There is an enormous number of motivational theories that have been employed to describe motivational factors that impact the motivation of workers. Theories of work motivation usually comprised both personality and situational traits [21]. Dwivedula and Bredillet [8] categorise motivation for workers as content-based and process-based theories. This categorisation was recognised by [4], who explain motivation as one directed towards motivating individuals, such as construction operatives whereas the process-based theories draw attention to motivation of operators. Abraham Maslow as one of the founders within the work motivation domain developed, well-known Needs Hierarchy Theory in 1943; The Maslow hierarchy needs theory has been a source of motivation for organisations and construction industry is no exception. Founded on Maslow’s theory, Schrader [22] anticipated a need for construction staff (artisans) motivation and recognised suitable methods that can address motivational issues. Hazeltine [23] proposed that the lower level needs are typically satisfied and the higher-level needs necessitate consideration. He encouraged that motivation can be utilised to accomplish the higher-level needs of construction workers (artisans). Shoura and Singh [24] highlighted the significance of self-development to satisfy the self-actualization requirement for construction engineers.

The construction industry in Ghana seems to be doing well, and indeed contributes significantly to gross domestic product (GDP) in Ghanaian economy and significantly employs good number of people to the economy. Ofori [25] informed that construction accounted for 7.2% of GDP in 2018 physical year. Again Ofori [25] posited that 584,513 peoples involve in construction, and out of that 316,368 peoples were employed, whereas those employed 309,312 gain their employment in informal sector. Moreover, Ofori [25] opines that 101,154 Apprentices are engaged in Ghanaian construction. The report from Ghana Statistical Service (GSS), was that amid 2009 and 2013, the construction and real estate industry accounted for 14.34 per cent to the country’s GDP [26]. Ghanaian construction industry appears to be one of the major employers in the economy as compare to number of people in the industry. The trend of growth rate of construction to GDP is accelerating from 2006 to 2016. The report of GSS [26] (2018) indicated that the growth rate of construction industry to GDP has been more than double, thus 5.7% and 13.7% in 2006 and 2016 respectively. The construction industry in Ghana is multifaceted in nature, since it involves various stakeholders [27] such as Ghana Institute of Construction (GIOC), Ghana Institution of Architects (GIA), Ghana Real-Estate Development Agency (GREDA), Ghana Institution of Engineers (GhIE) and Ghana Institution of Surveyors (GhIS). Also, the Ministry of Water Resources, Works and Housing, and Ministry of Road and Highways are responsible for housing and road respectively. However, other departments that play a tremendous role in Ghanaian construction industry are Architectural & Engineering Services Limited (AESL), Metropolitan, Municipal and District Authorities (MMDAs), Department of Feeder Roads, Department of Urban Roads, Ghana Highway Authority, Ghana Building contractors Association, Ghana Road contractors Association etc. all these bodies make management of construction complex. The challenges to Ghanaians construction industry cannot be underestimated. According to [28] challenges to construction sector in Ghana include planning deficiency, unsuitable water and energy use, building material consumption, not able to meet consumer/tenant requirements, and fragmented stakeholders’ cooperation in the industry. However, in the opinion of [29] all these challenges are the reasons for corruption and untransparent procurement procedures with regard to hiring services of consultants and contractors. Further, [30] opine that the continuous degradation of the environment has impacted the development in Ghana and has resulted in building construction procedures unsustainable. According to [31] the number of challenges recognised as impacting the various construction organisation involves difficulty in accessing sufficient fund to execute project, inadequate management deficiency, deficient in engineering competence and poor workmanship. Whereas Badu, Edwards and Owusu-Manu [32] acknowledge that available debt financing arrangement for large and small construction firms comes with very high interest rate and these are the leading causes of project abandonment. Adu Gyamfi et al. [33] discovered that delays in payments, under-budgeting, freeze in capital, bankruptcy of stakeholders, and corruption as financial challenges associated to public and private project.

The association between motivation and productivity is briefly described as a direct relationship amid motivation, and productivity. Motivation is, related to productivity. The proper motivation of craftsman can be assumed as a significant factor to enhance employees’ productivity, and employee’s performance in various institutions can be influenced mainly by motivation [34]. As opined by [35], numerous approaches of motivating employees exist as compared with different firms, establishments, organisations etc. working in the surroundings worldwide. There are common measures frequently used across all organisations to improve workers motivation. Strategies such as creativity and innovation, learning, empowerment, monetary incentive, quality of life and rewards are considered as measures to increase productivity. In the view of Woodman et al. [36] novelty and creativity are vital for organisational success and make organisations more competitive above their competitors. A commonly recognised explanation argues that creativity is producing new and valuable concepts, whereas innovation is the effective application of creative concepts in a society [37]. Gumusluoglu, and Ilsev [38] in their study found that creativity and innovation are vital in that it can contribute to identifying transformational leaders in organisations. Amabile [37] posits that creative ideas will be required not necessary for the development of novel, valuable products and services, but also the resolution of ever-changing and ever more mystifying business difficulties. Diliello & Houghton [39] predict that a great self-leader with high-level creative capacity, are always eager to apply creativity and innovations in their environment than a weak self-leader. Aghayar, [40] opined that the advantages of empowerment could be increasing of profit and quality satisfaction of the customer, feeling of belonging and ownership of personnel to the organisation, improvement of job’s condition and reduction of expenses, wastages, nervous pressure, accidents and direct control of the supervisor. Empowering workers to meet customer requirements or resolving problems related services are considered the best ways to satisfy customers to perform well in their workplace [41]. According to Spreitzer [42] empowerment offer workers the opportunity to make a decision and discretionary power over how they perform their work. Light [43] in her PhD dissertation found that personnel empowerment influences on job’s satisfaction, whenever their empowerment becomes more, their job’s satisfaction becomes more [44]. Bonner et al. [45] said, financial incentives influence workers to set targets when they have not thought of it, financial incentives may perhaps influence workers to set more demanding targets they have not thought of it; these targets, requires putting in much effort to attain the goals. Finally, financial incentives schemes might lead to higher commitment in setting targets as compare with non-incentive schemes [45]. Delfgaauw & Dur, [46] in their opinion when competition in organisations become high; employees had opportunities to decide on which agency they will attach themselves, owing to stronger incentives, idle workers are influenced to work harder in the public sector organisation, when they are aware that their remuneration is tied to their performance. Again, they opine that monetary incentives are not a motivator for the effort of the public worker, is a significant motivator to the effort in the private condition. According to Ariely, Bracha, & Meier, [47] monetary incentive depends significantly on what the workers see being implemented on incentives: financial incentives are more effective in expediating private, prosocial activities than public. The implication is that financial incentives as motivation promote workers prosocially.

The analysis of the demographic characteristics looked at respondents’ position held in the company, number of working experiences in the industry, age group and level of educational qualification. Table 1 presents results on the position held by respondents in the company.

Respondents specify how long they have worked in the industry. Their responses are presented in Table 2.

The findings revealed that the major part of the artisans had spent more than 6 years in the organisation. This revelation is in line with Aguinis [53] assertion that the longer you work in organisation the more you gain experience to perform task better. Perhaps one of the reasons could be due to the level of motivation in the organisation.

The study sought to determine the key factors that influence artisans’ motivation at the construction workplace. Table 3 indicates the results of motivational strategies that can be employed by construction industry practitioners to motivate artisans.

Smart PLS is one of the structural equation models (SEM) that, provides an explanation to association existing between multiple research items concurrently and further predicts the relationship among dependent and independent variables employed in the analysis. In the opinion of Gefen et al. [54] SEM has an exceptional benefit over linear regression; thus, SEM provides an opportunity to create an estimated model of many dependent variables and their interrelationship simultaneously. Again, the benefit of SEM over linear regression is that it

Source: Researchers’ Field survey (2020).

Source: Researchers’ Field survey (2020).

Source: Researchers’ Field survey (2020).

offers better results in path diagram analysis when multiple latent variables indicators are considered [54]. PLS-SEM is gaining popularity as numerous studies have been extensively employed PLS-SEM in social science disciplines, such as strategic management, supply chain management, operations management, human resource management, hospitality management, organisational management, information systems management, management of marketing, and accounting management [55] - [63]. Some of the researchers study workers’ motivation and performance in their various thematic areas and since the current study investigates the strategies for motivating artisans’ performance in building construction industry, the study adopts PLS-SEM to model the situation under consideration. Also, the study employs PLS-SEM because the structural model is complex and consists of many constructs, observed variables and model correlation, and application of small sample size [64]. The current study focused on how the various construct such as empowerment, qualify of life, learning and monetary incentive influences the dependent variable motivation as regards the construction operatives (Artisans). Moreover, PLS-SEM has user friendly interface and easy to work with [65] [66]. PLS SEM is described as a method most appropriate where the study intention is prediction or exploratory modeling. Whiles, covariance-based SEM is chosen when the study aim is confirmatory modeling [67].

Since the various observed variables are measuring the individual construct and the constructs are also determining their relationship with the dependent variable (motivation), these situations require a robust statistical tool to analyse these relationships, hence the application of Smart PLS-SEM. According to Gerbing and Anderson [68] for the construct to be analysed by PLS-SEM two essential procedures must be followed, thus the determination of path and measurement model. The path coefficient is used to predict the association between the dependent and independent variables. Chin [69] hypothesized that path coefficients and the R² are both employs to evaluate the model whereas the error estimates and t-values are applied to determined associations. The path coefficient is also used to test the hypothesis of the study. Table 6 signifies that t-values above 1.9 were all significant. The t-value for hypothesis H1, H3 and H4 were statistically significant with t-value as 1.948, 2.724 and 1.958 and p-value 0.052, 0.007 and 0.052 respectively. The t-statistic for H1, H3, and H4 support the study hypothesis as a strong association between study construct empowerment, quality of life, a monetary incentive and motivation. The observed indicators are used to determine the reliability and validity of the construct.

According to Hair et al. [70] reliability is the degree where a study produces the same results when applied in different situations. The type of reliability used for the survey was Cronbach alpha and Composite Reliability (CR) as revealed in Table 4, the study produces Cronbach alpha values between 0.759 to 0.876 which is acceptable good fit as recommended by [71]. According to Koufteros, [71] the CR represent a set of possible observe variables that share in their measurement of a construct. Diamantopoulos et al., [72] and Hair et al. [73] (2010:710) posited that a CR bigger than 0.60 is considered as the desired value, CR of 0.70

or higher stipulates strong composite reliability. Ning [74] stated that higher CR values show strong latent reliabilities, indicating an acceptable internal reliability from variable of each construct. The CR values of the study ranged from 0.704 to 1.00 as reported in Table 4. The study employed convergent and discriminant validity. The convergent validity is the degree of connection amid two different sources answering to the same measure. However, discriminant validity is the amount to which means of different latent variables are unmatched [75] [76]. Convergent validity is determined by considering the average variance extracted ( AVE ) and factor loadings of the construct variables. The AVE value of 0.5 or more is significant and factor loading of 0.5 or more is significant, indicating higher convergent validity [73] [74] [77]. From Table 4 AVE value ranges from 0.534 - 1.00, whereas factor loadings range from 0.534 - 0.975 indicating higher convergent validity for the study construct variables. However, the determination of discriminant validity can be achieved by using Fornell and Larcker [77] recommendation, that square root of AVE in each construct latent variable are employed to determine discriminant validity, when the value under consideration is more significant than other associated values amid the latent indicators. It can be observed from Table 4, that the lowest AVE value for construct latent variables is 0.534 when this value is squared base on the recommendation of Fornell and Larcker [74] (1981) the calculated results will be 0.731. The estimated value is higher than the correlated value obtained among the latent variables as indicated in Table 5. The result shows that the study has achieved strong discriminant validity. The reasons for such higher correlation are due to strong relationship among the constructs.

The study hypothesis (H1) theorized that there is an association between empowerment and motivation. The result is indicated in Table 6, and Figure 1 supported the study hypothesis with p < 0.052 and path coefficient of −0.165. The results show that empowering skilled craftsman in the construction site motivated them to perform adequately in their various work environments. The findings are in line with Chiang & Jang [41] (2008). They posited that empowering workers

Note: EMP = Empowerment, LENG = Learning, MOINTV = Monetary Incentive, MOT = Motivation, QUAOL = Quality of life.

Note: p < 0.05.

to meet customer requirements or resolving problems related services are considered the best ways to satisfy customers. According to Spreitzer [42] (1995) empowerment offers workers the opportunity to make a decision and discretionary power over how they perform their work. Light [43] (2004) showed that personnel empowerment influences on job’s satisfaction. Whenever empowerment becomes more, their job’s achievement becomes more [44] (Shelton, 2002).

The study hypothesis (H3) posited that there exists a significant correlation amid monetary incentive and workers’ motivation. The result is shown in Table 6 and Figure 1 supported the study hypothesis with p < 0.007 and path coefficient of −0.175. The result indicates that providing a monetary incentive to artisans in the construction industry motivated them to function effectively in their work environment. Bonner et al. [45] (2002) said, financial incentives may perhaps influence workers to set more demanding targets they have not thought of it; these targets, requires putting in much effort to attain the goals. Delfgaauw & Dur [46] (2004) in their opinion believed that when competition in organisations becomes high, employees had opportunities to decide on which agency they will attach themselves, due to stronger incentives. According to Ariely, Bracha, & Meier, [41] (2007) monetary incentive depends significantly on how workers experience its implementation: financial incentives are more effective in enabling private, prosocial activity than public. The study hypothesis (H4) hypothesised that there is a significant association amid quality of life and employee’s motivation. The result shown in Table 6 and Figure 1 supported the study hypothesis with p < 0.051 and path coefficient of −0.256. The result informs that ensuring quality of life among artisan in construction industry will motivate them to perform efficiently in their work environment.