Management Insights

When academic researchers participate in commercialization using for-profit firms, there is a potentially costly trade-off—their time and effort are diverted away from academic knowledge production. This is a form of brain drain on the not-for-profit research sector that may reduce knowledge accumulation and adversely impact long-run economic growth. In this paper, we examine the economic significance of the brain drain phenomenon using scientist-level panel data. We identify life scientists who start or join for-profit firms using information from the Small Business Innovation Research program and analyze the research performance of these scientists relative to a control group of randomly selected research peers. Combining our statistical results with data on the number of university spin-offs in the United States from 1994 to 2004, we find the academic brain drain has a nontrivial impact on knowledge production in the not-for-profit research sector.

Supply chain management is one of the new approaches that are considered significantly by variety of experts and enterprises in today competitive world. Supply chain refers to the network of facilities, supply centers, production centers and distribution centers which encompass various tasks such as providing raw materials, transforming raw materials to components or finished products and distributing them among customers. Regarding this issue, studying literature indicates on this fact that multi-level, multi-product, multi-period models in multi-sourcing situation by considering the supply capacity have not been taken into account notably and just few mathematical models are proposed for the analysis of such decisions. In this paper, it is attempted to investigate and delve into the supply chain planning issue in multi-level, multi-product, multi-period situation. In the proposed model, simultaneously optimization of two objectives is considered which entails maximizing the service level related to giving agreeable services to customers at each retailer's site and minimizing the overall costs of supply chain. As the proposed mixed integer non-linear model has specific complexity, branch and bound solver is utilized and has been applied for a data set in an automotive supply chain. In this way, a model has been presented which determines the lot size of ordering among various members in a supply chain, the amount of holding inventory at each elements of supply chain's site, optimal combination of selecting potential suppliers and the amount of ordering components to suppliers.

Principal–agent problem for returns handling in a reverse supply chain with one manufacturer and two competing dealers

The evolution of e-retailing is driving a rise in logistics costs and risk of late delivery. Collaborative logistics has become the key to help businesses eliminate inefficiencies, improve responsiveness to market changes, and reduce overall supply chain costs by adjusting transportation capacity efficiently. In this study, we propose a stochastic mixed integer linear programming model that incorporates shipper’s transportation operations via truck sharing service. The model supports strategic network design decisions in uncertain market environments by optimizing the number of trucks under uncertain demand. Through several case studies on a small-scale truck sharing network, we show the influence of demand uncertainty on the network performance in terms of the on-time delivery ratio and the gross profit margin ratio. We also show the influence of the sharing platform features such as the transaction price and the number of available trucks, on shippers as well as a platformer in terms of the turnover of trucks.

Closed-loop supply chain is an important path to realize the sustainable development of supply chain, and cap-and-trade and carbon tax policies further promote closed-loop supply chain to invest in low-carbon technologies. This paper combines Economic Production Quantity with Economic Order Quantity models and designs multiple carbon policies. Abatement rate and collection rate are the key variables used to explore the mechanism of the interaction between carbon tax and cap-and-trade, inventory dynamics of closed-loop supply chain and impact of multiple carbon policies on closed-loop supply chain. Construct and analyze benchmark model, investment model under multiple carbon policies, remanufacturing model under multiple carbon policies and mixed strategies model under multiple carbon policies, and the results show that there is a non-linear complementary relationship between carbon price and carbon tax, and both remanufacturing and low-carbon investment can optimize cost and carbon emissions when carbon price is distributed at a certain interval. Furthermore, mixed strategies combining remanufacturing and low-carbon investment can optimize cost and carbon emissions simultaneously. The main contribution of this paper is to build a low-carbon circular system, which can help balance cost and carbon emissions of closed-loop supply chain.

Under the context of globalization of Supply Chain and the diversity of product with the shortening product life cycle, the supply chain network design method with recycling reusable resources is being advocated. Hence this paper intent to qualify the impact of recycle strategy on the performance of global supply chain for short life cycle product, and propose an optimization method to provide an integrated planning for incorporating supply chain partners activities during the entire life cycle period of products in order to minimize supply chain operating cost. A Mixed Integer Programming model is proposed to formulate the supply chain network for short life cycle product demanded in multiple markets with recycle material flows. The experiment result shows that proper recycle operation policy will effectively down the total cost of entire supply chain.

Simulation based evolutionary algorithms for fuzzy chance-constrained biogas supply chain design

Optimizing a bi-objective multi-product multi-period three echelon supply chain network with warehouse reliability

In Surakarta and its surroundings (Solo Raya), there exists more than 400 Small-Medium Enterprises (SMEs) that produce finished products of rattan. Due to the high procurement cost as total operational cost of raw rattan distribution network from the sources, e.g. Borneo and Celebes to the rattan industries, the competitiveness of their products is lower than products from other countries. Therefore, to overcome the problem, those costs should be reduced for example by aggregating the demand of rattan industries. This police needs to be supported by the warehouse for storing and distributing raw rattan. Hence, this research aims to develop a facility location-allocation model so that total supply chain costs, including raw rattan procurement costs as well as facilities opening and closing costs can be minimized. The location-allocation model will be presented in a mixed integer non-linear programming model and solved using MS-Excel Solver. The results are number and location of the warehouse along with the raw rattan allocation in the warehouse to ensure raw rattan supply for rattan industries.