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Change management (CM) and project management (PM) literatures examine the key roles (change agent, project manager, project or change sponsor) played during projects or changes only from their respective points of view. They do so even in cases where projects and changes occur at the same time – or are so-called change projects. In such cases, effective management should utilize both scientific fields’ bodies of knowledge (BoK). The purpose of this paper is to unfold how and in which domain(s) typical roles of the two disciplines correspond to each other.

This paper is a systematic, bi-disciplinary meta-review that simultaneously studies relevant literature on roles performed during projects and changes. The common domain of CM and PM was identified; the systematic review and comparison of role definitions followed.

This paper examines and illustrates the correspondence of 7 CM and 14 PM roles; e.g., “sponsor” refers to the same role and “change agent” and “project manager” are corresponding ones, referring to the same role up to a certain degree.

This paper does not provide an exhaustive overview of various instances of different role (and stakeholder) interpretations.

Findings should facilitate the better management of changes that require CM-type and PM-type capabilities and actions.

As a result of the meta-review, two CM roles were re(de)fined. Linking PM and CM roles provides common ground on which practitioners of both fields can rely. A step-by-step tool for the identification of such cases in practice, when both types of roles should be played and both BoK can be utilized complementarily, was developed.

The purpose of this paper is to provide classification confidence value to every individual sample classified by decision trees and use this value to combine the classifiers.

The proposed system is first theoretically explained, and then the use and effectiveness of the proposed system is demonstrated on sample datasets.

In this paper, a novel method is proposed to combine decision tree classifiers using calculated classification confidence values. This confidence in the classification is based on distance calculation to the relevant decision boundary (distance conditional), probability density estimation and (distance conditional) classification confidence estimation. It is shown that these values – provided by individual classification trees – can be integrated to derive a consensus decision.

The proposed method is not limited to axis‐parallel trees, it is applicable not only to oblique trees, but also to any kind of classifier system that uses hyperplanes to cluster the input space.

A novel method is presented to extend decision tree like classifiers with confidence calculation and a voting system is proposed that uses this confidence information. The proposed system possesses several novelties (e.g. it not only gives class probabilities, but also classification confidences) and advantages over previous (traditional) approaches. The voting system does not require an auxiliary combiner or gating network, as in the mixture of experts structure and the method is not limited to decision trees with axis‐parallel splits; it is applicable to any kind of classifiers that use hyperplanes to cluster the input space.

The article applies the citizen science phenomenon – i.e. lay people involvement in research endeavours aimed at pushing forward scientific knowledge – to healthcare. Attention is paid to initiatives intended to tackle the COVID-19 pandemic as an illustrative case to exemplify the contribution of citizen science to system-wide innovation in healthcare.

A mixed methodology consisting of three sequential steps was developed. Firstly, a realist literature review was carried out to contextualize citizen science to healthcare. Then, an account of successfully completed large-scale, online citizen science projects dealing with healthcare and medicine has been conducted in order to obtain preliminary information about distinguishing features of citizen science in healthcare. Thirdly, a broad search of citizen science initiatives targeted to tackling the COVID-19 pandemic has been performed. A comparative case study approach has been undertaken to examine the attributes of such projects and to unravel their peculiarities.

Citizen science enacts the development of a lively healthcare ecosystem, which takes its nourishment from the voluntary contribution of lay people. Citizen scientists play different roles in accomplishing citizen science initiatives, ranging from data collectors to data analysts. Alongside enabling big data management, citizen science contributes to lay people's education and empowerment, soliciting their active involvement in service co-production and value co-creation.

Citizen science is still underexplored in healthcare. Even though further evidence is needed to emphasize the value of lay people's involvement in scientific research applied to healthcare, citizen science is expected to revolutionize the way innovation is pursued and achieved in the healthcare ecosystem. Engaging lay people in a co-creating partnership with expert scientist can help us to address unprecedented health-related challenges and to shape the future of healthcare. Tailored health policy and management interventions are required to empower lay people and to stimulate their active engagement in value co-creation.

Citizen science relies on the wisdom of the crowd to address major issues faced by healthcare organizations. The article comes up with a state of the art investigation of citizen science in healthcare, shedding light on its attributes and envisioning avenues for further development.

Ongoing environmental threats have intensified the need for firms to take big leaps forward to operate in a manner that is both ecologically sustainable and socially responsible. This paper aims to assess the degree to which firms are adopting citizen science as a tool to achieve sustainability and social responsibility targets.

This study applies a qualitative content analysis approach to assess the current presence of citizen science in sustainability and social responsibility reports issued by Globescan sustainability leaders and by firms ranked by the Fortune 500 and Fortune Global 500.

While the term itself is mostly absent from reports, firms are reporting on a range of activities that could be classified as a form of “citizen science.”

Citizen science can help firms achieve their corporate sustainability and corporate social responsibility goals and targets. Linking sustainability and social responsibility efforts to this existing framework can help triangulate corporate efforts to engage with stakeholders, collect data about the state of the environment and promote better stewardship of natural resources.

Supporting citizen science can help firms work toward meeting UN Sustainable Development Goals, which have highlighted the importance of collaborative efforts that can engage a broad range of stakeholders in the transition to more sustainable business models.

This paper is the first to examine citizen science in a corporate sustainability and social responsibility context. The findings present information to support improvements to the development of locally relevant science-based indicators; real-time monitoring of natural resources and supply chain sustainability; and participatory forums for stakeholders including suppliers, end users and the broader community.