Special Issue "Big Data Analytics in Green Supply Chain and Social Media Influences"

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Big Data and Augmented Intelligence".

Deadline for manuscript submissions: 30 June 2023 | Viewed by 469

Special Issue Editors

College of Business, School of Business and Law, Central Queensland University, Brisbane 4000, Australia
Interests: operations and sustainable supply chain; product recovery; circular economy; business analytics and optimisation; decision support systems
Special Issues, Collections and Topics in MDPI journals
Australian Council for STEAM, Brisbane 4100, Australia
Interests: social media marketing; online WOM; new media and communications; consumer behavior
Department of Informatics, Modeling, Electronics, and Systems Engineering (DIMES), University of Calabria, 87036 Rende, Italy
Interests: big data analysis; social media analysis; cloud computing; data mining; machine learning; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the development of computing and sensing technologies, such as the internet of things, mobile device technologies, and industrial applications of social media, new media communication platforms have changed over the past decade and will continue to evolve. At the same time, they have become more and more complicated. Organisations are now facing significant challenges in sustaining their businesses and supply chains because they need to evaluate a large amount of data in different forms and much faster than before. In addition, the use of digital information and big data analytics has also been identified as a key strategy to achieve competitive advantages through new media and social media platforms, such as using data, process and analytical modelling, and managing the green and sustainable supply chain to turn big data into meaningful insights.

Submissions may include but are not restricted to the following topics:

  • Big data analytics and/or its impacts on new media and consumer behaviour;
  • Data analytics in social media and online word of mouth and communication;
  • Online and media community and big data influence;
  • Green supply chain management in computing and sensing technologies;
  • The influence of cloud computing and big data analytics in supply chains;
  • Development of decision support systems and big data analytics;
  • Real-world applications of big data analytics and impacts;
  • Business analytics and optimisation.

Dr. Swee Kuik
Dr. Xiaolie Qi
Dr. Fabrizio Marozzo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • big data analytics
  • social media influence
  • online word of mouth
  • sustainability in supply chain
  • green product
  • consumer behavior

Published Papers

This special issue is now open for submission, see below for planned papers.

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: The Role of Social Media Analytics as Strategic Decision Tools for Tourism and Hospitality Business
Authors: Yohannes Kurniawan (a); Erwin Halim (a); Norizan Anwar (b)
Affiliation: (a) Bina Nusantara University; (b) Universiti Teknologi Mara
Abstract: Industries in the service sector, such as tourism and hospitality, during the COVID-19 pandemic, experienced disruption and decreased interest in all countries, including Indonesia. Recently pandemic changed to an endemic, and all activities and businesses related to tourism and hospitality began to bounce back in 2022. Therefore, it is essential for business stakeholders engaged in Tourism and Hospitality to understand data on the internet, one of which is one of them. Is social media behavioral data that can be used for the right systematic business strategy? This research has on social media coverage in Indonesia; this study aims to understand the patterns of data in social media in the tourism and hospitality industry to help make more structured and systematic decisions. The method used in this study is to analyze the behavior of users of the data obtained through data analysis tools (secondary data) and user behavior through questionnaires (primary data). The analysis gives recommendations for the pattern of strategic decisions entrepreneurs in this field can take. One of the essential indicators that attract the attention of business actors in the hospitality and tourism sector is price-focused content for national segmentation and focus on security for foreign visitor segmentation.

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