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Discuss about the Analysis Of Decreasing Productivity For Construction.

Data Analysis

The study of the research topic of ‘Analysis of decreasing productivity (MFP and LP) for construction and manufacturing industries’ would be developed for understanding the simplification of the effective and smart analysis development. The analysis of the factors like design issues, changes, delays, exhaustion of resources, and limiting carbon emission would help in understanding the impact on decreasing productivity of (MFP and LP). The study would comprise the involvement of the literature review of the topic for determining the understanding of the situation and formation of the effective and smart project completion process. The identification of the research objectives would be considered for successfully effecting the development of the improved operations. The project schedule has been developed for the implication of the operations and alignment for easing the implication of the effective and smart functional development. The Ms-Project is developed for easing the implication of the factors aligning the development of the improved communication. The Gantt chart is the diagrammatical representation of the factors aligning with the utilization of the timeline for the alignment of the effective project completion.

The data analysis from the sources would allow the identification of the possible change in fluctuation using the improved factor analysis. The analysis of the study of ‘Estimates of Industry Multifactor Productivity’ would allow the simplification of the factors of decreasing the productivity of the organization. The analysis of the factors like design issues, changes, delays, exhaustion of resources, and limiting carbon emission would help in understanding the impact on decreasing productivity of (MFP and LP). The organization is composed many sectors and the analysis would be dependent on taking care of the operations. The analysis of the data would show the concept of % change in productivity with the involvement of the improved formation. The table has shown the change in MFP, labour input and labour productivity.  The variables required for the data analysis are change in MFP/LP and Time. The comparison of the two variables would be effective for understanding the decrease in the productivity

The project research plan has been developed for considering the research on the topic of analysis of decreasing productivity (MFP and LP) due to the increasing possible risks and issues in construction and manufacturing industries. The following is the source of data required for the execution of the research work,

Article Name: 5260.0.55.002 - Estimates of Industry Multifactor Productivity

Year: 2017, Website Source: www.abs.gov.au

Data Sources

The project research plan has been developed for considering the research on the topic of analysis of decreasing productivity (MFP and LP) due to the increasing possible risks and issues in construction and manufacturing industries. The quantitative research methodology with secondary data analysis had been used for analysing the factors of decreasing productivity (MFP and LP) for construction and manufacturing industries. The variables required for the data analysis are change in MFP/LP and Time. The comparison of the two variables would be effective for understanding the decrease in the productivity.

The project research plan has been developed for considering the research on the topic of analysis of decreasing productivity (MFP and LP) due to the increasing possible risks and issues in construction and manufacturing industries. The traditional waterfall model would be most optimistic for execution of the research project. The support and development would be aligned for executing the project in four phases. Each of the project phases would be aligned with the next phase for the completion of the project execution. The research project involves the phases of research initiation, plan development, activities execution, and closing. The quantitative research methodology with secondary data analysis had been used for analysing the factors of decreasing productivity (MFP and LP) for construction and manufacturing industries.

The following are the research questions for the project,

  • Why the productivity rate (MFP and LP) decreasing for construction and manufacturing industries?
  • What is the declining rate of MFP in the last 15 years?
  • What is the declined state of LP for different countries and OECD?

Secondary data has been used for the study and understanding of the decreasing productivity (MFP and LP) with the passage of time for construction and manufacturing industries. The qualitative research would be based on the simplification of the functions utilizing the secondary data resource. The quantitative research methodology with secondary data analysis had been used for analysing the factors of decreasing productivity (MFP and LP) for construction and manufacturing industries. The quantitative study limits the project data with the factor of data being authentic and effective. The inclusion of the improved functional and development process would be helpful for easing the development of the successful and effective data analysis.

The research project of ‘analysis of decreasing productivity (MFP and LP) due to the increasing possible risks and issues in construction and manufacturing industries’ would be aligned for easing the utilization of the factors describing the utilization of the effective and smart formation process. The following is the project schedule for the research activities on the topic.

WBS

Task Name

Duration

Start

Finish

Predecessors

0

Analysis of decreasing productivity (MFP and LP) for construction and manufacturing industries

39 days

Mon 9/3/18

Thu 10/25/18

1

Research Initiation

10 days

Mon 9/3/18

Fri 9/14/18

1.1

Resource Accumulation

4 days

Mon 9/3/18

Thu 9/6/18

1.2

Analysis of research requirements

2 days

Fri 9/7/18

Mon 9/10/18

2

1.3

Documenting the initial requirements

3 days

Tue 9/11/18

Thu 9/13/18

3

1.4

Document Submission

1 day

Fri 9/14/18

Fri 9/14/18

4

1.5

Kick off

0 days

Fri 9/14/18

Fri 9/14/18

5

2

Plan Development

4 days

Mon 9/17/18

Thu 9/20/18

2.1

Listing the activities required

1 day

Mon 9/17/18

Mon 9/17/18

6

2.2

Making project schedule

2 days

Tue 9/18/18

Wed 9/19/18

8

2.3

Reviewing project plan

1 day

Thu 9/20/18

Thu 9/20/18

9

2.4

Approval of project plan

0 days

Thu 9/20/18

Thu 9/20/18

10

3

Activities Execution

21 days

Fri 9/21/18

Fri 10/19/18

3.1

Research Objectives are identified

1 day

Fri 9/21/18

Fri 9/21/18

11

3.2

Questions supporting research are identified

2 days

Mon 9/24/18

Tue 9/25/18

13

3.3

Collecting required data

5 days

Wed 9/26/18

Tue 10/2/18

14

3.4

Data Filtering for authenticity

2 days

Wed 10/3/18

Thu 10/4/18

15

3.5

Analysis of data

3 days

Fri 10/5/18

Tue 10/9/18

16

3.6

Making summary of the data analyzed

2 days

Wed 10/10/18

Thu 10/11/18

17

3.7

Journals and articles are reviewed

4 days

Fri 10/12/18

Wed 10/17/18

18

3.8

Documenting them

2 days

Thu 10/18/18

Fri 10/19/18

19

4

Closing

4 days

Mon 10/22/18

Thu 10/25/18

4.1

Making final report

1 day

Mon 10/22/18

Mon 10/22/18

20

4.2

Developing conclusion

1 day

Tue 10/23/18

Tue 10/23/18

22

4.3

Documenting and reviewing

1 day

Wed 10/24/18

Wed 10/24/18

23

4.4

Sign off

1 day

Thu 10/25/18

Thu 10/25/18

24


The project schedule has been developed for the implication of the operations and alignment for easing the implication of the effective and smart functional development. The Ms-Project is developed for easing the implication of the factors aligning the development of the improved communication. The research project development and execution of the operations had been successful with the inclusion of identification of the research objectives and research questions. The Gantt chart is the diagrammatical representation of the factors aligning with the utilization of the timeline for the alignment of the effective project completion. The following is the Gantt chart of the research project.

Variables

According to Nitecka-Buchta et al. (2018), the productivity (MFP and LP) of the project operations for construction and manufacturing is dependent on several factors including design issues, changes, delays, exhaustion of resources, and limiting carbon emission. The MFP stands for multi factor productivity and LP stands for labour productivity. These two plays a significant role for the innovation and technology development using the improved performance development (Peinado et al. 2018). The successful implication of the data would be helpful for easing the alignment of the production analysis and development. The utilization would be implied for aligning with the simplification of the factors for developing the effective project execution. The analysis of the factors would help in understanding the consequences of the problems like design issues, changes, delays, and exhaustion of resources on the MFP and LP. However Nitecka-Buchta et al. (2018) have provided an analysis of the possible project schedule development for forming the impact on the existing project productivity. The support and development would be aligned for executing the project in four phases. Each of the project phases would be aligned with the next phase for the completion of the project execution. The project schedule plays a significant role in forming the utilization of the probable development form. The improved communication would align with the alignment methods of operations. The factors for analysis would play a significant role in listing the formation of the improved communication and development. The role of the several issues on the productivity would be aligned for supporting the implication of the possible project development. The activities execution is the most crucial factor for developing the final project completion. The research project development and execution of the operations had been successful with the inclusion of identification of the research objectives and research questions.

Conclusion

It can be concluded from the assignment that the utilization of the analysis of decreasing productivity (MFP and LP) due to the increasing possible risks and issues in construction and manufacturing industries was helpful for ensuring the future development schemes. The prospect of supporting the analysis of the factors was limited to the support and development. The successful implication of the production factors had been supporting the involvement of the improved operations. The process of project was developed using the traditional waterfall model. The project phases of research initiation, plan development, activities execution, and closing were considered for the completion of the project. Moreover, the analysis of the effective and smart project completion was resulted due to the development of the proper project report structure. The deployment had aligned for successfully considering the support and development. The alignment of the probable solutions had considered the alignment of the smart and effective execution. The completion of the research report was aimed for supporting in the future study and further analysis.

Albrizio. S. & Nicoletti, G., (2018). Boosting Productivity: A Framework For Analysis And A Checklist For Policy. Oecd.org. Retrieved 23 August 2018, from https://www.oecd.org/global-forum-productivity/events/Boosting%20Productivity.pdf

Andrews, D., Criscuolo, C., & Gal, P. (2016). The global productivity slowdown, technology divergence and public policy: A firm level perspective. Brookings Institution Hutchins Center Working Paper, (24).

Andrews, D., Criscuolo, C., & Gal, P. (2016). The global productivity slowdown, technology divergence: A firm level perspective. Brookings Institution Hutchins Center Working Paper, (24).

Barba, L., Cupeiro, R., Díaz, Á. E., Santiago, E., Alfaro, V., Rael, B., ... & Peinado, A. B. (2018). Menstrual Cycle Influence on Hepcidin Secretion and Inflammatory Reponses in Female Athletes. Ironfemme Pilot Study: Funding. Medicine & Science in Sports & Exercise, 50(5S), 99.

Bls.gov. (2018).  Multifactor Productivity Home Page (MFP).Retrieved 23 August 2018, from https://www.bls.gov/mfp/

Brown, J. D., Dinlersoz, E., & Earle, J. S. (2016). Does Higher Productivity Dispersion Imply Greater Misallocation? A Theoretical and Empirical Analysis.

Csls.ca (2018). Labour or Total Factor Productivity: Do We Need to Choose?. Retrieved 23 August 2018, from https://www.csls.ca/ipm/1/sargent-un-en.pdf

Gordon, J., Zhao, S., & Gretton, P. (2015). On productivity: concepts and measurement. Productivity Commission Staff Research Note, Canberra, February.

Lory, P. F., Pailhès, S., Giordano, V. M., Euchner, H., Nguyen, H. D., Ramlau, R., ... & Tomeš, P. (2017). Direct measurement of individual phonon lifetimes in the clathrate compound Ba 7.81 Ge 40.67 Au 5.33. Nature communications, 8(1), 491.

Malabayabas, A. (2018). Labor Productivity vs. Total Factor Productivity. Cem.uplb.edu.ph. Retrieved 23 August 2018, from https://cem.uplb.edu.ph/research-extension-training/economicissues/34-vol-1-no-1/67-labor-productivity-vs-total-factor-productivity

Moore, R., Jones, S. R., Dev, S. I., Soontornniomkij, B., Joseph, J., Achim, C. L., ... & Eyler, L. T. (2015). Association Between Peripheral Immune Markers and Functional Neuroimaging Findings Among Healthy Older Adults. The American Journal of Geriatric Psychiatry, 23(3), S134-S135.

Nitecka-Buchta, A., Walczynska-Dragon, K., Batko-Kapustecka, J., & Wieckiewicz, M. (2018). Comparison between Collagen and Lidocaine Intramuscular Injections in Terms of Their Efficiency in Decreasing Myofascial Pain within Masseter Muscles: A Randomized, Single-Blind Controlled Trial. Pain Research and Management, 2018.

Peinado, A. B., Barba, L., Díaz, Á. E., Butragueño, J., Romero-parra, N., Calderón, F. J., ... & Cupeiro, R. (2018). Menstrual Cycle Influence on Iron-status Markers in Female Athletes. Ironfemme Pilot Study: 428 Board# 269 May 30 11. Medicine & Science in Sports & Exercise, 50(5S), 98.

Abs.gov.au. (2017).  5260.0.55.002 - Estimates of Industry Multifactor Productivity, 2016-17. Retrieved 23 August 2018, from https://www.abs.gov.au/ausstats/[email protected]/0/E95A0098761C9EC9CA25807D00172D73?

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