The role of supply chain management in Irish enterprise strategy development:a three-dimensional approach

The Irish economy has grown strongly in recent years. This, combined with other factors in the international trading environment, has sharpened the focus on the need for innovative strategies at a national level which can contribute positively from an enterprise strategy development perspective. As traditional manufacturing activity has migrated to lower labour cost economies questions have been raised concerning the role of supply chain management (SCM) in the evolving Irish business environment. This paper describes some of the main drivers in terms of both SCM and the changing economic and business environment. It goes on to propose a three-dimensional approach to understanding the potential role of SCM in the new scenario. This in turn informs the logistics and SCM research agenda from a national policy point of view.

Using the max-sum algorithm for supply chain emergence in dynamic multiunit environments

Supply chain formation (SCF) is the process of determining the set of participants and exchange relationships within a network with the goal of setting up a supply chain that meets some predefined social objective. Many proposed solutions for the SCF problem rely on centralized computation, which presents a single point of failure and can also lead to problems with scalability. Decentralized techniques that aid supply chain emergence offer a more robust and scalable approach by allowing participants to deliberate between themselves about the structure of the optimal supply chain. Current decentralized supply chain emergence mechanisms are only able to deal with simplistic scenarios in which goods are produced and traded in single units only and without taking into account production capacities or input-output ratios other than 1:1. In this paper, we demonstrate the performance of a graphical inference technique, max-sum loopy belief propagation (LBP), in a complex multiunit unit supply chain emergence scenario which models additional constraints such as production capacities and input-to-output ratios. We also provide results demonstrating the performance of LBP in dynamic environments, where the properties and composition of participants are altered as the algorithm is running. Our results suggest that max-sum LBP produces consistently strong solutions on a variety of network structures in a multiunit problem scenario, and that performance tends not to be affected by on-the-fly changes to the properties or composition of participants.

Life cycle assessment in the food supply chain:a case study

This research aims at assessing the environmental impact of the poultry supply chain from cradle to grave using case study research and also life cycle assessment (LCA). While a limited number of generic poultry production LCA studies have been published, fewer yet assess the whole process of a specific organisation, none comparing the increased impact of further processing. Our results show that irrespectively of the impact assessment method utilised, the process of producing portions is considerably higher in total environmental impact due to the extra raw material required to produce the same mass into retail. Our research contributes to the growing number of LCA studies and could be used by practitioners for comparison against national and international averages. From a theoretical point of view, this research provides new insights into the relationship between vertically integrated supply chains and environmental performance which has not been examined in the past.

The implementation of supply chain management theory in practice:an empirical investigation

Purpose: The purpose of the research described in this paper is to disentangle the rhetoric from the reality in relation to supply chain management (SCM) adoption in practice. There is significant evidence of a divergence between theory and practice in the field of SCM. Design/methodology/approach: Based on a review of extant theory, the authors posit a new definitional construct for SCM – the Four Fundamentals – and investigated four research questions (RQs) that emerged from the theoretical review. The empirical work comprised three main phases: focussed interviews, focus groups and a questionnaire survey. Each phase used the authors’ definitional construct as its basis. While the context of the paper’s empirical work is Ireland, the insights and results are generalisable to other geographical contexts. Findings: The data collected during the various stages of the empirical research supported the essence of the definitional construct and allowed it to be further developed and refined. In addition, the findings suggest that, while levels of SCM understanding are generally quite high, there is room for improvement in relation to how this understanding is translated into practice. Research limitations/implications: Expansion of the research design to incorporate case studies, grounded theory and action research has the potential to generate new SCM theory that builds on the Four Fundamentals construct, thus facilitating a deeper and richer understanding of SCM phenomena. The use of longitudinal studies would enable a barometer of progress to be developed over time. Practical implications: The authors’ definitional construct supports improvement in the cohesion of SCM practices, thereby promoting the effective implementation of supply chain strategies. A number of critical success factors and/or barriers to implementation of SCM theory in practice are identified, as are a number of practical measures that could be implemented at policy/supply chain/firm level to improve the level of effective SCM adoption. Originality/value: The authors’ robust definitional construct supports a more cohesive approach to the development of a unified theory of SCM. In addition to a profile of SCM understanding and adoption by firms in Ireland, the related critical success factors and/or inhibitors to success, as well as possible interventions, are identified.

Managing imbalanced supply chain relationships for sustainability:a power perspective

This study adopts a power perspective to investigate sustainable supply chain relationships and specifically uses resource-dependence theory (RDT) to critically analyze buyer-supplier-supplier relationships. Empirical evidence is provided, extending the RDT model in this context. The concept of power relationships is explored through a qualitative study of a multinational company and agricultural growers in the UK food industry that work together to implement sustainable practices. We look at multiple triadic relationships involving a large buyer and its small suppliers to investigate how relative power affects the implementation of sustainable supply-management practices. The study highlights that power as dependence is relevant to understanding compliance in sustainable supply chains and to identifying appropriate relationship-management strategies to build more sustainable supply chains. We show the influences of power on how players manage their relationships and how it affects organizational responses to the implementation of sustainability initiatives. Power notably influences the sharing of sustainability-related risks and value between supply chain partners. From a managerial perspective, the study contributes to developing a better understanding of how power can become an effective way to achieve sustainability goals. This article offers insights into the way in which a large organization works with small and medium size enterprises to implement sustainable practices and shows how power management-that is, the way in which power is used-can support or hinder effective cooperation around sustainability in the supply chain. © 2014 Decision Sciences Institute.

A knowledge driven approach towards the validation of externally acquired traceability datasets in supply chain business processes

The sharing of near real-time traceability knowledge in supply chains plays a central role in coordinating business operations and is a key driver for their success. However before traceability datasets received from external partners can be integrated with datasets generated internally within an organisation, they need to be validated against information recorded for the physical goods received as well as against bespoke rules defined to ensure uniformity, consistency and completeness within the supply chain. In this paper, we present a knowledge driven framework for the runtime validation of critical constraints on incoming traceability datasets encapuslated as EPCIS event-based linked pedigrees. Our constraints are defined using SPARQL queries and SPIN rules. We present a novel validation architecture based on the integration of Apache Storm framework for real time, distributed computation with popular Semantic Web/Linked data libraries and exemplify our methodology on an abstraction of the pharmaceutical supply chain.

Green manufacturing supply chain design and operations decision support

This special issue of International Journal of Production Research provides a platform for sharing the knowledge base, recent research outputs and a review of recent developments highlighting the critical aspects of green manufacturing supply chain design and operations decision support. The special issue includes 15 contributions presenting new and significant research in the relevant area. Contributions mainly present either a novel green/sustainable manufacturing supply chain design and operations decision support approach applied to a problem, or a state-of-the-art method on green/sustainable factors in supply chain design and operations. The article delineates an overview of the contributions and their significance, and an introspection on the ‘green’ factors involved.

Detecting EPCIS exceptions in linked traceability streams across supply chain business processes

The EPCIS specification provides an event oriented mechanism to record product movement information across stakeholders in supply chain business processes. Besides enabling the sharing of event-based traceability datasets, track and trace implementations must also be equipped with the capabilities to validate integrity constraints and detect runtime exceptions without compromising the time-to-deliver schedule of the shipping and receiving parties. In this paper we present a methodology for detecting exceptions arising during the processing of EPCIS event datasets. We propose an extension to the EEM ontology for modelling EPCIS exceptions and show how runtime exceptions can be detected and reported. We exemplify and evaluate our approach on an abstraction of pharmaceutical supply chains.

The challenges of representing human behaviour in simulation models:some case examples from supply chain, evacuation modelling and rail disruption

As more of the economy moves from traditional manufacturing to the service sector, the nature of work is becoming less tangible and thus, the representation of human behaviour in models is becoming more important. Representing human behaviour and decision making in models is challenging, both in terms of capturing the essence of the processes, and also the way that those behaviours and decisions are or can be represented in the models themselves. In order to advance understanding in this area, a useful first step is to evaluate and start to classify the various types of behaviour and decision making that are required to be modelled. This talk will attempt to set out and provide an initial classification of the different types of behaviour and decision making that a modeller might want to represent in a model. Then, it will be useful to start to assess the main methods of simulation in terms of their capability in representing these various aspects. The three main simulation methods, System Dynamics, Agent Based Modelling and Discrete Event Simulation all achieve this to varying degrees. There is some evidence that all three methods can, within limits, represent the key aspects of the system being modelled. The three simulation approaches are then assessed for their suitability in modelling these various aspects. Illustration of behavioural modelling will be provided from cases in supply chain management, evacuation modelling and rail disruption.

Balancing push and pull information management within the supply chain

The aim of this paper is to explore the management of information in an aerospace manufacturer's supply chain by analysing supply chain disruption risks. The social network perspective will be used to examine the flows of information in the supply chain. The examination of information flows will also be explored in terms of push and pull information management. The supply chain risk management (SCRM) strategy is to assess the management of information that allows companies to gather information which will allow them to mitigate that risk before any disruption to the supply chain occurs. There is a shortage of models in analysing the supply chain risk associated with information flows, possibly due to the omission of appropriate modelling techniques in this area (Tang and Nurmaya, 2011). This paper uses an exploratory case study consisting of a multi method qualitative approach using fifteen interviews and four focus groups.

Representing supply chain events on the Web of data

The Electronic Product Code Information Service (EPCIS) is an EPCglobal standard, that aims to bridge the gap between the physical world of RFID1 tagged artifacts, and information systems that enable their tracking and tracing via the Electronic Product Code (EPC). Central to the EPCIS data model are "events" that describe specific occurrences in the supply chain. EPCIS events, recorded and registered against EPC tagged artifacts, encapsulate the "what", "when", "where" and "why" of these artifacts as they flow through the supply chain. In this paper we propose an ontological model for representing EPCIS events on the Web of data. Our model provides a scalable approach for the representation, integration and sharing of EPCIS events as linked data via RESTful interfaces, thereby facilitating interoperability, collaboration and exchange of EPC related data across enterprises on a Web scale.

Practitioner perspectives on supply chain management and logistics:a study from the United Kingdom

Purpose: The focus of this paper is the evolution of supply chain management (SCM) and logistics, as well as of the relationship between them. Its purpose is to generate deep insights into practice, particularly in relation to the fundamental issue of how practitioners define these key terms and phrases. Research approach: A largely qualitative study which involved in depth interviews with managers from two third party logistics providers (3PLs)/distributors, two retailers and two manufacturers from the United Kingdom. This interview protocol is based on the template used in a previous study published over a decade ago. Findings and originality: The data collected during the focussed interviews in the United Kingdom is contrasted with results from the earlier study. The findings suggest that there is variation between practitioners particularly in relation to what SCM is specifically concerned with. This variation mirrors to a large extent the differing orientations and emphases evident in the many theoretical definitions of SCM that have been proposed in recent decades. Research impact: The authors introduced the concept of refined replication in SCM research. This allows previous research to be built upon in order to test understanding of SCM theory and its practical implementation among SCM professionals in the United Kingdom. Practical impact: A profile of SCM understanding and adoption by firms in the United Kingdom is presented .

Advances in decision support systems on the endeavour for supply chain optimality

Industry practitioners are seeking to create optimal logistics networks through more efficient decision-making leading to a shift of power from a centralized position to a more decentralized approach. This has led to researchers, exploring with vigor, the application of agent based modeling (ABM) in supply chains and more recently, its impact on decision-making. This paper investigates reasons for the shift to decentralized decision-making and the impact on supply chains. Effective decentralization of decision-making with ABM and hybrid modeling is investigated, observing the methods and potential of achieving optimality.