Assessing Technological Sophistication of Energy Distribution Warehouses Using a Technometric Framework
DOI:
https://doi.org/10.12928/si.v24i2.653Keywords:
Technometric, Technology contribution Coefficient (TCC), Warehouse energy Distribution, Warehouse technologyAbstract
Warehousing plays a critical role in energy distribution systems, where operational reliability depends on technological sophistication. However, structured and quantitative approaches for assessing technological capability in energy distribution warehouses remain limited. This study aims to evaluate the technological sophistication of a real-world energy distribution warehouse using a technometric-based measurement instrument. The novelty of this research lies in the empirical application of a specialized technometric instrument for multidimensional warehouse technology assessment. A quantitative case study approach was employed using five assessment components: warehouse facility, warehouse operation, warehouse maintenance, warehouse product, and warehouse human and organization. Technological sophistication was evaluated using State of the Art (SOTA), component contribution, and Technology Contribution Coefficient (TCC) analyses. The results showed a TCC value of 0.456, indicating a semi-modern level of technological sophistication. The findings reveal an imbalance in technological development across warehouse components and identify priority areas for improvement. This study demonstrates the usefulness of technometric assessment in supporting technology development and modernization planning in energy distribution warehouses.
References
Ali, S. S., & Kaur, R. (2022). Exploring the impact of technology 4.0 driven practice on warehousing performance: a hybrid approach. In Mathematics. https://doi.org/10.3390/math10081252
Atikah, N. (2020). Analisis Kemampuan Industri Solar Panel di Indonesia. etd.repository.ugm.ac.id. https://etd.repository.ugm.ac.id/penelitian/detail/194060
Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: a literature review. International Journal of Production Research. https://doi.org/10.1080/00207543.2017.1402140
Boysen, N., Koster, R. De, & Weidinger, F. (2019). Warehousing in the e-commerce era: A survey. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2018.08.023
Ellithy, K., Salah, M., Fahim, I. S., & Shalaby, R. (2024). AGV and Industry 4.0 in warehouses: a comprehensive analysis of existing literature and an innovative framework for flexible automation. In The International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-024-14127-0
Esmaeilion, F., Soltani, M., & Luna-Triguero, A. (2025). Soft computing optimization of a renewable energy-integrated multigeneration system with liquid air energy storage. In Journal of Energy Storage. https://doi.org/10.1016/j.est.2025.117140
Facchini, F., Oleskow-Szlapka, J., Ranieri, L., & Urbinati, A. (2019). A maturity model for logistics 4.0: An empirical analysis and a roadmap for future research. In Sustainability. https://doi.org/10.3390/su12010086
Gu, J., Goetschalckx, M., & McGinnis, L. F. (2007). Research on warehouse operation: A comprehensive review. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2006.02.025
Haines, J. D., & Sharif, N. M. (2006). A framework for managing the sophistication of the components of technology for global competition. Competitiveness Review an International Business Journal incorporating. https://doi.org/10.1108/10595420610760888
International Energy Agency. (2020). Power systems in transition Challenges and opportunities ahead for electricity security.
Karunarathna, N., Vidanagamachchi, K., & Wickramarachchi, R. (2020). A calibrated model of critical success factors for Industry 4.0 warehousing performance improvement: Insights from multiple case studies. In International Journal of Multidisciplinary Sciences and Advanced Technology.
Kisanjani, A., Andivas, M., & Hirwandi, H. (2026). Six Sigma-Based Quality Management Strategy to Enhance the Competitiveness of Food Souvenir MSMEs in East Kalimantan. Spektrum Industri. https://doi.org/10.12928/si.v24i1.521
Le, T. S., Nguyen, T. N., Bui, D. K., & Ngo, T. D. (2023). Optimal sizing of renewable energy storage: A techno-economic analysis of hydrogen, battery and hybrid systems considering degradation and seasonal storage. In Applied Energy. Elsevier. https://doi.org/10.1016/j.apenergy.2023.120817
Liu, L., Zhang, S., Zhang, H., Zhang, Z., & Liu, Y. (2024). Optimal scheduling study of green warehousing microgrid based on improved sparrow search algorithm. In Frontiers in Energy Research. frontiersin.org. https://doi.org/10.3389/fenrg.2024.1383376
Lu, Z., Wang, P., & Zhang, X. (2024). Research on irregular warehouse layout based on optimised genetic algorithm. Promet-Traffic&Transportation. https://hrcak.srce.hr/clanak/460550
Piratelo, P. H. M., Azeredo, R. N. de, Yamao, E. M., & Leandro, G. V. (2021). Blending colored and depth cnn pipelines in an ensemble learning classification approach for warehouse application using synthetic and real data. In Machines. https://doi.org/10.3390/machines10010028
Ribeiro, A., Carmo, P. R. X. do, Endo, P. T., Rosati, P., & Lynn, T. G. (2022). Short-and very short-term firm-level load forecasting for warehouses: A comparison of machine learning and deep learning models. In Energies. https://doi.org/10.20944/preprints202201.0107.v1
Sharif, M. N. (2012). Technological innovation governance for winning the future. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2011.12.004
Sharif, M. N., & Bowonder, B. (1987). Components of technology for resources transformation. In Technological Forecasting and Social Change. https://doi.org/10.1016/0040-1625(87)90004-7
Sharif, N. (1994). Project evaluation framework for industrial technology capacity enhancement. Technology Analysis &Strategic Management. https://doi.org/10.1080/09537329408524153
Sharif, N., & Ramanathan, K. (1991). Measuring contribution of technology for policy analysis. In The 9th International Conference of the System.
Strom, E. M., Busch, J. A., Hvam, L., & Haug, A. (2025). Conceptualizing warehouse 4.0 technologies in the third-party logistics industry: An empirical study. In Logistics. https://doi.org/10.3390/logistics9030125
Sukma, F. H., Handayani, E. T., & Supriyono, S. (2023). Technological capabilities assessment by using Technometrics models in routine maintenance of commuter trains to increase service performance. SINERGI. https://doi.org/10.22441/sinergi.2023.1.007
Tikwayo, L. N., & Mathaba, T. N. D. (2023). Applications of industry 4.0 technologies in warehouse management: A systematic literature review. In Logistics. https://doi.org/10.3390/logistics7020024
Tiwari, S. (2023). Smart warehouse: A bibliometric analysis and future research direction. In Sustainable Manufacturing and Service Economics. https://doi.org/10.1016/j.smse.2023.100014
Tubis, A. A., & Rohman, J. (2023). Intelligent warehouse in industry 4.0—systematic literature review. In Sensors. https://doi.org/10.3390/s23084105
Utama, D. M., & Salsabilah, A. L. (2025). Optimizing Green Vehicle Routing Problem for Halal and Non-Halal Products using Salp Swarm Algorithm. Spektrum Industri. https://doi.org/10.12928/si.v23i2.413
Winkelhaus, S., & Grosse, E. H. (2020). Logistics 4.0: a systematic review towards a new logistics system. International Journal of Production Research. https://doi.org/10.1080/00207543.2019.1612964
Zhang, X., Mo, T., & Zhang, Y. (2023). Optimization of storage location assignment for non-traditional layout warehouses based on the firework algorithm. In Sustainability. https://doi.org/10.3390/su151310242
Zoubek, M., & Simon, M. (2021). A Framework for A Logistics 4.0 Maturity Model with A Specification for Internal Logistics. In MM Science Journal. https://doi.org/10.17973/MMSJ.2021_03_2020073
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Putri Khosuma, Alva Edy Tontowi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
.png)
