Factors influencing Brazilian internal auditors' behavioural intention to adopt big data analytics

2020 ◽  
Vol 4 (3) ◽  
pp. 217
Author(s):  
Marcio Kawahara Iguma ◽  
Edson Luiz Riccio
Author(s):  
Amin Khalil Alsadi ◽  
Thamir Hamad Alaskar ◽  
Karim Mezghani

Supported by the literature on big data, supply chain management (SCM), and resource-based theory (RBT), this study aims to evaluate the organizational variables that influence the intention of Saudi SCM professionals to adopt big data analytics (BDA) in SCM. A survey of 220 supply chain respondents revealed that both top management support and data-driven culture have a high significant influence on their intention to adopt BDA. However, the firm entrepreneurial orientation showed no significant effect. Also, the findings revealed that supply chain connectivity positively moderates the link between top management support and intention. This study contributes to the practical field, offering valuable insights for decision makers considering BDA adoption in SCM. It also contributes to the literature by helping minimize the research gap in BDA adoption in the Saudi context.


2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Douglas Omoregie Aghimien ◽  
Matthew Ikuabe ◽  
Clinton Aigbavboa ◽  
Ayodeji Oke ◽  
Wealthy Shirinda

The construction industry has been producing massive data that can be transformed for improved decision-making and better construction project delivery. However, the industry has been adjudged as a slow adopter of digital technologies such as big data analytics (BDA) to improve its service delivery. The implication of this slow adoption is the lack of innovativeness and unsustainable project delivery that has characterised the industry in most countries, particularly in developing ones like South Africa. Therefore, this study assessed the intention to adopt BDA by construction organisations using the unified theory of technology adoption and use of technology (UTAUT) model. A post-positivism philosophical stance was employed, which informed the use of quantitative research with a questionnaire designed to solicit information from construction organisations in South Africa. Data analysis was done using Cronbach alpha to test for reliability and Fuzzy Synthetic Evaluation to evaluate the impact of the different constructs of the UTAUT on the adoption of BDA by construction organisations in South Africa. The study found that variables relating to facilitating conditions, performance expectancy, and social influence will significantly impact an organisation’s intention to adopt BDA. However, issues surrounding effort expectancy, resistance to use, and perceived risk cannot be overlooked as they also have high impact levels. The study provides an excellent theoretical and practical contribution to the existing discourse on construction digitalisation.


2019 ◽  
Vol 54 (5) ◽  
pp. 20
Author(s):  
Dheeraj Kumar Pradhan

2020 ◽  
Vol 49 (5) ◽  
pp. 11-17
Author(s):  
Thomas Wrona ◽  
Pauline Reinecke

Big Data & Analytics (BDA) ist zu einer kaum hinterfragten Institution für Effizienz und Wettbewerbsvorteil von Unternehmen geworden. Zu viele prominente Beispiele, wie der Erfolg von Google oder Amazon, scheinen die Bedeutung zu bestätigen, die Daten und Algorithmen zur Erlangung von langfristigen Wettbewerbsvorteilen zukommt. Sowohl die Praxis als auch die Wissenschaft scheinen geradezu euphorisch auf den „Datenzug“ aufzuspringen. Wenn Risiken thematisiert werden, dann handelt es sich meist um ethische Fragen. Dabei wird häufig übersehen, dass die diskutierten Vorteile sich primär aus einer operativen Effizienzperspektive ergeben. Strategische Wirkungen werden allenfalls in Bezug auf Geschäftsmodellinnovationen diskutiert, deren tatsächlicher Innovationsgrad noch zu beurteilen ist. Im Folgenden soll gezeigt werden, dass durch BDA zwar Wettbewerbsvorteile erzeugt werden können, dass aber hiermit auch große strategische Risiken verbunden sind, die derzeit kaum beachtet werden.


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