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In many security domains, the ‘human in the system’ is often a critical line of defence in identifying, preventing and responding to any threats (Saikayasit, Stedmon, & Lawson, 2015). Traditionally, such security domains are often focussed on mainstream public safety within crowded spaces and border controls, through to identifying suspicious behaviours, hostile reconnaissance and implementing counter-terrorism initiatives. More recently, with growing insecurity around the world, organisations have looked to improve their security risk management frameworks, developing concepts which originated in the health and safety field to deal with more pressing risks such as terrorist acts, abduction and piracy (Paul, 2018). In these instances, security is usually the specific responsibility of frontline personnel with defined roles and responsibilities operating in accordance with organisational protocols (Saikayasit, Stedmon, Lawson, & Fussey, 2012; Stedmon, Saikayasit, Lawson, & Fussey, 2013). However, understanding the knowledge that frontline security workers might possess and use requires sensitive investigation in equally sensitive security domains.

This chapter considers how to investigate knowledge elicitation in these sensitive security domains and underlying ethics in research design that supports and protects the nature of investigation and end-users alike. This chapter also discusses the criteria used for ensuring trustworthiness as well as assessing the relative merits of the range of methods adopted.

This article is an executive summary of a full scientific paper that appeared in the journal Personality & Individual Differences. A study was conducted to examine the factor structure of the Occupational Personality Questionnaire (OPQ) on a sample of 94 British undergraduates. The results indicated that five factors should be extracted, providing further evidence for the “Big Five” structural model of personality. This lends support for the use of the OPQ Pentagon model (Extroversion, Vigorous, Methodical, Emotional Stability and Abstract), but use of the Concept model (containing 30 scales) cannot be recommended.

The purpose of this paper is to identify potential helicopter pilots’ errors during their interaction with the flight deck in the process of starting a helicopter in night-time conditions.

Systematic Human Error Reduction and Prediction Approach is used for the analysis of the pilot–flight deck interaction. This methodology was used for the identification of errors for 30 pilots during a period of 10 years. In total, 55 errors were identified, and most common errors noted are: error of omission, caused by pilots’ lack of attention or longer periods of no flying, and error of wrong execution, caused by misunderstanding a situation.

Hierarchical task analysis and classification of pilot’s tasks were used for the analysis of consequences, probability of occurrence, criticality and remedial strategies for the identified pilot error.

This paper does not give an ergonomic analysis of the flight deck, as that is not its subject. However, results of the research presented in this paper, together with results presented in references, clearly show that there are disadvantages in the ergonomic design of flight decks.

Based on the identified pilot errors and with respect of existing ergonomic solution, it is possible to begin with the reconstruction of flight decks.

Higher quality of pilot–flight deck interaction must be ensured for both pilots’ and passengers’ safety, as even a slightest error can lead to catastrophic consequences.

The value of this paper lies in the fact that it points to the need for synergy of ergonomic design and human reliability methods.

Decision-making in human resources management is done at both the micro and macro level of organizations. Unfortunately, the decisions at each level are often executed without consideration of the other, and current theory reflects this issue. In response to a call for integration of micro- and macro-level processes by Huselid and Becker (2011), we review the extant literature on strategic human resources and high-performance work systems to provide recommendations for both research and practice. We aimed to contribute to the literature by proposing the incorporation of the situation awareness literature into the high-performance work systems framework to encourage the alignment of human resources efforts. In addition, we provide practical recommendations for integrating situation awareness and strategic decision-making. We discuss a process for the employment of situation awareness in organizations that might not only streamline human resources management but also result in more effective decisions. Additional considerations include implications for teams, boundary conditions (e.g., individual differences), and measurement.

This paper aims to report a study into the levels of abstraction hierarchy (LOAH) in two energy distribution teams. The original proposition for the LOAH was that it depicted five levels of system representation, working from functional purpose through to physical form to determine causes of a malfunction, or from physical form to functional purpose to determine the purpose of system function. The LOAH has been widely used throughout human supervisory control research to explain individual behaviour. The research seeks to focus on the application the LOAH to human supervisory control teams in semi‐automated “intelligent” systems.

A series of interviews were conducted in two energy distribution companies.

The results of the study suggest that people in the teams are predominantly operating at different levels of system representation, depending on their role. Managerial personnel work at functional purpose and abstract function levels, whereas operational personnel work at physical function and physical form levels. It is argued that both types of personnel are part of the wider distributed problem‐solving system, which includes both people and technology.

The research provides useful information on the application of the LOAH to human supervisory control teams in semi‐automated “intelligent” systems.

The purpose of this paper is to investigate how to measure collaborative design performance and, in turn, improve the final design output during a design process, with a clear objective to develop a design performance measurement (DPM) matrix to measure design project team members' design collaboration performances.

The methodology adopted in this research uses critical literature reviews, in‐depth focus group interviews and a questionnaire survey.

The main finding of this study is a DPM matrix that addresses five DPM indicators: efficiency, effectiveness, collaboration, management skill, and innovation, and 25 detailed DPM criteria. It was found that decision‐making efficiency is the most important DPM criterion for collaborative design efficiency; plus delivering to the brief for effectiveness; clear team goal/objectives for collaboration; decision‐making ability for management skill; and competitive advantage for innovation.

As the present study was focused on exploring DPM during a design process, some key DPM criteria which are not measurable during a design development process were not included in this study. The proposed multi‐feedback approach for DPM matrix implementation needs to be validated in future research.

The DPM matrix can be applied to support a design manager in measuring and improving collaborative design performance during a design process, by reviewing and modifying collaborative design development, identifying the design team strengths and weaknesses, improving team communication, and suggesting suitable responsive actions.

The major contribution of this study is the investigation and development of a DPM matrix to measure collaborative design performance during a design process.