Big data analytics in facilities management higher education: a way forward
Background and aim: In this digital era, the facilities management (FM) industry tends to apply Big Data analytics (BDA), employing machine learning for functions such as predictive maintenance, energy management and workplace management. Therefore, it is essential to discuss the digital transformat...
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
European Facility Management Network (EuroFM)
2024
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| Online Access: | https://repository.londonmet.ac.uk/9764/1/Big%20data%20analytics%20in%20facilities%20management%20higher%20education%20A%20way%20forward.pdf |
| _version_ | 1824446494554456064 |
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| author | Sumanarathna, Nipuni Dahanayake, Kalani C. Adhikari, Aravinda |
| author_facet | Sumanarathna, Nipuni Dahanayake, Kalani C. Adhikari, Aravinda |
| author_sort | Sumanarathna, Nipuni |
| collection | LMU |
| description | Background and aim: In this digital era, the facilities management (FM) industry tends to apply Big Data analytics (BDA), employing machine learning for functions such as predictive maintenance, energy management and workplace management. Therefore, it is essential to discuss the digital transformation of facilities management higher education (FMHE) and the requirements for FMHE to be future-proof. This paper aims to explore the extent to which BDA is applied in FM and how it is manifested within FMHE.
Methods: This viewpoint paper is developed based on the industry, academic and research experience of the authors. Prior literature findings are also incorporated to develop and support the views regarding the application of BDA in the industry and its representation in FMHE.
Results: Based on the experiential learning perspective, recommendations for BDA-related teaching and learning in FMHE are delivered.
Originality: This study addresses the potential gaps between the FM industry and higher education by discussing the advanced approaches which have not yet been extensively recognised in FMHE. Hence, this paper contributes to developing new FM capabilities among students within the context of digital
transformation in FM.
Practical or social implications: The recommendations derived from the experiential learning perspective add depth to the discussion, offering suggestions for understanding and advancing FMHE. This study can also serve as a guide for conducting future research in this area.
Type of paper: Viewpoint |
| first_indexed | 2025-02-19T01:16:03Z |
| format | Conference or Workshop Item |
| id | oai:repository.londonmet.ac.uk:9764 |
| institution | London Metropolitan University |
| language | English |
| last_indexed | 2025-02-19T01:16:03Z |
| publishDate | 2024 |
| publisher | European Facility Management Network (EuroFM) |
| record_format | eprints |
| spelling | oai:repository.londonmet.ac.uk:97642024-10-28T12:52:40Z https://repository.londonmet.ac.uk/9764/ Big data analytics in facilities management higher education: a way forward Sumanarathna, Nipuni Dahanayake, Kalani C. Adhikari, Aravinda 000 Computer science, information & general works 370 Education 620 Engineering & allied operations 650 Management & auxiliary services 690 Buildings Background and aim: In this digital era, the facilities management (FM) industry tends to apply Big Data analytics (BDA), employing machine learning for functions such as predictive maintenance, energy management and workplace management. Therefore, it is essential to discuss the digital transformation of facilities management higher education (FMHE) and the requirements for FMHE to be future-proof. This paper aims to explore the extent to which BDA is applied in FM and how it is manifested within FMHE. Methods: This viewpoint paper is developed based on the industry, academic and research experience of the authors. Prior literature findings are also incorporated to develop and support the views regarding the application of BDA in the industry and its representation in FMHE. Results: Based on the experiential learning perspective, recommendations for BDA-related teaching and learning in FMHE are delivered. Originality: This study addresses the potential gaps between the FM industry and higher education by discussing the advanced approaches which have not yet been extensively recognised in FMHE. Hence, this paper contributes to developing new FM capabilities among students within the context of digital transformation in FM. Practical or social implications: The recommendations derived from the experiential learning perspective add depth to the discussion, offering suggestions for understanding and advancing FMHE. This study can also serve as a guide for conducting future research in this area. Type of paper: Viewpoint European Facility Management Network (EuroFM) 2024-06 Conference or Workshop Item PeerReviewed text en cc_by_nd_4 https://repository.londonmet.ac.uk/9764/1/Big%20data%20analytics%20in%20facilities%20management%20higher%20education%20A%20way%20forward.pdf Sumanarathna, Nipuni, Dahanayake, Kalani C. and Adhikari, Aravinda (2024) Big data analytics in facilities management higher education: a way forward. In: 23rd EuroFM Research Symposium, June 10-12, 2024, London Metropolitan University, London (UK). https://www.doi.org/10.5281/zenodo.11658176 10.5281/zenodo.11658176 10.5281/zenodo.11658176 |
| spellingShingle | 000 Computer science, information & general works 370 Education 620 Engineering & allied operations 650 Management & auxiliary services 690 Buildings Sumanarathna, Nipuni Dahanayake, Kalani C. Adhikari, Aravinda Big data analytics in facilities management higher education: a way forward |
| title | Big data analytics in facilities management higher education:
a way forward |
| title_full | Big data analytics in facilities management higher education:
a way forward |
| title_fullStr | Big data analytics in facilities management higher education:
a way forward |
| title_full_unstemmed | Big data analytics in facilities management higher education:
a way forward |
| title_short | Big data analytics in facilities management higher education:
a way forward |
| title_sort | big data analytics in facilities management higher education a way forward |
| topic | 000 Computer science, information & general works 370 Education 620 Engineering & allied operations 650 Management & auxiliary services 690 Buildings |
| url | https://repository.londonmet.ac.uk/9764/1/Big%20data%20analytics%20in%20facilities%20management%20higher%20education%20A%20way%20forward.pdf |
| work_keys_str_mv | AT sumanarathnanipuni bigdataanalyticsinfacilitiesmanagementhighereducationawayforward AT dahanayakekalanic bigdataanalyticsinfacilitiesmanagementhighereducationawayforward AT adhikariaravinda bigdataanalyticsinfacilitiesmanagementhighereducationawayforward |