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The purpose of this paper is to find out what role intermediaries have in facilitating communication with victims and prisoners at Parole Board (PB) oral hearings.

A survey was designed and administered to 39 PB members to find out their perceptions of, and experiences with, the use of intermediaries. Frequency tables and verbatim quotations are used to report the results.

Overall, participants had not experienced any use of intermediaries with victims or family members presenting victim personal statements at an oral hearing. Further, there had been limited use of intermediaries for prisoners attending oral hearings. Nevertheless, there was a good recognition of a range of communication needs that a prisoner might present with at a hearing. There was also general support for the use of intermediaries with some caution about possible delays to procedural fairness.

The early identification of communication support needs for prisoners and victims attending an oral hearing is essential. The PB should raise awareness with the PB Membership about the role of intermediaries. The PB should continue to develop guidance and policy surrounding intermediaries. Prison lawyers and HM Prison and Probation Service may require specialist training in identifying communication needs in vulnerable prisoners and identifying when a communication specialist might be required for an oral hearing.

To the best of the authors’ knowledge, this is the first published paper examining the role of intermediaries at PB oral hearings. It builds on the evidence base of the use of intermediaries in other criminal justice contexts.

Imprisonment impacts women’s childbearing and mothering experiences. Using sociological concepts of total institutions, pains of imprisonment and gendered pains of imprisonment, this study aims to explore the childbearing experiences of 18 Filipino incarcerated women.

A qualitative, inductive approach was undertaken to explore imprisoned women’s pregnancy experiences. This research project used reflexive thematic analysis to examine the data from semi-structured interviews with 18 Filipino pregnant prisoners.

The participants’ experiences of childbearing in prison were reflected in three overarching themes: lack of autonomy over pregnancy; reduced capacity to manage discomforts and needs; and coping with prison deprivations. These themes embody women’s experiences of how imprisonment disrupts Filipino women’s childbearing and mothering experiences. Furthermore, the results illustrated how the women navigated the prison regime to address their needs and cope with the pains of imprisonment.

Although there is a small but growing body of research specifically focusing on mothering and imprisonment, little consideration has been given to analyzing Filipino women’s pregnancy experiences in custody. This paper highlights an urgent need to reform correctional policies and practices to address incarcerated women’s distinct needs.

This study aims to establish a model for rapid and accurate emotion recognition in restaurant online reviews, thus advancing the literature and providing practical insights into electronic word-of-mouth management for the industry.

This study elaborates a hybrid model that integrates deep learning (DL) and a sentiment lexicon (SL) and compares it to five other models, including SL, random forest (RF), naïve Bayes, support vector machine (SVM) and a DL model, for the task of emotion recognition in restaurant online reviews. These models are trained and tested using 652,348 online reviews from 548 restaurants.

The hybrid approach performs well for valence-based emotion and discrete emotion recognition and is highly applicable for mining online reviews in a restaurant setting. The performances of SL and RF are inferior when it comes to recognizing discrete emotions. The DL method and SVM can perform satisfactorily in the valence-based emotion recognition.

These findings provide methodological and theoretical implications; thus, they advance the current state of knowledge on emotion recognition in restaurant online reviews. The results also provide practical insights into intelligent service quality monitoring and electronic word-of-mouth management for the industry.

This study proposes a superior model for emotion recognition in restaurant online reviews. The methodological framework and steps are elucidated in detail for future research and practical application. This study also details the performances of other commonly used models to support the selection of methods in research and practical applications.

This study aims to present a framework for automatically collecting, cleaning and analyzing text (news articles, in this case) to provide valuable decision-making information to destination management organizations. Keeping a record of certain aspects of the projected destination image of an attraction (Cancun in this study) will grant the design of better strategies for the promotion and administration of destinations without the time-consuming effort of manually evaluating high quantities of textual information.

Using Web scraping, news articles were collected from the USA, Mexico and Canada over an interval of one year. The documents were analyzed using an automatic topic modeling method known as Latent Dirichlet Allocation and a coherence analysis to determine the number of themes present in each collection. With the data provided, the authors were able to extract valuable information to understand how Cancun is presented to the countries.

It was found that in all countries, Cancun is an important destination to travel and vacation; however, given the period defined for this study (from July 2021 to July 2022), an important part of the articles analyzed was concerned with the sanitary measures derived from the COVID-19 pandemic. Besides, given the rise of violence and the threat of organized crime, many articles from the three countries are focused on warning potential tourists about the risks of traveling to Cancun.

The examination of the relevant literature revealed that similar analyses are manually performed by the experts on a set of predefined categories. Although those approaches are methodologically sound, the logistic effort and the time used could become prohibitively expensive, precluding carrying out this analysis frequently. Additionally, the preestablished categories to be studied in press articles may distort the results. For these reasons, the proposed framework automatically allows for gathering valuable information for decision-making in an unbiased manner.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

Once a corporate crisis is entangled with a social issue, how consumers make sense of the crisis can be impacted by issue-based opinion polarization. This study investigates the underlying mechanisms as consumers go through this process. This study also examines whether corporate social advocacy (CSA) can be an effective crisis-response strategy for mitigating reputational loss.

Theoretical inquiries were empirically tested using an online experiment (N = 792). The experiment set the context in China, in a working-overtime-issue-related crisis. It had a 2 (online exposure: anti-issue opinion vs. pro-issue opinion) × 2 (CSA: absence vs. presence) between-subject design with a continuous variable (pre-existing issue attitudes) measured before the manipulation.

This study found that pre-existing issue attitudes can be directly and indirectly associated with corporate reputation, for the issue attitudes influence how consumers attribute crisis blame. Such a direct effect of pre-existing issue attitudes varies depending on which polarized opinion consumers were exposed to on social media. This study also found CSA to be a robust crisis response strategy, through multiple mechanisms, in protecting the corporate reputation.

Scholars are scarcely aware of the threats that issue-based opinion polarization poses to corporate reputation. This study serves as an early attempt to provide theoretical explanations. In addition to this, this study extends the current conceptual understandings of CSA during corporate crises that involve social issues while adding fresh insights into the established typology of crisis-response strategies.

The purpose of this paper is to review ontologies and data models currently in use for augmented reality (AR) applications, in the cultural heritage (CH) domain, specifically in an urban environment. The aim is to see the current trends in ontologies and data models used and investigate their applications in real world scenarios. Some special cases of applications or ontologies are also discussed, as being interesting enough to merit special consideration.

A search using Google Scholar, Scopus, ScienceDirect and IEEE Xplore was done in order to find articles that describe ontologies and data models in AR CH applications. The authors identified the articles that analyze the use of ontologies and/or data models, as well as articles that were deemed to be of special interest.

This review found that CIDOC-CRM is the most popular ontology closely followed by Historical Context Ontology (HiCO). Also, a combination of current ontologies seems to be the most complete way to fully describe a CH object or site. A layered ontology model is suggested, which can be expanded according to the specific project.

This study provides an overview of ontologies and data models for AR CH applications in urban environments. There are several ontologies currently in use in the CH domain, with none having been universally adopted, while new ontologies or extensions to existing ones are being created, in the attempt to fully describe a CH object or site. Also, this study suggests a combination of popular ontologies in a multi-layer model.

The study focuses on drug safety regulation capture, reveals the inner mechanism and evolutionary characteristics of drug safety regulation capture and provides suggestions for effective regulation by pharmacovigilance.

The article introduces prospect theory into the game strategy analysis of drug safety events, constructs a benefit perception matrix based on psychological perception and analyzes the risk selection strategies and constraints on stable outcomes for both drug companies and drug regulatory authorities. Moreover, simulation was used to analyze the choice of results of different parameters on the game strategy.

The results found that the system does not have a stable equilibrium strategy under the role of cognitive psychology. The risk transfer coefficient, penalty cost, risk loss, regulatory benefit, regulatory success probability and risk discount coefficient directly acted in the direction of system evolution toward the system stable strategy. There is a critical effect on the behavioral strategies of drug manufacturers and drug supervisors, which exceeds a certain intensity before the behavioral strategies in repeated games tend to stabilize.

In this article, the authors constructed the perceived benefit matrix through the prospect value function to analyze the behavioral evolution game strategies of drug companies and FDA in the regulatory process, and to evaluate the evolution law of each factor.

To adapt to the rapidly changing market environment, firms must constantly adjust and change their knowledge base to develop new technologies. The purpose of this paper is to analyze the improvement path of firms’ breakthrough innovation from the perspective of knowledge recombination in the context of dynamic change in the knowledge base. By analyzing the influencing mechanism of environmental dynamism on the relationship between the two, this paper provides a theoretical foundation for managers to make knowledge recombination decisions under a dynamic external environment while further enriching the firm’s innovation achievements.

Using data from 220 manufacturing firms listed on the Shanghai and Shenzhen A-share stock from 2010 to 2018, an extensive panel data set was constructed to investigate the effect of knowledge recombination, which was divided into recombination creation and recombination reuse, on firms’ breakthrough innovation. In addition, the authors differentiated environmental dynamism as market dynamism and technological dynamism and then examined its moderating role in the above relationships.

The research results show that various recombination behaviors of knowledge elements have a differentiated effect on firms’ breakthrough innovation presented as follows: Knowledge recombination creation is significantly positively correlated with firms’ breakthrough innovation, while knowledge recombination reuse is significantly negatively correlated with firms’ breakthrough innovation. In addition, environmental dynamism has a considerable moderating effect between knowledge recombination and firms’ breakthrough innovation further, emphasizing that the moderating effect on different types of knowledge recombination behaviors is significantly distinct.

First, given that this study refers to several Chinese noted databases to collect second-hand data for empirical analysis, future research could use first-hand data by collecting questionnaire survey and interview to provide a more practical and detailed research conclusion. Second, the authors focused on the contextual variable to explore the moderating role of environmental dynamism on the relationship between knowledge recombination and breakthrough innovation. Nevertheless, the indirect effects of other internal factors were not discussed. The authors advocate future studies to involve other moderators from employee social and phycological perspectives, such as trust in colleagues in the proposed theoretical models in this study.

This study is conducive for managers to attach great attention to knowledge management practices in the firm and to understand the critical role of knowledge recombination in affecting innovation performance under dynamic environmental changes. Moreover, this study provides practical guidance and serves as a reference for firms to strengthen their knowledge recombination ability as full utilization of existing knowledge elements and exploration of new knowledge values.

Primarily, from the perspective of dynamic changes in the knowledge base, this paper explores how the knowledge recombination behaviors affect firms’ breakthrough innovation, thereby enriching and extending the relationship theory between knowledge recombination capabilities and breakthrough innovation, while new and valuable ideas are provided in the study of issues related to the firms’ breakthrough innovation; Moreover, this study analyzes the moderating effects of diverse types of environmental dynamism on the relationship between knowledge recombination and firms’ breakthrough innovation from a multi-dimensional perspective proposing that the moderating effects of environmental dynamism on different knowledge recombination behaviors are distinct.

Sustainable economic growth in both developed and developing countries requires the restructuring and expansion of road transportation infrastructures (RTIs). However, RTIs are always subject to high costs and delays, especially in developing countries with fewer resources than developed ones. Cost overruns and inaccurate forecasts usually lead to project failures. In this regard, some governments in developing countries have adopted public–private partnerships (PPPs) to deliver RTI projects with very positive outcomes. However, academic research has not yet studied the most recurring barriers and associated solutions to adopting PPPs in RTIs particularly for developing countries. This paper aims to fill up this knowledge gap in the existing literature.

A Delphi survey method involving 103 experts in RTIs based in Iran was implemented. Results indicated that the most perceived barriers to applying PPPs in RTIs in developing countries are linked to political, legal and economic factors. Ten other experts also participated in semistructured interviews, which were thematically analyzed to provide practical effective solutions for overcoming those identified barriers.

The findings indicated that all the presented barriers achieved above-average scores and could be considered severe obstacles of applying PPPs in RTIs for developing countries. In terms of barriers and solutions reported, these seem to converge on three profound elements: political stability, legal framework and conjoint management.

To the best of the authors’ knowledge, this is the first-ever research study regarding the barriers to adopting PPPs in delivering RTI projects for developing countries. Practical recommendations for overcoming these perceived barriers and achieving better implementation of PPPs in RTIs for developing countries were advocated. This work has contributed to the extant PPP theory as the management of coproduction in delivering RTI projects.