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: 6 / 6 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 03:03 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.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 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 |
|---|---|---|---|---|---|
| 2024 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 5 | 6 | 6/6 | 6/6 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 10 | 6 | 6/6 | 6/6 |
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 6 / 6 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): 2026-10-21T07:22:53.443046+00:00 — 2026-10-22T03:03:13.470561+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 | 6 | 6/6 |
| 2018 | All selected publications | 0 | 6 | 6/6 |
| 2019 | All selected publications | 0 | 6 | 6/6 |
| 2020 | All selected publications | 0 | 6 | 6/6 |
| 2021 | All selected publications | 0 | 6 | 6/6 |
| 2022 | All selected publications | 0 | 6 | 6/6 |
| 2023 | All selected publications | 0 | 6 | 6/6 |
| 2024 | All selected publications | 2 | 6 | 6/6 |
| 2025 | All selected publications | 5 | 6 | 6/6 |
| 2026 | All selected publications | 3 | 6 | 6/6 |
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 |
|---|---|
| 2024 | 6 |
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 | 2 | 1 | 3 | 2/2 | 0.5 | 0.5 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 4 | 4 | 7 | 4/4 | 1.0 | 1.0 | 75.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
This study examines the collaboration between Lean Six Sigma principles and order fulfilment procedures, which are essential for facilitating international trade. The objective is to ascertain the extent to which sustainable and effective lean processes improve customer satisfaction and accelerate global product delivery. The study employs a dual methodology: initially, doing a comprehensive analysis of the current body of literature on the integration of Lean Six Sigma in order fulfilment inside various manufacturing companies, with the aim of finding any deficiencies or areas that require further investigation. Furthermore, we utilise a quantitative approach by administering surveys to professionals in the South African manufacturing industry. Deductive reasoning examines responses using random sampling to ensure unbiased selection. The findings emphasise that using Lean Six Sigma practices in the South African manufacturing sector can address customer concerns regarding the quality of orders and the timeliness of deliveries. This can provide a competitive advantage in the global market. The study validates that the inclusion of Lean Six Sigma measurements alleviates bottlenecks by focusing on improvements in operations, procedures, and communication. The study demonstrates the effectiveness of Lean Six Sigma methodologies in improving order fulfilment for enterprises engaged in international trade. It promotes these concepts to optimise processes, assuring timely deliveries and increased customer satisfaction. This study addresses several deficiencies in the current research on the incorporation of Lean Six Sigma in the manufacturing order fulfilment process. These gaps encompass the challenges of incorporating emerging technology, integrating collaborative supply chains, and incorporating sustainable practices. The distinctive methodology of integrating a comprehensive analysis of existing literature with empirical evidence enhances the novelty of the research outcomes. Manufacturing companies that aim to achieve global market excellence get practical advantages.
This study seeks to create a model for the management of the steel production supply chain in South Africa amid the Fourth Industrial Revolution (4IR), tackling persistent interruptions and delays within the supply chain despite current models. A mixed methodology was utilised in the model's development. The qualitative component entailed a Delphi research corroborated by literature to ascertain pertinent hypotheses, whereas the quantitative component validated the model through structural equation modelling (SEM) utilising SmartPLS software. The research delineated a seven-construct framework comprising cooperation, integration, communication, supply chain structure, Fourth Industrial Revolution technology, organisational culture, and trust. The amalgamation of these designs proved enough for improving the efficacy of the steel production supply chain. The research revealed that the use of Fourth Industrial Revolution technologies and the cultivation of a conducive organisational culture are essential for effective supply chain management in the steel manufacturing industry. The research presents a detailed model that facilitates the planning and organisation of steel industry supply networks in South Africa. This approach underscores the necessity of a cooperative organisational culture, client contentment, and the incorporation of Fourth Industrial Revolution technologies. Steel industry stakeholders are urged to implement adaptable supply chain frameworks (lean, agile, leagile) based on project goals. This study enhances theoretical frameworks by highlighting essential features that have not been previously incorporated into supply chain management models for the steel sector, including the integration of Fourth Industrial Revolution technology and organisational culture. It provides actionable insights for stakeholders in steel manufacture, enhancing supply chain performance via the proposed paradigm. The research methodology improves comprehension of supply chain management within the framework of the Fourth Industrial Revolution (4IR).
Supply chain management is the process of integrating critical business procedures throughout the supply chain to generate value for stakeholders and customers. Total Quality Management is a system that emphasises quality and focuses on ensuring customer satisfaction. Customer satisfaction is a very important instrument for operational performance and business continuity. Therefore, this study aims to determine and analyse the effect of supply chain management (SCM) and total quality management (TQM) on operational performance (OP) mediated by competitive advantage (CA). Sample collection was carried out by distributing questionnaires, using purposive sampling technique, which is one of the non-probability sampling categories. The data analysis method uses structural equation model-partial least square (SEM-PLS). The results stated that the strategy of implementing supply chain management and total quality management together can increase competitive advantage. Increased competitive advantage can improve operational performance. The suggested policy implications are that the company can continue to maintain good relations with partners, produce products according to customer desires, competitive prices and timely products.
Dynamic capabilities in the supply chain play an essential role in improving an organization's operational performance. This research aims to see the influence of supply chain dynamic capabilities, including collaboration, integration, agility, and responsive capabilities, on the operational performance of food and beverage MSMEs in Sleman, Indonesia. The sample of this study is food and beverage MSMEs located in Sleman, Indonesia, which apply supply chain management capabilities such as collaboration, integration, agility, and responsive capabilities. The MSMEs must have been operated for more than three years, starting from 2019, so MSMEs already have a more robust supply chain network. Data from sixty food and beverage MSMEs was collected in 2024 using a set of questionnaires tested for validity using Pearson’s correlation and reliability using Cronbach’s Alpha. Data processing in this research uses SPSS 25 software with an analysis tool, namely multiple regression analysis. This analysis helps prove whether or not there is an influence between two or more independent variables on the dependent variable. The results of this research show that collaboration capabilities, integration capabilities, agility capabilities, and responsive capabilities partially have a significant positive effect on operational performance. Increasing collaboration capabilities between MSMEs and internal and external parties must be maintained to improve value from the MSMEs themselves. According to the hypothesis test results, the integration capability variable significantly influences the operational performance of MSMEs in Sleman, Indonesia. The agility capability variable significantly influences the operational performance of MSMEs in Sleman, Indonesia. The responsiveness significantly influences the operational performance of MSMEs in Sleman, Indonesia.
In general, this research aims to analyze and determine the effect of the application of lean manufacturing which is focused on eliminating waste and the influence of the physical work environment on labor productivity. This research used primary data through the distribution of questionnaires conducted to employees of Company X with a total of 230 respondents from sections in departments directly related to research variables. Data analysis methods using the Structural Equation Model (SEM) measured by the Partial Least Square (PLS) model, and data processing using SmartPLS 4.0 Software. Based on the results of calculations, data analysis shows that the application of principles related to lean manufacturing, which in this research is focused on the process of eliminating waste has a positive effect on the productivity of the workforce. The creation of a physical work environment that meets standards also positively affects the productivity of the workforce.
This study seeks to create a model for the management of the steel production supply chain in South Africa amid the Fourth Industrial Revolution (4IR), tackling persistent interruptions and delays within the supply chain despite current models. A mixed methodology was utilised in the model's development. The qualitative component entailed a Delphi research corroborated by literature to ascertain pertinent hypotheses, whereas the quantitative component validated the model through structural equation modelling (SEM) utilising SmartPLS software. The research delineated a seven-construct framework comprising cooperation, integration, communication, supply chain structure, Fourth Industrial Revolution technology, organisational culture, and trust. The amalgamation of these designs proved enough for improving the efficacy of the steel production supply chain. The research revealed that the use of Fourth Industrial Revolution technologies and the cultivation of a conducive organisational culture are essential for effective supply chain management in the steel manufacturing industry. The research presents a detailed model that facilitates the planning and organisation of steel industry supply networks in South Africa. This approach underscores the necessity of a cooperative organisational culture, client contentment, and the incorporation of Fourth Industrial Revolution technologies. Steel industry stakeholders are urged to implement adaptable supply chain frameworks (lean, agile, leagile) based on project goals. This study enhances theoretical frameworks by highlighting essential features that have not been previously incorporated into supply chain management models for the steel sector, including the integration of Fourth Industrial Revolution technology and organisational culture. It provides actionable insights for stakeholders in steel manufacture, enhancing supply chain performance via the proposed paradigm. The research methodology improves comprehension of supply chain management within the framework of the Fourth Industrial Revolution (4IR).
Dynamic capabilities in the supply chain play an essential role in improving an organization's operational performance. This research aims to see the influence of supply chain dynamic capabilities, including collaboration, integration, agility, and responsive capabilities, on the operational performance of food and beverage MSMEs in Sleman, Indonesia. The sample of this study is food and beverage MSMEs located in Sleman, Indonesia, which apply supply chain management capabilities such as collaboration, integration, agility, and responsive capabilities. The MSMEs must have been operated for more than three years, starting from 2019, so MSMEs already have a more robust supply chain network. Data from sixty food and beverage MSMEs was collected in 2024 using a set of questionnaires tested for validity using Pearson’s correlation and reliability using Cronbach’s Alpha. Data processing in this research uses SPSS 25 software with an analysis tool, namely multiple regression analysis. This analysis helps prove whether or not there is an influence between two or more independent variables on the dependent variable. The results of this research show that collaboration capabilities, integration capabilities, agility capabilities, and responsive capabilities partially have a significant positive effect on operational performance. Increasing collaboration capabilities between MSMEs and internal and external parties must be maintained to improve value from the MSMEs themselves. According to the hypothesis test results, the integration capability variable significantly influences the operational performance of MSMEs in Sleman, Indonesia. The agility capability variable significantly influences the operational performance of MSMEs in Sleman, Indonesia. The responsiveness significantly influences the operational performance of MSMEs in Sleman, Indonesia.
Efficient supply chain management is essential for small and medium-sized enterprises (SMEs) in Ghana to guarantee a dependable flow of products and services, sustain competitiveness, and promote growth and job creation. The objective of this study is to analyse the current supply chain models utilised by manufacturing small and medium-sized enterprises (SMEs) in Ghana. Additionally, it intends to propose a prototype model that will aid manufacturing SMEs in achieving sustainability, growth, and future expansion in Ghana and other regions. The Conceptual framework was developed by examining variables identified in the existing literature on supplier management practices in small and medium-sized enterprises (SMEs), as well as inventory management approaches that are relevant to SMEs. A structured questionnaire was employed to collect data from the main source. This study employs a mixed method approach, which includes the participation of 363 respondents. Interviews and surveys were carried out with small and medium-sized enterprise (SME) owners and managers. The data was analysed using the SPSS (v 27.0) computer application, which involved both inferential and descriptive statistical analysis. The findings revealed essential components of the prototype, such as the implementation of supply management (SM), proficient information management (IM), streamlined distribution strategies, and strong marketing and sales strategies, in addition to customer relationship management (CRM) and effective post-sales services. Implementing these supply chain management (SCM) principles effectively can guarantee the sustainability, growth, employment generation, and overall performance of small and medium-sized enterprises (SMEs) in Ghana.
This study examines the collaboration between Lean Six Sigma principles and order fulfilment procedures, which are essential for facilitating international trade. The objective is to ascertain the extent to which sustainable and effective lean processes improve customer satisfaction and accelerate global product delivery. The study employs a dual methodology: initially, doing a comprehensive analysis of the current body of literature on the integration of Lean Six Sigma in order fulfilment inside various manufacturing companies, with the aim of finding any deficiencies or areas that require further investigation. Furthermore, we utilise a quantitative approach by administering surveys to professionals in the South African manufacturing industry. Deductive reasoning examines responses using random sampling to ensure unbiased selection. The findings emphasise that using Lean Six Sigma practices in the South African manufacturing sector can address customer concerns regarding the quality of orders and the timeliness of deliveries. This can provide a competitive advantage in the global market. The study validates that the inclusion of Lean Six Sigma measurements alleviates bottlenecks by focusing on improvements in operations, procedures, and communication. The study demonstrates the effectiveness of Lean Six Sigma methodologies in improving order fulfilment for enterprises engaged in international trade. It promotes these concepts to optimise processes, assuring timely deliveries and increased customer satisfaction. This study addresses several deficiencies in the current research on the incorporation of Lean Six Sigma in the manufacturing order fulfilment process. These gaps encompass the challenges of incorporating emerging technology, integrating collaborative supply chains, and incorporating sustainable practices. The distinctive methodology of integrating a comprehensive analysis of existing literature with empirical evidence enhances the novelty of the research outcomes. Manufacturing companies that aim to achieve global market excellence get practical advantages.
Supply chain management is the process of integrating critical business procedures throughout the supply chain to generate value for stakeholders and customers. Total Quality Management is a system that emphasises quality and focuses on ensuring customer satisfaction. Customer satisfaction is a very important instrument for operational performance and business continuity. Therefore, this study aims to determine and analyse the effect of supply chain management (SCM) and total quality management (TQM) on operational performance (OP) mediated by competitive advantage (CA). Sample collection was carried out by distributing questionnaires, using purposive sampling technique, which is one of the non-probability sampling categories. The data analysis method uses structural equation model-partial least square (SEM-PLS). The results stated that the strategy of implementing supply chain management and total quality management together can increase competitive advantage. Increased competitive advantage can improve operational performance. The suggested policy implications are that the company can continue to maintain good relations with partners, produce products according to customer desires, competitive prices and timely products.
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 |