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This paper aims to investigate how supply chain risks can be identified in both collaborative and adversarial buyer–supplier relationships (BSRs).

This research includes a multiple-case study involving ten Chinese manufacturers with two informants per organisation. Data have been interpreted from a multi-level social capital perspective (i.e. from both an individual and organisational level), supplemented by signalling theory.

Buyers use different risk identification strategies or apply the same strategy in different ways according to the BSR type. The impact of organisational social capital on risk identification is contingent upon the degree to which individual social capital is deployed in a way that benefits an individual’s own agenda versus that of the organisation. Signalling theory generally complements social capital theory and helps further understand how buyers can identify risks, especially in adversarial BSRs, e.g. by using indirect signals from suppliers or other supply chain actors to “read between the lines” and anticipate risks.

Data collection is focussed on China and is from the buyer side only. Future research could explore other contexts and include the supplier perspective.

The types of relationships that are developed by buyers with their supply chain partners at an organisational and an individual level have implications for risk exposure and how risks can be identified. The multi-level analysis highlights how strategies such as employee rotation and retention can be deployed to support risk identification.

Much of the extant literature on supply chain risk management is focussed on risk mitigation, whereas risk identification is under-represented. A unique case-based insight is provided into risk identification in different types of BSRs by using a multi-level social capital approach complemented by signalling theory.

Risk identification plays a key role identifying patient safety risks. As previous research on risk identification practices, as applied to patient safety, and its association with safety culture is limited, the purpose of this paper is to evaluate current practice to address gaps and potential room for improvement.

The authors carry out interview-based questionnaires in one UK hospital to investigate real-world risk identification practices with eight healthcare staff, including managers, nurses and a medical consultant. Considering various aspects from both risk identification and safety culture practices, the authors investigate how these two are interrelated.

The interview-based questionnaires were helpful for evaluating current risk identification practices. While gaining significant insights into risk identification practices, such as experiences using current tools and methods, mainly retrospective ones, results also explicitly showed its link with the safety culture and highlighted the limitation in measuring the relationship.

The interviews addressed valuable challenges affecting success in the risk identification process, including limitations in safety culture practice, training, balancing financial and safety concerns, and integrating risk information from different tools and methods.

In this paper risk identification is investigated as a basic stage in risk management. The risk identification phase as the first stage in the risk management process is presented and its leading role for effective risk management is proved. The basic terms that are necessary for building of the frame approach for risk identification are defined: sources of risk‐hazard, factor‐peril‐resources exposed to risk. A classification of risk sources – physical, social, political, operational, economic, legal and cognitive environment – is proposed. It allows covering all types of risk facing the organisation. A grouping of the resources exposed to risk such as physical, human, and financial resources is introduced. It is based on a practical consideration of the risk situations in the organisations.

The outbreak of COVID-19 pandemic has posed severe challenges to infrastructure construction in China. Particularly, the complex technology and high process uncertainty of deep foundation pit construction make its safety risk identification a challenging issue of general concern. To address these challenges, Building Information Modeling (BIM) can be used as an important tool to enhance communication and decision-making among stakeholders during the pandemic. The purpose of this study is to propose a knowledge management and BIM-integrated safety risk identification method for deep foundation pit construction to improve the management efficiency of project participants.

This paper proposes a risk identification method that integrates BIM and knowledge management for deep foundation pit construction. In the framework of knowledge management, the topological relationships between objects in BIM are extracted and visualized in the form of knowledge mapping. After that, formal expressions of codes are established to realize the structured processing of specification provisions and special construction requirements. A comprehensive plug-in for deep foundation pit construction is designed based on the BIM software.

The proposed method was verified by taking a sub-project in deep foundation pit project construction as an example. The result showed the new method can make full use of the existing specification and special engineering requirements knowledge. In addition, the developed visual BIM plug-in proves the feasibility and applicability of the proposed method, which can help to increase the risk identification efficiency and refinement.

The deep foundation pit safety risk identification is challenged by the confusion of deep foundation pit construction safety knowledge and the complexity of the BIM model. By establishing the standardized expression of normative knowledge and special construction requirements, the efficiency and refinement of risk identification are improved while ensuring the comprehensiveness of results. Moreover, the topology-based risk identification method focuses on the project objects and their relations in the way of network, eliminating the problem of low efficiency from the direct BIM-based risk identification method due to massive data.

In any information security risk assessment, vulnerabilities are usually identified by information‐gathering techniques. However, vulnerability identification errors – wrongly identified or unidentified vulnerabilities – can occur as uncertain data are used. Furthermore, businesses' security needs are not considered sufficiently. Hence, security functions may not protect business assets sufficiently and cost‐effectively. This paper aims to resolve vulnerability errors by analysing the security requirements of information assets in business process models.

Business process models have been selected for use, because there is a close relationship between business process objectives and risks. Security functions are evaluated in terms of the information flow of business processes regarding their security requirements. The claim that vulnerability errors can be resolved was validated by comparing the results of a current risk assessment approach with the proposed approach. The comparison is conducted both at three entities of an insurance company, as well as through a controlled experiment within a survey among security professionals.

Vulnerability identification errors can be resolved by explicitly evaluating security requirements in the course of business; this is not considered in current assessment methods.

It is shown that vulnerability identification errors occur in practice. With the explicit evaluation of security requirements, identification errors can be resolved. Risk assessment methods should consider the explicit evaluation of security requirements.

The purpose of this paper is to develop a model for upstream supply chain risk management linking risk identification, risk assessment and risk mitigation to risk performance and validate the model empirically. The effect of a continuous improvement process on identification, assessment, and mitigation is also included in the model.

A literature review is undertaken to derive the hypotheses and operationalize the included constructs. The paper then tests the path analytical model using partial least squares analyses on survey data from 162 large and mid‐sized manufacturing companies located in Germany.

All items load high on their respective constructs and the data provides robust support to all hypothesized relationships. Superior risk identification supports the subsequent risk assessment and this in turn leads to better risk mitigation. The model explains 46 percent of the variance observed in risk performance.

This study empirically validates the sequential effect of the three risk management steps on risk performance as well as the influence of continuous improvement activities. Limitations of this study can be seen in the use of perceptional data from single informants and the focus on manufacturing firms in a single country.

The detailed operationalization of the constructs sheds further light on the problem of measuring risk management efforts. Clear evidence of the performance effect of risk management provides managers with a business case to invest in such initiatives.

This is one of the first large‐scale, empirical studies on the process dimensions of upstream supply chain risk management.

Merging and updating project information and recording changes can give dynamic risk identification at all stages of the project. The main purpose of this research is to create an integration in construction information.

In this research, the 5D model was prepared and then all model information was entered into the database designed in SQL Server, the project report tables were coded, and finally, a database with four groups of information was ready for risk identification.

Creating an integrated risk identification platform reduced rework and time and cost control and change management, which were positive effects of risk identification at the right time.

In order to identify risks, creating multilateral databases whose information integration enables timely completion of the project and compliance with the planning.

This research is the basis for identifying project risks within the framework of building information modeling and can be an effective contribution to increasing the risk-taking efficiency of the project.

As a matter of fact, marked time and cost are terrific motivating forces for the building industry, materializing with identify risk well-time. In any case, identifying risk engaged with all of the dimensions depend on this industry.

This paper aims to propose a risk identification method which is a synthesis of existing tools and techniques.

Risks are viewed as a temporal hierarchy of major decisions or events at the highest level, projects at the middle level, and routine operations at the lowest level. Furthermore, risks emerge as organizational activities progress over time. The organizational activities, called movements in this paper, typically follow the phases of routine (operations) > major decision/event > project > adjustment > routine which correspond to the chosen temporal hierarchy. Risks are identified by examining the movements in all applicable phases of their development. The method was applied in a case study of an enterprise in the energy sector.

Focus on movements bridges company silos. Risk logs make sense only when supplied with visualization tools. The future state of the enterprise's routines should be modelled early in the decision‐making process. Attention should be paid to changes that major decisions, events, and projects impose on organizational routines.

The method belongs to the minority of approaches which explore risk evolution, relationships, and hierarchy rather than risk likelihood and impact. Risk evolution is explored by choosing movements as the basic units of risk identification. Risk relationships are detected on the level of routines where risk relationships are the least obvious but most important. The chosen hierarchy serves an enterprise‐deep view of risks and makes it possible to be alert for periods when the organization's risks change or new ones emerge.

This paper aims to investigate the purpose, reach and effectiveness of the customer identification framework of the Financial Action Task Force (FATF).

The article draws on relevant research and documents of the FATF, the Basel Committee on Banking Supervision and the Alliance for Financial Inclusion to determine whether compliance with the standards and practices of the FATF would prevent anonymous usage of financial services.

The FATF’s identification principles, guidance and practices resulted in processes that are largely bureaucratic and do not ensure that identity fraud is effectively prevented. Strict identification requirements on the other hand may impact on financial inclusion, leaving the FATF with little leeway to raise its standards. There are potential solutions, but they are longer-term and partial in nature.

Current identification and verification practices affect the lives of millions of people around the globe. The measures are being enforced to ensure that users are appropriately identified. This article informs the debate by highlighting the weaknesses of the current approach.

The purpose of this research is to investigate Australian property valuers' identification and consideration of physical risks to properties in valuation practice. The research further explores valuers' considerations of climate change-related risks.

The research approach comprised an online survey of Australian valuers who were members of the Australian Property Institute. The online survey included structured and unstructured questions to explore types and extent of risk investigations in valuation practice.

The analysis reflects that while valuers easily identified and engaged with physical risks, there is a lack of understanding of, and engagement with, climate change risks. This supports the need for better information sources and guidance to inform valuers of climate change risks per se, as well as the development of specific mechanisms for consideration of such risks to be included in valuation processes, practices and reports.

The research is limited by the small sample size achieved due to the timing of the survey deployment, which occurred during the first wave of COVID-19 lockdowns in Australia. Thus, the findings are not necessarily representative of the Australian valuation profession, but they do provide indications of current approaches to risk identification in practice and the need for more guidance in relation to climate change risks.

This research identifies that more support, guidance, information and tools, as well as awareness-raising, are required to enable valuers to accurately identify all risks affecting a property.

The research provides a snapshot of current understandings of physical risk identification in valuation practice. As investors and other organisations integrate and build up their analysis of climate risks to their portfolios and organisations, this research indicates that valuers also need to be aware of changing market assessment of physical and climate risks associated with property for consideration in valuation.