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Successful implementation of statistical process control techniques requires for operational definitions and precise measurements. Nevertheless, very often analysts can dispose of process data available only by linguistic terms, that would be a waste to neglect just because of their intrinsic vagueness. Thus a hybrid approach, which integrates fuzzy set theory and common statistical tools, sounds useful in order to improve effectiveness of statistical process control in such a case. In this work, a fuzzy approach is adopted to manage linguistic information, and the use of a Chi‐squared control chart is proposed to monitor process performance.

The aim of the study is to explore the genesis of entrepreneurial ecosystems (EE) and highlight the role played by intellectual capital (IC) in that process. Specifically, the paper adopts the collective intelligence approach, and the study shows how human capital (HC), structural capital (SC) and relational capital (RC) interact to create an entrepreneurial ecosystem.

The paper adopts a single case study of an Italian EE. The data analysis is based upon the collection of different sources of data: semi-structured interviews with representatives of each actor of the ecosystem; email correspondence; meetings report; a 24-months period of direct observation. Given the novelty of the topic, the qualitative method seems well suited for studying innovation-based EE since the method offers rich data about a phenomenon in real-life context.

The case is a top-down, innovation-based EE in which all main components of the IC play a crucial role from the initial stage. Findings show how the constant interchange between IC components occurs at two different levels: the micro and the meso level. HC and RC play major roles at both levels, whilst SC only occurs at a meso level, representing the environment in which the whole ecosystem takes place. Additionally, the use case, a new intangible asset integrating all three components of IC, emerged as one of the main outcomes of this innovation-based EE.

The paper contributes to a rather unexplored topic in the existing literature on EE and IC, namely the formation process of EE and the role played by IC within that process. Additionally, through the application of the collective intelligence approach, the authors shed light on the need to manage IC at both micro and meso level in the creation of an EE.

While the economic literature mostly tackled discrimination looking at labour costs, this work focuses on its relation to labour productivity, arguing that discrimination may worsen the performance of female employees. In this view, it represents a source of allocative inefficiency, which contributes to reducing output.

Female discrimination is both a social and an economic problem. In social terms, consolidated gender stereotypes impose constraints on women’s behaviour, worsening their overall well-being. In economic terms, women face generally worse labour market conditions. Using long-run Italian data spanning from 1861 to 2009, the authors propose a novel measure of female discrimination based on the observed frequency of discriminating epithets. Following social capital theory, the authors distinguish between structural and voluntary discrimination, and use Data Envelopment Analysis for time series data to assess the extent of inefficiency that each component of discrimination induces in the production process.

The results draw the trajectory of female discrimination in Italy and provide evidence in favour of the idea that female discrimination reduces productive efficiency. In particular, the structural component of female discrimination, although less sizeable than the voluntary component, plays a major role, especially in recent years, where more stringent beauty standards fuel looks-based discrimination.

The contribution of this work is twofold. First, based on contributions from social sciences different from economics, it proposes a novel theoretical framework that explores the effect of discriminatory language on labour productivity. Second, it introduces a novel and direct measure of female discrimination at the country level, based on the bidirectional link between language and culture. The indicator is easily understood by policymakers and may be used to evaluate the effectiveness of anti-discrimination policies.

The purpose of this paper is to describe the method of virtually and physically reconstructing the missing part of a badly damaged medieval skull by means of reverse engineering, computer‐aided design (CAD) and rapid prototyping (RP) techniques.

Laser scanning data were used to create the 3D model of the damaged skull. Starting from this digital model, a virtual reconstruction of the missing part of the skull, based on the ideal symmetry with respect to the mid‐sagittal plane, was achieved in a CAD environment. Finally, the custom‐designed model was directly fabricated by means of the RP process.

The result shows that the designed missing part of the skull fits very well with the existing skeletal remains. The final physical assembly of the prototyped element on the damaged skull was tested, restoring it to its whole original shape.

The entire process was time‐consuming and may be applied just to the most representative skeletal remains.

The method allows accurate fabrication of the missing part of the skull to be joined with the original skeletal remains. The advantage of using this technique is that the joining operation can be carried out without any need of supplementary connecting material, such as glue or plaster, to fix together the two parts.

The reversible and non‐invasive method improves the restoration process, reduces the risk of damage to the skeletal structure and allows reversion to the original repair as it was before.

Referring to the theory of organizational empowerment, the purpose of this study is to examine the relationship of organizational support and perceived environment on quality of care and job satisfaction, with organizational commitment as a mediator for the first variable.

This study employed a cross-sectional research design and data was collected from seven private and public sector hospitals in Pakistan, involving 352 nurses on a voluntary basis through a self-administered survey.

The results showed that organizational commitment mediates the relationship between organizational support and job satisfaction with the quality of care. Moreover, the perceived environment has an impact on job satisfaction and quality of care.

Healthcare service quality seems strictly dependent on the perceived quality of care and job satisfaction among healthcare workers. Theoretical and practical implications for policymakers and HR management are discussed.

Considering the ongoing international debate on the role of public administrations in economic systems, the interest around public service motivation (PSM) has significantly grown among practitioners and scholars in the past two decades. Following the research streams that have investigated topics of organizational behavior within the public context, the purpose of this paper is to examine the influence of PSM on public employees’ feelings of job satisfaction. The novelty of the study lies in linking some characteristics of the work context presumed to be more prevalent in public organizations with specific job characteristics, regarded as relevant antecedents of job satisfaction.

The study is based on two complementary studies conducted in an Italian public administration. The paper shows how PSM influences job satisfaction, job engagement, and life satisfaction.

This paper shows how PSM influences job satisfaction, job engagement, and life satisfaction. The findings display how job engagement affects both job and life satisfaction in such contexts. Additionally, the findings display how job engagement affects both job and life satisfaction in such contexts.

Although based on a specific context of public administration, the analysis allows some generalizations.

Based on these results, the paper contributes to two main streams of the literature. First, it enriches the existing research on PSM by analyzing how it can be managed in complex organizations. Second, it informs the literature on job satisfaction and work-related stress and relates to the intersection between organizational behavior and human resource management that informs the drawing up of HR policies. Furthermore, the paper sheds new light on how to deal with such problems and at the same time opens new avenues for investigations.

The design process of a bio-model involves multiple factors including data acquisition technique, material requirement, resolution of the printing technique, cost-effectiveness of the printing process and end-use requirements. This paper aims to compare and highlight the effects of these design factors on the printing outcome of bio-models.

Different data sources including engineering drawing, computed tomography (CT), and optical coherence tomography (OCT) were converted to a printable data format. Three different bio-models, namely, an ophthalmic model, a retina model and a distal tibia model, were printed using two different techniques, namely, PolyJet and fused deposition modelling. The process flow and 3D printed models were analysed.

The data acquisition and 3D printing process affect the overall printing resolution. The design process flows using different data sources were established and the bio-models were printed successfully.

Data acquisition techniques contained inherent noise data and resulted in inaccuracies during data conversion.

This work showed that the data acquisition and conversion technique had a significant effect on the quality of the bio-model blueprint and subsequently the printing outcome. In addition, important design factors of bio-models were highlighted such as material requirement and the cost-effectiveness of the printing technique. This paper provides a systematic discussion for future development of an engineering design process in three-dimensional (3D) printed bio-models.

This paper aims to examine the factors related to organizational attractiveness (OA), a concept originating in the strategy of employer branding. Previous research on OA has predominantly adopted the perspective of external applicants. In contrast, the present study takes the perspective of internal and current employees, extending further the scope of studies on OA.

Quantitative data were collected from a survey consisting of a sample of 164 nurses, all employees of public hospitals. Confirmatory factor analysis and structural equation modeling were used to analyze the data. Furthermore, the indirect effects were tested by mediator analysis.

Interdepartmental collaboration climate, management support and service quality of care were shown to have a positive effect on OA, with the three factors explaining 45% (R² = 0.45) of OA. The relationship between management support and OA was found to be mediated through the interdepartmental collaboration climate, and that between the interdepartmental collaboration climate and OA was found to be mediated through the service quality of care.

This study contributes to an understanding of OA from a current employee perspective. Specifically, it reveals how the three factors of interdepartmental collaboration climate, management support and service quality of care influence and shape the perception of current employees (nurses) toward the attractiveness of their organization.