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This paper investigates effective strategies for enhancing completion rates of apprentices and their retention after completing their training. The study was cross sectional and qualitative, involving semi‐structured interviews with managers and four focus groups involving current and completed apprentices from within the engineering sector. The findings revealed that the factors that can enhance intentions of completing an apprenticeship were perceived organisation support (POS) factors such as apprentice pay, recognition and employer support. Leader Member Exchange (LMX) factors such as support from trainers and supervisors, would increase their intentions to complete an apprenticeship and stay on with an organisation after training. The key Percieved Organisational Support factors that would enhance intentions to stay with the organisation after completion were post apprenticeship pay, career progression and challenging and interesting work. Participants with high Perceived Organisational Support and Leader‐Member Exchange, had higher intentions of completing an apprenticeship and staying with the employer after completion and vice versa. This research added to the literature on apprenticeships as it analysed the factors influencing current and completed apprentices’ intentions to discontinue or complete an apprenticeship and stay with or leave their employer after completion through the lens of social exchange theory (SET) (Blau, 1964). This is unlike previous studies that emphasised motivation theory. Social Exchange Theory was supported as both employers and apprentices weighed the costs and benefits of their relationship which impacted on their completion and retention choices. The implication of this study is that employers should develop effective strategies for enhancing completion and retention rates to reap the full benefits from apprenticeships. 相似文献
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Aaron Zimba Zhaoshun Wang Mwenge Mulenga 《Journal of Organizational Computing & Electronic Commerce》2019,29(1):40-59
Crypto-mining attacks have emerged as a new generation of web-based attacks which have seen cybercriminals eschew the infamous crypto ransomware. The watering hole attack vector has by far been the most widely employed attack methodology but it faces the task of luring the victim to the infected web resources. However, cryptojacking injection presents a paradigm shift to web-based crypto-mining attacks in that it eliminates the need for a pivotal third-party such as the exploitable web server. Thus, instead of attacking credit card and other private information of e-commerce users, attackers seek to maliciously abuse a victim’s CPU to generate cryptocurrency. In this paper, we investigate and evaluate cryptojacking injection – a state-of-the-art web-centric attack vector in the crypto-mining attacks landscape. We formulate an attack model based on finite state machines which depicts the various breaches of confidentiality, integrity and availability in the web system as the attack progresses. We show how this new attack vector attacks some of the core components of e-commerce (URL, HTTP and HTML) to generate Monero crypto currency from benign web users. We evaluate our modeling approach with a series of experiments with two attack scenarios using different operating systems. Results show that the attack is indeed cross-platform and feasible on any operating system of a browser-capable device. We analyze the generated network traffic during the attack and draw features such as URLs and the parsed files, the associated cryptographic hashes, and the IP addresses of the crypto-mining domains. These, together with host-based features such as exhaustive CPU usage can be used as indicators of compromise and subsequently act as feed into intrusion detection systems. 相似文献
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