The rapid spread and acceptance of globalization and the enormous developments in information technology, has led to dramatic changes in the business environment. These changes have brought new challenges not only to business but also to business education. Business schools that prepare future managers in different disciplines are responsible for closing the gap between the skills acquired by its graduates and the required skills by the global markets. This paper identifies the challenges facing accounting education in providing students with the knowledge and skills that raise their competency level to meet that required by the market. These challenges warrant that the competency level of accountants should be improved. Current accounting education and the skill levels of accountants are not in line with what is required in the dynamic environments of global business. A strategic plan for closing the gap between the acquired and required skills is presented to help prepare students for facing and dealing with the challenges of the new global business environment.

In today’s global business environment, it is not a viable economic alternative for a nation or an economy to be isolated from the rest of the world. There are many challenges that every nation (especially a developing nation) faces. Are our potential graduates from the educational systems capable enough of facing these challenges? Is business education capable of preparing future managers to face these challenges? This paper investigates the characteristics of a contemporary business education, analyses the challenges posed by global market trends, and proposes learning strategies that meet market requirements.

PurposeThe purpose of the paper is to present an integrated model for the location of warehouse, the allocation of retailers to warehouses, and finding the number of vehicles to deliver the demand and the required vehicle routing in order to minimize total transportation costs, fixed and operating costs, and routing costs.Design/methodology/approachThe model assumes that the number of plants has already been determined and answers the following questions: what is the number of warehouses to open? How warehouse are allocated to plants? How retailers are allocated to warehouses? Who are the retailers that will be visited and in what order? How many vehicles are required for each route? What are the total minimum costs?FindingsThe model was formulated as a mixed integer linear programming model and solved using Lagrange relaxation and sub‐gradient search for the location/allocation module and a traveling salesman heuristic for the routing module. The results for the randomly selected problems show that the deviation in objective function value ranges between 0.29 and 2.05 percent from the optimum value. Also, from the CPU time point of view, the performance was very good.Originality/valueAn attempt is made to integrate location, allocation, and routing decisions in the design of a supply chain network.

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