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This paper aims to develop a model that supports public organisations in making informed strategic decisions as to which public services are most suitable to be improved through co-creation. Thus, it first identifies the features that make public services (un)suitable for co-creation and then applies this knowledge to develop a multi-criteria decision support model for the assessment of their co-creation readiness.

The decision support model is the result of design science research. While its structure is determined by a qualitative multi-criteria decision analysis, its substance builds on a content analysis of Web of Science papers and over a dozen empirical case studies.

The model is comprised of 13 criteria clustered into two groups: service readiness criteria from the perspective of service users and service readiness criteria from the perspective of a public organisation.

The model attributes rely on a limited number of empirical cases and references from the literature review. The model was tested by only one public organisation on four of its services.

The paper shifts the research focus from organisational properties and capacity, as the key co-creation drivers and barriers, to features of public services as additional factors that affect the prospect of co-creation. Thus, it makes a pioneering step towards the conceptualisation of the idea of “service readiness for co-creation” and the development of a practical instrument that supports co-creation in the public sector.

This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.

Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

Decisions taken during the early design of adaptive façades involving kinetic, active and responsive envelope for complex commercial buildings have a substantial effect on inclusive building functioning and the comfort level of inhabitants. This study aims to present the application of an analytic network process (ANP) model indicating the order of priority for high performance criteria that must be taken into account in the assessment of the performance of adaptive façade systems for complex commercial buildings.

The nominal group technique (NGT) stimulating and refining group judgments are used to find and categorize relevant high performance attributes of the adaptive façade systems and their relative pair-wise significance scores. An ANP model is applied to prioritize these high performance objectives and criteria for the adaptive façade systems.

Embodied energy and CO₂ emission, sustainability, energy saving, daylight and operation maintenance were as the most likely and crucial high performance criteria. The criteria and the weights presented in this study could be used as guidelines for evaluating the performance of adaptive façade systems for commercial buildings in planning and design phases.

This research primarily provides the required actions and evaluations for design managers in accomplishing a high performance adaptive façade system, with the support of an ANP method. Before beginning the adaptive façade system of a building design process, the design manager must determine the significance of each of these attributes as high performance primacies will affect the results all through the entire design process.

In this research, a relatively innovative, systematic and practical approach is proposed to sustain the decision-making procedure for evaluation of the high performance criteria of adaptive façade systems in complex commercial buildings.

This paper aims to solve the facility location problem of mobility industry call centers comprehensively, considering both investment efficiency and long-term development efficiency.

In this paper, a two-phase decision-making approach within a multi-criteria decision-making (MCDM) framework has been proposed to help select optimal locations among various alternate locations. Both quantitative and qualitative information is collected and processed based on fuzzy set theory and fuzzy analytic hierarchy process. Then the fuzzy technique for order preference by similarity to an ideal solution method is incorporated in the framework to assess the overall feasibility of all alternates.

A real case of a mobility giant in China is applied to verify the effectiveness of the proposed framework. Sensitivity analysis also proves the robustness of the framework.

This two-phase MCDM framework allows the mobility industry call center location to be selected considering economic, human resource and sustainability elements comprehensively. The framework proposed in this paper might be applicable to other companies in the mobility industry when deciding optimal locations of call centers.

Most countries face important economic, social and environmental challenges and are strongly committed to invest in research and development (R&D) activities to help support the long-run economic sustainable growth. This paper aims to extend the previous research on macro-economic growth models and introduces endogenous variables to determine the amount of investments in R&D activities.

The model considers four different criteria and six economic sectors and aims at finding the optimal allocation of labor across different sectors. The model also endogenously determines the amount of investments in pollution abatement activities together with energy-related R&D efforts. The paper presents an application to the case of Kazakhstan, an emerging Asian country, that aims to become one of the top 30 most developed countries in the world by 2050.

The model shows the limits of the Kazakh agenda that identified too ambitious goals as the country has to go through a sociotechnical transition that involves a range of modifications in institutional structures, together with changes in user practices and the technological dimension. Kazakhstan should invest more in R&D activities able to develop sustainable energy sources to face the current electricity consumption demand and to reduce the greenhouse gas emission in the future.

The paper provides valuable knowledge for researchers and policy makers interested in the impact of R&D on the long-run economic sustainable growth.

The purpose of this work is to investigate industrial asset management (AM) in manufacturing. After depicting gaps for AM in this sector, the role of information as a key dimension is considered to realise a summary of challenges and advices for future development.

The work is grounded on an extensive systematic literature review. Considering the eligible documents, descriptive statistics are provided and a content analysis is performed, both based on a sector-independent normative-based framework of analysis.

AM principles, organisation and information are the dimensions defined to group ten areas of interest for AM in manufacturing. Information is the major concern for an effective AM implementation. Moreover, Internet of Things and big data management and analytics, as well as data modelling and ontology engineering, are the major technologies envisioned to advance the implementation of AM in manufacturing.

The identified challenges and advices for future development may serve to stimulate further research on AM in manufacturing, with special focus on information and data management. The sector-independent normative-based framework may also enable to analyse AM in different contexts of application, thus favouring cross-sectorial comparisons.

Industries with higher operational risk, like Oil&Gas and infrastructure, are advanced in AM, while others, like some in manufacturing, are laggard in this respect. This literature review is the first of a kind addressing AM in manufacturing and depicts the state-of-the-art to pave the way for future research and development.

Several healthcare quality assessment tools measure the processes and outcomes of the care system. The actual physical infrastructure (buildings and organizational) aspects are, however, rarely considered. The purpose of this paper is to describe the process of validation and weighting of an evidence-informed framework for the quality assessment of hospital facilities from social, environmental and organizational perspectives to complement other assessments.

Sustainable High-quality Healthcare version 2 (SustHealth v2) is the updated version of an existing framework composed of three domains (social, environmental and organizational quality). To validate and establish a relevant weighting, interviews were conducted with 15 professionals within the field of healthcare planning, design, research and management. The study has been conducted through semi-structured interviews and the application of the Simon Roy Figueras (SRF) procedure for the elicitation of weights criteria. The data collected have been processed through the DecSpace web platform.

Among the three domains, the organizational qualities appear to be the most important (W = 49%), followed by the environmental (W = 29%) and social aspects (W = 22%). Relevant indicators such as future-proofing, wayfinding and users’ space control emerged as the most important within each macro-area. Those results are confirmed by the outcome of the interviews that highlight user/patient-centeredness, wayfinding strategies and space functionality as the most important concepts to foster in existing healthcare facilities improvement.

The study highlights important structural and organizational aspects that hospital managers and planners can consider when dealing with healthcare facilities’ quality improvement.

The use of the SRF multicriteria method is novel in this context when used to weight an assessment tool with a focus on hospital built environment.