Information and Service Flow Modeling and Performance Analysis of Cloud Supply Chain Networks

Abstract

Industry forecasts on Information Technology (IT) in adopting cloud computing services for supply chain networks indicates potential benefits for enterprises. Firms can integrate cloud computing services for managing their supply chain network (SCN) and increase their efficiency. Today, cloud integrated with supply chain network (CSCN) is in its infancy stage. Cloud computing service providers offers varieties of services for various applications. The potential benefits that cloud computing services can offer to the supply chain network has to be explored. The inter-relationships between various service characteristics of cloud computing needs to be identified on a case to case basis depending on the nature of operations of a supply chain network firm. In this research, various cloud services that can be utilized and integrated within the systems used for managing the supply chain network are identified. The cloud services that were identified to be beneficial to supply chain networks are collaboration services, price flexibility, no upfront investment, convenience of development, IT efficiency, scalability, launch of new products and services, savings in operational cost savings, savings in software cost, savings in costs and better utilization of hardware. Almost 11 benefits of cloud computing services were considered for testing on their significance with respect to three cloud IT services IaaS, PaaS and SaaS. The benefits were considered as variables offering varying benefits to supply chain networks and the same were utilized for various modelling and analysis in this research. It was found that currently there is no significant difference in the rating between the three cloud services when it comes to benefits for supply chain networks. As more and more developments take place in cloud computing services, service benefits for supply chain networks will evolve separately through services of IaaS, PaaS and SaaS.Variations in each of the characteristics based on maximum rating of PY are observed to be -14.3%, -15.6%, +26%, +0.02% on (SL, IC, DS, CS). This indicates that the Pay as per usage and Cost savings are stable while the variations are high with +26% for Decision support services and -15.6% for Collaborations. Similarly, for IC, variations in each of the characteristics based on maximum rating of IC are -12.5%, +30.5%, +50.5%, -67.6% on (SL, DS, PY, CS). Details of Consumer level, wholesaler and retailer level, manufacturer level and supplier level indicating proportion of impact of bullwhip is furnished. A relationship between Estimation (X1), Pricing (X2), Costing (X3) and Partnership (X4) in terms of cost function is derived. newlineThe function is C(X) = 0.403X1 + 0.305X2 + 0.131X3 + 0.154X4 newlineThe detailed work on information and service flow modelling and the performance analysis of cloud supply chain networks is reported in various chapters of this thesis. Various works done were submitted for publications in Journals and presentations in Conferences. A list of all publications and presentations is furnished for reference. newline