Quantifying Biopharma Alliance Fragility Using a Strategic Shock Risk Index (SSRI)

Gasification facility operators increasingly find it cost effective to outsource the supply of industrial gases, such as oxygen and nitrogen, to companies with a proven track record for designing and operating safe and reliable air separation unit (ASU) equipment. Air Products have built & operated many such ASU facilities in recent years and supplied industrial gases to customers directly by pipeline, with long term supply partnerships. Most of these ASU facilities are located within the customer boundary and are effectively integrated with customer gasification facilities. In addition to any risks that the ASU may pose to the customer's operations or personnel, there may be significant hazards originating with the customer's equipment or processes that pose a risk to the ASU personnel.Air Products developed an approach to assessing risks from neighboring facilities to the ASU equipment and personnel. The focus of this article is on the work process and sequence of steps used to develop a risk assessment and mitigation plan. Overall safety and risk management is improved by sharing hazard information between the industrial gas supplier and the customer, as well as developing a joint emergency response program. © 2019 American Institute of Chemical Engineers Process Saf Prog 38: e12032, 2019

In 2023 and 2024 and in partnership with Sage on Earth Consulting, BGC Engineering undertook a province-wide hazard exposure assessment for the provincial government of British Columbia, Canada. British Columbia spans approximately 940,000 square kilometers, stretching from the Pacific Ocean in the west to the Rocky Mountains in the east and from the Yukon border in the north to Washington State in the south. This expansive region faces a wide array of natural hazards, including flooding from mountain streams, tsunamis and shoreline erosion in coastal communities; earthquakes; landslides; debris flows; wildfires; drought; extreme heat and, increasingly, cascading hazards intensified by climate change. The goal of this project was to design and implement a geospatial workflow for assessing exposure of valued assets to hazards, delivered to a government agency in a standardized format that facilitated future updates and public governance over data sharing.  To accomplish this, BGC designed a data model and analysis pipeline that had sufficient performance for the iterative processing of large multi-hazard and asset datasets and that could be packaged for government agency development of a data portal. Within the data model, hazards were defined as areas which exceed hazard-specific intensity thresholds and/or annual probability of occurrence; these binary hazard data were the primary input to the analysis pipeline for each hazard type. The list of assets to be included in the analysis was determined through a series of consultations with project stakeholders aimed at identifying which assets are most important and what data was available consistently for the entire province. The result of the analysis was a set of exposure metrics representing population counts, monetary values of property exposed to hazards, and the lengths of transportation and utility networks within hazard zones summarized using a uniform 1.5 km x 1.5 km grid. These metrics were delivered along with documentation of the data model, the data, and the codebase for the analysis pipeline.The resulting analysis revealed spatial patterns of hazard exposure and provided actionable insights to support provincial-scale risk management. This work represents a foundational step in risk assessment and mitigation planning. It offers a means of prioritizing local-scale risk assessments within a jurisdiction as vast as British Columbia, enabling focused resource allocation and informed decision-making. Collaboration was central to the project's success. In association with Sage on Earth Consulting , BGC engaged with multiple stakeholders to refine inputs and validate assumptions, and ensure the outputs were accessible and meaningful. The results are designed for government-managed web access to both data inputs and analysis outputs, promoting transparency and usability for diverse audiences.This provincial hazard exposure assessment highlights the importance of integrating data,  geospatial analysis, stakeholder collaboration, and practical tools to address the complex challenges posed by natural hazards in British Columbia. The findings not only advance the understanding of hazard exposure but also lay the groundwork for more detailed, localized risk assessments and targeted mitigation efforts. 

The swelling behavior of clay-sulfate rocks poses significant challenges in geotechnical engineering due to complex hydro-mechanical and chemical interactions. This study introduces a hybrid framework combining finite element modeling (FEM) with machine learning (ML) to efficiently analyze and predict the nonlinear behavior of swelling processes. We generated synthetic datasets representing swelling phenomena at the Staufen site, Germany, using a coupled hydro-mechanical FEM simulation in OpenGeoSys. A parametric analysis was conducted to systematically vary critical parameters, including Young's modulus, permeability, maximum swelling pressure, and air entry pressure, to capture the inherent uncertainty and variability of swelling processes. A constrained CatBoost ML model was trained on the FEM outputs to predict porosity, saturation, and displacement under varying hydro-mechanical conditions. Results demonstrate strong alignment between the ML surrogate and FEM simulations, achieving high accuracy while significantly reducing computational demands. Sensitivity analysis indicated the dominance of swelling pressure and Young's modulus in influencing swelling-induced deformation, while Monte Carlo simulations quantified prediction uncertainties. This contribution discusses the potential of integrating FEM with ML for site-specific risk assessment and mitigation planning in geotechnical engineering.

Potential chemical impacts of CO2 leakage on underground source of drinking water assessed by quantitative risk analysis

Infrastructure projects that transform ecosystems and landscapes, such as hydropower developments, are essential for economic growth but pose significant socio-environmental challenges. Addressing these complexities requires advanced, dynamic management strategies. This study presents the Bayesian integrated risk mitigation model (BIRMM), a novel probabilistic framework designed to augment traditional environmental impact assessments. BIRMM enables comprehensive risk evaluation, scenario-based analysis, and mitigation planning, empowering stakeholders to make informed decisions throughout project lifecycles. BIRMM integrates socio-environmental and economic risks using a three-dimensional risk assessment approach grounded in a Bayesian belief network influence diagram. It provides a holistic view of risk interactions by capturing interdependencies across spatial, temporal, and magnitude dimensions. Through simulation of risk dynamics and adaptive evaluation of mitigation strategies, BIRMM offers actionable insights for resource allocation, enhancing project resilience, and minimizing socio-environmental disruptions. The framework was validated using the Balakot Hydropower Project in Pakistan. BIRMM successfully simulated proposed risks and assessed mitigation strategies under varying scenarios, demonstrating its reliability in navigating complex socio-environmental challenges. The case study highlighted its potential to support adaptive decision-making across all project phases. With its versatility and practical ease, BIRMM is particularly suited for large-scale energy, transportation, and urban development projects. By bridging gaps in traditional methodologies, BIRMM advances sustainable development practices, promotes equitable stakeholder outcomes, and establishes itself as an indispensable decision-support tool for modern infrastructure projects.

The study aimed to analyze the lived experiences of Agta men and women, including their gender roles, before, during, and after a natural calamity. Also, the study sought to examine the implications of breaking gender stereotypes in disaster preparedness, in the Agta community to develop gender-inclusive and culturally-sensitive disaster risk preparedness, mitigation, response, and recovery plans within the Agta community. Employing a case study research design, in-depth interviews with the Agta research participants, key informant interviews, naturalistic observation, and triangulation using the retrieved documents were conducted to gather relevant and significant data. Based on thematic analysis, the lived experiences of the Agta men and women before, during, and after the typhoon highlighted the traditional roles of men and women from disaster preparedness, risk reduction, and disaster recovery. Agta men typically performed the hard and critical jobs while women performed the household chores and took care of the children during calamities. However, during the observation, there were non-traditional roles that both Agta men and women have performed. The switching of gender roles between Agta men and women formed new schema to the minds of younger Agta regarding the roles of men and women, thus, embracing both traditional and untraditional gender roles.

Public participation in environmental management, and more specifically in hazard mitigation planning, has received much attention from scholars and practitioners. A shift in perspective now sees the public as a fundamental player in decision-making rather than simply as the final recipient of a policy decision. Including the public in hazard mitigation planning brings widespread benefits. First, communities gain awareness of the risks they live with, and thus, this is an opportunity to empower communities and improve their resilience. Second, supported by a collaborative participation process, emergency managers and planners can achieve the ultimate goal of strong mitigation plans. Although public participation is highly desired as an instrument to improve hazard mitigation planning, appropriate participation techniques are context dependent and some trade-offs exist in the process design (such as between representativeness and consensus building). Designing participation processes requires careful planning and an all-around consideration of the representativeness of stakeholders, timing, objectives, knowledge, and ultimately desired goals to achieve. Assessing participation also requires more consistent methods to facilitate policy learning from diverse experiences. New decision-support tools may be necessary to gain widespread participation from laypersons lacking technical knowledge of hazards and risks.

Academy of Management Annual Meeting Proceedings includes abstracts of all papers and symposia presented at the annual conference, plus 6-page abridged versions of the “Best Papers” accepted for inclusion in the program (approximately 10%). Papers published in the Proceedings are abridged because presenting papers at their full length could preclude subsequent journal publication. Please contact the author(s) directly for the full papers. ArticlesBUSINESS POLICY & STRATEGY Conference Symposia Abstracts.Published Online:30 Nov 2017https://doi.org/10.5465/ambpp.2005.18778372AboutSectionsPDF/EPUB ToolsDownload CitationsAdd to favoritesTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail AbstractThis section presents conference symposia abstracts related to business policy and strategy. Some of the symposium's include "Set-Theoretic Methods in Management and Strategy Research," that focuses on set-theory in management and strategy research; "Interdependence in Organizations, Circa 2005," about how interdependence in organizations affects people within that organization; and "Contractual Design of Technology Alliances," regarding how contract structures affect incentives.FiguresReferencesRelatedDetails Vol. 2005, No. 1 Permissions Metrics in the past 12 months History Published online 30 November 2017 Published in print 1 August 2005 InformationCopyright of Academy of Management Journal is the property of Academy of Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s express written permission. However, users may print, download, or email articles for individual use.KeywordsCONFERENCES & conventions -- AbstractsABSTRACTSSTRATEGIC alliances (Business)TECHNOLOGY -- AbstractsCOMPETITIVE advantageTECHNOLOGICAL innovations -- AbstractsMANAGEMENT science -- AbstractsSTRATEGIC alliances (Business) -- AbstractsPARTNERSHIP (Business) -- AbstractsMANAGEMENT research -- AbstractsDownload PDF

Pipeline interdiction and bridging in Nigeria: is a modification to the spatial connectivity matrix model required?

The Philippines have been challenged on livelihood, tourism, and economy due to flooding from consistent super typhoon occurrence throughout the year. The degree of the natural disaster ranges from constant rainfall to super typhoons which evidently led to the resilience of the people from the country. The objective of this study was to assess the factors affecting flood response effectiveness using artificial neural network. Adopted framework of integrating both protection motivation theory and theory of planned behavior has been applied with extension of government response and geographical location as deemed significant by related studies. Results have shown that perceived behavioral control, knowledge, and experience of flooding have promoted a positive perceived response to flooding. This in turn have affected other behavioral factors towards others in the country. With that, the government may want to consider the positive response of individuals when it comes to risk reduction and mitigation plans to reduce the aftermath of flooding from super typhoons. The findings of this study can be applied and extended by the government to prompt different mitigation plans and risk reduction practices for safety initiatives among individuals. Moreover, the framework and methodology of this study can be applied and extended to assess other behavioral and protection aspects among other countries.

Current research on landslide susceptibility modeling is often constrained by reliance on conventional topographic and geological features, potentially overlooking the discriminative power of surface material properties derived from multi-source remote sensing. This study aims to enhance the accuracy and reliability of susceptibility assessment by innovatively integrating spectral information and advanced machine learning techniques. Focusing on Chongqing, a landslide-prone mountainous region in China, this work conducted three innovative investigations: it (i) introduced 12 spectral features into the feature set; (ii) systematically evaluated spectral features contribution, redundancy, and set completeness through feature engineering; and (iii) implemented a comprehensive Stacking ensemble framework with multiple meta-learners and enhancement strategies (Bagging and Cross-Training) to identify the optimal integration scheme. The key results show that spectral features provided a significant positive impact, boosting the AUC of tree-based ensemble models by up to 4.52%. The optimal model, a Stacking ensemble with Bagging_XGBoost as the meta-learner, achieved a superior test AUC of 0.8611, outperforming all individual base learners. Furthermore, the spatial analysis revealed a concentration of high and very high susceptibility areas in Engineering Geological Zone I, which represents approximately 38% of such areas. This study provides a replicable framework for enhancing landslide susceptibility mapping through the integration of spectral features and ensemble learning, offering a scientific basis for targeted risk management and mitigation planning in complex mountainous terrains.

The COVID-19 pandemic has created uncertainty and disruptions in Supply Chain (SC), which has caused many researchers to re-study Supply Chain Risk Management (SCRM) to deal with risks due to the pandemic. Moreover, the direction of post-pandemic SCRM research is more toward Supply Chain Resilience (SCRes) which is the ability of a supply chain to prepare for disruptions and return to normalcy. Many researchers have started researching SCRes to carry out SC recovery measures. However, research on the quantification of SCRes is still rare and is an opportunity. One of the risk quantification methods in the SCRM field is the House of Risk (HoR). This study develops a SCRes assessment framework with the help of the HoR. HoR has two stages, namely: HoR1 for identifying the risks and HoR2 for mitigating the risks. In this study, one step was added, namely the level assessment stage of resilience. The resilience profile is calculated based on the risk map and mitigation plan. This study succeeded in providing a framework for assessing the level of resilience using the help of HoR. Meanwhile, only an illustrative case study is used. Our future research is on how to apply the proposed resilience assessment framework to a real case. Keywords: supply chain, risk management, supply chain resilience, house of risk, framework

The rapid urbanization in Denpasar City has intensified the challenges of municipal solid waste management, especially after the closure of the Suwung Final Disposal Site due to overcapacity. In response, the local government initiated the development of 3R-based Waste Processing Facilities (TPS 3R) at the community level, including the facility in Panjer Urban Village. However, the implementation of this community-based infrastructure project faces significant risks, ranging from technical and operational issues to social resistance.This study aims to analyze the risk management process in the development and operation of the TPS 3R Panjer, focusing on risk identification, assessment, classification, mitigation planning, and risk ownership allocation. The research employed a semi-quantitative descriptive method with a case study approach, supported by primary data from questionnaires and expert interviews. A total of 58 validated risks were assessed using a risk matrix adapted from Godfrey, combining frequency and consequence scores based on Likert scales.The results show that 67% of the identified risks fall into the "Unacceptable" and "Undesirable" categories. These risks are primarily related to community rejection, lack of technical capacity, and poor coordination. Risk mitigation strategies were formulated, and responsibilities were assigned among key stakeholders including the Public Works Department, Urban Village Office, Traditional Village leaders, Field Facilitator Team (FFT), and Community-Based Organization (CBO). The findings emphasize the importance of participatory planning, technical readiness, and structured risk control to minimize delays and cost overruns in TPS 3R implementation.

This chapter describes how the impacts of risk, or we may say risk exposure, are dependent upon the losses already occurred by the risk and probability to occur. There are various methods for estimating the risks and its impacts. The loss created by the threat can be reduced if the attacker does not have access to the system's objects or resources which are vulnerable to the risk. Attacker capabilities play the major role in the risk estimation and mitigation approach. Use of appropriate knowledge, skill and time to exploit the system or to create the threat comes under Attacker Capability. In this chapter, we will discuss how to include attacker capabilities when the risk estimation or mitigation plan is made. We will conclude the chapter with an appropriate study of various examples which indicate that impacts of risks can be minimised or reduced if we include the attacker capability while estimating the risk impacts and preparing the risk mitigation approach.

Industry incidents happened more frequently when various processes safety and Risk Management activities associated with various sub-processes are not followed, tracked and address on a timely basis. Having a robust tracking system of mitigations plan help to follow up to closure identified corrective actions and consequently this data can be of the valuable support for any incident investigation. Cabinda Gulf Oil Company Limited (CABGOC) has developed over the years several Process Safety (PS) metrics involving Management of Change (MOC) Process, Risk Management (RM) studies recommendations, Loss of Containment (LOC), Safety System Function Test, Control System Data, and open Non-Conformance Report (NCR) related to discrepant material conditions. This manuscript will describe how these metrics are put together, the process and how the teams involved are functioning around that. It also describes the process of closure and the functional authority of each metrics governance. The sufficient information on the data analysis, inference and the utilization of the historical trend for the continual improvement of the targets on the risk mitigation and RM planning are discussed. The key challenges of building the Organizational Capability (OC) to sustain the processes and Process Safety Information (PSI) validation for an effective RM studies will be highlighted in the article. These PS metrics created a multi-disciplinary teams working on different tasks and tracking the actions leading to work culture improvement. CABGOC Leadership Teams does field verification and validation through General Manager of Operations (GMO), audits, Facility Engineering (FE)/ Heath Environment Safety (HES) field audits, operations top 10 critical safeguard verification list to authenticate the importance of verification and action tracking. Some of the key risk reduction benefits of the PS metrics tracking and monitoring will be deliberated in the article. The article will provide key lesson learned for future industry practices. PS Metrics help to track, trend, and have dialog about our high risk areas.