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This study aims to examine the impact of controversial governance practices on media coverage under a specific context. Based on the attribution theory, this study develops a theoretical framework to explore how antecedent factors can influence attribution process under a particular cultural context.

This paper presents a behavioral view of the media and corporate governance to demonstrate how media attributes different reasons for the same controversial governance practice in Chinese-specific context. Using 1,198 non-state-owned listed company observations in China as the study sample, cross-section data are used to build a multiple linear regression mode to test hypotheses.

The analysis indicates that the media imposes fewer penalties on founder-CEO firms than on non-founder-CEO firms for engaging in controversial governance practices, such as CEO compensation. CEO tenure negatively moderates the effect of CEO compensation on negative media coverage in non-founder-CEO firms. The positive media bias evidence for founder-CEO firms exists only when the firm is better performed.

This study’s contribution to the governance literature starts with its logical reasoning of basic assumptions in the agency theory, and that media penalty will arise when managers impose actions that against interests of shareholders or other stakeholders. This study shows that the rule is not always true. The findings also bridge the connection of governance literature and reputation literature to better explain how media can act as a social arbitration role.

This study provides insights into how belief and information of reputational evaluators affect attribution consequences on controversial governance practices. Moreover, this study looks beyond the internal elements and focuses on China’s traditional cultural context as well. Specifically, the authors concentrate on the attribution process by showing the importance of evaluators’ framing tendency with regard to controversial practices. The results extend the knowledge about how conformity makes media coverage shows a bias effect on interactions during the evaluation process.

In the recent dynamic market, supply chain disruptions are rapidly increasing with varied customer demand, technological changes, uncertain pandemic events etc. To overcome the unexpected disruptions, supply chain of each business should be resilient and pharmaceutical supply chain (PSC) is no exception. Motivated by the challenges and unexpected pandemic disruptions, this paper aims to examine the performance indicators (PIs) of the resilient PSC and to predict the resilience level for a certain time period in the context of Bangladesh.

The aim of this paper presents a structured framework based on the Delphi method, fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) and system dynamics (SD). The proposed methodology was validated using expert's inputs from the relevant field in Bangladesh. This study reveals the influential relationships of indicators and resilience level using fuzzy DEMATEL and SD to improve the resiliency.

Findings revealed that “Supply chain risk orientation”, “Visibility”, “Flexibility”, “Agility in supply chain” and “Collaboration” are the top five influential performance indicators for resilient PSC. The cause and effect relationship found that “IT capability”, “Flexibility”, “Supply chain network design”, “Resource availability”, “Supply chain risk orientation” and “Velocity” were in cause category which play a vital role for establishing resilient supply chain. SD approach has developed a model for predicting the resilience level of the supply chain.

This work is one of the initial contributions in the literature that has targeted on the identification and analysis of the significant PIs and predicting the resilience level of the PSC.

In this contribution to EDI's professional insights, the authors develop practical and evidence-based recommendations that are developed for bias mitigation, discretion elimination and process optimization in panel evaluations and decisions in research funding. An analysis is made of how the expectation of “selling science” adds layers of complexity to the evaluation and decision process. The insights are relevant for optimization of similar processes, including publication, recruitment and selection, tenure and promotion.

The recommendations are informed by experiences and evidence from commissioned projects with European research funding organizations. The authors distinguish between three aspects of the evaluation process: written applications, enacted performance and group dynamics. Vignettes are provided to set the stage for the analysis of how bias and (lack of) fit to an ideal image makes it easier for some than for others to be funded.

In research funding decisions, (over)selling science is expected but creates shifting standards for evaluation, resulting in a narrow band of acceptable behavior for applicants. In the authors' recommendations, research funding organizations, evaluators and panel chairs will find practical ideas and levers for process optimization, standardization and customization, in terms of awareness, accountability, biased language, criteria, structure and time.

Showing how “selling science” in research funding adds to the cumulative disadvantage of bias, the authors offer design specifications for interventions to mitigate the negative effects of bias on evaluations and decisions, improve selection habits, eliminate discretion and create a more inclusive process.

In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

As hybrid organizations become increasingly common, the authors observe that some hybrid forms are becoming institutionalized and legitimated. The authors explore the implications of the institutionalization of hybridity, addressing both the internal tensions that plague many hybrids and the external tensions stemming from evaluator assessments and stakeholder uncertainty. The authors propose that institutionalization can dampen internal tensions associated with hybridity and also facilitate legitimation and acceptance by external audiences. The authors present identity as a useful theoretical lens through which to examine these questions, as identities are born from, but also have the potential to modify, existing institutional arrangements. The authors present directions for future research at the juncture of identity, hybridity, and institutionalization, suggesting potential avenues of inquiry in this productive stream of research.

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.

Digital voice-of-customer (digital VoC) analysis is gaining much attention in the field of quality management. Digital VoC can be a great source of knowledge about customer needs, habits and expectations. To this end, the most popular approach is based on the application of text mining algorithms named topic modelling. These algorithms can identify latent topics discussed within digital VoC and categorise each source (e.g. each review) based on its content. This paper aims to propose a structured procedure for validating the results produced by topic modelling algorithms.

The proposed procedure compares, on random samples, the results produced by topic modelling algorithms with those generated by human evaluators. The use of specific metrics allows to make a comparison between the two approaches and to provide a preliminary empirical validation.

The proposed procedure can address users of topic modelling algorithms in validating the obtained results. An application case study related to some car-sharing services supports the description.

Despite the vast success of topic modelling-based approaches, metrics and procedures to validate the obtained results are still lacking. This paper provides a first practical and structured validation procedure specifically employed for quality-related applications.

The voice of school principals represents the principals' thoughts and experiences because of their as teachers' evaluator. It provides principals' perception on making sense the teacher evaluation. In qualitative research, voice can provide the truth and meaning of principals' experience in teachers evaluation. Their voices in the qualitative interviews are recorded and transcribed into words (Jackson and Mazzei, 2009 and Charteris and Smardon, 2018). By listening to the voices of principals in five provinces in Indonesia, this study, a qualitative research, intends to explore the principals' sensemaking in teacher evaluation.

This study adopted a qualitative approach, as it was principally concerned with capturing participants' direct experiences in their natural setting as both the teachers' evaluator and school leader (Patton, 2002). The qualitative interview and content analysis were used in this study. The qualitative interview is a type of conversation used to explore informants' experiences and interpretations; in this study, the headmaster (Mishler, 1986; Spradley, 1979 in Hatch, 2002). Researchers used the interviews to uncover the structure of meaning used by principals in making sense the policies that determine teacher evaluations and that are used to carry out evaluations within principal's local authority. The implicit structure can be discovered from direct observation, and the qualitative interviews can bring this meaning to the surface (Hatch, 2002). Therefore, by applying the qualitative interviews, it is expected that information or “unique” interpretations from the principal can be obtained (Stake, 2010). Content analysis is a research technique for making valid conclusions from oral texts into a research context. This analysis can provide new insights, improve researchers' understanding of certain phenomena, or inform other practical actions through the use of verbal data collected in the form of answers to open interview questions (Krippendorff, 2004).

There are three important findings relating to principals' sensemaking of teachers' evaluation; they are teachers' length of service, principals' perceptions of teacher evaluations and consistency in teacher performance improvement. The principals' perception greatly influences their beliefs and sensemaking of teacher evaluation. In essence, teacher evaluation has not been used to identify high-quality teachers. Principals focus more on the improvement of teachers' welfare than teacher actual performance.

Future research should explore principals' attitude toward the stakeholders when student achievement is not in line with the consistent increase in teachers' performance ratings. And, it is also necessary to investigate the policy makers response to see the consistent improvement in teacher's evaluation is not in line with student achievement. Finally, how to eliminate the culture of joint responsibility without causing frictions in the school environment.

The authors hereby declare that this submission is their own work, and to the best of their knowledge, it contains no materials previously published or written by another person, or substantial proportions of material that have been accepted for the award of any other degree or diploma any other publishers.

The objective of this research is to investigate the capabilities of the ChatGPT GPT-4 model, a form of artificial intelligence (AI), in comparison to human experts in the context of construction project risk management.

Employing a mixed-methods approach, the study draws a qualitative and quantitative comparison between 16 human risk management experts from Finnish construction companies and the ChatGPT AI model utilizing anonymous peer reviews. It focuses primarily on the areas of risk identification, analysis, and control.

ChatGPT has demonstrated a superior ability to generate comprehensive risk management plans, with its quantitative scores significantly surpassing the human average. Nonetheless, the AI model's strategies are found to lack practicality and specificity, areas where human expertise excels.

This study marks a significant advancement in construction project risk management research by conducting a pioneering blind-review study that assesses the capabilities of the advanced AI model, GPT-4, against those of human experts. Emphasizing the evolution from earlier GPT models, this research not only underscores the innovative application of ChatGPT-4 but also the critical role of anonymized peer evaluations in enhancing the objectivity of findings. It illuminates the synergistic potential of AI and human expertise, advocating for a collaborative model where AI serves as an augmentative tool, thereby optimizing human performance in identifying and managing risks.

The purpose of this paper is to understand the dynamic and power-laden nature of university–society collaboration from the individual academic's point of view.

This paper applies an autoethnographic approach in following a specific collaboration process through detailed fieldnotes and continuous reflections.

This research presents university–society collaboration as an emergent, volatile and fairly unpredictable process, involving a multitude of actors on both sides. The interactions among actors shape the emerging process and power relationships. The academic's situation could be understood in terms of multiple and shifting subject positions that could be embraced, accepted, resisted or surrendered to by the academic.

These findings may help academics with own experiences of collaboration to shed light on their observations. Novice academics, interested in collaborating with society, should be aware of the possibility of tensions and exercise of power in interactions with societal actors. When setting up collaboration agreements, academic and societal actors are advised to openly discuss potential problems and how to handle those.

This unique, in-depth testimony of a single collaboration process from the individual academic's point of view uncovers previously unobserved dynamic and political attributes of the process.