Developing a Success Model for Assessing the Impact of Wearable Sensing Devices in the Construction Industry
Publication: Journal of Construction Engineering and Management
Volume 147, Issue 7
Abstract
In a bid to optimize jobsite safety, wearable sensing devices (WSDs) are slowly emerging as a class of viable tools with strong potential to improve safety measurement and monitoring. While some industries have successfully utilized WSDs, such as smart personal protective equipment (PPE), to track data related to health, fitness, or even location, the construction industry has been relatively slow in implementing WSDs. Although some progress is expected, construction management research is yet to provide clear evidence of the impact of WSDs on vital project and organizational performance metrics such as safety and productivity. To fill this gap, the present study established the first WSD success model using multiple complementary frameworks and theories. The success model comprises individual adoption factors that influence individual WSD use and highlights implementation success indicators needed to evaluate adoption success. It was tested using survey questionnaires retrieved from 415 users of WSDs in the United States. Test results indicate the success model was a good fit. Moreover, findings suggest a strong positive relationship between the use of WSDs and individual performance, and project performance. This hybrid model provided critical insights on the impact of WSDs on workers’ performance, project metrics, as well as essential information for supporting the increased adoption of WSDs. It is believed that this framework will also guide construction practitioners in the effective integration of WSDs into their work processes.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. This includes survey data, path diagrams, and data derived from structural equation modeling.
Acknowledgments
This work was supported by the Small Study Program administered by the Office for Research and Economic Development (ORED) at the University of Alabama.
References
Aggelidis, V. P., and P. D. Chatzoglou. 2009. “Using a modified technology acceptance model in hospitals.” Int. J. Med. Inf. 78 (2): 115–126. https://doi.org/10.1016/j.ijmedinf.2008.06.006.
Ahn, C. R., S. Lee, C. Sun, H. Jebelli, K. Yang, and B. Choi. 2019. “Wearable sensing technology applications in construction safety and health.” J. Constr. Eng. Manage. 145 (11): 03119007. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001708.
Ajzen, I. 1991. “The theory of planned behavior.” Organ. Behav. Hum. Dec. Processes 50 (2): 179–211. https://doi.org/10.1016/0749-5978(91)90020-T.
Arias, O. E., A. J. Caban-Martinez, P. E. Umukoro, C. A. Okechukwu, and J. T. Dennerlein. 2015. “Physical activity levels at work and outside of work among commercial construction workers.” J. Occup. Environ. Med. 57 (1): 73. https://doi.org/10.1097/JOM.0000000000000303.
Awolusi, I., E. Marks, and M. Hallowell. 2018. “Wearable technology for personalized construction safety monitoring and trending: Review of applicable devices.” Autom. Constr. 85 (Jan): 96–106. https://doi.org/10.1016/j.autcon.2017.10.010.
Barclay, D., C. Higgins, and R. Thompson. 1995. “The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration.” Technol. Stud. 2 (2): 285–309.
BLS (Bureau of Labor Statistics). 2019. “National census of fatal occupational injuries in 2018.” Accessed January 30, 2020. https://www.bls.gov/news.release/pdf/cfoi.pdf.
Bolarinwa, O. A. 2015. “Principles and methods of validity and reliability testing of questionnaires used in social and health science researches.” Niger. Postgraduate Med. J. 22 (4): 195. https://doi.org/10.4103/1117-1936.173959.
Bollen, K. A., and J. Pearl. 2013. “Eight myths about causality and structural equation models.” In Handbook of causal analysis for social research, 301–328. Dordrecht, Netherlands: Springer.
Bryne, B. M. 2010. “Structural equation modelling with AMOS: Basic concepts.” In Applications and programming. 2nd ed. New York: Taylor and Francis Group.
Cangur, S., and I. Ercan. 2015. “Comparison of model fit indices used in structural equation modeling under multivariate normality.” J. Mod. Appl. Stat. Methods 14 (1): 152. https://doi.org/10.22237/jmasm/1430453580.
Chan, F. K., J. Y. Thong, V. Venkatesh, S. A. Brown, P. J. Hu, and K. Y. Tam. 2010. “Modeling citizen satisfaction with mandatory adoption of an e-government technology.” J. Assoc. Inf. Syst. 11 (10): 519–549. https://doi.org/10.17705/1jais.00239.
Chang, H. S., S. C. Lee, and Y. G. Ji. 2016. “Wearable device adoption model with TAM and TTF.” Int. J. Mobile Commun. 14 (5): 518–537. https://doi.org/10.1504/IJMC.2016.078726.
Cheung, G. W., and R. B. Rensvold. 2001. “The effects of model parsimony and sampling error on the fit of structural equation models.” Organ. Res. Methods 4 (3): 236–264. https://doi.org/10.1177/109442810143004.
Choi, B., S. Hwang, and S. Lee. 2017. “What drives construction workers’ acceptance of wearable technologies in the workplace?: Indoor localization and wearable health devices for occupational safety and health.” Autom. Constr. 84 (Dec): 31–41. https://doi.org/10.1016/j.autcon.2017.08.005.
Chung, B., M. J. Skibniewski, and Y. H. Kwak. 2009. “Developing ERP systems success model for the construction industry.” J. Constr. Eng. Manage. 135 (3): 207–216. https://doi.org/10.1061/(ASCE)0733-9364(2009)135:3(207).
Cui, G., W. Bao, and T. S. Chan. 2009. “Consumers’ adoption of new technology products: The role of coping strategies.” J. Consum. Marketing 26 (2): 110–120. https://doi.org/10.1108/07363760910940474.
DeLone, W. H., and E. R. McLean. 2003. “The DeLone and McLean model of information systems success: A ten-year update.” J. Manage. Inf. Syst. 19 (4): 9–30. https://doi.org/10.1080/07421222.2003.11045748.
De Wit, A. 1988. “Measurement of project success.” Int. J. Project Manage. 6 (3): 164–170. https://doi.org/10.1016/0263-7863(88)90043-9.
Doloi, H., K. C. Iyer, and A. Sawhney. 2010. “Structural equation model for assessing impacts of contractor’s performance on project success.” Int. J. Project Manage. 29 (6): 687–695. https://doi.org/10.1016/j.ijproman.2010.05.007.
Edirisinghe, R. 2019. “Digital skin of the construction site: Smart sensor technologies towards the future smart construction site.” Eng. Constr. Archit. Manage. 26 (2): 184–223. https://doi.org/10.1108/ECAM-04-2017-0066.
Fadel, K. J. 2012. “User adaptation and infusion of information systems.” J. Comput. Inf. Syst. 52 (3): 1–10. https://doi.org/10.1080/08874417.2012.11645553.
Flett, R., F. Alpass, S. Humphries, C. Massey, S. Morriss, and N. Long. 2004. “The technology acceptance model and use of technology in New Zealand dairy farming.” Agric. Syst. 80 (2): 199–211. https://doi.org/10.1016/j.agsy.2003.08.002.
Fromhold-Eisebith, M., and G. Eisebith. 2005. “How to institutionalize innovative clusters? Comparing explicit top-down and implicit bottom-up approaches.” Res. Policy 34 (8): 1250–1268. https://doi.org/10.1016/j.respol.2005.02.008.
Golant, S. M. 2017. “A theoretical model to explain the smart technology adoption behaviors of elder consumers (Elderadopt).” J. Aging Stud. 42 (Aug): 56–73. https://doi.org/10.1016/j.jaging.2017.07.003.
Hair, J. F., J. J. Risher, M. Sarstedt, and C. M. Ringle. 2019. “When to use and how to report the results of PLS-SEM.” Eur. Bus. Rev. 31 (1): 2–24. https://doi.org/10.1108/EBR-11-2018-0203.
Hooper, D., J. Coughlan, and M. Mullen. 2008. “Evaluating model fit: A synthesis of the structural equation modelling literature.” In Proc., 7th European Conf. Research Methodology for Business and Management Studies, 195–200. Prague, Czech Republic: International Institute of Social and Economic Sciences.
Howard, R., L. Restrepo, and C. Y. Chang. 2017. “Addressing individual perceptions: An application of the unified theory of acceptance and use of technology to building information modeling.” Int. J. Project Manage. 35 (2): 107–120. https://doi.org/10.1016/j.ijproman.2016.10.012.
Khakurel, J., S. Pöysä, and J. Porras. 2016. “The use of wearable devices in the workplace—A systematic literature review.” In Proc., Int. Conf. on Smart Objects and Technologies for Social Good, 284–294. Cham, Switzerland: Springer.
Kim, K. J., and D.-H. Shin. 2015. “An acceptance model for smart watches: Implications for the adoption of future wearable technology.” Internet Res. 25 (4): 527–541. https://doi.org/10.1108/IntR-05-2014-0126.
Kishore, R., and E. McLean. 1998. “Diffusion and infusion: Two dimensions of ‘success of adoption of IS innovations’.” In AMCIS 1998 Proc., 245. Littleton, MA: System Dynamics Society.
Kline, R. B. 2011. Principles and practice of structural equation modeling. 3rd ed. New York: Guilford Press.
Krejcie, R. V., and D. W. Morgan. 1970. “Determining sample size for research activities.” Educ. Psychol. Meas. 30 (3): 607–610. https://doi.org/10.1177/001316447003000308.
Lai, P. C. 2017. “The literature review of technology adoption models and theories for the novelty technology.” J. Inf. Syst. Technol. Manage. 14 (1): 21–38.
Lee, S., J. Yu, and D. Jeong. 2013. “BIM acceptance model in construction organizations.” J. Manage. Eng. 31 (3): 04014048. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000252.
Lee, W., K. Y. Lin, E. Seto, and G. C. Migliaccio. 2017. “Wearable sensors for monitoring on-duty and off-duty worker physiological status and activities in construction.” Autom. Constr. 83 (Nov): 341–353. https://doi.org/10.1016/j.autcon.2017.06.012.
Lee, Y. H., Y. C. Hsieh, and C. N. Hsu. 2011. “Adding innovation diffusion theory to the technology acceptance model: Supporting employees’ intentions to use e-learning systems.” J. Educ. Technol. Soc. 14 (4): 124–137.
Li, H., J. Wu, Y. Gao, and Y. Shi. 2016. “Examining individuals’ adoption of healthcare wearable devices: An empirical study from privacy calculus perspective.” Int. J. Med. Inf. 88 (Apr): 8–17. https://doi.org/10.1016/j.ijmedinf.2015.12.010.
Lu, M., C. M. Cheung, H. Li, and S. C. Hsu. 2016. “Understanding the relationship between safety investment and safety performance of construction projects through agent-based modeling.” Accid. Anal. Prev. 94 (Sep): 8–17. https://doi.org/10.1016/j.aap.2016.05.014.
Majid, T. A., M. N. A. Azman, S. A. S. Zakaria, A. S. Yahya, S. S. Zaini, M. S. S. Ahamad, and M. H. Hanafi. 2011. “Quantitative analysis on the level of IBS acceptance in the Malaysian construction industry.” J. Eng. Sci. Technol. 6 (2): 179–190.
Marakhimov, A., and J. Joo. 2017. “Consumer adaptation and infusion of wearable devices for healthcare.” Comput. Hum. Behav. 76 (Nov): 135–148. https://doi.org/10.1016/j.chb.2017.07.016.
McDonald, M. A., H. J. Lipscomb, J. Bondy, and J. Glazner. 2009. “(Safety is everyone’s job): The key to safety on a large university construction site.” J. Saf. Res. 40 (1): 53–61. https://doi.org/10.1016/j.jsr.2008.12.005.
Miltgen, C. L., A. Popovič, and T. Oliveira. 2013. “Determinants of end-user acceptance of biometrics: Integrating the ‘Big 3’ of technology acceptance with privacy context.” Decis. Support Syst. 56 (Dec): 103–114. https://doi.org/10.1016/j.dss.2013.05.010.
Mun, Y. Y., J. D. Jackson, J. S. Park, and J. C. Probst. 2006. “Understanding information technology acceptance by individual professionals: Toward an integrative view.” Inf. Manage. 43 (3): 350–363. https://doi.org/10.1016/j.im.2005.08.006.
Nath, N. D., T. Chaspari, and A. H. Behzadan. 2018. “Automated ergonomic risk monitoring using body-mounted sensors and machine learning.” Adv. Eng. Inf. 38 (Oct): 514–526. https://doi.org/10.1016/j.aei.2018.08.020.
NIOSH (National Institute for Occupational Safety and Health). 2019. “About NIOSH: NIOSH Strategic Plan: FYs 2019−2023.” Accessed October 8, 2019. https://www.cdc.gov/niosh/about/strategicplan/researchgoals.html.
Nnaji, C., J. Gambatese, A. Karakhan, and C. Eseonu. 2019a. “Influential safety technology adoption predictors in construction.” Eng. Constr. Archit. Manage. 26 (11): 2655–2681. https://doi.org/10.1108/ECAM-09-2018-0381.
Nnaji, C., and A. Karakhan. 2020. “Technologies for safety and health management in construction: Current use, implementation benefits and limitations, and adoption barriers.” J. Build. Eng. 29 (May): 101212. https://doi.org/10.1016/j.jobe.2020.101212.
Nnaji, C., I. Okpala, and I. Awolusi. 2020. “Wearable sensing devices: Potential impact & current use for incident prevention.” Prof. Saf. 65 (4): 16–24.
Nnaji, C., I. Okpala, and S. Kim. 2019b. “A simulation framework for technology adoption decision making in construction management: A composite model.” In Proc., Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation, 499–506. Reston, VA: ASCE.
Nunnally, J., C. 1978. Psychometric theory. New York: McGraw-Hill.
Okpala, I., C. Nnaji, and A. Karakhan. 2020. “Utilizing emerging technologies for construction safety risk mitigation.” Pract. Period. Struct. Des. Constr. 25 (2): 04020002. https://doi.org/10.1061/(ASCE)SC.1943-5576.0000468.
OSHA (Occupational and Safety Health Administration). 2019. “OSHA data and statistics: Commonly used statistics.” Accessed October 8, 2019. https://www.osha.gov/data/commonstats.
Ozorhon, B., D. Arditi, I. Dikmen, and M. T. Birgonul. 2010. “Performance of international joint ventures in construction.” J. Manage. Eng. 26 (4): 209–222. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000022.
Park, E., H. Kim, and J. Y. Ohm. 2015. “Understanding driver adoption of car navigation systems using the extended technology acceptance model.” Behav. Inf. Technol. 34 (7): 741–751. https://doi.org/10.1080/0144929X.2014.963672.
Pesudovs, K., J. M. Burr, C. Harley, and D. B. Elliott. 2007. “The development, assessment, and selection of questionnaires.” Optom. Vis. Sci. 84 (8): 663–674. https://doi.org/10.1097/OPX.0b013e318141fe75.
Pierce, R., and L. Ball. 2009. “Perceptions that may affect teachers’ intention to use technology in secondary mathematics classes.” Educ. Stud. Math. 71 (3): 299–317. https://doi.org/10.1007/s10649-008-9177-6.
Rahman, M. M., M. F. Lesch, W. J. Horrey, and L. Strawderman. 2017. “Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems.” Accid. Anal. Prev. 108 (Nov): 361–373. https://doi.org/10.1016/j.aap.2017.09.011.
Rai, R. S., and F. Selnes. 2019. “Conceptualizing task-technology fit and the effect on adoption—A case study of a digital textbook service.” Inf. Manage. 56 (8): 103161. https://doi.org/10.1016/j.im.2019.04.004.
Raskovic, D., T. Martin, and E. Jovanov. 2004. “Medical monitoring applications for wearable computing.” Comput. J. 47 (4): 495–504.
Sargent, K., P. Hyland, and S. Sawang. 2012. “Variables influencing the adoption of information technology in a construction business.” Australas. J. Constr. Econ. Build. 12 (2): 72.
Schneider, A., G. Hommel, and M. Blettner. 2010. “Linear regression analysis: Part 14 of a series on evaluation of scientific publications.” Dtsch. Arztebl. Int. 107 (44): 776.
Shapiro, S. A., and R. Rabinowitz. 2000. “Voluntary regulatory compliance in theory and practice: The case of OSHA.” Admin. L. Rev. 52 (1): 97–155.
Sierzchula, W. 2014. “Variables influencing fleet manager adoption of electric vehicles.” Transp. Res. Part D Transp. Environ. 31 (Aug): 126–134. https://doi.org/10.1016/j.trd.2014.05.022.
Sijtsma, K. 2009. “On the use, the misuse, and the very limited usefulness of Cronbach’s alpha.” Psychometrika 74 (1): 107–120. https://doi.org/10.1007/s11336-008-9101-0.
SmartMarket Report. 2017. Safety management in the construction industry 2017. Bedford, MA: Dodge Data and Analytics.
Son, H., Y. Park, C. Kim, and J. S. Chou. 2012. “Toward an understanding of construction professionals’ acceptance of mobile computing devices in South Korea: An extension of the technology acceptance model.” Autom. Constr. 28 (Dec): 82–90. https://doi.org/10.1016/j.autcon.2012.07.002.
Stoelting, R. 2002. “Structural equation modeling/path analysis.” Accessed October 16, 2020. http://userwww.sfsu.edu/efc/classes/biol710/path/SEMwebpage.htm.
Suebsin, C., and N. Gerdsri. 2009. “Key factors driving the success of technology adoption: Case examples of ERP adoption.” In Proc., PICMET’09-2009 Portland Int. Conf. on Management of Engineering and Technology, 2638–2643. New York: IEEE.
Sultan, N. 2015. “Reflective thoughts on the potential and challenges of wearable technology for healthcare provision and medical education.” Int. J. Inf. Manage. 35 (5): 521–526. https://doi.org/10.1016/j.ijinfomgt.2015.04.010.
Taherdoost, H. 2018. “A review of technology acceptance and adoption models and theories.” Procedia Manuf. 22 (2018): 960–967. https://doi.org/10.1016/j.promfg.2018.03.137.
Teo, T., W. S. Luan, and C. C. Sing. 2008. “A cross-cultural examination of the intention to use technology between Singaporean and Malaysian pre-service teachers: An application of the technology acceptance model (TAM).” J. Educ. Technol. Soc. 11 (4): 265–280.
Thompson, S. K. 1987. “Sample size for estimating multinomial proportions.” Am. Stat. 41 (1): 42–46.
Tu, Y. K., M. Kellett, V. Clerehugh, and M. S. Gilthorpe. 2005. “Problems of correlations between explanatory variables in multiple regression analyses in the dental literature.” Br. Dent. J. 199 (7): 457. https://doi.org/10.1038/sj.bdj.4812743.
Vass, S., and T. K. Gustavsson. 2017. “Challenges when implementing BIM for industry change.” Constr. Manage. Econ. 35 (10): 597–610. https://doi.org/10.1080/01446193.2017.1314519.
Venkatesh, V., M. G. Morris, G. B. Davis, and F. D. Davis. 2003. “User acceptance of information technology: Toward a unified view.” MIS Q. 27 (3): 425–478. https://doi.org/10.2307/30036540.
Viswanathan, M., J. A. Rosa, and J. E. Harris. 2005. “Decision making and coping of functionally illiterate consumers and some implications for marketing management.” J. Marketing 69 (1): 15–31. https://doi.org/10.1509/jmkg.69.1.15.55507.
Walczuch, R., J. Lemmink, and S. Streukens. 2007. “The effect of service employees’ technology readiness on technology acceptance.” Inf. Manage. 44 (2): 206–215. https://doi.org/10.1016/j.im.2006.12.005.
Wanberg, J., C. Harper, M. R. Hallowell, and S. Rajendran. 2013. “Relationship between construction safety and quality performance.” J. Constr. Eng. Manage. 139 (10): 04013003. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000732.
Wang, W. T., and C. Y. Liu. 2005. “The application of the technology acceptance model: A new way to evaluate information system success.” In Proc., 23rd Int. System Dynamics Conf. Littleton, MA: System Dynamics Society.
Xiong, B., M. Skitmore, and B. Xia. 2015. “A critical review of structural equation modeling applications in construction research.” Autom. Constr. 49 (Jan): 59–70. https://doi.org/10.1016/j.autcon.2014.09.006.
Xu, H., and S. Gupta. 2009. “The effects of privacy concerns and personal innovativeness on potential and experienced customers’ adoption of location-based services.” Electron. Markets 19 (2–3): 137–149. https://doi.org/10.1007/s12525-009-0012-4.
Yang, L. R., J. H. Chen, and H. W. Wang. 2012. “Assessing impacts of information technology on project success through knowledge management practice.” Autom. Constr. 22 (Mar): 182–191. https://doi.org/10.1016/j.autcon.2011.06.016.
Yeo, C. J., J. H. Yu, and Y. Kang. 2020. “Quantifying the effectiveness of IoT technologies for accident prevention.” J. Manage. Eng. 36 (5): 04020054. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000825.
Zack, J. G. 2016. “Trends in construction technology—The potential impact on project management and construction claims.” In Proc., Navigant Construction Forum. Boulder, CO: Navigant Consulting.
Zhang, P., and F. F. Ng. 2013. “Explaining knowledge-sharing intention in construction teams in Hong Kong.” J. Constr. Eng. Manage. 139 (3): 280–293. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000607.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 147 • Issue 7 • July 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Jun 30, 2020
Accepted: Dec 30, 2020
Published online: Apr 27, 2021
Published in print: Jul 1, 2021
Discussion open until: Sep 27, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.