scholarly journals The Adoption of Big Data Analytics Among Manufacturing Small and Medium Enterprises During Covid-19 Crisis in Malaysia

2021 ◽  
Author(s):  
Chun-Hong Loh ◽  
Ai-Ping Teoh
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Small And Medium Enterprises ◽  
Big Data Analytics ◽  
Medium Enterprises

scholarly journals JAPAN’S EXPERIENCE IN USING ANALYTICS OF BIG DATA TO REDUCE CREDIT RISK IN FINANCING SMALL AND MEDIUM ENTERPRISES

2019 ◽  
pp. 182-187
Author(s):  
S. Matveevskii
Keyword(s):  
Big Data ◽  
Credit Risk ◽  
Data Analytics ◽  
Small And Medium Enterprises ◽  
Big Data Analytics ◽  
Subject Area ◽  
Development Bank ◽  
Financial Model ◽  
Bank Account ◽  
Medium Enterprises

The experience of Japanese experts in using big data analytics to reduce credit risk when financing small and medium-sized enterprises has been reviewed. Three multiple regression models were used to predict the likelihood of medium-sized enterprises default. The results of the study have showed, that the bank account model complements the financial model well, which will allow credit organizations to increase lending to medium-sized enterprises. It has been concluded, that the use of big data analytics requires the development of an information model of the subject area, which will provide a significant improvement in lending to medium-sized enterprises in Russia. The experience of the Asian Development Bank in researching the activities of medium-sized enterprises shows the practical possibility of using big data analytics by any development bank.

Big data analytics adoption model for small and medium enterprises

2020 ◽  
Vol 11 (4) ◽  
pp. 483-513 ◽  
Author(s):  
Parisa Maroufkhani ◽  
Wan Khairuzzaman Wan Ismail ◽  
Morteza Ghobakhloo
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Structural Equation ◽  
Small And Medium Enterprises ◽  
Big Data Analytics ◽  
Mediation Effect ◽  
Unified Framework ◽  
Content Type ◽  
Medium Enterprises ◽  
The Relationship

Purpose Big data analytics (BDA) is recognized as a turning point for firms to improve their performance. Although small- and medium-sized enterprises (SMEs) are crucial for every economy, they are lagging far behind in the usage of BDA. This study aims to provide a single and unified model for the adoption of BDA among SMEs with the integration of the technology–organization–environment (TOE) model and resource-based view. Design/methodology/approach A survey of 112 manufacturing SMEs in Iran was conducted, and the data were analysed using structural equation modelling to test the model of this study. Findings The results offer evidence of a BDA mediation effect in the relationship between technological, organizational and environmental contexts, and SMEs performance. The findings also demonstrated that technological and organizational elements are the more significant determinants of BDA adoption in the context of SMEs. In addition, the result of this study confirmed that BDA adoption could enhance the financial and market performance of SMEs. Practical implications Providing a single unified framework of BDA adoption for SMEs enables them to appreciate the importance of most influential elements (technology, organization and environment) in the adoption of BDA. Also, this study may encourage SMEs to be more willing to use BDA in their businesses. Originality/value Although there are studies on BDA adoption and firm performance among large companies, there is a lack of empirical research on SMEs, in particular, based on the TOE model. SMEs differ from large companies in terms of the availability of resources and size. Therefore, this study aimed to initiate a conceptual framework of BDA adoption for SMEs to assist them to be able to take advantage of the adoption of such technology.

scholarly journals Big data analytics-A review of data-mining models for small and medium enterprises in the transportation sector

2018 ◽  
Vol 8 (3) ◽  
pp. e1238 ◽  
Author(s):  
Siti Aishah Mohd Selamat ◽  
Simant Prakoonwit ◽  
Reza Sahandi ◽  
Wajid Khan ◽  
Manoharan Ramachandran
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Analytics ◽  
Small And Medium Enterprises ◽  
Big Data Analytics ◽  
Transportation Sector ◽  
Medium Enterprises

Risks in Adoption and Implementation of Big Data Analytics

2021 ◽  
Vol 10 (3) ◽  
pp. 1-11
Author(s):  
Rajasekhara Mouly Potluri ◽  
Narasimha Rao Vajjhala
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Data Privacy ◽  
Small And Medium Enterprises ◽  
Big Data Analytics ◽  
Small Companies ◽  
Privacy And Security ◽  
Adoption And Implementation ◽  
Research Outcome ◽  
Medium Enterprises

The research investigates the risks in adopting and implementing big data analytics in Indian micro, small, and medium enterprises (MSMEs). The researchers outlined a survey questionnaire for accumulating reactions from managers working in 50 Indian micro, small, and medium-sized enterprises on behalf of five vital commercial sectors. The application and use of big data analytics offer several significant problems for small companies as an investment in hardware and software resources are substantial. This study's findings provided experimental evidence on five critical challenges that Indian MSMEs face while adopting and implementing big data analytics: lack of human resources, data privacy and security, shortage of technological resources, deficiency of awareness, and financial implications. This study's findings emphasize the challenges that MSMEs face while leveraging big data analytics benefits. The research outcome will promote MSMEs' organizational leadership in planning and developing short-term and long-term information systems strategies.

Big Data Transforming Small and Medium Enterprises

Web Services ◽  
2019 ◽  
pp. 1368-1377
Author(s):  
Donna M. Schaeffer ◽  
Patrick C. Olson
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Business Models ◽  
Small And Medium Enterprises ◽  
Big Data Analytics ◽  
Fortune 500 ◽  
Customer Interaction ◽  
The Media ◽  
Medium Enterprises ◽  
Data Transforming

The terms big data, analytics, and business intelligence are often used in the media, with much attention on Fortune 500 enterprises. Small and medium-sized businesses (SMEs) also handle large amounts of data, and it is important to their decision making and planning. This chapter explores options for handling Big Data in SMEs. It presents a framework that considers not just the volume of data, but the variety of types of data, the velocity in which data is created and transmitted, the importance of data veracity, and its value in transforming small and medium-sized enterprises. SMEs need to work with big data, and doing so will impact their business models and require them transform themselves. Their transformation will be ongoing because all indicators show that the volume of data is rising and will continue to do so simply because of the trends related to customer interaction.

Big Data Transforming Small and Medium Enterprises

2015 ◽  
pp. 106-115
Author(s):  
Donna M. Schaeffer ◽  
Patrick C. Olson
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Business Models ◽  
Small And Medium Enterprises ◽  
Big Data Analytics ◽  
Fortune 500 ◽  
Customer Interaction ◽  
The Media ◽  
Medium Enterprises ◽  
Data Transforming

The terms big data, analytics, and business intelligence are often used in the media, with much attention on Fortune 500 enterprises. Small and medium-sized businesses (SMEs) also handle large amounts of data, and it is important to their decision making and planning. This chapter explores options for handling Big Data in SMEs. It presents a framework that considers not just the volume of data, but the variety of types of data, the velocity in which data is created and transmitted, the importance of data veracity, and its value in transforming small and medium-sized enterprises. SMEs need to work with big data, and doing so will impact their business models and require them transform themselves. Their transformation will be ongoing because all indicators show that the volume of data is rising and will continue to do so simply because of the trends related to customer interaction.

Big Data Analytics: The Next Big Thing

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

Strategy in Discovery Mode - Wie Big Data & Analytics strategisches Denken verdrängen kann

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

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.

A Review on Big Data Analytics Tools in Context with Scalability

2019 ◽  
Vol 7 (2) ◽  
pp. 273-277
Author(s):  
Ajay Kumar Bharti ◽  
Neha Verma ◽  
Deepak Kumar Verma
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics
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