Cyber-Risk Analysis and Security in Supply Chain Management Based on ICT Systems

Purpose: The purpose of this case study is to develop and framework supply chain characteristics and risk mitigation strategies in the context of biodiesel downstream supply chain.Design/methodology/approach: This study employs an expert interview-based approach as a qualitative approach with a multi-perspectives view.Findings: There are vary strategies among perspectives, such as perspectives of organization and business types, stakeholder types, times and methods. These also shows that business strategy of collaborative, coordinative, and cooperative arise as alternative strategies for each perspective and each level of stakeholder. Those business strategies may apply in a vary operation strategies which linking through an energy security framework element as company’s competitive priorities.Research limitations/implications: The research scope includes only a certain area of the country’s territory and the target company’s supply chain areas of activity. The research method includes only internal stakeholders and experts as respondents and data sources. The level of analysis was only at corporate level in the corporate case study context. The research also targets only a downstream activities of biodiesel supply chain context. The interview-based approach as a qualitative approach faces some subjectivity challenges among respondents.Practical implications: The research result provides some positive implications for business practice, includes how to minimize the impact of supply chain risk on company’s business activities and performance, how supply chain experts and practitioners used risk mitigation practices, how to formulate strategic plans to minimize the impact of supply chain risk and enhance the effectivity and sustainability of the supply chain activities.Social implications: The implication for business practice was that company’s leaders implemented supply chain risk mitigation strategies that provide positive impacts on the more valuable relationship among supply chain actors and stakeholders.Originality/value: The first, is an activities areas and operation schemes-based of biodiesel supply chain point of view. The second, is a multi-perspectives-based biodiesel supply chain characteristics framework. The third, is an energy security framework-based biodiesel risk mitigation strategies framework.

PurposeHealthcare organizations are placing greater emphasis on enhancing supply chain performance to cut costs and boost operational efficiency. Despite the growth of literature on the relevance of contemporary supply chain technologies in enhancing supply chain performance, it is still unclear how healthcare organizations could leverage supply chain analytics through supply chain strategies to improve healthcare supply chain performance (HSCP). This paper attempts to bridge this gap by examining how enhanced HSCP could be achieved through supply chain analytics (SCA) as well as building responsive, resilient, and reconfiguration (3Rs) SCs. The paper further assessed the moderating role of desorptive capacity between SCA and HSCP.Design/methodology/approachThe practice-based view motivated the study. The model underwent validation using primary data collected from 374 managers of healthcare facilities in Ghana. Data analysis was conducted using a structural equation model.FindingsThe findings revealed that SCA significantly drives HSCP, supply chain resilience, responsiveness, and reconfiguration. The findings further showed that the three supply chain strategies (supply chain resilience, responsiveness, and reconfiguration) aid in channeling the effect of SCA to drive enhanced HSCP. Finally, we also observed high levels of desorptive capacity amplifying SCA’s impact on HSCP.Practical implicationsThis paper makes important contributions to both literature and practice by empirically demonstrating how the effect of SCA can be channeled through supply chain strategies (supply chain resilience, responsiveness, and reconfiguration) to enhance SCP at varying levels of desorptive capacity. Practically, our study has demonstrated that SCA is not a “silver bullet” and that it must be integrated with supply chain strategies to reap the full benefits.Originality/valueTo the best of our knowledge, this paper is among the few attempts to empirically validate the relevance of supply chain analytics from the healthcare perspective. Moreover, the novelty of this paper demonstrates the coverage of the newfound mechanism, where supply chain resilience, responsiveness, and reconfiguration mediate and desorptive capacity moderate SCA and HSCP relationship. Finally, the paper questions the use of traditional organizational theories (RBV and DCT) and validates the applicability of a practice-based view as an alternative theoretical lens that could offer more nuanced insights into the unique characteristics and challenges of healthcare supply chains.

Uncertainty and supply chain risk: The moderating role of supply chain flexibility in risk mitigation

Driven by fierce global competition, reducing costs while improving customer services by effective supply chain logistics management has become one main concern of most companies. This has created needs for modelling, performance analysis and optimisation tools that can help these companies to improve their logistics networks and operations. In this paper, the advantages of Petri nets as modelling and analysis tools for logistics systems are demonstrated, the recent developments of using Petri net based approaches for modelling, performance analysis, and optimisation of supply chains are reviewed, and future research directions for this important area are explored.

Nowadays business world requires more collaboration along supply chains in order to sustain production, optimize cost structure and speed up delivery. The growing inter twist among supply chainpartners causesnumerous risks whose impacting magnitude and scope are larger than ever before. The risks are not just limited in operations any more but further extend to relationships related aspects. It demonstrates new features that we think should deserve careful investigation. Although supply chain risks and partnerships are great concerns in both academics and industry, the existing literature seldom links them together, and it echoesinadequately upon the new situations happened in the past decade. As such, this research project is made with ambition to improve the understanding of risks in the context of today’s collaborative supply chains where interorganizational linkages are strengthened through partnerships.
\nThe research project contains three studies. They constitute an integrated series subjected to the overall research objective. The first study starts with concept building and fundamental notion rethinking of risks in supply chains. We conceptualize supply chain risks into a general form in which risks are integrated into a system capable to reflect the correlation and chain effect among them. Through analytical inference and simulation it is found that the level of collaboration of partners contributes to the resilience of supply chains. It implies that partnerships can positively affect the integration of supply chain risk system, thus enhancing supply chain operations by improved ability in fault recovery.In the following two studies we are concerned with the impacts of different types of risks in supply chains upon companies’ operational performance given the effect of partnerships. The pre risk event effect and post risk event effect of partnerships are investigated in study two and study three respectively. The second study uses survey to research practitioners’ view on the role of supply chain risks and partnerships in supply chain performance. The validated sample of 162 responses reveals that the depth of partnerships imposes the most significant impact on supply chain risks and the collaboration risks are considered the top risk type that can influence supply chain performance to the most extent. The third study focuses on the negative consequence brought to the companies by supply chain risks when they have been realized. Event study is employed as the research methodology to identify and analyzethe effects of different risks under different partnerships. With respect to impact analysis, relationship risks are shown to cause the most significant loss to firm value. Moreover, deeper partnerships are found to have more negative impact on firm value resulted from relationship risks.
\nThis research project could contribute to the supply chain risk management literature by furthering the understanding of the important role of supply chain risks in enhancing the company’svalue and operational performance. The findings uncover the crucialrelationship between partnerships and supply chain risks, offering a novel view from a risk perspective to explain why an increasing number of supply chain companies are consciously engaged in partnerships nowadays. They may confer academicians and industrial practitioners with some new insights for risk management in supply chains and encouragefuture research in this area.

The beef and red meat sector in Australia is undergoing rapid change because of globalization, a highly competitive beef and red meat market (local and export). Risk management in the Australian beef and red meat supply chain has become increasingly important as companies both large and small seek to extend their global reach. It is important to manage these supply chain risks. The purpose of the conceptual paper is to present a framework for managing supply chain risk in the Australian beef and red meat industry. The supply chain risk management strategy is critical and significant to strategically support the supply chain and business success in the long run. However, little research has been conducted in the industry so far. Based on the resource-based view (RBV) approach, the firms’ capability is considered as effective tools for mitigating the supply chain risk in the real operational environment. The paper identified major types of supply chain risks in the red meat industry. The conceptual framework focuses on the relationships among the firms’ capabilities and supply chain risks. This provides insights into the supply chain risk management. Although, the study focuses on the Australian red meat industry, the proposed framework can be validated with an empirical work in different sectors. Moreover, this paper contributes to the supply chain risk management literature.

This research aims to identify, measure and analyse the operational risk in supply chain of milkfish at Semarang. The supply chain activities emphasize on cooperation between parties to reduce risks in all stage of supply chain. Risk event occur are the return of fish to suppliers due to the poor quality, damaged product during the production process, and customer complaints due to improper order services. These problems result on out of stock of fresh fish, low customer satisfaction, and financial loss for the fish processing industries and distributors. Therefore, it is important to identify, measure and analyse the risks that probably occur in the supply chain from harvest area to end customer. The house of risk method used to analyse the supply chain risk and Supply Chain Operation Reference (SCOR) approach used to divided the business process into 5 main processes i.e., plan, source, make, deliver and return. The data collection was done by deep interview and spread questionnaires to industries manager and staff. The risk identification result shows that 7 risk events occur in the production process and 8 risk events in delivery process. These two processes have highest risk event number. The highest risk severity is found on Chlorine contaminated products. Based on severity value, some recommendation was formulated to reduce the impact of occurred risks to increase the supply chain resilience.

How do supply chain leaders know when to take costly risk mitigating actions to recover from the impact of a natural event (ie. a hurricane or earthquake) and when can they simply take caution, but no action? Course Overview: Managing global supply chains can be a risky business. The race for leaner supply chains has placed supply chain sites and suppliers in some unstable regions of the world. Events ranging from major hurricanes to social unrest and epidemics, threaten to disrupt the delivery of products and services. Risk Insights is a threat visualization service which uses the power of Watson to help supply chain leaders mitigate risk. Risk Insights utilizes news, weather event and social media data using Watson technologies to delivers new insights to IBM Risk Analysts on Bluemix. Data is ingested from dozens of real time reports ranging from the TWC to Twitter feeds from the National Hurricane Center. The trajectory of each named storm is monitored and displayed on Risk Insights. The storm track is supplemented with hourly analyzed news about the climatic event as it occurs. Risk analysts get the latest view of typhoons and hurricanes and are alerted when these intersect with their supply base. Objectives: Automated storm tracking, visualization, and risk assessments speed decision-making to minimize impact Automated monitoring of impactful news events and social media feeds Geospatial visualization of internal and external operations and supply chain locations Extendable to other risk events, for example, strikes, conflicts, geo-political events, epidemics, and natural / man-made disasters Risk mitigation workflow based on analytics Share best practices for developing and deploying an supply chain cognitive service About the Presenters: Tom Ward is currently the IBM Enterprise Services Cloud and Cognitive strategist. He has led supply chain cloud projects over the past six years and for the past three years, Tom has led Watson applications for the Supply Chain. He has been a featured supply chain conference speaker and published author in Forbes, Supply Chain Management Review, AME, ASQ and APICS. Tom has a Master's degree in EE from RPI. Rahul Nahar is the IBM Enterprise Services Analytics, Architecture & Strategy Senior Technical Staff Member. In his current role Rahul leads the development of Analytics and Cognitive Solutions for Enterprise Services. Rahul has been leading the effort to leverage Watson API's and Solutions in Account Receivables Collections, Supply Chain Risk Management (Risk Insights), Quality and Client Satisfaction. Rahul has a broad experience in developing and implementing Analytic Solutions for across the Supply Chain. Rahul has a Master's in ME from UVa. On Demand Webinar

The emergence of Supply Chains (SCs) is an outcome of the recent advances in logistics and information technology. SCs are complex networks interconnecting different independent manufacturing and logistics companies integrated with material, information and financial flows (Viswanadham & Raghavan, 2000). Typically, SC management decisions are classified into three hierarchical levels according to the time horizon of decisions: strategic (longterm), tactical (medium-term), and operational (short-term, real-time) (Chopra & Meindl, 2001; Shapiro, 2001). Accordingly, different models have to be defined at each level of the decision hierarchy to describe the multiple aspects of the SC. While the development of formal models for SC design at strategic and tactical levels was addressed in the related literature (Dotoli et al., 2005; Dotoli et al., 2006; Gaonkar & Viswanadham, 2001; Luo et al., 2001; Vidal & Goetschalckx, 1997; Viswanadham & Gaonkar, 2003), research efforts are lagging behind in the subject of modeling and analyzing the SC operational performance. At the operational level, SCs can be viewed as Discrete Event Dynamical Systems (DEDSs), whose dynamics depends on the interaction of discrete events, such as customer demands, departure of parts or products from entities, arrival of transporters at facilities, start of assembly operations at manufacturers, arrival of finished goods at customers etc (Viswanadham & Raghavan, 2000). Among the available DEDS analytical formalisms, Petri Nets (PNs) may be singled out as a graphical and mathematical technique to model systems concurrency and synchronization. Moreover, PNs are able to capture precedence relations and structural interactions and may be executed in standard engineering software packages simply implementing their dynamics via the corresponding matrix equations. However, most SC models based on PNs proposed in the related literature share the limitation that products are modelled by means of discrete quantities, called tokens (Desrochers et al., 2005; Dotoli & Fanti, 2005; Elmahi et al., 2003; Viswanadham & Raghavan, 2000; Von Mevius & Pibernik, 2004; Wu & O’Grady, 2005). This assumption is not realistic in large systems with a huge amount of material flow: the state space of the SC model generally turns out to be excessively large, so that inconveniences in the simulation and performance optimization often arise, leading to large computational efforts. Since SCs are DEDSs whose number of reachable states is very large, PN formalisms using fluid approximations provide an

: The purpose of this research was to improve defense supply chain risk management processes through better intelligence integration. To this end, this research sought to capture the present state of academic and Department of Defense (DoD) thought regarding supply chain resiliency and risk management through an extensive review of current academic and DoD literature regarding supply chain risk management and intelligence doctrine. This review established the importance of supply chain risk analysis to ensuring supply chain resiliency and identified a significant gap in DoD acquisitions policy and guidance regarding intelligence support to supply chain risk analysis. This research culminated in the development of a methodology for intelligence professionals to use to support supply chain risk management processes. Specifically, this paper provides analysts a methodology to provide intelligence support to risk analysis for United States Air Force (USAF) weapon system supply chains based on the Intelligence Preparation of the Operational Environment process established in Joint doctrine. While the methodology developed in this paper is targeted at USAF weapon system supply chains, it is readily adaptable to other DoD acquisitions program supply chains. Additionally, this paper provides recommendations for future research to further improve intelligence support to supply chain risk management.

The supply chain is an extremely important and complex system, which is widely related to the social system and the management system. The hierarchical scheduling and production planning of a dynamic supply chain can enable enterprises in the supply chain to obtain, and maintain, stable and lasting competitive advantages; thus, improving the overall competitiveness of the supply chain. Simultaneously, research on supply chains is also a hotspot in system engineering. At present, research on complex supply chain systems with dual channels is insufficient, and analysis of dynamic supply chains with supply failure of goods is rare. In the epidemic era, dynamic supply chain management was affected by the epidemic and became a very challenging topic. The control of the supply chain system under the impact of an epidemic situation is particularly important. This paper focused on H∞ the fault-tolerant control of a complex supply chain system with dual channels. First, from the perspective of engineering practice and green production, we established a new green supply chain model. This supply chain model includes the dual-channel supply of goods and also considers the supply failure of goods. At the same time, production delay and supply delay are also considered in this model. Second, a supply scheduling scheme was designed through cybernetics to ensure the stability of a supply chain with dual channels under supply failure of goods, and we completed supply chain management. Finally, the effectiveness of our results was verified by specific Chinese enterprise data.

This study aims to analyze the effect of Supply Chain Integration and the Quality of Accounting Information Systems on Operational Performance with Supply Chain Risk as a mediating variable. The study uses a quantitative approach with an explanatory design. The study population is MSMEs in the food & beverage sector in one of the districts in Medan City. Sampling using purposive sampling technique and obtained 42 respondents with questionnaires eligible to be tested. The research data is primary data collected through questionnaire distribution and analyzed using multiple linear regression techniques based on a mediation model or MRA, with direct and indirect effects testing using the Sobel test. The results revealed that simultaneously the variables Supply Chain Integration and the Quality of Accounting Information Systems affect Operational Performance, but partially only the Supply Chain Integration variable affects Operational Performance. The mediation test showed that Supply Chain Integration and the Quality of Accounting Information Systems have a negative effect on Supply Chain Risk. This indicates that increasing Supply Chain Integration and the Quality of Accounting Information Systems can reduce exposure to Supply Chain Risk. However, Supply Chain Risk cannot mediate the relationship between Supply Chain Integration and the Quality of Accounting Information Systems on Operational Performance. These findings demonstrate that operational performance in MSMEs is improved more through the influence of supply chain integration and the quality of accounting information systems than through supply chain risk mitigation mechanisms.

The domestic biofuel program of Indonesia has been facing number of dynamics and challenges, such as: low production, uncertainty of feedstock availability, low realized consumption, price fluctuation and less competitive, unfit and viewer infrastructure, imbalance distribution. This study aims to map and analyze supply chain risks of biodiesel downstream business and offers a practical implementation of Failure Mode and Effect Analysis (FMEA) in the supply chain risk analysis. It employs a qualitative approach. A semi-structured surveys and interviews applied in data collection. The research level of analysis is at corporate level. The study result shows that there are three highest risks arise related to regulation related risk, product arrival (delays) risk and transportation facilities risk with the Risk Priority Number (RPN) of 72 to 48 and the Risk Score Value (RSV) of 24 to 16. The result also shows that there is correlation between stakeholder types, locations and levels of information with their perception of biodiesel supply chain risk and risk priorities. The result may become a valuable input for developing such risk mitigation strategy to improve and enhance the effectivity and the sustainability of supply chain in both the company and the biodiesel industry.

In today’s competitive environment, managing the entire supply chain becomes a key factor for the successful business. However, the manufactured housing (MH) industry has mainly focused on manufacturing and quality improvements in the past years. It is important for the MH industry to extend its focus to the efficiency and effectiveness of the entire supply chain. In this paper, as a first step, current supply chain practices in the manufactured housing industry have been identified and analyzed along with the characteristics of customer, retailer, and manufacturer. This analysis assists the supply chain participants in planning new products and preparing for new consumer needs. As a result, the entire supply chain process was modeled and a conceptual supply chain model was developed. This conceptual supply chain model can be used for understanding the current supply chain relationship at the macro level as well as a framework for developing a supply chain management system for the manufactured housing in...

Yu, Y.; Xiong, W., and Cao, Y., 2015. A conceptual model of supply chain risk mitigation: The role of supply chain integration and organizational risk propensity. Supply chain risk management has drawn great attention from both researchers and practitioners in recent years. Economic globalization and the resultant complexity of the supply chain network plus the uncertainty of the environment makes risk and vulnerability a major challenge to related firms. This paper aims to establish a conceptual model for mitigating supply chain risk by introducing two variables named supply chain integration and organizational risk propensity. Based on extensive literature review, some major propositions are proposed including the following four aspects: supply chain risk is negatively related to supply chain integration; supply chain integration is positively related to company performance; organizational risk propensity moderates the relationship between supply chain risk and supply chain integration; the integrative model is moderated-mediation. The integrative model is theoretically valuable in further exploring the internal path and mechanism of the impact of supply chain risk on a firm's performance. The model is also practically useful in providing suggestions and references for supply chain risk management and supply chain integration. Finally, the future directions for empirical research are also presented.