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A significant increase in financial crime globally emphasises the importance of forensic interviewing to obtain useful and reliable information as part of a commercial forensic investigation. Previous research has identified two interviewing strategies that are aligned with the legal framework in South Africa: the PEACE model (P = preparation and planning; E = engage and explain; A = account, clarify and challenge; C = closure; E = evaluation) and the person-centred approach (PCA). The purpose of this paper is to explore the theoretical underpinnings and application of the PEACE model and the PCA as commercial investigative strategies aligned with the legal context in South Africa.

A scoping review was undertaken to identify literature relevant to the theoretical assumptions and application of the PEACE model and the PCA.

Literature for the most part reports on the PEACE model but offers very little information about the PCA. A critical analysis revealed that the PEACE model incorporates a clear guiding structure for eliciting information but lacks content needed to create an optimal interpersonal context. To promote this, the PCA proposes that interviewers demonstrate three relational variables: empathy, congruence and unconditional positive regard. The PCA suggests a basic structure for interviewing (beginning, middle and end), while providing very little guidance on how to structure the forensic interview and what information is to be elicited in each phase.

Combining the PEACE model and PCA presents an integrated interviewing technique best suited for obtaining useful and reliable information admissible in a South African court of law. The PEACE model has a clear structure, and the PCA assists in creating an optimal interpersonal context to obtain information in an interview.

Research on employee non-/compliance to information security policies suffers from inconsistent results and there is an ongoing discussion about the dominating survey research methodology and its potential effect on these results. This study aims to add to this discussion by investigating discrepancies between what the authors claim to measure (theoretical properties of variables) and what they actually measure (respondents’ interpretations of the operationalized variables). This study asks: How well do respondents’ interpretations of variables correspond to their theoretical definitions? What are the characteristics of any discrepancies between variable definitions and respondent interpretations?

This study is based on in-depth interviews with 17 respondents from the Swedish public sector to understand how they interpret questionnaire measurement items operationalizing the variables Perceived Severity from Protection Motivation Theory and Attitude from Theory of Planned Behavior.

The authors found that respondents’ interpretations in many cases differ substantially from the theoretical definitions. Overall, the authors found four principal ways in which respondents interpreted measurement items – referred to as property contextualization, extension, alteration and oscillation – each implying more or less (dis)alignment with the intended theoretical properties of the two variables examined.

The qualitative method used proved vital to better understand respondents’ interpretations which, in turn, is key for improving self-reporting measurement instruments. To the best of the authors’ knowledge, this study is a first step toward understanding how precise and uniform definitions of variables’ theoretical properties can be operationalized into effective measurement items.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

The purpose of the current innovative practice paper is to introduce a technique to explore leader identity development and meaning-making that builds on the narrative pedagogical tradition. In this paper, we recommend a process for combining turning-point graphing and responsive (semi-structured) interviews to co-explore leadership identity development and meaning-making with college students.

The paper provides student feedback data on the effectiveness of the technique in improving understanding of leader identity and transforming meaning-making.

We hope practitioners can utilize this approach to build leadership identity development and meaning-making capacity in college students.

The increasing complexity of civil engineering projects necessitates focusing on new competencies of project participants. Based on the research on team performance and design processes that are more closely linked to the relevance of the project context, it is hypothesised that empathic abilities could play an important role in the performance of civil engineering projects. Therefore, this study aims to investigate whether performance can be improved by focusing on empathic abilities during the integrated design phase.

Semi-structured in-depth interviews with experts were conducted to explore the relevance of empathic abilities and their interaction with performance in a real-life infrastructure project. The project team’s empathy level was measured by means of a survey using Davis’ Interpersonal Reactivity Index method. Finally, differences between expected and measured levels of empathy were analysed.

The results provide insights into how empathic abilities interact with performance. The measurement indicates that, on average, professionals in the civil engineering industry score relatively low on empathy. In addition, differences were identified between the expected distribution and the measured empathy levels of the team, implying a potential for improvement, in particular by increasing the empathic abilities of the project management and increasing gender diversity.

To the best of the authors’ knowledge, this study is the first to investigate a relationship between empathy and the performance of civil engineering projects. The results provide initial insights into the empathic ability of civil engineering project teams and the potential of empathy to improve performance. Furthermore, from an empathy perspective, this study advocates increasing the gender diversity of project teams to improve performance.

This paper investigates the change talk (CT) strategies of the motivational interviewing (MI) technique and their relevance in achieving change goals within communities of practice (CoP), focusing on addressing real-world problems in today's complex world.

We employ a literature review and conceptual analysis to study the interactions and potential areas of complement between CT, MI and CoP theories.

This paper combines CT, MI and CoP theories to develop an integrated model called Facilitative Change Talk Leadership (FCTL).

This paper provides an innovative model (FCTL) to inform leadership educators about facilitating communities of practice. We provide a hypothetical case study to suggest how FCTL might foster collaborative inquiry and resilience amidst complex challenges. This case study illustrates a practical pathway for leadership educators and community practitioners to use this model in their own contexts.

This paper aims to investigate the formation of an inter-organizational collaboration network that made it possible to repair 2,516 mechanical respirators that were inoperative in Brazil during the first wave of the COVID-19 pandemic.

A qualitative approach was used in a single case study with semi-structured interviews. The interviewee selection process was non-probabilistic through snowball sampling.

The results suggest that society, through different social groups with their different roles, can organize itself quickly through the formation of collaborative networks, and this organizational configuration can be an alternative for facing crises where actions isolated would be insufficient or slow to urgently address complex situations.

This paper aims to (1) demonstrate that society, through different social groups with their different roles, can organize itself quickly through the formation of collaborative networks; (2) favor the understanding and dynamics of the formation of a network; and (3) contribute to a possible replication of this initiative in future contexts.

The case portrays an unprecedented formation of a collaboration network involving more than 144 organizations that mobilized quickly in a complex context of a pandemic and that generated remarkable results through the reintroduction of equipment that were responsible for the preservation of thousands of lives during the year from 2020.

The purpose of this paper is to analyze if the sport trajectory could be an impact factor in leadership development.

A qualitative research method has been adopted by conducting 17 in-depth, semi-structured interviews. The data were analyzed with the program Open Code (4.03).

The findings of this study revealed that the interviewed managers perceived that their sport trajectory has had an important influence in the development of their leadership. This influence is determined by four factors: (1) sport profile, (2) sport referents, (3) competences, values and abilities and (4) experiences from different sport roles played during their lifespan.

The research is based on interviews with a small sample of managers. In order to develop the research further, a more extensive sample is required.

The paper is unique as it examines the impact of the sport trajectory as an impact factor in leadership development.

According to the Project Management Institute, 70% of projects fail globally. The causes of project failure in many instances can be identified as non-technical or behavioral in nature arising from interactions between participants. These intangible risks can emerge in any project setting but especially in project settings having diversity of cultures, customs, beliefs and traditions of various companies or countries. This paper provides an objective framework to address these intangible risks.

This paper presents a structured approach to identify, assess and manage intangible risks to enhance a project team’s ability to meet its objectives. The authors propose a user-friendly framework, Intangible Risk Assessment Methodology for Projects (IRAMP), to address these risks and the factors that cause them. Meta-network (e.g., a network of networks) simulation and established social network analysis (SNA) measures provide a quantitative assessment and ranking of causal events and their influence on the intangible behavior centric risks.

The proposed IRAMP and meta-network approach were utilized to examine the project delivery process of an international energy firm. Data were gathered using structured interviews, surveys and project team workshops. The use of the IRAMP to highlight intangible risk areas underpinned by the SNA measures led to changes in the company’s organizational structure to enhance project delivery effectiveness.

This work extends the existing project risk management literature by providing a novel objective approach to identify and quantify behavior centric intangible risks and the conditions that cause them to emerge.

With Industry 4.0 and the extensive rise of smart technologies, we are seeing remarkable transformations in work practices and workplaces. Scholars report the phenomenal progress of smart technologies. At the same time, we can hear the rhetoric emphasising their potential threats. This study focusses on how and where intelligent machines are leveraged in the workplace, how humans co-working with intelligent machines are affected and what they believe can be done to mitigate the risks of the increased use of intelligent machines.

We conducted in-depth interviews with 15 respondents working in various leadership capacities associated with intelligent machines and technologies. Using NVivo, we coded and churned out the themes from the qualitative data collected.

This study shows how intelligent machines are leveraged across different industries, ranging from chatbots, intelligent sensors, cognitive systems and computer vision to the replica of the entire human being. They are used end-to-end in the value chain, increasing productivity, complementing human workers’ skillsets and augmenting decisions made by human workers. Human workers experience a blend of positive and negative emotions whilst co-working with intelligent machines, which influences their job satisfaction level. Organisations adopt several anticipatory strategies, like transforming into a learning organisation, identifying futuristic technologies and upskilling their human workers, regularly conducting social learning events and designing accelerated career paths to embrace intelligent technologies.

This study seeks to understand the emotional and practical implications of the use of intelligent machines by humans and how both entities can integrate and complement each other. These insights can help organisations and employees understand what future workplaces and practices will look like and how to remain relevant in this transformation.