How to cite this paper
Attri, R & Grover, S. (2015). Analyzing the scheduling system stage of production system life cycle.Management Science Letters , 5(5), 431-442.
Refrences
Ahuja, V., Yang, J. & Shankar, R. (2009). Benefits of collaborative ICT adoption for building project management. Construction Innovation, 9(3), 323-340.
Attri, R. & Grover, S. (2013). Production system life cycle: An Inside story. Accepted in International Journal of Industrial and Systems Engineering.
Attri, R. & Grover, S., (2012). A comparison of production system life cycle models. Frontiers of Mechanical Engineering, 7(3), 305-311.
Attri, R., Grover, S., Dev, N. & Kumar, D. (2013a). An ISM approach for modelling the enablers in the implementation of Total Productive Maintenance (TPM). International Journal of Systems Assurance Engineering and Management, 4(4), 313-326.
Attri, R., Grover, S., Dev, N. & Kumar, D. (2013b). Analysis of barriers of Total Productive Maintenance (TPM). International Journal of Systems Assurance Engineering and Management, 4(4), 365-377.
Attri, R., Dev, N. & Sharma, V. (2013c). Interpretive Structural Modelling (ISM) approach: An Overview. Research Journal of Management Sciences, 2(2), 3-8.
Bolanos, R., Fontela, E., Nenclares, A. & Pastor, P. (2005). Using interpretive structural modelling in strategic decision-making groups. Management Decision, 43(6), 877-895.
Cagno, E., Micheli, G. J. L., Jacinto, C. & Masi, D. (2014). An interpretive model of occupational safety performance for Small- and Medium-sized Enterprises. International Journal of Industrial Ergonomics, 44, 60-74.
Cowling, P. I., and Johansson, M. (2002). Using real-time information for effective dynamic scheduling. European Journal of Operational Research, 139(2), 230-244.
Duperrin, J. C. & Godet, M. (1973). Methode De Hierar Chization Des Elements D’um System. Rapport Economique De CEA, R-45-51, Paris.
Faisal, M. N. (2010). Analysing the barriers to corporate social responsibility in supply chains: an interpretive structural modelling approach. International Journal of Logistics: Research and Applications, 13(3), 179-195
Govindan, K., Palaniappan, M., Zhu, Q. & Kannan, D. (2014). Analysis of third party reverse logistics provider using interpretive structural modelling. International Journal of Production Economics, 140, 204-211.
Haleem, A., Sushil, Qadri, M. A. & Kumar, S. (2012). Analysis of critical success factors of world-class manufacturing practices: an application of interpretative structural modelling and interpretative ranking process. Production Planning & Control, 23(10-11), 722-734.
Joshi, K. & Kant, R. (2012). Structuring the underlying relations among the enablers of supply chain collaboration. International Journal of Collaborative Enterprise, 3(1), 38-59.
Kumar, R., Agrawal, R. & Sharma, V. (2013). E-Applications in Indian Agri-Food Supply Chain: Relationship among Enablers. Global business review, 14(4), 711-727.
Kumar, S. A. & Suresh, N. (2008). Production and Operations Management. New Age International (P) Ltd., Publishers, New Delhi.
More, D. & Basu, P. (2013). Challenges of supply chain finance: A detailed study and a hierarchical model based on the experiences of an Indian firm. Business Process Management Journal, 19(4), 624-647.
Nath, V., Kumar, R., Agrawal, R., Gautam, A. & Sharma, V. (2013). Consumer Adoption of Green Products: Modelling the enablers. Global business review, 14(3), 453-470.
Ouelhadj, D. & Petrovic, S. (2009). A survey of dynamic scheduling in manufacturing systems. Journal of Scheduling, 12(4), 417-431.
Raj, T. & Attri, R. (2011). Identification and modelling of barriers in the implementation of TQM. International Journal of Productivity and Quality Management, 8(2), 153-179.
Raj, T., Attri, R. & Jain, V. (2012). Modelling the factors affecting flexibility in FMS. International Journal of Industrial and System Engineering, 11(4), 350-374.
Sabuncuoglu, I., & Bayiz, M. (2000). Analysis of reactive scheduling problems in a job shop environment. European Journal of Operational Research, 126(3), 567-586.
Sage, A. P. (1977). Interpretive Structural Modelling: Methodology for Large Scale Systems. McGraw-Hill, New York, NY, 91-164.
Singh, R. K. (2011). Developing the framework for coordination in supply chain of SMEs. Business Process Management Journal, 17(4), 619-638.
Tokta?-Palut, Baylav, E., Teoman, S. & Altunbey, M. (2014). The impact of barriers and benefits of e-procurement on its adoption decision: An empirical analysis. International Journal of Production Economics, 158, 77-90.
Vieira, G. E., Hermann, J. W., & Lin, E. (2003). Rescheduling manufacturing systems: a framework of strategies, policies and methods. Journal of Scheduling, 6(1), 39-62.
Warfield, J. N. (1974). Developing interconnection matrices in structural modelling. IEEE Transactions on Systems Man and Cybernetics, 4(1), 81-87.
Attri, R. & Grover, S. (2013). Production system life cycle: An Inside story. Accepted in International Journal of Industrial and Systems Engineering.
Attri, R. & Grover, S., (2012). A comparison of production system life cycle models. Frontiers of Mechanical Engineering, 7(3), 305-311.
Attri, R., Grover, S., Dev, N. & Kumar, D. (2013a). An ISM approach for modelling the enablers in the implementation of Total Productive Maintenance (TPM). International Journal of Systems Assurance Engineering and Management, 4(4), 313-326.
Attri, R., Grover, S., Dev, N. & Kumar, D. (2013b). Analysis of barriers of Total Productive Maintenance (TPM). International Journal of Systems Assurance Engineering and Management, 4(4), 365-377.
Attri, R., Dev, N. & Sharma, V. (2013c). Interpretive Structural Modelling (ISM) approach: An Overview. Research Journal of Management Sciences, 2(2), 3-8.
Bolanos, R., Fontela, E., Nenclares, A. & Pastor, P. (2005). Using interpretive structural modelling in strategic decision-making groups. Management Decision, 43(6), 877-895.
Cagno, E., Micheli, G. J. L., Jacinto, C. & Masi, D. (2014). An interpretive model of occupational safety performance for Small- and Medium-sized Enterprises. International Journal of Industrial Ergonomics, 44, 60-74.
Cowling, P. I., and Johansson, M. (2002). Using real-time information for effective dynamic scheduling. European Journal of Operational Research, 139(2), 230-244.
Duperrin, J. C. & Godet, M. (1973). Methode De Hierar Chization Des Elements D’um System. Rapport Economique De CEA, R-45-51, Paris.
Faisal, M. N. (2010). Analysing the barriers to corporate social responsibility in supply chains: an interpretive structural modelling approach. International Journal of Logistics: Research and Applications, 13(3), 179-195
Govindan, K., Palaniappan, M., Zhu, Q. & Kannan, D. (2014). Analysis of third party reverse logistics provider using interpretive structural modelling. International Journal of Production Economics, 140, 204-211.
Haleem, A., Sushil, Qadri, M. A. & Kumar, S. (2012). Analysis of critical success factors of world-class manufacturing practices: an application of interpretative structural modelling and interpretative ranking process. Production Planning & Control, 23(10-11), 722-734.
Joshi, K. & Kant, R. (2012). Structuring the underlying relations among the enablers of supply chain collaboration. International Journal of Collaborative Enterprise, 3(1), 38-59.
Kumar, R., Agrawal, R. & Sharma, V. (2013). E-Applications in Indian Agri-Food Supply Chain: Relationship among Enablers. Global business review, 14(4), 711-727.
Kumar, S. A. & Suresh, N. (2008). Production and Operations Management. New Age International (P) Ltd., Publishers, New Delhi.
More, D. & Basu, P. (2013). Challenges of supply chain finance: A detailed study and a hierarchical model based on the experiences of an Indian firm. Business Process Management Journal, 19(4), 624-647.
Nath, V., Kumar, R., Agrawal, R., Gautam, A. & Sharma, V. (2013). Consumer Adoption of Green Products: Modelling the enablers. Global business review, 14(3), 453-470.
Ouelhadj, D. & Petrovic, S. (2009). A survey of dynamic scheduling in manufacturing systems. Journal of Scheduling, 12(4), 417-431.
Raj, T. & Attri, R. (2011). Identification and modelling of barriers in the implementation of TQM. International Journal of Productivity and Quality Management, 8(2), 153-179.
Raj, T., Attri, R. & Jain, V. (2012). Modelling the factors affecting flexibility in FMS. International Journal of Industrial and System Engineering, 11(4), 350-374.
Sabuncuoglu, I., & Bayiz, M. (2000). Analysis of reactive scheduling problems in a job shop environment. European Journal of Operational Research, 126(3), 567-586.
Sage, A. P. (1977). Interpretive Structural Modelling: Methodology for Large Scale Systems. McGraw-Hill, New York, NY, 91-164.
Singh, R. K. (2011). Developing the framework for coordination in supply chain of SMEs. Business Process Management Journal, 17(4), 619-638.
Tokta?-Palut, Baylav, E., Teoman, S. & Altunbey, M. (2014). The impact of barriers and benefits of e-procurement on its adoption decision: An empirical analysis. International Journal of Production Economics, 158, 77-90.
Vieira, G. E., Hermann, J. W., & Lin, E. (2003). Rescheduling manufacturing systems: a framework of strategies, policies and methods. Journal of Scheduling, 6(1), 39-62.
Warfield, J. N. (1974). Developing interconnection matrices in structural modelling. IEEE Transactions on Systems Man and Cybernetics, 4(1), 81-87.