ارزیابی ریسک در زنجیره تامین مرکب

Complexity and disintegration are emerging as major challenges in supply-chain risk management. It has become more difficult to identify risks as supply-chain operations have fallen into the hands of outside service providers, and are therefore less visible. The risks, their identification and impact depend on the position of the companies in the chain, and on the level of analysis they can carry out. In this paper we present preliminary research concepts and findings concerning the identification and analysis of risks in multimodal supply chains. Our research approach is holistic, and incorporates perspectives from different parts of the chain. The multimodal maritime supply chain in focus runs from the Gulf of Finland to the Finnish mainland. We map the process and the structure, and present a new framework for categorizing the risks in terms of their driver factors in order to assess the overall impact on the performance of the supply chain. Finally, we analyze the risk impacts in terms of delays in the chain by means of Monte-Carlo-based simulation.

Global supply chains are formed by a multitude of companies acting as part of a long and complex logistics system. The continuing disintegration and the specialization of operations have made the chains vulnerable to disturbances coming from both inside and outside the system. The visibility of operations outside the companies’ own functions has decreased, and with it the ability to identify risks threatening them and the whole supply chain. Harland et al. (2003) found that less than 50% of the risks were visible to the focal company in the supply chains they examined. The risks that are identified are typically related to the companies’ own functions. In most cases, in terms of business impact, risks of disruption are much greater than the operational risks (Tang, 2006). There is therefore a need for a broader view of the supply chain that would facilitate proper risks identification. Managers selecting a supply-chain-management strategy should first understand the sources of uncertainty and find the way of reducing the level that suits them best (Cucchiella and Gastaldi, 2006). Integrated and seamless logistics can play a crucial role in facilitating global supply-chain processes (Banomyong, 2005). Yet, in practice, greater integration increases dependency between companies and exposes them to more risks (Hallikas et al., 2004). Indeed, the increasing amount of risk in the supply chain is a current focus of interest in logistics (Minahan, 2005). According to Jüttner (2005), any approach to managing risks from such a perspective must have a broader scope than that of a single organization, and provide insights into how the key processes should operate across at least three organizations. Hence, in assessing supply-chain vulnerabilities companies need to identify the risks not only to their own operations but also to all other entities, as well as those caused by linkages between organizations. A disruption affecting an entity anywhere in the supply chain can have a direct effect on a corporation’s ability to continue operations, get finished goods to the market, and provide critical services to customers. For example, a ten-day shutdown of 29 US ports cost the US economy one to two billion dollars per day, which illustrates the effects that such disruptions can have (Park et al., 2008 and Jüttner, 2005). Multimodal container transportation is playing an increasingly important role in global supply chains and trade. Container transportation has expanded significantly over the last 10 years, and the trend shows no sign of slowing down. According to the World Trade Organization, the world’s container-shipping capacity tripled in the last decade (World Trade Organization, International Trade Statistics, 2010), which illustrates the significance of multimodal maritime supply chains as part of a global logistics system. Even though there have been several studies on supply-chain risk management, however, very few of them focus on the multimodal maritime supply chain. Given that supply risks, and further the likelihood of disruption, are emerging as a key challenge in supply-chain management, the ability to identify the parts of the chain that are more prone to disruption is becoming a critical first step in managing the frequency and impact of disruptions that may endanger the security of supply (Trkman and McCormack, 2009 and Singhal et al., 2009). The limited information sharing and collaboration that is typical in the supply chain limit the visibility of risks to some practitioners. There is thus a need to provide a more holistic view by studying the processes involved as an integrated system. The Gulf of Finland (GoF) is the most important transport route accommodating Finnish cargo flows. Finland’s major ports are on its shores, and are in a key position as far as security of supply is concerned. The risks affecting GoF supply chains could have a devastating effect on the downstream organizations, and furthermore endanger Finnish business life and the livelihood of the people. The sources and impacts of the risks should therefore be studied, and that is precisely where the contribution of this paper lies. The aim is to present an assessment of risks and their effects in a multimodal maritime supply chain. A case study was conducted, the purpose of which was to systematically analyze and evaluate the risks affecting a multimodal maritime supply chain between the Gulf of Finland and the Finnish mainland in terms of the nature of their impact. The study is based on literature focusing on risks and supply-chain risk management, and on the findings from interviews. Most of the research was carried out in three overlapping phases. The interviewees were identified and the interviews conducted in the first phase. The risk analysis comprising the second phase involved an expert group of researchers and practitioners in the field. In the final phase, the risk impact of time delay was evaluated by means of simulation in order to obtain a more in-depth perspective on the possible consequences. The paper continues with a literature review covering the key concepts of supply-chain risk management and multimodality. The following, empirical part of the study begins with a description of the operational area, the study methods, and the process of the case supply chain. The uncertainties are identified and assessed, and a risk analysis follows in which the simulation results illustrate the delay impact of the risks. The conclusions are presented and discussed in the final section.

This study broadens the perspective on risk management in multimodal maritime supply chains in considering both the needs of the supply chain and the security of supply to the end customers. The main objective was twofold: first, to identify and assess the risks affecting the cargo flows in the case multimodal maritime supply chain from the perspective of risk management, and secondly, to analyze the impact of the risks in terms of delay. A review of the current literature on maritime supply chains and supply-chain risk management gave a holistic understanding of the field. The empirical part of the research was carried out in two sequential but overlapping stages. Representatives of organizations comprising part of a supply chain originating in the Gulf of Finland and ending up on the Finnish mainland were interviewed in the first stage of the case study. These interviews were semi-structured and exploratory. The second stage involved mapping and evaluating the identified risks according to their outcomes in the supply chain. Thirdly, a simulation model was constructed based on the delay impact of the identified risks in order to investigate any variation in the distribution of possible supply-chain outcomes, their likelihood, and their subjective values (see e.g., March and Shapira, 1987). Given the background of the interviewees, neither the conceptual clarity of the risk nor the risk sources and drivers were taken into consideration; the interviewees rather responded with tales of cause and effect. In this respect the findings reflect those reported by Peck (2005) and Zsidisin (2003), who note that practitioners perceive risk as a multi-dimensional construct. The low-hierarchy trucking companies seemed only to have some idea about their functions in the supply chain and how any disruption would affect it. Their perspectives were typically narrow, single-functioned and logistics based, although there were significant individual differences (Skjøtt-Larsen et al., 2007). The risks imposed on different parts of a multimodal supply chain depend on numerous factors, and many of the practitioners thought their company’s business was somewhat different with regard to the other companies. Effective risk management clearly requires a holistic understanding. Increasing visibility and co-operation in the supply chain would improve the identification of risks and thus make them easier to manage. Some of the logistics operators who were interviewed had taken steps in this direction, but a lack of trust seemed to prevent more extensive co-operation and information sharing. The risks identified as the most severe, namely strikes, fire and ice conditions in winter, affected the whole chain and most parts of it, and co-operation would therefore be most beneficial in this context. The most significant source of risk seemed to relate to supply, as well as to the operational environment, and the main effect in most cases was a time delay: in other words, the greatest impact is on cargo that is time-sensitive. For companies applying proper risk management the ability to mitigate or respond to these risks could prove to be a key benefit in the intense competition of present-day logistics. The expected outcome of the vulnerability analysis is the top-down analysis of supply-chain risk drivers and their impact, and a more in depth investigation into the connection between risk exposure and supply-chain performance measures such as time. This paper connects both of these in exploring risks in a multimodal supply chain. Risk drivers and uncertainty in supply chains are often analyzed separately, but this study presents an integrated framework. Exposure in terms of likelihood and impact provides a solid structure on which to explore risks in different parts of the chain. Simulation with its inherent sensitivities sheds light on the drivers of risk and their impact on supply-chain performance. The delay impact was used to model risk exposure on the case supply chain in this study. However, it may be extremely difficult to obtain data for simulation applications, in which case expert opinions would be invaluable. We believe that this study provides valuable information for practitioners and researchers alike. It illustrates the value of a holistic view to actors in the supply chain attempting to assess the risks facing them. On the national or regional level it enhances understanding of such risks, their likelihood and consequences, which gives a good basis on which to prepare for and respond to them in order to ensure the security of supply. The viewpoint adopted and the methods used will enhance current research and arouse more discussion. The approaches to risk analysis adopted in the study rely on the expert knowledge of a few people and on subjective assessment. The case-study method therefore imposes limitations. The study also has limitations in terms of generalizability, given the size of the sample and the subjective nature of the data. There is thus a need for further empirical research employing a more extensive data set, or a comparative study involving some other geographical location. It would also be useful to analyze the financial and qualitative aspects of risk and its effects in the supply-chain context.