Strategic Groups in the Portuguese Banking Industry

2019 ◽  
pp. 1-29
Author(s):  
Albérico Travassos Rosário ◽  
Antonio Carrizo Moreira ◽  
Pedro Macedo
Keyword(s):  
Data Collection ◽  
Banking Industry ◽  
Retail Banking ◽  
Strategic Groups ◽  
Competitive Strategies ◽  
Strategic Actions ◽  
Banking Institutions ◽  
Over Time ◽  
Competitive Structure

This chapter analyzes the retail banking behavior in Portugal for the period between 2008 and 2010. The data collection took place through the accounting consultation of the reports and accounts of the years under analysis. The selected variables reflect the strategic actions of retail banking during the period under analysis, and it can be argued that retail banking in Portugal has clear differences among players over time. In particular, banking institutions have different competitive strategies, the strategic groups do not have similar resources, and strategies also differ between strategic groups. This reflects the competitive structure of the national retail banking industry.

scholarly journals Competitive dynamics of strategic groups in the Portuguese banking industry

2021 ◽  
Vol 2021-02-25 (OLF) ◽  
Author(s):  
Albérico Travassos Rosário ◽  
◽  
António Carrizo Moreira ◽  
Pedro Macedo ◽  
◽  
...  
Keyword(s):  
Banking Industry ◽  
Retail Banking ◽  
Competitive Dynamics ◽  
Economic Assistance ◽  
Strategic Groups ◽  
Competitive Strategies ◽  
Strategic Group ◽  
European Central ◽  
Assistance Programme ◽  
The International Monetary Fund

The objective of this paper is to analyse the retail banking behaviour in Portugal (2008–2010, 2011–2013 and 2014–2016), by taking into account the financial and economic assistance programme (FEAP) – monitored by the European Commission, the European Central Bank and the International Monetary Fund – that Portugal went through and that started in 2011. With competitive dynamics it is possible to understand the evolution of competitive strategies of the institutions of a strategic group within a given time horizon. Data were collected after consultation of reports and accounts of Banks from Banco de Portugal database. The results were analysed and discussed in light of the theory of strategic groups and their competitive dynamics allows us to conclude that: Banks implemented different competitive strategies; Strategic groups have dissimilar resources; and Strategic groups display different strategies. The 2008–2010 period can be considered as a ‘deregulated’ period, the 2011–2013 as a period of ‘imposed regulation’, and the 2014–2016 as a period of ‘strategic consolidation’ with strategic changes that have prompted strategic groupings of the various institutions as consequence of a low mobility barrier strategy.

Percutaneous Tracheostomy: A Multidisciplinary Approach

2008 ◽  
Vol 18 (2) ◽  
pp. 87-98 ◽  
Author(s):  
Vinciya Pandian ◽  
Thai Tran Nguyen ◽  
Marek Mirski ◽  
Nasir Islam Bhatti
Keyword(s):  
Health Care ◽  
Quality Assurance ◽  
Data Collection ◽  
Health Care Professionals ◽  
Multidisciplinary Approach ◽  
Percutaneous Tracheostomy ◽  
Johns Hopkins Hospital ◽  
Prospective Data ◽  
Comprehensive Service ◽  
Over Time

Abstract The techniques of performing a tracheostomy has transformed over time. Percutaneous tracheostomy is gaining popularity over open tracheostomy given its advantages and as a result the number of bedside tracheostomies has increased necessitating the need for a Percutaneous Tracheostomy Program. The Percutaneous Tracheostomy Program at the Johns Hopkins Hospital is a comprehensive service that provides care to patients before, during, and after a tracheostomy with a multidisciplinary approach aimed at decreasing complications. Education is provided to patients, families, and health-care professionals who are involved in the management of a tracheostomy. Ongoing prospective data collection serves as a tool for Quality Assurance.

Kajian Interaksi Obat Metformin pada Pasien Diabetes Mellitus

2019 ◽  
Vol 8 (2) ◽  
pp. 55-58
Author(s):  
Havizur Rahman ◽  
Teresia Anggi Octavia
Keyword(s):  
Diabetes Mellitus ◽  
Drug Interaction ◽  
Data Collection ◽  
Drug Interactions ◽  
Degenerative Disease ◽  
Moderate Severity ◽  
Purposive Sampling ◽  
Chronic Degenerative Disease ◽  
Over Time ◽  
Diabetes Melitus

Diabetes melitus merupakan penyakit degeneratif kronis yang apabila tidak ditangani dengan tepat, lama kelamaan bisa timbul berbagai komplikasi, ini cenderung menyebabkan pasien mendapatkan banyak obat dalam satu resep yang dapat menimbulkan interaksi antar obat. Tujuan dari penelitian ini adalah mengetahui persentase terjadinya interaksi obat metformin secara teori serta mengkaji efek yang mungkin timbul dan solusinya. Teknik pengambilan data dengan purpossive sampling, yaitu resep pasien rujuk balik yang menderita diabetes mellitus yang menggunakan metformin. Data yang diperoleh ditemukan bahwa obat yang berinteraksi dengan metformin dengan tingkat keparahan minor ialah sebesar 60%. Kemudian untuk tingkat keparahan moderat ialah sebesar 20%. Sedangkan untuk tingkat keparahan mayor tidak ditemukan. Dari tabel diatas juga dapat diketahui bahwa terdapat 4 obat yang saling berinteraksi dengan metformin, sedangkan untuk obat yang tidak saling berinteraksi dengan metformin terdapat 9 obat. Jumlah obat yang berinteraksi secara teori sebesar 6,85% dan yang tidak berinteraksi 93,15%. Terdapat interaksi obat metformin dengan beberapa obat yaitu furosemid, lisinopril, acarbose dan ramipril.   Kata kunci: interaksi obat, metformin, diabetes mellitus   STUDY OF METFORMIN INTERACTION IN MELLITUS DIABETES PATIENTS   ABSTRACT Mellitus is a chronic degenerative disease which if not handled properly, over time can arise various complications, this tends to cause patients to get many drugs in one recipe that can cause interactions between drugs. The purpose of this study is to determine percentage of metformin drug interactions in theory and examine the effects that may arise and solutions. Data collection techniques using purposive sampling, which is a recipe for reconciliation patients who suffer from diabetes mellitus using metformin. The data obtained it was found that drugs that interact with metformin with minor severity were 60%. Then for moderate severity is 20%. Whereas the major severity was not found. From the table above it can also be seen that there are 4 drugs that interact with metformin, while for drugs that do not interact with metformin there are 9 drugs. The number of drugs that interacted theoretically was 6.85% and 93.15% did not interact. An interaction of the drug metformin with several drugs namely furosemide, lisinopril, acarbose and ramipril.   Keywords: drug interaction, metformin, diabetes mellitus

Developing a sustainable Digital Health Innovation Ecosystem in a rural and resource-poor region: A monitored networking approach (Preprint)

2020 ◽  
Author(s):  
Arunangsu Chatterjee ◽  
Sebastian Stevens ◽  
Sheena Asthana ◽  
Ray B Jones
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Data Collection ◽  
Digital Health ◽  
Resource Poor Setting ◽  
Quadruple Helix ◽  
Innovation Ecosystem ◽  
Resource Poor ◽  
Quadruple Helix Model ◽  
Over Time

BACKGROUND Digital health (DH) innovation ecosystems (IE) are key to the development of new e-health products and services. Within an IE, third parties can help promote innovation by acting as knowledge brokers and the conduits for developing inter-organisational and interpersonal relations, particularly for smaller organisations. Kolehmainen’s quadruple helix model suggests who the critical IE actors are, and their roles. Within an affluent and largely urban setting, such ecosystems evolve and thrive organically with minimal intervention due to favourable economic and geographical conditions. Facilitating and sustaining a thriving DH IE within a resource-poor setting can be far more challenging even though far more important for such peripheral economics and the health and well-being of those communities. OBJECTIVE Taking a rural and remote region in the UK, as an instance of an IE in a peripheral economy, we adapt the quadruple helix model of innovation, apply a monitored social networking approach using McKinsey’s Three Horizons of growth to explore: • What patterns of connectivity between stakeholders develop within an emerging digital health IE? • How do networks develop over time in the DH IE? • In what ways could such networks be nurtured in order to build the capacity, capability and sustainability of the DH IE? METHODS Using an exploratory single case study design for a developing digital health IE, this study adopts a longitudinal social network analysis approach, enabling the authors to observe the development of the innovation ecosystem over time and evaluate the impact of targeted networking interventions on connectivity between stakeholders. Data collection was by an online survey and by a novel method, connection cards. RESULTS Self-reported connections between IE organisations increased between the two waves of data collection, with Small and Medium-sized Enterprises (SMEs) and academic institutions the most connected stakeholder groups. Patients involvement improved over time but still remains rather peripheral to the DH IE network. Connection cards as a monitoring tool worked really well during large events but required significant administrative overheads. Monitored networking information categorised using McKinsey’s Three Horizons proved to be an effective way to organise networking interventions ensuring sustained engagement. CONCLUSIONS The study reinforces the difficulty of developing and sustaining a DH IE in a resource-poor setting. It demonstrates the effective monitored networking approach supported by Social Network Analysis allows to map the networks and provide valuable information to plan future networking interventions (e.g. involving patients or service users). McKinsey’s Three Horizons of growth-based categorisation of the networking assets help ensure continued engagement in the DH IE contributing towards its long-term sustainability. Collecting ongoing data using survey or connection card method will become more labour intensive and ubiquitous ethically driven data collection methods can be used in future to make the process more agile and responsive.

Coping with longitudinal data in research on developmental psychopathology

2006 ◽  
Vol 30 (1) ◽  
pp. 20-25 ◽  
Author(s):  
David A. Cole
Keyword(s):  
Data Collection ◽  
Longitudinal Data ◽  
Developmental Psychopathology ◽  
Careful Consideration ◽  
Two Dimensions ◽  
The Other ◽  
Outcome Variable ◽  
The Third ◽  
Data Analytic ◽  
Over Time

Many outcome variables in developmental psychopathology research are highly stable over time. In conventional longitudinal data analytic approaches such as multiple regression, controlling for prior levels of the outcome variable often yields little (if any) reliable variance in the dependent variable for putative predictors to explain. Three strategies for coping with this problem are described. One involves focusing on developmental periods of transition, in which the outcome of interest may be less stable. A second is to give careful consideration to the amount of time allowed to elapse between waves of data collection. The third is to consider trait-state-occasion models that partition the outcome variable into two dimensions: one entirely stable and trait-like, the other less stable and subject to occasion-specific fluctuations.

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