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The purpose of this paper is to explore the views of NHS England (NHSE) and Her Majesty’s Prison and Probation Service (HMPPS) commissioners about the Offender Personality Disorder (OPD) pathway.

A thematic analysis of four semi-structured interviews with NHSE and HMPPS commissioners is conducted.

Commissioners offered a cautious but confident assessment of the potential effectiveness of the OPD pathway, drawing particular attention to its potential to enhance the confidence and competency of staff, offer better value for money and provide enhanced progression routes for offenders with personality disorders. Additionally, commissioners identified a number of potential risks for the pathway including wider system flux, funding availability, multi-agency working, offender engagement and the need to evidence effectiveness.

The analysis is based on a small number of interviews. However, there are only a limited number of commissioners involved with the OPD pathway.

While the stronger focus on progression in the OPD pathway is a welcome departure from a narrow focus on high security Dangerous and Severe Personality Disorder (DSPD) services, the foundations of the OPD pathway ultimately lie with the DSPD programme and similar challenges are likely to follow. The system within which the pathway operates is subject to a great deal of flux and this inevitably poses significant challenges for pathway services, staff and offenders, as well as for those of us charged with its evaluation.

There has been limited empirical work with commissioners in the mental health field. The paper offers a unique insight into the perspectives of those responsible for commissioning the OPD pathway.

This paper aims to examine how consumers respond to social media influencers that are created through artificial intelligence (AI) and compares effects to traditional (human) influencers.

Across two empirical studies, the authors examine the efficacy of AI social media influencers. With Study 1, the authors establish baseline effects for AI influencers and investigate how social-psychological distance impacts consumer perceptions. The authors also investigate the role of an influencer’s agency – being autonomous or externally managed – to test the boundaries of the results and determine the interactive effects between influencer type and influencer agency. Study 2 acts as an extension and validation of Study 1, whereby the authors provide generalisability and overlay the role of need for uniqueness as a moderated mediator.

The authors show that there are similarities and differences in the ways in which consumers view AI and human influencers. Importantly, the authors find no difference in terms of intention to follow or personalisation. This suggests that consumers are equally open to follow an AI or human influencer, and they perceive the level of personalisation provided by either influencer type as similar. Furthermore, while an AI influencer is generally perceived as having lower source trust, they are more likely to evoke word-of-mouth intentions. In understanding these effects, the authors show that social distance mediates the relationship between influencer type and the outcomes the authors investigate. Results also show that AI influencers can have a greater effect on consumers who have a high need for uniqueness. Finally, the authors find that a lack of influencer agency has a detrimental effect.

The studies investigate consumers’ general response to AI influencers within the context of Instagram, however, future research might examine consumers’ response to posts promoting specific products across a variety of category contexts and within different social media platforms.

The authors find that in some ways, an AI influencer can be as effective as a human influencer. Indeed, the authors suggest that there may be a spill-over effect from consumer experiences with other AI recommendation systems, meaning that consumers are open to AI influencer recommendations. However, the authors find consistent evidence that AI influencers are trusted less than traditional influencers, hence the authors caution brands from rushing to replace human influencers with their AI counterparts.

This paper offers novel insight into the increasingly prominent phenomenon of the AI influencer. Specifically, it takes initial steps towards developing understanding as to how consumers respond to AI influencers and contrast these effects with human influencers.

This research explores anticipated long-term change in the retail and services marketplace, directly arising as a result of the Covid-19 pandemic.

A series of 20 in-depth interviews were conducted with retail and service stakeholders (executives, suppliers and thought-leaders) from across Asia-Pacific (New Zealand and Australia), the United Kingdom, Europe and the United States.

We identify six guiding principles for long-term change in the retail and services sector required to guide future business development and practice, including embedding new ways of working, rethinking the role and purpose of physical space, prioritizing digital elements, integrating employees in community, building agile supply and planning for future turbulence.

The Covid-19 pandemic is different from prior disruptive experiences in that it was a sudden shock to business and was collectively experienced by firms, workers and consumers across the globe. This research provides a view of decision-makers’ sensemaking and anticipated changes impacting the future retail and services marketplace.

This paper aims to explore how business-to-business (B2B) salespeople use social media and emulate value creation strategies used by social media influencers.

Using 28 interviews with salespeople, this paper develops six propositions and a conceptual framework that outlines when and how B2B salespeople use social media in value-creating sales.

This study’s findings provide a critical analysis of when social media are most effective and beneficial in supporting salespeople’s value-creating sales in various stages in the sales process (e.g. prospecting, opening relationships, qualifying prospects and serving accounts) and when they are less effective (e.g. presenting sales messages and closing sales).

This research yields a substantive understanding of the evolving role that social media play in B2B sales by examining B2B salespeople’s value creation strategies through the lens of social media influencers’ practice and outlines ideas for future research on B2B salespeople’s social media strategies.

The findings of this research can be used by B2B organizations to structure the training of B2B salespeople to use social media to the fullest extent by aligning specific strategies with different parts of the sales process.

This paper contributes by summarizing the B2B sales literature on social media and integrating recent insights from the social media influencer literature; empirically identifying how B2B salespeople use social media to create value, thus validating previous findings and extending understanding by offering a set of six theoretical propositions; and delineating B2B salespeople’s social media practice into 11 value creation strategies that are critically explored for their place in the sales process.

Brands are increasingly considering the use of chatbots to supplement, or even replace, humans in service interactions. Like humans, chatbots can follow certain service scripts in their encounters, which can subsequently determine the customer experience. Service scripts are verbal prescriptions that seek to standardize customer service interactions. However, while the role of service scripts is well documented, despite the increasing use of chatbots as a service mechanism, less is known about the effect, on consumers, of different service scripts presented during chatbot service encounters.

An experimental scenario was developed to test the research hypotheses. Respondents were randomly allocated to scenarios representing a 2 (service interaction: human, chatbot) × 2 (service script: education, entertainment) design. A total of 262 US consumers constituted the final sample for the study.

The findings indicate that when employing an education script, a significant positive effect occurs for human service agents (compared to chatbots) in terms of both satisfaction and purchase intention. These effects are fully mediated by emotion and rapport, showing that the bonds developed through the close proximity to a human service agent elicit emotion and develop rapport, which in turn influence service outcomes. However, this result is present only when an educational script is used.

This paper contributes to the emerging service marketing literature on the use of digital services, in particular chatbots, in service interactions. We show that differences occur in key outcomes dependent on the type of service script employed (education or entertainment). For managers, this study indicates that chatbot interactions can be tailored (in script delivered) in order to maximize emotion and rapport and subsequently consumer purchase intention and satisfaction.

This paper develops a generalizable, machine-learning-based method for measuring established marketing constructs using passive analysis of consumer-generated textual data from service reviews. The method is demonstrated using topic and sentiment analysis along dimensions of an existing scale: lodging quality index (LQI).

The method induces numerical scale ratings from text-based data such as consumer reviews. This is accomplished by automatically developing a dictionary from words within a set of existing scale items, rather a more manual process. This dictionary is used to analyze textual consumer review data, inducing topic and sentiment along various dimensions. Data produced is equivalent with Likert scores.

Paired t-tests reveal that the text analysis technique the authors develop produces data that is equivalent to Likert data from the same individual. Results from the authors’ second study apply the method to real-world consumer hotel reviews.

Results demonstrate a novel means of using natural language processing in a way to complement or replace traditional survey methods. The approach the authors outline unlocks the ability to rapidly and efficiently analyze text in terms of any existing scale without the need to first manually develop a dictionary.

The technique makes a methodological contribution by outlining a new means of generating scale-equivalent data from text alone. The method has the potential to both unlock entirely new sources of data and potentially change how service satisfaction is assessed and opens the door for analysis of text in terms of a wider range of constructs.

Since the early 1980s there have been fundamental changes in the structure and management of the UK public sector, based on the introduction of quasi‐markets. The literature suggests that, for markets to operate at their maximum level of efficiency, there is an overwhelming need for entrepreneurial activity. Attempts through a synthesis of the published literature, surveys of educational and health managers and case examples, to determine whether a new strain of leadership ‐ the public sector entrepreneur ‐ is emerging to display many of the characteristics of their business counterparts.

This paper aims to develop a novel and generalizable machine-learning based method of measuring established marketing constructs through passive analysis of consumer-generated textual data. The authors term this method scale-directed text analysis.

The method first develops a dictionary of words related to specific dimensions of a construct that is used to assess textual data from any source for a specific meaning. The method explicitly recognizes both specific words and the strength of their underlying sentiment.

Results calculated using this new approach are statistically equivalent to responses to traditional marketing scale items. These results demonstrate the validity of the authors’ methodology and show its potential to complement traditional survey approaches to assessing marketing constructs.

The method we outline relies on machine learning and thus requires either large volumes of text or a large number of cases. Results are reliable only at the aggregate level.

The method detail provides a means of less intrusive data collection such as through scraped social media postings. Alternatively, it also provides a means of analyzing data collected through more naturalistic methods such as open-response forms or even spoken language, both likely to increase response rates.

Scale-directed text analysis goes beyond traditional methods of conducting simple sentiment analysis and word frequency or percentage counts. It combines the richness of traditional textual and sentiment analysis with the theoretical structure and analytical rigor provided by traditional marketing scales, all in an automatic process.

This paper aims to set out an analysis of Gregory Bateson's thought about the relations between parts and wholes, between separateness and togetherness in order to illuminate the kind of answers Bateson proposed to the contemporary ecological dilemma.

It roughly situates discourses of the “enchantment” of nature on the side of togetherness and discourses of scientific disenchantment on the side of togetherness.

The essay looks at Bateson's discovery that neither separateness nor togetherness can ever be thought of without the other as an indication of the limits of both disenchantment and enchantment, and it suggests that awareness of these limits enables ecological insight.

The essay proposes a broad summary of a general problem in Gregory Bateson's epistemology and shows how it emerges in political, social and ecological space.

Argues that changes in education policy over the last decade‐and‐a‐half have moved some of the most traditionalist organizations in the UK, the “old” universities into a totally alien environment. The numbers of universities has nearly doubled, competition is encouraged through external audit and league tables, resourcing has been cut, while the student numbers have grown; and the twin concepts of “business” and “management” have entered their vocabulary. Asks whether, in a period of such accelerating change, the leadership styles in the old universities have changed to accommodate the new managerial culture. Gives a case example of the changing management and organizational development at the University of Nottingham to provide an example of the new style of higher education leadership.