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: 21 Oct 2026 00:14 UTC — 21 Oct 2026 07:23 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 |
|---|---|---|---|---|---|
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 17 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 19 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 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): 2026-10-21T00:14:27.800768+00:00 — 2026-10-21T07:23:09.640855+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 | 5 | 5/5 |
| 2018 | All selected publications | 0 | 5 | 5/5 |
| 2019 | All selected publications | 0 | 5 | 5/5 |
| 2020 | All selected publications | 0 | 5 | 5/5 |
| 2021 | All selected publications | 0 | 5 | 5/5 |
| 2022 | All selected publications | 2 | 5 | 5/5 |
| 2023 | All selected publications | 1 | 5 | 5/5 |
| 2024 | All selected publications | 8 | 5 | 5/5 |
| 2025 | All selected publications | 8 | 5 | 5/5 |
| 2026 | All selected publications | 5 | 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 |
|---|---|
| 2021 | 1 |
| 2022 | 2 |
| 2024 | 1 |
| 2026 | 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 | 1 | 11 | 12 | 1/1 | 11.0 | 11 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 4 | 10 | 12 | 4/4 | 2.5 | 2.0 | 50.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
This study aims to examine and analyze the effect of environmental awareness and knowledge on green behavior mediated by employee wellbeing. The research was conducted at the Batik Warna SMEs in the Kebon Indah Community located in Klaten, Central Java, with 118 respondents. Data analysis used the quantitative method of Structural Equation Modeling (SEM) SMART – Partial Least Square (PLS) Software. The results showed that: (i) There is a positive and significant influence between environmental awareness and employee well-being, (ii) There is a positive and significant influence between environmental knowledge and employee well-being, (iii) There is a positive and significant effect between employee wellbeing and employee green behavior, (iv) There is a positive and significant effect between environmental awareness on employee green behavior mediated by employee wellbeing, (v) There is a positive and significant effect on environmental knowledge on employee green behavior mediated by employee wellbeing at Batik Warna Alam SMEs in the Kebon Indah Community, located in Klaten, Central Java.
While economic incentives, technical developments, and government policies and regulations can all contribute to reduce residential water use, householders, on the other hand, can also help lessen overall water demands by using less water. In this study, we look at how to modify people's behaviour to conserve water at home. Using the theory of reasoned action which suggest human behaviour is a construct of subjective norms, and attitude, this study aimed to identify the factors that influences water conservation behaviour in low-income households in South Africa South Africa. The study focused on the Waterloo Township, which is located north of Durban in KwaZulu-Natal. This study followed a positive paradigm and employed a descriptive cross-sectional research design and a quantitative survey design with a sample of (n=305). Both descriptive and inferential analysis was used to analyze and present the data. Path analysis using regression coefficient was performed to establish the factors that predict water conservation behaviour. The results suggest that although the knowledge of water conservation was high among the respondents, there was however a negative gap difference (-20.3) between their knowledge (94.4%) and actual behaviour (74.1%) towards water saving techniques. The regression analysis conducted revealed that subject norms were the strongest predictor towards water conservation intentions in the Waterloo LCH. This conclusively suggest that the conceptualisation of water conservation behaviour as a function of attitude and subjective norm may be appropriate in the context of the low-cost housing areas within South Africa.
The study aims to investigate the energy conservation behaviour of owners and managers of small hospitality firms by incorporating social norms into an extended Value-Belief-Norm (VBN) model. In addition, the study examines the mediating effects of causal chain of the VBN model in the context of energy conservation behaviour. The world faces serious environmental challenges such as loss of biodiversity, pollution, depletion of natural resources and global warming. One of the causes of these environmental challenges is the production and consumption of energy by households and firms. The hospitality sector uses a significant amount of energy in its operation leading to negative environmental impacts. Reducing energy use will improve environmental and financial sustainability of hospitality firms. Energy conservation behaviour is one of the significant ways to reduce energy consumption. The study adopts the survey method for data collection and the respondents are conveniently sampled. The Partial Least Square Structural Equation Modelling is used for data analysis. Based on a dataset of 360 respondents, the study finds that the extended VBM model that includes social norms is applicable in explaining the energy conservation behaviour of owners/managers of small hospitality firms. The mediating effects of the causal chain of the VBN model are significant. The theoretical implication is the applicability of an extended VBN model that includes social norms to predict energy conservation behaviour. Recommendations on how to improve energy conservation behaviour include improving the level of awareness of ecological problems caused by energy consumption. The study aims to investigate the energy conservation behaviour of owners and managers of small hospitality firms by incorporating social norms into an extended Value-Belief-Norm (VBN) model. In addition, the study examines the mediating effects of causal chain of the VBN model in the context of energy conservation behaviour. The world faces serious environmental challenges such as loss of biodiversity, pollution, depletion of natural resources and global warming. One of the causes of these environmental challenges is the production and consumption of energy by households and firms. The hospitality sector uses a significant amount of energy in its operation leading to negative environmental impacts. Reducing energy use will improve environmental and financial sustainability of hospitality firms. Energy conservation behaviour is one of the significant ways to reduce energy consumption. The study adopts the survey method for data collection and the respondents are conveniently sampled. The Partial Least Square Structural Equation Modelling is used for data analysis. Based on a dataset of 360 respondents, the study finds that the extended VBM model that includes social norms is applicable in explaining the energy conservation behaviour of owners/managers of small hospitality firms. The mediating effects of the causal chain of the VBN model are significant. The theoretical implication is the applicability of an extended VBN model that includes social norms to predict energy conservation behaviour. Recommendations on how to improve energy conservation behaviour include improving the level of awareness of ecological problems caused by energy consumption.
The successful achievement of the UN Sustainable Development Goals (SDGs) largely depends on human behavior. Will people act sustainably when they consume, work, travel, or simply go about their lives? Only if the answer is yes can we truly make progress toward sustainability. Research into what influences SDG-supportive behavior has identified several factors. However, some studies emphasize knowledge, others highlight economic barriers, and still others focus on traits and psychological factors—rarely all at once. In this paper, we aim to broaden this perspective. By reviewing multiple sources, we develop and empirically test a comprehensive model of sustainable behavior. We propose that awareness of sustainability issues influences how individuals interpret and understand societal challenges. At the same time, a person’s motivational orientation will determine whether they internalize sustainability values as their own beliefs and develop positive attitudes toward the SDGs. Nonetheless, even if individuals strongly believe in sustainability, their actions also depend on other factors. Using data from the Japan Household Panel Survey on Sustainable Development Goals, this study constructs psychometric measures and creates a nomological framework to examine the mechanisms behind the formation of sustainability behavior. The findings suggest that prosocial peace orientation and awareness of sustainability issues positively influence sustainability values and attitudes, which, in turn, shape sustainability behaviors.
The study aims to systematically map and describe the evidence on individual’s sustainable consumption behaviour and energy and transport use in Africa. The paper employed Arskey and O’Malley’s’ framework of 2005 as a guide to conduct a scoping review. Using keywords separated by Boolean terms (AND/OR) with all limiters removed, relevant published studies in Science Direct, SCOPUS, and Google Scholar were searched. Full-text screening guided by the inclusion criteria was independently conducted and data extraction was done using a piloted form to ensure the accuracy and reliability of the data. The results revealed that out of 176 studies, six met this study’s inclusion criteria and were included for data extraction. Among the six included studies, two were multi-country studies involving African countries, and study each was conducted in Ghana, Mauritius, South Africa, and Egypt. Of the included studies, five were on sustainable energy consumption domain, one on energy use and recycling behaviour, and the factors influencing sustainable energy consumption; price, income, urbanization, intention, attitudes, subjective norms and personal values. However, we found no evidence on individual’s sustainable consumption behaviour and transport use. Concluding, the results suggest that limited studies on sustainable consumption behaviour of energy and transport use are found in Africa. Therefore, further studies are needed to protect the gains made so far on environmental sustainability as well as to encourage and improve the individual’s sustainable consumption practices.
The successful achievement of the UN Sustainable Development Goals (SDGs) largely depends on human behavior. Will people act sustainably when they consume, work, travel, or simply go about their lives? Only if the answer is yes can we truly make progress toward sustainability. Research into what influences SDG-supportive behavior has identified several factors. However, some studies emphasize knowledge, others highlight economic barriers, and still others focus on traits and psychological factors—rarely all at once. In this paper, we aim to broaden this perspective. By reviewing multiple sources, we develop and empirically test a comprehensive model of sustainable behavior. We propose that awareness of sustainability issues influences how individuals interpret and understand societal challenges. At the same time, a person’s motivational orientation will determine whether they internalize sustainability values as their own beliefs and develop positive attitudes toward the SDGs. Nonetheless, even if individuals strongly believe in sustainability, their actions also depend on other factors. Using data from the Japan Household Panel Survey on Sustainable Development Goals, this study constructs psychometric measures and creates a nomological framework to examine the mechanisms behind the formation of sustainability behavior. The findings suggest that prosocial peace orientation and awareness of sustainability issues positively influence sustainability values and attitudes, which, in turn, shape sustainability behaviors.
The study aims to investigate the energy conservation behaviour of owners and managers of small hospitality firms by incorporating social norms into an extended Value-Belief-Norm (VBN) model. In addition, the study examines the mediating effects of causal chain of the VBN model in the context of energy conservation behaviour. The world faces serious environmental challenges such as loss of biodiversity, pollution, depletion of natural resources and global warming. One of the causes of these environmental challenges is the production and consumption of energy by households and firms. The hospitality sector uses a significant amount of energy in its operation leading to negative environmental impacts. Reducing energy use will improve environmental and financial sustainability of hospitality firms. Energy conservation behaviour is one of the significant ways to reduce energy consumption. The study adopts the survey method for data collection and the respondents are conveniently sampled. The Partial Least Square Structural Equation Modelling is used for data analysis. Based on a dataset of 360 respondents, the study finds that the extended VBM model that includes social norms is applicable in explaining the energy conservation behaviour of owners/managers of small hospitality firms. The mediating effects of the causal chain of the VBN model are significant. The theoretical implication is the applicability of an extended VBN model that includes social norms to predict energy conservation behaviour. Recommendations on how to improve energy conservation behaviour include improving the level of awareness of ecological problems caused by energy consumption. The study aims to investigate the energy conservation behaviour of owners and managers of small hospitality firms by incorporating social norms into an extended Value-Belief-Norm (VBN) model. In addition, the study examines the mediating effects of causal chain of the VBN model in the context of energy conservation behaviour. The world faces serious environmental challenges such as loss of biodiversity, pollution, depletion of natural resources and global warming. One of the causes of these environmental challenges is the production and consumption of energy by households and firms. The hospitality sector uses a significant amount of energy in its operation leading to negative environmental impacts. Reducing energy use will improve environmental and financial sustainability of hospitality firms. Energy conservation behaviour is one of the significant ways to reduce energy consumption. The study adopts the survey method for data collection and the respondents are conveniently sampled. The Partial Least Square Structural Equation Modelling is used for data analysis. Based on a dataset of 360 respondents, the study finds that the extended VBM model that includes social norms is applicable in explaining the energy conservation behaviour of owners/managers of small hospitality firms. The mediating effects of the causal chain of the VBN model are significant. The theoretical implication is the applicability of an extended VBN model that includes social norms to predict energy conservation behaviour. Recommendations on how to improve energy conservation behaviour include improving the level of awareness of ecological problems caused by energy consumption.
While economic incentives, technical developments, and government policies and regulations can all contribute to reduce residential water use, householders, on the other hand, can also help lessen overall water demands by using less water. In this study, we look at how to modify people's behaviour to conserve water at home. Using the theory of reasoned action which suggest human behaviour is a construct of subjective norms, and attitude, this study aimed to identify the factors that influences water conservation behaviour in low-income households in South Africa South Africa. The study focused on the Waterloo Township, which is located north of Durban in KwaZulu-Natal. This study followed a positive paradigm and employed a descriptive cross-sectional research design and a quantitative survey design with a sample of (n=305). Both descriptive and inferential analysis was used to analyze and present the data. Path analysis using regression coefficient was performed to establish the factors that predict water conservation behaviour. The results suggest that although the knowledge of water conservation was high among the respondents, there was however a negative gap difference (-20.3) between their knowledge (94.4%) and actual behaviour (74.1%) towards water saving techniques. The regression analysis conducted revealed that subject norms were the strongest predictor towards water conservation intentions in the Waterloo LCH. This conclusively suggest that the conceptualisation of water conservation behaviour as a function of attitude and subjective norm may be appropriate in the context of the low-cost housing areas within South Africa.
This study aims to examine and analyze the effect of environmental awareness and knowledge on green behavior mediated by employee wellbeing. The research was conducted at the Batik Warna SMEs in the Kebon Indah Community located in Klaten, Central Java, with 118 respondents. Data analysis used the quantitative method of Structural Equation Modeling (SEM) SMART – Partial Least Square (PLS) Software. The results showed that: (i) There is a positive and significant influence between environmental awareness and employee well-being, (ii) There is a positive and significant influence between environmental knowledge and employee well-being, (iii) There is a positive and significant effect between employee wellbeing and employee green behavior, (iv) There is a positive and significant effect between environmental awareness on employee green behavior mediated by employee wellbeing, (v) There is a positive and significant effect on environmental knowledge on employee green behavior mediated by employee wellbeing at Batik Warna Alam SMEs in the Kebon Indah Community, located in Klaten, Central Java.
The study aims to systematically map and describe the evidence on individual’s sustainable consumption behaviour and energy and transport use in Africa. The paper employed Arskey and O’Malley’s’ framework of 2005 as a guide to conduct a scoping review. Using keywords separated by Boolean terms (AND/OR) with all limiters removed, relevant published studies in Science Direct, SCOPUS, and Google Scholar were searched. Full-text screening guided by the inclusion criteria was independently conducted and data extraction was done using a piloted form to ensure the accuracy and reliability of the data. The results revealed that out of 176 studies, six met this study’s inclusion criteria and were included for data extraction. Among the six included studies, two were multi-country studies involving African countries, and study each was conducted in Ghana, Mauritius, South Africa, and Egypt. Of the included studies, five were on sustainable energy consumption domain, one on energy use and recycling behaviour, and the factors influencing sustainable energy consumption; price, income, urbanization, intention, attitudes, subjective norms and personal values. However, we found no evidence on individual’s sustainable consumption behaviour and transport use. Concluding, the results suggest that limited studies on sustainable consumption behaviour of energy and transport use are found in Africa. Therefore, further studies are needed to protect the gains made so far on environmental sustainability as well as to encourage and improve the individual’s sustainable consumption practices.
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 |