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 / 19 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 — 29 Oct 2026 17:36 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.
19 / 19 with data · 0 missing or unmatched. Percentages use all 19 selected publications.
19 / 19 with data · 0 missing or unmatched. Percentages use all 19 selected publications.
19 / 19 with data · 0 missing or unmatched. Percentages use all 19 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 |
|---|---|---|---|---|---|
| 2015 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 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 | 2 | 2 | 2/2 | 2/2 |
| 2020 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 7 | 7 | 7/7 | 7/7 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2015 | All selected publications | 10 | 1 | 1/1 | 1/1 |
| 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 | 22 | 2 | 2/2 | 2/2 |
| 2020 | All selected publications | 99 | 5 | 5/5 | 5/5 |
| 2021 | All selected publications | 14 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 106 | 7 | 7/7 | 7/7 |
| 2023 | All selected publications | 29 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 15 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2015 | All selected publications | 25 | 1 | 1/1 | 1/1 |
| 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 | 68 | 2 | 2/2 | 2/2 |
| 2020 | All selected publications | 233 | 5 | 5/5 | 5/5 |
| 2021 | All selected publications | 24 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 182 | 7 | 7/7 | 7/7 |
| 2023 | All selected publications | 51 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 23 | 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 19 / 19 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): 2026-10-21T07:22:45.257766+00:00 — 2026-10-29T17:36:20.896209+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 | 2 | 19 | 19/19 |
| 2018 | All selected publications | 3 | 19 | 19/19 |
| 2019 | All selected publications | 4 | 19 | 19/19 |
| 2020 | All selected publications | 14 | 19 | 19/19 |
| 2021 | All selected publications | 45 | 19 | 19/19 |
| 2022 | All selected publications | 66 | 19 | 19/19 |
| 2023 | All selected publications | 147 | 19 | 19/19 |
| 2024 | All selected publications | 152 | 19 | 19/19 |
| 2025 | All selected publications | 110 | 19 | 19/19 |
| 2026 | All selected publications | 53 | 19 | 19/19 |
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 |
|---|---|
| 2015 | 1 |
| 2019 | 2 |
| 2020 | 5 |
| 2021 | 1 |
| 2022 | 7 |
| 2023 | 2 |
| 2024 | 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 | 3 | 44 | 74 | 3/3 | 14.67 | 16 | 100.0 | 3/3 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 2 | 57 | 119 | 2/2 | 28.5 | 28.5 | 100.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 14 | 194 | 413 | 14/14 | 13.86 | 14.5 | 100.0 | 14/14 · 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.
Gen Z controls almost the entire population in the world with a total number of almost two billion people worldwide. This generation will be the largest consumer group in the world. In Indonesia itself, In 2020, Gen Z occupied the highest percentage of the population. Therefore, Gen Z is a potential target market that has a considerable influence on purchasing decisions. Based on the characteristics of Gen Z, who are digital natives, the use of social media is the right marketing strategy for consumers who are counted into Gen Z category. Promotional activities, as part of a marketing strategy, especially through social media require influencers as endorsers. This study aims to investigate the factors that influence the credibility attributes of social media influencers on the purchase intentions of Gen Z consumers. This study uses influencer credibility attributes (attractiveness, expertise, and trustworthiness) as independent variables that influence the purchase intention of Gen Z consumers with brand image as a mediation. This research is categorized as explanatory research. The respondents in this study were Gen Z who used Korean cosmetic products throughout Indonesia, the determination of the number of samples in this study used a purposive sampling technique with a sample of 210 respondents. The method of collecting data is using a questionnaire, the data is analyzed using PLS-SEM. The results showed that the three attributes of influencer credibility had a significant effect on the purchase intention of Gen Z. The three attributes of credibility had a significant effect on brand image, brand image had a significant effect on purchase intention. Brand image can provide a full mediating role in the relationship of influencer credibility to the purchase intention of Gen Z consumers. Local cosmetic industry players are expected to improve marketing strategies through online channels, especially social media by utilizing the right influencers as their endorsers, because it is proven in this study, credibility of social media influencers have a significant effect on the brand image of a product and the purchase intention of Gen Z consumers, so that the local cosmetic industry in Indonesia can compete with foreign cosmetic industries.
This research aims to analyze and look for empirical evidence of the influence of organizational transformation on job satisfaction, the influence of organizational culture on job satisfaction, the influence of employee engagement on job satisfaction, the influence of transformational leadership on job satisfaction, the influence of work environment on job satisfaction, the influence of organizational transformation on employee performance, the influence of employee engagement on employee performance, the influence of leadership. Transformational to employee performance, the influence of organizational transformation on employee performance with job satisfaction as an intervening variable, the influence of employee engagement on employee performance with job satisfaction as an intervening variable, the influence of transformational leadership on employee performance as a varied intervening, the influence of the work environment on employee performance with job satisfaction as an intervening variable. From the results of the tests conducted known transformation. Organizational Culture, Employee Engagement, Transformational Leadership, Work environment have significant effects on Job Satisfaction, as variable intervening employee performance has a significant influence on fixed variables.
This study aims to empirically examine the impact of tax penalties, tax audits, and taxpayers’ awareness of corporate taxpayer compliance and the role of compliant intentions as the moderating variable in its correlation. The analytical method used is the Multiple Linear Regression (Multiple Regression Analysis) and the Moderated Regression Analysis (MRA). The population of this study is the corporate taxpayers in North Banjarmasin Tax Office in 2019 with a sample of 142 corporate rate taxpayers. The sampling method used is convenience sampling. The results show that tax penalties, tax audits, and taxpayers’ awareness positively affect corporate taxpayer compliance. However, the compliant intention is unable to moderate the effect of fines, tax audits, and taxpayers’ awareness toward corporate taxpayer compliance. This is due to the applied penalties and tax audits following the taxation laws and the corporate taxpayer’s awareness of the importance of taxation as the source of state income. The purposes of this research are to provide inputs and references for the tax authorities and taxpayers, to examine further about tax penalties and tax audits that have been implemented, and to raise awareness among taxpayers for complying with taxes. Then, this research is influenced by external factors and internal factors, namely penalty sanctions, tax audits, and awareness of taxpayers who make taxpayers compliant with taxes, so that the presence or absence of intentions will continue to make taxpayers obedient to taxes.
The contribution of organizational culture to the organization which includes the uniqueness of values, behavior, and psychology is needed by the organization. It also includes trust, experience, ways of thinking, and organizational expectations. Improving employee behavior into organizational citizenship behavior is needed by every organization. To bring OCB to employees, a well-formed commitment is needed. This study uses a quantitative approach to test 3 hypotheses using path analysis to see the role of mediation. Respondents numbered 169 in this study. The results found in this study are that mediators play a maximum role between organizational culture and OCB.
This study aims to investigate the effect of employee motivation and employee engagement mediated by job satisfaction on job performance. This study employs explanatory research with a quantitative approach. The population in this study consisted of all employees of retail company X. The sampling technique used was saturated sampling, and the number of research samples was 150. Data was collected through surveys and documentation, and the instrument was tested using Likert scales. The data was analysed using Structural Equation Model Partial Least Squares (SEM-PLS) modelling. The results of this study indicate that employee motivation can increase job performance, while employee engagement cannot increase job performance. Furthermore, the findings revealed that employee motivation can increase job satisfaction while employee engagement cannot. Job satisfaction can increase job performance. Job satisfaction can mediate the effect of employee motivation on job performance, but it cannot mediate the effect of employee engagement on job performance. According to the findings of this study, Company X should be able to provide motivational stimulus to employees by increasing salaries and work incentives, as well as increasing training and developing employee skills, so that workers can work effectively and efficiently.
In today’s technology and digital era, the main problem that can impact the life sector is the aspect of Human Resources with the expertise and competence of an employee. Organizational goals will be achieved, however, with advances in information technology, activities carried out by humans can be completed efficiently and effectively to obtain optimal results. This study aims to determine employees' service performance by linking several variables including digital competence, work-life balance, work stress, and emotional intelligence. This study used the PLS (Partial Least Square) analysis tool and the number of samples was 190 respondents. The study results show that digital competence has no effect on service performance but positively impacts work-life balance and stress. Moreover, emotional intelligence does not moderate the relationship between digital competence and work life balance on service performance but moderates the relationship between work stress and service performance. This research was conducted to determine the performance of employee services and the employees of PT. X were the object of analysis.
This study aims to explain the effect of product knowledge, brand image, e-WOM on purchase intentions for edtech products in Indonesia. Data were obtained using a closed questionnaire involving 230 respondents, from Indonesians who know about edtech startup products and are between 18 and 35 years old. The sampling technique used was convenience sampling. The analysis technique used is Structural Equation Modeling (SEM) and uses the help of the AMOS version 24 program. The results show that 1) product knowledge has a positive but not significant effect on purchase intention, 2) product knowledge and brand image have a positive and significant effect on e-commerce WOM, 3) brand image and e-WOM have a positive and significant effect on purchase intention. It was also found that e-WOM functions as a mediator variable from the effect of product knowledge and brand image on purchase intention. The effect of the e-WOM mediator is stronger than the direct effect of brand image on purchase intention.
Financial management for young entrepreneurs needs to be done because disciplined financial arrangements will be able to minimize the risk of uncertainty. Young entrepreneurs have problems with financial management behavior, that is knowledge and skills in managing finances which have an impact on financial decision-making. This study aims to see the effect of financial knowledge, financial attitudes, and personality on financial management behavior in young entrepreneurs in Malang. The approach used in this research is quantitative with an explanatory approach. This study's population is young entrepreneurs in the Brawijaya University environment. The sampling technique used purposive sampling with a sample size of 150 samples. The results of this study prove that partially financial knowledge has no significant effect on Financial Management Behavior. Financial attitudes have a significant effect on Financial Management Behavior, and personality has a significant effect on Financial Management Behavior in Young Entrepreneurs in Malang City.
Mining sector companies are closely related to pollution, waste, and strong interactions with the environment. If the pollution and waste are ignored, it will cause environmental damage that consequently impacts environmental sustainability and the community around the company. Therefore, companies are requested to address environmental and social issues through corporate social responsibility activities. Determinants of corporate social responsibility disclosure include company size, liquidity, leverage, and profitability. The purpose of this study is to examine the effect of the determinants of corporate social responsibility disclosure on corporate social responsibility in mining companies listed on the Indonesia Stock Exchange (IDX) from 2016 to 2020. The number of sample companies studied was seven mining sector companies, and the number of data tested was 35 (for five years). The data used in this research were derived from financial and sustainability reports. The sampling technique used in this study was the saturated sample. Data were analyzed using regression analysis processed using the SPSS application. This study revealed that company size, liquidity, leverage, and profitability affect corporate social responsibility disclosure.
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 |