A Survey of Privacy-Aware Supply Chain Collaboration: From Theory to Applications

Abstract

In the contemporary information era, the ubiquitous collection of data from different parties frequently accommodates significant mutual benefits to the involved participants. However, data is a double-bladed sword. Inappropriate access or use of data by the recipients may pose serious privacy issues that explicitly harm the data owners. In the past decade, swiftly increasing privacy concerns arise in many business processes such as supply chain management. How to protect the private information of different participants in the supply chain has become a key multidisciplinary research problem in information systems, production and operations management, computer science, and mathematics. Specifically, in the real world, manufacturers, distributors, and retailers commonly collaborate with each other to cater to the demands of supplying and marketing. In their traditional cooperation, all the parties completely share their proprietary information so as to jointly optimize their operations (e.g., maximize their profit or minimize their cost). Now, they realize that completely sharing such information would bring considerable negative impact to themselves. For overcoming this, some recent research results begin to make the following ideal occasion possible—all the participants collaboratively solve a realistic problem without revealing any private proprietary information to each other. In this paper, we primarily review the literature on the applications of privacy-preserving techniques to supply chain collaboration among multiple parties. We first identify various private proprietary information required in the supply chain collaboration, and discuss several potential privacy-preserving techniques. Then, we review the relevant research results from theory to applications. Since intensive collaboration in modern supply chains opens even more opportunities in both academia and industry, we finally outline the future research trend and the potential challenges in this promising area.

Efficient Energy Consumption Scheduling: Towards Effective Load Leveling

“…Such information disclosure would explicitly compromise the consumers' privacy on the power grid [40,41]. We will explore privacy-preserving schemes [42,43] to effectively formulate and efficiently solve the ECS/GECS problem among multiple agents on the smart grid with limited disclosure [44,45]. Furthermore, we will extend the agent-based ECS problems for appliances to the entities with renewable energy sources [46,47], considering each agent and its appliances as a microgrid (which both consumes and generates electricity).…”

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“…As collaborative approaches lead to a more open sharing of data between supply chain partners, security and privacy protection issues also attract progressively more attention (ALICE [30], Zeng et al [31], Hong et al [32]). …”

Supply chain management 1982–2015: a review

“…Although a significant amount of research has looked at the information and financial requirements to create effective collaboration and decision making across a SC (such as Cao et al 2010 andLehoux et al 2014), no research to date has investigated the security issues that might present and how they can be overcome as organizations make planning, negotiation and pricing decisions more collaboratively across a SC (Hong et al 2014). This is an increasingly important concern within businesses in general (Upton and Creese, 2014) and its implications for effective SCM need to be better understood.…”