International Journal of Supply and Operations Management
Volume:5 Issue: 2, spring 2018

The purpose of this study is to explore the relationship between dimensions of supply management performance and the components of cash conversion cycle. Although previous literature investigated the link between supply management performance and financial performance, the relationship between supply management performance and liquidity of the firms, which can be assessed by cash conversion cycle, has been largely overlooked. The proposed model and hypotheses were tested by using data from small and medium size enterprises (SMEs) operating in Greece. Support was found for the relationship between supply management performance and cash conversion cycle. The results of our investigation will help supply management professionals not only to achieve a clear understanding of the importance of financial measures of cash flow in relation to supply management performance but also to pay more attention on the contribution of supply management practices on ratios derived from balance sheets and profit and loss statements.

In order to compete effectively in the international markets, pharmaceutical companies must improve their competency. Competition in the global market needs to select the certain level of commitment for sustainability practices by companies to sustain their supply chains. This research presents a multi-objective model to design the pharmaceutical distribution network according to the main concepts of sustainability i.e. economic, environmental and social. This model helps managers to make strategic and technical decisions in the pharmaceutical distribution network (capacity of main and local distribution centers and the flow of drug among the network). Minimizing the costs and maximizing the welfare of society along with minimizing the adverse environmental effects make sustainable decisions. The NSGA-II algorithm was also applied to catch the Pareto-optimal front for the proposed model with respect to three objective functions. To test the model with real data, Darupakhsh distribution company was chosen, the results of the customized model for the case indicates the strategic and technical decisions in the pharmaceutical distribution network.

More and more companies in routing industry are interested in dynamic transportation problems that can be found in several real-life scenarios. In this paper, we addressed a dynamic vehicle routing problem with soft time windows (D-VRPSTW) in which new requests appear at any point during the vehicle’s route. We presented a mathematical formulation of the problem as well as a genetic algorithm hybridized with a variable neighborhood search (VNS) metaheuristic designed for the considered problem. Then, using the time discretization in intervals with new features, we focused on the proposed solution method to solve each partial static problem. We extended the dynamic vehicle routing problem (D-VRPSTW) by considering several objective functions, i.e. minimizing the transportation time by producing better planning, improving the quality of service by minimizing the delay time for each customer, and minimizing time loss by increasing the stopping time for each vehicle. The solution quality of this method has been compared against the existing results on benchmark problems.

An integrated model of maintenance planning and statistical process control is developed for a production process. The process has two operational states including an in-control state and an out-of-control state, where the process failure mechanism is supposed as a general continuous distribution with non-decreasing failure rate. Based on the information obtained from the control chart, three types of maintenance actions may be implemented on the process. The integrated model optimally determines the parameters of the control chart and maintenance actions so that the expected cost per time unit is minimized. To evaluate the performance of the integrated model, a stand-alone model is developed. In the stand-alone model, only maintenance planning is considered. Finally, a real case study is presented to clarify the performances of these models.

In this paper, we develop an integrated bi-objective model of two-stage supply chain composed of a vendor and a buyer under an imperfect production process. The stochastic inflationary condition wherein the first objective is minimizing the expected costs of the proposed supply chain model and the second objective is minimizing buyer’s shortage variance. We assume lead time and ordering cost are controllable parameters and lead time crashing cost is considered as a function of both order quantity and reduced lead time. An effective solution procedure is developed to determine the optimal policy of the proposed model. Finally, a numerical example and sensitivity analysis are proposed to show the performance of the model.

Efficiency is regarded as an important factor for both managers in different companies and organizations and customers who are interested in using the services related to these companies and organizations. However, the biggest challenges managers are coping with include an increase in the competition between companies and manufacturing centers, an increase in the efficiency of production, and finding suitable suppliers. The present study aimed to investigate the efficiency of green supply chain (GSC) by using Malmquist productivity index (MPI) based on the input and output indicators of the BSC model and accordingly providing some rules using the decision tree. To this aim, the efficiency of 15 automotive parts manufacturer firms in Iran was evaluated in the state of constant returns to scale during 2013-2016. Then, the obtained results were used as the class label of Decision Making Units (DMUs) which are regarded as the inputs of decision tree method. Finally, the implicit rules in the data were extracted by using the decision tree. The results indicated that the proposed model had a high degree of accuracy and interpretation in evaluating performance compared to previous models and helps managers to make better decisions to increase the efficiency.

The essence of global supply chain management (GSCM) encumbers several different areas of vertical and horizontal operations throughout the chain. The competitive advantages gained through succinct GSCM provide businesses with optimized operations and increase stakeholder value. Development of sustainability, collaboration, and reputational risk initiatives offers multinational corporations (MNCs) capabilities to drive GSCM while limiting supply chain (SC) liabilities. The research showed that MNCs are competing through SCs to increase global market share and customer satisfaction through social, environmental, and economic initiatives. Consistent improvement in these areas affords MNCs with future aims such as delivering renewable resources to developing and emerging markets, less expensive goods, services as SCs improve operations, and cultural awareness as multiple countries and organizations work together. Creating this synergy among SC stakeholders and the environment affords social, environmental, and economic sustainability.