INTRODUCTION:

In India, construction industry has played a crucial role and has contributed to an average of 8.04% GDP in the economic growth of the country. Additionally, construction sector has been functional in improving the quality of life of the people. It helps in improving the necessary social and economic infrastructure. This particular sector has shown a growth of 18% in the recent years which provides the evidence for its unlimited growth. In construction industry, there are many parameters by which a project can be evaluated such as cost optimization or material management. But when it comes to evaluate the project outcome or project success, the only scale by which one can measure is project management efficiency which accounts all considerable potential factors which include Machinery, Manpower, Monetary and Material. These primary factors are considered as latent variables under which further there are many secondary factors which are termed as manifest variables. Any factor which may influence the project management efficiency or outcome can be categorized into one of these four latent variables and hence, is a manifest variable. A literature review has been included which identifies all related factors and develops a hypothetical model with latent variables and manifest variables to investigate the construction sector. Coming to the latent variables being considered in this study, Material is one of the foremost factors which adds essence to the construction industry. It mirrors a major fraction of the total value of the project. Material Management system is needed to identify, acquire, store and distribute and ensure the disposal properly. This management system varies on the project, location and many factor. All factors which may be accounting for any change in the project outcome and related to the material management system have been enlisted as manifest variables under Materials. It includes various factors ranging from supply and delivery of materials to ineffective usage of materials. Secondly, Monetary related factors oil the wheels of project management efficiency and are the most conducive aspect of the project. The financial management assists in controlling all money related activities of any project ^[1]. It’s the foremost and primary resource of any construction work. All designs and speculations depend upon the budget of money allocated. There are many manifest variables which are accounted here such as, Cash flow processes or ineffective financial control onsite ^[2].

Third, Machinery has a considerable advantage over human resources as it can work consistently and continuously. And moreover, it can reduce the usage of manual labor. However, the costs associated with this factor is also huge and also has to be analyzed with utmost care. There are manifest variables to be considered under Machinery such as, failure of equipment etc. Finally, Manpower is another latent variable which is influential in the project management system. For any project ranging from small scale to large scale, manpower is as vital as financial aspect and if efficiently used, ensures the success of the project. Proper allocation of manpower with efficient utilization of human resources can provide good results. There are many manifest variables which can be considered into this particular latent variable such as overtime or labor costs. Human resource management is critical in project success and can reduce labor costs and thereby improve the financial aspect also. Below are the list of latent variables and manifest variables which are considered to be significant and influential in affecting the efficiency of project management:

Machinery:

1. Late Machinery production by manufacturers to contractors. If machinery produced by manufacturers is lagging behind in schedule, it may reach the construction site late, which may affect project efficiency.

2. Late transportation of machinery from place of manufacture to construction onsite. There may be problems in transportation of huge machinery which may require additional costs and may even take time thereby affecting project efficiency.

3. Inefficient installation or working of equipment.

If equipment is installed in the wrong manner, it may not function properly.

4. Ineffective usage of machines.

If a machine is not used to it full potential, it doesn’t ensure 100% efficiency.

5. Preference of new machines over old machinery.

If old machinery is used repeatedly, efficiency may decrease gradually, new machines are required then. If these new machines are not provided, then project efficiency may decrease.

6. Government subsidized initiatives on usage of machinery.

If government provides incentives for Small scale industrial units using machinery, this may encourage many industries to adopt machinery which may increase project efficiency.

7. Availability of equipment in local areas.

If equipment is available in local areas, then there may not be problems arising in transportation of equipment which may reduce time involved as well as costs.

8. Over usage of machinery.

A machinery if used beyond its potential may lead to failure of equipment.

9. Reuse of machinery.

Machinery can be re-used for multiple projects which may help in reduction of extra costs.

10. Additional and Customary requirements as per customer.

There may be additional and customary requirements of contractor due to which production of the machinery may become late for the manufacturer.

Monetary:

11. Delay in payment between any two parties.

If any party involved in a transaction is unable to proceed with the payment terms, it leads to the temporal halting of the project which affects the project efficiency.

12. Poor financial control management onsite.

There may be many financial decision involved in on-site management. And if the supervisor is unable to take the better decision, it may affect the project efficiency.

13. Labor Wages – Temporary or Permanent.

If labor wages are temporary or permanent, it may have different effects on the financial outcome of a project thereby affecting its project efficiency.

14. Ineffective contract making.

If a contract made between any two parties is made in such a way that there may be multiple loopholes, it can be nullified and exploited in many ways which negatively affects the project efficiency.

15. Improper budget allocation to different categories.

If the decision maker is unable to properly allocate the allotted money to various categories based on the priority, it may lead to improper financial control.

16. Effect of wages on labor.

Labor can be influenced by the types of wages- temporary or permanent as they would be working if they are assured of long term benefits in case of permanent wages or higher wages in case of temporary wages.

17. Fluctuation of machinery and material prices.

If prices of material and machinery change or fluctuate during the progress of a project, it may cynically affect the project efficiency.

18. Insurances to labor.

If a labor is provided many incentive such as insurance assurances, it may compel him to work in that particular environment.

19. Cash Flow processes.

Cash flow processes are an integral part of financial processing of any construction project and any inefficiency in cash flow processes may affect the efficiency of project management cynically.

20. Asset Management into budget allocation.

There may be many contractors who convert their assets into capital investment for projects. Such conversions may work efficiently only if the assets are sold at the expected rate.

21. Availability of alternative low-cost materials.

If materials which can be used as alternative instead of the conventional ones and if available at a cheaper rate, it would encourage the contractor to use these alternative options.

22. Added incentives if the project is completed within time or budget.

If the project is completed within a certain target of budget or time, the contractor will be provided with some added incentives which may encourage him to complete the project with better efficiency.

23. Usage of loans as capital investment.

Capital investment can either be provided within an organization or by a bank which may charge a rate of interest. It may lead to different financial solutions thereby affecting the project efficiency.

24. Safety and productivity bonus payments.

If a project is followed within the safety procedures and if all personnel involved in the project follow the required safety measures, bonus payments may be provided which encourages the workers.

25. Inaccurate cost estimates.

If a cost estimate is made with many mistakes, it may lead to ordering of materials more than required and may incur huge losses thereby affecting project efficiency.

26. Late charges on product delivery processes.

There may be extra penalty charges on delivery of any project extending beyond the deadline which may be unforeseen costs for the construction project.

Manpower:

27. Shortage of technical labor

If there isn’t enough technical labor to operate the machinery, it may lead to inefficient usage of machinery which may decrease the project efficiency.

28. Weak labor productivity.

If labor isn’t productive enough during the course of project, it may decrease the project efficiency.

29. Shortage of site labor.

If there isn’t enough site labor to work for the construction project, it would be difficult to complete the project within the deadline, thereby, decreasing project management efficiency.

30. Absence of Labor in Daily Shifts

If there isn’t enough presence from the labor, it would negatively affect the project efficiency. This is an issue frequently associated with daily contracted labor.

31. Lack of experience in personnel.

If there is experienced labor involved, it may lead to higher efficiency.

32. Incompetent sub-contractors

If there aren’t enough competent subcontractors or enthusiastic subcontractors, it may negatively affect the project efficiency.

33. Lack of communication between labor and higher management.

If there isn’t enough communication between any two managements, it may lead to mistakes in the project which negatively affects the project efficiency.

34. Availability of labor in local areas.

If there is enough labor in the local surrounding areas, we can avoid high costs of bringing labor from far areas which may affect the project efficiency.

35. Training and Safety of labor.

If there is enough training and if safety measures are taught to labor, it may increase the productivity and hence increase the project efficiency.

36. Disputes among labor (Strikes).

If there are disputes among labor, it may lead to strikes which delay the progress of projects and affect the project management efficiency.

37. Incentives and Promotion to labor.

If there are enough incentives and promotions assured to the labor, this may lead to encouragement of labor to work more extensively which increases project efficiency.

MATERIAL:

38. Availability of sustainable materials.

If there are sustainable materials available as alternatives to the conventional materials, they could be used which could increase the project efficiency.

39. Changes in Material Specifications.

If there are any changes in the specifications, it may lead to different outcome in the project which many decrease the project efficiency.

40. Quality Management in Materials.

If there is a quality management process which ensures that the quality of materials is improved, it may lead to increase in project efficiency.

41. Ineffective storage and preservation of materials.

If the materials are stored and preserved without enough attention, it may lead to wastage of materials which may decrease the project efficiency.

42. Prevention of wastage of materials.

If there is a proper management system which prevents wastage of materials, this may lead to better project management efficiency.

43. Usage of cheap materials.

In some projects, the sub-contractors may use cheap materials without caring about the quality which may decrease the project efficiency.

44. Recycling of materials.

If the materials used are recycled properly, they could be used in another project also which increase the project management efficiency.

45. Waste Minimization in construction sites.

If there is a waste management system which ensures that there is less waste produced, it would increase the project efficiency.

46. Local Availability of Materials.

If materials are available in the local areas, then there would be less efforts and costs involved in the transportation of materials from far away areas.

47. Quality of Materials purchased.

The Quality of Materials purchased plays a huge role as even though the project would be finished within the deadline, the degraded quality of materials used would affect the project efficiency.

48. Effect of weather conditions on material.

Weather Conditions are a major issue when it comes to quality of materials, since aggressive weather conditions may lead to the spoilage of material quality when materials are ineffectively stored and preserved.

49. Inappropriate usage of materials.

Materials should be used appropriately and wastage of any materials may lead to ineffectiveness in the project management thereby affecting project management efficiency.

50. Damage of materials using transportation.

Materials are transported to the site and during this time, enough care has to be ensured that the materials aren’t damaged during the transportation phase and if the materials are damaged, this may render the material useless.

METHODOLOGY:

As discussed, a total of 50 manifest variables are included under 4 latent variables, namely, Machinery, Monetary, Manpower and Material. A survey questionnaire was prepared for all the manifest variables and how they would be affecting project management efficiency. This survey questionnaire was targeted towards construction personnel in the field with significant work experience. A total of 83 responses were collected in the survey and these responses were obtained in the states of Andhra Pradesh and Telangana. The respondents involved in the survey were associated with various types of works in construction projects and also varied in specializing large scale projects as well as small scale projects. They ranged in working in Highway Projects, Residential Projects and Industrial projects etc. The responses collected for each question were on a scale of 1 to 5, with 1 being Not Significant and 2 being Slightly Significant and 3 being Moderately Significant and 4 being Very Significant and 5 being Extremely Significant. These responses were then recorded in an excel sheet. Then the Average of each result and the Standard Deviation was calculated through which the normalized data could be obtained and the correlation coefficients were also obtained. Normalization is a process which is normally done to convert all the given data to one set of common scale. The scaling factor is the standard deviation. Therefore, a data set with extreme values may have a greater effect on the outcome^[3]. Normalization of data is adjusting the values measured on different scales to a common scale. It is done so to align all the data distributions to normal distributions. To compare any two variables of different scales, we use normalization process so as to ensure that they are being evaluated on the same scale. Although this data does not need normalization, normalization is done to ensure that the data is enhanced and cannot be anymore better. By doing normalization, we ensure that the obtained data is not ill-conditioned and we obtain a clear linear relationship between variables. For instance, let’s say, we are counting the frequency of occurrence of a phenomenon in two different data sets and if we wanted to compare them, we need to normalize them to know the influence. From this normalized data, we obtain correlation coefficient^[4]. This correlation coefficient depicts the influence and correlation of the particular manifest variable on the desired output. This coefficient indicates the length to which pairs of variables lie on a straight linear line. For perfect linear relationship, the coefficient is +1 or -1. For example, if the correlation coefficient of one manifest variable was +0.08 and it was affecting the project outcome in a particular way and if it was -0.08, it would have the same magnitude of outcome, but in the opposite direction. Covariance divided by the standard deviations of the variables provides us the correlation coefficients. If the correlation coefficient is close to +1, it signifies that the variables have a positive linear relationship and the plot between the variables is a linear line with a positive slope and it could be considered a directly proportional relationship. Likewise, a correlation coefficient of -1 indicates the variable having the same linear relationship, with the sign being negative and in an inversely proportional relationship^[5]. So after obtaining the correlation coefficients, they are squared so as to cancel out their negative signs and the highest path analysis coefficient is obtained which can be deemed as the inhibiting factor. Graphs were also plotted with the top 5 manifest variables affecting project management efficiency and another graph showing the effect of latent variables on project management efficiency was also obtained. Individually, every latent variable has few factors which are more effective and these factors were also plotted on each graph of latent variable.

OBSERVATIONS:

Table 1(Sample Data of 8 questions and 6 survey cases)

	Question	1	2	3	4	5	6	7	8
Survey Case
1		2	3	1	2	1	3	3	5
2		5	1	3	4	1	4	1	4
3		5	3	5	1	2	3	5	4
4		5	3	3	1	3	3	3	4
5		4	1	4	3	2	2	5	5
6		5	5	3	1	5	3	4	2
Average		4.333	2.667	3.167	2	2.333	3	3.5	4
Std. Dev		1.105	1.374	1.213	1.154	1.374	0.577	1.384	1
Normalized Data
1		-2.111	0.243	-1.786	0	-0.97	0	-0.361	1
2		0.603	-1.213	-0.137	1.732	-0.97	1.732	-1.806	0
3		0.603	0.243	1.511	-0.866	-0.243	0	1.083	0
4		0.603	0.243	-0.137	-0.866	0.485	0	-0.361	0
5		-0.302	-1.213	0.687	0.866	-0.243	-1.732	1.083	1
6		0.603	1.698	-0.137	-0.866	1.94	0	0.361	-2

Table 1 shows the collected raw data for 8 survey questions and answering of 6 survey case studies for these questions. The averages and standard deviations of each manifest variable are calculated. If following a process without normalization, one can use the assistance of the average or mean to decide the most inhibiting factor among the manifest variables. The normalized data also is calculated using the given raw data, from which correlation coefficients and path effects could also be evaluated.

Figure 1 (Top factors affecting project management efficiency)

Figure 1 shows the top 5 manifest variables which have been instrumental in affecting the efficiency of project management. As mentioned, Inaccurate Cost Estimates has been a crucial factor because it has effects on almost every aspect of the project including financial aspects, material estimates etc. The next effective factor is Ineffective Storage and Preservation of Materials. This can owed to the fact that Materials are a foremost asset of any construction project and any negligence in their storage may lead to late project delivery.

Figure 2 (Latent Variables affecting Project Management Efficiency)

Figure 2 shows the comparison of 4 latent variables effects on project management efficiency. It comes with no surprise that Monetary factors tops the list due to the fact that Financial Management is one of the most vital aspect in Construction sector, followed by Manpower, Machinery and Material.

Figure 3(Major Manifest Variables of Machinery)

Figure 3 shows the top effective manifest variables under the latent variable, Machinery. The most effective variable is Government initiatives. The main reason most construction companies are less encouraged for usage of machinery is due to the non-availability of government subsidized initiatives for buying high cost machinery. If such initiatives and schemes are introduced, it will reduce the dependence of construction projects on manpower, thereby, increasing project management efficiency.

Figure 4(Major Manifest Variables of Monetary)

Figure 4 shows top effective manifest variables under the latent variable, Monetary. The most effective variable is Inaccurate Cost Estimates, followed by Fluctuation of prices and Asset Management. Fluctuation of prices has become an issue since it can falter with the initial cost budget of the construction project and lead to financial problems and even Asset Management is a crucial aspect of financial management which needs to be analyzed with caution.

Figure 5 (Major Manifest Variables of Manpower)

Figure 5 shows top effective manifest variables under the latent variable, Manpower. The most effective variable is Weak Labor Productivity and Lack of Communication between management and Labor. Weak Labor Productivity leads to lagging behind in project delivery schedule data and Lack of Communication leads to mistakes in the construction of a project.

Figure 6 (Major Manifest Variables of Material)

Figure 8 shows top effective manifest variables under the latent variable, Material. The most effective variable is Ineffective Storage and Preservation of materials followed by Prevention of Wastage. Ineffective Storage may lead to spoilage of materials which is an unforeseen cost in any construction project and ineffective preservation of materials would lead to shortage of materials which would delay the project.

CONCLUSION:

· It can be concluded that monetary factor has been the most influential and significant parameter in project management efficiency of any construction project. Following monetary factors, manpower factors also have a considerable impact on project management efficiency.

· Specifically, among the monetary factors, Inaccurate Cost Estimates has been the most effective manifest variable due to effect on various aspects of construction project. In manpower, the most effective manifest variable was weak labor productivity and lack of communication.

· Coming to machinery, Government subsidized initiative play a crucial role in determining project management efficiency. And for materials, storage and preservation of materials has found to be the influential factor.

REFERENCES:

1. Ameh, O.J., Soyingbe, A.D., and Odusami, K.T. (2010). Significant Factors Causing Cost Overruns in Telecommunication Projects in Nigeria. Journal of Construction in Developing Countries, 15.

2. Flyvbjerg, B., Holm, M., and Buhl, S. (2003). How common and how large are cost overruns in transport infrastructure projects? Transport Reviews, 23(1), 71-88. http://dx.doi.org/10.1080/01441640309904

3. Litwin, M. S. (1995). How to Measure Survey Reliability and Validity. Sage, Thousand Oaks, CA.

4. Nudurupati, S., Arshad, T., and Turner, T. (2007). "Performance measurement in the construction industry: An action case investigating manufacturing methodologies. Computers in Industry, 58(7), 667-676

5. Fornell, C. and D.F. Larcker, 1981. Evaluating structural equation models with unobservable variables and measurement error. J. Market. Res., 18(1): 39-50.

Received on 05.11.2015 Accepted on 06.12.2015

Int. J. Tech. 5(2): July-Dec., 2015; Page 157-163

DOI: 10.5958/2231-3915.2015.00013.9