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: 9 / 9 publications (100.0%). Latest observation: 21 Oct 2026, 00:14 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: 22 Oct 2026 00:43 UTC — 27 Oct 2026 19:04 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.
9 / 9 with data · 0 missing or unmatched. Percentages use all 9 selected publications.
9 / 9 with data · 0 missing or unmatched. Percentages use all 9 selected publications.
9 / 9 with data · 0 missing or unmatched. Percentages use all 9 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 |
|---|---|---|---|---|---|
| 2025 | All selected publications | 9 | 9 | 9/9 | 9/9 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 13 | 9 | 9/9 | 9/9 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 12 | 9 | 9/9 | 9/9 |
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 9 / 9 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): 2026-10-22T00:43:10.646736+00:00 — 2026-10-27T19:04:41.523423+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 | 9 | 9/9 |
| 2018 | All selected publications | 0 | 9 | 9/9 |
| 2019 | All selected publications | 0 | 9 | 9/9 |
| 2020 | All selected publications | 0 | 9 | 9/9 |
| 2021 | All selected publications | 0 | 9 | 9/9 |
| 2022 | All selected publications | 0 | 9 | 9/9 |
| 2023 | All selected publications | 0 | 9 | 9/9 |
| 2024 | All selected publications | 0 | 9 | 9/9 |
| 2025 | All selected publications | 3 | 9 | 9/9 |
| 2026 | All selected publications | 9 | 9 | 9/9 |
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 |
|---|---|
| 2025 | 9 |
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 |
|---|---|---|---|---|---|---|---|---|
| Bussecon Review of Social Sciences Bussecon International Academy | 5 | 8 | 7 | 5/5 | 1.6 | 1 | 100.0 | 5/5 · 100.0% |
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 4 | 5 | 5 | 4/4 | 1.25 | 1.0 | 50.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
This study mainly aimed to investigate the impact of seasonal changes on media advertising revenues (AR) in R environment through a visual-print media company example. So, the study primarily aimed to examine whether visual, print and internet ARs were affected by seasonal change. The study also aimed to indicate the trends of visual/ print/ and internet ARs over time in the light of seasonality. Furthermore, it was also aimed to make AR estimates for the next year with the best performing methods covering ARIMA and ETS. Methodologically, R programming language and its libraries were used together with ARIMA and ETS time series models. The data set consisted of a monthly ARs series consisting of 180 rows covering the period between January/2007-December/2021 and having a sufficient number of observations for the application of the models. Data were analyzed with R and next year’s forecasts were done with ARIMA and ETS. The study revealed that all AR types were affected by seasonal changes in the specified period and included seasonality, i.e. specially in the summer months. Additionally, it was observed that AR types have different trends despite containing seasonality. The study found that visual ARs denoted a slight downward trend including seasonality during the period. It was also indicated that print ARs reflected a very rapid and drastic downward trend covering seasonality. The study also revealed that internet ARs showed a very rapid and sharp upward trend compared to the other two AR types despite having seasonality. Furthermore, taking into account the calculated error metrics, it was found that the ARIMA model showed the best estimation performance in both i.e. visual and internet ARs. On the other hand, the ETS model indicated the best estimation performance in print ARs. Accordingly, estimations of the visual/print and internet ARs for the next year were made with the best performing methods. It was pointed out that estimated ARs included seasonality in the summer months and revealed similar results to the previous trends based on historical data.
Artificial intelligence (AI) is a rapidly developing technological development that helps individuals in many areas. However, this progress is met with different reactions from individuals. The paper aims to investigate the associations among the concepts of spiritual intelligence, intolerance of uncertainty and AI anxiety. Furthermore, mediating role of intolerance of uncertainty on the relationship between spiritual intelligence and AI anxiety is another aim to examine in this study. In order to measure the mentioned variables, data was collected from 382 white-collar employees using survey method. We conducted explanatory and confirmatory factor analyses to control validity, and Crombach Alpha values to control reliability of the scales. Findings represented that each scale was valid and reliable. After that measurement model and structural equation modelling was conducted for model testing. The results represented the significant relationship between spiritual intelligence and intolerance of uncertainty, between uncertainty tolerance and AI anxiety (also its dimensions). In addition, findings showed that intolerance of uncertainty fully mediates the relationship between spiritual intelligence and learning of AI anxiety, also between job replacement of AI anxiety. Furthermore, results presented that intolerance of uncertainty partially mediates the relationship between spiritual intelligence and sociotechnical blindness and configuration of AI anxiety.
This study explores the influence of digital marketing strategies on brand loyalty among young airline passengers, specifically targeting Millennials and Gen Z individuals aged 18-35 years old. With the increasing reliance on digital channels such as social media, email marketing, and search engine marketing, it is crucial to understand how these strategies impact the customer-brand relationship, brand trust, and ultimately, brand loyalty. The research employs a quantitative approach, gathering data from 230 participants who are frequent users of digital platforms and have recent travel experiences with airlines. The findings reveal that social media marketing has the most significant impact on the customer-brand relationship, followed by email and search engine marketing. Additionally, the study confirms that brand trust acts as a critical mediator between digital marketing activities and brand loyalty. These results highlight the importance of tailored digital marketing strategies for airlines aiming to engage and retain young passengers in a highly competitive industry.
Industry 4.0 technologies have optimized efficiency and effectiveness through the manufacture of sophisticated products and services, which result in enhancement of operations, improvement in safety, time, and cost-saving, and have revolutionized operations in almost all industries and have tremendously transformed the aviation sector. This study aims to examine the passenger travel experience with the implementation of e-services before, during, and after trips, from ticket bookings, self-check-in, smart boarding, in-flight services to baggage tracking after flight. Furthermore, the study seeks to identify the modern technologies with which air passengers are familiar or actively use, and to analyze the factors that influence their acceptance of these e-services. A research model was developed based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and modified to suit the objectives of this study. The study objectives were achieved through a survey, a self-administered online questionnaire from 253 air passengers was obtained, and data was analyzed using SPSS 25 software. The results reveal that performance expectancy, price-value, hedonic motivations, perceived benefits and habit have a positive significant influence on behavioral intention, while social influence, perceived challenges, facilitating conditions and effort expectancy were not supported. The results of the study give insights into how different passengers, different age groups, different geographical locations, and different technological maturity perceive such implementations. This will provide policymakers ideas on how to better manage and enhance e-services.
In today's competitive business landscape, organizations constantly seek strategies to enhance their market position and profitability. One of the pivotal inquiries that many industry experts and scholars are delving into is: How do cost leadership, service innovation, and customer value creation influence business performance? Cost leadership, often seen as a way to gain a competitive edge through operational efficiency, might offer immediate financial benefits. Given the frequent economic challenges, it has become increasingly crucial for hotel businesses to embrace strong competitive and marketing strategies. The hospitality sector, particularly susceptible to the ramifications of such crises, has long been scrutinized to discern the strategic measures they employ during turbulent times. This empirical investigation, encompassing insights from 437 industry professionals, underscores that initiatives centered on corporate service innovation yield a direct and favorable augmentation in organizational performance. However, the study found inconclusive evidence regarding the mediating impact of value creation through customer engagement.
In today’s business world, where technology and competition are intensely experienced, one of the most essential factors for organizational success is the establishment of healthy and harmonious relationships between managers and employees. In this context, paternalistic leadership refers to managers approaching their employees with the same care and protection that a father shows to his children, while employees willingly embrace this attitude. Such an approach can have significant effects on employees’ performance, commitment, job satisfaction, work engagement, and overall happiness. The primary purpose of this study is to examine the mediating role of employee happiness in the effect of paternalistic leadership on employees’ work engagement. The research population consists of all employees (N=1120) of Bortar Group Catering operating in ?zmir, while the sample comprises 428 participants who voluntarily completed the survey. The data were analyzed using the SPSS 23 statistical software. The findings aim to reveal how paternalistic leadership influences employees’ work engagement and whether happiness serves as a mediating factor in this relationship.
In today's competitive business landscape, organizations constantly seek strategies to enhance their market position and profitability. One of the pivotal inquiries that many industry experts and scholars are delving into is: How do cost leadership, service innovation, and customer value creation influence business performance? Cost leadership, often seen as a way to gain a competitive edge through operational efficiency, might offer immediate financial benefits. Given the frequent economic challenges, it has become increasingly crucial for hotel businesses to embrace strong competitive and marketing strategies. The hospitality sector, particularly susceptible to the ramifications of such crises, has long been scrutinized to discern the strategic measures they employ during turbulent times. This empirical investigation, encompassing insights from 437 industry professionals, underscores that initiatives centered on corporate service innovation yield a direct and favorable augmentation in organizational performance. However, the study found inconclusive evidence regarding the mediating impact of value creation through customer engagement.
There has been an increase in the elderly population worldwide in recent years. This situation creates some needs both at individual and social level. In particular, elderly individuals need support in carrying out their daily activities. Therefore, elderly care centers are seen as an important supporter in this respect. This study aims to identify the criteria affecting the selection of elderly care centers and prioritize them with SWARA method. The SWARA method was used to weight the criteria affecting the selection of elderly care centers in order of priority. Eight criteria identified through literature review were evaluated by five experts experienced in the relevant field. The experts evaluated the criteria by ranking them according to their importance and the final prioritization was carried out by taking the geometric mean of the evaluations. According to the results of the analysis, the most important factor affecting the selection of an elderly care center was the Quality-of-Life Comfort and Service with a weight of 22%. This was followed by Financial Status with 20%, Health Services with 16%, and Professional Staff with 13%. Location and Transportation criterion was determined as the least important factor with a weight of 0.7%. The fact that life comfort and service quality have the highest weight indicates that elderly individuals expect a quality and comfortable living environment. The results obtained from the study show that policies for elderly care homes should be organized in a way that aims to increase the comfort of living, improve service quality, ensure economic accessibility and ensure the sustainability of health services.
The study aims to investigate the extent to which the concepts of social innovation and talent management will affect the innovation performance of enterprises as a result of the literature studies on the concepts of social innovation and talent management in family businesses in the Marmara Region. A questionnaire consisting of 78 questions was applied to the employees of small, medium and large-sized family businesses operating in the Marmara Region. A total of 460 questionnaires were evaluated. SPSS program was used for the survey results and the answers were analyzed by reliability analysis, factor analysis, correlation analysis and regression analysis methods. With the analysis study, the impact of social innovation and talent management on innovation performance was tried to be determined. As a result, it has been determined that there is a significant relationship between talent management practices and innovation performance. In other words, it has been determined that talent management is a strong factor in increasing the innovation performance of enterprises. In addition, no effect of social innovativeness on innovation performance was observed. In the light of the findings, the results of the research are discussed and recommendations are presented for both managers and academicians.
This study explores the influence of digital marketing strategies on brand loyalty among young airline passengers, specifically targeting Millennials and Gen Z individuals aged 18-35 years old. With the increasing reliance on digital channels such as social media, email marketing, and search engine marketing, it is crucial to understand how these strategies impact the customer-brand relationship, brand trust, and ultimately, brand loyalty. The research employs a quantitative approach, gathering data from 230 participants who are frequent users of digital platforms and have recent travel experiences with airlines. The findings reveal that social media marketing has the most significant impact on the customer-brand relationship, followed by email and search engine marketing. Additionally, the study confirms that brand trust acts as a critical mediator between digital marketing activities and brand loyalty. These results highlight the importance of tailored digital marketing strategies for airlines aiming to engage and retain young passengers in a highly competitive industry.
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 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |
| ojs-rest | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:02 UTC |
| oai-pmh | 20 Oct 2026 19:50 UTC · brss | complete · brss · 20 Oct 2026 19:49 UTC |
| openalex-enrichment | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |