World's Best Scientists 2026 revealed!

D-Index & Metrics

Business and Management

D-Index
31
Citations
5585
World Ranking
2779
National Ranking
454

Hakeem A. Owolabi publication distribution in Business and Management in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Business and Management in 2026. The highlighted bar marks where Hakeem A. Owolabi sits on this spectrum.

35–39 publications: 2 scientists 40–44 publications: 2 scientists 45–49 publications: 5 scientists 50–54 publications: 20 scientists 55–59 publications: 39 scientists 60–64 publications: 66 scientists 65–69 publications: 52 scientists 70–74 publications: 80 scientists 75–79 publications: 83 scientists 80–84 publications: 116 scientists 85–89 publications: 94 scientists 90–94 publications: 111 scientists 95–99 publications: 122 scientists 100–104 publications: 104 scientists 105–109 publications: 113 scientists 110–114 publications: 96 scientists 115–119 publications: 97 scientists 120–124 publications: 112 scientists 125–129 publications: 93 scientists 130–134 publications: 79 scientists 135–139 publications: 69 scientists 140–144 publications: 80 scientists 145–149 publications: 81 scientists 150–154 publications: 85 scientists 155–159 publications: 50 scientists 160–164 publications: 74 scientists 165–169 publications: 61 scientists 170–174 publications: 40 scientists 175–179 publications: 44 scientists 180–184 publications: 47 scientists 185–189 publications: 59 scientists 190–194 publications: 35 scientists 195–199 publications: 37 scientists 200–204 publications: 49 scientists 205–209 publications: 48 scientists 210–214 publications: 34 scientists 215–219 publications: 31 scientists 220–224 publications: 37 scientists 225–229 publications: 34 scientists 230–234 publications: 25 scientists 235–239 publications: 28 scientists 240–244 publications: 34 scientists 245–249 publications: 28 scientists 250–254 publications: 23 scientists 255–259 publications: 22 scientists 260–264 publications: 11 scientists 265–269 publications: 16 scientists 270–274 publications: 23 scientists 275–279 publications: 12 scientists 280–284 publications: 16 scientists 285–289 publications: 10 scientists 290–294 publications: 12 scientists 295–299 publications: 12 scientists 300–304 publications: 8 scientists 305–309 publications: 13 scientists 310–314 publications: 13 scientists 315–319 publications: 6 scientists 320–324 publications: 10 scientists 325–329 publications: 9 scientists 330–334 publications: 7 scientists 335–339 publications: 10 scientists 340–344 publications: 10 scientists 345–349 publications: 7 scientists 350–354 publications: 4 scientists 355–359 publications: 10 scientists 360–364 publications: 3 scientists 365–369 publications: 7 scientists 370–374 publications: 2 scientists 375–379 publications: 8 scientists 380–384 publications: 4 scientists 385–389 publications: 5 scientists 390–394 publications: 5 scientists 395–399 publications: 2 scientists 400–404 publications: 2 scientists 405–409 publications: 4 scientists 410–414 publications: 3 scientists 415–419 publications: 2 scientists 420–424 publications: 5 scientists 425–429 publications: 3 scientists 430–434 publications: 1 scientists 435 publications: 1 scientists 436+ publications: 100 scientists
35 publications 436+

This scientist: 49 publications — 1st percentile

1% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 436 publications or more.

Hakeem A. Owolabi D-index placement in Business and Management in 2026

The chart shows the D-index (discipline H-index) distribution of Business and Management scientists ranked by Research.com in 2026. The highlighted bar marks where Hakeem A. Owolabi sits on this spectrum.

30 D-Index: 156 scientists 31 D-Index: 159 scientists 32 D-Index: 171 scientists 33 D-Index: 161 scientists 34 D-Index: 135 scientists 35 D-Index: 124 scientists 36 D-Index: 114 scientists 37 D-Index: 111 scientists 38 D-Index: 103 scientists 39 D-Index: 89 scientists 40 D-Index: 81 scientists 41 D-Index: 97 scientists 42 D-Index: 80 scientists 43 D-Index: 69 scientists 44 D-Index: 68 scientists 45 D-Index: 63 scientists 46 D-Index: 54 scientists 47 D-Index: 69 scientists 48 D-Index: 50 scientists 49 D-Index: 58 scientists 50 D-Index: 54 scientists 51 D-Index: 62 scientists 52 D-Index: 54 scientists 53 D-Index: 43 scientists 54 D-Index: 49 scientists 55 D-Index: 35 scientists 56 D-Index: 40 scientists 57 D-Index: 44 scientists 58 D-Index: 34 scientists 59 D-Index: 29 scientists 60 D-Index: 48 scientists 61 D-Index: 32 scientists 62 D-Index: 30 scientists 63 D-Index: 22 scientists 64 D-Index: 22 scientists 65 D-Index: 19 scientists 66 D-Index: 20 scientists 67 D-Index: 18 scientists 68 D-Index: 17 scientists 69 D-Index: 21 scientists 70 D-Index: 20 scientists 71 D-Index: 19 scientists 72 D-Index: 14 scientists 73 D-Index: 10 scientists 74 D-Index: 16 scientists 75 D-Index: 24 scientists 76 D-Index: 13 scientists 77 D-Index: 19 scientists 78 D-Index: 8 scientists 79 D-Index: 6 scientists 80 D-Index: 4 scientists 81 D-Index: 12 scientists 82 D-Index: 7 scientists 83 D-Index: 7 scientists 84 D-Index: 6 scientists 85 D-Index: 10 scientists 86 D-Index: 4 scientists 87 D-Index: 11 scientists 88 D-Index: 6 scientists 89+ D-Index: 96 scientists
30 D-Index 89+

This scientist: 31 D-Index — 10th percentile

10% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 89 D-Index or more.

Best Publications

  • Big Data in the construction industry

    Muhammad Bilal;Lukumon O. Oyedele;Junaid Qadir;Kamran Munir

  • Robotics and automated systems in construction: Understanding industry-specific challenges for adoption

    Juan Manuel Davila Delgado;Lukumon Oyedele;Anuoluwapo Ajayi;Lukman Akanbi

  • Cloud computing in construction industry: Use cases, benefits and challenges

    Sururah A. Bello;Lukumon O. Oyedele;Olugbenga O. Akinade;Muhammad Bilal

  • Systematic Review of Bankruptcy Prediction Models: Towards A Framework for Tool Selection

    Hafiz A. Alaka;Lukumon O. Oyedele;Hakeem A. Owolabi;Vikas Kumar

  • Waste effectiveness of the construction industry: Understanding the impediments and requisites for improvements

    Saheed O. Ajayi;Lukumon O. Oyedele;Muhammad Bilal;Olugbenga O. Akinade

  • Waste minimisation through deconstruction: A BIM based Deconstructability Assessment Score (BIM-DAS)

    Olugbenga O. Akinade;Lukumon O. Oyedele;Muhammad Bilal;Saheed O. Ajayi

  • Design for Deconstruction (DfD): Critical success factors for diverting end-of-life waste from landfills.

    Olugbenga O Akinade;Lukumon O Oyedele;Saheed O Ajayi;Muhammad Bilal

  • Designing out construction waste using BIM technology: Stakeholders’ expectations for industry deployment

    Olugbenga O. Akinade;Lukumon O. Oyedele;Saheed O. Ajayi;Muhammad Bilal

  • Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy

    Lukman A. Akanbi;Lukman A. Akanbi;Lukumon O. Oyedele;Kamil Omoteso;Muhammad Bilal

  • Critical management practices influencing on-site waste minimization in construction projects.

    Saheed O. Ajayi;Lukumon O. Oyedele;Muhammad Bilal;Olugbenga O. Akinade

  • Big data architecture for Construction Waste Analytics (CWA): A conceptual framework

    Muhammad Bilal;Lukumon O. Oyedele;Olugbenga O. Akinade;Saheed O. Ajayi

  • Reducing waste to landfill: A need for cultural change in the UK construction industry

    Saheed O. Ajayi;Lukumon O. Oyedele;Olugbenga O. Akinade;Muhammad Bilal

  • Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings

    X.J. Luo;Lukumon O. Oyedele;Anuoluwapo O. Ajayi;Olugbenga O. Akinade

  • Design for deconstruction using a circular economy approach: barriers and strategies for improvement

    Olugbenga Akinade;Lukumon Oyedele;Ahmed Oyedele;Juan Manuel Davila Delgado

  • BIM-based deconstruction tool: Towards essential functionalities

    Olugbenga O. Akinade;Lukumon O. Oyedele;Kamil Omoteso;Saheed O. Ajayi

  • Optimising material procurement for construction waste minimization: An exploration of success factors

    Saheed O. Ajayi;Lukumon O. Oyedele;Olugbenga O. Akinade;Muhammad Bilal

  • Analysis of critical features and evaluation of BIM software: Towards a plug-in for construction waste minimization using big data

    Muhammad Bilal;Lukumon O. Oyedele;Junaid Qadir;Kamran Munir

  • Attributes of design for construction waste minimization: A case study of waste-to-energy project

    Saheed O. Ajayi;Lukumon O. Oyedele;Olugbenga O. Akinade;Muhammad Bilal

  • Deep Learning Models for Health and Safety Risk Prediction in Power Infrastructure Projects

    Anuoluwapo Ajayi;Lukumon Oyedele;Hakeem Owolabi;Olugbenga Akinade

  • Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings

    X.J. Luo;Lukumon O. Oyedele;Anuoluwapo O. Ajayi;Olugbenga O. Akinade

Frequent Co-Authors

Junaid Qadir
Junaid Qadir Information Technology University
V Kumar
V Kumar Brock University

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