Prior research on network attacks is predominantly technical, yet little is known about behavioral patterns of attackers inside computer systems. This study adopts a criminological perspective to examine these patterns, with a particular focus on data thieves targeting organizational networks. By conducting interviews with cybersecurity experts and applying crime script analysis, we developed a comprehensive script that describes the typical progression of attackers through organizational systems and networks in order to eventually steal data. This script integrates phases identified in previous academic literature and expert-defined phases that resemble phases from industry threat models. However, in contrast to prior cybercrime scripts and industry threat models, we did not only identify sequential phases, but also illustrate the circular nature of network attacks. This finding challenges traditional perceptions of crime as a linear process. In addition, our findings underscore the importance of considering both successful and failed attacks in cybercrime research to develop more effective cybersecurity strategies.
MULTIFILE
Artificial intelligence-driven technology increasingly shapes work practices and, accordingly, employees’ opportunities for meaningful work (MW). In our paper, we identify five dimensions of MW: pursuing a purpose, social relationships, exercising skills and self-development, autonomy, self-esteem and recognition. Because MW is an important good, lacking opportunities for MW is a serious disadvantage. Therefore, we need to know to what extent employers have a duty to provide this good to their employees. We hold that employers have a duty of beneficence to design for opportunities for MW when implementing AI-technology in the workplace. We argue that this duty of beneficence is supported by the three major ethical theories, namely, Kantian ethics, consequentialism, and virtue ethics. We defend this duty against two objections, including the view that it is incompatible with the shareholder theory of the firm. We then employ the five dimensions of MW as our analytical lens to investigate how AI-based technological innovation in logistic warehouses has an impact, both positively and negatively, on MW, and illustrate that design for MW is feasible. We further support this practical feasibility with the help of insights from organizational psychology. We end by discussing how AI-based technology has an impact both on meaningful work (often seen as an aspirational goal) and decent work (generally seen as a matter of justice). Accordingly, ethical reflection on meaningful and decent work should become more integrated to do justice to how AI-technology inevitably shapes both simultaneously.
Supply chain collaboration, in which two or more autonomous firms work together to plan and execute supply chain operations, is becoming ever more important to remain competitive in business. Yet, through collaboration concerns arise about whether the benefits and risks of collaboration are split in an acceptable and fair manner. This research illustrates the role of fairness (organizational justice theory) in creating and appropriating value from supply chain collaborations. We therefore analyze an extensive case study in the Dutch floricultural industry, in which six companies enter a supply chain collaboration. We conclude that fairness considerations are very important for explaining the outcomes of supply chain collaborations. Asymmetries in perceived value appropriation can be offset if the collaboration is deemed fair on distributive, procedural, interpersonal and informational justice dimensions. Firms may improve the success rate of supply chain collaborations if the fairness perceived is considered to be adequate.
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