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Purpose: To outline recent developments in digital service delivery in order to encourage researchers to pursue collaborations with computer science, operations research, and data science colleagues and to show how such collaborations can expand the scope of research on emotion in service delivery.

Design/methodology/approach: Uses archived resources available at http://LivePerson.com to extract data based in genuine service conversations between agents and customers. We refer to these as “digital traces” and analyze them using computational science models.

Findings: Although we do not test significance or causality, the data presented in this chapter provide a unique lens into the dynamics of emotions in service; results that are not obtainable using traditional research methods.

Research limitations/implications: This is a descriptive study where findings unravel new dynamics that should be followed up with more research, both research using traditional experimental methods, and digital traces research that allows inferences of causality.

Practical implications: The digital data and newly developed tools for sentiment analyses allow exploration of emotions in large samples of genuine customer service interactions. The research provides objective, unobtrusive views of customer emotions that draw directly from customer expressions, with no self-report intervention and biases.

Originality/value: This is the first objective and detailed depiction of the actual emotional encounters that customers express, and the first to analyze in detail the nature and content of customer service work.

This chapter describes how conversational computer agents have been used in collaborative problem-solving environments. These agent-based systems are designed to (a) assess the students’ knowledge, skills, actions, and various other psychological states on the basis of the students’ actions and the conversational interactions, (b) generate discourse moves that are sensitive to the psychological states and the problem states, and (c) advance a solution to the problem. We describe how this was accomplished in the Programme for International Student Assessment (PISA) for Collaborative Problem Solving (CPS) in 2015. In the PISA CPS 2015 assessment, a single human test taker (15-year-old student) interacts with one, two, or three agents that stage a series of assessment episodes. This chapter proposes that this PISA framework could be extended to accommodate more open-ended natural language interaction for those languages that have developed technologies for automated computational linguistics and discourse. Two examples support this suggestion, with associated relevant empirical support. First, there is AutoTutor, an agent that collaboratively helps the student answer difficult questions and solve problems. Second, there is CPS in the context of a multi-party simulation called Land Science in which the system tracks progress and knowledge states of small groups of 3–4 students. Human mentors or computer agents prompt them to perform actions and exchange open-ended chat in a collaborative learning and problem-solving environment.

The purpose of this paper is to develop a measurement scale for assessing the quality of dialogic conversations among companies and digital publics in social media. Dialogic conversations are defined as sequences of communicative actions and counteractions taken by social actors for different purposes based on specific linguistic choices and characterised by diverse communicative approaches and the role played by the involved parties.

A multidimensional scale for measuring dialogic conversations is developed from relevant literature concerning dialogue and public engagement in the fields of corporate communication, public relations, management studies and conversation analysis. The scale is built on three main dimensions: organisation turn-taking, sequencing of conversation, repair strategies and procedures. A pilot study was conducted to purify it from irrelevant variables.

Results of the pilot study show a general good level of reliability for the majority of the proposed variables for Facebook but not for Twitter. This may indicate that Facebook is a more dialogical forum than Twitter.

This is the first study proposing a systematic measurement of the dialogue orientation of online conversations that takes into consideration the role of language and communicative actions. The proposed measurement offers corporate communication managers a concrete tool for evaluating the quality of their online communications and for identifying those areas of their online communication that need improvement.

If institutions of higher education are to remain at the forefront of the knowledge-generating enterprise, the nature of graduate-level teaching must be critically examined. Exploring the manner in which discussion is facilitated in a seminar-like context offers one avenue for attaining this understanding. This study aims to shed light on the prevalence, purpose, and form of discussion facilitation practices that were observed in a small group setting within a social science academic program at a large Southern California university. An exploratory, embedded case study was conducted over approximately 24 weeks using ethnographic and conversation analytic methods. Data sources consisted of ethnographic field notes, audio recordings of meetings, transcripts from those recordings, and artifacts, including literature used during each session. Results suggest that facilitating small group discussions requires balancing focus on the selected text and participant engagement, a diverse set of facilitation practices, and use of different strategies (or micro-avenues) to arrive at the same end. Study findings emphasize the importance of intersubjectivity and form versus function of speech in an educational environment. What is said and how it is said both have great implications for shared learning and understanding. Adaptability of mixed qualitative methods in this study demonstrates the potential of ethnography and conversation analysis as complementary approaches for understanding the functional nature of talk and interaction. Thus, the criteria for rigorous qualitative research, the view that ethnography and conversation analysis do not mix, and the under-valuing of critical multiplism in research need to be re-examined.

This study investigates associations between Facebook (FB) conversations and self-reports of substance use among youth experiencing homelessness (YEH). YEH engage in high rates of substance use and are often difficult to reach, for both research and interventions. Social media sites provide rich digital trace data for observing the social context of YEH's health behaviors. The authors aim to investigate the feasibility of using these big data and text mining techniques as a supplement to self-report surveys in detecting and understanding YEH attitudes and engagement in substance use.

Participants took a self-report survey in addition to providing consent for researchers to download their Facebook feed data retrospectively. The authors collected survey responses from 92 participants and retrieved 33,204 textual Facebook conversations. The authors performed text mining analysis and statistical analysis including ANOVA and logistic regression to examine the relationship between YEH's Facebook conversations and their substance use.

Facebook posts of YEH have a moderately positive sentiment. YEH substance users and non-users differed in their Facebook posts regarding: (1) overall sentiment and (2) topics discussed. Logistic regressions show that more positive sentiment in a respondent's FB conversation suggests a lower likelihood of marijuana usage. On the other hand, discussing money-related topics in the conversation increases YEH's likelihood of marijuana use.

Digital trace data on social media sites represent a vast source of ecological data. This study demonstrates the feasibility of using such data from a hard-to-reach population to gain unique insights into YEH's health behaviors. The authors provide a text-mining-based toolkit for analyzing social media data for interpretation by experts from a variety of domains.

This paper proposes a research method for analysing talk about accounting concepts, systems and numbers. The authors argue that studying accounting talk in situ is a fruitful way to understand both the role accounting plays in the framing of relationships between individuals and the associated emotional content of these exchanges. As such, the authors argue that conversation analysis (CA) is a useful complement to interviews in qualitative research.

The authors introduce a specific approach to CA called positioning theory, which captures the linguistic and emotional subtleties embedded within interpersonal interactions, and the way accounting impacts and mediates these relations through measuring, assessment and control. The authors draw on one particularly animated conversation about accounting in a manufacturing company. The conversation was a largely emotional and animated exchange between individuals where talk about accounting was imbued with metaphors, violence, sex and humour.

While participants in conversations may appear to draw on similar forms of language and expression, CA allows researchers to see that the meaning of these shared expressions change based on who is saying them, whom they are saying them to and how they are saying them. Dissecting conversations as they unfold, offers a more nuanced and multifaceted understanding of accounting as central to the social fabric of organisational life.

As opposed to interviews, which often suffer from the rationality of hindsight (referred to as retrospective rationality), CA captures the unfolding nature of accounting talk in real-time–not upon reflection.

This study operationalizes risks in stakeholder dialog (SD). It conceptualizes SD as co-produced organizational discourse and examines the capacities of organizers' and stakeholders' practices to create a shared understanding of an organization’s risks to their mutual benefit. The meetings and online forum of a German public service media (PSM) organization were used as a case study.

The authors applied corpus-driven linguistic discourse analysis (topic modeling) to analyze citizens' (n = 2,452) forum posts (n = 14,744). Conversation analysis was used to examine video-recorded online meetings.

Organizers suspended actors' reciprocity in meetings. In the forums, topics emerged autonomously. Citizens' articulation of their identities was more diverse than the categories the organizer provided, and organizers did not respond to the autonomous emergence of contextualizations of citizens' perceptions of PSM performance in relation to their identities. The results suggest that risks arise from interactionally achieved occasions that prevent reasoned agreement and from actors' practices, which constituted autonomous discursive formations of topics and identities in the forums.

This study disentangles actors' practices, mutuality orientation and risk enactment during SD. It advances the methodological knowledge of strategic communication research on SD, utilizing social constructivist research methods to examine the contingencies of organization-stakeholder interaction in SD.

The purpose of this paper is to explore the contribution of conversation as an element of interaction that occurs in a hairdressing service encounter with the aim of seeking to understand variations in conversation between “short” and “long‐term” clients; how conversation contributes to the development of “commercial friendships”; and how relationships develop through conversation.

Quota sampling is used to select eight hairdressing service encounters in one Australian salon for recording and subsequent interviews with clients. Quotas address gender and duration of continued patronage. Conversations and interviews were analysed thematically and using conversation analysis.

The progress and evolution of conversations varied between short and long‐term customers; topics also varied by this classification as well as gender. Conversation played an important function with respect to building friendship with the service provider; conversation also assisted in the development of long‐term relationships.

Apart from the small sample, the study was highly contextualised because it investigated encounters in a single hairdressing salon and explored perceptions of the service conversation from the perspective of only one party to the conversation, the client.

The findings point out the important role non‐task conversation can play in retaining customers in people‐processing services. Service providers perhaps can achieve more to improve the service experience and satisfaction of customers by placing less emphasis on the need for physical resources or promotion, instead focussing on the intangible of improving the conversation skills of their providers. More non‐task conversation and less task‐related talk may also facilitate a closer relationship between hairdresser and client. Further research on the nature and role of conversation during service encounters should offer guidance for improving the conversation skills of service providers and in improving customer retention.

This study specifically focuses on the role and nature of non‐task conversation as a specific aspect contributing to a customer's service encounter experience in a people processing service.

The notion of vulnerability underlies relationships of trust. Trust between leaders and staff is needed to solve concerns that hinder equity and excellence in teaching and learning. The purpose of this paper is to examine whether and how leaders show vulnerability by disclosing own possible contributions to concerns they try to resolve.

Data included transcripts of conversations held by 27 educational leaders about a concern with another staff and a questionnaire about the nature, causes and history of the concern. Questionnaire analysis identified if and how leaders described their own possible contribution prior to the conversation. Transcript analysis identified instances of leaders’ contribution disclosure.

Results indicate that while two-thirds of leaders identified an own contribution, when prompted prior to the conversation, one-third saw no own contribution. Leaders indicated contributing by not acting on the concern, by acting in ways inappropriate or insufficient to resolve the concern, or by not clearly communicating their concern in the past. Eight of the 27 leaders publicly disclosed their contribution in the actual conversation. In some conversations this disclosure prompted reciprocal disclosure of information about the concern and its causes by the other person, aiding a more effective concern resolution.

Through examining leaders’ interpersonal behavior in difficult conversations, the importance of leaders’ acknowledgments of own mistakes and communication of their own vulnerability is highlighted. A positive view of vulnerability is argued for, epistemic vulnerability, which manifests itself in the willingness to be honest and open to learning by accepting one’s own fallibility.

The success of e-retailers is intrinsically linked to the effectiveness of their logistics processes which, inevitably, involve third party service providers. As the most tangible representative of the e-retailers it is inevitable that customers expect the e-retailer to resolve delivery queries, including on social media platforms. The purpose of this paper is to investigate the effectiveness of e-retailers’ logistics-related customer service interactions on Twitter with a view towards identifying effective and ineffective social media customer service strategies.

The design and public nature of Twitter encourages organic conversations between e-retailers and customers as well as between customers and other customers. The methodology applied here accounts for this by collecting and analysing interactions within and as part of conversations, not as independent observations. In total, 203,349 tweets were collected from 22 of the most popular e-retailers. A random sample of 5,000 logistics-related conversations (16,998 tweets) is used for the analysis presented here and forms a foundation for future research.

Conversations are initiated by customers on the basis of 24 event triggers which can be categorised as occurring either before or after an order is delivered. These can be general queries or related to a specific order or delivery issue. The paper identifies a number of significant findings such as the extent to which e-retailers and logistics providers redirect customers to other channels to resolve queries, ignoring the implicit preference by customers to use Twitter to resolve their problem. Similarly, the lack of interactions between e-retailers and their logistics providers within the Twitter platform to help resolve customer queries results in ineffective customer service.

The study identifies the way in which e-retailers can substantially improve the effectiveness of the customer service they provide on Twitter by ensuring that customer queries can be resolved within the platform and by working with their logistics partners to do the same. This is critical since problems may be directed to the e-retailer or the logistics provider but both companies jointly suffer the consequences of poor customer service.

The study examines a hitherto underexplored aspect of retail logistics – the social media-based customer service activities of e-retailers. Methodologically, the study is rooted in the acknowledgement that interactions on Twitter form conversations and analyses should take this into account. This is a distinctly different approach from existing Twitter-related studies which conduct an automated sentiment analysis of tweets. This approach reveals a rich picture of interactions and, importantly, identifies where conversations between e-retailers begin, how they develop and how they conclude.