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Computer-aided/assisted qualitative data analysis software (CAQDAS) supports qualitative and mixed methods researchers to organize, analyze, and explore data in a meaningful, and efficient, way. Successfully utilizing CAQDAS software can be challenging, particularly for the novice researcher. To assist all researchers 21 CAQDAS dilemmas are articulated. These relate to choosing, using, and getting started with the software, as well as writing about CAQDAS use. These dilemmas suggest there is no right way to use CAQDAS programs, rather the specific research project, along with researcher experience and philosophy, should drive the extent to which any project utilizes the extensive CAQDAS capabilities, while also encouraging the researcher(s) to drive their ideas and exploration beyond what they initially thought possible.

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.

Social and technological changes of the 21st century influence how and what students learn while in college. New research about student learning suggests a critical need for higher education to reform teaching and learning methods. Experiential and inquiry-based learning (IBL) are essential to engaging students and achieving the type of learning demanded by today’s global workforce. These skills include critical analysis, systems thinking, problem-solving, and spanning cultural and disciplinary boundaries. For decades, international educators purported that education abroad provided these skills for participants, yet recent research suggests that the same factors inhibiting deep learning on campus can also affect global, experiential environments. No longer can faculty members assume that students will learn from experience alone; they must intentionally construct activities accounting for the specific characteristics and needs of learners. This chapter outlines trends influencing student learning, making the case that traditional, content-based, directed instruction is poorly suited for student learning in the 21st century. The authors suggest that applying experiential and inquiry-based practices is essential to constructing effective education abroad program. Case studies, strategies, tools, and resources are provided to assist faculty with developing competencies to teach through an experiential and inquiry-based pedagogical framework.

Purpose: This study explores the perspectives of data experts (DXs) and refugees on the algorithms used by law enforcement officers and focuses on emerging insecurities. The authors take police risk-scoring algorithms (PRSA) as a proxy to examine perceptions on algorithms that make/assist sensitive decisions affecting people’s lives.

Methodology/approach: In-depth interviews were conducted with DXs (24) in Estonia and refugees (19) in Estonia and Turkey. Using projective techniques, the interviewees were provided a simple definition of PRSA and a photo to encourage them to share their perspectives. The authors applied thematic analysis to the data combining manual and computer-aided techniques using the Maxqda software.

Findings: The study revealed that the perspectives on PRSA may change depending on the individual’s position relative to the double security paradox surrounding refugees. The use of algorithms for a sensitive matter such as security raises concerns about potential social outcomes, intentions of authorities and fairness of the algorithms. The algorithms are perceived to construct further social borders in society and justify extant ideas about marginalized groups.

Research limitations: The study made use of a small population sample and aimed at exploring perspectives of refugees and DXs by taking PRSA as the case without targeting representativeness.

Originality/value: The study is based on a double security paradox where refugees who escape their homelands due to security concerns are also considered to be national security threats. DXs, on the other hand, represent a group that takes an active role in decisions about who is at risk and who is risky. The study provides insights on two groups of people who are engaged with algorithms in different ways.

The chapter discusses abductive thematic analysis as an innovative qualitative methodology in hospitality and tourism research. The novelty of the abductive approach is to combine the power of both deductive and inductive reasoning: it is possible to initiate the research starting from an existing theoretical, without renouncing to a creative phase where the researcher interprets the phenomenon beyond the words utilized and theorizes dependencies between concepts. The chapter further presents a case study to illustrate how abductive thematic analysis can be applied to study small hospitality and tourism businesses. The chapter further highlights the benefits of adapting thematic analysis to abductive reasoning, which is a paradigmatic position thus adding rigor to hospitality and tourism. The chapter finally highlights future avenues for development of methodology research toward adding further rigor to this novel methodology.

The rise of arts and culture is transforming citizen politics. Though new to many social scientists, this is a commonplace for many policy makers. We seek to overcome this divide by joining culture and the arts with classic concepts of political analysis. We offer an analytical framework incorporating the politics of cultural policy alongside the typical political and economic concerns. Our framework synthesizes several research streams that combine in global factors driving the articulation of culture into political/economic processes. The contexts of Toronto and Chicago are explored as both enhanced the arts dramatically, but Toronto engaged artists qua citizens, while Chicago did not.

In antitrust class-action litigation, courts are increasingly unlikely to accept the presumption that all class members were harmed by price-fixing among a group of firms or by exclusionary behavior by a single firm. Econometric methods typically applied in antitrust and other settings estimate the average effect of the challenged conduct, but do not inform impact for individual class members. We present classwide econometric methods and statistical tests for detecting the existence (or lack thereof) of common impact and determining what proportion (if any) of the proposed class suffered injury in many class actions. We conclude that econometric tools can meaningfully inform the legal process, even when courts demand proof of common impact.