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To explore Finnish experts' perceptions of the forms of digital healthcare that are anticipated to be the most utilised in healthcare in the medium-term future (year 2035) and anticipated healthcare workforce impacts those forms will have.

A total of 17 experts representing relevant interest groups participated in a biphasic online Delphi study. The results for each round were analysed using descriptive statistical methods and inductive content analysis.

The forms of digital healthcare that the experts perceived as most likely to be utilised were those enabling patient participation, efficient organisation of services and automated data collection and analysis. The main impacts on the healthcare workforce were seen as being the redirection of workforce needs within the healthcare sector and need for new skills and new professions. The decrease in the need for a healthcare workforce was seen as less likely. The impacts were perceived as being constructed through three means: impacts within healthcare organisations, impacts on healthcare professions and impacts via patients.

The results are not necessarily transferable to other contexts because the experts anticipated local futures. Patients' views were also excluded from the study.

Healthcare organisations function in complex systems where drivers, such as regional demographics, legislation and financial constraints, dictate how digital healthcare is utilised. Anticipating the workforce effects of digital healthcare utilisation has received limited attention; the study adds to this discussion.

This paper presents an interpretation of freehand drawings produced by supply chain management undergraduates in response to the question: “What is sustainability?” Having to explain sustainability pictorially forced students to distill what the essence of sustainability meant to them and provided insights into how they perceived sustainability and their roles in achieving sustainability in the context of supply chain management.

Students were asked to draw and answer the question “What is sustainability?” These drawings were discussed/interpreted in class. All drawings were initially examined quantitatively, before a sample of four were selected for presentation here.

Freehand drawing can be used as part of a critical pedagogy to create a visual representation to bypass cognitive verbal processing routes. This allows students to produce clear, more critical and inclusive images of their understanding of a topic regardless of their vocabulary.

The authors offer this as a model for educators seeking alternative methods for engaging with sustainability and for creating a learning environment where students can develop their capacity for critical self-reflection.

This study shows how a collaborative learning experience facilitates learners demonstrating their level of understanding of sustainability.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0718

The purpose of this study is to propose an innovative and efficient process in urban policy-making that combines a divergent and creative method with a convergent and strategic one. At the same time, the purpose is also to propose a useful innovation to enforce the usability of both methods. On the one hand, mission-oriented policies run the risk of being overly focused on the present and of not being able to develop preparedness in organization. On the other hand, scenario development has the reverse problem it often does not point out how to use scenario narratives to inform and devise short-term strategic actions.

The paper proposes an innovative methodological approach, the mission-oriented scenarios, which hybridizes Mazzucato's mission-oriented public policy framework with Jim Dator's Manoa school four futures method. The proposed methodological innovation emerges from a urban foresight academic-led project carried out in the context of the Metropolitan City of Turin, Italy, where a first application of the mission-oriented scenarios was tested on six different focal issues (from reindustrialization to cultural policies) and the scenario narratives were used as sources for the grounding of 12 missions and 48 strategic actions towards 2030.

Mission-oriented scenarios can contribute to the generation of more sustainable and inclusive urban public policies. This methodological proposal is based on an original mix of knowledge exchange procedures borrowed from methodological approaches with different backgrounds: the mission-oriented and the archetypal scenarios. Their conjunction could support the formulation of ambitious yet pragmatic policies, giving a plurality of actors the opportunity to act and establish fruitful and lasting partnerships.

The paper reconstructs one of the first urban foresight projects carried out in a major Italian city by two prestigious universities and exposes a methodological innovation resulting from reflection on the strengths and weaknesses of the project, which opens the door to the development of a new scenario technique.

Currently, foresight studies have been adapted to incorporate new techniques based on big data and machine learning (BDML), which has led to new approaches and conceptual changes regarding uncertainty and how to prospect future. The purpose of this study is to explore the effects of BDML on foresight practice and on conceptual changes in uncertainty.

The methodology is twofold: a bibliometric analysis of BDML-supported foresight studies collected from Scopus up to 2021 and a survey analysis with 479 foresight experts to gather opinions and expectations from academics and practitioners related to BDML in foresight studies. These approaches provide a comprehensive understanding of the current landscape and future paths of BDML-supported foresight research, using quantitative analysis of literature and qualitative input from experts in the field, and discuss potential theoretical changes related to uncertainty.

It is still incipient but increasing the number of prospective studies that use BDML techniques, which are often integrated into traditional foresight methodologies. Although it is expected that BDML will boost data analysis, there are concerns regarding possible biased results. Data literacy will be required from the foresight team to leverage the potential and mitigate risks. The article also discusses the extent to which BDML is expected to affect uncertainty, both theoretically and in foresight practice.

This study contributes to the conceptual debate on decision-making under uncertainty and raises public understanding on the opportunities and challenges of using BDML for foresight and decision-making.

This study explores how a small minority of social entrepreneurs break free from third sector constraints to conceive, create and grow non-profit organisations that generate social value at scale in new and innovative ways.

Six narrative case histories of innovative social enterprises were developed based on documents and semi-structured interviews with founders and long serving executives. Data were coded “chrono-processually”, which involves locating thoughts, events and actions in distinct time periods (temporal bracketing) and identifying the processes at work in establishing new social ventures.

This study presents two core findings. First, the paper demonstrates how successful social entrepreneurs draw on their lived experiences, private and professional, in driving the development and implementation of social innovations, which are realised through application of their capabilities as analysts, strategists and resources mobilisers. These capabilities are bolstered by personal legitimacy and by their abilities as storytellers and rhetoricians. Second, the study unravels the complex processes of social entrepreneurship by revealing how sensemaking, theorising, strategizing and sensegiving underpin the core processes of problem specification, the formulation of theories of change, development of new business models and the implementation of social innovations.

The study demonstrates how social entrepreneurs use sensemaking and sensegiving strategies to understand and address complex social problems, revealing how successful social entrepreneurs devise and disseminate social innovations that substantially add value to society and bring about beneficial social change. A novel process-outcome model of social innovation is presented illustrating the interconnections between entrepreneurial cognition and strategic action.

Engaged employees assure organizational competitiveness and sustainability. The purpose of this study is to explore the relationship between job resources and employee turnover intentions, with employee engagement as a mediating variable.

Data were collected from 934 employees of eight wholly-owned pharmaceutical industries. The proposed model and hypotheses were evaluated using structural equation modeling. Construct reliability and validity was established through confirmatory factor analysis.

Data supported the hypothesized relationship. The results show that job autonomy and employee engagement were significantly associated. Supervisory support and employee engagement were significantly associated. However, performance feedback and employee engagement were nonsignificantly associated. Employee engagement had a significant influence on employee turnover intentions. The results further show that employee engagement mediates the association between job resources and employee turnover intentions.

The generalizability of the findings will be constrained due to the research’s pharmaceutical industry focus and cross-sectional data.

The study’s findings will serve as valuable pointers for stakeholders and decision-makers in the pharmacuetical industry to develop a proactive and well-articulated employee engagement intervention to ensure organizational effectiveness, innovativeness and competitiveness.

By empirically demonstrating that employee engagement mediates the nexus of job resources and employee turnover intentions, the study adds to the corpus of literature.

Entrepreneurial trait and behaviour approaches are used to identify differing entrepreneurial profiles. Specifically, this study aims to determine which entrepreneurial competencies (ECs) can predict entrepreneurial action (EA) for distinct profiles, such as male versus female, start-up versus established and for entrepreneurs within different age groups and educational levels.

The research was conducted using a survey method on a large sample of 1,150 South African entrepreneurs. Chi-squared automatic interaction detection (CHAID) algorithms were used to build decision trees to illustrate distinct entrepreneurial profiles.

Each profile has a different set of ECs that predict EA, with a growth mindset being the most significant predictor of action. Therefore, this study confirms that a “one-size-fits-all” approach cannot be applied when profiling entrepreneurs.

From a pedagogical standpoint, different combinations of these ECs for each profile provide priority information for identification of appropriate candidates (e.g. the highest potential for success) and training initiatives, effective pedagogies and programme design (e.g. which individual ECs should be trained and how should they be trained).

Previous work has mostly focused on demographic variables and included a single sample to profile entrepreneurs. This study maintains much wider applicability in terms of examining profiles in a systematic way. The large sample size supports quantitative analysis of the comparisons between different entrepreneurial profiles using unconventional analyses. Furthermore, as far as can be determined, this represents the first CHAID conducted in a developing country context, especially South Africa, focusing on individual ECs predicting EA.

Urban digital transformation has become a key strategy in global countries. This study aims to provide a comprehensive and dynamic exploration of the intrinsic traits associated with urban digital transformation, in order to yield detailed insights that can contribute to the formulation of well-informed decisions and strategies in the field of urban development initiatives.

Through analysis of parallels between urban digital transformation and gyroscope motion in physics, the study developed the urban digital transformation gyroscope model (UDTGM), which comprises of seven core elements. With the balanced panel dataset from 268 cities at and above the prefecture level in China, we validate the dynamic mechanism of this model.

The findings of this study underscore that the collaboration among infrastructure development, knowledge-driven forces and economic operations markedly bolsters the urban digital transformation gyroscope’s efficacy.

This research introduces a groundbreaking framework for comprehending urban digital transformation, potentially facilitating its balanced and systemic practical implementation.

This study pioneers the UDTGM theoretically and verifies the dynamic mechanism of this model with real data.

This study aims to explore the relationship between promoter share pledging and the company’s dividend payout policy in India. Furthermore, this study also analyses the moderating impact of family involvement in business on the association between share pledging and dividend payout.

A sample of 236 companies from the S&P Bombay Stock Exchange Sensitive (BSE) 500 Index (2014–2023) has been analysed through fixed-effects panel data regression. For additional testing, robustness checks include alternative measures of dividend payout and promoter share pledging, as well as alternative methodologies such as Bayesian regression. Lastly, to address potential endogeneity, instrumental variables with a two-stage least squares (IV-2SLS) methodology have been implemented.

Upholding the agency perspective, a significantly negative impact of promoter share pledging on corporate dividend payouts in India has been uncovered. Moreover, family involvement in business moderates this relationship, highlighting that the negative association between promoter share pledging and dividend payouts is more pronounced in family companies. The findings are consistent throughout the robustness testing.

The present study represents a pioneering endeavour to empirically analyse the link between promoter share pledging and dividend payouts in India. It enhances the theoretical underpinnings of the agency relationship, particularly by substantiating the existence of Type II agency conflicts between majority and minority shareholders. The findings of this research bear significant implications for investors, researchers and policymakers, particularly in light of the widespread prevalence of promoter-controlled entities in India.

This paper presents a follow-on study that quantifies geolingual markers and their apparent connection with authorship collaboration patterns in canonical Digital Humanities (DH) journals. In particular, it seeks to detect patterns in authors' countries of work and languages in co-authorship networks.

Through an in-depth co-authorship network analysis, this study analysed bibliometric data from three canonical DH journals over a range of 52 years (1966–2017). The results are presented as visualised networks with centrality calculations.

The results suggest that while DH scholars may not collaborate as frequently as those in other disciplines, when they do so their collaborations tend to be more international than in many Science and Engineering, and Social Sciences disciplines. DH authors in some countries (e.g. Spain, Finland, Australia, Canada, and the UK) have the highest international co-author rates, while others have high national co-author rates but low international rates (e.g. Japan, the USA, and France).

This study is the first DH co-authorship network study that explores the apparent connection between language and collaboration patterns in DH. It contributes to ongoing debates about diversity, representation, and multilingualism in DH and academic publishing more widely.