2,779 research outputs found
Digitalization of business models : impacts and opportunities for the healthcare industry : a multiple case study approach
The purpose of this applied-research project is to understand how digitalized business models
can be assessed and analyzed with regard to their success in the broad field of healthcare.
Digitalization holds enormous opportunities, but also requires a particular degree of tact and
sensitivity concerning business model design. In order to propose specific guidelines for
business model design this paper highlights the major dynamics of the digital business
ecosystem, like turbulence, disruptiveness and blurred industry boundaries, and describes
Omar El Sawy’s VISOR model, with its components Value Proposition, Interface, Service
Platform, Organizing Model and Revenue Model. Following this, the main part consists of
two case studies, Nike+ and Kinematix, and narrates the stories of one major, incumbent
player and of one new entrant, with the purpose to achieve extensive insights on different
perspectives of digital business models. Both companies operate in the field of E-health, more
specifically running wearables, Nike with a more generic, Kinematix a more sophisticated
approach. The main implications drawn from the case studies cover inter-industry partnership
choices, the potential of motivational force based on Social Media, the transformation of the
patient-caregiver relationship, the barriers to overcome originating from primary healthcare
players, as well as specific dynamic and adaptive capabilities. The paper concludes with
suggestions to stimulate future research to find solutions and ways to transform healthcare in
a more advanced, forward-looking sector.Esta tese tem como objectivo perceber a aplicação de modelos de negócios digitais no sector
da saúde e entender o seu sucesso. As oportunidades deste modelo de negócio são várias
contudo o seu sucesso na aplicação requer sensibilidade e conhecimento especifico. Este
trabalho propõe directrizes para lidar com este tipo de abordagem e realça as principais
características deste modelo de negócio como turbulência, perturbações devido a esta nova
visão de negócio, fronteiras da Indústria mal definidas e explica o modelo VISOR de Omar El
Sawy em todas as suas componentes: Proposição de Valor, Interface, Plataforma de Serviço
Modelo de Organização e de Receita. O corpo desta tese analisa os casos de estudo Nike+ e
Kinematix descrevendo a história de um primeiro modelo já incumbente e de outro que é
recente, respectivamente. Este processo pretende compreender duas estratégias diferentes em
modelos de negócio digitais no sector da saúde. Ambas as empresas operam no segmento de
E-saúde, especificamente roupa de corrida. Nike adopta uma abordagem mais genérica
enquanto Kinematix tem uma abordagem mais específica. A principal implicação do estudo
dos casos são parcerias inter-indústria, o potencial das redes socias em factores motivacionais,
a transformação da relação paciente-cuidador, as barreiras a ultrapassar provenientes dos
fornecedores de cuidados de saúde primários, bem como as dinâmicas e capacidades
adaptativas. No fim deste trabalho são enumeradas sugestões para pesquisa académica futura
com vista a transformar os cuidados de saúde num sector mais moderno e avançado
Barriers to IoT Business Model Innovation
The vision of an Internet of Things (IoT), in which virtually all physical things become connected to the internet, promises enormous economic potential. The IoT might disrupt entire industries and it forces companies to rethink their current business activities. In light of these challenges, research on business model innovation (BMI) can offer promising insights. This research paper aims to contribute to the emerging BMI literature by identifying innovation barriers in an IoT context. 16 barriers are identified on the basis of ten expert interviews that were conducted with employees from five multinational companies. The contributions of our study might lay a fruitful ground for future research, e.g. in respect to prescriptive IoT BMI processes or quantitative investigations of IoT success
Work extraction from unknown quantum sources
Energy extraction is a central task in thermodynamics. In quantum physics,
ergotropy measures the amount of work extractable under cyclic Hamiltonian
control. As its full extraction requires perfect knowledge of the initial
state, however, it does not characterize the work value of unknown or untrusted
quantum sources. Fully characterizing such sources would require quantum
tomography, which is prohibitively costly in experiments due to the exponential
growth of required measurements and operational limitations. Here, we therefore
derive a new notion of ergotropy applicable when nothing is known about the
quantum states produced by the source, apart from what can be learned by
performing only a single type of coarse-grained measurement. We find that in
this case the extracted work is defined by the Boltzmann and observational
entropy, in cases where the measurement outcomes are, or are not, used in the
work extraction, respectively. This notion of ergotropy represents a realistic
measure of extractable work, which can be used as the relevant figure of merit
to characterize a quantum battery.Comment: 5+1(Appendix)+7(Supplemental) pages, 4 figures. Comments and
questions welcome. v2: changed the interpretation of the coarse-grained
extraction operations (former eq (6), now eq (7)). Appendix with examples
added. Results unchanged. v3: technical details moved into a short appendix.
Added explanatory figure for the extraction operations. Added extra proof in
the Supplemental Materia
Sparse Power Factorization: Balancing peakiness and sample complexity
In many applications, one is faced with an inverse problem, where the known
signal depends in a bilinear way on two unknown input vectors. Often at least
one of the input vectors is assumed to be sparse, i.e., to have only few
non-zero entries. Sparse Power Factorization (SPF), proposed by Lee, Wu, and
Bresler, aims to tackle this problem. They have established recovery guarantees
for a somewhat restrictive class of signals under the assumption that the
measurements are random. We generalize these recovery guarantees to a
significantly enlarged and more realistic signal class at the expense of a
moderately increased number of measurements.Comment: 18 page
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