4.12 Discussion
4.12.3 Organisation’s Awareness towards AI Adoption in Construction Logistics
more concern about the development and adoption of AI in construction logistics.
4.12.3 Organisation’s Awareness towards AI Adoption in Construction Logistics
a) Awareness on relevance of AI in construction logistics
The top three construction logistics activities with highest perception on relevance of AI are “process of contracts and invoices”, “further planning after prediction of delay” and “planning and management of loading and unloading zones”. Local construction organisations perceived that AI is the most relevant in processing contracts and invoices when every project has its own unique need, and all contracts and payables have to be controlled all the time. Thus, automation of contract and invoice process is important to save time and increase accuracy (Gesing, et al, 2018; Stampli, 2021). Suppliers are more perceived the relevance of AI in the top two construction logistics activities if compare to contractors (Section 4.6 (i) (a) & (d)). This may imply that suppliers who contracted to provide materials or goods more aware the transformation of AI adoption in their supply logistics for manufacturing and supply management.
Moreover, deputy directors and directors as well as the respondents who worked more than 10 years perceived the top three construction logistics activities’
higher relevance to AI if compared to assistant, executive and the respondents who worked less than 2 years and 3 years to 5 years (Section 4.6 (v)(a)(d)(f) &
(viii)(a)(c)(e)(f)(g)). This implies that the superiors with more working experiences able to feel the AI disruptions and its competitive advantages to construction logistics. They have heightened awareness towards the development of AI in construction logistics when compare to subordinates who have fewer working experiences.
The third to last ranked construction logistics activities with only 66 respondents perceived “very” relevant to AI adoption is delivery and traffic management. This is opposed with findings of the research by McKinsey, et al.
(2017) which indicates transportation is one of the sector with highest potential for automation. This may because most of the respondents misunderstood the word ‘relevance’ and they tend to interpret its meaning as how possible the reality of “delivery automation and traffic management automation” will come true in this few years. As these technologies are still under testing and validation all around the world and have not been adopted widespread, the respondents give the relevance of AI in “delivery and traffic management” a low rating.
In overall, the group perceived AI is “extremely” relevant to construction logistics activities in Table 4.6 have higher awareness towards AI adoption in construction logistics when compared with the group perceiving AI is “not at all”, “slight”, “moderately” and “very” relevant to construction logistics. This shows that this group which able to visualise relevance of AI is “extremely”
relevant to construction logistics tends to perceive the potentials of AI development and more aggressive in exploring the uses of AI in construction logistics.
b) Awareness on functions of AI in construction logistics
The respondents most agreed on the “AGV is useful for repetitive transportation works in warehouse”. AGV can offer accurate navigation and safer transportation in warehouse by mapping their travel path without human intervention (Modern Material Handling, 2020). Respondents tend to have highest awareness towards usefulness of AGV if compared to other nine adoptions of AI in construction logistics. Respondents worked in logistics firm are more agreed the functions of AGV compared to other respondents who worked in contractor, sub-contractor, specialist and supplier firm (Section 4.7 (ii to v) (a)). They tend to have higher awareness and more likely understand the value of AGV in warehousing.
Next, the second ranked statements with 98 respondents strongly agreed the statements related the functions of AI-based drones. The traditional method in gathering information for site layout planning by walking around site can be replaced by AI-based drones. The innovation of AI-based drone eases this
drudge preparation works by producing different types of detailed construction site map and site progress report automatically (Dukowitz, 2019).
The functions of AI-back offices ranked the third among other AI adoptions in construction logistics when 101 respondents slightly agreed on
“AI-back office is useful for detecting fraud by logistics service providers, classifying contractual clauses, managing and keeping all delivery information precisely”. The combination of RPA and AI can well-cooperated in detecting fraud, automating processing of invoices as well as processing in classifying sections, clauses and signature portions in contracts. AI-back office ensures the correctness, completeness and consistency of billions of data (Gesing, et al., 2018).
These findings also reveal that the group with only 2 years or 3 to 5 years working experiences has the highest agreement on functions of AI adoption in construction logistics compared to those with 6 to 10 years or more than 10 years working experiences. This may imply that those with less working experience has a higher exposure towards the knowledge of AI development.
These younger groups are grown alongside with these new introduced technologies which gradually related to their academic lessons. This is concurrent with the research of Meyer (2008) which indicated younger workers who less than 30 years old has higher acceptance towards new technology.
To conclude, the group who “strongly agree” the statements related to functions of AI adoptions in Table 4.7 has heightened awareness towards usefulness of AI adoptions in construction logistics compared to those who
“slightly agree”, “moderately’, “slightly disagree” and “strongly agree”.
Comparatively, the group who “strongly agree” the functions of AI adoptions tend to accept the applications and more likely to resort to the particular AI adoption in construction logistics. They tend to more concern and appreciate the chances in learning and adopting AI. Moreover, they tend to foresee the potential barriers and issues which undermining the adopting of AI.