Special Issue: Big Data in Technology, Accounting, Finance, Tourism and Economics

A Special Issue of EJASA (open access journal indexed in SCOPUS and Thomson Reuters Web of ScienceTM Core Collection - Emerging Sources Citation Index) is devoted to the introduction of the ideas of Technology and Big data in different business aspects of the economy today. Big data has gradually been attached to importance in the economic field, especially the traditional economic management has not met the needs of society.

Big Data allows for better prediction of economic phenomena and improves causal inference. Machine learning techniques allow researchers to create simple models that describe very large, complex data sets (Chebbi et al., 2015). Big data has become a main priority for companies in technology circles. Interest is growing in enterprises that want to harness the power of Big data and among consumers who want to benefit from Big data-driven applications (Byers, 2014).

The applications of Technology and Big data in the economy especially in finance sector such as automated trading, risk management, fraud detection, customer service, personalized marketing, and credit scoring. Besides, the application of Technology and Big data also solves many problems in other fields including supply chain management, manufacturing, human resources, logistics, agriculture, energy, and utilities. Most typically in human resource management, Technology and Big Data are being used in human resources to improve employee engagement and retention. Employee data is analyzed to identify patterns and trends that can help improve workplace culture and productivity.

This special issue aims at collecting qualified research papers that propose developments of new statistical methods for the analysis of the above-mentioned and the impact of Technology and Big data on different business aspects of the economy today. The fields of application include those of economic and social sciences (economics, accounting, finance, tourism, marketing, etc.). Statistical techniques such as:

  • Exploratory statistics;
  • Network analysis;
  • Multilayer perceptron;
  • Decision trees;
  • Generalized mixed-effect models;
  • Statistical models for count data;
  • Categorical data analysis;
  • Big data;
  • Artificial neural network;
  • Data visualization with the Power BI tool;
  • Mediation and moderation analysis;
  • Sentiment analysis;
  • Text mining;
  • Statistical models for spatial data
  • Structural Equation Modelling
  • PLS Path Modelling

Papers investigating Big data, as well as applying the technology in organizations from an economic, and sociological perspective are thus welcome.

Guest Editors

  • Thanh Tri Ho, Ho Chi Minh City University of Food Industry, Vietnam
  • Phuoc Tran, Ho Chi Minh City University of Food Industry, Vietnam

Submission and Review Process

The manuscript must fully comply with the Electronic Journal of Applied Statistical Analysis’s instruction for authors.Authors must use the official Electronic Journal of Applied Statistical Analysis submission portal, and select ‘Special Issue BigData2023’ special issue for their submission.

The deadline for the submission is July 31, 2023. All the submitted manuscripts will go through a two-round peer-review process. There is no guarantee of publication. Authors who publish with EJASA agree to the Creative Commons 3.0

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e-ISSN: 2070-5948