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A qualitative approach based on grounded theory was utilized, with data collected through 26 semi-structured interviews with social entrepreneurs. Alas’s Triangular Model provided the framework for data analysis and interpretation.

This study explores how Hong Kong social enterprises approached crisis and change management during the COVID-19 pandemic, examining their resilience-building strategies.

The pandemic triggered an existential crisis for many social enterprises, causing severe revenue losses. However, strong leadership and cultures based on social mission enabled resilience. Enterprises demonstrated agility by rapidly transitioning operations online and establishing partnerships. Technology adaptation and social innovation were pivotal to sustaining impact.

As the sample comprises enterprises that survived the pandemic, insights into failed enterprises are lacking. Comparative analysis could illuminate differences in crisis response between successful and unsuccessful cases.

The study’s practical implications suggest that social enterprises should focus on developing flexible crisis management plans, cultivating purposeful leadership, embracing digital transformation, strengthening collaborative networks and prioritizing organizational learning to effectively navigate crises while staying true to their social missions.

Findings demonstrate how shared values and cultures grounded in purpose can anchor organizations amidst upheaval, fostering resilience. This underscores the role of social enterprises in modeling responsiveness to societal needs.

While research has examined social enterprises’ vulnerability in crises, investigation into their crisis management practices is limited. This study enriches understanding of how social enterprises effectively navigate turbulence.

Drawing on the socioemotional selectivity theory and the volunteerism literature, this study aims to examine the influence of empathy, altruism and opportunity recognition, on social entrepreneurial intentions (SEI) of people who have retired from a full-time career. Furthermore, the study examines whether the above-mentioned relationships are mediated by moral obligation.

A set of hypotheses is tested by applying partial least squares structural equation modelling on a survey sample of 227 retirees in Oman, who had participated in an entrepreneurial leadership training after retirement. Using SmartPLS software, the path model is tested through bootstrapping.

The findings suggest that altruism and opportunity recognition do not have a direct relationship with SEI, however, they are significant only when mediated through moral obligation. Nevertheless, empathy has a significant direct association with SEI, and an indirect relationship through moral obligation.

The findings of this study demonstrate that to develop intentions to indulge in social entrepreneurship, among retirees who are approaching their senior years, the focus should be on driving their sense of moral obligation to society. Hence, policymakers and authorities connected to social wellbeing goals can fine-tune their initiatives, such as training, by emphasizing on moral obligation to address social issues through social entrepreneurship.

The novelty of this study is twofold. Firstly, to the best of the authors’ knowledge, it seems to be among the first empirical study that is at the crossroads of the senior entrepreneurship and the social entrepreneurship literature. Secondly, this study fills a gap in the extant literature by deploying the socioemotional selectivity theory to examine the antecedents of SEI of people who have retired from full-time employment in their early to late senior years.

This study demonstrates how artificial intelligence (AI) shapes the strategic planning process in volatile, uncertain, complex and ambiguous (VUCA) business environments. Having adopted various domains of the Cynefin framework, the research explores AI's transformative potential and provide insights regarding how organisations can harness AI-driven solutions for strategic planning.

This conceptual paper theorises the role of AI in strategic planning process in a VUCA world by integrating extant knowledge across multiple literature streams. The “model paper” approach was adopted to provide a theoretical framework predicting relationships among considered concepts.

The paper highlights potential application of the Cynefin framework to manage complexities in strategic decision-making process, the transformative impact of AI at different stages of strategic planning, the required strategic planning characteristics within VUCA to be supported by AI and the attendant challenges posed by AI integration in the uncertain business landscape.

This study pioneers a theoretical exploration of AI's role in strategic planning within the VUCA business landscape, guided by the Cynefin framework. Thus, it enriches scholarly discourse and expands knowledge frontiers.

Alternative theoretical perspectives on performance measurement and management (PMM) have been advanced in response to shortcomings observed with the dominant control systems-based paradigm. The purpose of this investigation is to ascertain whether one such perspective, rooted in social systems theory and practice theory, can accommodate these shortcomings and positively impact organisational effectiveness (OE) and performance.

Longitudinal critical realism-based case study research is employed in action research mode to investigate how adopting a social complexity perspective on PMM affected the behaviour and performance of a commercial organisation.

The case study observations suggest that by putting people and their behaviour and organisational practices at the centre of PMM, near-term organisational outcomes can be influenced favourably in complex and dynamic environments.

This investigation provides a tool for undertaking a social complexity interpretation of PMM.

This research supports the proposal that complexity theory provides an alternative paradigm for managing performance in organisations and describes the first practical application of a social complexity interpretation of PMM. It presents a model for use and further development by other researchers.

Quality management (QM) can support organisations in contributing to sustainable development. As a result of an expanding focus from customers towards stakeholders within QM, the perspectives to consider multiply. Understanding how practices and tools for process management are specifically affected by this increase in perspectives is key to creating the right conditions for improvement initiatives that support sustainable development.

This paper constructs a typology wherein the use of process management practices and tools is described in nine distinguished system contexts. Inductive discrimination is used to differentiate the system contexts and different use cases for process practices and tools.

Using the system of systems grid (SOSG), mainstream business process management (BPM) practices are positioned in a simple unitary context, whilst sustainability challenges also involve more complex contexts. Addressing these challenges requires integrating new tools and methods from paradigms outside of traditional functionalist business process management practices.

This paper highlights the necessity to consider system contexts when developing feasible practices and tools for effective process management.

Practical implications are that quality practitioners aiming to exploit the potential in process management to support sustainability get support for planning and conducting process improvement initiatives aiming to consider several stakeholder perspectives.

This paper presents a new typology for understanding the context of QM process initiatives and BPM in light of a contemporary sustainability focus.

The purpose of this paper is to examine whether mandatory disclosure of information accompanying the sale of real estate achieves its aim of informed purchasers.

Using a case study approach focused on mandatory disclosure in South Australia data was collected from interviews and focus groups with key personnel in the property industry involved in the production of information required to fulfil vendors’ disclosure obligations.

The authors found that purchasers are ill-served by a long and complex form of mandatory disclosure with a short time frame that prevents the use of the information provided. Without good form design and increased digital affordances provided by the cadastral and conveyancing systems, mandatory disclosure is insufficient to ensure minimisation of information asymmetry between vendor and purchaser.

To the best of the authors’ knowledge, this is the first Australian qualitative study that examines the utility of mandatory vendor disclosure in real estate sales and the first to consider the impact of the digitalisation of cadastral and conveyancing systems upon the efficacy of mandatory disclosure regimes.

To advance understanding of transparency by problematising the motivations and strategies of a so far underexplored group: its users.

We explore the relationship between blindness, visibility, and transparency by drawing on our analysis of Max Frisch’s experimental novel Gantenbein (1964), in which the protagonist lives a life of feigned blindness.

The accounting scholarly debate on transparency has neglected the users of transparency. We address this through a novel theorisation of transparency as a game, highlighting some of its distinctive features and paradoxes.

By theorising the transparency game we move beyond concerns with what transparency reveals or conceals and conceptualise the motivations and strategies of the players engaged in this game. We show how different players have something to gain from the transparency game and warn of its emancipatory limits.

This article problematizes the concept of freedom rooted in liberalism, examining the detention of historian Ilan Pappe by the Federal Bureau of Investigation (FBI) at Detroit Airport in the United States as an emblematic case study.

The research adopts a methodological triangulation approach, based on an analysis that combines data about the event and theories about the concept of freedom, problematizing authors who focused on the relationship between the individual and society in a liberal context, where individualism serves as the basis for specific conceptions of social relations.

Through the use of authors such as John Stuart Mill and John Locke, as well as the contributions of authors like Norbert Elias, it is argued that true freedom is relational, rooted in social interdependencies and the social construction of an individuality that is not individualistic but intrinsically linked to collective aspects.

Pappe’s case illustrates the tensions between individual freedom and collective interests, highlighting the need to reassess freedom of expression in complex political and social contexts.

This article proposes a more inclusive and interconnected view of human freedom, where individual and collective interests are negotiated within a dynamic web of social relations.

This study aims to use regression Least-Square Support Vector Machine (LS-SVM) as a probabilistic model to determine the factor of safety (FS) and probability of failure (PF) of anisotropic soil slopes.

This research uses machine learning (ML) techniques to predict soil slope failure. Due to the lack of analytical solutions for measuring FS and PF, it is more convenient to use surrogate models like probabilistic modeling, which is suitable for performing repetitive calculations to compute the effect of uncertainty on the anisotropic soil slope stability. The study first uses the Limit Equilibrium Method (LEM) based on a probabilistic evaluation over the Latin Hypercube Sampling (LHS) technique for two anisotropic soil slope profiles to assess FS and PF. Then, using one of the supervised methods of ML named LS-SVM, the outcomes (FS and PF) were compared to evaluate the efficiency of the LS-SVM method in predicting the stability of such complex soil slope profiles.

This method increases the computational performance of low-probability analysis significantly. The compared results by FS-PF plots show that the proposed method is valuable for analyzing complex slopes under different probabilistic distributions. Accordingly, to obtain a precise estimate of slope stability, all layers must be included in the probabilistic modeling in the LS-SVM method.

Combining LS-SVM and LEM offers a unique and innovative approach to address the anisotropic behavior of soil slope stability analysis. The initiative part of this paper is to evaluate the stability of an anisotropic soil slope based on one ML method, the Least-Square Support Vector Machine (LS-SVM). The soil slope is defined as complex because there are uncertainties in the slope profile characteristics transformed to LS-SVM. Consequently, several input parameters are effective in finding FS and PF as output parameters.