Using Chatbot Technologies to Support Argumentation

Chatbots are extensively used in modern times and are exhibiting increasingly intelligent behaviors. However, being relatively new technologies, there are significant demands for further advancement. Numerous possibilities for research exist to refine these technologies, including integration with other technologies, especially in the field of artificial intelligence (AI), which has received much attention and development. This study aims to explore the ability of chatbot technologies to classify arguments according to the reasoning patterns used to create them. As argumentation is a significant aspect of human intelligence, categorizing arguments according to various argumentation schemes (reasoning patterns) is a crucial step towards developing sophisticated human-computer interaction interfaces. This will enable agents (chatbots) to engage in more sophisticated interactions, such as argumentation processes

Virtual assistants in customer interface

This thesis covers use of virtual assistants from a user organization’s perspective, exploring challenges and opportunities related to introducing virtual assistants to an organization’s customer interface. Research related to virtual assistants is spread over many distinct fields of research spanning several decades. However, widespread use of virtual assistants in organizations customer interface is a relatively new and constantly evolving phenomenon. Scientific research is lacking when it comes to current use of virtual assistants and user organization’s considerations related to it. A qualitative, semi-systematic literature review method is used to analyse progression of research related to virtual assistants, aiming to identify major trends. Several fields of research that cover virtual assistants from different perspectives are explored, focusing primarily on Human-Computer Interaction and Natural Language Processing. Additionally, a case study of a Finnish insurance company’s use of virtual assistants supports the literature review and helps understand the user organization’s perspective. This thesis describes how key technologies have progressed, gives insight on current issues that affect organizations and points out opportunities related to virtual assistants in the future. Interviews related to the case study give a limited understanding as to what challenges are currently at the forefront when it comes to using this new technology in the insurance industry. The case study and literature review clearly point out that use of virtual assistants is hindered my various practical challenges. Some practical challenges related to making a virtual assistant useful for an organization seem to be industry-specific, for example issues related to giving advice about insurance products. Other challenges are more general, for example unreliability of customer feedback. Different customer segments have different attitudes towards interacting with virtual assistants, from positive to negative, making the technology a clearly polarizing issue. However, customers in general seem to be becoming more accepting towards the technology in the long term. More research is needed to understand future potential of virtual assistants in customer interactions and customer relationship management.Tämä tutkielma tutkii virtuaaliassistenttien käyttöä käyttäjäorganisaation perspektiivistä, antaen käsityksen mitä haasteita ja mahdollisuuksia liittyy virtuaaliassistenttien käyttöönottoon organisaation asiakasrajapinnassa. Virtuaaliassistentteihin liittyvä tutkimus jakautuu monien eri tutkimusalojen alaisuuteen ja useiden vuosikymmenien ajalle. Laajamittainen virtuaaliassistenttien käyttö asiakasrajapinnassa on kuitenkin verrattain uusi ja jatkuvasti kehittyvä ilmiö. Tieteellinen tutkimus joka liittyy virtuaaliassistenttien nykyiseen käyttöön ja käyttäjäorganisaation huomioon otetaviin asioihin on puutteellista. Tämä tutkielma käyttää kvalitatiivista, puolisystemaattista kirjallisuusanalyysimetodia tutkiakseen virtuaaliassistentteihin liittyviä kehityskulkuja, tarkoituksena tunnistaa merkittäviä trendejä. Tutkimus kattaa useita tutkimusaloja jotka käsittelevät virtuaaliassistentteja eri näkökulmista, keskittyen pääasiassa Human-Computer Interaction- sekä Natural Language Processing -tutkimusaloihin. Lisäksi tutkielmassa on tapaustutkimus suomalaisen vakuutusyhtiön virtuaaliassistenttien käytöstä, joka tukee kirjallisuusanalyysiä ja auttaa ymmärtämään käyttäjäorganisaation perspektiiviä. Tutkielma kuvailee kuinka keskeiset teknologiat ovat kehittyneet, auttaa ymmärtämään tämänhetkisiä ongelmia jotka koskettavat organisaatioita sekä esittelee virtuaaliassistentteihin liittyviä mahdollisuuksia tulevaisuudessa. Tapaustutkimukseen liittyvät haastattelut antavat rajoitetun kuvan kyseisen uuden teknologian käyttöön liittyvistä haasteista vakuutusalalla. Tapaustutkimus ja kirjallisuusanalyysi osoittavat että virtuaaliassistenttien käyttöönottoon liittyy erilaisia käytännön haasteita. Jotkut haasteet vaikuttavat olevan toimialakohtaisia, liittyen esimerkiksi vakuutustuotteita koskeviin neuvoihin. Toiset haasteet taas ovat yleisempiä, liittyen esimerkiksi asiakaspalautteen epäluotettavuuteen. Eri asiakassegmenteillä on erilaisia asenteita virtuaaliassistentteja kohtaan, vaihdellen positiivisesta negatiiviseen, joten kyseinen teknologia on selvästi polarisoiva aihe. Pitkällä aikavälillä asiakkaiden asenteet teknologiaa kohtaan vaikuttavat kuitenkin muuttuvan hyväksyvämpään suuntaan. Lisää tutkimusta tarvitaan jotta voidaan ymmärtää virtuaaliassistenttien tulevaisuuden potentiaalia asiakaskohtaamisissa ja asiakkuudenhallinnassa

Understanding chatbot service encounters:consumers’ satisfactory and dissatisfactory experiences

Abstract. The service industry keeps growing these years. Artificial intelligence (AI) has started to be used in the service industry gradually, and the service chatbot is an excellent example of this phenomenon. Many giants have applied chatbots to handle their consumer services, such as LATTJO from IKEA, Stylebot from Nike, and Siri from Apple. Understanding the advanced chatbot service experiences can help companies to optimize their chatbot services and improve their consumers’ satisfaction, which can bring them positive word-of-mouth, customer loyalty, re-purchase behavior, etc. However, chatbot services is an edge research area with limited studies about it. Thus, having the most advanced understanding of chatbot service experiences becomes particularly important. This study intends to fill this gap from chatbot service encounters’ perspective by understanding consumers’ satisfactory and unsatisfactory experiences with chatbots. Due to this study focuses on chatbot service encounters and online customer service experiences, a qualitative research method be applied because it enables data to be explainable and justifiable. Data collection methods consist of the critical incident technique (CIT) and the online focus group. In the end, 22 validity incidents were collected. Through data analysis, the author developed an incident sorting process and concluded eight types of chatbot service encounters within three groups by this process. The three groups are chatbot response to after-sales services, chatbot response to consumers’ needs, and unprompted chatbot actions. Moreover, 16 sources of different types of chatbot service encounters were found. Based on all the findings stated above, this study created an integrated framework for chatbot service encounters in online customer service experiences. In conclusion, this study develops theoretical contributions by developing the integrated framework, creating an incident sorting process, and finding the sources for different service encounters. Based on these findings, this study also provides some managerial implications that companies could use to manage their chatbot services

See you soon again, chatbot? A design taxonomy to characterize user-chatbot relationships with different time horizons

Users interact with chatbots for various purposes and motivations – and for different periods of time. However, since chatbots are considered social actors and given that time is an essential component of social interactions, the question arises as to how chatbots need to be designed depending on whether they aim to help individuals achieve short-, medium- or long-term goals. Following a taxonomy development approach, we compile 22 empirically and conceptually grounded design dimensions contingent on chatbots’ temporal profiles. Based upon the classification and analysis of 120 chatbots therein, we abstract three time-dependent chatbot design archetypes: Ad-hoc Supporters, Temporary Assistants, and Persistent Companions. While the taxonomy serves as a blueprint for chatbot researchers and designers developing and evaluating chatbots in general, our archetypes also offer practitioners and academics alike a shared understanding and naming convention to study and design chatbots with different temporal profiles. © 2021 The Author

See you soon again, chatbot? A design taxonomy to characterize user-chatbot relationships with different time horizons

Users interact with chatbots for various purposes and motivations – and for different periods of time. However, since chatbots are considered social actors and given that time is an essential component of social interactions, the question arises as to how chatbots need to be designed depending on whether they aim to help individuals achieve short-, medium- or long-term goals. Following a taxonomy development approach, we compile 22 empirically and conceptually grounded design dimensions contingent on chatbots’ temporal profiles. Based upon the classification and analysis of 120 chatbots therein, we abstract three time-dependent chatbot design archetypes: Ad-hoc Supporters, Temporary Assistants, and Persistent Companions. While the taxonomy serves as a blueprint for chatbot researchers and designers developing and evaluating chatbots in general, our archetypes also offer practitioners and academics alike a shared understanding and naming convention to study and design chatbots with different temporal profiles