Apple Inc’s acquisition of Lions Gate Entertainment Corp.

This dissertation intends to analyze the potential acquisition of Lions Gate Entertainment Corporation by Apple Inc. Apple is putting a notable amount of resources into competing in the entertainment market, and this acquisition would significantly improve its competitiveness in the industry. An analysis of the industry and the individual companies is provided, to substantiate the deal's rationale. Valuations are done of the individual companies and the synergies created by the merger to work out the transaction details. By finding the value of the merged entity with synergy effects, the combined enterprise value suggests the maximum bid that Apple can offer for the target. The intrinsic enterprise values of Apple and Lions Gate are approximately $3 trillion and$5.2 billion, respectively. The proposed merger creates $1.65 billion in net synergy value. The recommended bid price for each share is as follows: Apple will pay a 30prices for each of Lions Gate's share classes, which equals a bid price of$18.2 for Class A and $17.0 for Class B. The total purchase price adds up to$3.9 billion. The recommended transaction will be structured as a friendly takeover, as the acquisition will create value for shareholders of both companies. Apple will finance the takeover with 100% cash to signal confidence in the merger and the vast amount of excess cash on its balance sheets. By 2024, the acquisition will create value for Apple shareholders with a positive accretion yield.Esta dissertação pretende analisar a potencial aquisição da Lions Gate pela Apple. A Apple tem investido uma quantidade notável de recursos para competir no mercado do entretenimento, e esta aquisição melhoraria significativamente a sua competitividade na indústria. Forneço uma análise do setor e das empresas individuais que fundamentam a lógica do negócio. São feitas avaliações das empresas individuais e das sinergias criadas pela fusão para definir os detalhes da transação. Ao encontrar o valor da entidade fundida com os efeitos das sinergias, o valor combinado da empresa sugere o preço máximo que a Apple pode oferecer para o alvo de aquisição. Os valores empresariais intrínsecos da Apple e da Lions Gate são de aproximadamente US$3 triliões e US$ 5,2 biliões, respetivamente. A fusão proposta cria US$1,65 biliões em valor líquido de sinergia. O preço de oferta recomendado para cada ação é o seguinte: a Apple pagará um premium de 30classes de ações da Lions Gate, o que equivale a um preço de oferta de US$ 18,2 para a Classe A e US$17,0 para a Classe B. O preço total de compra totaliza US$ 3,9 biliões. A transação recomendada será estruturada como uma aquisição amigável, pois a aquisição criará valor para os acionistas de ambas as empresas. A Apple financiará a aquisição com 100% em dinheiro para sinalizar confiança na fusão e a grande quantidade de caixa excedente no seu balanço

New ventures in the age of digital media technologies – A qualitative study of influencer entrepreneurs

Master of Science in Business med spesialisering innen entreprenørskap og innovasjonsledelse, 201

Power estimations for non-primary outcomes in randomised clinical trials

Objective and methods: It is rare that trialists report power estimations of non-primary outcomes. In the present article, we will describe how to define a valid hierarchy of outcomes in a randomised clinical trial, to limit problems with Type I and Type II errors, using considerations on the clinical relevance of the outcomes and power estimations. Conclusion: Power estimations of non-primary outcomes may guide trialists in classifying non-primary outcomes as secondary or exploratory. The power estimations are simple and if they are used systematically, more appropriate outcome hierarchies can be defined, and trial results will become more interpretable

Predicting Survival Time of Ball Bearings in the Presence of Censoring

Ball bearings find widespread use in various manufacturing and mechanical domains, and methods based on machine learning have been widely adopted in the field to monitor wear and spot defects before they lead to failures. Few studies, however, have addressed the problem of censored data, in which failure is not observed. In this paper, we propose a novel approach to predict the time to failure in ball bearings using survival analysis. First, we analyze bearing data in the frequency domain and annotate when a bearing fails by comparing the Kullback-Leibler divergence and the standard deviation between its break-in frequency bins and its break-out frequency bins. Second, we train several survival models to estimate the time to failure based on the annotated data and covariates extracted from the time domain, such as skewness, kurtosis and entropy. The models give a probabilistic prediction of risk over time and allow us to compare the survival function between groups of bearings. We demonstrate our approach on the XJTU and PRONOSTIA datasets. On XJTU, the best result is a 0.70 concordance-index and 0.21 integrated Brier score. On PRONOSTIA, the best is a 0.76 concordance-index and 0.19 integrated Brier score. Our work motivates further work on incorporating censored data in models for predictive maintenance.Comment: Accepted at AAAI Fall Symposium 2023 on Survival Predictio

The effects of ventilation tubes versus no ventilation tubes for recurrent acute otitis media or chronic otitis media with effusion in 9 to 36 month old Greenlandic children, the SIUTIT trial:study protocol for a randomized controlled trial

SPIRIT 2013 Checklist. (DOCX 61 kb