfaction through the proper development of customer loyalty programs.
Pakistan is experiencing an enormous increase in the acceptance of western apparel shopping among people. To bind this opportunity, it is necessary to understand ensure the repurchase intention among customers. Hence this research article explored the impact of Service and Product related attributes on Re-purchase Intention: Role of customer characteristics and customer satisfaction in an apparel shopping context. The importance of product attributes and service attributes to the result of repurchase intention has been well documented. In the past, scarce studies will be done to check this relationship. The theoretical repurchase model was developed and tested using SEM on experiential data of 350 apparel brand customers. In Pakistan's scenario, the study's significance is that the clothing industry is becoming more frequent and increasingly focused on developing brands. Simultaneously, the Pakistan textile and clothing brands industry became more and more developed and strongly influenced the international market worldwide. The current research finding will enable marketers to realize the value of product and service attributes and depict the different factors of customer characteristics and customer satisfaction impact on repurchase intention for ensuring continuity among old customers. Furthermore, the current research will make a valuable addition to increasing repurchase intention literature for marketers.
The study's primary objective was to analyze the effectiveness of e-customer service platforms on customer satisfaction in commercial banks in Botswana, using ABSA bank as a case study. The secondary objectives were to assess the effectiveness of reliability, responsiveness, assurance, empathy and tangibles of e-customer service platforms on customer satisfaction at ABSA bank. A positivist research philosophy was adopted. A cross-sectional survey design was used to collect data and probability sampling was employed. Data were collected from 180 customers who use ABSA e-customer services platforms using a structured questionnaire with Likert-type questions. Reliability was assessed using Cronbach’s alpha (?). Data were analysed using descriptive statistics, which include mean and standard deviation. Regression and correlation were applied to test research hypotheses. Results indicate that reliability, responsiveness, assurance, empathy and tangibles of e-customer services platforms at ABSA are positively linked to customer satisfaction. ABSA Bank management is therefore recommended to focus on continuous improvement on customer experiences to satisfy customers. Thus, ABSA should ensure that its services are unique, unforgettable and memorable such that customers are satisfied and share the positive word of mouth about the benefits offered by the bank. ABSA should also consider customer experience and continuous improvement of digital banking platforms as tools that can be used to increase customer satisfaction and loyalty. It is recommended that future studies be carried out across other banks in Botswana and the African context as well.
The amount of e-wallet providers in Indonesia is so many, so there is intense competition between each e-wallet provider. The tighter competition for e-wallet, makes users not only loyal to one type of e-wallet and makes users switch brands or providers in using an e-wallet. This study aims to investigate the factors that influence e-service quality on e-loyalty mediated by e-trust and brand image. This research is categorized as explanatory research. Respondents in this study were users of the OVO e-wallet application in Malang City, determining the number of samples in this study using a purposive sampling technique with a sample of 200 respondents. The method of collecting data is using a questionnaire, the data is analyzed using PLS-SEM. The results showed that e-service quality had no significant effect on e-loyalty. E-service quality has a significant effect on e-trust, e-trust has a significant effect on e-loyalty. E-service quality has a significant effect on brand image, brand image has a significant effect on e-loyalty. E-trust and brand image can play a fully mediating role in the relationship between e-service quality and e-loyalty. OVO is expected to continue to maintain and increase e-trust because it is proven in this research that e-trust has the greatest influence on e-loyalty so that it can be a competitive advantage for OVO. Keywords: e-service quality, e-loyalty, e-trust, brand image.
The purpose of this study is to explain and analyze the effect of the e-servicescape dimension on perceived value and loyalty to e-commerce sites in Indonesia. The sampling technique used a non-probability sampling technique with a sample of 195 respondents who had shopped at e-commerce more than three times. Data collection is done by spreading the distribution through WhatsApp, Instagram, and Facebook. The research variables consist of aesthetic appeal, layout & functionality, and financial security as independent variables, perceived value as a mediator, and attitude and behavior loyalty variables as dependent variables. The study used AMOS 24 to analyze the data. The results of the study show that the three independent variables are only layout & functionality that have a positive and significant effect on consumers' perceived value perceptions, while the variables of aesthetic appeal and financial security harm perceived value. Furthermore, the perceived value variable has a positive and significant effect on attitude and behavior loyalty as well as attitude loyalty has a significant positive effect on behavioral loyalty. The implication of this research is to add literature and insight for e-commerce players in Indonesia to increase the aesthetic appeal of online stores and financial security so that consumers are loyal in attitude and behavior and that practices that can harm consumers and negatively impact e-commerce players do not occur. Research needs to do further research on the same object but with different results or different objects, such as electronic products or e-commerce bills.
This study aims to examine the effects of price discount and delivery service on purchase decision and their subsequent impact on customer satisfaction and customer loyalty within an urban franchise retail context. A quantitative approach was employed using a survey of 220 consumers of Indomaret Anggrek Rosliana Raya, West Jakarta. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that price discount has a significant but relatively weak effect on purchase decision, while delivery service demonstrates a stronger influence, highlighting the increasing importance of service convenience in urban retail environments. Furthermore, purchase decision has a substantial effect on customer satisfaction, which in turn strongly influences customer loyalty. The study also confirms a sequential mediation mechanism, where marketing stimuli influence customer loyalty indirectly through purchase decision and customer satisfaction. Unlike previous customer loyalty studies that predominantly examine the direct effects of marketing stimuli on satisfaction or loyalty, this study develops a sequential framework in which purchase decision functions as a cognitive mediator preceding customer satisfaction as an affective mediator. This model extends existing customer loyalty frameworks by demonstrating that loyalty emerges through a two-stage evaluation process rather than through isolated direct relationships.
This study explores how customer service influences consumer buying patterns among SMEs in East London, South Africa. SMEs are crucial to the local economy, yet many face challenges in retaining customers due to inconsistent service quality and limited resources. The research examines how service factors such as staff professionalism, communication, complaint handling, and responsiveness impact customer satisfaction, loyalty, and purchasing choices. Using the SERVQUAL model, Expectancy-Disconfirmation Theory, and Relationship Marketing Theory, a quantitative, cross-sectional survey was conducted. Data from 100 consumers who recently interacted with East London’s SMEs indicate that customer service is the top factor influencing purchasing decisions, surpassing price, product quality, and convenience. Friendly, helpful staff, strong after-sales support, and effective communication are key to fostering loyalty and repeat business. Although perceptions of service quality are generally positive, 25% of respondents expressed dissatisfaction due to delays, poor communication, and a lack of product knowledge. These issues underscore the need for targeted initiatives, including staff training, digital engagement, and loyalty programs. The study highlights the growing role of digital platforms in improving service delivery, especially for younger, tech-savvy consumers. Overall, the study recommends that SMEs should focus on regular training programs centered on customer engagement, product knowledge, and complaint handling. This will enhance service consistency and professionalism, leading to higher customer satisfaction and loyalty.
Customer service quality is still a major problem in Zimbabwe’s telecommunications sector. This study aimed to develop a framework to improve customer service in the sector. It focused on how network reliability, how quickly complaints are resolved, staff skills and empathy, and customer involvement in service improvement affect customer satisfaction. Customers often face network failures, slow responses to complaints, and poor communication with service providers. These problems reduce customer satisfaction.: The study used data collected in Manicaland Province, Zimbabwe. A convergent parallel mixed-methods approach was used. Quantitative data were collected from a random sample of 220 customers, while qualitative data were collected from 13 purposively selected participants, including managers and frontline customer service staff. Data analysis was conducted using SPSS AMOS version 23 and thematic analysis. The results showed that network reliability had a strong and positive effect on customer satisfaction. Staff competence and empathy also had a significant positive effect on customer satisfaction, showing that skilled, respectful, and caring staff improve customers’ experiences. In contrast, complaint-resolution efficiency did not have a significant effect on customer satisfaction. The analysis further showed that value co-creation partially mediated the relationship between network reliability and customer satisfaction, as well as between staff competence and customer satisfaction. The study recommended that regulators such as Postal and Telecommunications Regulatory Authority of Zimbabwe (POTRAZ) enforce service quality standards, and that policymakers support digital inclusion and innovation. The study contributes that customer satisfaction can be improved by upgrading network infrastructure, providing ongoing staff training, empowering frontline employees, and creating formal ways to engage customers.
In the competitive business environment, organisations are increasingly adopting Customer Relationship Management (CRM) strategies to strengthen customer retention and improve service delivery. This study explored CRM as a strategic tool for customer retention at a selected Information Communication Technology (ICT) company based in Johannesburg, South Africa. A quantitative research approach was employed, targeting 121 employees across sales, marketing, business development, logistics, and finance departments. These employees were selected due to their direct engagement with customers. Data were collected through structured online questionnaires and analysed using the Statistical Package for the Social Sciences (SPSS) version 26. Descriptive and inferential statistical techniques, including Pearson’s correlation and regression analysis, were applied to evaluate the relationship between CRM and customer retention. The findings revealed a moderate but significant positive correlation between CRM and customer retention, indicating that strategic CRM practices contribute to stronger customer loyalty. The research concludes that CRM is a critical organisational strategy that can enhance customer retention if properly integrated and supported across business functions. It recommends further investment in CRM systems, employee training, and customer engagement initiatives to sustain competitive advantage and long-term growth.
The continued increase in food demand globally, has witnessed a corresponding growth in the fast-food restaurant business. The study of food and service quality as major drivers of customer satisfaction and behavioural intention has therefore become a strategic area of interest. This study explored how food and service quality affect customer satisfaction and behavioural intention in the context of quick-service restaurants in Tshwane City of South Africa. Guided by a positivist philosophy, the study employed a deductive approach to theory development. A cross-sectional descriptive research design was adopted and a structured survey instrument was used to collect data from 173 online participants. The results were analysed using IBM SPSS 26, and partial least squares structural equation modelling in Smart PLS 4 to test hypotheses. The findings showed that although food quality had a significant positive effect on behavioural intention, it was not a predictor of customer satisfaction. All the elements of service quality exhibited significant positive influence on satisfaction and behavioural intention. This study offers invaluable insights for managers to embrace customer-driven strategies such as offering high quality food and service because the success of culinary business revolves around achieving customer satisfaction, which is vital for creating positive behavioural intentions. Future studies can be done using relatively larger sample sizes for more generalisability in related studies or other service domains.
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 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |
| ojs-rest | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 06:46 UTC |
| oai-pmh | 20 Oct 2026 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |