How to cite this paper
Prasad, S. (2016). Modelling the factors influencing the selection of the construction equipment for Indian construction organizations.Management Science Letters , 6(9), 575-584.
Refrences
Alzebdeh, K., Bashir, K.A., & Al Siyabi, S.K. (2015). Applying interpretive structural modelling to cost overruns in construction projects in the Sultanate of Oman. The Journal of Engineering Research, 12, 53-68.
Ameh, O. J., Soyingbe, A. A., & Odusami, K. T. (2010). Significant factors causing cost overruns in telecommunication projects in Nigeria. Journal of Construction in Developing Countries, 15(2), 49-67.
Arditi, D., Kale, S., & Tangkar, M. (1997). Innovation in construction equipment and its flow into the construction industry. Journal of Construction Engineering and Management, 123(4), 371-378.
Azevedo, S., Carvalho, H., & Cruz-Machado, V. (2013). Using interpretive structural modelling to identify and rank performance measures: an application in the automotive supply chain. Baltic Journal of Management,8(2), 208-230.
Arvind, J., & Azhar, M. (2014). Analysis of the Barriers for Implementing Green Supply Chain Management Practices: An Interpretive Structural Modelling Approach, 12th Global Congress on Manufacturing and Management. Procedia Engineering, 97, 2157-2166.
Attri, R., Dev, N., & Sharma, V. (2013). Interpretive structural modelling (ISM) approach: an overview. Research Journal of Management Sciences,2(2), 3-8.
Avetisyan, H. G., Miller-Hooks, E., & Melanta, S. (2011). Decision models to support greenhouse gas emissions reduction from transportation construction projects. Journal of Construction Engineering and Management,138(5), 631-641.
Azhar, N., Farooqui, R. U., & Ahmed, S. M. (2008, August). Cost overrun factors in construction industry of Pakistan. In First International Conference on Construction In Developing Countries (ICCIDC–I), Advancing and Integrating Construction Education, Research & Practice (pp. 499-508).
Cagdac Arslan, M., Catay, B., & Budak, E. (2004). A decision support system for machine tool selection. Journal of Manufacturing Technology Management, 15(1), 101-109.
Chan, F. T. S., Ip, R. W. L., & Lau, H. (2001). Integration of expert system with analytic hierarchy process for the design of material handling equipment selection system. Journal of Materials Processing Technology, 116(2), 137-145.
Chinchore, M. N. D. (2014). Planning and selection of heavy construction equipment in civil engineering. International Journal of engineering Research and Applications, 1(4), 29-31.
Creedy, G. (2005). Risk factors leading to cost overrun in highway projects: Paper presented at the Proceeding of Queenland University of Technology Research Week International Conference, Brisbane, Australia.
Eldin, N. N., & Mayfield, J. (2005). Determination of most economical scrapers fleet. Journal of construction engineering and management,131(10), 1109-1114.
Goldenberg, M., & Shapira, A. (2007). Systematic evaluation of construction equipment alternatives: case study. Journal of construction engineering and management, 133(1), 72-85.
Gransberg, D.D., Popescu, C.M., & Ryan, R.C. (2006). Construction Equipment Management for Engineers, Estimators and Owners, Taylor & Francis, London.
Guggemos, A. A., & Horvath, A. (2006). Decision-support tool for assessing the environmental effects of constructing commercial buildings. Journal of Architectural Engineering, 12(4), 187-195.
Haidar, A., Naoum, S., Howes, R., & Tah, J. (1999). Genetic algorithms application and testing for equipment selection. Journal of Construction Engineering and Management, 125(1), 32-38.
Hajji, A. M. (2013). Estimating the emissions of nitrogen oxides (NOX) and particulate matter (PM) from diesel construction equipment by using the productivity model. World Journal of Science, Technology and Sustainable Development, 10(3), 212-228.
Idoro, G. I. (2011). Effect of mechanisation on occupational health and safety performance in the Nigerian construction industry. Journal of Construction in Developing countries, 16(2), 27-45.
Iyer, K. C., & Sagheer, M. (2009). Hierarchical structuring of PPP risks using interpretative structural modeling. Journal of Construction Engineering and Management, 136(2), 151-159.
Koo, D. H., & Ariaratnam, S. T. (2008). Application of a sustainability model for assessing water main replacement options. Journal of Construction Engineering and Management, 134(8), 563-574.
Kumar, N. (2013). Implementing lean manufacturing system: ISM approach.Journal of Industrial Engineering and Management, 6(4), 996.
Kumar, S., & Kant, R. (2013). Supplier selection process enablers: an interpretive structural modeling approach. International Journal of Mechanical and Industrial Engineering, 3(1), 89-95.
Kumar, R., & Kumar, V. (2016). Analysis of significant lean manufacturing elements through application of interpretive structural modeling approach in Indian industry. Uncertain Supply Chain Management, 4(1), 83-92.
Mackenzie, S., Kilpatrick, A. R., & Akintoye, A. (2000). UK construction skills shortage response strategies and an analysis of industry perceptions.Construction Management & Economics, 18(7), 853-862.
Mudgal, R. K., Shankar, R., Talib, P., & Raj, T. (2009). Greening the supply chain practices: an Indian perspective of enablers' relationships. International Journal of Advanced Operations Management, 1(2-3), 151-176.
Oglesby, H., & Parker, A. (2012). Howell, Productivity improvement in construction. McGraw Hill.
Phogat, M. V. S., & Singh, A. P. (2013). Selection of equipment for construction of a hilly road using multi criteria approach. Procedia-Social and Behavioral Sciences, 104, 282-291.
Prasertrungruang, T., & Hadikusumo, B. H. W. (2007). Heavy equipment management practices and problems in Thai highway contractors.Engineering, Construction and Architectural Management, 14(3), 228-241.
Robert, I., Peurifoy, P.E., Clifford, J., Schexnayder, P.E., & Shapira, A. (2006). Construction Planning, Equipment and Methods. International Edition, 7th ed., McGraw-Hill, New York.
Samee, K., & Pongpeng, J. (2016). Structural equation model for construction equipment selection and contractor competitive advantages.KSCE Journal of Civil Engineering, 20(1), 77-89.
Sandbhor, S., & Botre, R. (2014). Applying total interpretive structural modeling to study factors affecting construction labour productivity.Australasian Journal of Construction Economics and Building, The, 14(1), 20.
Schexnayder, P.E., & Hancher, F. (2009). The True Cost of Equipment Failure. 3rd ed., Netta Hook, Germany
Siddharth, J., & Pitroda, J. (2014) A critical literature review on review on factors affecting in selection of construction equipment. International Journal of Advanced Technology in Engineering and Science, 2(12), 559-567.
Tseng, M. L., & Lin, Y. H. (2011). Modeling a hierarchical structure of municipal solid waste management using interpretive structural modeling. WSEAS Transactions on Environment and Development, 7(11), 337-348.
Talib, F., Rahman, Z., & Qureshi, M. N. (2011). An interpretive structural modelling approach for modelling the practices of total quality management in service sector. International Journal of Modelling in Operations Management, 1(3), 223-250.
Tatari, O., & Skibniewski, M. (2006). Integrated agent‐based construction equipment management: Conceptual design. Journal of Civil Engineering and Management, 12(3), 231-236.
Tavakoli, A., Masehi, J. J., & Collyard, C. S. (1990). FLEET: Equipment management system. Journal of Management in Engineering, 6(2), 211-220.
Valli, P., & Jeyasehar, C. A. (2012). Genetic algorithm based equipment selection method for construction project using MATLAB tool. Iran University of Science & Technology, 2(2), 235-246.
Waris,A., Khamidi,M.F., & Idrus, A. (2013) Heavy equipment acquisition in Malaysian construction industry, Proceedings of the International Symposium on Business, Engineering and Industrial Applications, Kuching, Malaysia.
Waris, M., Liew, M. S., Khamidi, M. F., & Idrus, A. (2014). Criteria for the selection of sustainable onsite construction equipment. International Journal of Sustainable Built Environment, 3(1), 96-110.
Yeo, K. T., & Ning, J. H. (2006). Managing uncertainty in major equipment procurement in engineering projects. European journal of operational research, 171(1), 123-134.
Ameh, O. J., Soyingbe, A. A., & Odusami, K. T. (2010). Significant factors causing cost overruns in telecommunication projects in Nigeria. Journal of Construction in Developing Countries, 15(2), 49-67.
Arditi, D., Kale, S., & Tangkar, M. (1997). Innovation in construction equipment and its flow into the construction industry. Journal of Construction Engineering and Management, 123(4), 371-378.
Azevedo, S., Carvalho, H., & Cruz-Machado, V. (2013). Using interpretive structural modelling to identify and rank performance measures: an application in the automotive supply chain. Baltic Journal of Management,8(2), 208-230.
Arvind, J., & Azhar, M. (2014). Analysis of the Barriers for Implementing Green Supply Chain Management Practices: An Interpretive Structural Modelling Approach, 12th Global Congress on Manufacturing and Management. Procedia Engineering, 97, 2157-2166.
Attri, R., Dev, N., & Sharma, V. (2013). Interpretive structural modelling (ISM) approach: an overview. Research Journal of Management Sciences,2(2), 3-8.
Avetisyan, H. G., Miller-Hooks, E., & Melanta, S. (2011). Decision models to support greenhouse gas emissions reduction from transportation construction projects. Journal of Construction Engineering and Management,138(5), 631-641.
Azhar, N., Farooqui, R. U., & Ahmed, S. M. (2008, August). Cost overrun factors in construction industry of Pakistan. In First International Conference on Construction In Developing Countries (ICCIDC–I), Advancing and Integrating Construction Education, Research & Practice (pp. 499-508).
Cagdac Arslan, M., Catay, B., & Budak, E. (2004). A decision support system for machine tool selection. Journal of Manufacturing Technology Management, 15(1), 101-109.
Chan, F. T. S., Ip, R. W. L., & Lau, H. (2001). Integration of expert system with analytic hierarchy process for the design of material handling equipment selection system. Journal of Materials Processing Technology, 116(2), 137-145.
Chinchore, M. N. D. (2014). Planning and selection of heavy construction equipment in civil engineering. International Journal of engineering Research and Applications, 1(4), 29-31.
Creedy, G. (2005). Risk factors leading to cost overrun in highway projects: Paper presented at the Proceeding of Queenland University of Technology Research Week International Conference, Brisbane, Australia.
Eldin, N. N., & Mayfield, J. (2005). Determination of most economical scrapers fleet. Journal of construction engineering and management,131(10), 1109-1114.
Goldenberg, M., & Shapira, A. (2007). Systematic evaluation of construction equipment alternatives: case study. Journal of construction engineering and management, 133(1), 72-85.
Gransberg, D.D., Popescu, C.M., & Ryan, R.C. (2006). Construction Equipment Management for Engineers, Estimators and Owners, Taylor & Francis, London.
Guggemos, A. A., & Horvath, A. (2006). Decision-support tool for assessing the environmental effects of constructing commercial buildings. Journal of Architectural Engineering, 12(4), 187-195.
Haidar, A., Naoum, S., Howes, R., & Tah, J. (1999). Genetic algorithms application and testing for equipment selection. Journal of Construction Engineering and Management, 125(1), 32-38.
Hajji, A. M. (2013). Estimating the emissions of nitrogen oxides (NOX) and particulate matter (PM) from diesel construction equipment by using the productivity model. World Journal of Science, Technology and Sustainable Development, 10(3), 212-228.
Idoro, G. I. (2011). Effect of mechanisation on occupational health and safety performance in the Nigerian construction industry. Journal of Construction in Developing countries, 16(2), 27-45.
Iyer, K. C., & Sagheer, M. (2009). Hierarchical structuring of PPP risks using interpretative structural modeling. Journal of Construction Engineering and Management, 136(2), 151-159.
Koo, D. H., & Ariaratnam, S. T. (2008). Application of a sustainability model for assessing water main replacement options. Journal of Construction Engineering and Management, 134(8), 563-574.
Kumar, N. (2013). Implementing lean manufacturing system: ISM approach.Journal of Industrial Engineering and Management, 6(4), 996.
Kumar, S., & Kant, R. (2013). Supplier selection process enablers: an interpretive structural modeling approach. International Journal of Mechanical and Industrial Engineering, 3(1), 89-95.
Kumar, R., & Kumar, V. (2016). Analysis of significant lean manufacturing elements through application of interpretive structural modeling approach in Indian industry. Uncertain Supply Chain Management, 4(1), 83-92.
Mackenzie, S., Kilpatrick, A. R., & Akintoye, A. (2000). UK construction skills shortage response strategies and an analysis of industry perceptions.Construction Management & Economics, 18(7), 853-862.
Mudgal, R. K., Shankar, R., Talib, P., & Raj, T. (2009). Greening the supply chain practices: an Indian perspective of enablers' relationships. International Journal of Advanced Operations Management, 1(2-3), 151-176.
Oglesby, H., & Parker, A. (2012). Howell, Productivity improvement in construction. McGraw Hill.
Phogat, M. V. S., & Singh, A. P. (2013). Selection of equipment for construction of a hilly road using multi criteria approach. Procedia-Social and Behavioral Sciences, 104, 282-291.
Prasertrungruang, T., & Hadikusumo, B. H. W. (2007). Heavy equipment management practices and problems in Thai highway contractors.Engineering, Construction and Architectural Management, 14(3), 228-241.
Robert, I., Peurifoy, P.E., Clifford, J., Schexnayder, P.E., & Shapira, A. (2006). Construction Planning, Equipment and Methods. International Edition, 7th ed., McGraw-Hill, New York.
Samee, K., & Pongpeng, J. (2016). Structural equation model for construction equipment selection and contractor competitive advantages.KSCE Journal of Civil Engineering, 20(1), 77-89.
Sandbhor, S., & Botre, R. (2014). Applying total interpretive structural modeling to study factors affecting construction labour productivity.Australasian Journal of Construction Economics and Building, The, 14(1), 20.
Schexnayder, P.E., & Hancher, F. (2009). The True Cost of Equipment Failure. 3rd ed., Netta Hook, Germany
Siddharth, J., & Pitroda, J. (2014) A critical literature review on review on factors affecting in selection of construction equipment. International Journal of Advanced Technology in Engineering and Science, 2(12), 559-567.
Tseng, M. L., & Lin, Y. H. (2011). Modeling a hierarchical structure of municipal solid waste management using interpretive structural modeling. WSEAS Transactions on Environment and Development, 7(11), 337-348.
Talib, F., Rahman, Z., & Qureshi, M. N. (2011). An interpretive structural modelling approach for modelling the practices of total quality management in service sector. International Journal of Modelling in Operations Management, 1(3), 223-250.
Tatari, O., & Skibniewski, M. (2006). Integrated agent‐based construction equipment management: Conceptual design. Journal of Civil Engineering and Management, 12(3), 231-236.
Tavakoli, A., Masehi, J. J., & Collyard, C. S. (1990). FLEET: Equipment management system. Journal of Management in Engineering, 6(2), 211-220.
Valli, P., & Jeyasehar, C. A. (2012). Genetic algorithm based equipment selection method for construction project using MATLAB tool. Iran University of Science & Technology, 2(2), 235-246.
Waris,A., Khamidi,M.F., & Idrus, A. (2013) Heavy equipment acquisition in Malaysian construction industry, Proceedings of the International Symposium on Business, Engineering and Industrial Applications, Kuching, Malaysia.
Waris, M., Liew, M. S., Khamidi, M. F., & Idrus, A. (2014). Criteria for the selection of sustainable onsite construction equipment. International Journal of Sustainable Built Environment, 3(1), 96-110.
Yeo, K. T., & Ning, J. H. (2006). Managing uncertainty in major equipment procurement in engineering projects. European journal of operational research, 171(1), 123-134.