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3D printing of composites has a high degree of design freedom, which allows for the manufacture of complex shapes that cannot be achieved with conventional manufacturing processes. This paper aims to assess the design variables that might affect the mechanical properties of 3D-printed fibre-reinforced composites.

Markforged Mark-Two printers were used to manufacture samples using nylon 6 and carbon fibres. The effect of fibre volume fraction, fibre layer location and fibre orientation has been studied using three-point flexural testing.

The flexural strength and stiffness of the 3D-printed composites increased with increasing the fibre volume fraction. The flexural properties were altered by the position of the fibre layers. The highest strength and stiffness were observed with the reinforcement evenly distributed about the neutral axis of the sample. Moreover, unidirectional fibres provided the best flexural performance compared to the other orientations. 3D printed composites also showed various failure modes under bending loads.

Despite multiple studies available on 3D-printed composites, there does not seem to be a clear understanding and consensus on how the location of the fibre layers can affect the mechanical properties and printing versatility. Therefore, this study covered this design parameter and evaluated different locations in terms of mechanical properties and printing characteristics. This is to draw final conclusions on how 3D printing may be used to manufacture cost-effective, high-quality parts with excellent mechanical performance.

Despite the boom corporate social responsibility (CSR) and sustainability are enjoying nowadays in the agendas of both small and big companies, we still have difficulties in providing a clear definition of the concept of sustainability. There is no consensus on the criteria to be used to define and enhance responsible management that creates sustainable development.

After a systematic revision of the literature, authors have been mapping the limits of the research already done at different levels, dimensions, and horizons, so we do have a 360° map of the research on sustainability. Future developments are also explored to enrich and align the diverse approaches demanded to define this wide, complex, and by now, equivocal concept and the conclusions reveal the many gaps not yet covered in the research field, signposting key issues for further work.

The purpose of this paper is to evaluate the effectiveness of two different academic office environments in supporting collaboration and privacy.

The approach takes the form of case studies involving post‐occupancy questionnaire surveys of academic occupants.

The combi‐office design was found to be associated with higher levels of occupant satisfaction than the open‐plan office design, with respect to support for collaboration and privacy.

The findings highlight the importance of understanding user requirements and the role of office space as a cognitive resource.

Designers should consider the default location of occupants when designing academic and other creative workspaces.

Academic creativity and innovation are seen to be important for society. However, there needs to be a better understanding of how to support this through workspace design.

This study contributes to the small but growing body of research on academic office design and creative workspaces in general.

Heterogeneity in choice models is typically assumed to have a normal distribution in both Bayesian and classical setups. In this paper, we propose a semiparametric Bayesian framework for the analysis of random coefficients discrete choice models that can be applied to both individual as well as aggregate data. Heterogeneity is modeled using a Dirichlet process, which varies with consumers’ characteristics through covariates. We develop a Markov Chain Monte Carlo algorithm for fitting such model, and illustrate the methodology using two different datasets: a household-level panel dataset of peanut butter purchases, and supermarket chain-level data for 31 ready-to-eat breakfast cereal brands.

Quantitative objective studies on the problem of celebrity selection are lacking. Furthermore, existing research does not recognize the group decision-making nature and the possibility of customer involvement in celebrity or influencer selection for social media marketing. This study conceptualizes celebrity selection as a multi-attribute group decision-making problem while deriving the final ranking of celebrities/influencers using interactive and flexible criteria based on the value tradeoff approach. The article thus proposes and demonstrates a quantitative objective method of celebrity selection for a brand or campaign in an interactive manner incorporating customer's preferences as well.

Each decision-maker's preferences for celebrity selection criteria are objectively captured and converted into an overall group preference using a modified generalized fuzzy evaluation method (MGFEM). The final ranking of celebrities is then derived from an interactive and criteria-based value tradeoff approach using the flexible and interactive tradeoff method.

The approach gives a different ranking of celebrities for two campaigns based on group members' perceived importance of the selection criteria in different scenarios. This group includes decision-makers (DMs) from the brand, marketing communication agency and brand's customers. Further, each group member has an almost equal say in the decision-making based on fuzzy evaluation and an interactive and flexible value tradeoff approach to celebrity selection for receiving a rank order.

The approach uses secondary data on celebrities and hypothetical scenarios. Comparison with other methods is difficult, as no other study proposes a multi-criteria group decision-making approach to celebrity selection especially in a social media context.

This approach can help DMs make more informed, objective and effective decisions on celebrity selection for their brands or campaigns. It recognizes that there are multiple stakeholders, including the end customers, each of whose views is objectively considered in the aspects of group decision-making through a fuzzy evaluation method. Further, this study provides a selection mechanism for a given context of endorsement by objectively and interactively encapsulating stakeholder preferences.

This robust and holistic approach to celebrity selection can help DMs objectively make consensual decisions with partial or complete information. This quantitative approach contributes to the literature on selection mechanisms of influencers, celebrities, social media opinion leaders etc. by providing a methodological aid that encompasses aspects of interactive group decision-making for a given context. Moreover, this method is useful to DMs and stakeholders in understanding and incorporating the effect of nature or context of the brand and the campaign type in the selection of a celebrity or an influencer.

To describe a new approach to the performance evaluation and benchmarking of analytical laboratory services and their associated supply chains.

Life cycle and industrial process approaches are adapted for consideration of the environmental performance of multidisciplinary laboratories as found in large multifunctional facilities. Models are developed to facilitate performance evaluation.

The laboratory product model (LPM) considers laboratory service delivery from a whole‐of‐life perspective. It defines an information product as a standard unit of production that facilitates performance evaluation of laboratories using both normalised and absolute values. Performance evaluation boundaries are extended beyond the internal laboratory processes to incorporate the supply chain, i.e. from sample collection to the end use of the information product.

Application of the research is limited by the availability of relevant corporate data. Future work could address routine collection of data appropriate to environmental performance evaluation so as to reduce the need for extensive life cycle inventories.

Focus is on a practical approach to improving the environmental performance of laboratory services through objective evaluation of laboratory and facility performance. The research provides a means of comparing laboratories founded in different disciplines, e.g. chemistry and microbiology.

Addresses laboratory supply chain issues by providing new tools for performance evaluation and benchmarking of laboratories. It uses new approaches to laboratory performance evaluation that help achieve sustainability.

The purpose of this paper is to dig out enablers of sustainable industrial ecosystem to develop a framework.

To test the framework statistically, a structured questionnaire was designed. Measures for the questionnaire were adopted from an extensive literature review. Further, the questionnaire was pretested and further pilot study was conducted. Adding to this, the reliability and validity of the constructs was examined using confirmatory factor analysis followed by covariance-based structural equation modeling to test research hypotheses.

The statistical analyses suggest that the model exceeds the threshold limit for goodness of fit after undergoing through few iterations. Normative pressure has a low effect than rest of the factors.

The present study is a unique contribution in terms of its theoretical implications and practical use. Finally, research findings are concluded and further research directions is outlined.