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The single- and double-sided truncated normal distributions have been used in a wide range of engineering fields. However, most of the previous research works have focused primarily on the non-truncated population distributions. The authors present reference tables to estimate the values of density and cumulative density functions of truncated normal distribution for practitioners. Finally, the authors explain how to use the tables to estimate other properties, such as mean, median and variance. The purpose of this paper is to provide an efficient method to summarize tables, and furthermore, to provide readers with statistical tables on truncated standard normal distribution.

A new methodology is developed to summarize the tables with ordered values. The introduced method allows for the reduction of the number of pages required for such tables into a reasonable level by using linear interpolation. Moreover, it allows for the estimation of the required truncation values accurately with an error value less than 0.005.

The data in the tables can be summarized into a significantly reduced amount. The new summarized table can be designed for any number of pages and/or level of error wanted. However, with reducing the level of error, the number of pages increases and vice versa.

The value of this work is through two major points. First, all provided summarized tables in the literature are for single-sided and symmetry truncation cases. However, there is no attempt to summarize the tables of the asymmetry truncation normal distribution due to the requirement of huge number of pages. In this paper, the case of asymmetry truncation is included. Second, the methodology provided in this research can be used to summarize similar large tables.

The purpose of this paper is to review the extant literature on supply chain risk management (SCRM, including risk identification, assessment, treatment, and monitoring), developing a comprehensive definition and conceptual framework; to evaluate prior theory use; and to identify future research directions.

A systematic literature review of 354 articles (published 2000-2016) based on descriptive, thematic, and content analysis.

There has been a considerable focus on identifying risk types and proposing risk mitigation strategies. Research has emphasised organisational responses to supply chain risks and made only limited use of theory. Ten key future research directions are identified.

A broad, contemporary understanding of SCRM is provided; and a new, comprehensive definition is presented covering the process, pathway, and objectives of SCRM, leading to a conceptual framework. The research agenda guides future work towards maturation of the discipline.

Managers are encouraged to adopt a holistic approach to SCRM. Guidance is provided on how to select appropriate risk treatment actions according to the probability and impact of a risk.

The first review to consider theory use in SCRM research and to use four SCRM stages to structure the review.

The purpose of this paper is to explore the relationship between various risk management strategies and risk management practices in order to design and hence enact a suitable supply chain risk mitigation (RM) plan. Additionally, this study proposes a hierarchical framework to explain the mutual relationship between supply chain risk management (SCRM) practices and strategies by considering the underlying dimensions between them.

An amalgamation of systematic literature analysis (SLA) and correspondence analysis (CA) has been performed to develop the conceptual framework. A real-life case of Indian petroleum supply chain has been considered to validate and explain the proposed model.

The results reveal three underlying dimensions, which associate the relationship between RM strategies. They are, risk adaptability of SC managers with a variance of 34.71%, followed by resource capability of the firm and the degree of sophistication of RM practices, with variances of 27.72 and 20.35%, respectively. Risk avoidance strategy comprises of practices such as supplier evaluation, technology adaption, flexible process and information security. On the other extreme, the risk sharing strategy includes revenue sharing, insurance, collaboration, public–private partnership and so on as essential RM practices.

The study not only focuses on the distinction between RM strategies and practices, which were used interchangeably in the prior literature, but also provides an association between the same by exploring the underlying dimensions. These underlying dimensions perform a crucial role while developing a risk management plan. This study explicitly focuses on the RM step of SCRM process. Pre and post risk mitigation phases of SCRM process, such as risk assessment and risk monitoring, are beyond the scope of the current research.

The paper develops a framework for mapping various RM strategies with their corresponding practices by considering the Indian petroleum supply chain as a viable case study. Various theoretical and business implications are derived in the context of the developing country.

The purpose of this paper is twofold: to investigate the antecedents of resilience and to highlight the importance of resilience in achieving reconfiguration in supply chains.

This paper draws on literature on supply chain resilience and collects data from 253 companies in Qatar to understand the influence of the antecedents of supply chain resilience and the impact of resilience on reconfiguration using partial least squares structural equation modeling.

The findings show that antecedents like risk management culture, agility and collaboration positively affect the supply chain resilience. Further, the study establishes that companies can leverage their supply chain resilience to reconfigure supply chain in case of disruptions.

This study is important for supply chain managers in Qatar, as the country faced major disruption of supply chains in wake of the blockade imposed by its neighbors with which it had the only land route and maximum trade. The findings from this study should aid mangers in developing resilient supply chains.

This paper highlights the role of supply chain resilience in achieving reconfiguration. Further, novelty of the work reported in this paper lies in its context where supply chains recently faced actual disruptions.

One of the most important issues in supply chain (SC) management is the identification and management of the risk involved in it. The purpose of this paper is to propose a comprehensive model of supply chain risk management (SCRM) in the product life cycle (PLC) and the operational process cycle (OPC). To decrease the risks in a fuzzy environment, the model considers the organizational performance factors (OPF) and the risk operational practices (ROP).

Fuzzy analytic hierarchy process is used to determine the weights of the relationships between the PLC, OPC and OPF in the hierarchical structure of the decision problem. In addition, the fuzzy technique for order preference by similarity to ideal solution is employed to recognize the priority of ROPs in dealing with the performance factors. The integrated framework is evaluated using the case study of an automotive company in Iran.

The results demonstrated that the proposed model can be used to formulate an appropriate method for prioritizing defined alternatives to decrease risk and improve the organizational performance in SCRM under fuzzy conditions.

A major limitation of the study is that a few of the selected criteria for risk assessment are focused only on economic factors. Another limitation of the current study is related to the PLC, OPC and OPF being based on the work of Xia and Chen (2011).

The current study identified the more important stage in the PLC. More significant process in each stage of the PLC and weightier risk factors in each process of the OPC were determined. Some strategies for reducing risk in each stage of the PLC were presented. The best alternatives for reducing risks in SC were indicated.

It is worth mentioning that previous studies have not applied multiple criteria and alternatives to decrease the risks involved in the PLC and OPC parts of the SC under fuzzy conditions. However, it should be stated that some academics have used these techniques separately, in other specialized areas of the SC.

The purpose of this paper is to develop a decision support system (DSS) to assist supply chain (SC) risk managers to select a suitable risk management (RM) strategy and expedite the implementation of corresponding RM enablers. The relationship between RM strategies and RM enablers is explored by identifying the underlying factors between them, which is further used to build the DSS.

The DSS is built by integrating heterogeneous techniques. A systematic review approach is employed to explore both proactive and reactive RM enablers, and they are further mapped to various RM strategies by using correspondence analysis (CA). An in-depth interview is conducted to develop the rules for constructing the decision system. A rule-based fuzzy inference system (FIS) is utilized to counteract the uncertainty involved in the decision variables. The efficacy of the proposed DSS is demonstrated by considering two conjectural scenarios in the case of Indian petroleum SC (IPSC).

The results reveal three primary underlying factors between the risk mitigation strategies viz. SC managers' preparedness to face risk, organization's resource capability to deal with risk and the sophistication of the implementation of the RM enablers; with explained variances of 37%, 29% and 22%, respectively. Risk avoidance strategy comprises of RM enablers such as supplier evaluation, technology adaption, information security, etc. Whereas, the risk-sharing strategy includes revenue sharing, insurance, collaboration, public-private-partnership, etc. as essential RM enablers. The DSS recommends risk-mitigation and risk-sharing as effective RM strategies for the IPSC under the considered scenarios.

This paper develops a decision support framework for recommending an effective risk mitigation strategy and outranking the corresponding enablers. The study explicitly focuses on the risk mitigation step of the supply chain risk management (SCRM) process. Pre- and post-risk mitigation steps of the SCRM process, such as risk assessment and risk monitoring are beyond the scope of this research.

The operational procedure of the proposed DSS is explained by considering a real-life case of petroleum SC in the Indian scenario. The unique contributions of this study are presented as theoretical implications and managerial propositions in the context of a developing country.

According to the definitions presented for agility drivers, it can be mentioned that supply chain risk factors in terms of feature have very close roles to agility drivers and both of these factors impact the uncertainty in the environment. However, the risk factors with a wider domain are more comprehensive. This study aims to examine the effectiveness of risk as a driver on the organizational agility.

To conduct the research, after identification of influential risk factors of supply chain and indicators of organizational agility, questionnaires needed for the research were designed and after confirming their validity and reliability were distributed among the member of the sample. To assess the relationship between supply chain risk and the amount of organizational agility, data obtained from the questionnaires were analyzed using structural equation modeling technique.

The results of data analysis showed that supply chain risk factors could be considered as a driver affecting the organizational agility. In addition, in this study, supply chain risk factors were ranked using interpretive structural modeling. The presented comprehensive model indicated that based on causal relationships between risk factors, sovereign risk as the basis for model (three levels) and product and customer satisfaction risks as the output of the model (Level 1) were considered.

This paper fulfills an identified need to study how the risk factors as drivers of supply chain agility can have effect on agility.

The purpose of this paper is to identify various risk and sub-risk drivers that affect the supply chain (SC) performance and to propose a framework to quantify the overall SC risk index by considering the importance of each risk and sub-risk drivers and their mutual interactions.

A hybrid method based on decision-making trial and evaluation laboratory and analytical network process has been proposed to develop the risk quantification framework. A case study of Indian petroleum supply chain (PSC) has been illustrated to explain the proposed method.

The results of this study found that transportation/logistics (delivery system), quality of the petroleum products, crude supply, customer’s order and legal/political regulations are the most significant risk drivers of a typical PSC. It is also found that the Indian PSC possesses a risk score of 34 percent.

The quantification of risk in operational measure provides an unblemished representation of the overall SC risk. Unlike the existing financial measure, it takes complex subjective operational effectiveness like product quality, customer satisfaction, etc., into consideration. Identifying the high-prioritized risks helps the decision and policy makers to merely focus on the most prominent risk drivers, and reduce the impact of overall SC risk. Planning a risk mitigation strategy at a given level of risk is however beyond the scope of this research.

The paper develops a risk quantification framework in the context of a PSC.