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Cyber resilience in cyber supply chain (CSC) systems security has become inevitable as attacks, risks and vulnerabilities increase in real-time critical infrastructure systems with little time for system failures. Cyber resilience approaches ensure the ability of a supply chain system to prepare, absorb, recover and adapt to adverse effects in the complex CPS environment. However, threats within the CSC context can pose a severe disruption to the overall business continuity. The paper aims to use machine learning (ML) techniques to predict threats on cyber supply chain systems, improve cyber resilience that focuses on critical assets and reduce the attack surface.

The approach follows two main cyber resilience design principles that focus on common critical assets and reduce the attack surface for this purpose. ML techniques are applied to various classification algorithms to learn a dataset for performance accuracies and threats predictions based on the CSC resilience design principles. The critical assets include Cyber Digital, Cyber Physical and physical elements. We consider Logistic Regression, Decision Tree, Naïve Bayes and Random Forest classification algorithms in a Majority Voting to predicate the results. Finally, we mapped the threats with known attacks for inferences to improve resilience on the critical assets.

The paper contributes to CSC system resilience based on the understanding and prediction of the threats. The result shows a 70% performance accuracy for the threat prediction with cyber resilience design principles that focus on critical assets and controls and reduce the threat.

Therefore, there is a need to understand and predicate the threat so that appropriate control actions can ensure system resilience. However, due to the invincibility and dynamic nature of cyber attacks, there are limited controls and attributions. This poses serious implications for cyber supply chain systems and its cascading impacts.

ML techniques are used on a dataset to analyse and predict the threats based on the CSC resilience design principles.

There are no social implications rather it has serious implications for organizations and third-party vendors.

The originality of the paper lies in the fact that cyber resilience design principles that focus on common critical assets are used including Cyber Digital, Cyber Physical and physical elements to determine the attack surface. ML techniques are applied to various classification algorithms to learn a dataset for performance accuracies and threats predictions based on the CSC resilience design principles to reduce the attack surface for this purpose.

This study seeks to operationalise the reporting of corporate natural assets (i.e. habitats, flora and fauna). A natural inventory model is used, building on existing methodology. This study significantly extends the prior research by considering environmental accounting in the context of a large site and by using a UK publicly listed company, Hyder plc. The research finds that the methodology is generally applicable. Data were available to identify and value ten important habitats. Moreover, data were present for critical species (especially birds and mammals), and for flora and fauna on critical habitats. However, for some non‐critical species, data, particularly population data, was problematic. The potential benefits of the natural inventory model are substantial, the costs are modest.

The paper seeks to respond to calls by Jones for more studies exploring the possibility of operationalising accounting for biodiversity.

Archival data are used to produce a natural inventory report for the Sundarbans, the world's largest mangrove forest declared as a World Heritage site by UNESCO in 2007.

The study extends prior research on biodiversity accounting by exploring the applicability of Jones' natural inventory model in the context of Bangladesh. The results indicate that application of Jones' natural inventory model is feasible in the context of developing countries such as Bangladesh. It is also recognised that the socio‐economic and political environment prevailing in developing economies may lead to the emergence of important stakeholder groups including local civil society bodies, international donor agencies and foreign governments. Biodiversity accounting may provide a legitimate basis for the government in allaying concerns regarding environmental stewardship and assist in negotiations with powerful stakeholder groups on important issues such as financial assistance after natural disasters and claims to the global climate change fund.

This is one of the early attempts to operationalise biodiversity accounting in the context of a developing economy.

Many methodologies exist to assess the security risks associated with unauthorized leakage, modification and interruption of information used by organisations. This paper argues that these methodologies have a traditional orientation towards the identification and assessment of technical information assets. This obscures key risks associated with the cultivation and deployment of organisational knowledge. The purpose of this paper is to explore how security risk assessment methods can more effectively identify and treat the knowledge associated with business processes.

The argument was developed through an illustrative case study in which a well‐documented traditional methodology is applied to a complex data backup process. Follow‐up interviews were conducted with the organisation's security managers to explore the results of the assessment and the nature of knowledge “assets” within a business process.

It was discovered that the backup process depended, in subtle and often informal ways, on tacit knowledge to sustain operational complexity, handle exceptions and make frequent interventions. Although typical information security methodologies identify people as critical assets, this study suggests a new approach might draw on more detailed accounts of individual knowledge, collective knowledge and their relationship to organisational processes.

Drawing on the knowledge management literature, the paper suggests mechanisms to incorporate these knowledge‐based considerations into the scope of information security risk methodologies. A knowledge protection model is presented as a result of this research. This model outlines ways in which organisations can effectively identify and treat risks around process knowledge critical to the business.

This paper aims to respond to recent calls by Jones (2014) and Jones and Solomon (Accounting, Auditing & Accountability Journal, 2013) for more studies on biodiversity accounting and reporting. In particular, this paper explores biodiversity reporting of the Murray-Darling Basin Authority (MDBA), an Australian public sector enterprise.

The paper uses content analysis of MDBA’s published annual reports over the period of 15 years (1998-2012). Archival data (from different government departments) are also used to prepare natural inventory model.

The paper finds that although specific species, such as flora and fauna, and habitats-related disclosures have increased over the time, such information still allows only a partial construction of an inventory of natural assets, using Jones’ (1996, 2003) model. However, unlike prior studies that find lack of data availability to be the main impediment for operationalising biodiversity accounting, the abundance of biodiversity data in Australia makes it comparatively easier to produce such a statement.

Informed by the environmental stewardship framework, the results of this paper suggest that the disclosures made by MDBA are constrained potentially due to its use of traditional accounting mechanisms of reporting that only allow tradable items to be reported to stakeholders. An alternative reporting format would be more relevant to stakeholder groups who are more interested in information regarding quality and availability of water, and loss of biodiversity in the basin area rather than the financial performance of the MDBA.

Although there are a growing number of studies exploring biodiversity reporting in Australia, this paper is one of the earlier attempts to operationalise biodiversity (particularly habitats, flora and fauna) within the context of an Australian public sector enterprise.

Households are exposed to a wide array of risks, characterized by a known or unknown probability distribution of events. Disasters are one of these risks at the extreme end. Understanding the nature of these risks is critical to recommending appropriate mitigation measures. A household’s resilience in resisting the negative outcomes of these risky events is indicative of its level of vulnerability. Vulnerability has emerged as the most critical concept in disaster studies, with several attempts at defining, measuring, indexing and modeling it. The paper presents the concept and meanings of risk and vulnerability as they have evolved in different disciplines. Building on these basic concepts, the paper suggests that assets are the key to reducing risk and vulnerability. Households resist and cope with adverse consequences of disasters and other risks through the assets that they can mobilize in face of shocks. Asustainable strategy for disaster reduction must therefore focus on asset‐building. There could be different types of assets, and their selection and application for disaster risk management is necessarily a contextual exercise. The mix of asset‐building strategies could vary from one community to another, depending upon households’ asset profile. The paper addresses the dynamics of assets‐risk interaction, thus focusing on the role of assets in risk management.

Knowledge assets and performance improvement have recently emerged as important and interacting research areas in company business management. The purpose of this research is to highlight the role and relevance of knowledge assets as critical factors for improving the performances of a new product development (NPD) process.

Interpreting the NPD as a knowledge‐based process, the paper presents three case studies which provide empirical evidence of the impact on performance of the assessment and management of the knowledge assets at the basis of NPD process.

The outcomes of the research is a set of managerial implications, useful in order to drive managers towards the design and implementation of knowledge assets management initiatives aimed to support the improvement of the NPD performances.

Through an integration of the results of the inductive research, based on multiple case studies, with the main findings taken from a literature review, the paper addresses managerial implications for improving NPD process performances by developing knowledge asset value drivers.

The purpose of this paper is to present a study of reliability-centred maintenance (RCM), which is conducted on the key sub-assets of a newly constructed road junction infrastructure in Nigeria.

The classical RCM methodology, a type of RCM, which has a top down, zero-based approach for maintenance analysis, is implemented in this study.

The implementation of the classical RCM is successful in its application of various PM policies assigned to the assets and it shows that its application in the highway industry could reduce excessive maintenance backlog and frequent reactive maintenance by effective optimisation of its preventive maintenance (PM) intervals.

Road junctions are originators of more than 70 per cent of road traffic congestion and account for high accident rate. The traditional methods of reliability assurance used in the highway industry such as reactive maintenance and routine maintenance are often inadequate to meet the round the clock usage demands of these assets, thus the consideration for the application of a systematic RCM process for maintaining the system function by selecting and applying effective PM tasks.

It uses an approach that critically develops and analyses thoroughly preventive and continuous maintenance strategy in a new circumstance with environment of uncertainty and limited operating data. The case-based reasoning cycle has been applied in the RCM approach with real-time data obtained from a UK-based network maintenance management system for highway infrastructures.

This chapter identifies the five new roles that are critical to establishing and sustaining a knowledge preservation and curation practice. For each role, the authors describe fundamental responsibilities and competencies. Two of the roles support knowledge preservation, including business knowledge analyst and specialized knowledge preservationist. Three of the roles support knowledge curation including business interlocutor/translator, knowledge curator, and knowledge asset developer. Each role faces peculiar challenges in a dynamic and chaotic knowledge economy.

Implementation of accrual-based accounting systems and the related preparation of an initial balance sheet are stimulating a debate on valuation and management of fixed assets, emphasising how critical it is to have adequate asset information. This chapter aims to propose a framework to clarify the relationship between the asset inventory and the asset register by examining the objectives and characteristics of asset information systems, drawing from experience regarding the implementation of asset inventories and registers from four countries (Malaysia, South Africa, Switzerland, and Australia – State of Victoria).