Methodology for Assessing the Digital Image of an Enterprise with Its Industry Specifics
This study provides a framework for the comparative assessment of the key industry aspects of competitiveness among logistics services and the logistics systems of enterprises in the informational environment. Frequently, the relationships between a consumer and a company created by means of the inf...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-05-01
|
| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/15/6/177 |
| _version_ | 1797490818012938240 |
|---|---|
| author | Dmitriy Rodionov Darya Kryzhko Timur Tenishev Victor Uimanov Alsu Abdulmanova Ani Kvikviniia Pavel Aksenov Mark Solovyov Fedor Kolomenskii Evgenii Konnikov |
| author_facet | Dmitriy Rodionov Darya Kryzhko Timur Tenishev Victor Uimanov Alsu Abdulmanova Ani Kvikviniia Pavel Aksenov Mark Solovyov Fedor Kolomenskii Evgenii Konnikov |
| author_sort | Dmitriy Rodionov |
| collection | DOAJ |
| description | This study provides a framework for the comparative assessment of the key industry aspects of competitiveness among logistics services and the logistics systems of enterprises in the informational environment. Frequently, the relationships between a consumer and a company created by means of the informational environment determine how the enterprise positions itself in the market. For instance, the evaluation of a company’s representation in the information field is an essential aspect of determining the company’s competitiveness. The study suggests a set of special metrics for measuring the representation of digital components and other aspects of an enterprise’s digital image via data gathering and analysis of the most encountered tokens. The proposed automated analysis algorithm allows companies to examine their image in the digital environment and implement effective decisions. The functionality of the algorithm fosters data collection, helping to form the desired image of the company. Tokens of several thematic groups on social media are collected during the process, and the most significant of them that are valuable for the competitiveness of the enterprise are extracted. The outcome can be used for the tracking of the dynamics of key parameters of an enterprise’s image and for conducting a comparative analysis of the digital image of its competitors. |
| first_indexed | 2024-03-10T00:38:30Z |
| format | Article |
| id | doaj.art-978b14c73d6249aaa93cd53c2bda6d67 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-10T00:38:30Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-978b14c73d6249aaa93cd53c2bda6d672023-11-23T15:12:50ZengMDPI AGAlgorithms1999-48932022-05-0115617710.3390/a15060177Methodology for Assessing the Digital Image of an Enterprise with Its Industry SpecificsDmitriy Rodionov0Darya Kryzhko1Timur Tenishev2Victor Uimanov3Alsu Abdulmanova4Ani Kvikviniia5Pavel Aksenov6Mark Solovyov7Fedor Kolomenskii8Evgenii Konnikov9Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, RussiaGraduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, RussiaGraduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, RussiaGraduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, RussiaGraduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, RussiaGraduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, RussiaGraduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, RussiaGraduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, RussiaGraduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, RussiaGraduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, RussiaThis study provides a framework for the comparative assessment of the key industry aspects of competitiveness among logistics services and the logistics systems of enterprises in the informational environment. Frequently, the relationships between a consumer and a company created by means of the informational environment determine how the enterprise positions itself in the market. For instance, the evaluation of a company’s representation in the information field is an essential aspect of determining the company’s competitiveness. The study suggests a set of special metrics for measuring the representation of digital components and other aspects of an enterprise’s digital image via data gathering and analysis of the most encountered tokens. The proposed automated analysis algorithm allows companies to examine their image in the digital environment and implement effective decisions. The functionality of the algorithm fosters data collection, helping to form the desired image of the company. Tokens of several thematic groups on social media are collected during the process, and the most significant of them that are valuable for the competitiveness of the enterprise are extracted. The outcome can be used for the tracking of the dynamics of key parameters of an enterprise’s image and for conducting a comparative analysis of the digital image of its competitors.https://www.mdpi.com/1999-4893/15/6/177digital imagebrandinformation environmentlogisticssupply chaine-commerce |
| spellingShingle | Dmitriy Rodionov Darya Kryzhko Timur Tenishev Victor Uimanov Alsu Abdulmanova Ani Kvikviniia Pavel Aksenov Mark Solovyov Fedor Kolomenskii Evgenii Konnikov Methodology for Assessing the Digital Image of an Enterprise with Its Industry Specifics Algorithms digital image brand information environment logistics supply chain e-commerce |
| title | Methodology for Assessing the Digital Image of an Enterprise with Its Industry Specifics |
| title_full | Methodology for Assessing the Digital Image of an Enterprise with Its Industry Specifics |
| title_fullStr | Methodology for Assessing the Digital Image of an Enterprise with Its Industry Specifics |
| title_full_unstemmed | Methodology for Assessing the Digital Image of an Enterprise with Its Industry Specifics |
| title_short | Methodology for Assessing the Digital Image of an Enterprise with Its Industry Specifics |
| title_sort | methodology for assessing the digital image of an enterprise with its industry specifics |
| topic | digital image brand information environment logistics supply chain e-commerce |
| url | https://www.mdpi.com/1999-4893/15/6/177 |
| work_keys_str_mv | AT dmitriyrodionov methodologyforassessingthedigitalimageofanenterprisewithitsindustryspecifics AT daryakryzhko methodologyforassessingthedigitalimageofanenterprisewithitsindustryspecifics AT timurtenishev methodologyforassessingthedigitalimageofanenterprisewithitsindustryspecifics AT victoruimanov methodologyforassessingthedigitalimageofanenterprisewithitsindustryspecifics AT alsuabdulmanova methodologyforassessingthedigitalimageofanenterprisewithitsindustryspecifics AT anikvikviniia methodologyforassessingthedigitalimageofanenterprisewithitsindustryspecifics AT pavelaksenov methodologyforassessingthedigitalimageofanenterprisewithitsindustryspecifics AT marksolovyov methodologyforassessingthedigitalimageofanenterprisewithitsindustryspecifics AT fedorkolomenskii methodologyforassessingthedigitalimageofanenterprisewithitsindustryspecifics AT evgeniikonnikov methodologyforassessingthedigitalimageofanenterprisewithitsindustryspecifics |