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During the evaluation of European Capital of Culture (ECoC) Aarhus 2017, the evaluation organisation rethinkIMPACTS 2017 formulated a set of “dilemmas” capturing the main challenges arising during the design of the ECoC evaluation. This functioned as a framework for the evaluation process. This paper aims to present and discuss the relevance of the “Evaluation Dilemmas Model” as subsequently applied to the Galway 2020 ECoC programme evaluation.

The paper takes an empirical approach including auto-ethnography and interview data to document and map the dilemmas involved in undertaking an evaluation in two different European cities. Evolved via a process of practice-based research, the article addresses the development of and the arguments for the dilemmas model and considers its potential for wider applicability in the evaluation of large-scale cultural projects.

The authors conclude that the “Evaluation Dilemmas Model” is a valuable heuristic for considering the endogenous and exogenous issues in cultural evaluation.

The model developed is useful for a wide range of cultural evaluation processes including – but not limited to – European Capitals of Culture.

What has not been addressed in the academic literature is the process of evaluating ECoCs; especially how evaluators often take part in an overall process that is not just about the evaluation but also planning and delivering a project that includes stakeholder management and the development of evaluation criteria, design and methods.

As a crucial institutional form established since the Chinese economic reform, the system of competitive local governments has been shaping the characteristics of China's socialist market economy to a considerable degree.

This study not only adopts the view of existing studies that attribute the economic motive of local governments to rent and consider land public finance as a means through which local governments carry out strategic investment but also attempts to further develop the view within a Marxist analytical framework.

As a result, the local governments have helped to maintain an incredibly high investment rate over a considerable period of time, facilitating the continuous, rapid growth of the Chinese economy.

This study concludes that China's local governments function as the productive allocator and user of rent in the strategic investment based on land public finance and thereby embed themselves in the relative surplus-value production initially arising from competition amongst enterprises, forming the dual structure of relative surplus-value production unique to China's economy.

The purpose of this paper is to discuss findings from an Arts and Humanities Research Council (AHRC)-funded research project into the heritage culture of British folk tales. The project investigated how such archival source material might be made relevant to contemporary audience via processes of artistic remediation. The research considered artists as “cultural intermediaries”, i.e. as actors occupying the conceptual space between production and consumption in an artistic process.

Interview data is drawn from a range of 1‐2‐1 and group interviews with the artists. These interviews took place throughout the duration of the project.

When artists are engaged in a process of remediation which has a distinct arts marketing/audience development focus, they begin to intermediate between themselves and the audience/consumer. Artist perceptions of their role as “professionals of qualification” is determined by the subjective disposition required by the market context in operation at the time (in the case of this project, as commissioned artists working to a brief). Artists’ ability (and indeed willingness) to engage in this process is to a great extent proscribed by their “sense-of-self-as-artist” and an engagement with Romantic ideas of artistic autonomy.

A consideration of the relationship between cultural intermediation and both cultural policy and arts marketing. The artist-as-intermediary role, undertaking creative processes to mediate how goods are perceived by others, enables value-adding processes to be undertaken at the point of remediation, rather than at the stage of intermediation.

This article informs school leaders and staffs about existing research findings on the use of data-driven decision-making in creating class rosters. Given that teachers are the most important school-based educational resource, decisions regarding the assignment of students to particular classes and teachers are highly impactful for student learning. Classroom compositions of peers can also influence student learning.

A literature review was conducted on the use of data-driven decision-making in the rostering process. The review addressed the merits of using various quantitative metrics in the rostering process.

Findings revealed that, despite often being purposeful about rostering, school leaders and staffs have generally not engaged in data-driven decision-making in creating class rosters. Using data-driven rostering may have benefits, such as limiting the questionable practice of assigning the least effective teachers in the school to the youngest or lowest performing students. School leaders and staffs may also work to minimize negative peer effects due to concentrating low-achieving, low-income, or disruptive students in any one class. Any data-driven system used in rostering, however, would need to be adequately complex to account for multiple influences on student learning. Based on the research reviewed, quantitative data alone may not be sufficient for effective rostering decisions.

Given the rich data available to school leaders and staffs, data-driven decision-making could inform rostering and contribute to more efficacious and equitable classroom assignments.

This article is the first to summarize relevant research across multiple bodies of literature on the opportunities for and challenges of using data-driven decision-making in creating class rosters.

The purpose of this paper is to provide an inside-out perspective on the practices and effects of talent management (TM) in a multinational organization.

The study adopts an autoethnographic approach focusing on the experiences of the first author during her employment in a multinational organization. This approach contributes to the literature by providing an insider talent perspective that thus far has not been presented in TM research.

Applying autoethnography as a means to address the inside-out perspective in TM reveals a tension. The authors label this phenomenon the “talent paradox,” defined as the mix of simultaneously occurring opportunities and risks for individuals identified and celebrated as a talent.

The paper may be of value to TM scholars and practitioners, as well as to employees who have been identified as high potentials or talents in their organizations. In contrast with the TM literature’s optimism, the findings illuminate that being identified as a talent may paradoxically produce both empowerment and powerlessness. Attending to personal aspects of TM processes is relevant for organizations as well as for individuals as it enables reflection and sensemaking.

The present study contributes to our understanding of how to curb burnout among hospital staff over time. The authors extend existing research by examining the mediating role of mission valence in the link between transformational leadership and burnout.

Self-administered questionnaire data from employees in a Canadian general hospital (N = 185) were analyzed using a time-lagged research design to examine whether transformational leaders can increase employees' attraction to the organization's mission (i.e. mission valence) and in turn alleviate long-term burnout.

Structural equation modeling analysis demonstrated that transformational leadership (time 1) was negatively related to the burnout components of emotional exhaustion and depersonalization (time 2). Further, the results showed that mission valence mediated these relationships.

The study findings are important for managers and professionals as they identify transformational leadership as a potent strategy to alleviate employee burnout and clarify the process through which this is achieved, namely, by increasing mission valence.

To date, surprisingly little research has explored how transformational leadership influences followers' burnout. To address this issue, the present study examined the role of transformational leadership on staff burnout through the mechanism of increasing mission valence. Understanding how to mitigate burnout is particularly critical in health care organizations given that burnout not only negatively impacts employee wellbeing but also the wellbeing and quality of care provided to patients.

According to the significant growth of literature and continued adoption of people analytics in practice, it has been promised that people analytics will inform evidence-based decision-making and improve business outcomes. However, existing people analytics literature remains underdeveloped in understanding whether and how such promises have been realized. Accordingly, this study aims to investigate the current reality of people analytics and uncover the debates and challenges that are emerging as a result of its adoption.

This study conducts a systematic literature review of peer-reviewed articles focused on people analytics published in the Association of Business School (ABS) ranked journals between 2011 and 2021.

The review illustrates and critically evaluates several emerging debates and issues faced by people analytics, including inconsistency among the concept and definition of people analytics, people analytics ownership, ethical and privacy concerns of using people analytics, missing evidence of people analytics impact and readiness to perform people analytics.

This review presents a comprehensive research agenda demonstrating the need for collaboration between scholars and practitioners to successfully align the promise and the current reality of people analytics.

This systematic review is distinct from existing reviews in three ways. First, this review synthesizes and critically evaluates the significant growth of peer-reviewed articles focused on people analytics published in ABS ranked journals between 2011 and 2021. Second, the study adopts a thematic analysis and coding process to identify the emerging themes in the existing people analytics literature, ensuring the comprehensiveness of the review. Third, this study focused and expanded upon the debates and issues evolving within the emerging field of people analytics and offers an updated agenda for the future of people analytics research.

The purpose of this paper is to examine how participants in diverse schools newly implement the Sanford Harmony social and emotional learning (SEL) program and perceive its benefits for students and overall school climate.

The current study employed a convergent parallel mixed-methods design with a sample of five elementary schools in the western USA. Measures included classroom observations, administrator interviews, teacher interviews and focus groups, student focus groups, and a teacher questionnaire.

Findings indicated expected variation in implementation across schools, although all participants reacted favorably to the program and, importantly, would recommend the program to others. Administrators, teachers and students all saw the value of the program, particularly in terms of student relationship building and improved school climate. Implementation challenges experienced by schools were consistent with research on diffusion of innovations.

The present study demonstrates the importance of effective professional development, continued support, collective decision making and intentional integration of the SEL program throughout a school to support robust implementation and ultimately achieve intended outcomes.

Researchers have yet to examine in-depth implementation of the Sanford Harmony program and how best to support scale-up and more intentional implementation in schools. As implementation fidelity is a key component of a program achieving intended outcomes, the findings from the present study contribute to the knowledge base of supporting SEL program implementation.

Limited facilities operating and modernization budgets require organizations to carefully identify, prioritize and authorize projects to ensure allocated resources align with strategic objectives. Traditional facility prioritization methods using risk matrices can be improved to increase granularity in categorization and avoid mathematical error or human cognitive biases. These limitations restrict the utility of prioritizations and if erroneously used to select projects for funding, they can lead to wasted resources. This paper aims to propose a novel facility prioritization methodology that corrects these assessment design and implementation issues.

A Mamdani fuzzy logic inference system is coupled with a traditional, categorical risk assessment framework to understand a facilities’ consequence of failure and its effect on an organization’s strategic objectives. Model performance is evaluated using the US Air Force’s facility portfolio, which has been previously assessed, treating facility replicability and interruptability as minimization objectives. The fuzzy logic inference system is built to account for these objectives, but as proof of ease-of-adaptation, facility dependency is added as an additional risk assessment criterion.

Results of the fuzzy logic-based approach show a high degree of consistency with the traditional approach, though the value of the information provided by the framework developed here is considerably higher, as it creates a continuous set of facility prioritizations that are unbiased. The fuzzy logic framework is likely suitable for implementation by diverse, spatially distributed organizations in which decision-makers seek to balance risk assessment complexity with an output value.

This paper fills the identified need for portfolio management strategies that focus on prioritizing projects by risk to organizational operations or objectives.

Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of all or many processes is seen as the way forward, with robots performing various tasks instead of people. Meat cutting is one of these tasks. Smart novel solutions, including smart knives, are required, with the smart knife being able to analyse and predict the meat it cuts. This paper aims to review technologies with the potential to be used as a so-called “smart knife” The criteria for a smart knife are also defined.

This paper reviews various technologies that can be used, either alone or in combination, for developing a future smart knife for robotic meat cutting, with possibilities for their integration into automatic meat processing. Optical methods, Near Infra-Red spectroscopy, electrical impedance spectroscopy, force sensing and electromagnetic wave-based sensing approaches are assessed against the defined criteria for a smart knife.

Optical methods are well established for meat quality and composition characterisation but lack speed and robustness for real-time use as part of a cutting tool. Combining these methods with artificial intelligence (AI) could improve the performance. Methods, such as electrical impedance measurements and rapid evaporative ionisation mass spectrometry, are invasive and not suitable in meat processing since they damage the meat. One attractive option is using athermal electromagnetic waves, although no commercially developed solutions exist that are readily adaptable to produce a smart knife with proven functionality, robustness or reliability.

This paper critically reviews and assesses a range of sensing technologies with very specific requirements: to be compatible with robotic assisted cutting in the meat industry. The concept of a smart knife that can benefit from these technologies to provide a real-time “feeling feedback” to the robot is at the centre of the discussion.