Table 2 Operational difficulties of...

Table 2

Operational difficulties of integrated BIM–AI

s/n	Sub-constructs and items	F_L	N_T	α	A_V	E_V
A	Interoperability of data from BIM and AI platform		4	0.87	0.55	0.76
1	Data security and data training	0.77
2	Differences in AI and BIM models	0.86
3	Lack of information in existing BIM software to support AI features	0.88
4	Unfamiliarity with user interfaces and AI features in BIM software	0.78
B	Employees’ growth and development		7	0.83	0.63	1.13
1	Employee engagement with BIM and AI tools	0.56
2	Employees’ learning culture	0.78
3	Employees’ learning effectiveness	0.54
4	Employees’ resistance to change	0.53
5	Brain drain	0.96
6	Employees’ learning style	0.89
7	Employees’ motivation	0.88
C	Governance for integrated BIM–AI		5	0.87	0.52	0.74
1	Corruption in training and investment	0.87
2	Prioritizing equal access to BIM–AI platforms	0.56
3	Prioritizing transparency	0.51
4	Strengthening decision-making process	0.71
5	Ensuring commitment to investment in BIM–AI platforms	0.77
D	Infrastructure for integrated BIM–AI		5	0.82	0.59	0.93
1	Inadequate infrastructure	0.71
2	Flexibility of infrastructure	0.50
3	Reliability of infrastructure	0.72
4	Security of infrastructure	0.51
5	Availability of software integrating BIM and AI	0.81
E	Finances for integrated BIM–AI		7	0.82	0.69	1.01
1	Inadequate cash flow and debt	0.70
2	Funding instability	0.62
3	Budget constraints	0.81
4	Lack of working capital	0.61
5	Manual financial management	0.50
6	Complex financial operations	0.44
7	Economic downturns	0.76
F	Internal process for integrated BIM–AI		7	0.87	0.72	1.23
1	Operational complexity	0.32
2	Inefficient workflows	0.70
3	Poor communication	0.44
4	Inefficient management practices	0.45
5	Lack of support for innovation	0.73
6	Lack of teamwork	0.66
7	Negative culture	0.71
G	Client relation through BIM–AI platform		6	0.84	0.55	0.19
1	Data quality issues	0.41
2	Miscommunication and communication gaps	0.68
3	Differing expectations	0.70
4	Clients’ dissatisfaction with BIM–AI platforms	0.41
5	Uncertainty about the output of integrated BIM–AI	0.86
6	Work overload	0.80

s/n	Sub-constructs and items	F_L	N_T	α	A_V	E_V
A	Interoperability of data from BIM and AI platform		4	0.87	0.55	0.76
1	Data security and data training	0.77
2	Differences in AI and BIM models	0.86
3	Lack of information in existing BIM software to support AI features	0.88
4	Unfamiliarity with user interfaces and AI features in BIM software	0.78
B	Employees’ growth and development		7	0.83	0.63	1.13
1	Employee engagement with BIM and AI tools	0.56
2	Employees’ learning culture	0.78
3	Employees’ learning effectiveness	0.54
4	Employees’ resistance to change	0.53
5	Brain drain	0.96
6	Employees’ learning style	0.89
7	Employees’ motivation	0.88
C	Governance for integrated BIM–AI		5	0.87	0.52	0.74
1	Corruption in training and investment	0.87
2	Prioritizing equal access to BIM–AI platforms	0.56
3	Prioritizing transparency	0.51
4	Strengthening decision-making process	0.71
5	Ensuring commitment to investment in BIM–AI platforms	0.77
D	Infrastructure for integrated BIM–AI		5	0.82	0.59	0.93
1	Inadequate infrastructure	0.71
2	Flexibility of infrastructure	0.50
3	Reliability of infrastructure	0.72
4	Security of infrastructure	0.51
5	Availability of software integrating BIM and AI	0.81
E	Finances for integrated BIM–AI		7	0.82	0.69	1.01
1	Inadequate cash flow and debt	0.70
2	Funding instability	0.62
3	Budget constraints	0.81
4	Lack of working capital	0.61
5	Manual financial management	0.50
6	Complex financial operations	0.44
7	Economic downturns	0.76
F	Internal process for integrated BIM–AI		7	0.87	0.72	1.23
1	Operational complexity	0.32
2	Inefficient workflows	0.70
3	Poor communication	0.44
4	Inefficient management practices	0.45
5	Lack of support for innovation	0.73
6	Lack of teamwork	0.66
7	Negative culture	0.71
G	Client relation through BIM–AI platform		6	0.84	0.55	0.19
1	Data quality issues	0.41
2	Miscommunication and communication gaps	0.68
3	Differing expectations	0.70
4	Clients’ dissatisfaction with BIM–AI platforms	0.41
5	Uncertainty about the output of integrated BIM–AI	0.86
6	Work overload	0.80

Note(s): N_T = number of items; F_L = factor loading; α = Cronbach Alpha; A_V = average variance explained; E_V = Eigen value

Source(s): Table by authors

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