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: 24 / 24 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 07:22 UTC — 22 Oct 2026 03:19 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.
24 / 24 with data · 0 missing or unmatched. Percentages use all 24 selected publications.
24 / 24 with data · 0 missing or unmatched. Percentages use all 24 selected publications.
24 / 24 with data · 0 missing or unmatched. Percentages use all 24 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 |
|---|---|---|---|---|---|
| 2020 | All selected publications | 11 | 11 | 11/11 | 11/11 |
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 9 | 9 | 9/9 | 9/9 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 76 | 11 | 11/11 | 11/11 |
| 2021 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 31 | 9 | 9/9 | 9/9 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 168 | 11 | 11/11 | 11/11 |
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 67 | 9 | 9/9 | 9/9 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 4 | 3 | 3/3 | 3/3 |
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 24 / 24 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): 2026-10-21T07:22:43.940924+00:00 — 2026-10-22T03:19:06.965030+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 | 24 | 24/24 |
| 2018 | All selected publications | 0 | 24 | 24/24 |
| 2019 | All selected publications | 0 | 24 | 24/24 |
| 2020 | All selected publications | 2 | 24 | 24/24 |
| 2021 | All selected publications | 20 | 24 | 24/24 |
| 2022 | All selected publications | 34 | 24 | 24/24 |
| 2023 | All selected publications | 67 | 24 | 24/24 |
| 2024 | All selected publications | 57 | 24 | 24/24 |
| 2025 | All selected publications | 46 | 24 | 24/24 |
| 2026 | All selected publications | 14 | 24 | 24/24 |
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 |
|---|---|
| 2020 | 11 |
| 2021 | 1 |
| 2022 | 9 |
| 2024 | 3 |
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 | 3 | 15 | 38 | 3/3 | 5.0 | 3 | 66.7 | 3/3 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 8 | 69 | 156 | 8/8 | 8.62 | 2.5 | 75.0 | 8/8 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 13 | 26 | 46 | 13/13 | 2.0 | 1 | 61.5 | 13/13 · 100.0% |
* Percentage among publications with a known citation count.
As an industry that has an important role for other industrial sectors, the plastic and packaging industry is the supply chain for consumer products. Behind the high industrial growth and the potential is still large, there are problems with plastic waste, consumption power, and changes in people's lifestyles that can affect the growth of the plastic and packaging industry. This study aims to determine how much impact the NPM (Net Profit Margin), GPM (Gross Profit Margin), TAT (Total Assets Turnover) on Profit Growth in the plastic and packaging industry sub-sector companies listed in IDX (Indonesia Stock Exchange) for the period 2014 to 2018. The method used in this study is a quantitative descriptive. The sampling technique used was purposive sampling in order to obtain a sample of 11 companies from a population of 12 companies. In the study the method of data analysis used the multiple linear regression analysis techniques by processing data using Eviews 8, because the data is not normally distributed, it uses the log transformation method. The results showed that simultaneously NPM (Net Profit Margin), GPM (Gross Profit Margin), TAT (Total Assets Turnover) had a significant effect on profit growth. And partially NPM (Net Profit Margin) has a significant effect on profit growth, while GPM (Gross Profit Margin) and TAT (Total Assets Turnover) have no significant effect on profit growth.
This study aims to examine and understand the influence of psychological capital on employee turnover intention through the mediating role of organizational commitment and work-life balance on Generation Z and millennial employees in Bandung, West Java. The data used in this study are primary and secondary data obtained from the employees of the companies and the company data. This study uses the census method as a sampling technique, with a number of samples of 100 respondents. The data is collected by distributing questionnaires and carrying out observations in the company. The data is further processed using Structural Equation Modeling with the Partial Least Square method. The results of this study indicate that psychological capital has a significant influence on employee turnover intention, organizational commitment, and work-life balance. Furthermore, organizational commitment and work-life balance are found to have a direct negative influence on turnover intention. Both of these variables also act as mediators in the relationship between psychological capital and turnover intention.
The purpose of this study is to determine which indicators are more capable of showing more accurate sell and buy signals on the LQ45 index by using the oscillator indicator Moving Average Divergent Convergent (MACD), Bollinger Band, and Relative Strength Index (RSI). The results in this study indicate that the sell signal can be captured well by the Bollinger band and MACD indicators, but it cannot be captured properly by the RSI, the volume can be small or heading and are in the side ways, while the MACD plays a too slow role in capturing the signal buy compared to Bollinger bands and RSI. The use of a single indicator will never show a buy and sell signal that is really accurate, this is based on the results of research that shows the difference in timeliness in Bollinger, RSI and also MACD so that the combination of several types of indicators will be better compared to using single indicators. Although in statistics there are no significant differences, there are only differences in increment and improvement in the placement of existing values, but in this case, the order of this value is crucial for traders because it requires very high accuracy to determine the right decision in daily transactions.
Making strategic decisions in a dynamic business environment has become a challenge for business people, especially in small and medium-sized enterprises (SMEs). Contextual knowledge gained in understanding the external environment is a factor that must be owned by every business person so that they gain a competitive advantage in increasing competition. This study aims to test the Entrepreneurial Performance model. The research was conducted on SMEs in West Java, in the city of Bandung. The sample selection was determined using the purposive sampling method and obtained 170 respondents as a sample. The analysis was carried out using the Structural Equation Model (SEM). The results of the study indicate the fit model after modification and produce an alternative model in the form of a correlation between Marketing Intelligence and Entrepreneurial Performance. Marketing Intelligence, Product Innovation and Competitive Advantage have a direct significant influence on Entrepreneurial Performance. Product Innovation partially has no significant effect on Competitive Advantage. This research is expected to contribute to SMEs in the city of Bandung to always have a good knowledge before making a decision. This knowledge includes an understanding of trends, media, competitors, and suppliers. The limitation in this study is also in its scope, which is only limited to a few SMEs in the city of Bandung. It is expected that future researchers will add samples and use other variables that can improve entrepreneurial performance.
This research aims to determine the influence of macroeconomic variables on stock return and its impact on corporate values. The population in this research is the sector of agriculture because based on the results of the sector's observation, the most severe decline in performance among others. Further sampling is done by the purposive sampling method, so from 22 companies that listings only 15 companies that meet the criteria. The analytical technique to be used in this study is to use a double linear regression analysis technique expanded with a pathway analysis method to obtain a comprehensive picture of the relationship between variables of one variable with other. We find is an inflation and interest rate negatively and significantly affecting the return of shares. The exchange rate positively and significantly affects the stock return and the influential stock return rate positively and significant to the corporate values.
This paper aims to determine to extend to which leadership and communication influence employee performance in the KOTAKU Bandung program. Employees who are able to work well are the company’s most desirable resources in order to achieve company goals. Employee performance can be improved from a leader by setting a good example, paying attention to employees and always communicating well with employees at work, especially employees who behave less well. In this paper, it is also describe about leadership, communication and employee performance in the KOTAKU Bandung program. We employed a hybrid analytics method for descriptive and verification methods with qualitative and quantitative approaches. Questionnaires were used to collect data. Inferential statistics were used to analyze the data, data analysis made use of multiple regressions and Pearson’s correlation. The Statistical Package for Social Science was used to aid the analysis. A dataset of 57 respondents from employee in KOTAKU Bandung program. Data processing was carried out by analyzing correlation coefficients, coefficients of determination, and hypothesis testing. Main findings study demonstrate that (i) employee responses regarding leadership and communication were stated to be quiet good, (ii) employee reponses regarding employee performance are stated to be quite high, and finally (iii) leadership and communication have influence employee performance both partially and simultaneously in the KOTAKU Bandung program.
One of the Indonesian government's policies since 2015 has been to increase development through its developed infrastructure, by increasing its budget for this sector from year to year. However, companies listed in the engineering and construction subsector on the Indonesian Stock Exchange, both state-owned enterprises and private companies, experienced losses so it could be said that their financial performance was poor. This study intends to evaluate the financial performance engineering and construction sub-sector companies using the Economic Value Added (EVA), Market Value Added (MVA), Refined Economic Value Added (REVA), Financial Value Added (FVA), and Shareholder Value Added (SVA) in 2018 – 2023 and determine their influence on stock prices. This type of research is quantitative descriptive research using E-Views 12 with a population 26 companies and a sample size 16 companies. Based on the results the calculations and analysis, it stated that EVA, MVA, REVA, FVA, SVA and stock prices engineering and construction companies, both state-owned and private, during the 2018 - 2023 period obtained an average of negative amounts. The research results show that the financial performance variables using value added have an influence on stock prices with influence of 74.57% while the rest is influenced by other variables not examined in this research. Partially only MVA and SVA have an influence on stock prices because based on the probability test using E-Views 12 it appears that only MVA and SVA produce results below the alpha. The suggestion for this research is that company management should pay attention to the company's financial performance, especially the MVA and SVA variables and further researcher can make comparative research between all value-added variables.
The increasingly rapid development of education in Indonesia requires strong involvement and engagement of lecturers, including in West Java. In reality, there are still some lecturers who have low involvement and engagement in education at their universities. This study examines the influence of proactive personality and emotional regulation on employee engagement, by considering the moderation of religiosity in this relationship pattern. expertise and knowledge in their field make them not focus on developing the quality of the campus they hold. The population of this study were Muslim lecturers who taught at universities in Bandung City, selected using the purposive sampling method, with 100 respondents. The data obtained was processed using Structural Equation Modeling with Partial Least Square (SEM-PLS). The results of this study show that employee engagement can be influenced by proactive personality and emotional regulation, and this influence is stronger when the lecturer's level of religiosity is high. These findings provide important insights for understanding factors that influence employee engagement in academic contexts.
Organizations are currently seeking for ways to improve their performance in order to remain in the fierce competition in the business environment. In this regard, leadership plays a crucial role as they can shape employees’ behavior and attitude in the organization. This study is carried out to analyze and understand the relationship between servant leadership, work engagement, and job performance. It also aims to examine the mediating role of work engagement in the relationship between servant leadership and job performance. This study uses quantitative approach with the survey. The population of this study is employees of manufacturing companies in West Java, Indonesia, with a total number of samples of 115 respondents, which are chosen using purposive sampling. The data collection is done using a survey by distributing questionnaires to respondents online. The data analysis uses Structural Equation Modeling with Partial Least Square (SEM-PLS). The results of this study indicate that servant leadership has a positive influence on both work engagement and job performance, while work engagement has a positive influence on job performance. In addition, this study also proved that work engagement is a mediator in the relationship between servant leadership and job performance. This study provides a fruitful contribution for managers or leaders of employees in manufacturing companies, such that they can foster employee performance through leading in a servant leadership style. This leadership style will be able to help employees to develop engagement in their work, and it will eventually increase their job performance.
This study aims to examine and understand the influence of psychological capital on employee turnover intention through the mediating role of organizational commitment and work-life balance on Generation Z and millennial employees in Bandung, West Java. The data used in this study are primary and secondary data obtained from the employees of the companies and the company data. This study uses the census method as a sampling technique, with a number of samples of 100 respondents. The data is collected by distributing questionnaires and carrying out observations in the company. The data is further processed using Structural Equation Modeling with the Partial Least Square method. The results of this study indicate that psychological capital has a significant influence on employee turnover intention, organizational commitment, and work-life balance. Furthermore, organizational commitment and work-life balance are found to have a direct negative influence on turnover intention. Both of these variables also act as mediators in the relationship between psychological capital and turnover intention.
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 |