IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v23y2021i5d10.1007_s10796-020-10033-4.html
   My bibliography  Save this article

Behavioral and Migration Analysis of the Dynamic Customer Relationships on Twitter

Author

Listed:
  • Eleanna Kafeza

    (Zayed University)

  • Christos Makris

    (University of Patras)

  • Gerasimos Rompolas

    (University of Patras)

  • Feras Al-Obeidat

    (Zayed University)

Abstract

Relationship management has been of strategic importance for businesses that are interested to evaluate the state of the relationship with the customer and if possible to migrate customers to better and more binding states. This work addresses the problem of estimating the relationship state of a customer and examining the migration policy of the customer, using social media analytics. We propose an innovative framework, where clustering, linguistic and emotional analytics are used to automatically assign users to relationship states. Our research is of multi-disciplinary nature, where we are using existing results from surveys on users’ behavior when mitigating states to verify the semantics of our metrics, showing that they follow similar behavior. Our results show that clustering users based on communication, emotions and perceived product mix can result in an automated assignment of users to states. Furthermore, trust, commitment and homophily are defined and our results show that users are migrating states influenced by these values. Our work provides data analytics metrics for businesses that will identify and address the problem of relationship management thus improving the overall users’ satisfaction using a data analytics approach.

Suggested Citation

  • Eleanna Kafeza & Christos Makris & Gerasimos Rompolas & Feras Al-Obeidat, 2021. "Behavioral and Migration Analysis of the Dynamic Customer Relationships on Twitter," Information Systems Frontiers, Springer, vol. 23(5), pages 1303-1316, September.
    • Handle: RePEc:spr:infosf:v:23:y:2021:i:5:d:10.1007_s10796-020-10033-4
    DOI: 10.1007/s10796-020-10033-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-020-10033-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-020-10033-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tien T. Nguyen & F. Maxwell Harper & Loren Terveen & Joseph A. Konstan, 2018. "User Personality and User Satisfaction with Recommender Systems," Information Systems Frontiers, Springer, vol. 20(6), pages 1173-1189, December.
    2. Ryals, Lynette & Knox, Simon, 2001. "Cross-functional issues in the implementation of relationship marketing through customer relationship management," European Management Journal, Elsevier, vol. 19(5), pages 534-542, October.
    3. Luvai Motiwalla & Amit V. Deokar & Surendra Sarnikar & Angelika Dimoka, 2019. "Leveraging Data Analytics for Behavioral Research," Information Systems Frontiers, Springer, vol. 21(4), pages 735-742, August.
    4. Chengde Zheng & Xiaofeng Yu & Qiming Jin, 2017. "How user relationships affect user perceived value propositions of enterprises on social commerce platforms," Information Systems Frontiers, Springer, vol. 19(6), pages 1261-1271, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eleanna Kafeza & Christos Makris & Gerasimos Rompolas & Feras Al-Obeidat, 0. "Behavioral and Migration Analysis of the Dynamic Customer Relationships on Twitter," Information Systems Frontiers, Springer, vol. 0, pages 1-14.
    2. Ray Qing Cao & Dara G. Schniederjans & Vicky Ching Gu, 2021. "Stakeholder sentiment in service supply chains: big data meets agenda-setting theory," Service Business, Springer;Pan-Pacific Business Association, vol. 15(1), pages 151-175, March.
    3. Reema Nofal & Pelin Bayram & Okechukwu Lawrence Emeagwali & Lu’ay Al-Mu’ani, 2022. "The Effect of eWOM Source on Purchase Intention: The Moderation Role of Weak-Tie eWOM," Sustainability, MDPI, vol. 14(16), pages 1-20, August.
    4. Kahn, Kenneth B. & Reizenstein, Richard C. & Rentz, Joseph O., 2004. "Sales-distribution interfunctional climate and relationship effectiveness," Journal of Business Research, Elsevier, vol. 57(10), pages 1085-1091, October.
    5. Garrido-Moreno, Aurora & Padilla-Meléndez, Antonio, 2011. "Analyzing the impact of knowledge management on CRM success: The mediating effects of organizational factors," International Journal of Information Management, Elsevier, vol. 31(5), pages 437-444.
    6. Raed S. Algharabat & Nripendra P. Rana, 0. "Social Commerce in Emerging Markets and its Impact on Online Community Engagement," Information Systems Frontiers, Springer, vol. 0, pages 1-22.
    7. Carmen-Maria, IORDACHE & Alexandrina, SÎRBU, 2013. "Customer Loyalty - The Guaranteed Success Of An Organization On The Market," Management Strategies Journal, Constantin Brancoveanu University, vol. 22(4), pages 41-48.
    8. van Aaken, Dominik & Kirsch, Werner & Seidl, David, 2015. "Gesetzmäßigkeiten in der Unternehmensführung? – Unternehmensführung als das Verfügen über Notwendigkeiten," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 69(1), pages 54-66.
    9. Wei Wu & Qianwen Yang & Xiang Gong, 2024. "Impulsive Social Shopping in Social Commerce Platforms: The Role of Perceived Proximity," Information Systems Frontiers, Springer, vol. 26(4), pages 1527-1541, August.
    10. Chi, Nguyen Thi Khanh, 2021. "Innovation capability: The impact of e-CRM and COVID-19 risk perception," Technology in Society, Elsevier, vol. 67(C).
    11. Waseem John, 2019. "Scale Development and Construct Validity of Organizational Capital in Customer Relationship Management Context: A Confirmatory Factor Analysis Approach," Business Perspectives and Research, , vol. 7(1), pages 76-91, January.
    12. Chun-Chu Liu & Li-min Chuang & Chien-Min Huang, 2012. "A Study of the Impact of the e-CRM Perspective on Customer Satisfaction and Customer Loyalty-Exemplified by Bank Sinopac," Journal of Economics and Behavioral Studies, AMH International, vol. 4(8), pages 467-476.
    13. Chia-Ying Li & Yu-Hui Fang & Badri Munir Sukoco, 2021. "Value proposition as a catalyst for innovative service experience: the case of smart-tourism destinations," Service Business, Springer;Pan-Pacific Business Association, vol. 15(2), pages 281-308, June.
    14. Ransome Epie Bawack & Emilie Bonhoure, 2023. "Influencer is the New Recommender: insights for Theorising Social Recommender Systems," Information Systems Frontiers, Springer, vol. 25(1), pages 183-197, February.
    15. Mengyue Wang & Xin Li & Patrick Y. K. Chau, 2021. "Leveraging Image-Processing Techniques for Empirical Research: Feasibility and Reliability in Online Shopping Context," Information Systems Frontiers, Springer, vol. 23(3), pages 607-626, June.
    16. Muhammad Ashraf & Mohammad Asif Khan & Noor Ismawati Jaafar & Ainin Sulaiman, 2015. "The impact of Involvement in CRM Initiative on Inter-functional Integration and Organizational Performance: Evidence from Pakistani Enterprises," Information Management and Business Review, AMH International, vol. 7(1), pages 29-40.
    17. Hong, Zhaofu & Li, Mengfan & Han, Xiaoya & He, Xuhuai, 2020. "Innovative green product diffusion through word of mouth," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    18. Anastasia Griva & Cleopatra Bardaki & Katerina Pramatari & Georgios Doukidis, 2022. "Factors Affecting Customer Analytics: Evidence from Three Retail Cases," Information Systems Frontiers, Springer, vol. 24(2), pages 493-516, April.
    19. A.R. ABDUL-AZIZ & Bashiru I.I. SAEED & Ayogyam ALEXANDER, 2014. "Customer satisfaction of mobile telecommunication networks in Ghana: service delivery perspective," The Journal of Accounting and Management, Danubius University of Galati, issue 1, pages 61-71, April.
    20. Narjes Vara & Mahdieh Mirzabeigi & Hajar Sotudeh & Seyed Mostafa Fakhrahmad, 2022. "Application of k-means clustering algorithm to improve effectiveness of the results recommended by journal recommender system," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3237-3252, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infosf:v:23:y:2021:i:5:d:10.1007_s10796-020-10033-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.