Ilaria Giannoccaro

A fuzzy echelon approach for inventory management in supply chains

Abstract This paper presents a methodology to define a supply chain (SC) inventory management policy, which is based on the concept of echelon stock and fuzzy set theory. In particular, the echelon stock concept is adopted to manage the SC inventory in an integrated manner, whereas fuzzy set theory is used to properly model the uncertainty associated with both market demand and inventory costs (e.g. holding and backorder costs). The methodology is applied on a three stage SC so as to show the ease of implementation. Finally, by adopting simulation, the performance of the three stage SC is assessed and shown to be superior to that, which the adoption of a local inventory management policy would guarantee.

Inventory management in supply chains: a reinforcement learning approach

Abstract A major issue in supply chain inventory management is the coordination of inventory policies adopted by different supply chain actors, such as suppliers, manufacturers, distributors, so as to smooth material flow and minimize costs while responsively meeting customer demand. This paper presents an approach to manage inventory decisions at all stages of the supply chain in an integrated manner. It allows an inventory order policy to be determined, which is aimed at optimizing the performance of the whole supply chain. The approach consists of three techniques: (i) Markov decision processes (MDP) and (ii) an artificial intelligent algorithm to solve MDPs, which is based on (iii) simulation modeling. In particular, the inventory problem is modeled as an MDP and a reinforcement learning (RL) algorithm is used to determine a near optimal inventory policy under an average reward criterion. RL is a simulation-based stochastic technique that proves very efficient particularly when the MDP size is large.

Supply chain cooperation in industrial districts: A simulation analysis

In the past few years the literature on supply chain management has widely emphasized that cooperation among supply chain (SC) firms is a key source of competitive advantage. This paper explores the topic in a particular context, i.e. the industrial district (ID), which constitutes a specific production model where complex SC networks can be identified. SC cooperation may take on several forms in IDs and may produce several benefits (e.g. upgrading quality and reducing costs) so this paper also analyzes the benefits of a specific form of SC cooperation in different competitive scenarios and for diverse ID organizational structures. An agent-based model of SC cooperation in IDs has been developed and a simulation analysis carried out.

Supply chains within industrial districts: A theoretical framework

Abstract The literature on Industrial Districts (IDs) has emphasised the importance of inter-organisational relationships within this specific production model. However, this stream of studies has given less attention to conceptualise models and define techniques to effectively manage such relationships. In the paper a theoretical framework is proposed to characterise the IDs as a kind of production systems, on which basis appropriate managerial guidelines can be derived. In particular, the framework focuses on the supply chain/s within an ID and describes them in terms of physical, technological, strategic, and organisational dimensions. The theoretical framework is intended to help IDs, particularly the leader firms, better understand the whole production process so as to enhance the process performance. A case study of an Italian ID localised in Southern Italy is then discussed to validate the framework.

Operations planning and flexibility in a supply chain

In dynamic competitive markets, the flexibility of manufacturing system networks such as supply chains (SCs) is particularly interesting. The SC flexibility considered in this paper takes into account two main aspects: the process flexibility of each SC firm and the logistics flexibility concerning the possible connections between suppliers, assemblers and markets. Different configurations of an SC are proposed, in correspondence to different degrees of the process and logistics flexibility. The effects of SC flexibility are then investigated on the operations planning performance of an SC subject to production capacity uncertainty and coping with demand volume and mix variability. In particular, an optimization model is defined to analyse the SC performance in every SC configuration. Managerial guidelines, supporting the management of selecting the appropriate degrees of flexibility and the corresponding SC configuration to be adopted, are finally obtained.

The organizational perspective in supply chain management: an empirical analysis in Southern Italy

This paper addresses the supply chain (SC) co-ordination problem and emphasises the need to consider the involved organisational issues when dealing with it. In particular, the influence of the form of SC governance on the selection of SC co-ordination mechanisms is investigated. An empirical analysis on a sample of firms located in Southern Italy is carried out to study some theoretical assumptions. The latter are based on the available literature and suggest specific configurations of fit between the SC form of governance and the types of co-ordination mechanisms. In particular, we propose a conceptual model wherein the fit between the SC form of governance and the co-ordination mechanism is associated with a higher level of SC operational performance.

Model of human collective decision-making in complex environments

A continuous-time Markov process is proposed to analyze how a group of humans solves a complex task, consisting in the search of the optimal set of decisions on a fitness landscape. Individuals change their opinions driven by two different forces: (i) the self-interest, which pushes them to increase their own fitness values, and (ii) the social interactions, which push individuals to reduce the diversity of their opinions in order to reach consensus. Results show that the performance of the group is strongly affected by the strength of social interactions and by the level of knowledge of the individuals. Increasing the strength of social interactions improves the performance of the team. However, too strong social interactions slow down the search of the optimal solution and worsen the performance of the group. In particular, we find that the threshold value of the social interaction strength, which leads to the emergence of a superior intelligence of the group, is just the critical threshold at which the consensus among the members sets in. We also prove that a moderate level of knowledge is already enough to guarantee high performance of the group in making decisions.

A cost analysis of supply chain flexibility configurations

In this paper, some Supply Chain (SC) configurations based on different degrees of flexibility are considered. The SC flexibility here refers to both process and logistics aspects. Process flexibility concerns the number of product types that can be manufactured in each production site (supplier or assembler); logistics flexibility concerns the possibility of shifting the assignment of an item (component or final product) to different sites of an SC stage. An optimisation model provides the best operations planning performance (lost sales) of a given SC configuration, subject to different values of capacity uncertainty and both volume and mix demand variability. Based on these results, a cost analysis of the different SC configurations is provided, aimed at finding critical ratios among process flexibility, logistics flexibility and lost sale costs, which may drive managers to make appropriate decisions for SC management.

Complex Systems Methodologies for Behavioural Research in Operations Management: NK Fitness Landscape

From a methodology point of view, most Behavioural Operations Management (BOM) studies have employed experiments. However, no reason, either theoretical or practical, exists to limit BOM to experimental research. In this chapter, I discuss my conviction that methodologies coming from complexity science have the proper characteristics to be successfully applied in BOM research, since real operating systems, such as processes, factories, organisations and supply chains, are complex adaptive systems (CASs) where human behaviour is the central driver. Moving from this assumption, I suggest applying complexity science in order to study operating systems in diverse OM contexts and I also propose research questions coherent with a complexity science approach. They concern how operating systems behave, adapt and show new orders in terms of processes, structures and performances. Then, I suggest the adoption of a simulation tool to study CASs to develop BOM models, i.e. NK fitness landscape. After reviewing the methodology and its main applications in organisational contexts, I propose how different OM contexts can be modelled and how behavioural factors both at an individual and at a population level might be operationalised through the methodology proposed. Finally, I formulate research questions that might be addressed by applying NK fitness landscape.

Interpreting the role of proximity on Industrial District competitiveness using a complexity science-based view and Systems Dynamics simulation

The paper investigates how proximity affects Industrial District competitiveness. We adopt the complexity theory by analyzing the influence of the proximity on the Industrial District adaptive capacity. Our argument in fact is that the more adaptive the Industrial District, the more the competitive success. Based on the complexity theory, we identify the structural features that allow Industrial District adaptation and their best values. Then, by developing a computational model based on the Systems Dynamics, we conduct a simulation analysis to evaluate the influence of proximity on the values of Industrial District structural features affecting its adaptive capacity. Results show that too much proximity is detrimental for the Industrial District competitiveness.