MEASURING TECHNOLOGICAL IMPACT ON CONSTRUCTION

MANAGEMENT USING PREDICTIVE MODEL

Muhammad Hanafi

(1380236)

Contents

bull Introduction

bull Description

bull Predictive Model Systematics

bull Results

bull Discussion

bull Conclusion

bull References

bull Questions amp Answers Session

Introduction

bullTechnology invented to facilitate humans

bullThe emerging technology brought some significant

improvement eg prefabricated building quick-

curing concrete information

bullFailures to implement the technology in

construction still frequently occur

Contents

bull Introduction

bull Description

bull Predictive Model Systematics

bull Results

bull Discussion

bull Conclusion

bull References

bull Questions amp Answers Session

Introduction

bullTechnology invented to facilitate humans

bullThe emerging technology brought some significant

improvement eg prefabricated building quick-

curing concrete information

bullFailures to implement the technology in

construction still frequently occur

Introduction

bullTechnology invented to facilitate humans

bullThe emerging technology brought some significant

improvement eg prefabricated building quick-

curing concrete information

bullFailures to implement the technology in

construction still frequently occur

Introduction

bullThe lack of demonstrated benefits related withtechnology hindered optimization from advancedtechnology (Bohn and Teizer 2010)

bull Important to inspect how promising the technology(Cheng 2011)

bullGoodrum etal (2011) develop a predictive model toevaluate the potential impact of technology onconstruction productivity

Description

bull Construction management is about fulfilling clientrsquos requirements

to produce a functionally and financially viable project

bull To meet the requirements advancement in technology needed

Productivity improvement

bull Goodrum etal (2011) formulated various studies into a predictive

model to measure the impact of technology

Description

Predictive Model

Statistical Analysis

Productivity Changes

Historical Changes

Predictive Model

bull Table A AHP Weight Result for Each Stage and Category (Goodrum etal 2011)

Stage and Category Weight () Score

I ndash Strategic economic analysis 101 121

A Budget Analysis 41 49

B Potential benefits associated with adoption 49 58

C Technology documentation 11 14

II ndash Technology feasibility 229 276

D Technology maturity 151 182

E Technology risks 36 43

F Technology performance 42 51

III ndash Technology usage issues 319 383

G Technology acceptance 137 164

H Technology synergy and protocol 137 164

I Technology logistic functions 45 55

IV ndash Technology impacts 351 420

J Equipment technology 163 195

K Material Technology 76 91

L Automation and integration potential 112 134

Total 100 1200

Predictive Modelbull Table B Predictive Model Stage IV ndash Technical Impact of Construction Equipment and Material Technology (Goodrum P etal 2011)

L CONSTRUCTION EQUIPMENT TECHNOLOGY

Level of Control (0 to 22 points)

Does the equipment technology involve a manual hand tool

Does the equipment technology involve a manually controlled device

Does the equipment technology involve a remote controlled device

Does the equipment technology involve a computer assisted device

Does the equipment technology involve a fully intelligent (autonomous) device

Amplification of Human Energy (0 to 26 points)

Does the operator supply all of the driving energy for the equipment to operate

Does the equipment technology supply a certain amount of driving energy

Does the equipment supply all of the driving energy and the worker only has to operate the controls

Information Processing (0 to 25 points)

Does the equipment provide no level of information feedback

Does the equipment provide information feedback concerning internal operations

Does the equipment provide information concerning environmental parameters

Does the equipment include on-board computing systems that process internal and external data so supervisory level

control is available

Functional Range (0 to 27 points)

Does the equipment provide no enhancement or extend the capabilities to the operatorrsquos work envelope

Does the equipment extend the physical range of the operatorrsquos work envelope

Does the equipment enhance the operatorrsquos precision within the work envelope

Results

bull Purpose of this model is to evaluate and distribute technologies

into three categories ldquosuccessfulrdquo ldquoinconclusiverdquo ldquounsuccessfulrdquo

bull The results from ANOVA test indicate that among the three

categories the deviations of average percentage scores are

statistically significant

Successful Inconclusive Unsuccessful

gt 60 45 - 60 lt 45

Discussion

bull Advantages

Produced Reliable Results

Categorization

Question Lists

Discussion

bull Barriers

The complexity in weighing every single question from each

category

Need to be simplify to attract users

Discussion

bull Review

History of Past Performance

Nonexistence Historical

Data

Changes in Condition and

Culture Robust Measurement

Awareness of Key

Factors

References

Analytical Capability

Conclusions

bull The predictive model is an applicable tool to measure the impact

of appropriate technology

bull this model provide a lot of references and facilitate the decision

maker to indicate the awareness about key factors

bull This model gives an overview to the user but to determine the

appropriate technology for the project remains the userrsquos duty

based on the own understanding knowledge and experience

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

Description

bull Construction management is about fulfilling clientrsquos requirements

to produce a functionally and financially viable project

bull To meet the requirements advancement in technology needed

Productivity improvement

bull Goodrum etal (2011) formulated various studies into a predictive

model to measure the impact of technology

Description

Predictive Model

Statistical Analysis

Productivity Changes

Historical Changes

Predictive Model

bull Table A AHP Weight Result for Each Stage and Category (Goodrum etal 2011)

Stage and Category Weight () Score

I ndash Strategic economic analysis 101 121

A Budget Analysis 41 49

B Potential benefits associated with adoption 49 58

C Technology documentation 11 14

II ndash Technology feasibility 229 276

D Technology maturity 151 182

E Technology risks 36 43

F Technology performance 42 51

III ndash Technology usage issues 319 383

G Technology acceptance 137 164

H Technology synergy and protocol 137 164

I Technology logistic functions 45 55

IV ndash Technology impacts 351 420

J Equipment technology 163 195

K Material Technology 76 91

L Automation and integration potential 112 134

Total 100 1200

Predictive Modelbull Table B Predictive Model Stage IV ndash Technical Impact of Construction Equipment and Material Technology (Goodrum P etal 2011)

L CONSTRUCTION EQUIPMENT TECHNOLOGY

Level of Control (0 to 22 points)

Does the equipment technology involve a manual hand tool

Does the equipment technology involve a manually controlled device

Does the equipment technology involve a remote controlled device

Does the equipment technology involve a computer assisted device

Does the equipment technology involve a fully intelligent (autonomous) device

Amplification of Human Energy (0 to 26 points)

Does the operator supply all of the driving energy for the equipment to operate

Does the equipment technology supply a certain amount of driving energy

Does the equipment supply all of the driving energy and the worker only has to operate the controls

Information Processing (0 to 25 points)

Does the equipment provide no level of information feedback

Does the equipment provide information feedback concerning internal operations

Does the equipment provide information concerning environmental parameters

Does the equipment include on-board computing systems that process internal and external data so supervisory level

control is available

Functional Range (0 to 27 points)

Does the equipment provide no enhancement or extend the capabilities to the operatorrsquos work envelope

Does the equipment extend the physical range of the operatorrsquos work envelope

Does the equipment enhance the operatorrsquos precision within the work envelope

Results

bull Purpose of this model is to evaluate and distribute technologies

into three categories ldquosuccessfulrdquo ldquoinconclusiverdquo ldquounsuccessfulrdquo

bull The results from ANOVA test indicate that among the three

categories the deviations of average percentage scores are

statistically significant

Successful Inconclusive Unsuccessful

gt 60 45 - 60 lt 45

Discussion

bull Advantages

Produced Reliable Results

Categorization

Question Lists

Discussion

bull Barriers

The complexity in weighing every single question from each

category

Need to be simplify to attract users

Discussion

bull Review

History of Past Performance

Nonexistence Historical

Data

Changes in Condition and

Culture Robust Measurement

Awareness of Key

Factors

References

Analytical Capability

Conclusions

bull The predictive model is an applicable tool to measure the impact

of appropriate technology

bull this model provide a lot of references and facilitate the decision

maker to indicate the awareness about key factors

bull This model gives an overview to the user but to determine the

appropriate technology for the project remains the userrsquos duty

based on the own understanding knowledge and experience

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

Description

Predictive Model

Statistical Analysis

Productivity Changes

Historical Changes

Predictive Model

bull Table A AHP Weight Result for Each Stage and Category (Goodrum etal 2011)

Stage and Category Weight () Score

I ndash Strategic economic analysis 101 121

A Budget Analysis 41 49

B Potential benefits associated with adoption 49 58

C Technology documentation 11 14

II ndash Technology feasibility 229 276

D Technology maturity 151 182

E Technology risks 36 43

F Technology performance 42 51

III ndash Technology usage issues 319 383

G Technology acceptance 137 164

H Technology synergy and protocol 137 164

I Technology logistic functions 45 55

IV ndash Technology impacts 351 420

J Equipment technology 163 195

K Material Technology 76 91

L Automation and integration potential 112 134

Total 100 1200

Predictive Modelbull Table B Predictive Model Stage IV ndash Technical Impact of Construction Equipment and Material Technology (Goodrum P etal 2011)

L CONSTRUCTION EQUIPMENT TECHNOLOGY

Level of Control (0 to 22 points)

Does the equipment technology involve a manual hand tool

Does the equipment technology involve a manually controlled device

Does the equipment technology involve a remote controlled device

Does the equipment technology involve a computer assisted device

Does the equipment technology involve a fully intelligent (autonomous) device

Amplification of Human Energy (0 to 26 points)

Does the operator supply all of the driving energy for the equipment to operate

Does the equipment technology supply a certain amount of driving energy

Does the equipment supply all of the driving energy and the worker only has to operate the controls

Information Processing (0 to 25 points)

Does the equipment provide no level of information feedback

Does the equipment provide information feedback concerning internal operations

Does the equipment provide information concerning environmental parameters

Does the equipment include on-board computing systems that process internal and external data so supervisory level

control is available

Functional Range (0 to 27 points)

Does the equipment provide no enhancement or extend the capabilities to the operatorrsquos work envelope

Does the equipment extend the physical range of the operatorrsquos work envelope

Does the equipment enhance the operatorrsquos precision within the work envelope

Results

bull Purpose of this model is to evaluate and distribute technologies

into three categories ldquosuccessfulrdquo ldquoinconclusiverdquo ldquounsuccessfulrdquo

bull The results from ANOVA test indicate that among the three

categories the deviations of average percentage scores are

statistically significant

Successful Inconclusive Unsuccessful

gt 60 45 - 60 lt 45

Discussion

bull Advantages

Produced Reliable Results

Categorization

Question Lists

Discussion

bull Barriers

The complexity in weighing every single question from each

category

Need to be simplify to attract users

Discussion

bull Review

History of Past Performance

Nonexistence Historical

Data

Changes in Condition and

Culture Robust Measurement

Awareness of Key

Factors

References

Analytical Capability

Conclusions

bull The predictive model is an applicable tool to measure the impact

of appropriate technology

bull this model provide a lot of references and facilitate the decision

maker to indicate the awareness about key factors

bull This model gives an overview to the user but to determine the

appropriate technology for the project remains the userrsquos duty

based on the own understanding knowledge and experience

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

Predictive Model

bull Table A AHP Weight Result for Each Stage and Category (Goodrum etal 2011)

Stage and Category Weight () Score

I ndash Strategic economic analysis 101 121

A Budget Analysis 41 49

B Potential benefits associated with adoption 49 58

C Technology documentation 11 14

II ndash Technology feasibility 229 276

D Technology maturity 151 182

E Technology risks 36 43

F Technology performance 42 51

III ndash Technology usage issues 319 383

G Technology acceptance 137 164

H Technology synergy and protocol 137 164

I Technology logistic functions 45 55

IV ndash Technology impacts 351 420

J Equipment technology 163 195

K Material Technology 76 91

L Automation and integration potential 112 134

Total 100 1200

Predictive Modelbull Table B Predictive Model Stage IV ndash Technical Impact of Construction Equipment and Material Technology (Goodrum P etal 2011)

L CONSTRUCTION EQUIPMENT TECHNOLOGY

Level of Control (0 to 22 points)

Does the equipment technology involve a manual hand tool

Does the equipment technology involve a manually controlled device

Does the equipment technology involve a remote controlled device

Does the equipment technology involve a computer assisted device

Does the equipment technology involve a fully intelligent (autonomous) device

Amplification of Human Energy (0 to 26 points)

Does the operator supply all of the driving energy for the equipment to operate

Does the equipment technology supply a certain amount of driving energy

Does the equipment supply all of the driving energy and the worker only has to operate the controls

Information Processing (0 to 25 points)

Does the equipment provide no level of information feedback

Does the equipment provide information feedback concerning internal operations

Does the equipment provide information concerning environmental parameters

Does the equipment include on-board computing systems that process internal and external data so supervisory level

control is available

Functional Range (0 to 27 points)

Does the equipment provide no enhancement or extend the capabilities to the operatorrsquos work envelope

Does the equipment extend the physical range of the operatorrsquos work envelope

Does the equipment enhance the operatorrsquos precision within the work envelope

Results

bull Purpose of this model is to evaluate and distribute technologies

into three categories ldquosuccessfulrdquo ldquoinconclusiverdquo ldquounsuccessfulrdquo

bull The results from ANOVA test indicate that among the three

categories the deviations of average percentage scores are

statistically significant

Successful Inconclusive Unsuccessful

gt 60 45 - 60 lt 45

Discussion

bull Advantages

Produced Reliable Results

Categorization

Question Lists

Discussion

bull Barriers

The complexity in weighing every single question from each

category

Need to be simplify to attract users

Discussion

bull Review

History of Past Performance

Nonexistence Historical

Data

Changes in Condition and

Culture Robust Measurement

Awareness of Key

Factors

References

Analytical Capability

Conclusions

bull The predictive model is an applicable tool to measure the impact

of appropriate technology

bull this model provide a lot of references and facilitate the decision

maker to indicate the awareness about key factors

bull This model gives an overview to the user but to determine the

appropriate technology for the project remains the userrsquos duty

based on the own understanding knowledge and experience

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

Predictive Modelbull Table B Predictive Model Stage IV ndash Technical Impact of Construction Equipment and Material Technology (Goodrum P etal 2011)

L CONSTRUCTION EQUIPMENT TECHNOLOGY

Level of Control (0 to 22 points)

Does the equipment technology involve a manual hand tool

Does the equipment technology involve a manually controlled device

Does the equipment technology involve a remote controlled device

Does the equipment technology involve a computer assisted device

Does the equipment technology involve a fully intelligent (autonomous) device

Amplification of Human Energy (0 to 26 points)

Does the operator supply all of the driving energy for the equipment to operate

Does the equipment technology supply a certain amount of driving energy

Does the equipment supply all of the driving energy and the worker only has to operate the controls

Information Processing (0 to 25 points)

Does the equipment provide no level of information feedback

Does the equipment provide information feedback concerning internal operations

Does the equipment provide information concerning environmental parameters

Does the equipment include on-board computing systems that process internal and external data so supervisory level

control is available

Functional Range (0 to 27 points)

Does the equipment provide no enhancement or extend the capabilities to the operatorrsquos work envelope

Does the equipment extend the physical range of the operatorrsquos work envelope

Does the equipment enhance the operatorrsquos precision within the work envelope

Results

bull Purpose of this model is to evaluate and distribute technologies

into three categories ldquosuccessfulrdquo ldquoinconclusiverdquo ldquounsuccessfulrdquo

bull The results from ANOVA test indicate that among the three

categories the deviations of average percentage scores are

statistically significant

Successful Inconclusive Unsuccessful

gt 60 45 - 60 lt 45

Discussion

bull Advantages

Produced Reliable Results

Categorization

Question Lists

Discussion

bull Barriers

The complexity in weighing every single question from each

category

Need to be simplify to attract users

Discussion

bull Review

History of Past Performance

Nonexistence Historical

Data

Changes in Condition and

Culture Robust Measurement

Awareness of Key

Factors

References

Analytical Capability

Conclusions

bull The predictive model is an applicable tool to measure the impact

of appropriate technology

bull this model provide a lot of references and facilitate the decision

maker to indicate the awareness about key factors

bull This model gives an overview to the user but to determine the

appropriate technology for the project remains the userrsquos duty

based on the own understanding knowledge and experience

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

Results

bull Purpose of this model is to evaluate and distribute technologies

into three categories ldquosuccessfulrdquo ldquoinconclusiverdquo ldquounsuccessfulrdquo

bull The results from ANOVA test indicate that among the three

categories the deviations of average percentage scores are

statistically significant

Successful Inconclusive Unsuccessful

gt 60 45 - 60 lt 45

Discussion

bull Advantages

Produced Reliable Results

Categorization

Question Lists

Discussion

bull Barriers

The complexity in weighing every single question from each

category

Need to be simplify to attract users

Discussion

bull Review

History of Past Performance

Nonexistence Historical

Data

Changes in Condition and

Culture Robust Measurement

Awareness of Key

Factors

References

Analytical Capability

Conclusions

bull The predictive model is an applicable tool to measure the impact

of appropriate technology

bull this model provide a lot of references and facilitate the decision

maker to indicate the awareness about key factors

bull This model gives an overview to the user but to determine the

appropriate technology for the project remains the userrsquos duty

based on the own understanding knowledge and experience

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

Discussion

bull Advantages

Produced Reliable Results

Categorization

Question Lists

Discussion

bull Barriers

The complexity in weighing every single question from each

category

Need to be simplify to attract users

Discussion

bull Review

History of Past Performance

Nonexistence Historical

Data

Changes in Condition and

Culture Robust Measurement

Awareness of Key

Factors

References

Analytical Capability

Conclusions

bull The predictive model is an applicable tool to measure the impact

of appropriate technology

bull this model provide a lot of references and facilitate the decision

maker to indicate the awareness about key factors

bull This model gives an overview to the user but to determine the

appropriate technology for the project remains the userrsquos duty

based on the own understanding knowledge and experience

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

Discussion

bull Barriers

The complexity in weighing every single question from each

category

Need to be simplify to attract users

Discussion

bull Review

History of Past Performance

Nonexistence Historical

Data

Changes in Condition and

Culture Robust Measurement

Awareness of Key

Factors

References

Analytical Capability

Conclusions

bull The predictive model is an applicable tool to measure the impact

of appropriate technology

bull this model provide a lot of references and facilitate the decision

maker to indicate the awareness about key factors

bull This model gives an overview to the user but to determine the

appropriate technology for the project remains the userrsquos duty

based on the own understanding knowledge and experience

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

Discussion

bull Review

History of Past Performance

Nonexistence Historical

Data

Changes in Condition and

Culture Robust Measurement

Awareness of Key

Factors

References

Analytical Capability

Conclusions

bull The predictive model is an applicable tool to measure the impact

of appropriate technology

bull this model provide a lot of references and facilitate the decision

maker to indicate the awareness about key factors

bull This model gives an overview to the user but to determine the

appropriate technology for the project remains the userrsquos duty

based on the own understanding knowledge and experience

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

Conclusions

bull The predictive model is an applicable tool to measure the impact

of appropriate technology

bull this model provide a lot of references and facilitate the decision

maker to indicate the awareness about key factors

bull This model gives an overview to the user but to determine the

appropriate technology for the project remains the userrsquos duty

based on the own understanding knowledge and experience

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

Referencesbull Bohn JS Teizer J (2010) Benefits and Barriers of Construction Project Monitoring Using Hi-Resolution

Automated Cameras ASCE Journal of Construction Engineering and Management 136(6) 632ndash640

bull Cheng T Venugopal M Teizer J amp Vela P A (2011) Performance evaluation of ultra wideband technology for

construction resource location tracking in harsh environments Automation in Construction 20(8) 1173-1184

bull Goodrum P etal (2011) Model to Predict the Impact of a Technology on Construction Productivity ASCE

Journal of Construction Engineering and Management [online] 137 (9) (2011) 678ndash688 Available from

bull httpascelibraryorgezproxydbhamacukdoipdf10106128ASCE29CO1943-78620000328 [accessed on

11th October 2013]

bull Irianto A (2009) ldquoStatistik Konsep Dasar dan Aplikasinyardquo Jakarta Penerbit Kencana

bull McGarvey P (2002) Code of Practice for Project Management for Construction and Development [online]

Blackwell ISBN Available from httpenbookfiorg

httpdlluxbookfiorggenesis656000cf0d820eb4f6cbbed6d46c7e9ea1da42_as5BChartered_Institute_of_Build

ing5D_Code_of_Practice(BookFiorg)pdf [accessed on 11th October 2013]

bull Technology Oxford Dictionaries Oxford University Press

httpwwwoxforddictionariescomdefinitionenglishtechnology [accessed on 22nd October 2013]

The End

Questions

Questions