Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databases
Abstract Nowadays, we can express the experience we have lived with the products we use. Most of the time, we interact with brands and let our likes and dislikes be seen on digital platforms, either by interacting with social networks, filling out satisfaction surveys, or registering requests, compl...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-08-01
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| Series: | Journal of Innovation and Entrepreneurship |
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| Online Access: | https://doi.org/10.1186/s13731-025-00536-2 |
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| author | Ana Gutiérrez Jose Aguilar Ana Ortega Edwin Montoya |
| author_facet | Ana Gutiérrez Jose Aguilar Ana Ortega Edwin Montoya |
| author_sort | Ana Gutiérrez |
| collection | DOAJ |
| description | Abstract Nowadays, we can express the experience we have lived with the products we use. Most of the time, we interact with brands and let our likes and dislikes be seen on digital platforms, either by interacting with social networks, filling out satisfaction surveys, or registering requests, complaints, and claims. To get the value of all available customer data of the companies, in this article, we propose to study the data from different sources using an autonomic cycle of data analysis tasks to define innovation problems in an organization. The tasks of the autonomic cycle are filter the customer comments from different sources (e.g., from social networks, PCCS (petitions, complaints, claims, suggestions) systems of organizations, etc.), obtain their keywords, and analyze the patterns of the users to answer the questions of the 5W methodology (what, who, where, when and why?), to define innovation problems. Finally, this article analyzes a case study of a fashion company using its PCCS system and comments of Twitter, to identify useful information. Part of the information discovered was the reasons for customer returns, merchandise delivery problems, shipment failures, failure to respond timely to customers, among other things. With this information, the autonomic cycle is able to define customer and organization-oriented innovation problems, to respond to these identified problems. |
| format | Article |
| id | doaj-art-b804279e18bc4402b7d7de7cc6a0c8a1 |
| institution | Kabale University |
| issn | 2192-5372 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Innovation and Entrepreneurship |
| spelling | doaj-art-b804279e18bc4402b7d7de7cc6a0c8a12025-08-24T11:58:25ZengSpringerOpenJournal of Innovation and Entrepreneurship2192-53722025-08-0114112510.1186/s13731-025-00536-2Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databasesAna Gutiérrez0Jose Aguilar1Ana Ortega2Edwin Montoya3GIA, Universidad Francisco de Paula Santander, Av. Gran ColombiaGIDITICS, Universidad EAFITGIDITICS, Universidad EAFITGIDITICS, Universidad EAFITAbstract Nowadays, we can express the experience we have lived with the products we use. Most of the time, we interact with brands and let our likes and dislikes be seen on digital platforms, either by interacting with social networks, filling out satisfaction surveys, or registering requests, complaints, and claims. To get the value of all available customer data of the companies, in this article, we propose to study the data from different sources using an autonomic cycle of data analysis tasks to define innovation problems in an organization. The tasks of the autonomic cycle are filter the customer comments from different sources (e.g., from social networks, PCCS (petitions, complaints, claims, suggestions) systems of organizations, etc.), obtain their keywords, and analyze the patterns of the users to answer the questions of the 5W methodology (what, who, where, when and why?), to define innovation problems. Finally, this article analyzes a case study of a fashion company using its PCCS system and comments of Twitter, to identify useful information. Part of the information discovered was the reasons for customer returns, merchandise delivery problems, shipment failures, failure to respond timely to customers, among other things. With this information, the autonomic cycle is able to define customer and organization-oriented innovation problems, to respond to these identified problems.https://doi.org/10.1186/s13731-025-00536-2Innovation problemsAutonomic computingData analysisMachine learning |
| spellingShingle | Ana Gutiérrez Jose Aguilar Ana Ortega Edwin Montoya Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databases Journal of Innovation and Entrepreneurship Innovation problems Autonomic computing Data analysis Machine learning |
| title | Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databases |
| title_full | Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databases |
| title_fullStr | Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databases |
| title_full_unstemmed | Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databases |
| title_short | Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databases |
| title_sort | definition of innovation problems in organizations using data analysis tasks from hybrid sources social networks and organizational databases |
| topic | Innovation problems Autonomic computing Data analysis Machine learning |
| url | https://doi.org/10.1186/s13731-025-00536-2 |
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