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Special Issue "Innovative Knowledge-Based Methods for Business Success: Analysing User Generated Content"

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Management".

Deadline for manuscript submissions: closed (30 November 2020).

Special Issue Editors

Dr. José Ramón Saura
E-Mail Website1 Website2
Guest Editor
Prof. Dr. Ana Reyes-Menendez
E-Mail Website
Guest Editor
Department of Business Economics, Rey Juan Carlos University, Madrid, Spain
Interests: neuromarketing; digital behavior; social networks; business; consumer behavior
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The global development of the Internet, which has enabled the analysis of large amounts of data and the services linked to their use, has led companies to modify their business strategies in search of new ways to increase marketing productivity and profitability. Many strategies are based on business intelligence and marketing intelligence that make it possible to extract profitable knowledge and insights from large amounts of data generated by company customers in digital environments.

Additionally, the use of social networks and the Internet have become habits for consumers to the point that there are millions of devices connected to the Internet that are constantly generating new data. Furthermore, as the use of these technologies has become habitual for users, it has also become commonplace for users to share information about individual experiences and opinions, as well as content related to the interests of users and companies via social networks, known as user-generated content (UGC).

In looking at these types of data sources, several studies have analyzed the influence of the application of data mining to marketing strategies and knowledge discovery. UGC is defined as the content generated by users in social networks and digital platforms. Such content includes comments, opinions, expressions, and interactions between users and brands, or any other type of content shared publicly on the Internet that seeks to generate engagement between different profiles. The study of this type of content is important in the context of new business models and marketing strategies, as it can enable managers to generate meaningful insights that may in turn help to refine strategic responses or become the basis for further research.

Therefore, the purpose of this Special Issue is to analyze how these new data analysis techniques can influence the development of marketing strategies and decision-making processes in companies. The objective of this Special Issue, consequently, is to analyze how the application of automatic and semiautomatic data analysis techniques applied to marketing affects the business environment and decision-making.

For this Special Issue, we invite paper contributions related to any of the topics outlined above and which clearly relate to knowledge management and data mining for marketing using research approaches such as data mining, social network analysis, UGC analysis, sentiment analysis, big data, machine learning approaches, support vector machines, neuromarketing, case studies or reviews of literature on this topic as well as another quantitative, qualitative or mixed/multimethod perspectives.

Important References

Saura, J.R.; Bennett, D.R. A Three-Stage method for Data Text Mining: Using UGC in Business Intelligence Analysis. Symmetry 2019, 11, 519. doi:10.3390/sym11040519.

Reyes-Menendez, A.; Saura, J.R.; Alvarez-Alonso, C. Understanding #WorldEnvironmentDay User Opinions in Twitter: A Topic-Based Sentiment Analysis Approach. Int. J. Environ. Res. Public Health 2018, 15, 2537. doi:10.3390/ijerph15112537.

Daugherty, T.; Eastin, M.S.; Bright, L. Exploring consumer motivations for creating user generated content. J. Interact. Advert. 2008, 8, 16–25. doi:10.1080/15252019.2008.10722139.

Saura, J.R.; Rodriguez Herráez, B.; Reyes-Menendez, A. Comparing a traditional approach for financial Brand Communication Analysis with a Big Data Analytics technique. IEEE Access 2019, doi:10.1109/ACCESS.2019.2905301.

Goh, K.Y.; Heng, C.S.; Lin, Z. Social media brand community and consumer behavior: Quantifying the relative impact of user-and marketer-generated content. Inf. Syst. Res. 2013 24, 88–107. doi:10.1287/isre.1120.0469.

Prof. Dr. José Ramón Saura
Prof. Dr. Ana Reyes-Menendez
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 papers will be 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. Sustainability is an international peer-reviewed open access semimonthly 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 1900 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

  • Knowledge discovery
  • Innovative methods
  • Knowledge management
  • Data mining
  • User-generated content

Published Papers (2 papers)

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Research

Article
Developing a Product Knowledge Graph of Consumer Electronics to Manage Sustainable Product Information
Sustainability 2021, 13(4), 1722; https://doi.org/10.3390/su13041722 - 05 Feb 2021
Cited by 1 | Viewed by 639
Abstract
Transformational computing paradigms, such as artificial intelligence, home automation, and the Internet of Things, are being rapidly applied to consumer electronics products, thus aiding in the development of integrated and innovative features. Hence, ubiquitous computing and electronic devices are increasingly becoming essential to [...] Read more.
Transformational computing paradigms, such as artificial intelligence, home automation, and the Internet of Things, are being rapidly applied to consumer electronics products, thus aiding in the development of integrated and innovative features. Hence, ubiquitous computing and electronic devices are increasingly becoming essential to everyday life. In this context, a wide gulf often exists between the capabilities and technical features of consumer electronic devices and the consumers’ understanding of such devices and ability to operate them correctly and effectively. This study proposes a machine-readable knowledge model representing technical terms in product specifications along with a product knowledge graph to discover semantic relationships among various products. Formal concept analysis is applied to conceptually analyze the specification terms of heterogeneous electronic products and design a hierarchical knowledge structure of extracted concepts, to elaborate the proposed knowledge model. Full article
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Article
Location Based Business Recommendation Using Spatial Demand
Sustainability 2020, 12(10), 4124; https://doi.org/10.3390/su12104124 - 18 May 2020
Cited by 7 | Viewed by 1361
Abstract
Business locations is most important factor to consider before starting a business because the best location attracts more number of people. With the help of web search engines, the customers can search the nearest business location before visiting the business. For example, if [...] Read more.
Business locations is most important factor to consider before starting a business because the best location attracts more number of people. With the help of web search engines, the customers can search the nearest business location before visiting the business. For example, if a customer need to buy some jewel, he makes use of search engines to find the nearest jewellery shop. If some entrepreneur wants to start a new jewellery shop, he needs to find a best area where there is no jewellery shop nearby and there are more customers in need of jewel. In this paper, we propose an algorithm to find the best place to start a business where there is high demand and no (or very few supply). We measure the quality of recommendation in terms of average service time, customer-business ratio of our new algorithm by implementing in benchmark datasets and the results prove that our algorithm is more efficient than the existing kNN algorithm. Full article
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