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: 5 / 5 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: 22 Oct 2026 01:09 UTC — 22 Oct 2026 02:14 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.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 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 | 2 | 2 | 2/2 | 2/2 |
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2014 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 23 | 2 | 2/2 | 2/2 |
| 2017 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2014 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 53 | 2 | 2/2 | 2/2 |
| 2017 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 7 | 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 5 / 5 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): 2026-10-22T01:09:49.558698+00:00 — 2026-10-22T02:14:40.908520+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 | 1 | 5 | 5/5 |
| 2018 | All selected publications | 8 | 5 | 5/5 |
| 2019 | All selected publications | 6 | 5 | 5/5 |
| 2020 | All selected publications | 9 | 5 | 5/5 |
| 2021 | All selected publications | 11 | 5 | 5/5 |
| 2022 | All selected publications | 7 | 5 | 5/5 |
| 2023 | All selected publications | 9 | 5 | 5/5 |
| 2024 | All selected publications | 6 | 5 | 5/5 |
| 2025 | All selected publications | 4 | 5 | 5/5 |
| 2026 | All selected publications | 2 | 5 | 5/5 |
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 |
| 2016 | 2 |
| 2017 | 1 |
| 2019 | 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 Research in Business and Social Science SSBFNET | 5 | 25 | 64 | 5/5 | 5.0 | 2 | 60.0 | 5/5 · 100.0% |
* Percentage among publications with a known citation count.
The aim of this research is to understand the factors behind smartphone purchase decisions of consumers. Nowadays companies make use of various strategies in order to attract new customers, retain existing customers and differentiate their products from those of their competitors. Perhaps, the most important and effective strategy to influence consumer behavior in the product selection is emphasizing the “brand name” of the products. Our aim in this paper is to investigate how smartphone brands can influence consumers’ buying decisions. Brand equity is a set of brand assets and liabilities linked to a brand name and symbol, which add to or subtract from the value provided by a product or service. It enhances the customer’s ability to interpret and process information, improves confidence in the purchase decision and affects the quality of the user experience. Using this construct widely discussed in the literature, we use and build our hypothesis based on Aaker model about the brand equity, including perceived quality, brand awareness, brand association and brand loyalty. The study involved a questionnaire administered to 171 smartphone consumers between December 2015 and March 2016. The consumers were chosen by convenience sampling among the students from a prestigious university in the Istanbul district of Turkey. Our findings indicate that a majority of the smartphone buyers’ decisions are mainly influenced by brand loyalty and brand awareness. Perceived quality and brand association do not seem to influence purchase decisions for the sample of this study.
Concepts such as retro marketing, retro branding and nostalgia marketing are important issues that have come to the agenda in recent years in our world, which is undergoing intensive change and transformation processes. The longing for past periods can be an important source of marketing work for the consumer. Few scientific studies have been conducted in Turkey for retro marketing. It is possible to carry out researches on retro marketing and retro branding, to test relations with different concepts and to develop the researches in detailed form. The aim of this study is to determine whether the general hypotheses tested in the literature will have the same effect on brands carrying retro marketing activities. The scales for the concepts in the research were taken from the literature and 401 participants were reached by convenience sampling method. As a result of the study, it was detected that the dimensions of retro brand experience affect the intention of re-purchasing and brand loyalty. It has also been observed that the retro brand experience dimensions also affect the retro brand attitude, retro brand credibility and customer satisfaction. Finally, it has been tested whether retro brand attitude, retro brand credibility, and customer satisfaction concepts affect repurchase intention and brand loyalty. As a result, it has been observed that these concepts affect repurchase intention and brand loyalty.
This research aims to analyze the effect of brand trust and brand loyalty to consumer purchase intentions in the Smartphone market. All the residents of ?stanbul who use mobile phones are the population of the research. Due to the fact that it is very hard to reach all the population, simple sampling method has been used for data collection and 185 participants have been reached. Structural Equation Model has been used to explain the relationship among brand trust, brand loyalty and purchase intentions. SPSS for Windows 17.0 program and AMOS 20 program are used to analyze the data. Results show that both brand trust and brand loyalty have a positive effect on consumer’s purchase intentions. Also it had been determined that brand trust has a positive effect on brand loyalty. Moreover, brand trust has been found as the most effective factor for smartphones brands in the purchase intensions.
In psychology attitude is defined as favorable or unfavorable evaluations towards a person, group, object or event. Attitudes are formed by past and present experiences and are expected to change as a function of experience. Three components of the attitude defined as cognitive (what we know about the subject), affective (how we feel towards the subject) and behavioral (intention to behave towards the subject). Our behavior is defined as a complex combination of beliefs, feelings, capabilities and norms. The majority of consumer behavior literature examined the main antecedents of purchase behavior. Attitudes are described as one of the most important determinant of the behavior. There are several methods and techniques to assess attitude; the most used one is the self-report paper and pencil measures. Brand loyalty is another important concept related with repetitive purchasing behavior. While cognitive loyalty is related with the information, affective loyalty is related with feelings. Behavioral loyalty is described as the past behaviors or experiences. Some of our behaviors are determined by the cognitive component of the attitude while others may be directed by the affective part. Main focus of the research is to find out whether there is a level of compliance between cognitive, affective and behavioral attitude of consumers. 1000 forms are distributed in order to identify the attitudes and purchasing behaviors of consumers 783 forms are evaluated
This paper examines the nature of the Country of Origin effect by exploring suggested options to enhance positive COO associations in consumers’ minds and offsetting negative COO impact on purchase decisions. The approach taken is a literature review with a comparison of Turkey’s white goods brand Beko Plc’s international growth and marketing strategies. This paper focuses on suggested international marketing strategies in order to increase the country image of Turkey as well as the brand image of Beko Plc. In the interest of achieving a sustainable growth in foreign markets and offsetting the negative consumers’ perceptions of products made in particular countries, organizations are in need of advanced quality management practices and applicable pricing policies that respond adequately to consumer needs.
In psychology attitude is defined as favorable or unfavorable evaluations towards a person, group, object or event. Attitudes are formed by past and present experiences and are expected to change as a function of experience. Three components of the attitude defined as cognitive (what we know about the subject), affective (how we feel towards the subject) and behavioral (intention to behave towards the subject). Our behavior is defined as a complex combination of beliefs, feelings, capabilities and norms. The majority of consumer behavior literature examined the main antecedents of purchase behavior. Attitudes are described as one of the most important determinant of the behavior. There are several methods and techniques to assess attitude; the most used one is the self-report paper and pencil measures. Brand loyalty is another important concept related with repetitive purchasing behavior. While cognitive loyalty is related with the information, affective loyalty is related with feelings. Behavioral loyalty is described as the past behaviors or experiences. Some of our behaviors are determined by the cognitive component of the attitude while others may be directed by the affective part. Main focus of the research is to find out whether there is a level of compliance between cognitive, affective and behavioral attitude of consumers. 1000 forms are distributed in order to identify the attitudes and purchasing behaviors of consumers 783 forms are evaluated
Concepts such as retro marketing, retro branding and nostalgia marketing are important issues that have come to the agenda in recent years in our world, which is undergoing intensive change and transformation processes. The longing for past periods can be an important source of marketing work for the consumer. Few scientific studies have been conducted in Turkey for retro marketing. It is possible to carry out researches on retro marketing and retro branding, to test relations with different concepts and to develop the researches in detailed form. The aim of this study is to determine whether the general hypotheses tested in the literature will have the same effect on brands carrying retro marketing activities. The scales for the concepts in the research were taken from the literature and 401 participants were reached by convenience sampling method. As a result of the study, it was detected that the dimensions of retro brand experience affect the intention of re-purchasing and brand loyalty. It has also been observed that the retro brand experience dimensions also affect the retro brand attitude, retro brand credibility and customer satisfaction. Finally, it has been tested whether retro brand attitude, retro brand credibility, and customer satisfaction concepts affect repurchase intention and brand loyalty. As a result, it has been observed that these concepts affect repurchase intention and brand loyalty.
This research aims to analyze the effect of brand trust and brand loyalty to consumer purchase intentions in the Smartphone market. All the residents of ?stanbul who use mobile phones are the population of the research. Due to the fact that it is very hard to reach all the population, simple sampling method has been used for data collection and 185 participants have been reached. Structural Equation Model has been used to explain the relationship among brand trust, brand loyalty and purchase intentions. SPSS for Windows 17.0 program and AMOS 20 program are used to analyze the data. Results show that both brand trust and brand loyalty have a positive effect on consumer’s purchase intentions. Also it had been determined that brand trust has a positive effect on brand loyalty. Moreover, brand trust has been found as the most effective factor for smartphones brands in the purchase intensions.
The aim of this research is to understand the factors behind smartphone purchase decisions of consumers. Nowadays companies make use of various strategies in order to attract new customers, retain existing customers and differentiate their products from those of their competitors. Perhaps, the most important and effective strategy to influence consumer behavior in the product selection is emphasizing the “brand name” of the products. Our aim in this paper is to investigate how smartphone brands can influence consumers’ buying decisions. Brand equity is a set of brand assets and liabilities linked to a brand name and symbol, which add to or subtract from the value provided by a product or service. It enhances the customer’s ability to interpret and process information, improves confidence in the purchase decision and affects the quality of the user experience. Using this construct widely discussed in the literature, we use and build our hypothesis based on Aaker model about the brand equity, including perceived quality, brand awareness, brand association and brand loyalty. The study involved a questionnaire administered to 171 smartphone consumers between December 2015 and March 2016. The consumers were chosen by convenience sampling among the students from a prestigious university in the Istanbul district of Turkey. Our findings indicate that a majority of the smartphone buyers’ decisions are mainly influenced by brand loyalty and brand awareness. Perceived quality and brand association do not seem to influence purchase decisions for the sample of this study.
This paper examines the nature of the Country of Origin effect by exploring suggested options to enhance positive COO associations in consumers’ minds and offsetting negative COO impact on purchase decisions. The approach taken is a literature review with a comparison of Turkey’s white goods brand Beko Plc’s international growth and marketing strategies. This paper focuses on suggested international marketing strategies in order to increase the country image of Turkey as well as the brand image of Beko Plc. In the interest of achieving a sustainable growth in foreign markets and offsetting the negative consumers’ perceptions of products made in particular countries, organizations are in need of advanced quality management practices and applicable pricing policies that respond adequately to consumer needs.
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 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |