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This paper introduces a methodology to identify, analyse and represent heritage site attributes, emphasizing their impact on value, authenticity, integrity and management, with a case study on Ghadames, Libya. Inscribed in 1986 and moved to the In-Danger List in 2016 due to conflict, this work seeks to update the site's attributes and values for improved management.

This methodology, focusing on Ghadames, leverages recent heritage management advancements to monitor conflict-induced changes, aiming to enhance decision-making through a detailed analysis of the site's natural and cultural attributes.

Our findings highlight the need for systematic and holistic assessments of heritage site attributes and values, crucial for managing sites of both local and global significance. This approach is a key to understanding their identity, guiding interpretation, management and preserving cultural significance.

Developed for Ghadames, the methodology requires adaptation for other sites, underscoring the importance of identifying core tangible and intangible attributes that define a site's uniqueness.

Our developed methodology offers a replicable framework that can be modified by local heritage professionals to map attributes and assess the direct and indirect impact of conflict on heritage sites.

The detailed assessment provides a foundation for crafting informed policies and effective management strategies. It specifically targets minimizing the adverse effects of conflict on heritage sites' attributes. This effort is instrumental in preparing the necessary documentation to support the delisting of these sites from the UNESCO World Heritage Site In-Danger List, promoting their preservation and recovery.

This chapter discusses the development of tourism in peripheral areas, prompted by the “National Strategy for Inner Areas” developed by the Italian National Government. The strategy, backed by policymakers, business owners, local communities, and environmental nongovernmental organizations (NGOs), aims to stop demographic decline by boosting sustainable tourism practices. A case study of Valle D'aosta examines the problems and their solution in the implementation of the strategy. It discusses how to make strategy implementation less complex and whether sustainable tourism is possible in such areas – whether it is an oxymoron, or whether it is a utopia that is worth pursuing.

This study aims to examine how an educational intervention, using the lens of the LEADS framework, can influence the development of primary care doctors’ leadership skills in Aceh, Indonesia. In order to persevere in the face of inadequate resources and infrastructure, particularly in rural and remote settings of low- and middle‐income countries, physicians require strong leadership skills. However, there is a lack of information on leadership development in these settings.

This study applied an educational intervention consisting of a two-day workshop. The authors evaluated the impact of the workshop on participants’ knowledge and skill by combining quantitative pre- and post-intervention questionnaires (based on Levels 1 and 2 of Kirkpatrick’s model) with qualitative post-intervention in-depth interviews, using a phenomenological approach and thematic analysis.

The workshop yielded positive results, as evidenced by participants’ increased confidence to apply and use the information and skills acquired during the workshop. Critical success factors were as follows: participants were curiosity-driven; the use of multiple learning methodologies that attracted participants; and the use of authentic scenarios as a critical feature of the program.

The intervention may offer a preliminary model for improving physician leadership skills in rural and remote settings by incorporating multiple teaching approaches and considering local cultural norms.

This study aims to introduce the model of implementation to run the smart production factories. The study also aims to investigate the Industry 4.0 technologies as enablers to deal with challenges in the way of implementation.

This contribution benefits from two teams of experts to evaluate the challenges and technologies of Industry 4.0. The Hanlon method is applied to evaluate, rank and prioritise the challenges which are initially scored by experts’ Team 1. Then, the adjacency matrix among enablers and challenges is extracted through the opinions of experts’ Team 2. The study also uses fuzzy cognitive map (FCM) to evaluate the real weights of technologies and challenges, rank and prioritise subsequently.

A total of 8 challenging obstacles and 24 key technologies have been evaluated. The findings reveals that recruit and retention of experienced managers, undefined return on investment and recruit and retention of multi-skilled workers are the most serious challenges in the way of implementing smart production factories. Furthermore, big data, IT-based management and Internet of Things are the top-ranked key enablers to face the challenges.

To the best of the authors’ knowledge, this study is one of the pioneering studies that uses Hanlon method to evaluate industrial challenges. Integrating Hanlon method and FCM leads to a comprehensive model of evaluation and ranking which is another novelty of this contribution. Although many research studies have been released to implement the smart factories, practical model of implementation for production factories is identified as a literature gap.

This paper presents Quick Changeover Design (QCD), which is a structured methodological approach for Original Equipment Manufacturers to drive and support the design of machines in terms of rapid changeover capability.

To improve the performance in terms of set up time, QCD addresses machine design from a single-minute digit exchange of die (SMED). Although conceived to aid the design of completely new machines, QCD can be adapted to support for simple design upgrades on pre-existing machines. The QCD is structured in three consecutive steps, each supported by specific tools and analysis forms to facilitate and better structure the designers' activities.

QCD helps equipment manufacturers to understand the current and future needs of the manufacturers' customers to: (1) anticipate the requirements for new and different set-up process; (2) prioritize the possible technical solutions; (3) build machines and equipment that are easy and fast to set-up under variable contexts. When applied to a production system consisting of machines subject to frequent or time-consuming set-up processes, QCD enhances both responsiveness to external market demands and internal control of factory operations.

The QCD approach is a support system for the development of completely new machines and is also particularly effective in upgrading existing ones. QCD's practical application is demonstrated using a case study concerning a vertical spindle machine.

Despite the critical role of the policy environment in facilitating the advancement of building information modeling (BIM) as a systemic innovation to reshape traditional facility design, construction and operation processes, scant scholarly attention has been paid to systematically investigating how and why complex BIM policies are concretely and gradually implemented in different regional contexts from a dynamic policy diffusion perspective. This study aims to empirically investigate how different types of BIM policy instruments are dynamically implemented in heterogeneous regions over time and how the diffusion of BIM policies across different regions is comprehensively impacted by both internal efficiency needs and external legitimacy pressures.

This study employed a positivist research paradigm in which BIM policy data from 182 prefecture-level and above cities in China during 2011–2022 were analyzed with quantitative approaches for theory verification. Based on the content analysis of the evolutionary characteristics of the adopted BIM policy instruments in heterogeneous regions over time, the event history analysis (EHA) method was then used to further examine the mechanisms underlying the diffusion of BIM policies across different regions.

The content analysis results show that while environmental instruments (such as technological integration and goal planning) are the primary policy instruments currently adopted in China, recent years have also witnessed increasing adoptions of supply-side instruments (such as fiscal support and information support) and demand-side instruments (such as demonstration projects and tax incentives). After controlling for the impacts of regional fiscal and technical resources, the EHA results illustrate that BIM policy adoption positively relates to regional construction industry scale but negatively relates to regional industry productivity and that compared with public pressures from industry participants, vertical pressures from the central government and horizontal pressures from neighboring regions are more substantial drivers for policy adoption.

As an exploratory effort of using a dynamic policy diffusion perspective to systematically investigate how BIM policies are adopted in heterogeneous regional contexts to facilitate BIM advancement, this study not only characterizes the complexity and dynamics of BIM policies but also provides deepened understandings of the mechanisms underlying policy adoption in the conservative construction industry. The findings hold implications for how multifarious policy instruments can be more effectively and dynamically adopted to facilitate the advancement of BIM and related technologies as innovative solutions in the construction domain.

This paper aims to develop predictive methods, based on recurrent neural networks, useful to support facility managers in building maintenance tasks, by collecting information coming from a computerized maintenance management system (CMMS).

This study applies data-driven and text-mining approaches to a CMMS data set comprising more than 14,500 end-users’ requests for corrective maintenance actions, collected over 14 months. Unidirectional long short-term memory (LSTM) and bidirectional LSTM (Bi-LSTM) recurrent neural networks are trained to predict the priority of each maintenance request and the related technical staff assignment. The data set is also used to depict an overview of corrective maintenance needs and related performances and to verify the most relevant elements in the building and how the current facility management (FM) relates to the requests.

The study shows that LSTM and Bi-LSTM recurrent neural networks can properly recognize the words contained in the requests, thus correctly and automatically assigning the priority and predicting the technical staff to assign for each end-user’s maintenance request. The obtained global accuracy is very high, reaching 93.3% for priority identification and 96.7% for technical staff assignment. Results also show the main critical building elements for maintenance requests and the related intervention timings.

This work shows that LSTM and Bi-LSTM recurrent neural networks can automate the assignment process of end-users’ maintenance requests if trained with historical CMMS data. Results are promising; however, the trained LSTM and Bi-LSTM RNN can be applied only to different hospitals adopting similar categorization.

The data-driven and text-mining approaches can be integrated into the CMMS to support corrective maintenance management by facilities management contractors, i.e. to properly and timely identify the actions to be carried out and the technical staff to assign.

The improvement of the maintenance of the health-care system is a key component of improving health service delivery. This work shows how to reduce health-care service interruptions due to maintenance needs through machine learning methods.

This study develops original methods and tools easily integrable into IT workflow systems (i.e. CMMS) in the FM field.

Mental well-being is associated with positive outcomes throughout the life course. This study aims to examine interventions delivered by allied health professionals (AHPs) to alleviate community stressors adversely impacting public mental health and well-being.

Review inclusion criteria comprised experimental and qualitative process evaluations of public mental health interventions delivered by AHPs. Electronic searches in Cinahl, Embase, Medline, PsycINFO and the Cochrane Library, were combined with grey literature searches of National Institute for Health and Care Excellence public health guidance. A narrative synthesis and the Effective Public Health Practice Project appraisal tool were used to evaluate the evidence.

A total of 45-articles were included in the review describing AHP-delivered interventions addressing social disadvantage, trauma, bullying, loneliness, work-related stress, transitional stress, intersectionality, pain and bereavement. No articles were identified evaluating interventions delivered by operating department practitioners or orthoptists. A conceptual map was developed summarising the stressors, and a typology of public mental health interventions defined including: place-based interventions, discrete/one-off interventions, multi-component lifestyle and social connector interventions and interventions targeting groups at risk of mental health conditions.

Many mental health conditions begin in childhood, and a strength of the review is the life course perspective. A further strength is compiling a compendium of public mental health outcome measures used by AHPs to inform future research. The authors excluded many articles focussed on clinical interventions/populations, which did not meet review inclusion criteria. While playing a key role in delivering public mental health interventions, clinical psychologists are not defined as AHPs and were excluded from the review, and this may be construed a limitation. Given heterogeneity of study designs and interventions evaluated numerical analyses of pooled findings was not appropriate.

The review highlights the breadth of community stressors on which AHPs can intervene and contribute in public mental health contexts, stressors which correspond to those identified in UK Government guidance as currently important and relevant to address. The findings can inform developing community public mental health pathways that align with the UK National Health Service (NHS) Long Term Plan, on prevention and early intervention to protect community mental health and well-being. Further can inform the NHS strategic direction for AHPs including informing ways of increasing utilisation of core AHP skills to optimise contributions in public mental health agendas.

It is surprising there were not more AHP delivered evaluations of interventions for other stressors important to address in public mental health settings, for example gambling, domestic violence or that used digital technology, and these are areas for future research. Future research should identify the most active/effective dimensions of multi-component interventions which could be informed by frameworks to guide complex intervention development. The relative paucity of research identified, highlights the predominant focus of research to date on interventions for clinical mental health conditions and populations. The lack of preventative approaches is evident, and an important area for future research to align with UK health and social care priorities.

The review highlights AHP-delivered interventions impacting diverse community stressors across the life course. The findings can inform developing public mental health pathways aligned with government health service priorities to protect mental health and well-being, prioritise prevention and early intervention and increase utilisation of AHP skills across public mental health settings.

Agrifood value chains in developing countries are transforming into higher value markets which require sustainable practices, with smallholders playing a critical role. However, smallholders are a heterogeneous group which may have discrepancies in outcomes to meet sustainability standards. This paper aims to empirically investigate smallholders' heterogeneity towards sustainable value chain practice in developing countries.

Eight key enabling factors of sustainable value chain transformation were used to explore smallholders' typology, then profiled, based on their socio-economic status and current practices. A quantitative method was applied in Indonesia's cashew sector with 159 respondents from the primary producer area on Madura Island. A combination of descriptive analysis, cluster analysis, cross-tab analysis and one-way ANOVA analysis was used in this study.

Four types of groups were identified, each with distinct characteristics and arranged in priority order as follows: accelerator, progressor, inattentive and conservative groups. Interventions can be implemented on per clusters basis or based on potential similarities among clusters, depending on priority. It is noted that the pursuit of sustainable value chain practices by smallholders is not necessarily associated with high socio-economic status, as those with low socio-economic status may have a stronger inclination towards them.

The paper enhances awareness of practitioners and policymakers regarding smallholders' heterogeneity in sustainable value chain practice. It enables more effective and focused interventions to support smallholders who require assistance in sustainable production and value-adding activities. Different smallholders' characteristics call for different assistance/intervention. Practitioners can recognise smallholders' characteristics that are more compatible with higher value markets and sustainability requirements to better integrate their practices. Policymakers must carefully develop short-term and long-term interventions based on the activities prioritised by particular traits to “hit the right button” for smallholders' practice development.

This study investigates the typology of smallholders towards sustainable value chain practices by using eight enabling factors and profiling them based on their socio-economic condition and current practices. Additionally, this study shifts the focus of typology exploration away from the traditional lens of farm sustainability to a larger perspective which encompasses sustainable value chain activities.

Corporate social responsibility (CSR) was mandated and institutionalised in India through the Companies Act (2013), a decade ago. It is critical to understand the priorities of the models used by the companies to effectuate their CSR policy. This paper aims to understand the skewing of interest towards Education and Health interventions. The paper then proposes a framework to cross-level and effectuate CSR programme implementation.

The qualitative study conducted in-depth interviews of the stakeholders from the CSR environment. The findings are used to derive a model to effectuate CSR in India.

The findings may be divided into two sub-themes – (a) observations from the field study and (b) integrated solution ecosystem (ISE) framework. The qualitative study and the insights form the first component. The proposed framework which can enhance the efficiency of CSR practices may be found in the second sub-theme.

Operationalisation of the proposed model, if adopted would require integrated efforts from multiple functional departments which could lead to an extended timeframe for implementation. This may eventually lead to a need to revise the model in the making. The research could also include perspectives from governmental stakeholders which is missing here.

The emerging model can present an opportunity for corporates and policymakers to revisit the CSR structure and frameworks. It can also be used to evaluate and audit the CSR practices of companies.

The ISE posits a bunch of actionable themes which can deliver an impactful transition from the existing approach to CSR to a more far reaching one. While the ground rules are revisited, the approach also allows a critical departure from a corporate-driven model of engagement with the community. The modifications or corrections in this model would also mean a more inclusive layering of developmental interventions. The diversity which could potentially be brought in to designing interventions can be another key impact.

This paper presents insights for some of the pivotal stakeholders of CSR in countries like India. It presents a possible model of effective and optimal utilisation of CSR spending.