Towards a Novel Cooperative Logistics Information System Framework

Supply Chains and Logistics have a growing importance in global economy. Supply Chain Information Systems over the world are heterogeneous and each one can both produce and receive massive amounts of structured and unstructured data in real-time, which are usually generated by information systems, connected objects or manually by humans. This heterogeneity is due to Logistics Information Systems components and processes that are developed by different modelling methods and running on many platforms; hence, decision making process is difficult in such multi-actor environment. In this paper we identify some current challenges and integration issues between separately designed Logistics Information Systems (LIS), and we propose a Distributed Cooperative Logistics Platform (DCLP) framework based on NoSQL, which facilitates real-time cooperation between stakeholders and improves decision making process in a multi-actor environment. We included also a case study of Hospital Supply Chain (HSC), and a brief discussion on perspectives and future scope of work

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Logistics outsourcing and 3PL selection: A Case study in an automotive supply chain

Outsourcing logistics functions to third-party logistics (3PL) providers has been a source of competitive advantage for most companies. Companies cite greater flexibility, operational efficiency, improved customer service levels, and a better focus on their core businesses as part of the advantages of engaging the services of 3PL providers. There are few complete and structured methodologies for selecting a 3PL provider. This paper discusses how one such methodology, namely the Analytic Hierarchy Process (AHP), is used in an automotive supply chain for export parts to redesign the logistics operations and to select a global logistics service provider

Clusters and supply chain management: challenges and obstacles

Purpose: This paper provides an insight into cluster supply chain (CSC) management by identifying challenges and obstacles in the design, implementation and improvement of CSC. This evaluation aims to propose future research directions for the management of CSC. Research Approach: A systematic review of published research on CSC management between 2006 and 2013 is conducted in order to round up previous research in this area and identify the gaps in the design, implementation and management of CSC; up on which the paper closes with a proposed agenda for future work. Findings and Originality: There is a limited understanding of the supply chain cluster concept and the implementation of its practices in addition to the lack of studies that focused on how to model, manage and improve the performance of CSC. Therefore, this paper would contribute to knowledge by providing an insight into CSC management and identifying future research directions for developing SC cluster theories in order to maximize the integration of supply chain and accordingly improving the performance of firms. Research Impact: A limited number of studies have been conducted to demonstrate the potential impact of CSC. The previous research did not provide a comprehensive review focusing on the evolution and the development of CSC idea. The review in this paper will summarise the research up to now in CSC area in order to identify challenges and obstacles in the design, implementation and improvement of CSC and propose future research directions. Practical Impact: This paper helps companies to understand benefits that can be raised from creating CSC and gives them directions for improving their capabilities to create CSC and select SC partners, which consequently help in increasing their competitiveness in terms of enhancing performance and increasing sustainability

A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

Regional food clusters and government support for clustering: Evidence for a ‘dynamic food innovation cluster’ in Alberta, Canada?

Location-based clusters and virtual cluster configurations have received significant attention from policymakers due to their potential implications on productivity, innovation and regional growth. This paper presents a short review of studies that have analyzed clustering activity in the food sectors of several countries. The key insights from these studies with regard to the underlying factors for clustering success are contrasted with empirical evidence from the food processing sector of Alberta, Canada. This includes the presentation of results from an exploratory firm-level survey on government support for clustering activity in Alberta’s food. Considering the level of government support for innovation, the limited access to supporting business infrastructure, and the lack of effective networking between industry stakeholders, we find little evidence for an emerging innovation cluster in Alberta’s food industry.regional clusters, food processing, government support for innovation, Canada