Table 4.10 presents the means and standard deviations for each influential factor and arranged in descending order on the basis of overall and the respondent groups correspondingly. The five highly influential factors based on overall are as follows:
(1) Expertise and skill of project team (Mean = 4.451; δ = 0.821) (2) Proven technology effectiveness (Mean = 4.406; δ = 0.739) (3) Top management support (Mean = 4.383; δ = 0.785)
(4) Government promotion and initiative (Mean = 4.338; δ = 0.887) (5) Technology reliability (Mean = 4.331; δ = 0.785)
The five leading influential factors as perceived by developers to be:
(1) Expertise and skill of project team (Mean = 4.366; δ = 1.019) (2) Proven technology effectiveness (Mean = 4.317; δ = 0.934) (3) Top management support (Mean = 4.293; δ = 0.844) (4) Technology reliability (Mean = 4.220; δ = 1.013) (5) Capital cost of technology (Mean = 4.220; δ = 1.061)
The equivalent for consultants are:
(1) Expertise and skill of project team (Mean = 4.568; δ = 0.661) (2) Technology reliability (Mean = 4.545; δ = 0.589)
(3) Proven technology effectiveness (Mean = 4.523; δ = 0.590) (4) Technology compatibility (Mean = 4.500; δ = 0.665) (5) Organisation data security (Mean = 4.432; δ = 0.695) And for contractors:
(1) Government promotion and initiative (Mean = 4.521; δ = 0.772) (2) Government regulations (Mean = 4.500; δ = 0.715)
(3) Top management support (Mean = 4.479; δ = 0.743)
(4) Expertise and skill of project team (Mean = 4.417; δ = 0.767) (5) Proven technology effectiveness (Mean = 4.375; δ = 0.672)
“Expertise and skill of project team” is ranked the highest in overall, which is therefore regarded as the most influential factor of technologies adoption in construction safety management. This finding is as expected because human capital is one of the pivotal enablers of technology adoption (Riddell and Song, 2017). In support of this, similar observations are reported in the UK (Eadie, et al., 2013), US (Ku and Taiebat, 2011), Australia (Hong, et al., 2018), Gaza Strip (Enshassi, Ayyash and Choudhry, 2016) and India (Ahuja et al., 2018), all highlighting that the adoption of technologies depends very much on skills and expertise of the project team. Therefore, for successful implementation of safety technologies, construction practitioners with adequate skills and expertise would have to be nurtured. Certainly, technological advancements in the industry have heightened skill requirements in the construction workforce and lead to de-skilling in the workforce (Riddell and Song, 2017). Considering that the features of new technology could be significantly varied from existing practices or old technologies, companies embracing new technology have to acquire new skills and upgrade the skill level of their existing workforce (Boothby, Dufour and Tang, 2010). In this vein, Ayinla and Adamu (2018) affirmed that getting the right skills required is a pre- requisite for closing the gap in technology adoption. Notably, different technologies may have varied skill requirements, thus this suggests that training should be technology-specific.
“Proven technology effectiveness” is ranked second. This finding parallels with a recent study in the US, where it is revealed that proven technology effectiveness was perceived as the second topmost influential predictor of safety technologies adoption (Nnaji, et al., 2019). Construction firms are usually not willing to adopt a new technology if they are unsure about its effectiveness. That is to say, uncertainty about the usefulness of new technologies is a critical impediment for adopting them. In view of this, it is imperative that there is documented evidence proving that the technical attributes of the technology fulfil the desired performance requirements, thereby affirming that the technology is effective (Nnaji, et al., 2020). It should be pointed out that a technology with unproven effectiveness simply signifies that the technology is immature (Delgado, et al., 2019). For technologies to be
accepted by the construction practitioners, their effectiveness, applicability to the work process, and value-adding impact must be unceasingly evaluated and established.
“Top management support” is rated third in the overall ranking.
Technology adoption is closely linked to positive support from top management (Cao, Li and Wang, 2014; Nikas, Poulymenakou and Kriaris, 2007; Cheng and Teizer, 2013). This is echoed by several past studies that revealed that the most significant factor impacting adoption decision is the commitment and support from the top management (Son, Lee and Kim, 2015; Tsai, Mom and Hsieh, 2014;
Chen, et al., 2019). Essentially, this implies that the top management plays a key role in this aspect (Zheng, et al., 2017). This could be due to the fact that they always decide to what extent it is financially wise to invest in innovations (Bossink, 2004). The support from the top management may range from organisational strategy to day-to-day activities (Xu, Feng and Li, 2014). Their endorsement is vital to secure relevant resources such as capital to facilitate the diffusion process (Jensen and Jóhannesson, 2013; Fernandes, et al., 2006;
Aksorn and Hadikusumo, 2008). Besides, a proactive management will provide trainings to the workers to upgrade their skills and expertise (Wong and Fan, 2013). Therefore, this study indicates the necessity of great levels of attention, support, engagement and commitment from senior management and key project stakeholders.
“Government promotion and initiative” is ranked fourth. This finding is consistent with Suprun and Stewart (2015) but contravenes with a Turkish study where government-led initiatives were not considered as the main contributor to successful technology adoption (Ozorhon and Karahan, 2017). Zakaria, et al.'s (2018) literature review noted that government promotion is a vital aspect of government-related contextual factors as it engenders attention, awareness, insights and adoption in the industry. In response to the slow technological uptake, the governments of several developed countries like the US, UK and Australia have established various initiatives, including government subsidies to induce more investment in technologies for the aim of accelerating the rate of technology adoption. A study conducted by Low, Arain and Tang (2019) in Singapore also accentuated the role of government in this matter, where it is
pinpointed that government-initiated funding programs can aid small local contractors who are interested to adopt technologies. The government can also set up government-monitored technology online portal for firms to acquire useful latest technology updates. They should also provoke urge for technology adoption by engaging contractors in public pilot projects. Essentially, this finding suggests that the government plays a vital role in technology diffusion, by assembling an enabling environment that is conducive for firms to adopt safety technologies through a wide array of government measures.
“Technology reliability” is ranked fifth. To be of interest to the construction industry, the safety technologies must have high reliability to meet the required safety performance consistently (Nnaji, et al., 2020). For instance, a tracking technology is reliable if it is capable of recording and monitoring the activities accurately and precisely (Cheng, et al., 2011). This finding is aligned with Nnaji, et al.'s (2019) study where technology reliability was ranked as the most influential predictor, implying that the US construction firms are highly concerned about this factor before deciding to adopt a safety technology. In another study, AlHogail (2018) found that technology reliability has positive effects on trust towards its adoption. In this connection, Seo, et al. (2015) also highlighted that such technical issue is hindering the application of technologies in real practice. They posited that the essential requirement for successful safety and health control is the reliability and accuracy of data collected by the technology, which is challenging due to the unique nature of construction. That is being said, as construction is characterised by its dynamics such as job sites involving different workers, various types of equipment as well as building materials, and continuously changing working environments. These dynamic attributes at the sites may result in technical issues for safety technology application, such as poor technology reliability. Therefore, this study sheds some light on the importance of this technical feature for technology developers in the industry.