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To elaborate the nature of fact-checking in the domain of political information by examining how fact-checkers assess the validity of claims concerning the Russo-Ukrainian conflict and how they support their assessments by drawing on evidence acquired from diverse sources of information.

Descriptive quantitative and qualitative content analysis of 128 reports written by the fact-checkers of Snopes – an established fact-checking organisation – during the period of 24 February 2022 – 28 June, 2023. For the analysis, nine evaluation grounds were identified, most of them inductively from the empirical material. It was examined how the fact-checkers employed such grounds while assessing the validity of claims and how the assessments were bolstered by evidence acquired from information sources such as newspapers.

Of the 128 reports, the share of assessments indicative of the invalidity of the claims was 54.7%, while the share of positive ratings was 26.7%. The share of mixed assessments was 15.6%. In the fact-checking, two evaluation grounds, that is, the correctness of information and verifiability of an event presented in a claim formed the basis for the assessment. Depending on the topic of the claim, grounds such as temporal and spatial compatibility, as well as comparison by similarity and difference occupied a central role. Most popular sources of information offering evidence for the assessments include statements of government representatives, videos and photographs shared in social media, newspapers and television programmes.

As the study concentrated on fact-checking dealing with political information about a specific issue, the findings cannot be extended to concern the fact-checking practices in other contexts.

The study is among the first to characterise how fact-checkers employ evaluation grounds of diverse kind while assessing the validity of political information.

The purpose of this study is to demonstrate that Strategic Enterprise Management (SEM) and Business Intelligence (BI) have the potential to integrate management decisions vertically through an organization’s hierarchy. This study also aims to present a design theory framework and build a model dimension using eight principles serving as mid-range theories.

This study uses a design science perspective to posit how organizations can successfully implement SEMBI (a union of SEM and BI). This study then completes the design theory by building the method dimension using two principles. Finally, the study presents testable hypotheses for the theory and an evaluation using stakeholder attitudes and judgments as proxies for objective measures.

In the search for a prescription for SEMBI success, this study finds that the notion of the Capability Maturity Model (CMM) is a good artifact with which to organize the principles the authors are seeking. CMM has since been adapted to suit different contexts by incorporating relevant principles from those domains. Hereafter, this study refers to SEMBI–CMM as the adapted solution for SEMBI's success.

This study coins and uses the term SEMBI to represent the union of SEM and BI. This term retains its distinct identities and principles and forms a holistic and integrated view of SEM and BI implementation strategies. In an effort to advance this line of research, this study employs a design science perspective to address the question of how an organization can successfully implement SEMBI.

This paper proposes a method for managing client requirements with the use of Building Information Modelling (BIM). The development of healthcare projects demands a large amount of requirements information, in order to deal with a diversity of clients and frequents changes in healthcare services. The proposed method supports healthcare design by adopting a process-based approach for client requirements management, with the aim of improving value generation.

Design Science Research was the methodological approach adopted in this investigation. The main outcome of this study emerged from an empirical study carried out in a healthcare project in Brazil.

The proposed method involves three stages: (1) capturing and processing requirements; (2) product and requirements modelling, which involves the connection between requirements and the BIM 3-D model and (3) supporting design solution refinement, through the communication of requirements and the assessment of design in relation to updated client requirements information.

This study explores client requirements management from a process perspective, proposing activities and their interdependences and possible sources of data, including healthcare services information. The main theoretical contributions are related to the understanding of the nature and complexity of the information involved in client requirements management, and how this can be modelled.

The purpose of this paper is to analyze the evidence-based research strategy (EBRS) used to evaluate eight projects that applied the neighborhood approach for disaster risk reduction (NA-DRR) in informal urban settlements in Colombia, Guatemala, Haiti, Honduras, Jamaica and Peru, between 2012 and 2017.

The study covers the first five of the seven EBRS stages: first, identify relevant interventions; second, prepare evaluation questions; third, select evidence sources and implement a search strategy; fourth, appraise evidences and identify gaps; fifth, create an evaluation design to include an extensive literature review, followed by a mixed research method with surveys, focus groups and interviews; disaster risk modeling; georeferencing analysis; and engineering inspections. The last two stages: sixth, apply the evidence, and seventh, evaluate the evidence application, will be addressed in a near future.

Even though the reference to “evidence” is frequent in the DRR field, it is largely based on descriptive processes, anecdotal references, best practices, lessons learned and case studies, and particularly deficient on the subject of informal and precariousness settlements. The evaluation allowed a deep and broad analysis of NA-DRR in urban informal settlements, comparing it with other DRR strategies implemented by different stakeholders in fragile urban settings, assessing the effectiveness and sustainability of the various DRR interventions.

The abundant data, information and knowledge generated will serve as foundation for forthcoming thematic peer-reviewed publications informing evidence-based DRR research, policy and practice, with emphasis on informal and precariousness settlements in particular.

The purpose of this paper is three-fold. Firstly, through selected case studies, to provide an overview of how non-traditional data from digital public services were used as a source of knowledge for policymaking. Secondly, to argue for a design for policy approach to support the successful integration of non-traditional data into policymaking practice, thus supporting data-driven innovation for policymaking. Thirdly, to encourage a vision of the relation between data-driven innovation and public policy that considers policymaking outside the authoritative instrumental logic perspective.

A qualitative small-N case study analysis based on desk research data was developed to provide an overview of how data-centric public services could become a source of knowledge for policymaking. The analysis was based on an original theoretical-conceptual framework that merges the policy cycle model and the policy capacity framework.

This paper identifies three potential areas of contribution of a design for policy approach in a scenario of data-driven innovation for policymaking practice: the development of sensemaking and prefiguring activities to shape a shared rationale behind intra-/inter-organisational data sharing and data collaboratives; the realisation of collaborative experimentations for enhancing the systemic policy analytical capacity of a governing body, e.g. by integrating non-traditional data into new and trusted indicators for policy evaluation; and service design as approach for data-centric public services that connects policy decisions to the socio-technical context in which data are collected.

The small-N sample (four cases) selected is not representative of a broader population but isolates exemplary initiatives. Moreover, the analysis was based on secondary sources, limiting the assessment quality of the real use of non-traditional data for policymaking. This level of empirical understanding is considered sufficient for an explorative analysis that supports the original perspective proposed here. Future research will need to collect primary data about the potential and dynamics of how data from data-centric public services can inform policymaking and substantiate the proposed areas of a design for policy contribution with practical experimentations and cases.

This paper proposes a convergence, yet largely underexplored, between the two emerging perspectives on innovation in policymaking: data for policy and design for policy. This convergence helps to address the designing of data-driven innovations for policymaking, while considering pragmatic indications of socially acceptable practices in this space for practitioners.

The aim of this paper is to explore whether open innovation is emerging in the Italian fashion industry.

Based on available studies on innovation and open innovation, we first identified the main facets of open innovation within the industry investigated, such as the process of searching for new ideas, the involvement of external partners in the new product development process and the use of collaboration mechanisms between supply chain partners. Starting from these findings, the authors designed a semi-structured questionnaire that was used as a guideline for 15 case studies, carried out in the Italian fashion industry.

The outcomes from the case studies allow drawing some conclusions about the emergency of open innovation in the fashion industry and the related patterns.

Given its exploratory nature, this study is expected to start a debate about open innovation in the fashion industry, as well as to encourage future studies in this field.

This study aims to understand the extent to which a faculty development program that includes a week-long course design experience followed by sustained support changes new faculty's perceptions, beliefs and teaching practices. The authors employed the teacher professional knowledge and skill (TPK&S) framework and characteristics of effective educational development interventions to drive the program development, implementation and assessment.

This study utilized a mixed methods approach. Data sources include pre-/mid-/post-program responses to a validated survey, pre-/post-program course syllabi analyzed using a validated rubric and pre-/post-classroom observations collected using the Classroom Observation Protocol for Undergraduate STEM (COPUS) instrument.

Findings indicate transformative effects for participants' beliefs about their teaching and changes to their instructional practices. Significant and practical effects were observed across different portions of the program for increases in participants' self-efficacy, endorsement of a conceptual change approach toward teaching and perceptions of institutional support. Participants produced more learning-focused syllabi and many moved toward more student-centered instructional approaches in their teaching practices.

Due to the voluntary nature of the new faculty development program, this study may have been limited by participant self-selection bias and differential sample sizes for the study's individual measures. Future research should consider designs which maximize faculty participation in measurement across all data sources.

This study addresses shortcomings in prior studies which utilized limited data sources to measure intervention impact and answers the call for more rigorous research to obtain a more complete picture of instructional development in higher education.

There is growing interest around the world in more effectively linking public payments to the provision of public goods from agriculture. However, published evidence syntheses suggest mixed, weak or uncertain evidence for many agri-environment scheme options. To inform any future “public money for public goods” based policy, further synthesis work is needed to assess the evidence-base for the full range of interventions currently funded under agri-environment schemes. Further empirical research and trials should then focus on interventions for which there is mixed or limited evidence. Furthermore, to ensure the data collected is comparable and can be synthesised effectively, it is necessary to reach agreement on essential variables and methods that can be prioritised by those conducting research and monitoring. Future policy could then prioritise public money for the public goods that can most reliably be delivered, offering better value for taxpayers and improving the provision of ecosystem services from agricultural landscapes.

This paper aims to examine a two-way interaction between social influencers’ number of followers (micro vs meso) and argument quality (weak vs strong) on consumers’ self-reported and brain responses to advertising posts on Instagram. Further, drawing upon source credibility theory and contemporary theories of persuasion, the Instagram users’ perceptions of the influencer’s credibility are predicted to mediate the hypothesized effects.

Through an online (N = 192) and a lab study (N = 112), the authors examined Instagram users’ responses to an advertising post from Instagram influencers in terms of perceived source credibility and electronic word-of-mouth intention, using validated multi-item scales from existing literatures and electroencephalogram (EEG) measures. The hypotheses were tested with a 2 (type of influencer: micro vs meso) × 2 (argument quality: weak vs strong) between-subject design using mediated moderated linear regression analysis.

The results highlight that meso-influencers are perceived as a credible source of information only when their product-related post provides strong argument quality. Moreover, this process involves an increase in users’ cognitive work (measured with EEG), with possible implications on marketing communication strategies and online message design.

The limitations of the work can serve as ideas for future research. First, this study did not account for the influencer’s relevance and resonance. Second, the authors studied consumer responses to online communication produced by Instagram influencers within a single product category. Another important product type distinction that requires further attention is between hedonic and utilitarian products. Finally, the two studies only used positive review content. Further research should study how consumers evaluate the source credibility of a micro- vs meso-influencer when they are exposed to negative reviews containing weak vs strong arguments.

The results suggest that marketers should carefully consider Instagram influencers based on the trade-offs between credibility and reach. Specifically, micro-influencers are perceived as more credible sources of information than meso-influencers, which means that they have greater potential to affect Instagram users’ behavior. Moreover, the results suggest that meso-influencers should leverage argument quality to enhance their credibility and draw greater positive outcomes for the products and brands they endorse.

To the best of the authors’ knowledge, this study is the first to investigate how the interaction between the type of social media influencer and the argument quality affects consumers’ self-reported and brain responses to advertising posts on Instagram. Moreover, using neuroscience, this study aims to shed light on the neurophysiological processes that drive consumer responses to product-related communication posted by different influencer types.

The theory of complex adaptive systems (CASs) represents an interesting perspective to study the characteristics of circular supply chains (CSCs). In this regard, the current literature lacks evidence regarding coordination and integration mechanisms, characteristics of the environment and emerging system properties of CSCs. This paper aims to fill this gap and focuses on how and why companies design (i.e. configure and coordinate) their CSCs and what value these design choices help to create across different industries.

The authors use a multiple case study approach and analyze data collected from a sample of five sustainable start-ups operating in the fashion and construction industries in Italy to better understand how these companies design (i.e. configure and coordinate) their CSCs.

Results reveal that in the two industries under investigation, the design of CSCs built around open and closed–loop logic is triggered by the intention to solve a negative sustainability impact. The sustainability impact determines whether the value is restored within the same supply chain, in another, or inside or outside the same industry. Interestingly, start-ups appear to coordinate other CSC actors with three leading roles: (1) orchestrator, (2) integrated orchestrator and (3) circular manufacturer. The coordination role of the start-ups differs in each supply chain configuration based on the level of vertical integration of manufacturing activities.

From a theoretical perspective, the authors' results expand previous supply chain management (SCM) literature by presenting an empirical analysis of the configuration and coordination of CSCs, and discussing the drivers for creating such circularity from a CAS perspective. From a managerial perspective, the authors offer a practical experience to entrepreneurs on how to transform circular and sustainable business model aspirations into CSC practices.