IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i2p714-d1318819.html
   My bibliography  Save this article

An Assessment of Digitalization Techniques in Contact Centers and Their Impact on Agent Performance and Well-Being

Author

Listed:
  • Massimo Pacella

    (Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy)

  • Paride Vasco

    (Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy)

  • Gabriele Papadia

    (Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy)

  • Vincenzo Giliberti

    (IN & OUT S.p.A. a Socio Unico Teleperformance S.E., 74121 Taranto, Italy)

Abstract

The role of contact centers in improving the operational efficiency of numerous organizations is of utmost importance. Presently, digitalization technology has enabled contact centers to deliver exceptional customer service and support, while minimizing the adverse impact on agent well-being. Artificial intelligence techniques such as topic modeling and sentiment analysis can aid agents in addressing specific queries, providing real-time support and feedback, and helping them build stronger relationships with customers. This study aims to investigate the advantages of integrating these techniques in the analysis of customer–agent conversations within contact centers. This study examines whether there is a discernible advantage in analyzing customer–agent conversations in real-time and whether it is worth using this type of digitization to enhance agent performance and well-being. Furthermore, this study explores the impact of these technologies on European privacy, business, real-time agent support, the value of conversation data, brand reputation, and customer satisfaction. The results of this study demonstrate the significance of incorporating topic modeling and sentiment analysis into the analysis of customer–agent conversations at contact centers.

Suggested Citation

  • Massimo Pacella & Paride Vasco & Gabriele Papadia & Vincenzo Giliberti, 2024. "An Assessment of Digitalization Techniques in Contact Centers and Their Impact on Agent Performance and Well-Being," Sustainability, MDPI, vol. 16(2), pages 1-20, January.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:714-:d:1318819
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/2/714/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/2/714/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sheth, Jagdish N. & Jain, Varsha & Ambika, Anupama, 2023. "The growing importance of customer-centric support services for improving customer experience," Journal of Business Research, Elsevier, vol. 164(C).
    2. Pedota, Mattia & Grilli, Luca & Piscitello, Lucia, 2023. "Technology adoption and upskilling in the wake of Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    3. Hornik, Jacob & Miniero, Giulia, 2009. "Synchrony effects on customers' responses and behaviors," International Journal of Research in Marketing, Elsevier, vol. 26(1), pages 34-40.
    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. Juan José Fernández-Durán & María Mercedes Gregorio-Domínguez, 2021. "Consumer Segmentation Based on Use Patterns," Journal of Classification, Springer;The Classification Society, vol. 38(1), pages 72-88, April.
    2. Pedota, Mattia, 2023. "Big data and dynamic capabilities in the digital revolution: The hidden role of source variety," Research Policy, Elsevier, vol. 52(7).
    3. Yang, Shuai & Wang, Yizhe & Li, Zhen & Chen, Chiyin & Yu, Ziyue, 2022. "Time-of-day effects on (un)healthy product purchases: Insights from diverse consumer behavior data," Journal of Business Research, Elsevier, vol. 152(C), pages 447-460.

    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:gam:jsusta:v:16:y:2024:i:2:p:714-:d:1318819. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.