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.
New articles are checked daily. Citation sources are refreshed monthly. All times below are UTC. A successful check may find no new publications.
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: 4 / 4 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: 31 Oct 2026 19:35 UTC — 01 Nov 2026 08:05 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.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 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 |
|---|---|---|---|---|---|
| 2014 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2014 | All selected publications | 6 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 14 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 9 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 12 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2014 | All selected publications | 12 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 21 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 13 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 17 | 1 | 1/1 | 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 4 / 4 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): 2026-10-31T19:35:37.123297+00:00 — 2026-11-01T08:05:39.107676+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 | 4 | 4/4 |
| 2018 | All selected publications | 0 | 4 | 4/4 |
| 2019 | All selected publications | 1 | 4 | 4/4 |
| 2020 | All selected publications | 4 | 4 | 4/4 |
| 2021 | All selected publications | 2 | 4 | 4/4 |
| 2022 | All selected publications | 6 | 4 | 4/4 |
| 2023 | All selected publications | 11 | 4 | 4/4 |
| 2024 | All selected publications | 9 | 4 | 4/4 |
| 2025 | All selected publications | 13 | 4 | 4/4 |
| 2026 | All selected publications | 12 | 4 | 4/4 |
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 |
|---|---|
| 2014 | 1 |
| 2020 | 1 |
| 2021 | 1 |
| 2022 | 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 Business Ecosystem & Strategy Bussecon International Academy | 1 | 9 | 13 | 1/1 | 9.0 | 9 | 100.0 | 1/1 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 1 | 6 | 12 | 1/1 | 6.0 | 6 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 26 | 38 | 2/2 | 13.0 | 13.0 | 100.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
This study aims to evaluate the effect of rapid changes in financial technologies and their impact on the financial services industry of India. A descriptive study has been made on the implementation of financial technologies in modern-day financial services Industries. An intensive literature review has been done from the existing most recent available journals, newspaper articles, government websites, and magazines. We have discussed the effects of the financial technologies on the existing financial system of India, the threats and challenges faced by the regulators in regulating the novel disruptive technologies. We have also discussed potential threats, challenges and future prospects of upcoming technologies in the mutual funds industry in India. Based on the literature review, it is found that financial technologies (FinTech) have a positive and important effect on the financial services industry of India. The AUM (Asset Under Management) has seen a tremendous jump in the recent past. It has also increased the customer experience with better access to the back office, even from remote places. In addition, the paper has also discussed the challenges faced by the regulators, who are yet to fully understand the implication of the fast-changing technological environment around us. Finally, this article contributes to the knowledge building and understanding of financial technologies and its impact on the financial industry, challenges, and future prospects.
Human capital is a significant element in the attainment of sustained competitive advantage and economic survival of organizations. The study explored whether human capital mediates the nexus of human resource management practices and organizational performance. A field study was conducted among 11 internationally and 4 indigenously owned banks. The hypothesized relationships were supported by the data. The results show that the association between selective staffing with the levels of human capital was significant. The results also show that the levels of human capital influenced organizational performance significantly. The results further show that human capital mediated the nexus of HRM practices and organizational performance. The generalizability of the results obtained may be constrained since the present study focused on the banking industry. The study suggests the creation and maintenance of valuable human capital promote competitiveness and sustained competitive advantage. The study contributes to the extant literature by empirically evidencing that human capital mediated the nexus of HRM practice and organizational performance.
The automotive industry is standing on the edge of the digital era. Digitization is the motivating force behind this change and is influencing every aspect of consumer behavior. Forces behind this digital transformation are the new technological possibilities which range from comprehensive connectivity, 3D printing, and the social network of virtual solutions as well. The impact of digitization can already be seen in today’s world and also in the automotive industry of India. Digitization will play an imperative role in the upcoming years such as artificial intelligence. This paper is primarily concerned with the recent trends of digitization and it also tries to measure the impact of digitization on the automobile supply chain between automobile manufacturers and suppliers. It is discussed the thrust on the potentialities of digitalization in the automobile industry of India and its impact on the overall performance of the industry. The study concluded that digitization has a significant impact on the automotive industry of India. Today, all the business practices become digitalized and foreign players use advanced technology in their products as compared to the national automotive players. The selling of automotive products is increased after the adoption of more advanced technology. It upgrades the quality of products and its service after sale which ultimately leads to the customer and brand loyalty used by the consumers.
The link between stock market development and economic activity has always been the subject of considerable debate in the field of economics and it raises empirical question whether stock market development influences economic activity or whether it is a consequence of increased economic activity. This study attempts to investigate the direction of causality between stock market development and economic growth in the Indian context. Using the cointegration and causality tests for the period June 1991 to June 2013, the study confirms a well defined long-run equilibrium relationship between the stock market development indicators and economic growth in India. The empirical results show bidirectional causality between market capitalisation and economic growth and unidirectional causality from turnover ratio to economic growth in the long-run and short-run. By and large, it can be inferred that the stock market development indicators viz. market capitalisation and turnover ratio have a positive influence on economic growth in India.
Human capital is a significant element in the attainment of sustained competitive advantage and economic survival of organizations. The study explored whether human capital mediates the nexus of human resource management practices and organizational performance. A field study was conducted among 11 internationally and 4 indigenously owned banks. The hypothesized relationships were supported by the data. The results show that the association between selective staffing with the levels of human capital was significant. The results also show that the levels of human capital influenced organizational performance significantly. The results further show that human capital mediated the nexus of HRM practices and organizational performance. The generalizability of the results obtained may be constrained since the present study focused on the banking industry. The study suggests the creation and maintenance of valuable human capital promote competitiveness and sustained competitive advantage. The study contributes to the extant literature by empirically evidencing that human capital mediated the nexus of HRM practice and organizational performance.
The automotive industry is standing on the edge of the digital era. Digitization is the motivating force behind this change and is influencing every aspect of consumer behavior. Forces behind this digital transformation are the new technological possibilities which range from comprehensive connectivity, 3D printing, and the social network of virtual solutions as well. The impact of digitization can already be seen in today’s world and also in the automotive industry of India. Digitization will play an imperative role in the upcoming years such as artificial intelligence. This paper is primarily concerned with the recent trends of digitization and it also tries to measure the impact of digitization on the automobile supply chain between automobile manufacturers and suppliers. It is discussed the thrust on the potentialities of digitalization in the automobile industry of India and its impact on the overall performance of the industry. The study concluded that digitization has a significant impact on the automotive industry of India. Today, all the business practices become digitalized and foreign players use advanced technology in their products as compared to the national automotive players. The selling of automotive products is increased after the adoption of more advanced technology. It upgrades the quality of products and its service after sale which ultimately leads to the customer and brand loyalty used by the consumers.
This study aims to evaluate the effect of rapid changes in financial technologies and their impact on the financial services industry of India. A descriptive study has been made on the implementation of financial technologies in modern-day financial services Industries. An intensive literature review has been done from the existing most recent available journals, newspaper articles, government websites, and magazines. We have discussed the effects of the financial technologies on the existing financial system of India, the threats and challenges faced by the regulators in regulating the novel disruptive technologies. We have also discussed potential threats, challenges and future prospects of upcoming technologies in the mutual funds industry in India. Based on the literature review, it is found that financial technologies (FinTech) have a positive and important effect on the financial services industry of India. The AUM (Asset Under Management) has seen a tremendous jump in the recent past. It has also increased the customer experience with better access to the back office, even from remote places. In addition, the paper has also discussed the challenges faced by the regulators, who are yet to fully understand the implication of the fast-changing technological environment around us. Finally, this article contributes to the knowledge building and understanding of financial technologies and its impact on the financial industry, challenges, and future prospects.
The link between stock market development and economic activity has always been the subject of considerable debate in the field of economics and it raises empirical question whether stock market development influences economic activity or whether it is a consequence of increased economic activity. This study attempts to investigate the direction of causality between stock market development and economic growth in the Indian context. Using the cointegration and causality tests for the period June 1991 to June 2013, the study confirms a well defined long-run equilibrium relationship between the stock market development indicators and economic growth in India. The empirical results show bidirectional causality between market capitalisation and economic growth and unidirectional causality from turnover ratio to economic growth in the long-run and short-run. By and large, it can be inferred that the stock market development indicators viz. market capitalisation and turnover ratio have a positive influence on economic growth in India.
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 |
|---|---|---|
| Not available · | Not run | |
| Not available · | Not run | |
| Not available · | Not run |