Using PLS-SEM technique to model construction organizationsʹ willingness to participate in e-bidding

The push for the use of e-bidding is on the increase. In many countries, e-bidding has become part of the public procurement reform. However, previous studies have reported the low uptake of e-bidding in the construction industry. This study develops a theoretical structural model representing the impact six latent variables on the willingness of construction organizations to participate in e-bidding. Data from a questionnaire survey of 64 respondents from clients, contractors, consultants, and suppliers organizations was used to analyze the model. The result of the data analysis suggests that perceived barriers, cost, the perceived benefits of e-bidding and security concerns are the factors influencing willingness participate in e-bidding with perceived barriers being the most significant influencing factor. The perception about the adequacy of the existing traditional paper-based tendering and the perception about the non-readiness of business partners are the underlying barriers that need to be addressed when introducing e-biding. This study also discovers that when the respondents concern about the cost of e-bidding is high, their reported willingness to participate in e-bidding is higher when the perceived benefits is high that when the perceived benefits is low. To enhance the participation of the industry in e-bidding, public sector and large private clients would need to take leadership by making bidderʹs capability for e-bidding and e-project management at all project phases a criteria in bid evaluation. E-bidding developers and promoters need to use test project cases to monitor, measure, and document the benefits of e-bidding. To disseminate the perceived benefits, promoters would need to work closely with industry professional associations to develop promotional programmes linked to continuous professional development (CPD) points. The analytical approach used in this study should assist other researchers who might wish to address a similar research problem under a similar data and model constraints.