The emergence of social media and recommendation systems has profoundly transformed user interactions with digital content, bringing in both opportunities and ethical challenges. This thesis scrutinizes the online manipulation exerted by RS, which, while enhancing engagement and profitability, can guide user behavior subtly and without their awareness. This definition is based on covert influence, a particular account of manipulation.

A critical examination of existing literature reveals a significant gap: while the conceptual framework for online manipulation is well-discussed, empirical studies providing concrete evidence are scant. This research addresses this deficiency by employing an agent-based model to simulate interactions between users and recommendation systems, aiming to systematically analyze and quantify the effects of covert manipulation on user preferences.

This study contributes to the field by operationalizing the concept of manipulation within a controlled simulation of a book recommendation system, providing a clearer understanding of its mechanisms and effects. This approach not only offers insights into the ethical implications of RS but also aligns with current legislative movements, such as the European Union's Artificial Intelligence Act, aimed at regulating and mitigating harmful manipulative practices by intelligent systems. The findings are intended to guide the design and regulation of RS to ensure they serve the user's interests without compromising ethical standards.

The results show that book recommendation systems can modify user preferences by 9.79\% when prioritizing items covertly, while awareness of the intentions and social influence can diminish the effect of the manipulative algorithm's intention to 4.01\% and 3.64\%. When compared to the 2.58\% change in the case of a non-prioritized RS, the values provide a measurable estimation of the difference between manipulative and non-manipulative book RS for the change of user preferences after interacting with it for some time.

Generative AI is expected to have a significant impact on how business is done, especially for knowledge-intensive domains. Professional usage amongst knowledge workers is already widespread and many of them believe that LLM use for work will make them more efficient, help them generate ideas, and improve the quality of their work. Yet, the technology comes with numerous potential risks, including job displacement, threats to data privacy, unreliability, cybersecurity risks, and non-compliance with new AI regulation. The decision to adopt LLMs for knowledge work is thus a significant one as organisations must carefully weigh up the benefits and drawbacks that these models present.

Using a qualitative research approach, this study was aimed at exploring employee and organisational perceptions on the benefits and risks of LLM adoption within the Dutch financial sector. This study was conducted in partnership with a global Professional Services Firm and used their existing network of people and clients to conduct interviews with experts who act as advisors to top management in the decision-making process of new technology adoption such as LLMs. 18 semi-structured interviews were done to collect qualitative data. The research question to be answered is:

- How do employees’ and organisations’ perceived benefits and risks of Large Language Models (LLMs) influence financial organisations’ LLM adoption plans?

Exactly half of participants (9/18) said that they use LLMs in their own work while the other half stated that they do not due to a lack of perceived benefits. Microsoft was found to be a significant player in the current adoption of LLMs at Dutch financial institutions with 57% of all LLMs used by participants being owned by the software vendor. The most common LLM use cases were literary and creative in nature and included preparing presentation slides (16%), text generation (12%), email composition (12%), and structuring documents (12%).

The targeted capabilities that organisations would like to achieve with their future adoption plans include helping programmers write better code, analysing help desk conversations, assisting employees via LLM chatbots, and analysing emails to predict customer questions. Employees were most excited about the potential efficiency and productivity gains that LLMs offer for their work (19%), how LLM usage could free up more time for focused, interesting, and fun work (11%), repetitive tasks becoming automated by LLM (8%), the new opportunities that LLMs present (8%) such as new business models, and improvements to customer service (5%). General overlap can be seen between the targeted capabilities of future LLMs to be adopted and employee expectations.

Instead of restricting LLM usage, it is recommended that organisations find ways to incorporate them into their employee workflows by providing clear policies and guidelines. It was found that this approach will be most beneficial to creative and literary workflows like improving writing/grammar/translation, information search, structuring documents, and text generation. To achieve this integration, organisations should write and implement clear usage policies. This will ensure that the benefits of allowing LLM usage at work are enjoyed while mitigating the most important risks.

Aviation Maintenance Repair and Overhaul (MRO) organisations are facing a lack of sustainable alternatives within MRO, which could aid a more sustainable operation geared to meet short-term climate regulations. Hence, they need to establish an idea evaluation process, allowing organisations to assess and prioritise generated ideas to assess which have the potential to contribute to the industry's decarbonisation.
This research aims to determine how innovative ideas can be assessed and selected to speed up the innovation process within aviation-MRO. In particular, the Front-end of Innovation (FEI) is researched as this phase is considered extremely important within the innovation process. The FEI is the first phase of innovation, ranging from idea generation to concept development.
This study utilised a mixed method approach to achieve the research objective, in which multiple methodologies are synthesised into one more extensive study. Firstly, extensive literature research was performed to determine the evaluation models applied within the existing literature. Next, industry-specific interviews were conducted to acquire standard practices within the aviation MRO. Thirdly, survey research was employed to tailor the idea evaluation model toward the aviation MRO industry. Finally, a case study was performed to determine whether the proposed case study could be applied within the organisational context.
The framework incorporates a stage-gate process, incorporating two evaluation moments named the initial screen and the preliminary evaluation. The first evaluation includes a checklist with five criteria, followed by an evaluation matrix incorporating fourteen criteria. Although the framework serves as the basis for the idea evaluation process, the case study revealed that there is no one-size-fits-all process. The organisation context impacts the evaluation criteria, meaning each organisation should individually assess which of the proposed criteria are deemed relevant within their organisation.
The framework proposed in this research provides a structure and tools to organise the idea evaluation process, which can aid organisations in enhancing the speed of the innovation process potentially. On this basis, the proposed framework can be utilised by aviation MRO organisations to accommodate the foundation of the idea evaluation process.