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: 19 / 20 publications (95.0%). 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 07:22 UTC — 22 Oct 2026 19:36 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.
20 / 20 with data · 0 missing or unmatched. Percentages use all 20 selected publications.
20 / 20 with data · 0 missing or unmatched. Percentages use all 20 selected publications.
20 / 20 with data · 0 missing or unmatched. Percentages use all 20 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 |
|---|---|---|---|---|---|
| 2013 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2014 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| 2020 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 1 | 1 | 0/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 36 | 4 | 4/4 | 4/4 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 10 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 38 | 5 | 5/5 | 5/5 |
| 2020 | All selected publications | 7 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 25 | 4 | 4/4 | 4/4 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 3 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | — | 1 | 0/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 85 | 4 | 4/4 | 4/4 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 29 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 67 | 5 | 5/5 | 5/5 |
| 2020 | All selected publications | 9 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 47 | 4 | 4/4 | 4/4 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 1 | 0/1 | 1/1 |
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 20 / 20 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): 2026-10-21T07:22:50.550281+00:00 — 2026-10-22T19:36:25.583470+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 | 3 | 20 | 20/20 |
| 2018 | All selected publications | 9 | 20 | 20/20 |
| 2019 | All selected publications | 20 | 20 | 20/20 |
| 2020 | All selected publications | 15 | 20 | 20/20 |
| 2021 | All selected publications | 28 | 20 | 20/20 |
| 2022 | All selected publications | 43 | 20 | 20/20 |
| 2023 | All selected publications | 32 | 20 | 20/20 |
| 2024 | All selected publications | 32 | 20 | 20/20 |
| 2025 | All selected publications | 20 | 20 | 20/20 |
| 2026 | All selected publications | 11 | 20 | 20/20 |
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 |
|---|---|
| 2013 | 4 |
| 2017 | 1 |
| 2019 | 5 |
| 2020 | 2 |
| 2021 | 4 |
| 2023 | 2 |
| 2025 | 1 |
| 2026 | 1 |
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 Finance & Banking Studies SSBFNET | 4 | 23 | 41 | 4/4 | 7.67 | 4 | 100.0 | 3/4 · 75.0% |
| International Journal of Research in Business and Social Science SSBFNET | 16 | 97 | 199 | 16/16 | 6.06 | 4.5 | 87.5 | 16/16 · 100.0% |
* Percentage among publications with a known citation count.
In this research paper we investigated the determinants likely to influence the adoption of mobile banking services, with a special focus on under banked/unbanked low-income population of Pakistan. The adoption of mobile banking services has been a strategic goal, both for banks and telcos. For this purpose, Technology Acceptance Model (TAM) was used, with additional determinants of perceived risk and social influence. Data was collected by surveying 372 respondents from the two largest cities (Karachi and Hyderabad) of the province Sindh, in Pakistan using judgement sampling method. This study empirically concluded that consumers’ intention to adopt mobile banking services was significantly influenced by social influence, perceived risk, perceived usefulness, and perceived ease of use. The most significant positive impact was of social influence on consumers’ intention to adopt mobile banking services. The paper concluded with discussion on results, and several business implications for the banking industry of Pakistan.
The aim of the empirical study is to investigate credit risk determinants in banking sectors across three kinds of South Asian economies. An accumulated sample of 105 unbalanced panel data of financial firms over the period of 2000-2015, by applying General Method of Moment (GMM) estimation techniques one-step at the difference in order to identify factors influencing credit risk. This study is inspired by two broad categories of explanatory variables which are bank-specific and macroeconomic. Bank-specific factors influencing unsystematic risk, while macroeconomic factors promoting systematic risk. The study uses a proxy of non-performing loans for credit risk in banking sectors of Pakistan, India, and Bangladesh. The empirical results have been found aligned with theoretical arguments and literature as expected. In comparison, NPLs in Pakistan is greater than India and Bangladesh, while India has the lowest ratio of non-performing loans. The study documents that bank-specific factors (inefficiency, profitability, capital ratio and leverage) have a significant contribution towards credit risk. Further, the study also finds a significant impact of macroeconomic variables on non-performing loans. While, the result in the case of Bangladesh predicts contradictions that have no significant effect on non-performing loans at various levels. The overall results indicate that credit risk is not influenced by only external factors but also affect by internal factors like bad management and skimping etc.
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 key purpose of this research paper is to explore the moderating effect of Corporate Governance on the relationship between accounting base financial performance i.e. ROA, and ROE and Capital Structure of 173 Manufacturing firms listed in KSE of Pakistan for the period of 2009 to 2014. In this study multiple regression method is used under fixed effect regression model approach on panel data. The empirical results show that the inclusion of Corporate Governance Index (CGI) as moderating variable has influenced the interaction between Capital Structure and Financial Performance which was positively significant. The result is generally found that the most of Pakistani manufacturing listed firms pursue good corporate governance mechanism and use good and optimal level of Capital Mix to get the better and high financial performance. Furthermore, the corporate governance sub-indices i.e. board structure (BOD-I) and transparency & disclosure (DISC-III) both also have positive and statistically significant association with both firms performance variables: ROA and ROE. Moreover, the ownership structure sub-index (OWS-II) has not significant influence on financial performance. In last, the capital structure also has positive relationship with financial performance, interestingly about 70 per cent of Capital is financed by Equity capital and the Debt capital signifies 30 per cent only. The core significance of this paper is to investigate the impact of Corporate Governance practices on financial decisions from the Pakistani perspective.
The Covid-19 pandemic restricted the people around the world's boundaries. Therefore, online learning's importance increased in the current era, an essential topic for current research. Students are actively using Massive Open Online Courses (MOOCs) while restricted at their homes during the Covid-19 pandemic. This research investigates the Unified Theory of Acceptance and Use of Technology model (UTAUT) and quality factors to predict the users perceived satisfaction and reuse intentions toward MOOCs in the Covid-19 pandemic. We collected data from three public universities in Wuhan, China and 298 users who were actively using MOOCs participated in this research. The proposed hypotheses were tested by using PLS-SEM. The findings revealed that effort expectancy and social influence directly impacted users' reuse intentions while performance expectancy and perceived course quality positively impacted users' reuse intentions through perceived satisfaction toward MOOCs. This research found the critical role of perceived satisfaction in the current pandemic era. Finally, this research provides important theoretical implications for the researchers and practical implications for the developers, technologists, and policymakers for developing effective systems and strategies in online environments. In addition, this study revealed some limitations and future research guidelines for the researchers.
Studies on the impact of digitalisation on bank credit allocation are relatively scarce. Digital technologies have a significant impact on economic growth, the labour market, commodity and asset prices, and international trade. The recent surge in innovation and digitalisation within the financial sector has brought about tremendous changes in bank business models and credit distribution, significantly affecting economic growth. Digital transformation has led to a new banking business model of collaboration between emerging Fintechs and conventional commercial banks, often called a “partnership model”. Here, the banking system is viewed as the evolutionary outcome of monetary financial institutions, constantly adapting to technological change. This ongoing evolution has determined the pattern of credit allocation, ultimately shaping its effects on economic growth. Drawing upon authoritative primary data and sector-specific lending indicators, this study seeks to advance existing scholarly research regarding the impact of digital transformation on bank credit allocation. The contribution of this research stems from comparing the digital transformation of banking systems in the UK and Denmark and examining how digitalisation has led to divergent trajectories in bank credit allocation. The study explores credit allocation under the digital transformation of banking and its effect on overall economic growth. In this sense, bank credit allocation extends beyond traditional industrial firms to reach various other sectors of the economy. Specifically, this research demonstrates how technological advancements in the banking sector directly impact overall economic performance, drawing on empirical evidence from the UK and DK as selected case studies. Empirical evidence demonstrates that bank lending has prioritised credit for financial market trading and real estate mortgages at the expense of the productive sector. This is particularly evident in the ever-growing volume of lending directed toward already existing assets. The prevalence of non-productive credit effectively illustrates that the banking system is increasingly driving the financialisation of the economy.
Workplace stress and nurse retention are critical challenges in healthcare, affecting organizational stability and public health outcomes. Therefore, this study investigates the impact of stressors and job satisfaction on nurses’ turnover intentions in the western region of Ghana, with a focus on the moderating role of transformational leadership. Methodologically, a descriptive cross-sectional design was employed to collect data from 364 registered nurses working in four hospitals. Participants completed an online questionnaire measuring stress factors, job satisfaction, turnover intentions, and transformational leadership. Structural equation modelling was employed to analyze the data using Mplus 8.3. The results revealed stressors (stress from workload, superiors, and coworkers and daily life) significantly increased nurses’ turnover intentions while negatively influencing job satisfaction. Job satisfaction was inversely associated with turnover intentions, and transformational leadership moderated this relationship, reducing the likelihood of such intentions. The findings highlight the importance of fostering job satisfaction and implementing transformational leadership strategies, such as mentorship and effective stress management, to alleviate workplace stress and enhance nurse retention. These insights offer valuable guidance for hospital administrators and policymakers in designing interventions to improve nurse retention and overall organizational performance.
The overriding purpose of the study was to ascertain through empirical research whether Porter’s diamond firm strategy, structure and rivalry construct influence the key automotive industry of Pakistan. The Researchers applied positivism research philosophy to help generalize the research study outcomes. Descriptive analytics was deployed to help determine the significance, direction and magnitude of the study. Primary data was obtained from senior managers working in the industry by applying a structured questionnaire for subsequent analysis. While soliciting data, an 85.6% response rate was documented. Statistical techniques were applied which included parametric and nonparametric to arrive at objectively based results to draw safe conclusions. The research findings have created significant value for practitioners in the auto industry as well as the decision-makers at the helm of policy formulation. Pragmatic inferences to be drawn from the research findings include improving the performance of the automotive sector by internalizing Porter’s diamond construct firm strategy, structure, and rivalry. Results in other industries may be tested with future research to help establish generalizability in the area.
The prime purpose of the research was to examine, through empirical study, and help determine the government’s role as moderator in the relationship between Porter’s diamond firm strategy, structure, and rivalry construct and the firm’s performance in Pakistan’s automotive sector. In the study, the research philosophy was positivism, and a deductive approach was applied as the main reason to establish generalizations in the results. With a view to determining the magnitude, direction, and significance, researchers emphasized descriptive and inferential statistical techniques. Data was solicited from 166 sample respondents through a structured questionnaire. To establish the reliability perspective and validity context of the questionnaire constructs, a pilot study was part of the research study. Parametric and nonparametric statistical techniques also became an integral part of analysis for drawing objectively based conclusions. For moderation purposes, the tool was macro, Process v3.0 (model 1). The study findings aptly indicate that in a theoretical context, the relationship is not significant, whereas the practical perspective reflects that government policy does influence industry firms’ performance; however, the mediating role of government between Porter’s constructs, viz., firm strategy, structure, and rivalry, and industry firms’ performance documented no impact. In the constituencies of academia, automotive sector players, and policymakers, the moderation results shed light on theoretical and practical contextualization.
In this study, we review the literature to find how the financial development of a country attracts foreign direct investments for a sustainable real sector development of the country. The area is least focused on literature. Thus we don’t limit our search and review to any time or database or journal category. We find the theoretical logic and empirical evidence so far available in the literature. Our review finds that the development of the financial sector of a country is one of the most important attractors of FDIs. Theoretically, financial sector development works as a symbol of trust and goodness to the new potential investors and a good resource allocation channel for the existing investors. However, very few researchers find that FDIs are more prone to countries with a low developed financial system which may happen due to the presence of risk-taker foreign investors and risk-averse domestic entrepreneurs.
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 |