The Identification of Stakeholders’ Living Contexts in Stakeholder Participation Data: A Semantic, Spatial and Temporal Analysis
Stakeholders’ Participation (SP) aims to involve stakeholders in decision-making processes about significant choices affecting their organizations, cities, or communities. Stakeholders’ participation is maintained through SP processes (SPPs) that may be traditional (e.g., physical assemblies) or onl...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/11/6/798 |
| _version_ | 1827659329075937280 |
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| author | Amal Marzouki Sehl Mellouli Sylvie Daniel |
| author_facet | Amal Marzouki Sehl Mellouli Sylvie Daniel |
| author_sort | Amal Marzouki |
| collection | DOAJ |
| description | Stakeholders’ Participation (SP) aims to involve stakeholders in decision-making processes about significant choices affecting their organizations, cities, or communities. Stakeholders’ participation is maintained through SP processes (SPPs) that may be traditional (e.g., physical assemblies) or online (e.g., online forums). Whether traditional or online, the purpose of SPPs is to collect and analyze data in a way that it would bring a benefit to a given decision-making process. In SPPs, stakeholders try to communicate (a part of) their living contexts, i.e., to present their objectives, daily problems, intentions, and issues they are facing within their environment. A major challenge of decision-makers is then to ensure that the living contexts of stakeholders are considered in SPPs for an effective implementation of project and policies. This paper focuses on the specific issue of the “stakeholders’ living context identification” and attempts to account for how stakeholders implicitly identify their living contexts in their SP comments. Based on a qualitative analysis of SP data from four case studies in two countries, this paper identified a set of semantic, spatial, and temporal patterns allowing to capture the stakeholders’ living contexts in SPPs data. Moreover, a conceptual model emphasizing the importance for decision-makers to capture and understand semantic, spatial, and temporal dimensions in SPPs is proposed. |
| first_indexed | 2024-03-09T23:18:58Z |
| format | Article |
| id | doaj.art-d8176d3f75c54190852898d3c1c09891 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-09T23:18:58Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-d8176d3f75c54190852898d3c1c098912023-11-23T17:30:49ZengMDPI AGLand2073-445X2022-05-0111679810.3390/land11060798The Identification of Stakeholders’ Living Contexts in Stakeholder Participation Data: A Semantic, Spatial and Temporal AnalysisAmal Marzouki0Sehl Mellouli1Sylvie Daniel2Department of Information Systems, Université du Québec à Rimouski, Campus de Lévis 1595 Boulevard Alphonse-Desjardins, Lévis, QC G6V 0A6, CanadaDepartment of Information Systems, Université Laval, 2325, rue de la Terrasse, Québec, QC G1V 0A6, CanadaDepartment of Geomatics, Université Laval, 1055, Avenue du Séminaire, Québec, QC G1V 0A6, CanadaStakeholders’ Participation (SP) aims to involve stakeholders in decision-making processes about significant choices affecting their organizations, cities, or communities. Stakeholders’ participation is maintained through SP processes (SPPs) that may be traditional (e.g., physical assemblies) or online (e.g., online forums). Whether traditional or online, the purpose of SPPs is to collect and analyze data in a way that it would bring a benefit to a given decision-making process. In SPPs, stakeholders try to communicate (a part of) their living contexts, i.e., to present their objectives, daily problems, intentions, and issues they are facing within their environment. A major challenge of decision-makers is then to ensure that the living contexts of stakeholders are considered in SPPs for an effective implementation of project and policies. This paper focuses on the specific issue of the “stakeholders’ living context identification” and attempts to account for how stakeholders implicitly identify their living contexts in their SP comments. Based on a qualitative analysis of SP data from four case studies in two countries, this paper identified a set of semantic, spatial, and temporal patterns allowing to capture the stakeholders’ living contexts in SPPs data. Moreover, a conceptual model emphasizing the importance for decision-makers to capture and understand semantic, spatial, and temporal dimensions in SPPs is proposed.https://www.mdpi.com/2073-445X/11/6/798stakeholder participationstakeholders’ living contextssemantic data analysisspatial data analysistemporal data analysisplace-based knowledge |
| spellingShingle | Amal Marzouki Sehl Mellouli Sylvie Daniel The Identification of Stakeholders’ Living Contexts in Stakeholder Participation Data: A Semantic, Spatial and Temporal Analysis Land stakeholder participation stakeholders’ living contexts semantic data analysis spatial data analysis temporal data analysis place-based knowledge |
| title | The Identification of Stakeholders’ Living Contexts in Stakeholder Participation Data: A Semantic, Spatial and Temporal Analysis |
| title_full | The Identification of Stakeholders’ Living Contexts in Stakeholder Participation Data: A Semantic, Spatial and Temporal Analysis |
| title_fullStr | The Identification of Stakeholders’ Living Contexts in Stakeholder Participation Data: A Semantic, Spatial and Temporal Analysis |
| title_full_unstemmed | The Identification of Stakeholders’ Living Contexts in Stakeholder Participation Data: A Semantic, Spatial and Temporal Analysis |
| title_short | The Identification of Stakeholders’ Living Contexts in Stakeholder Participation Data: A Semantic, Spatial and Temporal Analysis |
| title_sort | identification of stakeholders living contexts in stakeholder participation data a semantic spatial and temporal analysis |
| topic | stakeholder participation stakeholders’ living contexts semantic data analysis spatial data analysis temporal data analysis place-based knowledge |
| url | https://www.mdpi.com/2073-445X/11/6/798 |
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