CiteNScope — Scholarly Index & Analytics
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Research across participating journals · All insights follow your collection filters.

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OpenAlex coverage 100.0% · 3/3 recordsLast OpenAlex observation 21 Oct 2026, 07:22 UTC
PUBLICATIONS3In the selected collection
CROSSREF CITATIONS23/3 with known counts
OPENALEX CITATIONS43/3 with known counts
OPENALEX MEAN1.33Per article with a known count
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topic: Labor market dynamics and wage inequality Remove ×
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Output and reach

Publication activity alongside incoming citations.

Publication activity

Articles grouped by publication year

Publications

Hover over a year or focus the chart and use arrow keys to inspect values.

2026 is year to date. 0 undated publications excluded.

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Citations received

OpenAlex · year of the citing work

OpenAlex

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.

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Research landscape

Leading affiliations and themes in this collection.

Full distributions & methodology ↓

Institutions

University of Dar es Salaam1North-West University1International Vision University13/3 records with data

Countries

North Macedonia1Tanzania1South Africa13/3 records with data

Primary topics

Labor market dynamics and wage inequality33/3 records with data
Two perspectives on citations

Follow the research impact

Independent sources. Clear time scales.

Lifetime citations by publication year

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.

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Citations received each year

OpenAlex · incoming citation links grouped by citing-work year

OpenAlex

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.

View data & coverage
Annual history: 3/3 articles. Latest history observation: 2026-10-21T07:22:57.129996+00:00. Source totals are never added together.
Research side by side

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Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.

Leave all unchecked to include every matching journal. Selection affects only comparison charts.
Display range
International Journal of Research in Business and Social Science

Publications

Articles by publication year

View data & coverage

Crossref citations

Latest lifetime totals · grouped by publication year

View data & coverage

OpenAlex citations

Latest lifetime totals · grouped by publication year

View data & coverage

OpenAlex · Citations received

By year of the citing work · 2017–2026

View data & coverage

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.

Full analytics report All distributions, publications, comparisons & data provenance
3 MATCHING PUBLICATIONSExplore results →Export CSV ↓
INDEXED PUBLICATIONS3
CROSSREF CITATIONS2
CROSSREF · CITED PUBLICATIONS66.7%
CROSSREF · MEAN CITATIONS0.67

Crossref citation coverage: 3 / 3 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 UTC. Means and percentages use records with known counts.

OpenAlex / Separate citation source

A broader view of this research

DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.

OPENALEX CITATIONS4
DOI MATCH COVERAGE100.0%3 / 3 publications
MEAN · KNOWN COUNTS ONLY1.333 known · 0 unknown
MEDIAN · KNOWN COUNTS ONLY1

Observation range: 21 Oct 2026 07:22 UTC — 21 Oct 2026 07:22 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.

OpenAlex citation distributionNo citations11–526–20021+0Unknown0

Institutions, countries & topics

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.

Institutions

3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.

Countries

3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.

Primary topics

3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.

Citation year / OpenAlex

Citations received over time

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 3 / 3 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): 2026-10-21T07:22:43.105612+00:00 — 2026-10-21T07:22:57.129996+00:00. Older observations may be retained after failed or incomplete refreshes.

OpenAlex · Citations received by year

21.00 2017 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32018 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32019 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32020 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32021 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32022 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32023 · All selected publications · OpenAlex · Citations received by year: 2 · Annual history coverage 3/32024 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 3/32025 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 3/32026 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/3 2017201820192020202120222023202420252026
View openalex · citations received by year data & coverage
Citation yearJournal / scopeOpenAlex · Citations received by yearPublicationsAnnual history known
2017All selected publications033/3
2018All selected publications033/3
2019All selected publications033/3
2020All selected publications033/3
2021All selected publications033/3
2022All selected publications033/3
2023All selected publications233/3
2024All selected publications133/3
2025All selected publications133/3
2026All selected publications033/3

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 ↗

Crossref citation distribution

Latest Crossref totals for the selected publications; not citations received in the selected years.

Mean0.67
Median1
No citations11–526–20021+0Unknown0

Unknown counts are excluded from the mean, median and cited-publication rate.

Journal comparison

Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.

Journal / publisherPublicationsCrossref citationsOpenAlex citationsOpenAlex coverageCrossref meanCrossref medianCrossref cited %*Crossref coverage
International Journal of Research in Business and Social Science
SSBFNET
3243/30.67166.73/3 · 100.0%

* Percentage among publications with a known citation count.

Explore publications

View all 3 →

Most cited · Crossref

JOURNAL ARTICLE

The effect of minimum wage increases on inflation

Bulent Dervishi

International Journal of Research in Business and Social Science · 2023

Read abstract

The wage level that employers cannot legally go below by setting a floor limit on wages is called the "minimum wage". In other words, the minimum wage is usually the lowest wage determined to meet the basic needs of workers. This wage is set to raise the living standards of workers and to reduce poverty. As a result of the increases in food prices in international markets in 2021 and especially in 2022, a food crisis emerged in the world economy in 2022. While the effects of the COVID-19 pandemic were overcome in 2021, the prices increased as a result of increased demand, on the other hand, at the beginning of 2022, the Russia-Ukraine tension triggered the food crisis while pushing food prices up. While rising prices affected fixed incomes the most, it became necessary to increase the minimum wage. Increasing the minimum wage encourages consumption by reducing poverty and increasing fixed income (workers) well-being. The increase in the minimum wage encourages consumption by reducing poverty and increases the welfare of the fixed income (workers), and on the one hand, increases the costs of the producers and leads to a decrease in production and unemployment. While increases can help improve workers' living standards, they can also have negative effects, such as reducing worker numbers or increasing costs for some businesses. The main purpose of this research is to examine that while increasing the minimum wage in the inflationary period is inevitable, it will again increase the general level of prices and trigger inflation.

DOI 10.20525/ijrbs.v12i3.25121 Crossref citations3 OpenAlex citations
JOURNAL ARTICLE

The common characteristics of employment status during the Covid-19 Lockdown

Steven Henry Dunga

International Journal of Research in Business and Social Science · 2022

Read abstract

The National Development Plan (NDP) of South Africa identifies the main ills that must be dealt with by 2030. These are poverty and inequality. The NDP also clearly points out the need to deal with unemployment. These build into the sustainable development goals with 2030 as the target year for achievement. Both the NDP for South Africa and the SDGs at the global level had these targets set way before the 2019 coronavirus hit. Now given the disruption that this pandemic caused, the trends and possibility of achieving these goes must be investigated. This paper looks at employment focusing on the characteristics of the people that had a job to return to after the hard lockdown in South Africa.  The main objective is to identify the significant predictors of employment status at the household level. The paper uses data from Statistics in South Africa that were collected in 2021 during the midst of the pandemic. Variables such as age, province, race or population group and gender were included in the analysis. The results of the logistic regression show that age, race, age of the province, and household size are all significant predictors of whether the head of the household was in salaried employment during the Covid-19 pandemic. The fact that females were more likely to be in employment is painting a unique picture of the labour force than what is normally observed in the surveys.

DOI 10.20525/ijrbs.v11i6.19641 Crossref citations1 OpenAlex citations
JOURNAL ARTICLE

Regulating the private security industry in Tanzania: the effect of minimum wage order

Eric Sambu

International Journal of Research in Business and Social Science · 2024

Read abstract

The principal objective of this paper is to explore the effect of minimum wage order as a form of regulatory mechanism for the private security industry in Tanzania. More precisely, it attempts to assess how minimum wage impact on the pricing of services to their consumers. It explores the background, comparative analysis of minimum wages, the current legal framework and interpretation of related legislation to support implementation and assesses compliance. The study that culminated in the paper was qualitative in nature, being based on the case study of the selected private security companies in Tanzania. For this end, this paper used observation, expert opinions, interviews and documentary review for getting both primary and secondary data. The findings of the study revealed that whereas the wage order is clear, there are extensive guidelines in the labour laws that require to be read together with it, leading to misinterpretation or deliberate omission due to their impact on the pricing. The set wage results in a selling price that is 4.3 times, even with a modest 10% profit mark-up. Compliance is very low, and enforcement is weak, leading to price undercutting and causes those willing to comply lax and follow non-compliers to survive in the market characterised with price wars. Consumer is conflicted in choosing cheap service providers and enforcing compliance with the minimum wage order for the welfare of guards. The study recommends improving regulatory oversight, more awareness training of PSC directors, simplifying the labour laws to avoid ambiguity, unifying minimum wages, regular audits and educating the consumers of the link between wage and pricing of service. It also recommends strengthening the capacity of trade associations to help in the regulation of their respective members.

DOI 10.20525/ijrbs.v13i5.34510 Crossref citations0 OpenAlex citations

Selected results

JOURNAL ARTICLE

Regulating the private security industry in Tanzania: the effect of minimum wage order

Eric Sambu

International Journal of Research in Business and Social Science · 2024

Read abstract

The principal objective of this paper is to explore the effect of minimum wage order as a form of regulatory mechanism for the private security industry in Tanzania. More precisely, it attempts to assess how minimum wage impact on the pricing of services to their consumers. It explores the background, comparative analysis of minimum wages, the current legal framework and interpretation of related legislation to support implementation and assesses compliance. The study that culminated in the paper was qualitative in nature, being based on the case study of the selected private security companies in Tanzania. For this end, this paper used observation, expert opinions, interviews and documentary review for getting both primary and secondary data. The findings of the study revealed that whereas the wage order is clear, there are extensive guidelines in the labour laws that require to be read together with it, leading to misinterpretation or deliberate omission due to their impact on the pricing. The set wage results in a selling price that is 4.3 times, even with a modest 10% profit mark-up. Compliance is very low, and enforcement is weak, leading to price undercutting and causes those willing to comply lax and follow non-compliers to survive in the market characterised with price wars. Consumer is conflicted in choosing cheap service providers and enforcing compliance with the minimum wage order for the welfare of guards. The study recommends improving regulatory oversight, more awareness training of PSC directors, simplifying the labour laws to avoid ambiguity, unifying minimum wages, regular audits and educating the consumers of the link between wage and pricing of service. It also recommends strengthening the capacity of trade associations to help in the regulation of their respective members.

DOI 10.20525/ijrbs.v13i5.34510 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

The effect of minimum wage increases on inflation

Bulent Dervishi

International Journal of Research in Business and Social Science · 2023

Read abstract

The wage level that employers cannot legally go below by setting a floor limit on wages is called the "minimum wage". In other words, the minimum wage is usually the lowest wage determined to meet the basic needs of workers. This wage is set to raise the living standards of workers and to reduce poverty. As a result of the increases in food prices in international markets in 2021 and especially in 2022, a food crisis emerged in the world economy in 2022. While the effects of the COVID-19 pandemic were overcome in 2021, the prices increased as a result of increased demand, on the other hand, at the beginning of 2022, the Russia-Ukraine tension triggered the food crisis while pushing food prices up. While rising prices affected fixed incomes the most, it became necessary to increase the minimum wage. Increasing the minimum wage encourages consumption by reducing poverty and increasing fixed income (workers) well-being. The increase in the minimum wage encourages consumption by reducing poverty and increases the welfare of the fixed income (workers), and on the one hand, increases the costs of the producers and leads to a decrease in production and unemployment. While increases can help improve workers' living standards, they can also have negative effects, such as reducing worker numbers or increasing costs for some businesses. The main purpose of this research is to examine that while increasing the minimum wage in the inflationary period is inevitable, it will again increase the general level of prices and trigger inflation.

DOI 10.20525/ijrbs.v12i3.25121 Crossref citations3 OpenAlex citations
JOURNAL ARTICLE

The common characteristics of employment status during the Covid-19 Lockdown

Steven Henry Dunga

International Journal of Research in Business and Social Science · 2022

Read abstract

The National Development Plan (NDP) of South Africa identifies the main ills that must be dealt with by 2030. These are poverty and inequality. The NDP also clearly points out the need to deal with unemployment. These build into the sustainable development goals with 2030 as the target year for achievement. Both the NDP for South Africa and the SDGs at the global level had these targets set way before the 2019 coronavirus hit. Now given the disruption that this pandemic caused, the trends and possibility of achieving these goes must be investigated. This paper looks at employment focusing on the characteristics of the people that had a job to return to after the hard lockdown in South Africa.  The main objective is to identify the significant predictors of employment status at the household level. The paper uses data from Statistics in South Africa that were collected in 2021 during the midst of the pandemic. Variables such as age, province, race or population group and gender were included in the analysis. The results of the logistic regression show that age, race, age of the province, and household size are all significant predictors of whether the head of the household was in salaried employment during the Covid-19 pandemic. The fact that females were more likely to be in employment is painting a unique picture of the labour force than what is normally observed in the surveys.

DOI 10.20525/ijrbs.v11i6.19641 Crossref citations1 OpenAlex citations

Data coverage & freshness

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

SourceMost recent successful journal syncLatest attempt
crossref21 Oct 2026 07:22 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 07:22 UTC
ojs-rest21 Oct 2026 07:22 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 06:46 UTC
oai-pmh20 Oct 2026 19:55 UTC · ijrbscomplete · ijrbs · 20 Oct 2026 19:50 UTC
openalex-enrichment21 Oct 2026 07:23 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 07:22 UTC
Full import history & methodology →