Risk adjustment for measuring health care outcomes

The massive rise of Big Data generated from smartphones, social media, Internet of Things (IoT), and multimedia, has produced an overwhelming flow of data in either structured or unstructured format. Big Data technologies are being developed and implemented in the food supply chain that gather and analyse these data. Such technologies demand new approaches in data collection, storage, processing and knowledge extraction. In this article, an overview of the recent developments in Big Data applications in food safety are presented. This review shows that the use of Big Data in food safety remains in its infancy but it is influencing the entire food supply chain. Big Data analysis is used to provide predictive insights in several steps in the food supply chain, support supply chain actors in taking real time decisions, and design the monitoring and sampling strategies. Lastly, the main research challenges that require research efforts are introduced.

Big Data in food safety- A review

As an innovative mode of supply chain finance, financing service offered by a third part logistics (3PL) firm has been practiced over the recent years. This paper investigates the optimal operation...

Optimal operational strategies of supply chain under financing service by a 3PL firm

In recent years, blockchain technology has been increasingly adopted in OTC medicine supply chains, enabling customers to track the entire process from raw material purchasing to finished medicine distribution. This improves the brand image and hence expands the market. With the use of blockchain, information transparency can be achieved because data are stored immutably and safely in a distributed database that is accessible by all supply chain members. However, will the incentives for supply chain members to participate in blockchain for larger-scale demand come at the cost of information disclosure? In this paper, to investigate the supply chain members’ incentive alignment opportunities towards the adoption of blockchain technology, we consider a two-stage supply chain comprising two medicine manufacturers and a common retailer that has more accurate demand information than the manufacturers have. We find that, interestingly, the retailer has incentives to participate in blockchain when the manufacturers’ competition is mild and the demand variance is low. We further investigate the impact of blockchain on total surplus and customer surplus and find that the adoption of blockchain always benefits customers and society; therefore, blockchain can be particularly useful for social goods such as OTC medicine.

Incentive alignment for blockchain adoption in medicine supply chains

The operations‐finance interface (OFI) jointly optimizes material, monetary, and information flows under intricate sources of uncertainty. To sketch the broad landscape in this emerging and interdisciplinary field, this study synthesizes literature across diverse themes and dispersed methodologies, screens systematically the research progression from original foundations to recent contributions in each major research stream, and thereby advocates future research innovations on prospective topics in light of the interconnections and potential reciprocity between operations and finance from risk management aspects.

Operations-Finance Interface in Risk Management: Research Evolution and Opportunities

This study investigates manufacturer guarantor financing (MG) and third‐party logistics (3PL) guarantor financing (LG) in a four‐party supply chain game that features a manufacturer, a 3PL, a capital‐constrained retailer, and a bank. The manufacturer or 3PL can act as the guarantor for the retailer who borrows bank credit. Two different leadership structures are investigated, namely, Nash game and manufacturer leadership Stackelberg game, where the manufacturer and 3PL decide simultaneously and sequentially, respectively. The supply chain under both leadership structures prefers guarantor financing to traditional bank financing when the supply chain is sufficiently cost‐efficient. In the Nash game, however, firms encounter a free‐rider dilemma when choosing between MG and LG, wherein both potential guarantors prefer the other to be the guarantor. This free‐rider dilemma can be resolved in the Stackelberg game. We also observe the follower–guarantor advantage in the Stackelberg game, wherein all firms favor the follower to provide guarantor financing. Our analysis shows that the supply chain under guarantor financing with a longer decision hierarchy (i.e., the Stackelberg game) can be conditionally more effective than that with a shorter one (i.e., the Nash game). By further analyzing different cost structures, pricing mechanism, and retailer’s initial capital, we find that most of our qualitative results remain accurate under more sophisticated conditions. These findings enhance our understanding of the value of guarantor financing in a capital‐constrained supply chain and the impact of leadership structure on financing decisions.

Guarantor Financing in a Four-Party Supply Chain Game with Leadership Influence

The present study investigates the benefit of joint decision making regarding whole blood collection and platelet production at a blood center. We consider a blood center that faces two types of platelet demands, differing in their freshness requirements and shortage penalty costs. We fully characterize the structure of the optimal policy regarding whole blood collection, platelet production, and inventory issuing, rationing and disposal. We find that the optimal platelet production quantity in each period is nonincreasing in the inventory levels of platelets and whole blood but that interestingly, the optimal blood collection effort may increase with the on‐hand platelet inventory level. We demonstrate with a real dataset that joint decision making leads to significant cost savings compared with separate decision making. The benefit is mainly derived from reduced blood collection and platelet production, better utilization of the collected whole blood, and reduced platelet shortage. For practical implementation, we develop a lookahead heuristic, which is shown to be very effective by numerical experiments.

Joint Decisions for Blood Collection and Platelet Inventory Control

This paper illustrates how supply chain (SC) analytics could provide strategic and operational insights to evaluate the risk-based allocation of regulatory resources in food SCs, for management of ...

Testing at the Source: Analytics-Enabled Risk-Based Sampling of Food Supply Chains in China

Manufacturing servitization has become a major trend in industry that is implemented by so called integrated production and service systems (IPSSs) to offer not only products but also their associated services. In this study, we explore the capacity allocation policy for an IPSS that consists of a manufacturing facility and a service center. The IPSS serves two classes of customers, each demanding a specific product produced at the manufacturing facility and, subsequently, the associated service offered by the service center. We formulate this problem of resource allocation as a Markov decision process. Our analysis suggests that it is optimal to serve the customer with the larger cost saving rate and slower service rate, where the cost saving rate equals service rate times the sum of holding cost and waiting cost. Then we explore production control policies coupled with optimal service ones. We demonstrate that, with light service traffic, the system under the optimal production policy becomes similar to a make‐to‐stock system. Such a system can effectively hedge the system uncertainty. Therefore, the optimal production policy for the IPSS is also a hedging point policy. Under this policy, switching and idling curves split the state space into three regions: one without any production, the two others for production of two type products, respectively. We also discuss the optimal control policies of the two extensions of the IPSS (one with multiple types of product and customers, and the other with a single product and two classes of customers) and find that the characters of the optimal production and service policy still hold. Finally, we develop three heuristic integrated scheduling policies. Numerical experiments show that one is very effective.

Capacity Allocation of an Integrated Production and Service System

This paper illustrates how supply chain (SC) analytics could provide strategic and operational insights to inform risk-based allocation of regulatory resources in food SCs, for management of food safety and adulteration risks. The paper leverages a massive, self-constructed dataset of food safety tests conducted by China Food and Drug Administration (CFDA) organizations. The integrated and structured dataset is used to conduct innovative analysis that identifies the sources of adulteration risks in China’s food SCs, and contrasts them with the current test resource allocations of the CFDA. The analysis highlights multiple strategic insights. Particularly, it suggests potential areas for improvement in the current CFDA testing allocation by SC location, that is heavily focused on retail and supermarkets. Instead, the analysis indicates that high risk parts of the SC, such as wholesale and wet markets, are undersampled. Additionally, the paper highlights the impact that SC analytics could have on policy-level operational decision making to regulate food SCs and manage food safety. The hope is that the paper will stimulate the interest of academics with expertise in these areas, to conduct more work in this important application domain.

Weihua Zhou

Papers

Guarantor Financing in a Four-Party Supply Chain Game with Leadership Influence

Joint Decisions for Blood Collection and Platelet Inventory Control

Testing at the Source: Analytics-Enabled Risk-Based Sampling of Food Supply Chains in China

Capacity Allocation of an Integrated Production and Service System

Testing at the Source: Analytics-Enabled Risk-Based Sampling of Food Supply Chains in China