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This chapter discusses the empirical data analysis that will form the basis of the early pricing framework. It focusses on the complexity of furniture production and describes the historical production data collected from companies, along with the potential applications of machine learning for knowledge management purposes. The chapter then presents the results of machine learning for early cost estimation as part of a lean innovation that is affordable and accessible for small and medium-sized enterprises (SMEs). Finally, the chapter describes an experiment on the structured expert evaluation methodology, which shows that a well-formed panel of experts can increase the predictive power of machine learning solutions, particularly at extreme points.

The aim of this paper is to analyse the relationship of crime on housing prices during the economic recovery of the housing sector in Spain (2014–2019).

For this purpose, it is used a regional panel data in first differences for the period 2014–2019 in order to control the endogeneity and multicollinearity that these models usually present in the empirical literature.

The results show that it takes between one and two years for housing prices in Spain to respond negatively to an increase in crime. Of the eight types of crime analysed, only four of them establish statistically significant relationships with housing prices, while robbery with violence (−2.2%) and burglary with forced entry (−0.5%) have the greatest negative impact on housing prices. Lastly, the results highlight the fact that the category “other crimes against property” – which includes squatting – is the only crime typology that has an immediate effect on housing prices (−1.7%).

These results demonstrate that the more serious property crimes have a greater quantitative negative impact on housing prices. These crimes combine both a violent nature and the fact that they affect property, thus generally causing greater harm to individuals’ emotional well-being and perception of criminality. These findings have direct implications for crime prevention strategies, as the housing market in Spain appears to be more affected by this type of criminal activity. Consequently, public institutions should focus their efforts on mitigating these crimes.

This is the first study that examines the role of crime in the recovery of the real estate sector in Spain following the economic crisis of 2008. It is also one of the pioneering works for the European context, utilizing a panel data approach with first differences and incorporating various types of criminal activities within the same model.

The chapter is designed to discuss the preconditions for the competitiveness of the furniture industry, global networks and regional perspectives, as well as the competitive advantages of different regions such as the USA, Europe and the East. The challenges created by customisation and the needs of consumers for individual products are also discussed. As consumers become more and more focussed on furniture designed exclusively for them, the furniture business has to reorient its production and has to deal with a number of management issues. It is necessary to reconsider not only how to involve consumers but also how to keep prices competitive because even for an individual order, the customer is less and less willing to pay more. The issue of new product development is also discussed. It delves into the management of furniture companies, the characteristic organisational structures, and management models that could ensure the sustainability of the business. Particular attention is paid to the digital issues of furniture manufacturing and enterprise resource planning (ERP) in particular. An examination of how the furniture sector evaluates prices and costs, which are the most popular methods and which can be used for forecasting, looks at the most important global trends. Such cost estimation methods as cost-based, competition-based, analogous-based, and expert-based are discussed, highlighting the limits of their applications. Then discusses current trends and the current IT supply, which unfortunately does not fully meet the needs of customised furniture production, and digitisation within a small company becomes more difficult. So, companies have to recognise the limits of digitisation.

The study was conducted to understand how the moral identity of employees mediates the relationship between servant leadership and the moral disengagement of employees. Additionally, the study explores whether servant leadership's ability to build the moral identity of employees is contingent upon employees' perception of organizational politics.

The data were collected from 500 service sector-employed knowledge workers. Data analysis was done through structural equation modeling.

The study found servant leadership to be related to the moral identity of employees. Additionally, moral identity and moral disengagement were found to be negatively related. Moral identity was found to mediate the relationship between servant leadership and moral disengagement. Finally, the study found that the relationship between servant leadership and employees' moral identity was contingent upon their perception of organizational politics.

The study explored the previously unexplored mediating role of moral identity linking servant leadership to the moral disengagement of employees. The study also explained how the relationship between servant leadership and the moral identity of employees was contingent upon employees' perception of organizational politics.

This study investigates the relationship between telework frequency and knowledge management (KM) activity in Japan and the USA. By examining how telework impacts KM activity differently across these two countries, this study aims to provide insights into the design and implementation of effective telework policies tailored to specific cultural contexts.

Linear and quadratic regression analyses were conducted to explore the relationship between telework frequency and KM activity. Data was collected from samples in Japan and the USA, with respondents categorized based on prior telework experience. Various KM activities such as knowledge acquisition, sharing and application were measured using established scales.

In Japan, an inverted U-shaped relationship between telework frequency and KM activity was observed, with optimal activity occurring at four days of telework per week. Conversely, the USA demonstrated a linear relationship, indicating sustained KM activity across different telework frequencies. Notably, individuals with prior telework experience showed higher levels of KM activity compared to those without experience.

This study contributes to the understanding of how cultural differences influence the relationship between telework and KM activity, and ultimately learning. By highlighting the nuanced patterns observed in Japan and the USA, it emphasizes the importance of tailored telework policies and support mechanisms for effective KM in diverse cultural contexts. Future research could further explore additional explanatory variables and their impact on telework-related outcomes.

Small-scale farmers are highly heterogeneous with regard to their types of farming, levels of technology adoption, degree of commercialization and many other factors. Such heterogeneous types, respectively groups of small-scale farming systems require different forms of government interventions. This paper applies a machine learning approach to analyze the typologies of small-scale farmers in South Africa based on a wide range of objective variables regarding their personal, farm and context characteristics, which support an effective, target-group-specific design and communication of policies.

A cluster analysis is performed based on a comprehensive quantitative and qualitative survey among 212 small-scale farmers, which was conducted in 2019 in the Limpopo Province of South Africa. An unsupervised machine learning approach, namely Partitioning Around Medoids (PAM), is applied to the survey data. Subsequently, the farmers' risk perceptions between the different clusters are analyzed and compared.

According to the results of the cluster analysis, the small-scale farmers of the investigated sample can be grouped into four types: subsistence-oriented farmers, semi-subsistence livestock-oriented farmers, semi-subsistence crop-oriented farmers and market-oriented farmers. The subsequently analyzed risk perceptions and attitudes differ considerably between these types.

This is the first typologisation of small-scale farmers based on a comprehensive collection of quantitative and qualitative variables, which can all be considered in the analysis through the application of an unsupervised machine learning approach, namely PAM. Such typologisation is a pre-requisite for the design of more target-group-specific and suitable policy interventions.

The purpose of this paper is to explore the dynamic relationship between formal and non-formal processes of accountability in a public services context.

The paper presents a case study of the impact of the Health and Social Care Act (2012) on the practices of Health and Wellbeing Board (HWB) members. It draws upon multiple data sources, including in-depth interviews with the members, comprehensive archival data published by the HWB (2011–2019), and observations of HWB public meetings. We utilise the concept of dynamic duality (Li, 2008) to further theorise the relationship between formal and non-formal processes of accountability and how they mutually transform one another.

The case illustrates the role of formal and non-formal processes of accountability at a HWB in England. Moreover, the case study reveals the relationship and interaction between the formal and non-formal accountability processes and how they change and transform each other over time. We find that whilst non-formal accountability processes were strengthened by a historical legacy of partnership working, over time the dynamics at play led to the development of formal accountability processes through more sophisticated performance systems, which in turn transformed non-formal accountability processes.

The paper presents a more holistic conceptualisation than articulated in prior accountability literature, dynamic duality, on the relationship between formal and non-formal accountability processes. Through application of this conceptualisation to a HWB in England, the paper spotlights the inter-relationship between formal and non-formal processes of accountability, and how they have the potential to transform each over an extended time-period.

The purpose of this paper is to present research on the flight demonstration of avionics technology for CS-23 commuter category aircraft. The Integrated Mission Management System (IMMS) is designed to reduce pilot workload by aggregating hazard information from multiple domains (airspace, traffic, weather and terrain) and automatically prefiltering this data to display only hazards relevant to the flight plan, from origin to destination. This paper details the design of the IMMS, along with the process of the integration on aircraft and flight demonstration results.

The IMMS integrates several technologies, including the Advanced Weather Awareness System, Tactical Separation System, Compact Computing Platform and Flight Reconfiguration System. Hazards are consolidated in a Unified Hazard Database (UHD) and assigned severity levels, providing automated hazard filtering and path planning.

Simulations and flight tests demonstrated that the IMMS effectively reduces the information displayed to pilots in real-time without loss of critical safety data. Feedbacks from test pilots on IMMS usage, as well as suggestions for improving the multi-source Graphical User Interface, are also discussed.

Limitations of the UHD were identified, offering insights into potential expansions to support more efficient automatic flight planning. The technology was validated through extensive laboratory testing and real-world flight trials, achieving Technology Readiness Level 5. This validation demonstrated how the severity of hazards can be linked to their transparency level on the display, with the aim of reducing information overload.

The IMMS shows potential to be ground-breaking system in the CS-23 aircraft category, autonomously supporting route planning and flight execution while adapting to in-flight weather changes and ensuring tactical separation from other aircraft. It also shows that multi-domain hazard information can be processed on limited on-board avionics systems.

This study highlights the importance of Hardware-In-The-Loop testing in verifying new technologies and mitigating risks related to software reliability, flight demonstrations and system integration.