research methodology
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This research uses a descriptive design to understand the characteristics of 20 students from Lovely Professional University by collecting primary data through questionnaires and secondary data from websites. The study aims to understand students' preferences for mobile internet and the variables that affect their usage by analyzing the collected qualitative data with software like SPSS, Google Drive, and Excel.
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Institutional Knowledge at Singapore Management University
Research Collection Lee Kong Chian School Of
Business
Lee Kong Chian School of Business
10-2016
Big data and data science methods for management
research: From the Editors
Gerard GEORGE
Singapore Management University, [email油protected]
Ernst C. OSINGA
Singapore Management University, [email油protected]
Dovev LAVIE
Technion
Brent A. SCOTT
Michigan State University
DOI: https://doi.org/10.5465/amj.2016.4005
Follow this and additional works at: https://ink.library.smu.edu.sg/lkcsb_research
Part of the Management Sciences and Quantitative Methods Commons, and the Strategic
Management Policy Commons
This Editorial is brought to you for free and open access by the Lee Kong Chian School of Business at Institutional Knowledge at Singapore
Management University. It has been accepted for inclusion in Research Collection Lee Kong Chian School Of Business by an authorized administrator
of Institutional Knowledge at Singapore Management University. For more information, please email [email油protected]
Citation
GEORGE, Gerard; Ernst C. OSINGA; LAVIE, Dovev; and SCOTT, Brent A.. Big data and data science methods for management
research: From the Editors. (2016). Academy of Management Journal. 59, (5), 1493-1507. Research Collection Lee Kong Chian School
Of Business.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/4964
https://ink.library.smu.edu.sg?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
https://ink.library.smu.edu.sg/lkcsb_research?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
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https://doi.org/10.5465/amj.2016.4005
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1
FROM THE EDITORS
BIG DATA AND DATA SCIENCE METHODS FOR MANAGEMENT RESEARCH
Published in Academy of Management Journal, October 2016, 59 (5), pp. 1493-1507.
http://doi.org/10.5465/amj.2016.4005
The recent advent of remote sensing, mobile technologies, novel transaction systems, and
high performance computing offers opportunities to un.Singapore Management UniversityInstitutional Knowledge at Si.docx
Singapore Management UniversityInstitutional Knowledge at Si.docxedgar6wallace88877
油
Singapore Management University
Institutional Knowledge at Singapore Management University
Research Collection Lee Kong Chian School Of
Business
Lee Kong Chian School of Business
10-2016
Big data and data science methods for management
research: From the Editors
Gerard GEORGE
Singapore Management University, [email油protected]
Ernst C. OSINGA
Singapore Management University, [email油protected]
Dovev LAVIE
Technion
Brent A. SCOTT
Michigan State University
DOI: https://doi.org/10.5465/amj.2016.4005
Follow this and additional works at: https://ink.library.smu.edu.sg/lkcsb_research
Part of the Management Sciences and Quantitative Methods Commons, and the Strategic
Management Policy Commons
This Editorial is brought to you for free and open access by the Lee Kong Chian School of Business at Institutional Knowledge at Singapore
Management University. It has been accepted for inclusion in Research Collection Lee Kong Chian School Of Business by an authorized administrator
of Institutional Knowledge at Singapore Management University. For more information, please email [email油protected]
Citation
GEORGE, Gerard; Ernst C. OSINGA; LAVIE, Dovev; and SCOTT, Brent A.. Big data and data science methods for management
research: From the Editors. (2016). Academy of Management Journal. 59, (5), 1493-1507. Research Collection Lee Kong Chian School
Of Business.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/4964
https://ink.library.smu.edu.sg?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
https://ink.library.smu.edu.sg/lkcsb_research?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
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https://ink.library.smu.edu.sg/lkcsb?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
https://doi.org/10.5465/amj.2016.4005
https://ink.library.smu.edu.sg/lkcsb_research?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
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mailto:[email油protected]
1
FROM THE EDITORS
BIG DATA AND DATA SCIENCE METHODS FOR MANAGEMENT RESEARCH
Published in Academy of Management Journal, October 2016, 59 (5), pp. 1493-1507.
http://doi.org/10.5465/amj.2016.4005
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10-2016
Big data and data science methods for management
research: From the Editors
Gerard GEORGE
Singapore Management University, [email油protected]
Ernst C. OSINGA
Singapore Management University, [email油protected]
Dovev LAVIE
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Michigan State University
DOI: https://doi.org/10.5465/amj.2016.4005
Follow this and additional works at: https://ink.library.smu.edu.sg/lkcsb_research
Part of the Management Sciences and Quantitative Methods Commons, and the Strategic
Management Policy Commons
This Editorial is brought to you for free and open access by the Lee Kong Chian School of Business at Institutional Knowledge at Singapore
Management University. It has been accepted for inclusion in Research Collection Lee Kong Chian School Of Business by an authorized administrator
of Institutional Knowledge at Singapore Management University. For more information, please email [email油protected]
Citation
GEORGE, Gerard; Ernst C. OSINGA; LAVIE, Dovev; and SCOTT, Brent A.. Big data and data science methods for management
research: From the Editors. (2016). Academy of Management Journal. 59, (5), 1493-1507. Research Collection Lee Kong Chian School
Of Business.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/4964
https://ink.library.smu.edu.sg?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
https://ink.library.smu.edu.sg/lkcsb_research?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
https://ink.library.smu.edu.sg/lkcsb_research?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
https://ink.library.smu.edu.sg/lkcsb?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
https://doi.org/10.5465/amj.2016.4005
https://ink.library.smu.edu.sg/lkcsb_research?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
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http://network.bepress.com/hgg/discipline/642?utm_source=ink.library.smu.edu.sg%2Flkcsb_research%2F4964&utm_medium=PDF&utm_campaign=PDFCoverPages
mailto:[email油protected]
1
FROM THE EDITORS
BIG DATA AND DATA SCIENCE METHODS FOR MANAGEMENT RESEARCH
Published in Academy of Management Journal, October 2016, 59 (5), pp. 1493-1507.
http://doi.org/10.5465/amj.2016.4005
The recent advent of remote sensing, mobile technologies, novel transaction systems, and
high performance computing offers opportunities to un.Singapore Management UniversityInstitutional Knowledge at Si.docx
Singapore Management UniversityInstitutional Knowledge at Si.docxedgar6wallace88877
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Singapore Management University
Institutional Knowledge at Singapore Management University
Research Collection Lee Kong Chian School Of
Business
Lee Kong Chian School of Business
10-2016
Big data and data science methods for management
research: From the Editors
Gerard GEORGE
Singapore Management University, [email油protected]
Ernst C. OSINGA
Singapore Management University, [email油protected]
Dovev LAVIE
Technion
Brent A. SCOTT
Michigan State University
DOI: https://doi.org/10.5465/amj.2016.4005
Follow this and additional works at: https://ink.library.smu.edu.sg/lkcsb_research
Part of the Management Sciences and Quantitative Methods Commons, and the Strategic
Management Policy Commons
This Editorial is brought to you for free and open access by the Lee Kong Chian School of Business at Institutional Knowledge at Singapore
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of Institutional Knowledge at Singapore Management University. For more information, please email [email油protected]
Citation
GEORGE, Gerard; Ernst C. OSINGA; LAVIE, Dovev; and SCOTT, Brent A.. Big data and data science methods for management
research: From the Editors. (2016). Academy of Management Journal. 59, (5), 1493-1507. Research Collection Lee Kong Chian School
Of Business.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/4964
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1
FROM THE EDITORS
BIG DATA AND DATA SCIENCE METHODS FOR MANAGEMENT RESEARCH
Published in Academy of Management Journal, October 2016, 59 (5), pp. 1493-1507.
http://doi.org/10.5465/amj.2016.4005
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