Publicação
Do Big Data Analytics Competencies Improve Banks’ Financial Performance? An Investigation using Portuguese data
| dc.contributor.advisor | Bravo, Jorge Miguel Ventura | |
| dc.contributor.advisor | Mata, Mário Nuno | |
| dc.contributor.author | Martins, Jéssica Cristina Nunes | |
| dc.date.accessioned | 2022-03-14T18:17:53Z | |
| dc.date.available | 2022-03-14T18:17:53Z | |
| dc.date.issued | 2022-02-01 | |
| dc.description | Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and Management | pt_PT |
| dc.description.abstract | Over the last few years, big data has been a popular technological advancement in games and changes as a virtual 'border' of a wide variety of IT-driven technologies and information-enabling possibilities. Due to technological advances, the internet, handheld machinery, decision support systems, transmission, and computations, the idea of big data was propelled by rapids in data processing and storage. The aim of our study is to determine how Portuguese banks' big data analytics capabilities will help them to improve their financial performance: the efficacy of the audit committee as a mediator and process-oriented dynamic capabilities (PODC) as a moderator. Companies have recently met with unpredictable environmental factors and shifts, and increasingly competitive trends. To obtain a competitive edge, attain superior performance and success and increase long-term survival and longevity, they have to apply, introduce and apply suitable techniques and strategies. Techniques and methods from a variety of fields have been examined rigorously and analytically. In this report, the audit committee is one of the most effective tools and procedures used by businesses, and it is a key driver of successful organizational mechanisms. In comparison, the audit committee's monitoring functions have been considerably greater and more effective. The study adopted a survey research design. Simple random sampling was used to ensure that those employees were found at their workplaces who were used for the study. This design was quantitative to allow for descriptive and inferential analysis. The data has been collected within one month (i.e., February 2021 to May 2021). As it was collected at one time so the design is cross-sectional in nature. Scholars received data from 330 target respondents, including hardcopies and softcopies due to the COVID-19 pandemic in the different public and private banks of Portuguese. The current study makes a substantial addition to big data analytics management and firm performance, and it has a wide range of applications. Because no previous study has directly addressed the moderating behavior of Process-oriented dynamic capability and the mediating role of audit committee effectiveness in this setting, the function played by the current study is quite important. Furthermore, the convergence of organizational resources examined in this study to assess a firm's big data analytics competency has never been attempted before. Using the resource-based Theory (RBT) and dynamic capabilities view (DCV) as theoretical lenses, the study investigates the relationship between BDA capabilities and firm performance. The main justification for adopting these two points of view is that the technological capability of utilizing BDA requires various additional firm-specific resources that can eventually contribute to increased performance. | pt_PT |
| dc.identifier.tid | 202962512 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/134447 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Big Data Analytics Competency | pt_PT |
| dc.subject | Process-oriented dynamic capabilities | pt_PT |
| dc.subject | Audit committee effectiveness | pt_PT |
| dc.subject | Firm Financial performance | pt_PT |
| dc.subject | Portuguese | pt_PT |
| dc.title | Do Big Data Analytics Competencies Improve Banks’ Financial Performance? An Investigation using Portuguese data | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Estatística e Gestão de Informação, especialização em Análise e Gestão de Risco | pt_PT |
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