D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Business and Management D-index 62 Citations 12,424 132 World Ranking 186 National Ranking 3

Overview

What is he best known for?

The fields of study he is best known for:

  • Marketing
  • The Internet
  • Information technology

Keng-Boon Ooi mainly investigates Marketing, Knowledge management, Response rate, Technology acceptance model and Supply chain. Marketing and Social influence are frequently intertwined in his study. His Social influence study incorporates themes from Control variable, Affect and Consumer behaviour.

His study in the fields of Knowledge sharing under the domain of Knowledge management overlaps with other disciplines such as Information technology, Original research, Empirical evidence and Manufacturing sector. His study looks at the relationship between Supply chain and topics such as Industrial organization, which overlap with Finance and Intellectual capital. His research in Emerging markets focuses on subjects like Mobile device, which are connected to Advertising.

His most cited work include:

  • What drives Malaysian m‐commerce adoption? An empirical analysis (334 citations)
  • Predicting consumer decisions to adopt mobile commerce (301 citations)
  • Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach (197 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Knowledge management, Marketing, Total quality management, Structural equation modeling and Mobile payment. His biological study spans a wide range of topics, including Manufacturing and Conceptual model. As part of the same scientific family, Keng-Boon Ooi usually focuses on Marketing, concentrating on Social influence and intersecting with Consumer behaviour.

His study in Total quality management is interdisciplinary in nature, drawing from both Service, Strategic planning and Quality management. His work in Structural equation modeling covers topics such as Expectancy theory which are related to areas like Mobile device. His study explores the link between Mobile payment and topics such as Mobile technology that cross with problems in Service, Advertising, Unified theory of acceptance and use of technology and Artificial neural network.

He most often published in these fields:

  • Knowledge management (39.10%)
  • Marketing (34.62%)
  • Total quality management (23.72%)

What were the highlights of his more recent work (between 2019-2021)?

  • Mobile payment (15.38%)
  • Mobile technology (16.03%)
  • Knowledge management (39.10%)

In recent papers he was focusing on the following fields of study:

Keng-Boon Ooi mainly focuses on Mobile payment, Mobile technology, Knowledge management, Artificial neural network and Telecommunications. Keng-Boon Ooi combines subjects such as Affect, Mobile commerce and Artificial intelligence with his study of Mobile payment. His studies in Mobile commerce integrate themes in fields like Cash and Conceptual model.

His Mobile technology research is multidisciplinary, relying on both Structural equation modeling and Advertising. Keng-Boon Ooi has researched Knowledge management in several fields, including Online advertising, Scale and Service provider. His Artificial neural network study combines topics in areas such as Developing country, Robustness and Service.

Between 2019 and 2021, his most popular works were:

  • Time to seize the digital evolution: Adoption of blockchain in operations and supply chain management among Malaysian SMEs (48 citations)
  • Predicting mobile wallet resistance: A two-staged structural equation modeling-artificial neural network approach (30 citations)
  • Unearthing the determinants of Blockchain adoption in supply chain management (17 citations)

In his most recent research, the most cited papers focused on:

  • Marketing
  • The Internet
  • Information technology

Supply chain management, Mobile payment, Mobile technology, Blockchain and Industrial organization are his primary areas of study. His research integrates issues of Telecommunications, Retail industry, Mobile commerce and Artificial intelligence in his study of Mobile payment. His Artificial intelligence research incorporates elements of Novelty and Knowledge management.

The study incorporates disciplines such as Artificial neural network and Structural equation modeling in addition to Novelty. Keng-Boon Ooi interconnects Expectancy theory and Transparency in the investigation of issues within Blockchain. His Industrial organization research incorporates themes from Business process and Immutability.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

What drives Malaysian m‐commerce adoption? An empirical analysis

Toh Tsu Wei;Govindan Marthandan;Alain Yee Loong Chong;Keng Boon Ooi.
Industrial Management and Data Systems (2009)

655 Citations

Predicting consumer decisions to adopt mobile commerce

Alain Yee-Loong Chong;Felix T.S. Chan;Keng-Boon Ooi.
decision support systems (2012)

403 Citations

Online banking adoption: an empirical analysis

Alain Yee Loong Chong;Keng Boon Ooi;Binshan Lin;Boon In Tan.
International Journal of Bank Marketing (2010)

378 Citations

NFC mobile credit card: The next frontier of mobile payment?

Garry Wei-Han Tan;Keng-Boon Ooi;Siong-Choy Chong;Teck-Soon Hew.
Telematics and Informatics (2014)

347 Citations

Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach

Lai-Ying Leong;Teck-Soon Hew;Garry Wei-Han Tan;Keng-Boon Ooi.
Expert Systems With Applications (2013)

331 Citations

Factors affecting the Adoption Level of C-Commerce: An Empirical Study

Alain Yee-Loong Chong;Binshan Lin;Keng-Boon Ooi;Murali Raman.
Journal of Computer Information Systems (2015)

301 Citations

What catalyses mobile apps usage intention: an empirical analysis

Jun-Jie Hew;Voon-Hsien Lee;Keng-Boon Ooi;June Wei.
Industrial Management and Data Systems (2015)

293 Citations

Does TQM influence employees' job satisfaction? An empirical case analysis

Keng Boon Ooi;Nooh Abu Bakar;Veeri Arumugam;Lorraine Vellapan.
International Journal of Quality & Reliability Management (2007)

279 Citations

TQM and customer satisfaction in Malaysia's service sector

Wen Yi Sit;Keng Boon Ooi;Binshan Lin;Alain Yee Loong Chong.
Industrial Management and Data Systems (2009)

268 Citations

The effects of convenience and speed in m-payment

Aik-Chuan Teo;Garry Wei-Han Tan;Keng-Boon Ooi;Teck-Soon Hew.
Industrial Management and Data Systems (2015)

263 Citations

Best Scientists Citing Keng-Boon Ooi

Alain Yee-Loong Chong

Alain Yee-Loong Chong

University of Nottingham Ningbo China

Publications: 28

Yogesh K. Dwivedi

Yogesh K. Dwivedi

Swansea University

Publications: 17

Zillur Rahman

Zillur Rahman

Indian Institute of Technology Roorkee

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Amandeep Dhir

Amandeep Dhir

University of Agder

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Felix T.S. Chan

Felix T.S. Chan

Hong Kong Polytechnic University

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Tiago Oliveira

Tiago Oliveira

Universidade Nova de Lisboa

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Nripendra P. Rana

Nripendra P. Rana

Qatar University

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Michael D. Williams

Michael D. Williams

Swansea University

Publications: 9

Samuel Fosso Wamba

Samuel Fosso Wamba

Toulouse Business School

Publications: 8

Binshan Lin

Binshan Lin

Louisiana State University in Shreveport

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Pedro Soto-Acosta

Pedro Soto-Acosta

University of Murcia

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Ali Tarhini

Ali Tarhini

Sultan Qaboos University

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Heikki Karjaluoto

Heikki Karjaluoto

University of Jyväskylä

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Angappa Gunasekaran

Angappa Gunasekaran

Pennsylvania State University

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Kannan Govindan

Kannan Govindan

University of Southern Denmark

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Rameshwar Dubey

Rameshwar Dubey

Liverpool John Moores University

Publications: 4

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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