Valuing the Contribution of Knowledge-oriented Workers to Projects: A Merit Based Approach in the Construction Industry Mehrdad Arashpour, (RMIT University, Australia) Majeed Shabanikia, (Isfahan University of Technology, Iran) Mohammadreza Arashpour, (Azad University, Iran) Abstract Evidence points to the fact that frequent resignation of project engineers from construction companies is primarily the result of dissatisfaction with the factors that shape the salary scale. This research aims to identify the major influencing factors in merit based salary calculation systems for knowledge-oriented engineers so as to more accurately reflect their contribution to construction projects. Results from a questionnaire sent to managers, engineers and HR professionals throughout the Iranian construction industry revealed that while there was overall agreement on principles for a merit-based approach, engineers in particular stressed ‘professional skills’, ‘experience’ and ‘creativity’. Management-oriented parties should take into account engineer perspectives in order to more accurately reflect the self-assessed contribution of these workers to construction projects. This research provides a basis for understanding the key factors in the merit based salary scale formulation through the construction industry. Keywords: Construction industry, knowledge-oriented workers, salary scale formulation Introduction As a rule of thumb the objective of any payment system is to attract, hold, and motivate employees. Consequently, such a system should be designed to not only help organisations to meet their goals, but also to improve employee performance and company productivity. Because construction projects are very employee intensive and need to attract a knowledge- oriented and professional workforce (Shabanikia 2009), the design of the payment system is crucial to employee retention. The aim of this study is to explore how managers, engineers and HR professionals in the Iranian construction industry perceive the value of the contribution of engineers to construction projects. It will then discuss a merit based wage system that includes project process and outcome in the salary scale formulation for “knowledge-oriented” engineers. This research has a direct application to construction industry supply chain companies that are seeking to reform their salary scales so as to retain their valuable assets by rewarding the contribution of a knowledge-oriented workforce. Literature Review Engineering companies work in a knowledge-oriented atmosphere. They are also production-oriented provided that drawings and document are considered as products. From this perspective, the construction industry needs engineers as knowledge-oriented workers. Knowledge workers are active in analyzing information, solving problems by means of their expertise, proposing opinions, and creating new items and services. In other words, engineers are idea and information processors. They are individuals who deploy their analytical and mental strengths more than hands in adding value to workplaces and are Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 2 likely to be autonomous, active and proud (Abdul-Aziz & Law 2012; Arif et al. 2012; Horibe 1999). Compensation systems can produce competitive advantages for construction firms as salary, working conditions, opportunities for promotion and lifelong learning are reported by both male and female employees as the most important factors (Chileshe & Haupt 2010). Valuing the contribution of knowledge-oriented HR to projects can increase productivity and skills of the personnel (Zakeri et al. 1996). One of the main methods of achieving job satisfaction in companies is to improve the salary structure and the social security system especially in developing countries (Fan & Yong 2011; Yisa, Holt & Zakeri 2000). Compensation structure acts as a tool for achieving companies’ strategic goals. Human resource performance appraisal is the core of project human resources management and the objective basis for implementing the scientific and rational salary management in project organisation (Cheng & Fan 2010). In fact, compensation strategy is the major component of the companies’ strategy, creating competitive advantages and success as well (Ferguson and Parsons 1992). Valuing the contribution of knowledge-oriented HR has two functions of attracting and retaining skilled workforce and also directing their efforts towards organisational goal (Chen & Edgington 2005). Therefore, the most important outcome of a merit-based compensation system is to create a fair dealing atmosphere within organisations (Konopaske & Werner 2002; Milkovich et al. 1999). In terms of employees’ demonstrable qualities, knowledge-oriented workers usually have four characteristics: performing cross-disciplinary tasks, acting with flexibility, attempting towards organisational objectives and collaborating with team members (Arashpour & Arashpour 2012; Flannery, Hofrichter & Platten 2003). Motivational pay systems aim to arouse the initiatives of staff by means of perfecting the structure of pay management, expanding the proportion of unfixed pay and defining the bonuses based on measures of performance (Anantatmula & Shrivastav 2012; Li 2011). In the field of human resource studies, little if any research has analysed interdependent factors associated with valuing the contribution of knowledge-oriented workers in the construction industry. The present research tries to bridge this gap. Research Method The method for the present study comprises a comprehensive literature review and a survey of the Iranian construction industry. Finally factors influencing the salary scale formulation in the construction industry are ranked based on respondents’ perspectives and significant differences in perspectives are discussed comprehensively. The questionnaire was designed to elicit perspectives that respondents had with regard to the significant factors for salary scale formulation. As such, the main feature of the survey asked respondents to classify influencing factors on salary calculation by their level of importance in the construction industry. A bipolar scaling system, which helps the respondents to express their ideas clearly, was employed (Sekaran 2006). Respondents identified each of the factors as “very insignificant = 1”, “insignificant = 3”, “neither significant nor insignificant = 5”, “significant = 7” or “very significant = 9”. A total of 185 survey questionnaires were sent out in April-August 2011 to selected construction firms. The respondents were an array of experts from the construction supply chain. Managers, engineers and HR professional were targeted as responding groups due to the aim of the research. The majority of participants came from firms employing more than 200 people (46.5 per cent), whilst 33.7 per cent were employed by firms with 50- 200 personnel. Only 19.8 per cent of respondents worked for firms employing less than 50 Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 3 people. Care was taken to select experienced individuals. No respondent had less than 10 years of experience in the construction industry. Of 185 sent questionnaires, 150 responses were deemed valid. The survey listed 20 factors associated with job and personal characteristics, which were sourced from a number of references presented in Table 1. Personal and Job related factors Who and when 1. Professional skills (Clemens 2009) 2. Leadership skills (Morrison 1994) 3. Compliance with organisations norms and values (Becker, Huselid & Ulrich 2001; Weaver & Trevino 1999) 4. Academic records (Chen & Edgington 2005; Robinson & Sexton 1994) 5. Creativity (Tian & Belk 2005) 6. Duration of employment in the current company: long term commitment (Cowherd & Levine 1992; O'Malley 2000) 7. Education relevancy (Arashpour & Farzanehfar 2011; Coelho 2010) 8. Experience quality: Local experience (Monks 1996) 9. Graduating university (Dowling & Fisher 1997) 10. Level of responsibility (McAuliffe et al. 2009) 11. Number of employees under management (Arashpour & Arashpour 2010; Delaney & Huselid 1996) 12. Overtime amount (Wilson 2008) 13. Performance speed and efficiency (Flannery, Hofrichter & Platten 2003) 14. Relevant past experience (Medoff & Abraham 1981) 15. Tasks complexity (Allan 2000; Verburg, Den Hartog & Koopman 2007) 16. Working condition: Physical and psychological (Milost 2007) 17. Years of experience (Arashpour, Wakefield & Blismas 2012) 18. Working hours (Johnson & Lipscomb 2006) 19. Workload (Bradley et al. 2010; Hollands & Wickens 1999) 20. Performance quality: outcomes (Paauwe & Boselie 2005) Table 1 Summary of personal and job related factors influencing salary calculations for knowledge-oriented workers The final question asked respondents to evaluate their own organisational attitudes towards knowledge-oriented workers. They were asked to select ‘satisfactory’ or ‘unsatisfactory’ in response. They had opportunity to make suggestions for improving salary scales through the construction industry. Data Analysis The analysis included the frequencies of the various respondents’ answers and the relative importance or rank of answers compared to others based on analysis of variance (ANOVA) Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 4 test. The results demonstrated significant differences among the means of the various responding groups. The F statistic demonstrated if two given variances differed from one another or were from the same population (Sekaran 2006). A post-hoc test complemented the ANOVA to identify the groups with opposing views. Tukey's HSD (honestly significant difference) test was selected as the post-hoc to compare all possible pairs of means based on a studentized range distribution (q) which is very similar to t-test distribution. First and foremost, to evaluate the reliability (providing same results in different situations by measurement instrument), and validity (exact measurement of the variables by the instrument), the following results were extracted by SPSS. Software evaluation illustrates the reliability of survey outcomes. Since Cronbach’s Alpha is 0.771 and it is greater than the benchmark of 0.7, the reliability of questionnaire results analysis is approved (See table 2). This table also illustrates the validity of results analysis for the two groups of variables. For the set of variables the Kaiser-Mayer-Oklin Measures of Sampling Adequacy is 0.575. As it is greater than the benchmark of 0.5, the validity of results is approved. Reliability of results Validity of results Cronbach’s alpha= 0.771 KMO measure of sampling adequacy= 0.575 Table 2 Data reliability and validity test Results and Discussions A key measure for the validity of this research was the distribution of survey responses across knowledge-oriented workers in the construction industry. In the current research, engineers (41.3%), and managers (40.8%) made up the majority of respondents and the remainders were HR professionals (17.9%). All respondent were involved in the construction industry projects. Of the respondents surveyed, 40.1% had 10-20 years of experience in the construction industry and 54.7% had more than 20 years. The wealth of experience is evenly dispersed throughout the industry and thus the high percentage of experienced respondents also validates the results of the survey. Furthermore, none of the HR professionals who responded to the survey had less than 10 years of experience. Influencing factors on salary calculations in construction industry Table 3 presents factors influencing the salary scale of knowledge-oriented personnel identified by the respondents. It compares and contrasts opinions of managers, engineers and human resource professionals. The most important factor identified was ‘performance quality’ with a mean of 8.34 and standard deviation (σ) = 0.98. It was followed by ‘compliance with organisation norms and values’ with a mean of 7.81 and σ = 0.90. Other important factors averaging above significance (scale 7) were ‘professional skills’, ‘relevant past experience’, ‘creativity’, ‘educational relevancy’, ‘leadership skills’, and ‘level of responsibility’. The factors considered to be least important were ‘academic records’, ‘graduating university’ and ‘duration of employment in the current company’. Some significant factors such as ‘compliance with organisations norms and values’ and ‘professional skills’ identify that personal characteristics are important factors in the salary calculation of knowledge-oriented workers. This finding is consistent with the literature where Horibe (1999) identified similar results, indicating this as a characteristic for unique knowledge workers. A great evidence to validate the survey design and factor selection is that none of the 20 investigated factors were identified ‘insignificant’ (i.e. factors with average means below 3) by the survey respondents. http://en.wikipedia.org/wiki/Sample_mean http://en.wikipedia.org/wiki/Studentized_range_distribution Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 5 Key factors to calculate salary Total perspective Managers’ perspective Engineers’ perspective HR professionals’ perspective Mean SD Mean SD Mean SD Mean SD 1 Performance Quality (outcomes) L e a s t i m p o rt a n t fa c to rs M o s t im p o rt a n t fa c to rs 8.34 0.98 8.40 1.20 8.27 0.84 8.35 1.20 2 Compliance with organisation norms and values 8.29 0.90 8.01 0.64 7.98 0.79 8.87 0.80 3 Professional skills 7.69 0.88 7.47 0.70 8.53 0.70 7.07 1.10 4 Relevant past experience 7.63 0.88 7.00 0.89 8.43 1.00 7.47 1.07 5 Creativity 7.43 0.85 7.43 0.68 8.41 0.89 6.45 0.85 6 Educational relevancy 7.23 0.83 7.02 0.83 7.00 1.01 7.67 1.40 7 Leadership skills 7.19 1.01 7.76 0.71 7.08 0.81 6.73 1.25 8 Level of responsibility 7.01 1.00 7.02 1.23 7.74 0.70 6.27 0.65 9 Years of experience 6.64 0.93 6.45 0.65 7.09 0.85 6.38 1.00 10 Work load 6.46 1.05 6.02 1.06 7.43 0.99 5.93 1.10 11 Working hours 6.45 0.90 6.79 0.63 5.35 0.95 7.21 1.00 12 Performance speed 6.24 1.03 6.31 0.99 6.70 0.93 5.71 1.05 13 Experience quality (Local experience) 6.21 0.97 6.29 0.76 5.93 0.85 6.41 1.25 14 No. of employees under management 6.05 0.89 6.18 0.61 5.81 0.79 6.16 1.20 15 Complexity of tasks 5.88 1.16 6.01 0.84 7.00 0.80 4.63 0.70 16 Working condition 5.54 0.80 5.01 0.89 6.61 0.91 5.00 0.52 17 Overtime amount 5.43 1.06 4.63 0.98 6.76 0.70 4.90 1.00 18 Duration of employment in the current company 5.16 1.05 6.09 1.00 4.10 1.00 5.29 0.40 19 Graduating university 5.06 1.13 4.94 1.00 5.26 0.70 4.98 1.00 20 Academic records 5.03 1.11 4.83 1.07 5.23 0.90 5.03 1.40 Table 3 Influencing factors on salary calculation: Diverse perspectives across construction industry Interestingly, engineers considered ‘professional skills’ as the most important factor. This is perhaps due to the high emphasis that knowledge-oriented workers place on the professional promotion. In the case of managers, ‘performance quality’ ranked as the most important factor in the salary calculation within the construction industry. This finding implies that there are continuous concerns at the top managerial levels about actual quality performance of highly skilled recruited employees. This result is alarming considering that compensation practices should contribute to competitive advantage by promoting more Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 6 productive workers. High-ranking factors reflected by HR professionals were ‘Compliance with organisation norms and values’, ‘Performance Quality (Best effort)’ and ‘Relevant professional experience’. As the frontline agent in recruiting, HR professionals consider the organisation norms and values as very important and employees’ compliance is regarded as highly significant factor in the salary scale formation. Table 4 summarizes significant factors (i.e. factors averaging above scale 7) identified in valuing HR contribution by the knowledge- oriented workers in the construction industry. Respondent Factors (In Order of Importance) Mean Manager Perspective (8 factors) Performance Quality 8.40 Compliance with organisation norms and values 8.01 Leadership skills 7.76 Professional skills 7.47 Creativity 7.43 Level of responsibility 7.02 Educational relevancy 7.02 Relevant past experience 7.00 Engineer Perspective (11 factors) Professional skills 8.53 Relevant past experience 8.43 Creativity 8.41 Performance Quality 8.27 Compliance with organisation norms and values 7.98 Level of responsibility 7.74 Workload 7.43 Years of experience 7.09 Leadership skills 7.08 Educational relevancy 7.00 Complexity of tasks 7.00 HR professional Perspective (6 factors) Compliance with organisation norms and values 8.87 Performance Quality 8.35 Educational relevancy 7.67 Relevant past experience 7.47 Professional skills 7.07 Working hours 7.00 Table 4 Most significant factors in valuing knowledge-oriented workers’ contribution to construction projects Surprisingly, whereas engineers identified 11 significant factors that should contribute to their salary calculation, managers and HR professionals only suggested eight and six factors, respectively. It shows that engineers expect the salary scales to include more contributing factors. Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 7 To find the controversial factors that attracted different perspectives, analysis of variance (ANOVA) was used for further statistical analysis of the survey results. As there were 20 variables and three groups of respondents, namely managers, engineers and HR professionals, ANOVA is the best mean to find out significant differences among survey participants’ opinions. “Whereas the (independent samples) t-test indicates whether or not there is a significant mean difference in a dependent variable between two groups, an analysis of variance (ANOVA) helps to examine the significant mean differences among more than two groups” (Sekaran 2006, p. 347). Table 5 summarizes the ANOVA results, highlighting six factors with significance difference (less than 0.05). No. Factor Sum of Squares Mean Square F statistic Significance of F 1 Performance Quality .430 .215 526.750 0.043 2 Compliance with organisation norms and values 25.543 12.772 31290.583 0.065 3 Professional skills 56.920 28.460 69727.000 0.034 4 Relevant past experience 53.123 26.562 65076.083 0.057 5 Creativity 96.040 48.020 117649.000 0.048 6 Educational relevancy 14.530 7.265 17799.250 0.066 7 Leadership skills 27.430 13.715 33601.750 0.045 8 Level of responsibility 54.030 27.015 66186.750 0.059 9 Years of experience 15.310 7.655 18754.750 0.061 10 Workload 70.770 35.385 86693.250 0.000 11 Working hour 90.750 45.375 111168.750 0.066 12 Performance speed 24.870 12.435 30465.750 0.052 13 Experience quality (Local experience) 6.240 3.120 7644.000 0.062 14 No. of employees under management 4.330 2.165 5304.250 0.067 15 Complexity of tasks 96.330 48.165 118004.250 0.043 16 Working condition 85.870 42.935 105190.750 0.062 17 Overtime amount 134.490 67.245 164750.250 0.056 18 Duration of employment in the current company 1.270 .635 1555.750 0.054 19 Graduating university 3.040 1.520 3724.000 0.071 20 Academic records 4.003 2.002 6538.778 0.066 Table 5 ANOVA analysis results: significantly different factors by participating groups (Sig<0.05 highlighted) As it is evident from the results, there are six significantly different factors by responding groups: compliance with organisation norms and values, professional skills, creativity, leadership skills and complexity of tasks, applying a confidence level of 95%. Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 8 In the next step of the data analysis, Tukey's HSD (honestly significant difference) test was used to compare all possible pairs of means based on a studentized range distribution. Table 6 illustrates the results of post-hoc Tukey test. Dependent Variable (I) Person (J) Person Mean Difference (I-J) Std. Error Significance Performance quality engineer manager -.13000 .00407 .045 HR -.08000 .00516 .011 Professional skills engineer manager 1.06000 .00362 .037 HR 1.46000 .00601 .008 Creativity engineer manager .98000 .00404 .030 HR 1.96000 .00516 .016 Leadership skills engineer manager -1.06000 .00209 . 063 HR .40000 .00103 .038 Workload engineer manager 1.41000 .00415 .039 HR 1.50000 .00328 .022 Complexity of tasks engineer manager .99000 .00439 .047 HR 2.37 .00401 .003 Table 6 Tukey's HSD (honestly significant difference) test: significantly different perspectives among groups The Post-hoc test reveals that engineers have significantly different perspectives about performance quality than have managers and HR professionals. Engineers rank this factor below other factors such as professional skills and creativity. This could be due to the fact that engineers consider the process of doing tasks as more important than outcomes; however, managers and HR professionals focus more on outcomes to measure performance quality as evidenced by their high ranking of this factor in salary scale formulations. In addition, the similar perspectives of management-oriented parties unveils the deep influence of managers on HR practices in engineering companies (Paauwe & Boselie 2005). Tukey’s HSD results for the Post-hoc test reveal significantly different perspectives about professional skills and complexity of tasks. Both managers and HR professionals underestimated these factors compared to engineers, which is evident from the negative mean difference illustrated in table six. It is probable that engineers regard professional skills as a kind of toolkit to get the work done. However, the other two management-oriented groups paid less attention to these factors focusing more heavily on the best results from their knowledge-oriented workers. Creativity is also a source of controversy. While engineers consider creativity as a very significant factor, HR professionals did not believe so. This might be because of the fact that HR professionals tend to quantify outcomes of employees’ jobs; however, creativity is very hard to quantify. It is not surprising that managers ranked creativity below compliance to organisational norms and values. In fact, some managers consider this quality as a potential threat to established rules and work routines in their organisation (Arashpour & Arashpour 2011). http://en.wikipedia.org/wiki/Sample_mean http://en.wikipedia.org/wiki/Studentized_range_distribution Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 9 Interestingly, HR professionals did not rate leadership skills as a significant factor but managers put more stress on this factor. It is likely that managers prefer a more autonomous workforce without the need for continuous instructions. Despite the managers’ desire to maintain hierarchy in their organisations, this finding shows their reluctance to be involved in administrative tasks. Results illustrate that ‘workload’ is another significant factor identified by engineers. It is likely that engineers, who work at the frontline of construction projects, are more concerned about balancing professional and family lives. However, management-oriented respondents did not consider workload as important as the performance quality. In response to the question about the degree of satisfaction about organisational attitudes towards knowledge-oriented workers, the majority of respondents (62.5%) felt that their organisation’s attitude was unsatisfactory, and this perception was stronger downstream in the industry (i.e. engineers). Most of the 27.5% of respondents considering their organisation’s performance as satisfactory were managers. Less dispersed in the results was the typical consensus that respondents’ organisations could implement the merit-based approach to salary calculation, paying special attention to both job outcomes and the processes involved to do jobs (83% of survey participants). Conclusion Prior work has documented the measures assessing performance of employees in the construction industry; Becker, Huselid and Ulrich (2001) for example, report how to link people, strategy and performance in firms. However, few researchers have analysed interdependent factors associated with valuing the contribution of knowledge-oriented workers in the construction industry This paper has presented the results of a survey on factors influencing merit based salary scale formulation in order to optimize the contribution of knowledge-oriented engineers in construction projects. It was assumed that process- oriented (engineers) and management-oriented (managers and HR professionals) parties would be able to provide valuable perspectives on the issue. The engineers perceive their work as complex and the salary scale should reflect that complexity by the inclusion of more process-oriented factors. This view conflicts with that of the two management-oriented parties, which focus more on outcome-related factors. While all parties agree in principle to a merit-based approach to salary calculation, each identified different key criteria for measuring merit. The survey illustrated that ‘performance quality’ was the most important factor identified by all parties. Other important shared perspectives included ‘Compliance with organisation norms and values’ and ‘Professional skills’. However, variations were identified in the ranking of these factors. From the HR professionals’ perspective, ‘Compliance with organisation norms and values’ was identified as the most important factor followed by ‘Performance Quality’, factors which emphasize job outcomes over processes. This is in direct contrast with factors identified by engineers as most significant, such as professional skills, experience and creativity. The findings suggest that if companies are to value the work of these knowledge-oriented engineers, not only the job outcomes but also the processes involved in doing the job should be considered in the formulation of a merit based salary scale. After all, the construction industry is only as strong as its knowledge-oriented workers. Replication of this study in construction industries in other regions of the world is recommended. Similar results might be achieved because of the significant difference in focus between management-oriented and process-oriented individuals, which is a characteristic of the different work aims and intentions. Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 10 References Abdul-Aziz, A.R. and Law, Y.H. (2012) 'Civil Engineering Consultants from Developing Countries: An Exploration of Malaysian Firms', International Journal of Construction Management, 12 (2) 1- 21 Allan, C. (2000) 'The hidden organisational costs of using non-standard employment', Personnel Review, 29 (2) 188-206 Anantatmula, V.S. and Shrivastav, B. (2012) 'Evolution of project teams for Generation Y workforce', International Journal of Managing Projects in Business, 5 (1) 9-26 Arashpour, M. and Arashpour, M. (2010) Gaining the Best Value from HR in Construction Companies, Proceedings of the 6th European Conference on Management Leadership and Governance ---- 2011, 'Important factors influencing personnel performance of construction companies', paper presented to International Conference on Economics, Business and Management, Manila, Philippines Arashpour, M. and Arashpour, M. (2012) 'A collaborative perspective in green construction risk management', paper presented to 37th Annual Conference Of The Australasian Universities Building Educators Association (AUBEA) Arashpour, M. and Farzanehfar, P. (2011) Project management and control, 1 edn, vol. 1, ISBN: 978-600-5442-74-8, Tehran Arashpour, M, Wakefield, R & Blismas, N 2012, 'Role of simulation in construction processes- Harmony in capturing resources- DOI: 10.3850/978-981-08-7920-4', paper presented to Research, Development, and Practice in Structural Engineering and Construction, Curtin University, Perth. Arif, M., Khalfan, M.M.A., Barnard, J.H. and Heller, N.A. (2012) 'Assessing knowledge retention in construction organisations: Cases from the UAE', Australasian Journal of Construction Economics and Building, 12 (2) 55-71 Becker, B.E., Huselid, M.A. and Ulrich, D. (2001) The HR scorecard: Linking people, strategy, and performance, Harvard Business Press Bradley, L., Brown, K., Lingard, H., Townsend, K. and Bailey, C. (2010) 'Talking the talk and walking the walk: How managers can influence the quality of work-life balance in a construction project', International Journal of Managing Projects in Business, 3 (4) 589-603 Chen, A.N.K. and Edgington, T.M. (2005) 'Assessing value in organizational knowledge creation: Considerations for knowledge workers', Management Information Systems, 29 (2) 279-309 Cheng, Y-J amd Fan, X-M (2010) 'The study of DEA method in performance evaluation of project human resource management', paper presented to 17th International Conference on Management Science and Engineering, ICMSE 2010, November 24, 2010 - November 26, 2010, Melbourne, VIC, Australia Chileshe, N. and Haupt, T.C. (2010) 'An empirical analysis of factors impacting career decisions in South African construction industry: Male and female high school students' perspectives', Journal of Engineering, Design and Technology, 8 (2) 221-39. Clemens, M. (2009) 'Skill flow: A fundamental reconsideration of skilled-worker mobility and development', Working paper 180. Centre for Global Development. Coelho, JVP 2010, 'Competence certification as a driver for professional development: A IT- related case-study', paper presented to Education Engineering (EDUCON), Lisbon, Portugal Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 11 Cowherd, D.M. and Levine, D.I. (1992) 'Product quality and pay equity between lower-level employees and top management: An investigation of distributive justice theory', Administrative Science Quarterly, 37 (2) 302-20. Delaney, J.T. and Huselid, M.A. (1996) 'The impact of human resource management practices on perceptions of organizational performance', Academy of management Journal, 39 (4) 949-69. Dowling, P.J. and Fisher, C. (1997) 'The Australian HR professional: A 1995 profile', Asia Pacific Journal of Human Resources, 35 (1) 1-20 Fan, G. and Yong, S. (2011) 'A demonstration research on job satisfaction of the employee from the private enterprise - Based on LH Group Co., LTD. Tang Shan', paper presented to 2011 International Conference on Business Management and Electronic Information, BMEI 2011, May 13, 2011 - May 15, 2011, Guangzhou, China Flannery, T.P., Hofrichter, D.A. and Platten, P.E. (2003) People, Performance, & Pay: Dynamic Compensation for Changing Organizations, Free Press. Hollands, J.G. and Wickens, C.D. (1999) Engineering psychology and human performance, Prentice Hall New Jersey Horibe, F. (1999) Managing knowledge workers: New skills and attitudes to unlock the intellectual capital in your organization, Wiley Johnson, J.V. and Lipscomb, J. (2006) 'Long working hours, occupational health and the changing nature of work organization', American Journal of Industrial Medicine, 49 (11) 921- 929 Konopaske, R. and Werner, S. (2002) 'Equity in non-North American contexts: Adapting equity theory to the new global business environment', Human Resource Management Review, 12 (3) 405-41. Li, Y. (2011) 'Exploring and analysis on strategies of SMEs' human resource management in the period of post financial crisis', paper presented to 2nd International Conference on E- Business and E-Government, ICEE 2011, May 6, 2011 - May 8, 2011, Shanghai, China McAuliffe, E., Bowie, C., Manafa, O., Maseko, F., MacLachlan, M., Hevey, D., Normand, C. and Chirwa, M. (2009) 'Measuring and managing the work environment of the mid-level provider-the neglected human resource', Human Resources for Health, 7 (1) p. 13 Medoff, J.L. and Abraham, K.G. (1981) Experience, performance, and earnings, National Bureau of Economic Research Cambridge, Mass., USA Milkovich, G.T., Newman, J.M., Milkovich, C. and Mirror, T. (1999) Compensation, Irwin/McGraw-Hill Milost, F. (2007) 'A dynamic monetary model for evaluating employees', Journal of Intellectual Capital, 8 (1), 124-38 Monks, K. (1996) 'Global or local HRM in the multinational company: the Irish experience', International Journal of Human Resource Management, 7 (3), 721-735 Morrison, E.K. (1994) Leadership skills: Developing volunteers for organizational success, Da Capo Press O'Malley, M. (2000) Creating commitment: How to attract and retain talented employees by building relationships that last, John Wiley & Sons Paauwe, J. and Boselie, P. (2005) 'HRM and performance: what nexta?', Human Resource Management Journal, 15 (4), 68-83 Robinson, P.B. and Sexton, E.A. (1994) 'The effect of education and experience on self- employment success', Journal of Business Venturing, 9 (2), 141-156 Australasian Journal of Construction Economics and Building Arashpour, M et al. (2012) ‘Valuing the contribution of knowledge-oriented workers to projects: a merit based approach in the construction industry’, Australasian Journal of Construction Economics and Building, 12 (4) 1-12 12 Sekaran, U. (2006) Research methods for business: A skill building approach, Wiley-India Shabanikia, M. (2009) ‘An investigation and recommendation for a system of salary and fringe benefit in consultant companies’ Unpublished MS dissertation, Grenoble University. Tian, K. and Belk, R.W. (2005) 'Extended self and possessions in the workplace', Journal of Consumer Research, 32 (2) 297-310 Verburg, R.M., Den Hartog, D.N. and Koopman, P.L. (2007) 'Configurations of human resource management practices: a model and test of internal fit', The International Journal of Human Resource Management, 18 (2), 184-208 Weaver, G.R. and Trevino, L.K. (1999) 'Compliance and values oriented ethics programs: Influences on employees' attitudes and behavior', Business Ethics Quarterly, 9 (2) 315-35. Wilson, A.L. (2008) Financial Management for Health-System Pharmacists, ASHP publications. Yisa, S.B., Holt, G.D. and Zakeri, M. (2000) 'Factors affecting management motivation in the Iranian construction industry: a survey of site managers', paper presented to Proceedings of the 16th annual conference, ARCOM Association of Researchers in Construction Management, 6–8 September. Zakeri, M., Olomolaiye, P.O., Holt, G.D. and Harris, F.C. (1996) 'A survey of constraints on Iranian construction operatives' productivity', Construction Management & Economics, 14 (5), 417-426