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Underpinning clean language interviewing is a set of skills that allow the interviewer great facility in tracking what has been presented. These skills include minimising personal inference and making an informed choice of what question to ask. They are grounded in the logic of the interviewee's data and the purpose of the interview.

This chapter makes visible four hidden skills I identified through reflection on a doctoral study I conducted using clean language interviewing. These are, how I: ‘parcel out’ sentences in order to build visual-spatial schema; apply content-free codes during the interview; decide what is salient in the interviewee's words and gestures; and use adjacency to navigate my way around the data. Since these skills are applied moment-by-moment during the interview, I refer to them as ‘coding in-the-moment’. I conclude with a comparison between grounded theory methodology and clean language interviewing.

Modelling is a research methodology that has received little academic attention since it began to be formulated in the 1970s. On the spectrum of clean language interviewing (CLI) applications described in Chapter 1, the most sophisticated is modelling, and especially modelling that takes place in real time during the interview.

This chapter defines what we mean by ‘a model’ and ‘modelling’ and explains how they are related to CLI. We situate the chapter by recounting how modelling became linked to CLI. To conclude we consider some of the methodological challenges faced by both the interviewee and interviewer involved in a modelling research project.

We also explain how interviewee metaphors discussed in Chapter 3 can support the modelling process. Much of the modelling that takes place during an interview resides in the background of the interaction. To illustrate modelling we provide an annotated transcript of a symbolic modelling interview that uses clean language to model the skill of ‘knowing what is essential’.

In this book the terms ‘clean language’ and ‘clean language interviewing’ are written using lower case, according to the convention of the American Psychological Association (sixth edition). ‘Clean language interviewing’ is sometimes abbreviated to CLI.

To conclude this book, we take stock of the state of the field of clean language interviewing (CLI). The field has matured considerably in 20 years and yet is still young and emergent. Through articulating the principles of CLI and exploring its application in many fields of practice, we hope this book might come to be seen as a milestone on its path. From its informal beginnings and earliest applications, we believe we can claim with justification that clean language interviewing has developed into a well-specified, well-tested and well-appreciated method that can be used to access both explicitly- and tacitly-held knowledge in a wide range of research projects.

As editors of this volume, we have been gratified and humbled by the ways in which CLI has been used by the contributors. Part II has demonstrated the value of clean language interviewing in both academic and applied research. The applications presented illustrate that CLI has breadth – given the diverse fields in which it has been applied – as well as depth, due to the various levels at which it can be used.

Our aim in this chapter is to reflect on themes that have emerged from the contributions in Part II and the experience of compiling the book as a whole. We begin by reviewing the frameworks that we regard as essential to CLI, then discuss three issues of practice and theory that have emerged from Part II. We sum up the key benefits and limitations of CLI for interviewers and interviewees before indicating some possible directions for future research.

This study aims to examine how the theory of planned behaviour and technology acceptance theory can be used to understand the adoption of non-pharmaceutical interventions (NPIs). The relationships between attitudes, behavioural intentions towards using NPIs, actual use of NPIs and word-of-mouth (WOM) were examined and compared between early and late adopters.

A survey was conducted to test the hypotheses with partial least squares structural equation modelling (n = 278).

The results indicate that relationships between attitudes, intentions and behavioural intentions were positive and significant in the whole data set – and that there were differences between the early and late adopters. WOM had no substantial relationship with actual usage and early adopters’ behavioural intentions.

This research gives a better sense of how WOM impacts attitudes, behavioural intentions and actual usage among early and late adopters of NPIs and highlights the effectiveness of WOM, especially among late adopters of NPIs. Furthermore, using the TAM allows us to make specific recommendations regarding encouraging the use of NPIs. A new three-stage communications model is introduced that uses early adopters as influencers to reduce the NPI adoption time by late adopters.

This paper replicates four highly cited, classic lab experimental studies in the provision of public goods. The studies consider the impact of marginal per capita return and group size; framing (as donating to or taking from the public good); the role of confusion in the public goods game; and the effectiveness of peer punishment. Considerable attention has focused recently on the problem of publication bias, selective reporting, and the importance of research transparency in social sciences. Replication is at the core of any scientific process and replication studies offer an opportunity to reevaluate, confirm or falsify previous findings. This paper illustrates the value of replication in experimental economics. The experiments were conducted as class projects for a PhD course in experimental economics, and follow exact instructions from the original studies and current standard protocols for lab experiments in economics. Most results show the same pattern as the original studies, but in all cases with smaller treatment effects and lower statistical significance, sometimes falling below accepted levels of significance. In addition, we document a “Texas effect,” with subjects consistently exhibiting higher levels of contributions and lower free-riding than in the original studies. This research offers new evidence on the attenuation effect in replications, well documented in other disciplines and from which experimental economics is not immune. It also opens the discussion over the influence of unobserved heterogeneity in institutional environments and subject pools that can affect lab results.

The Internet and social media have fundamentally transformed the ways in which individuals find jobs. Relatively little is known about how demand-side market actors use online information and the implications for social stratification and mobility. This study provides an in-depth exploration of the online recruitment strategies pursued by human resource (HR) professionals. Qualitative interviews with 61 HR recruiters in two southern US metro areas reveal two distinct patterns in how they use Internet resources to fill jobs. For low and general skill work, they post advertisements to online job boards (e.g., Monster and CareerBuilder) with massive audiences of job seekers. By contrast, for high-skill or supervisory positions, they use LinkedIn to target passive candidates – employed individuals who are not looking for work but might be willing to change jobs. Although there are some intermediate practices, the overall picture is one of an increasingly bifurcated “winner-take-all” labor market in which recruiters focus their efforts on poaching specialized superstar talent (“purple squirrels”) from the ranks of the currently employed, while active job seekers are relegated to the hyper-competitive and impersonal “black hole” of the online job boards.

This paper aims to examine project management segments based on customer satisfaction drivers and loyalty rather than traditional demographic or behavioural variables.

Data were gathered over 18 consecutive months, and 3,129 surveys were completed using a questionnaire. The statistical methods included partial least squares (PLS) structural equation modelling, finite mixture segmentation, prediction-oriented segmentation (PLS-POS) and multi-group analysis (PLS-MGA).

The findings indicate the existence of three segments among system delivery project customers based on the differences in the strengths of the path coefficients in the customer-centric structural model. In Segment 1, satisfaction based on the proposal was crucial for loyalty, with the value-for-money construct negatively impacting the repurchase intent construct. Segment 2 had a solid value-for-money orientation. In Segment 3, the critical path indicated that satisfaction drove repurchase intention, with satisfaction based mainly on the installation.

The research contributes to the segmentation theory by introducing a new way to segment the systems delivery projects customers based on the perceived strength of the relationships in a customer-centric structural model, which aligns with traditional segmentation theory in a way that most segmentation analyses do not. A new segmentation approach to the domain of project management theory is presented. Based on the results, treating the system delivery project customer base as a single homogenous group can lead to managerially misleading conclusions.