Managerial opportunities in application of business intelligence in construction companies
Abstract
In construction projects, managers make multiple decisions every day. Most of these decisions are relatively unimportant; some of them are critical and could lead to the success or failure of a construction project. To ensure construction companies make effective managerial decisions, decision making requires performing an initial technical and economic analysis, comparing different decision-making solutions, using a planning system, and ensuring project implementation based on the provided plans. Therefore, the use of powerful systems such as business intelligence (BI), which play a central role in management and decision-making, is essential in project-based companies. The current study aims to determine and evaluate the main managerial opportunities in the application of BI in project-based construction companies using a descriptive survey approach. An empirical research questionnaire consisting of 60 factors and 7 categories was adopted. The questionnaire, after confirming its validity and reliability, was distributed to 100 experts engaged in 5 active project-based construction companies who were familiar with BI topics. To analyse the data, a one-sample t-test and the Friedman test were performed using the SPSS software. The findings indicated that the importance of the identified opportunities for the use of BI in project-based construction companies is above average and that, in the case of using BI in such companies, these opportunities can be used to improve project performance. The results of the current study can help managers and other stakeholders as an effective decision-making tool to better implement BI in project-based companies.
Keyword : business intelligence, construction companies, construction project, project-based companies
How to Cite
Golestanizadeh, M., Sarvari, H., Chan, D. W. M., Banaitienė, N., & Banaitis, A. (2023). Managerial opportunities in application of business intelligence in construction companies. Journal of Civil Engineering and Management, 29(6), 487–500. https://doi.org/10.3846/jcem.2023.19533
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Abubakar, A. M., Elrehail, H., Alatailat, M. A., & Elçi, A. (2019). Knowledge management, decision-making style and organizational performance. Journal of Innovation & Knowledge, 4(2), 104–114. https://doi.org/10.1016/j.jik.2017.07.003
Abusweilem, M. A., & Abualous, S. (2019). The impact of knowledge management process and business intelligence on organizational performance. Management Science Letters, 9, 2143–2156. https://doi.org/10.5267/j.msl.2019.6.020
Akcay, E. C. (2021). An analytic network process based risk assessment model for PPP hydropower investments. Journal of Civil Engineering and Management, 27(4), 268–277. https://doi.org/10.3846/jcem.2021.14650
Amini, M., Salimi, S., Yousefinejad, F., Tarokh, M. J., & Haybatollahi, S. M. (2021). The implication of business intelligence in risk management: A case study in agricultural insurance. Journal of Data, Information and Management, 3(2), 155–166. https://doi.org/10.1007/s42488-021-00050-6
Azma, F., & Mostafapour, M. A. (2012). Business intelligence as a key strategy for development organizations. Procedia Technology, 1, 102–106. https://doi.org/10.1016/j.protcy.2012.02.020
Balachandran, B. M., & Prasad, S. (2017). Challenges and benefits of deploying big data analytics in the cloud for business intelligence. Procedia Computer Science, 112, 1112–1122. https://doi.org/10.1016/j.procs.2017.08.138
Bose, R. (2009). Advanced analytics: Opportunities and challenges. Industrial Management & Data Systems, 109(2), 155–172. https://doi.org/10.1108/02635570910930073
Brichni, M., Dupuy-Chessa, S., Gzara, L., Mandran, N., & Jeannet, C. (2017). BI4BI: A continuous evaluation system for business intelligence systems. Expert Systems with Applications, 76, 97–112. https://doi.org/10.1016/j.eswa.2017.01.018
Cataldo, I., Banaitis, A., Samadhiya, A., Banaitienė, N., Kumar, A., & Luthra, S. (2022). Sustainable supply chain management in construction: An exploratory review for future research. Journal of Civil Engineering and Management, 28(7), 536–553. https://doi.org/10.3846/jcem.2022.17202
Chen, Y., & Lin, Z. (2021). Business intelligence capabilities and firm performance: A study in China. International Journal of Information Management, 57, 102232. https://doi.org/10.1016/j.ijinfomgt.2020.102232
Cheng, C., Zhong, H., & Cao, L. (2020). Facilitating speed of internationalization: The roles of business intelligence and organizational agility. Journal of Business Research, 110, 95–103. https://doi.org/10.1016/j.jbusres.2020.01.003
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In Modern methods for business research (pp. 295–358). Lawrence Erlbaum Associates.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed). Lawrence Erlbaum Associates.
Cova, S., Andrade, C., Soares, O., & Lopes, J. (2021). Evaluation of cost-optimal retrofit investment in buildings: The case of Bragança fire station, Portugal. International Journal of Strategic Property Management, 25(5), 369–381. https://doi.org/10.3846/ijspm.2021.15082
Djatna, T., & Munichputranto, F. (2015). An analysis and design of mobile business intelligence system for productivity measurement and evaluation in tire curing production line. Procedia Manufacturing, 4, 438–444. https://doi.org/10.1016/j.promfg.2015.11.060
Djerdjouri, M. (2019). Data and business intelligence systems for competitive advantage: Prospects, challenges, and real-world applications. Mercados y Negocios, 41, 5–18. https://doi.org/10.32870/myn.v0i41.7537
Fadhil, G. A., & Burhan, A. M. (2021). Investigating the effects of economic crisis on construction projects in Iraq. E3S Web of Conferences, 318, 02005. https://doi.org/10.1051/e3sconf/202131802005
Fenstad, J., Dahl, Ø., & Kongsvik, T. (2016). Shipboard safety: Exploring organizational and regulatory factors. Maritime Policy & Management, 43(5), 552–568. https://doi.org/10.1080/03088839.2016.1154993
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Gad-Elrab, A. (2021). Modern business intelligence: Big data analytics and artificial intelligence for creating the data-driven value. In R. M. X. Wu & M. Mircea (Eds.), E-business. Higher education and intelligence applications. IntechOpen. https://doi.org/10.5772/intechopen.97374
Girsang, A. S., Isa, S. M., Saputra, H., Nuriawan, M. A., Ghozali, R. P., & Kaburuan, E. R. (2018). Business intelligence for construction company acknowledgement reporting system. In 2018 Indonesian Association for Pattern Recognition International Conference (INAPR) (pp. 113–122), Jakarta, Indonesia. IEE. https://doi.org/10.1109/INAPR.2018.8627012
Golestanizadeh, M., Sarvari, H., Cristofaro, M., & Chan, D. W. M. (2023). Effect of applying business intelligence on export development and brand internationalization in large industrial firms. Administrative Sciences, 13(2), 27. https://doi.org/10.3390/admsci13020027
Gudfinnsson, K., Strand, M., & Berndtsson, M. (2015). Analyzing business intelligence maturity. Journal of Decision Systems, 24(1), 37–54. https://doi.org/10.1080/12460125.2015.994287
Hajiani, M., Azizi, M., Eshtehardian, E., & Naseh, K. (2018). Exploring the challenges of financing Iran’s construction projects from China and providing improvement solutions. Civil Engineering Journal, 4(7), 1689. https://doi.org/10.28991/cej-03091105
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R. R. Sinkovics & P. N. Ghauri (Eds.), Advances in international marketing (vol. 20, pp. 277–319). Emerald Group Publishing Limited. https://doi.org/10.1108/S1474-7979(2009)0000020014
Hock, M., & Ringle, C. M. (2010). Local strategic networks in the software industry: An empirical analysis of the value continuum. International Journal of Knowledge Management Studies, 4(2), 132. https://doi.org/10.1504/IJKMS.2010.030789
Hosseinzadeh, S., Rostamzadeh, R., Saparauskas, J., & Kersuliene, V. (2022). The influence of innovation and marketing strategy on the market-oriented activities of the company in cement industry: The decisive role of environmental dynamics. Acta Montanistica Slovaca, 26, 748–760. https://doi.org/10.46544/AMS.v26i4.12
Huynh, T. T.-M., Pham, A.-D., & Le-Hoai, L. (2021). Building a strategic performance management model for enterprises investing to coastal urban projects toward sustainability. International Journal of Strategic Property Management, 25(2), 127–145. https://doi.org/10.3846/ijspm.2021.14298
Işik, M., Yarar, O., & Söylemez Sur, D. (2021). Measurement of the effects of business intelligence applications on performance in hospitals according to the managerial levels: A chain hospital application. Journal of International Health Sciences and Management, 7(13), 97–108. https://doi.org/10.48121/jihsam.776109
Kowalczyk, M., & Buxmann, P. (2015). An ambidextrous perspective on business intelligence and analytics support in decision processes: Insights from a multiple case study. Decision Support Systems, 80, 1–13. https://doi.org/10.1016/j.dss.2015.08.010
Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x
Lopes, A. B., & Boscarioli, C. (2020). Business intelligence and analytics to support management in construction: A systematic literature review. Revista Brasileira de Computação Aplicada, 13(1), 27–41. https://doi.org/10.5335/rbca.v13i1.11346
Luo, Q., Gao, R., Liu, J., & Li, Y. (2022). Path analysis on escalation of commitment of investors in different project scenarios of PPPs. International Journal of Strategic Property Management, 26(2), 127–140. https://doi.org/10.3846/ijspm.2022.16477
Mai, A. N., Vu, H. V., Bui, B. X., & Tran, T. Q. (2019). The lasting effects of innovation on firm profitability: Panel evidence from a transitional economy. Economic Research-Ekonomska Istraživanja, 32(1), 3417–3436. https://doi.org/10.1080/1331677X.2019.1660199
Mandičák, T., Behúnová, A., & Mesároš, P. (2016). Impact of implementation and use of business intelligence on cost reducing in construction project management. Acta Tecnología, 2(3), 5–11. https://doi.org/10.22306/atec.v2i3.14
Moss, E., Rousseau, D., Parent, S., St-Laurent, D., & Saintonge, J. (2008). Correlates of attachment at school age: Maternal reported stress, mother-child interaction, and behavior problems. Child Development, 69(5), 1390–1405. https://doi.org/10.1111/j.1467-8624.1998.tb06219.x
Musarat, M. A., Alaloul, W. S., & Liew, M. S. (2021). Impact of inflation rate on construction projects budget: A review. Ain Shams Engineering Journal, 12(1), 407–414. https://doi.org/10.1016/j.asej.2020.04.009
Naz, F., Kumar, A., Upadhyay, A., Chokshi, H., Trinkūnas, V., & Magda, R. (2022). Property management enabled by artificial intelligence post Covid-19: An exploratory review and future propositions. International Journal of Strategic Property Management, 26(2), 156–171. https://doi.org/10.3846/ijspm.2022.16923
Ndekugri, I., Braimah, N., & Gameson, R. (2008). Delay analysis within construction contracting organizations. Journal of Construction Engineering and Management, 134(9), 692–700. https://doi.org/10.1061/(ASCE)0733-9364(2008)134:9(692)
Niwash, M. N. K., Cek, K., & Eyupoglu, S. Z. (2022). Intellectual capital and competitive advantage and the mediation effect of innovation quality and speed, and business intelligence. Sustainability, 14(6), 3497. https://doi.org/10.3390/su14063497
Pande, C., Witschel, H. F., & Martin, A. (2022). New hybrid techniques for business recommender systems. Applied Sciences, 12(10), 4804. https://doi.org/10.3390/app12104804
Pantouvakis, A., Chlomoudis, C., & Dimas, A. (2008). Testing the SERVQUAL scale in the passenger port industry: A confirmatory study. Maritime Policy & Management, 35(5), 449–467. https://doi.org/10.1080/03088830802352095
Paradza, D., & Daramola, O. (2021). Business intelligence and business value in organisations: A systematic literature review. Sustainability, 13(20), 11382. https://doi.org/10.3390/su132011382
Petrini, M., & Pozzebon, M. (2009). Managing sustainability with the support of business intelligence: Integrating socio-environmental indicators and organisational context. The Journal of Strategic Information Systems, 18(4), 178–191. https://doi.org/10.1016/j.jsis.2009.06.001
Pondel, J., & Pondel, M. (2016). The concept of project management platform using BI and big data technology. In Proceedings of the 18th International Conference on Enterprise Information Systems (pp. 166–173), Rome, Italy. https://doi.org/10.5220/0005834601660173
Rausch, P., & Stumpf, M. (2013). Linking the operational, tactical and strategic levels by means of CPM: An example in the construction industry. In P. Rausch, A. F. Sheta, & A. Ayesh (Eds.), Business intelligence and performance management (pp. 27–42). Springer London. https://doi.org/10.1007/978-1-4471-4866-1_3
Rubin, A., & Babbie, E. R. (2017). Research methods for social work (9th ed.). Cengage Learning.
Rud, O. P. (2009). Business intelligence success factors: Tools for aligning your business in the global economy. Wiley & Sons.
Sabherwal, R., & Becerra-Fernandez, I. (2011). Business intelligence: Practices, technologies, and management. Wiley.
Sarvari, H., Cristofaro, M., Chan, D. W. M., Noor, N. Md., & Amini, M. (2020). Completing abandoned public facility projects by the private sector: Results of a Delphi survey in the Iranian water and wastewater company. Journal of Facilities Management, 18(5), 547–566. https://doi.org/10.1108/JFM-07-2020-0046
Sindhwani, R., Afridi, S., Kumar, A., Banaitis, A., Luthra, S., & Singh, P. L. (2022). Can industry 5.0 revolutionize the wave of resilience and social value creation? A multi-criteria framework to analyze enablers. Technology in Society, 68, 101887. https://doi.org/10.1016/j.techsoc.2022.101887
Taherdoost, H. (2016). Validity and reliability of the research instrument; How to test the validation of a questionnaire/survey in a research. SSRN. https://doi.org/10.2139/ssrn.3205040
Thanos, I. C. (2023). The complementary effects of rationality and intuition on strategic decision quality. European Management Journal, 41(3), 366–374. https://doi.org/10.1016/j.emj.2022.03.003
Turban, E. (2015). Business intelligence and analytics: Systems for decision support (10th ed.). Pearson.
Turban, E., Sharda, R., & Delen, D. (2011). Decision support and business intelligence systems (9th ed). Prentice Hall.
Uçaktürk, A., Uçaktürk, T., & Yavuz, H. (2015). Possibilities of usage of strategic business intelligence systems based on databases in Agile manufacturing. Procedia - Social and Behavioral Sciences, 207, 234–241. https://doi.org/10.1016/j.sbspro.2015.10.092
Werts, C. E., Linn, R. L., & Jöreskog, K. G. (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), 25–33. https://doi.org/10.1177/001316447403400104
Wetzels, M., Odekerken-Schröder, G., & van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 33(1), 177. https://doi.org/10.2307/20650284
Wieder, B., & Ossimitz, M.-L. (2015). The impact of business intelligence on the quality of decision making – A mediation model. Procedia Computer Science, 64, 1163–1171. https://doi.org/10.1016/j.procs.2015.08.599
Williams, S., & Williams, N. (2007). The profit impact of business intelligence. Elsevier. https://doi.org/10.1016/B978-0-12-372499-1.X5000-5
World Economic Forum. (2016). Shaping the future of construction: A breakthrough in mindset and technology. https://www3.weforum.org/docs/WEF_Shaping_the_Future_of_Construction_full_report__.pdf
Wu, D. D., Chen, S.-H., & Olson, D. L. (2014). Business intelligence in risk management: Some recent progresses. Information Sciences, 256, 1–7. https://doi.org/10.1016/j.ins.2013.10.008
Xie, H., Ge, Y., & Yi, J. (2022). Cost control analysis of construction projects based on wireless communication and artificial intelligence decisions. Wireless Communications and Mobile Computing, 2022, 8505922. https://doi.org/10.1155/2022/8505922
Zhu, X., Meng, X., & Zhang, M. (2021). Application of multiple criteria decision making methods in construction: A systematic literature review. Journal of Civil Engineering and Management, 27(6), 372–403. https://doi.org/10.3846/jcem.2021.15260
Abusweilem, M. A., & Abualous, S. (2019). The impact of knowledge management process and business intelligence on organizational performance. Management Science Letters, 9, 2143–2156. https://doi.org/10.5267/j.msl.2019.6.020
Akcay, E. C. (2021). An analytic network process based risk assessment model for PPP hydropower investments. Journal of Civil Engineering and Management, 27(4), 268–277. https://doi.org/10.3846/jcem.2021.14650
Amini, M., Salimi, S., Yousefinejad, F., Tarokh, M. J., & Haybatollahi, S. M. (2021). The implication of business intelligence in risk management: A case study in agricultural insurance. Journal of Data, Information and Management, 3(2), 155–166. https://doi.org/10.1007/s42488-021-00050-6
Azma, F., & Mostafapour, M. A. (2012). Business intelligence as a key strategy for development organizations. Procedia Technology, 1, 102–106. https://doi.org/10.1016/j.protcy.2012.02.020
Balachandran, B. M., & Prasad, S. (2017). Challenges and benefits of deploying big data analytics in the cloud for business intelligence. Procedia Computer Science, 112, 1112–1122. https://doi.org/10.1016/j.procs.2017.08.138
Bose, R. (2009). Advanced analytics: Opportunities and challenges. Industrial Management & Data Systems, 109(2), 155–172. https://doi.org/10.1108/02635570910930073
Brichni, M., Dupuy-Chessa, S., Gzara, L., Mandran, N., & Jeannet, C. (2017). BI4BI: A continuous evaluation system for business intelligence systems. Expert Systems with Applications, 76, 97–112. https://doi.org/10.1016/j.eswa.2017.01.018
Cataldo, I., Banaitis, A., Samadhiya, A., Banaitienė, N., Kumar, A., & Luthra, S. (2022). Sustainable supply chain management in construction: An exploratory review for future research. Journal of Civil Engineering and Management, 28(7), 536–553. https://doi.org/10.3846/jcem.2022.17202
Chen, Y., & Lin, Z. (2021). Business intelligence capabilities and firm performance: A study in China. International Journal of Information Management, 57, 102232. https://doi.org/10.1016/j.ijinfomgt.2020.102232
Cheng, C., Zhong, H., & Cao, L. (2020). Facilitating speed of internationalization: The roles of business intelligence and organizational agility. Journal of Business Research, 110, 95–103. https://doi.org/10.1016/j.jbusres.2020.01.003
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In Modern methods for business research (pp. 295–358). Lawrence Erlbaum Associates.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed). Lawrence Erlbaum Associates.
Cova, S., Andrade, C., Soares, O., & Lopes, J. (2021). Evaluation of cost-optimal retrofit investment in buildings: The case of Bragança fire station, Portugal. International Journal of Strategic Property Management, 25(5), 369–381. https://doi.org/10.3846/ijspm.2021.15082
Djatna, T., & Munichputranto, F. (2015). An analysis and design of mobile business intelligence system for productivity measurement and evaluation in tire curing production line. Procedia Manufacturing, 4, 438–444. https://doi.org/10.1016/j.promfg.2015.11.060
Djerdjouri, M. (2019). Data and business intelligence systems for competitive advantage: Prospects, challenges, and real-world applications. Mercados y Negocios, 41, 5–18. https://doi.org/10.32870/myn.v0i41.7537
Fadhil, G. A., & Burhan, A. M. (2021). Investigating the effects of economic crisis on construction projects in Iraq. E3S Web of Conferences, 318, 02005. https://doi.org/10.1051/e3sconf/202131802005
Fenstad, J., Dahl, Ø., & Kongsvik, T. (2016). Shipboard safety: Exploring organizational and regulatory factors. Maritime Policy & Management, 43(5), 552–568. https://doi.org/10.1080/03088839.2016.1154993
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Gad-Elrab, A. (2021). Modern business intelligence: Big data analytics and artificial intelligence for creating the data-driven value. In R. M. X. Wu & M. Mircea (Eds.), E-business. Higher education and intelligence applications. IntechOpen. https://doi.org/10.5772/intechopen.97374
Girsang, A. S., Isa, S. M., Saputra, H., Nuriawan, M. A., Ghozali, R. P., & Kaburuan, E. R. (2018). Business intelligence for construction company acknowledgement reporting system. In 2018 Indonesian Association for Pattern Recognition International Conference (INAPR) (pp. 113–122), Jakarta, Indonesia. IEE. https://doi.org/10.1109/INAPR.2018.8627012
Golestanizadeh, M., Sarvari, H., Cristofaro, M., & Chan, D. W. M. (2023). Effect of applying business intelligence on export development and brand internationalization in large industrial firms. Administrative Sciences, 13(2), 27. https://doi.org/10.3390/admsci13020027
Gudfinnsson, K., Strand, M., & Berndtsson, M. (2015). Analyzing business intelligence maturity. Journal of Decision Systems, 24(1), 37–54. https://doi.org/10.1080/12460125.2015.994287
Hajiani, M., Azizi, M., Eshtehardian, E., & Naseh, K. (2018). Exploring the challenges of financing Iran’s construction projects from China and providing improvement solutions. Civil Engineering Journal, 4(7), 1689. https://doi.org/10.28991/cej-03091105
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R. R. Sinkovics & P. N. Ghauri (Eds.), Advances in international marketing (vol. 20, pp. 277–319). Emerald Group Publishing Limited. https://doi.org/10.1108/S1474-7979(2009)0000020014
Hock, M., & Ringle, C. M. (2010). Local strategic networks in the software industry: An empirical analysis of the value continuum. International Journal of Knowledge Management Studies, 4(2), 132. https://doi.org/10.1504/IJKMS.2010.030789
Hosseinzadeh, S., Rostamzadeh, R., Saparauskas, J., & Kersuliene, V. (2022). The influence of innovation and marketing strategy on the market-oriented activities of the company in cement industry: The decisive role of environmental dynamics. Acta Montanistica Slovaca, 26, 748–760. https://doi.org/10.46544/AMS.v26i4.12
Huynh, T. T.-M., Pham, A.-D., & Le-Hoai, L. (2021). Building a strategic performance management model for enterprises investing to coastal urban projects toward sustainability. International Journal of Strategic Property Management, 25(2), 127–145. https://doi.org/10.3846/ijspm.2021.14298
Işik, M., Yarar, O., & Söylemez Sur, D. (2021). Measurement of the effects of business intelligence applications on performance in hospitals according to the managerial levels: A chain hospital application. Journal of International Health Sciences and Management, 7(13), 97–108. https://doi.org/10.48121/jihsam.776109
Kowalczyk, M., & Buxmann, P. (2015). An ambidextrous perspective on business intelligence and analytics support in decision processes: Insights from a multiple case study. Decision Support Systems, 80, 1–13. https://doi.org/10.1016/j.dss.2015.08.010
Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x
Lopes, A. B., & Boscarioli, C. (2020). Business intelligence and analytics to support management in construction: A systematic literature review. Revista Brasileira de Computação Aplicada, 13(1), 27–41. https://doi.org/10.5335/rbca.v13i1.11346
Luo, Q., Gao, R., Liu, J., & Li, Y. (2022). Path analysis on escalation of commitment of investors in different project scenarios of PPPs. International Journal of Strategic Property Management, 26(2), 127–140. https://doi.org/10.3846/ijspm.2022.16477
Mai, A. N., Vu, H. V., Bui, B. X., & Tran, T. Q. (2019). The lasting effects of innovation on firm profitability: Panel evidence from a transitional economy. Economic Research-Ekonomska Istraživanja, 32(1), 3417–3436. https://doi.org/10.1080/1331677X.2019.1660199
Mandičák, T., Behúnová, A., & Mesároš, P. (2016). Impact of implementation and use of business intelligence on cost reducing in construction project management. Acta Tecnología, 2(3), 5–11. https://doi.org/10.22306/atec.v2i3.14
Moss, E., Rousseau, D., Parent, S., St-Laurent, D., & Saintonge, J. (2008). Correlates of attachment at school age: Maternal reported stress, mother-child interaction, and behavior problems. Child Development, 69(5), 1390–1405. https://doi.org/10.1111/j.1467-8624.1998.tb06219.x
Musarat, M. A., Alaloul, W. S., & Liew, M. S. (2021). Impact of inflation rate on construction projects budget: A review. Ain Shams Engineering Journal, 12(1), 407–414. https://doi.org/10.1016/j.asej.2020.04.009
Naz, F., Kumar, A., Upadhyay, A., Chokshi, H., Trinkūnas, V., & Magda, R. (2022). Property management enabled by artificial intelligence post Covid-19: An exploratory review and future propositions. International Journal of Strategic Property Management, 26(2), 156–171. https://doi.org/10.3846/ijspm.2022.16923
Ndekugri, I., Braimah, N., & Gameson, R. (2008). Delay analysis within construction contracting organizations. Journal of Construction Engineering and Management, 134(9), 692–700. https://doi.org/10.1061/(ASCE)0733-9364(2008)134:9(692)
Niwash, M. N. K., Cek, K., & Eyupoglu, S. Z. (2022). Intellectual capital and competitive advantage and the mediation effect of innovation quality and speed, and business intelligence. Sustainability, 14(6), 3497. https://doi.org/10.3390/su14063497
Pande, C., Witschel, H. F., & Martin, A. (2022). New hybrid techniques for business recommender systems. Applied Sciences, 12(10), 4804. https://doi.org/10.3390/app12104804
Pantouvakis, A., Chlomoudis, C., & Dimas, A. (2008). Testing the SERVQUAL scale in the passenger port industry: A confirmatory study. Maritime Policy & Management, 35(5), 449–467. https://doi.org/10.1080/03088830802352095
Paradza, D., & Daramola, O. (2021). Business intelligence and business value in organisations: A systematic literature review. Sustainability, 13(20), 11382. https://doi.org/10.3390/su132011382
Petrini, M., & Pozzebon, M. (2009). Managing sustainability with the support of business intelligence: Integrating socio-environmental indicators and organisational context. The Journal of Strategic Information Systems, 18(4), 178–191. https://doi.org/10.1016/j.jsis.2009.06.001
Pondel, J., & Pondel, M. (2016). The concept of project management platform using BI and big data technology. In Proceedings of the 18th International Conference on Enterprise Information Systems (pp. 166–173), Rome, Italy. https://doi.org/10.5220/0005834601660173
Rausch, P., & Stumpf, M. (2013). Linking the operational, tactical and strategic levels by means of CPM: An example in the construction industry. In P. Rausch, A. F. Sheta, & A. Ayesh (Eds.), Business intelligence and performance management (pp. 27–42). Springer London. https://doi.org/10.1007/978-1-4471-4866-1_3
Rubin, A., & Babbie, E. R. (2017). Research methods for social work (9th ed.). Cengage Learning.
Rud, O. P. (2009). Business intelligence success factors: Tools for aligning your business in the global economy. Wiley & Sons.
Sabherwal, R., & Becerra-Fernandez, I. (2011). Business intelligence: Practices, technologies, and management. Wiley.
Sarvari, H., Cristofaro, M., Chan, D. W. M., Noor, N. Md., & Amini, M. (2020). Completing abandoned public facility projects by the private sector: Results of a Delphi survey in the Iranian water and wastewater company. Journal of Facilities Management, 18(5), 547–566. https://doi.org/10.1108/JFM-07-2020-0046
Sindhwani, R., Afridi, S., Kumar, A., Banaitis, A., Luthra, S., & Singh, P. L. (2022). Can industry 5.0 revolutionize the wave of resilience and social value creation? A multi-criteria framework to analyze enablers. Technology in Society, 68, 101887. https://doi.org/10.1016/j.techsoc.2022.101887
Taherdoost, H. (2016). Validity and reliability of the research instrument; How to test the validation of a questionnaire/survey in a research. SSRN. https://doi.org/10.2139/ssrn.3205040
Thanos, I. C. (2023). The complementary effects of rationality and intuition on strategic decision quality. European Management Journal, 41(3), 366–374. https://doi.org/10.1016/j.emj.2022.03.003
Turban, E. (2015). Business intelligence and analytics: Systems for decision support (10th ed.). Pearson.
Turban, E., Sharda, R., & Delen, D. (2011). Decision support and business intelligence systems (9th ed). Prentice Hall.
Uçaktürk, A., Uçaktürk, T., & Yavuz, H. (2015). Possibilities of usage of strategic business intelligence systems based on databases in Agile manufacturing. Procedia - Social and Behavioral Sciences, 207, 234–241. https://doi.org/10.1016/j.sbspro.2015.10.092
Werts, C. E., Linn, R. L., & Jöreskog, K. G. (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), 25–33. https://doi.org/10.1177/001316447403400104
Wetzels, M., Odekerken-Schröder, G., & van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 33(1), 177. https://doi.org/10.2307/20650284
Wieder, B., & Ossimitz, M.-L. (2015). The impact of business intelligence on the quality of decision making – A mediation model. Procedia Computer Science, 64, 1163–1171. https://doi.org/10.1016/j.procs.2015.08.599
Williams, S., & Williams, N. (2007). The profit impact of business intelligence. Elsevier. https://doi.org/10.1016/B978-0-12-372499-1.X5000-5
World Economic Forum. (2016). Shaping the future of construction: A breakthrough in mindset and technology. https://www3.weforum.org/docs/WEF_Shaping_the_Future_of_Construction_full_report__.pdf
Wu, D. D., Chen, S.-H., & Olson, D. L. (2014). Business intelligence in risk management: Some recent progresses. Information Sciences, 256, 1–7. https://doi.org/10.1016/j.ins.2013.10.008
Xie, H., Ge, Y., & Yi, J. (2022). Cost control analysis of construction projects based on wireless communication and artificial intelligence decisions. Wireless Communications and Mobile Computing, 2022, 8505922. https://doi.org/10.1155/2022/8505922
Zhu, X., Meng, X., & Zhang, M. (2021). Application of multiple criteria decision making methods in construction: A systematic literature review. Journal of Civil Engineering and Management, 27(6), 372–403. https://doi.org/10.3846/jcem.2021.15260