Investigating engineer’s actual usage intention to apply construction technologies in emerging countries

2.1. Acceptance behavior linked concepts

As stated [11], technology acceptance is about in which manner entities decide to take and accept a number of technologies for practice. Employers recognition of technology, is defined as the obvious inclination to take on information technology (IT) which is meant for everyday job [12]. However, technology is not considered valuable, unless it is recognized and practised by individuals.

The TAM is an adaptation of the philosophy of reasoned action and philosophy of planned behaviour exactly fitted for modelling user acceptance of technologies [10]. We are quite conscious, that TAM puts forward a description of the factors of technology acceptance that can define user behaviour towards actual usage of technologies in their daily schedule of work. In the time being, behavioural intentions of technology acceptance are in due course influenced by perceived usefulness and perceived ease-of-use, which are affected by means of numerous external variables. Advancement of acceptance behaviour-correlated ideas, the TAM has been largely used on the way to observe behavioural acceptance of emerging technology.

2.2. Construction technology acceptance in the construction industry

The Construction Industry Institute illustrates construction technology as “the group of innovative tools, machinery, modifications, software etc., implemented throughout the construction life-cycle of a project that allows advancement in-field of the construction techniques, including semi-automated and automated construction equipment”. According to [13, 14], c-tech recognizes the properties of each project and organization objectives and identifies the relationships between these assets. The above-mentioned allows variations to be applied instantaneously to each project assets, thus supporting more rapidly, enhanced project facilities all over the whole production method. Once c-techs are used, numerous kinds of data granted by the (AEC) engineering can be applied proficiently [5]. The below are the external factors which can be facilitated to an individual by their bosses or organization and can accepted or rejected and hence can result in one’s intentions to actual usage of these technologies.

– (ML) Machine learning models can attain big statistics of health record, productivity, quality and safety of employees in organization [4].

– (VR) Virtual reality can attain more effortless to clearly display the project work and eradicate miscommunication between designers, professionals and their clients [3, 4].

– (AI) Artificial intelligence models can prevent cost overruns, much enhanced designs for buildings via generative designs, supports risk mitigation and will address labour shortages [3, 4].

– (CC) Cloud computing models can attain Intelligent schedule administration, decision-making, cost control, quality control, Intelligent safety analysis and alarm approaches [3].

– (AE) Acoustic Emission can bring the finest nondestructive techniques between all features of structural health monitoring (SHM), it will be able to monitor and control all location of cracks without harming the structure [5].

– (TI) Technology information, companies are using data make enhanced decisions, increase productivity, better jobsite safety, and decrease risks can resolve Structure failure, falling from the rooftop while working in a restricted space with (TI) organizations can be able to turn the information they have gathered over the time-period and forecast future results on projects life-cycle [8].

– BIM (Building information modelling) assists from the conception stage to the handover stage of the project. It allows engineers to create a project on computer before building in field. It does not do clash identification, model-based amount estimation supervision, more efficient but helps to decrease material costs [2].

– (IoT) Internet of Things facilitates equipment tracking makes available firms to achieve utilization, control costs and make up smarter judgments. Real-time tracking and cloud-based data sets help out firms cut theft, improve efficiency and manage usage costs [6, 7].

The merits of c-tech in the firms contain provision intended for visual elements and an information supervision setting. C-tech not only makes available information associated with above-mentioned factors but also allows “Professional engineering services” [3]. C-tech implementation in the construction firms has been lacking because of the subsequent hindrances.

– Unsure and overturned profits of c-tech in current performs.

– Absence of acquaintance with implementing these latest technologies.

– Absence of teaching, training facilities for use of c-techs.

– Absence of resources (hardware, software) to practice c-tech means.

As discussed, c-tech allows unified information well-matched and distribution of the material in altogether phases of lifespan of projects. Accordingly, the acceptance of c-tech is probably after an individual is keen to apply the information and mechanical tools of c-tech in everyday jobs and the associated group is ready to begin a collaboration structure that functions c-tech [6].

3.1. Perceived ease of use (PEOU)

(PEOU) Perceived Ease of Use is described as “the degree to which an individual trust that using a specific system would be free of effort” In the TAM, TAM 2 and (DTPB) Decomposed Theory of Planned Behavior, PEOU was hypothesized as a direct factor of BI [10]. Still, numerous scientists bring into being a reinforcement to the indirect association of PEOU on BI over PU [19]. Strong confirmation reinforced the vital part that PEOU shows in forecasting the BI.

In the framework of this research, the presence of PEOU was to explore engineers’ opinions of whether or not the system would function without much labour to predict their behavioural intention to use the c-tech structure. We recommend the subsequent hypothesis:

H1: PU will have a positive effect on the intention to use c- tech.

H3: PEOU will have a positive influence on PU to use c-tech.

3.2. Perceived usefulness (PU)

(PU) Perceived Usefulness is described as “the degree to which an individual has trust in that via a specific structure must develop his/her professional working effectiveness”. PU is alike relative gain in the model DOI and working effectiveness hope in UTAUT. In other difference of opinion, it is the range to which profits are weighty responsibilities. In the TAM, TAM2 and Improved TAM, PU was hypothesized as a direct factor of BI. Additionally, numerous investigators have presented proof of its direct factors on AU [17].

In the current circumstantial of the research, PU was used to examine the engineers’ certainty about the possible merits of using the construction-technology structure. Numerous studies have emphasized the significant regulation PU shows on BI to practice technological tools [10].

H2 – PU will have a positive impact on the intention to use the c-tech.

3.3. Facilitating service conditions (FC)

(FC) Facilitating Service Condition is described as “the extent to which a person accepts as true that a structural and methodological substructure is to encourage and bring into play practice of the system” [17]. Exactly, it takes in the approachability of external back up supply (time, money and effort), which is recognized in the works as Resource Facilitating Conditions “RFC” [18].

For instance, the association between FC and BI was discovered to be important in numerous revisions. Therefore, the significance of the outward impact of enabling circumstances on policymaking development is a vital predecessor for behavioural tasks.

H4 – FC will have a positive outcome on actual intention usage to implement c-tech.

3.4. Behavioural intentions for acceptance of construction technologies (BI)

(BI) Behavioural Intention is described as an individual’s perceived probability or personal likelihood that he or she will involve in certain behaviour. The chief variances in (TRA) Theory of reasoned action are considered in BI. It is well-thought-out an instant predecessor of behaviour which provides a recommendation regarding entities’ eagerness to do a precise work [17]. While in TAM, together PU and PEOU impact a person’s intent to practice the technology, that in likelihoods impact the routine behaviour [19].

Within this framework of the investigation, structure usage was considered by means of an endogenous variable and is repeatedly calculated by lone BI [17, 18] or by lone AU [19] or together BI and AU [18]. The present study measured both BI and AU as endogenous variables in the hypothetical background. It is expectable that BI will impact in forecasting the function behaviour of engineers to admit the construction technology in the forthcoming applying procedures. The suggested model comprises 18 observed indicators illustrating 5 latent constructs. The researcher suggests the subsequent hypotheses:

H5 – BI will have a positive result on his or her intention of construction technology.

4.1. Descriptive analysis

Reliable with former experimental exploration in technology acceptance and technological background done by numerous academicians and practitioners like as [19], present research implemented a quantitative method to exam the projected model (see Table 1).

Data were gathered by way of self-administered questionnaires from Turkey, India and some functional managers, senior project manager respondents from across the globe via LinkedIn were also the contributors like South Korean, Middle East, Philippian who use construction technologies in their profession. The sample’s age span wide-ranging as of 24 to 55 years old, with 69.4 % (150 contributors) graduates and 45.7 % (98 contributors) master’s; their self-allied c-tech experience was what's more some or skilled, moreover an in-between or proficient rank in using emerging technologies. Males denote 58.4 % (145 contributors) of model and females denote 41.5 % (103 participants). It is important observing that all constructs and their dimensions were selected from previous works and calculated on a 5-point Likert rule, it stated to be valid and reliable to calculate constructs. Moreover, the descriptive information presented that the widely held of contributors specify positive answers are calculated in this research (see Table 1). Entire means remained greater than 5 for the exogenous constructs (PEOU, PU, FC) and 4.21 for the endogenous constructs (BI and AU). Our outcomes were expected in facilitating service condition construct provided by the administration or government as the previous literature suggests the c-tech system is still in its infancy [19].

4.2. Results

4.2.2. Construct reliability and validity

The reliability of the constructs was examined by Cronbach’s Alpha. It computes how the set of elements computes an only one direction latent construct. Unlike reliabilities, values were well-thought-out reasonable by diverse scholars. Such as, it must be at minimum 0.7 as stated by [16] or 0.6 is measured acceptable whereas a value of 0.8 or greater is favoured rendering to [16]. Assumed all constructs had absolute consistency results 0.8 and mean difference take out results greater than 0.5 and results, examined by SPSS, greater than 0.6, (See Table 1) proposes that the constructs had satisfactory reliability. Moreover, validity of constructs can be measured by means of discriminant and convergent validity. No convergent or discriminant validity at the construct or item level were found (see Fig. 2).

Fig. 2The measurement model: percei (PEU) – perceived ease of use, useful (PU) – perceived use, facilia (FC) – facilitating condition, behav (BI) – behavioural intention, actua (AU) – actual usage

4.2.3. The structural model analysis and hypothesis testing

With its extensive and widespread support amongst researches in IS, behavioural and social science [21], the SEM, as well identified as path examination, covariance structure examination, simultaneous calculation models is brought into play to assess and inspect the hypothesized associations amongst variables in the planned theoretical prototypical see Fig. 2; Fig. 3.

Fig. 3Structural model: ease (PEU) – perceived ease of use, useful (PU) – perceived use, facilit (FC) – facilitating condition, behav (BI) – behavioural intention, actual (AU) – actual usage

Table 2Model fit summary for the final measurement and structural model

Fit indices		Fit values
Index	Criterion	Measurement	Structural
${\chi }^2$	$p>$ 0.05	286.053	332.273
df	n/a	112	112
${\chi }^2$ /df	< 5 or < 3	2.55	2.72
GFI	> 0.90	0.896	0.875
AGFI	> 0.80	0.840	0.82
CFI	> 0.90	0.969	0.925
RMSR	< 0.10	0.040	0.51
RMSEA	< 0.08	0.079	0.084
NFI	> 0.90	0.951	0.888
PNFI	> 0.60	0.699	0.708

Predictable values of fit indices have revealed the good structural model fit to the statistics for the suggested examination model in this research see Table 2.

Table 3The summary of direct hypothesied results for the sample

H#	Proposed relationship	Effects type	Path coefficient	Study results
Perceived usefulness, Behavioural Intention and Actual Usage Prediction
H1	PU (+) → BI	Direct effect	0.148*	Supported
H2	PEU (+) → BI	Direct effect	0.653***	Supported
H3	PEU (+) → PU	Direct effect	0.520***	Supported
H4	FC (+) → AU	Direct effect	0.083	Not Supported
H5	BI (+) → AU	Direct effect	0.761***	Supported
Notes: * $p<$0.1; ** $p<$0.05; *** $p<$0.001; NS $p>$0.1

The outcomes of the relationships which were hypothetically proposed can be shown in Table 3, PU ($\beta =$ 0.148*; $p<$ 0.01) and PEOU ($\beta =$ 0.653***; $p<$ 0.001) brought into being to possess a significant positive effect on BI to use the construction-technology structure, supporting H1 and H2 and also PEOU ($\beta =$ 0.520***; $p<$ 0.001) was found to have a statistically significant positive effect on perceived usefulness, supporting H3 hypothesis. It must be notable that engineers were found to be extremely affected by their co-workers and trainers in using technology, FC was found to be statistically insignificant, FC ($\beta =$ 0.083; $p>$ 0.05) not supporting H4. Furthermore, the outcomes also illustrate that actual intention to use is impacted by the BI ($\beta =$0.761***; $p<$ 0.001) which supports H5.