More and more institutions have begun to implement digital transformation. Identifying the reasons behind institutions’ digital transformation can help them make the right strategies. This thesis focuses on the digital transformation taking place in the financial industry and uses organizational institutionalism theory to analyze the influence of external pressures, and what responsible strategies institutions may adopt. We use qualitative methods to conduct the research. We interview eight employees from different institutions in the financial industry in China. Our findings show how coercive, mimetic, and normative pressures affect these financial institutions differently, and in responding to these pressures, these financial institutions develop office management systems and new digital products and services. The study evaluates to which extent the new digital reality fits the theory of the influence of external pressures on institutions. For managerial practice, the findings provide guidance in describing and diagnosing external pressures that drive digital transformation, and in coping with these pressures appropriately to formulate effective digital transformation strategies.

Syftet med studien är att undersöka och skildra några studenters motiv, motivation och upplevelser kring högre studier. I bakgrunden ingår forskning kring studentidentiteter (Bron m. fl., 2013), men efter hand tillkommer andra begrepp och teorier som bidrar till att belysa undersökningsmaterialet. Studien är grundad på kvalitativ metod, med semistrukturerade intervjuer av sex studenter i åldrarna 25-30 år. Resultatet av de sex studenterna redovisas som personporträtt, där både likheter och skillnader mellan studenternas motiv, motivation och upplevelser i relation till högre studier framgår. Några studerar för att kunna få ett arbete, andra för att bevisa för sig själva att de kan. I några fall återfann vi det som kallas för det transformativa lärandet enligt Mezirow (1997). / The aim of this study is to explore motives, motivation and experiences reported by some students in relation to higher education. The study is inspired by previous research (Bron et al, 2013) about students´ identities, and after the collection of data other theories and previous research were added. The method used is qualitative, specifically semi-structured interviews, based on six interviews with students aged 25-30. Similarities as well as differences in students´ motives and motivation for higher education appear. Some students attend higher education mainly in order to get a job/profession while a few also want to prove to themselves that they are competent enough to succeed in higher education. Occationally, transformative learning (Mezirow, 1997) emerge in data.

The uptake of residential photovoltaic systems is essential for energy system transformation towards carbon neutrality and decentralization. However, despite numerous campaigns to incentivize their uptake, adoption by residential homeowners is lacking behind. While countless drivers and barriers have been identified, the decision process is not fully understood. To address this gap, we developed an agent-based residential rooftop photovoltaic adoption model called PVact. Our model analyzes the interactions of potential household adopters based on their utility functions and social network, with a focus on the role of monetary evaluation and social pressure in adoption behavior. In this paper, we aim to assess the influence of monetary evaluation and social pressure in an abstract case study based on real-world data from the municipality of Leipzig, Germany. We consider stochastic dynamics through scenario analysis to investigate the influence of these factors on adoption behavior. Our results show that monetary evaluation and social pressure have a significant impact on adoption behavior. Specifically, we find shifting adoption patterns with an increased requirement for monetary returns and higher level of normative pressure required for households to act. Higher resistance against these pressure shows more stochastic variations,