Abstract
This paper explores robust unconditional and conditional nonparametric approaches to support performance evaluation in problematic samples. Real-world assessments often face critical problems regarding available data, as samples may be relatively small, with high variability in the magnitude of the observed indicators and contextual conditions. This paper explores the possibility of mitigating the impact of potential outlier observations and variability in small samples using a robust nonparametric approach. This approach has the advantage of avoiding unnecessary loss of relevant information, retaining all the decision-making units of the original sample. We devote particular attention to identifying peers and targets in the robust nonparametric approach to guide improvements for underperforming units. The results are compared with a traditional deterministic approach to highlight the proposed method's benefits for problematic samples. This framework's applicability in internal benchmarking studies is illustrated with a case study within the wastewater treatment industry in Portugal.

Abstract

Abstract
Technological evolution has continuously driven the development of industries and consequently of society. The fourth industrial revolution consists in the combination of a set of physical and digital technologies that has been changing systems' operations within industries. The pharmaceutical industry has a considerable impact on well-being and has been strongly challenged with this new reality, not only by those that are transversal to all industries but also due to the fact that it is a highly regulated sector, which creates additional barriers for industry 4.0 (I4.0) initiative's implementation. However, it is due to the fact that this revolution provides high growth opportunities to the industry, and consequently for the improvement of population's quality of life, that this topic has been subject to so much research at a global level. This study's main purpose is to understand the impact of I4.0 paradigm implementation in the pharmaceutical industry (mainly in the production area), to analyze the technological readiness of Portuguese pharmaceutical companies to implement I4.0 technologies and to understand the role of the I4.0 paradigm to fight the pandemic situation caused by the COVID-19. To achieve this purpose, an exploratory multiple-case study based on semi-structured interviews was conducted in two Portuguese pharmaceutical companies. It is expected that the results of this work lead to recommendations that help the Portuguese pharmaceutical industry to be better prepared to face the challenges that are coming with this revolution.

Abstract

Abstract
Finding the right strategy enabled by a solid digital transformation is a key challenge that Small and Medium Enterprises (SMEs) face. With a high number of transformations that fail, there is a significant investment in research to identify critical factors that ultimately drive a more successful journey, and at the same time, quite a few different models to assess the digital transformation maturity. There is, however, a gap in assessing how ready a SME is to successfully embrace the transformation and an even more significant gap in assessing it from an employee's perspective. This work proposes a model to assess that readiness. The organizational readiness assessment aims to enable SMEs to better understand the foundations that need to be set to successfully deliver the transformation. From the employee's perspective, a user-friendly model assesses the non-technological aspects of an organization, indicating the clear gaps that ultimately might negatively impact the organization's future when digitally transforming. © 2022 Elsevier B.V.. All rights reserved.

Abstract
Recent studies have highlighted the potential of supply chain visibility (SCV) to improve companies' performance, support the decision-making process and increase the resilience and sustainability of supply chains (SC). However, the definition and the approaches to manage visibility are not consensual, especially when it comes to its assessment. This paper studies the influence that some characteristics of the information shared among SC partners have on SCV and provides a model that allows to assess the level of visibility. Focus group research was used to discuss the visibility assessment model with academic and practical experts and case studies were conducted to evaluate the implementation of the model in real contexts. The results support the applicability of the model in complex SCs and show that the visibility indices proposed can help managers to identify the SC partners where improvement actions are needed. This study contributes to literature and practice by means of a model to assess the visibility throughout the SC by considering different types and characteristics of the information shared.