scholarly journals Innovative Mobile Application for Measuring Big Data Maturity: Case of SMEs in Thailand

2020 ◽  
Vol 14 (18) ◽  
pp. 87
Author(s):  
Santisook Limpeeticharoenchot ◽  
Nagul Cooharojananone ◽  
Thira Chanvanakul ◽  
Nuengwong Tuaycharoen ◽  
Kanokwan Atchariyachanvanich
Keyword(s):  
Big Data ◽  
Mobile Application ◽  
Web Application ◽  
Data Analytics ◽  
Latent Class ◽  
Big Data Analytics ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Easy Access ◽  
Executive Officers

A Big Data maturity model (BDMM) is one of the key tools for Big Data assessment and monitoring, and a guideline for maximizing the usage and opportunity of Big Data in organizations. The development of a BDMM for SMEs is a new concept and is challenging in terms of development, application, and adoption. This article aims to create the novel online adaptive BDMM via responsive web application for SMEs. We develop the BDMM API and a responsive web application for easy access via mobile phone. We developed a model by analyzing the factors impacting the success of implementing Big Data Analytics (BDA) in SMEs based on literature reviews. The model was verified by conducting a survey of 180 SMEs in Thailand, interviewed against four extracted domains. Then, the scoring and classified levels for the model was developed through Latent Class Analysis (LCA) to depict four levels of each domain and four final maturity levels to create an adaptive model. As the experimental results with 33 users including executive officers, managers, IT and data analytic officers .The user acceptance for our mobile application using TAM indicates that executive officers group and non-executive group satisfied perceived usefulness, perceived ease of use, and intention to use factor. Use cases of the application include SMEs monitoring for their Big Data Analytics capability for improvement, and the Government Agency providing proper support on SMEs’ level of competency.

scholarly journals Integration of IoT, Data Analytics and Mobile Application towards Digitisation Facilities Management: A Case Study

2021 ◽  
Vol 15 (22) ◽  
pp. 154
Author(s):  
Irwan Mohammad Ali ◽  
Mohd Nasrun Mohd Nawi ◽  
Md Yusof Hamid ◽  
Fazly Izwan A Jalil ◽  
Baharinshah Hussain
Keyword(s):  
Big Data ◽  
Mobile Phone ◽  
Paradigm Shift ◽  
Mobile Application ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Facilities Management ◽  
Success Story ◽  
Mobile Phone Application

<p>Facilities Management (FM) industry players must be mindful of the current economic digitisation. It aims to empower the community and industry players with digital skills and digital-based businesses. Positively, this also will benefit FM industry players. Therefore, many FM organisations are starting to take advantage on IoT, big data analytics and mobile phone application in their activities. This paper utilised a literature review to discover the application of IoT, big data analytics and mobile application in FM processes. Then, a case study on Al Nabooda Chulia Facilities Management Co LLC (AN.C) success story as the recipient of Urbanise Smart City Pioneer Award 2017 were cross-examined on the tools they use in digitisation FM. The novelty from the integration of IoT, big data analytics and mobile phone application towards digitisation FM has significantly reducing management costs and improving facilities performance and service quality. The paper highlight an example of digitisation of FM activities that successfully optimising and innovating the current FM practices with the paradigm shift from cost management towards value creation in the future.<strong> </strong></p>

Big Data Analytics in Healthcare

2019 ◽  
Vol 10 (4) ◽  
pp. 45-58 ◽  
Author(s):  
Hiba Asri ◽  
Hajar Mousannif ◽  
Hassan Al Moatassime
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Real Time ◽  
Mobile Application ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Data Mining Algorithm ◽  
Time Data ◽  
Real World Data ◽  
Data Platform

Sensors and mobile phones shine in the Big Data area due to their capabilities to retrieve a huge amount of real-time data; which was not possible previously. In the specific field of healthcare, we can now collect data related to human behavior and lifestyle for better understanding. This pushed us to benefit from such technologies for early miscarriage prediction. This research study proposes to combine the use of Big Data analytics and data mining models applied to smartphones real-time generated data. A K-means data mining algorithm is used for clustering the dataset and results are transmitted to pregnant woman to make quick decisions; with the intervention of her doctor; through an android mobile application that we created. As well, she receives recommendations based on her behavior. We used real-world data to validate the system and assess its performance and effectiveness. Experiments were made using the Big Data Platform Databricks.

Users’ perception toward Bitcoin Green with big data analytics

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emna Mnif ◽  
Isabelle Lacombe ◽  
Anis Jarboui
Keyword(s):  
Big Data ◽  
Perceived Control ◽  
Positive Emotions ◽  
Empirical Work ◽  
Big Data Analytics ◽  
Text Messages ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Perceived Ease Of Use ◽  
Content Type

Purpose Nowadays, Bitcoin is facing many environmental problems arising from the proof of work based on blockchain. For this reason, Bitcoin Green (BITG) has been created and would solve these issues. The purpose of this paper is to visualize the users’ perception toward BITG through Twitter text analysis. Design/methodology/approach The big data used in this study includes two sources. The first data were extracted from the “Google Trends” engine during the period between 20 September 2015 and 15 September 2020. The second data were extracted from the Twitter application. This research explores the perceived ease of use, the perceived usefulness, the social influence, the perceived control and the user attitudes toward BITG. Therefore, lexicon-based sentiment analysis techniques combined with different dictionaries are built to visualize the drivers of investor attitudes toward the BITG using Twitter text messages. Besides, this study has checked the validity of two main assumptions using the normality (Jarque-Bera) and Kruskal-Wallis rank sum tests capable to conclude whether users mostly perceive BITG as a sustainable technology. Findings This empirical work affords insights into users’ intentions by exploring the drivers of BITG perception. The results show that users positively perceive the use of BITG as a sustainable blockchain. Besides, its usefulness is more appreciated from its ethical and technological characteristics, and its perceived application is mainly based on investment and coin offering use. Similarly, users are mostly showing positive emotions toward BITG. Research limitations/implications Tweets related to “BITG” are not as voluminous as the other cryptocurrencies like Bitcoin and Ethereum, which make it difficult to extract all the characteristics and use cases. Originality/value To the best of the authors’ knowledge, this work is the first one that uses the theory of planned behavior and the theory of acceptance model to explore cognitive factors in understanding investor intentions in adopting BITG.

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.

Sustaining Job Performance through Technology Acceptance with Usage of Whatsapp Mobile Application

2020 ◽  
Vol 5 (1) ◽  
pp. 123
Author(s):  
Nor Hayati Kassim ◽  
Norlina Mohamed Noor ◽  
Jati Kasuma ◽  
Juliza Saleh ◽  
Ceaser Dealwis ◽  
...  
Keyword(s):  
Job Performance ◽  
Technology Acceptance ◽  
Mobile Applications ◽  
Mobile Application ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Maximum Efficiency ◽  
Perceived Ease Of Use ◽  
Positive Attitudes ◽  
Willingness To Use

Companies are now recognizing that their employees require a spectrum of mobile applications in order to achieve maximum efficiency at the workplace. Mobile applications such as WeChat, Twitter and WhatsApp via smartphones have become influential tools and extensively used by employees at the workplace. This state-of-the-art technology in communication has penetrated various fields, including routine administrative jobs at the workplace. The objective of this research is toinvestigate the acceptance of the WhatsApp mobile application for formal use among support staff at The Commission of the City of Kuching North, Sarawak (DBKU). Perceived usefulness, perceived ease of use and behavioral intention of the users in using WhatsApp are the variables measured for job performance. The researchers utilized convenience sampling, whereby a total of 105 employees from two departments participated in the investigation. Data was collected using a set of selfadministered questionnaires which was adapted from Davis. The findings revealed that perceived usefulness and perceived ease of use of WhatsApp as a means of communication were significant for job performance at DBKU. The employees felt more competent during their formal interaction at the workplace as less effort was needed while using WhatsApp. The existence of features which were user-friendly and easy operational functions helped to create positive attitudes when utilizing the application. Faster feedback, ease of use, and convenience were some of the reasons for the employees’ willingness to use WhatsApp for communication at the workplace.

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
Sign in / Sign up

Export Citation Format

Share Document