Information Systems, Big Data and Knowledge Landscapes

This study aims to investigate the nature of the relationship between Big Data Analysis as a mediator in Process Orientation (PO) and Information Systems Programming (ISP) to supply chains processes in Saudi Arabian industrial organizations. A stratified random sample of 357 managers and employees working in 37 industrial companies in Saudi Arabia was tested. The study relied on the descriptive and analytical research methodology. The results indicated that there is a significant indirect effect of Big Data Analysis (Planning, Procuring, Manufacturing, Delivering) as the mediator on Process Orientation and Information Systems Programming (ISP) and (PO) to improve supply chain process as well as organizational effectiveness. The researcher made a number of recommendations for the Saudi Arabian manufacturing firms to develop analytical capabilities in managers in order to utilize big data analysis as a tool to increase efficiency and effectiveness in the organizational system. A wide spread awareness program about the benefits to adopt big data analysis and management information systems may be adopted to ensure an efficient supply chain system.

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Call for Special Issue Papers: Big Data and the Internet-of-Things in Complex Information Systems: Selections from IoTBDS 2022 and COMPLEXIS 2022

Big Data ◽

10.1089/big.2021.29050.cfp ◽

2022 ◽

Author(s):

Victor Chang ◽

Péter Kacsuk ◽

Gary Wills ◽

Reinhold Behringer

Keyword(s):

Big Data ◽

Information Systems ◽

Internet Of Things ◽

The Internet ◽

Special Issue ◽

Complex Information ◽

The Internet Of Things

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Book Reviews

INFORMS Journal on Applied Analytics ◽

10.1287/inte.2021.1071 ◽

2021 ◽

Vol 51 (3) ◽

pp. 242-244

Author(s):

Wenjing Shen

Keyword(s):

Big Data ◽

Information Systems ◽

Operations Research ◽

Management Science ◽

Diverse Range ◽

Optimization And Control ◽

Areas Of Interest ◽

And Control ◽

To Receive

In Book Reviews, we review an extensive and diverse range of books. They cover theory and applications in operations research, statistics, management science, econometrics, mathematics, computers, and information systems. In addition, we include books in other fields that emphasize technical applications. The editor will be pleased to receive an email from those willing to review a book, with an indication of specific areas of interest. If you are aware of a specific book that you would like to review, or that you think should be reviewed, please contact the editor. The following books are reviewed in this issue of INFORMS Journal on Applied Analytics, 51(3), May–June: Optimization and Control for Systems in the Big-Data Era: Theory and Applications, Tsan-Ming Choi, Jianjun Gao, James H. Lambert, Chi-Kong Ng, Jun Wang; Pricing Lives: Guideposts for a Safer Society, W. Kip Viscusi.

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An Accounting Information Systems Perspective on Data Analytics and Big Data

Journal of Information Systems ◽

10.2308/isys-51799 ◽

2017 ◽

Vol 31 (3) ◽

pp. 101-114 ◽

Cited By ~ 19

Author(s):

Esperanza Huerta ◽

Scott Jensen

Keyword(s):

Big Data ◽

Information Systems ◽

Data Analytics ◽

Accounting Information ◽

Security Requirements ◽

Future Research ◽

Accounting Information Systems ◽

Systems Perspective ◽

Analytic Skills

ABSTRACT Forty-six academics and practitioners participated in the second Journal of Information Systems Conference to discuss data analytics and Big Data from an accounting information systems perspective. The panels discussed the evolving role of technology in accounting, privacy within the domain of Big Data, and people and Big Data. Throughout all three panels, several topics emerged that impact all areas of accounting—developing enhanced analytical and data handling skills; evaluating privacy, security requirements, and risks; thinking creatively; and assessing the threat of automation to the accounting profession. Other topics were specific to a segment of the profession, such as the growing demand for privacy compliance audits and the curriculum adjustments necessary to develop data analytic skills. This commentary synthesizes and expands the discussions of the conference panels and suggests potential areas for future research.

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Big Data Analytics Adoption Factors in Improving Information Systems Security

10.4018/978-1-6684-3662-2.ch059 ◽

2022 ◽

pp. 1231-1248

Author(s):

Marouane Balmakhtar ◽

Scott E. Mensch

Keyword(s):

Big Data ◽

Information Systems ◽

Information Security ◽

Data Analytics ◽

Big Data Analytics ◽

Review Of The Literature ◽

Information Systems Security ◽

Systems Security ◽

Security Effectiveness ◽

Research Questions

This research measured determinants that influence the willingness of IT/IA professionals to recommend Big Data analytics to improve information systems security in an organization. A review of the literature as well as the works of prior researchers provided the basis for formulation of research questions. Results of this study found that security effectiveness, organizational need, and reliability play a role in the decision to recommend big data analytics to improve information security. This research has implications for both consumers and providers of big data analytics services through the identification of factors that influence IT/IA professionals. These factors aim to improve information systems security, and therefore, which service offerings are likely to meet the needs of these professionals and their organizations.

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HR Metrics and Talent Analytics

10.1093/oxfordhb/9780198758273.013.25 ◽

2017 ◽

Author(s):

Alexis A. Fink ◽

Michael C. Sturman

Keyword(s):

Big Data ◽

Information Systems ◽

Human Resource ◽

Investment Decisions ◽

Research And Practice ◽

Hr Practices ◽

History Of Research ◽

Decision Points ◽

History Of ◽

Current Practices

Taking advantage of the history of research quantifying the effects of human resource (HR) practices, leveraging current advances in information systems and opportunities presented by big data, HR metrics and talent analytics present a renewed opportunity to help drive effective HR practices. HR metrics are operational measures, addressing how efficient, effective, and impactful an organization’s HR practices are. In contrast, talent analytics focus on decision points, guiding investment decisions. The chapter provides an overview of the historic roots and current practices around HR metrics and talent analytics. Through this, we explore the role, benefits, and risks of benchmarking and utility analyses as two common approaches to setting HR metrics. We discuss how current advances in research and practice make the use of HR metrics and talent analytics a greater business necessity. We conclude the chapter with a discussion on fostering talent analytics within organizations.

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