Supply Chain Resilience? Definition of concept and its formative elements.

The objective of this paper is to conceptualize Supply Chain Resilience (SCRes) and identify which supply chain capabilities can support the containment of disruptions and how these capabilities affect SCRes. Through a systematic and structured review of literature, this paper provides insights into the conceptualization and research methodological background of the SCM field. A total of one hundred and thirty four carefully selected refereed journal articles were systematically analyzed leading to the introduction of a novel definition for SCRes, which the authors view as the as “the ability to proactively plan and design the Supply Chain network for anticipating unexpected disruptive (negative) events, respond adaptively to disruptions while maintaining control over structure and function and transcending to a post-event robust state of operations, if possible, more favorable than the one prior to the event, thus gaining competitive advantage”. Finally, a critical examination of existing conceptual frameworks for understanding the relationships between the SCRes concept and its identified formative elements, is taking place.

Point-and-shoot: rapid quantitative detection methods for on-site food fraud analysis – moving out of the laboratory and into the food supply chain

Major food adulteration and contamination events occur with alarming regularity and are known to be episodic, with the question being not if but when another large-scale food safety/integrity incident will occur. Indeed, the challenges of maintaining food security are now internationally recognised. The ever increasing scale and complexity of food supply networks can lead to them becoming significantly more vulnerable to fraud and contamination, and potentially dysfunctional. This can make the task of deciding which analytical methods are more suitable to collect and analyse (bio)chemical data within complex food supply chains, at targeted points of vulnerability, that much more challenging. It is evident that those working within and associated with the food industry are seeking rapid, user-friendly methods to detect food fraud and contamination, and rapid/high-throughput screening methods for the analysis of food in general. In addition to being robust and reproducible, these methods should be portable and ideally handheld and/or remote sensor devices, that can be taken to or be positioned on/at-line at points of vulnerability along complex food supply networks and require a minimum amount of background training to acquire information rich data rapidly (ergo point-and-shoot). Here we briefly discuss a range of spectrometry and spectroscopy based approaches, many of which are commercially available, as well as other methods currently under development. We discuss a future perspective of how this range of detection methods in the growing sensor portfolio, along with developments in computational and information sciences such as predictive computing and the Internet of Things, will together form systems- and technology-based approaches that significantly reduce the areas of vulnerability to food crime within food supply chains. As food fraud is a problem of systems and therefore requires systems level solutions and thinking.

Supply Chain Adaptation of Finnish Companies in Chinese Institutional Environment

Within the last few decades of operations and supply chain management, the field has seen the rise of so called best practices, methods that will help supply chains obtain their business goals and gain a competitive edge. These methods were thought to be universal. This however is not always the case, as the surrounding business environment could have a significant impact on what will be effective in gaining competitive edge. Contingency theory states that the success of a supply chain is determined by both internal capabilities, as well as external context aligning. This creates a strategic fit, which is a major determinant of success. In order for supply chains to reach this strategic fit, they must adapt. As China has seen rapid growth and over the last few decades become one of the major economies of the world, Western companies have tried to establish themselves there, only to find that the Chinese market is extremely difficult to operate in. The aim of this thesis was to investigate from contingency theory perspective, what are the institutional factors that affect supply chain management of Finnish companies operating in China, and how do Finnish companies adapt their supply chains to better fit the Chinese institutional environment. A theoretical model was created for this thesis, in which supply chains possess resources, which can be combined in a meaningful manner to create capabilities. Both resources and capabilities are affected by the surrounding institutional environment, which forces supply chains to adapt in order to find a better strategic fit. A total of six Finnish managers from three large and three small companies operating in China were interviewed. The results indicated that the Chinese business environment is significantly different, than that of Finland or Western countries in general. Three institutional factors were identified: Confucian though, fast-paced business environment, and managing labor force. These three institutional factors made the relationship and delivery capabilities particularly important, as well as human resources, reputation, physical resources and technological resources. In conclusion, it was discovered that the Chinese institutional environment is heavily affected by Confucian thought, as well as the rapid market growth. These are the two most important institutional factors that shape the Chinese market. If supply chains wish to be successful in China, adaptation regarding these two institutional factors should yield good results.

Development and Application of Predictive Models for Survival, Growth, and Death of Enteric Pathogens in Leafy Greens Supply Chain

Leafy greens are essential part of a healthy diet. Because of their health benefits, production and consumption of leafy greens has increased considerably in the U.S. in the last few decades. However, leafy greens are also associated with a large number of foodborne disease outbreaks in the last few years. The overall goal of this dissertation was to use the current knowledge of predictive models and available data to understand the growth, survival, and death of enteric pathogens in leafy greens at pre- and post-harvest levels. Temperature plays a major role in the growth and death of bacteria in foods. A growth-death model was developed for Salmonella and Listeria monocytogenes in leafy greens for varying temperature conditions typically encountered during supply chain. The developed growth-death models were validated using experimental dynamic time-temperature profiles available in the literature. Furthermore, these growth-death models for Salmonella and Listeria monocytogenes and a similar model for E. coli O157:H7 were used to predict the growth of these pathogens in leafy greens during transportation without temperature control. Refrigeration of leafy greens meets the purposes of increasing their shelf-life and mitigating the bacterial growth, but at the same time, storage of foods at lower temperature increases the storage cost. Nonlinear programming was used to optimize the storage temperature of leafy greens during supply chain while minimizing the storage cost and maintaining the desired levels of sensory quality and microbial safety. Most of the outbreaks associated with consumption of leafy greens contaminated with E. coli O157:H7 have occurred during July-November in the U.S. A dynamic system model consisting of subsystems and inputs (soil, irrigation, cattle, wildlife, and rainfall) simulating a farm in a major leafy greens producing area in California was developed. The model was simulated incorporating the events of planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. The predictions of this system model are in agreement with the seasonality of outbreaks. This dissertation utilized the growth, survival, and death models of enteric pathogens in leafy greens during production and supply chain.

Supply Chain Adaptation of Finnish Companies in Chinese Institutional Environment

Within the last few decades of operations and supply chain management, the field has seen the rise of so called best practices, methods that will help supply chains obtain their business goals and gain a competitive edge. These methods were thought to be universal. This however is not always the case, as the surrounding business environment could have a significant impact on what will be effective in gaining competitive edge. Contingency theory states that the success of a supply chain is determined by both internal capabilities, as well as external context aligning. This creates a strategic fit, which is a major determinant of success. In order for supply chains to reach this strategic fit, they must adapt. As China has seen rapid growth and over the last few decades become one of the major economies of the world, Western companies have tried to establish themselves there, only to find that the Chinese market is extremely difficult to operate in. The aim of this thesis was to investigate from contingency theory perspective, what are the institutional factors that affect supply chain management of Finnish companies operating in China, and how do Finnish companies adapt their supply chains to better fit the Chinese institutional environment. A theoretical model was created for this thesis, in which supply chains possess resources, which can be combined in a meaningful manner to create capabilities. Both resources and capabilities are affected by the surrounding institutional environment, which forces supply chains to adapt in order to find a better strategic fit. A total of six Finnish managers from three large and three small companies operating in China were interviewed. The results indicated that the Chinese business environment is significantly different, than that of Finland or Western countries in general. Three institutional factors were identified: Confucian though, fast-paced business environment, and managing labor force. These three institutional factors made the relationship and delivery capabilities particularly important, as well as human resources, reputation, physical resources and technological resources. In conclusion, it was discovered that the Chinese institutional environment is heavily affected by Confucian thought, as well as the rapid market growth. These are the two most important institutional factors that shape the Chinese market. If supply chains wish to be successful in China, adaptation regarding these two institutional factors should yield good results.

Green supply chain management practices and firm performance: evidence from Finland

In order to address the increasing stakeholder requirements for environmentally sustainable products and processes, firms often need the participation of their supply chain partners. Green supply chain management has emerged as a set of managerial practices that integrate environmental issues into supply chain management. If implemented successfully, green supply chain management can be a way to achieve competitive advantage while enhancing the environmental sustainability of the firm. The overall purpose of this dissertation is to contribute to the discussion on green supply chain management practices from the perspective of their drivers and performance implications. The theoretical background arises from the literature on competitive strategy, firm performance and green supply chain management. The research questions are addressed by analysing firm-level data from manufacturing, trading and logistics firms operating in Finland. The empirical data comes from two consecutive Finland State of Logistics surveys in 2012 and 2014, combined with financial reporting data from external databases. The data is analysed with multiple statistical methods. First, the thesis contributes to the discussion of the drivers of GSCM practices. To enhance the understanding of the relationship between competitive strategy and GSCM practices, a conceptual tool to describe generic competitive strategy approaches was developed. The findings suggest that firms pursuing marketing differentiation are more likely to be able to compete by having only small environmental effects and by adopting a more advanced form of external green supply chain management, such as a combination of strong environmental collaboration and the increased environmental monitoring of suppliers. Furthermore, customer requirements for environmental sustainability are found to be an important driver in the implementation of internal GSCM practices. Firms can respond to this customer pressure by passing environmental requirements on to their suppliers, either through environmental collaboration or environmental monitoring. Second, this thesis adds value to the existing literature on the effects of green supply chain management practices on firm performance. The thesis provides support for the idea that there is a positive relationship between GSCM practices and firm performance and enhances the understanding of how different types of GSCM practices are related to 1) financial, 2) operational and 3) environmental performance in manufacturing and logistics. The empirical results suggest that while internal GSCM practices have the strongest effect on environmentalperformance, environmental collaboration with customers seems to be the most effective way to improve financial performance. In terms of operational performance, the findings were more mixed, suggesting that the operational performance of firms is more likely to be affected by firm characteristics than by the choices they make regarding their environmental collaboration. This thesis is also one of the first attempts to empirically analyse the relationship between GSCM practices and performance among logistics service providers. The findings also have managerial relevance. Management, especially in manufacturing and logistics industries, may benefit by gaining knowledge about which types of GSCM practice could provide the largest benefits in terms of different performance dimensions. This thesis also has implications for policy-makers and regulators regarding how to promote environmentally friendly activities among 1) manufacturing; 2) trading; and 3) logistics firms.

Model predictive control applied to a supply chain management problem

Supply chains are ubiquitous in any commercial delivery systems. The exchange of goods and services, from different supply points to distinct destinations scattered along a given geographical area, requires the management of stocks and vehicles fleets in order to minimize costs while maintaining good quality services. Even if the operating conditions remain constant over a given time horizon, managing a supply chain is a very complex task. Its complexity increases exponentially with both the number of network nodes and the dynamical operational changes. Moreover, the management system must be adaptive in order to easily cope with several disturbances such as machinery and vehicles breakdowns or changes in demand. This work proposes the use of a model predictive control paradigm in order to tackle the above referred issues. The obtained simulation results suggest that this strategy promotes an easy tasks rescheduling in case of disturbances or anticipated changes in operating conditions. © Springer International Publishing Switzerland 2017

INTERACTIVE EFFECT OF FIXED TIME ORDER STRATEGIES WITHIN A SUPPLY CHAIN ON ACTUAL IN-STOCK PROBABILITIES

This report mainly deals with the interactive effect of different in-stock probabilities used by every individual in a supply chain. Based on a simulation for 10,000 weeks, the effects of varying in-stock probabilities are observed. Based on these observations, an individual in a supply chain can take counter measures in order to avoid stock out chances hence maintaining profits.

Design and management of a supply chain: a joint location-inventory problem under uncertainty (Part A)

In this paper, a joint location-inventory model is proposed that simultaneously optimises strategic supply chain design decisions such as facility location and customer allocation to facilities, and tactical-operational inventory management and production scheduling decisions. All this is analysed in a context of demand uncertainty and supply uncertainty. While demand uncertainty stems from potential fluctuations in customer demands over time, supply-side uncertainty is associated with the risk of “disruption” to which facilities may be subject. The latter is caused by external factors such as natural disasters, strikes, changes of ownership and information technology security incidents. The proposed model is formulated as a non-linear mixed integer programming problem to minimise the expected total cost, which includes four basic cost items: the fixed cost of locating facilities at candidate sites, the cost of transport from facilities to customers, the cost of working inventory, and the cost of safety stock. Next, since the optimisation problem is very complex and the number of evaluable instances is very low, a "matheuristic" solution is presented. This approach has a twofold objective: on the one hand, it considers a larger number of facilities and customers within the network in order to reproduce a supply chain configuration that more closely reflects a real-world context; on the other hand, it serves to generate a starting solution and perform a series of iterations to try to improve it. Thanks to this algorithm, it was possible to obtain a solution characterised by a lower total system cost than that observed for the initial solution. The study concludes with some reflections and the description of possible future insights.

Design and management of a supply chain: a joint location-inventory problem under uncertainty (Part B)

In recent years, global supply chains have increasingly suffered from reliability issues due to various external and difficult to-manage events. The following paper aims to build an integrated approach for the design of a Supply Chain under the risk of disruption and demand fluctuation. The study is divided in two parts: a mathematical optimization model, to identify the optimal design and assignments customer-facility, and a discrete-events simulation of the resulting network. The first one describes a model in which plant location decisions are influenced by variables such as distance to customers, investments needed to open plants and centralization phenomena that help contain the risk of demand variability (Risk Pooling). The entire model has been built with a proactive approach to manage the risk of disruptions assigning to each customer two types of open facilities: one that will serve it under normal conditions and a back-up facility, which comes into operation when the main facility has failed. The study is conducted on a relatively small number of instances due to the computational complexity, a matheuristic approach can be found in part A of the paper to evaluate the problem with a larger set of players. Once the network is built, a discrete events Supply Chain simulation (SCS) has been implemented to analyze the stock flow within the facilities warehouses, the actual impact of disruptions and the role of the back-up facilities which suffer a great stress on their inventory due to a large increase in demand caused by the disruptions. Therefore, simulation follows a reactive approach, in which customers are redistributed among facilities according to the interruptions that may occur in the system and to the assignments deriving from the design model. Lastly, the most important results of the study will be reported, analyzing the role of lead time in a reactive approach for the occurrence of disruptions and comparing the two models in terms of costs.

SUPPLY CHAIN RESILIENCE ANALYSIS: A BRAZILIAN AUTOMOTIVE CASE

Supply chain (SC) resilience and flexibility are important research topics receiving growing attention. However, the academic literature needs empirical studies on SC resilience capable of investigating the inter-organizational components of flexibility along different tiers. Therefore, this paper analyzes the main lack of flexibilities in three Brazilian automotive SCs that limit their resilience and therefore their capacity to better support and meet the demand changes in the marketplace. A multi-tier case study approach is adopted. Research findings identify lack of flexibilities in different tiers that inhibit the SC resilience as well as manufacturing and SC flexibilities that build SC resilience. The findings also highlight that the same SC may have the flexibility to be resilient for one of its products but not for another product, what sheds new lights on the academic literature. Finally, flexible SCs should be designed to increase SC resilience to cope with mishaps as significant demand changes.

An information model for lean, agile, resilient and green supply chain management

Dissertação para a obtenção de Grau de Mestre em Engenharia e Gestão Industrial