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The present study aims to bring out the impact of consanguinity on spontaneous pregnancy loss (SPL) and on descendants’ health, among the population of north Morocco.

Convenience sampling was used for collecting data. A questionnaire was randomly administered to 385 couples represented by either the husband, the wife or both. The study lasted for three months, from January to March 2015.

In total, 238 valid questionnaires were analysed. The results showed that the consanguinity rate was 45.23% and that most consanguineous unions were between first cousins (91%). Data analysis revealed that SPL risk was similar in consanguineous and non-consanguineous couples (OR = 1.6; IC95% = 0.9–2.9). Also, no significant difference was observed in terms of SPL type (OR = 1.6; IC95% = 0.7–3.9) and frequency (p = 0.81). However, late SPL frequency was significantly lower in consanguineous couples (p < 0.001), whereas no significant difference was registered in terms of early SPL frequency (p = 0.73). On the other hand, consanguineous couples displayed a significantly higher risk of descendants’ health disorders in comparison with non-consanguineous ones. Moreover, the consanguineous couples had a significantly higher number of children with health disorders (p < 0.001). The risk analysis also showed that consanguineous couples displayed a significantly higher risk of congenital malformations (OR = 7.23; IC95% = 3.52–14.84) and multifactorial diseases (OR = 3.72; IC95% = 1.46–9.49), but no significant difference was observed in terms of behavioural disorders risk.

The population awareness regarding the negative effects of consanguinity should be raised through education programmes and premarital, prenatal and genetic counselling services.

Goal 4.7 of the Sustainable Development Goals (SDGs) explicitly frames education as an enabler of change and a means to achieve all SDGs. This study aims to explore the nature and culture of science as an academic discipline and its capacity for the integration of education for sustainable development (ESD).

Drawing upon interviews with academics working in a Life Sciences Department (n = 11), focus groups with students (n = 21) and observations from lectures, laboratory sessions and field trips, the study advances a number of recommendations for the integration of ESD in Science Education programs.

Findings point to the nature and structure of scientific knowledge and the culture of science as articulated by study participants. The study provides a number of recommendations for the integration of ESD in Science Education programs including a greater emphasis on inquiry-based learning, enhancing ESD themes in science-related modules to teach for sustainability and adopting a department wide strategy that promotes ESD.

This study argues that ESD practitioners need to be cognizant of the nature and culture of the discipline area – as a particular discipline propagates a specific culture – encapsulating ways of being, thinking, acting and communicating, which can have implications for the integration of ESD.

The emergence of distributed manufacturing (DM) is examined as a new form of localised production, distinct from previous manifestations of multi-domestic and indigenous production.

Supply network (SN) configuration and infrastructural provisioning perspectives were used to examine the literature on established localised production models as well as DM. A multiple case study was then undertaken to describe and explore the DM model further. A maximum variation sampling procedure was used to select five exemplar cases.

Three main contributions emerge from this study. First, the research uniquely brings together two bodies of literature, namely SN configuration and infrastructure provisioning to explore the DM context. Second, the research applies these theoretical lenses to establish the distinctive nature of DM across seven dimensions of analysis. Third, emerging DM design rules are identified and compared with the more established models of localised production, drawing on both literature and DM case evidence.

This study provides a rich SN configuration and infrastructural provisioning view on DM leading to a set of design rules for DM adoption, thus supporting practitioners in their efforts to develop viable DM implementation plans.

The authors contribute to the intra- and inter-organisational requirements for the emerging DM context by providing new perspectives through the combined lenses of SN configuration and infrastructural provisioning approaches.

Variation, replication and selection processes are acknowledged as key constructs in studies on how industries evolve, but no theoretical and empirical contributions have applied these key constructs to analyzing industries in specific stages of their history. This paper aims to fill this gap, taking for reference the firm and its strategic action in particular.

After delineating and discussing the three processes of interest – variation, replication and selection – this paper analyzes three very different evolutionary contexts: “red” industries, that reached maturity maintaining a polypolistic structure, and that continue to evolve in this phase; the oligopolistic transformation undergone by certain industries; and the emergence of new market spaces around new products developed by firms.

Variations are mainly reactions to the competitive environment in the evolution of red industries or environment-modifying in the case of industries evolving toward an oligopoly, and in the creation of new market spaces. Horizontal replication through employee mobility prevails in red industries, while in the other two contexts firms driving the evolution raise barriers to replication, inhibiting both horizontal and vertical replication. While selection does not come about in a new market space as long as the barriers erected by the first comer remain in place, it occurs in the form of subset selection in the other two settings.

This paper takes an entirely novel approach and proposes a pluralist framing of how industries evolve, interpreting the different evolutionary situations on the strength of the key variables of variation, replication and selection.

The proliferation of (big) data provides numerous opportunities for service advances in practice, yet research on using data to advance service is at a nascent stage in the literature. Many studies have discussed phenomenological benefits of data to service. However, limited research describes managerial issues behind such benefits, although a holistic understanding of the issues is essential in using data to advance service in practice and provides a basis for future research. The purpose of this paper is to address this research gap.

“Using data to advance service” is about change in organizations. Thus, this study uses action research methods of creating real change in organizations together with practitioners, thereby adding to scientific knowledge about practice. The authors participated in five service design projects with industry and government that used different data sets to design new services.

Drawing on lessons learned from the five projects, this study empirically identifies 11 managerial issues that should be considered in data-use for advancing service. In addition, by integrating the issues and relevant literature, this study offers theoretical implications for future research.

“Using data to advance service” is a research topic that emerged originally from practice. Action research or case studies on this topic are valuable in understanding practice and in identifying research priorities by discovering the gap between theory and practice. This study used action research over many years to observe real-world challenges and to make academic research relevant to the challenges. The authors believe that the empirical findings will help improve service practices of data-use and stimulate future research.

Mapping and Geographic Information Systems (GIS) are widely used in disaster research and practice. While, in some cases, these practices incorporate methods inspired by critical cartography and critical GIS, they rarely engage with the theoretical discussions that animate those fields.

In this commentary, the author considers three such discussions, and draws out their relevance for disaster studies: the turn towards processual cartographies, political economy analysis of datafication and calls for theorising computing of and from the South.

The review highlights how these discussions can contribute to the work of scholars engaged in mapping for disaster risk management and research. First, it can counter the taken-for-granted nature of disaster-related maps, and encourage debate about how such maps are produced, used and circulated. Second, it can foster a reflexive attitude towards the urge to quantify and map disasters. Third, it can help to rethink the role of digital technologies with respect to ongoing conversations on the need to decolonise disaster studies.

The paper aims to familiarise disaster studies scholars with literature that has received relatively little attention in this field and, by doing so, contribute to a repoliticisation of disaster-related maps.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.