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The aim of this paper is to contribute to a greater understanding of non-profit organization (NPO) management control systems (MCS) and accountability in organizations providing support service for capacity constrained service users. Specifically, the paper examines the role of MCS and accountability in supporting mission realization in NPOs providing services to people with intellectual disabilities and reflects on this in the context of the COVID-19 pandemic.

The research comprised a case study of four NPOs providing services to people with intellectual disabilities in Ireland conducted prior to the global COVID-19 pandemic. The study probed management's perceptions of stakeholders and examined the manner in which the design and use of MCS and accountability processes supported mission realization.

Service users were regarded as the least powerful stakeholder and consequently the least attended to in terms of MCS and accountability processes. The absence of relational and dialogical accountability with service users is not only central to maintaining this power asymmetry but also poses a threat to mission realization. These deficits can be addressed through the integration and monitoring of internal advocacy activities into MCS and accountability processes, which, on reflection, may also mitigate some of the negative consequences for service users of isolation from external support networks in times of crisis.

This research has opened up an area for enquiry – internal advocacy – heretofore not addressed in the management accounting literature, opening up a novel vein for future research. Such research could further examine the role of internal advocacy, drawing from and adding to the research in other support service domains. A number of objectives and questions might be considered: (1) probing the level of management recognition of the role of direct engagement in advocacy activities in supporting service user agency; (2) identifying with service users and management the nature and attributes of effective advocacy activities and practices; (3) questioning how such advocacy activities and practices might be reflected in MCS; (4) identifying what service user stakeholders regard as effective accountability to them in relation to their needs and objectives; and (5) assessing the impact on service user experience and on NPO mission realization of internal advocacy activities and the monitoring and review thereof through MCS. These suggestions for future research draw attention to aspects of support service delivery that have the potential to be profoundly influential on service outcomes.

A performance management model reflecting the identified need to incorporate internal advocacy mechanisms into organizational management control systems is proposed in an effort to increase accountability of NPOs to their core mission stakeholder – service users. This model may be of value to NPO management as they move from a medical-model of care to a rights-based model for service delivery in care settings.

The paper reflects the importance of listening to the voice of vulnerable service users in NPO care settings and proposes a mechanism for embedding internal advocacy in formal management control systems and accountability processes.

In proposing an “agency” supportive relational and dialogical accountability logic for such organizations, underpinned by “internal advocacy”, this research provides theoretical and practical insights for accountability processes and the design of MCS. The findings contribute empirically, not just to the NPO management and MCS literature but also to understanding the relational interaction of service users with service organizations, and what this means in supporting service user objectives and realization of organizational mission.

This paper explores the characteristics and organisational attributes of hybrid non‐profit organisation (NPO)/public sector settings to identify the particular challenges presented for performance management and to further explore the extent to which such characteristics and attributes might impinge on a move to “performance governance” as a performance framework ideal type.

A preliminary case study of an Irish NPO/public sector hybrid organisation was used to ground a review of NPO and public sector performance management concepts and theoretical developments. The review focused on the implications of organisational characteristics/attributes of the hybrid case study organisation for performance management.

Five organisational characteristics/attributes are identified as central to the understanding of the challenges for performance management in such settings: inter‐stakeholder relationships; tensions across priority objectives; culture and institutional clashes; power distribution; and interdependent stress. Further, it is suggested that while the adoption of collaborative public sector models suggests a move toward performance governance, the performance challenges identified in the hybrid setting give rise to particular barriers to any substantive movement in that direction.

Performance of NPO/public sector hybrid organisations has only relatively recently attracted the attention of researchers. The paper contributes to this emerging area by identifying certain organisational characteristics/attributes particular to such hybrids that are critical to understanding the challenges for performance management in such settings.

In the performance measurement and management research field, the applicability of performance measurement systems (PMS) in nonprofit organizations (NPOs) and public administration has been considered a challenge. The diversity of these organizations makes it difficult to define proper terminology and organizational characteristics. PMS evolution has not yet been able to capture all performance dimensions of a public administration and, especially for NPO considering its dynamic and multiple goals. The purpose of this paper is to provide a conceptual framework that identifies and classifies the factors that influence the design of PMSs in NPOs and public administration.

The study was developed through a systematic literature review (SLR). A set of 29 papers were intensely studied, and the results provide a multi-disciplinary and holistic set of factors.

A set of ten factors that influence the design of PMSs in NPO and public administration were found. They were categorized into three groups: factor related to purpose, stakeholders and management.

The study synthesized the literature and provided a conceptual framework of the factors that influence the design of PMSs in NPO and public administration. No individual paper collected in the SLR shows a similar organization of the factors as the present paper. The set of factors indicates the importance of this study for NPO and public administration, and how complex a PMS in an NPO and public administration can become. The conceptual model presented can further assist practitioners in developing design process observing the role that the identified factors play.

Educators recognize that group work and physical involvement with learning materials can greatly enhance the understanding and retention of difficult concepts. As a result, math manipulatives ‐ such as pattern blocks and number lines ‐ have increasingly been making their way into classrooms and children’s museums. Yet without the constant guidance of a teacher, students can easily become distracted, confused, or frustrated. Math games with tangible user interfaces can address the needs of the modern learning environment by providing the guidance that a teacher would while allowing students to work together in a physical environment. This paper describes how math games with tangible user interfaces can be rapidly developed using a library of functions that were designed specifically for tracking visual tags in math games. The paper also discusses pedagogical principles and an approach to designing and developing games that utilize tangible technologies. Examples of math games that have been prototyped this way are presented. The paper concludes with a study that suggests that this approach helps children to stay focused, think about math problems in new ways, and complete the problem at hand. It also suggests that tangible math games may help children to develop problem‐solving skills that transfer to similar problems.

Construction companies are increasingly adopting sensing technologies like laser scanners, making it necessary to upskill the future workforce in this area. However, limited jobsite access hinders experiential learning of laser scanning, necessitating the need for an alternative learning environment. Previously, the authors explored mixed reality (MR) as an alternative learning environment for laser scanning, but to promote seamless learning, such learning environments must be proactive and intelligent. Toward this, the potentials of classification models for detecting user difficulties and learning stages in the MR environment were investigated in this study.

The study adopted machine learning classifiers on eye-tracking data and think-aloud data for detecting learning stages and interaction difficulties during the usability study of laser scanning in the MR environment.

The classification models demonstrated high performance, with neural network classifier showing superior performance (accuracy of 99.9%) during the detection of learning stages and an ensemble showing the highest accuracy of 84.6% for detecting interaction difficulty during laser scanning.

The findings of this study revealed that eye movement data possess significant information about learning stages and interaction difficulties and provide evidence of the potentials of smart MR environments for improved learning experiences in construction education. The research implication further lies in the potential of an intelligent learning environment for providing personalized learning experiences that often culminate in improved learning outcomes. This study further highlights the potential of such an intelligent learning environment in promoting inclusive learning, whereby students with different cognitive capabilities can experience learning tailored to their specific needs irrespective of their individual differences.

The classification models will help detect learners requiring additional support to acquire the necessary technical skills for deploying laser scanners in the construction industry and inform the specific training needs of users to enhance seamless interaction with the learning environment.

This study explores how the format of explanations used in artificial intelligence (AI)-based services affects consumer behavior, specifically the effects of explanation detail (low vs high) and consumer control (automatic vs on demand) on trust and acceptance. The aim is to provide service providers with insights into how to optimize the format of explanations to enhance consumer evaluations of AI-based services.

Drawing on the literature on explainable AI (XAI) and information overload theory, a conceptual model is developed. To empirically test the conceptual model, two between-subjects experiments were conducted wherein the level of detail and level of control were manipulated, taking AI-based recommendations as a use case. The data were analyzed via partial least squares (PLS) regressions.

The results reveal significant positive correlations between level of detail and perceived understanding and between level of detail and perceived assurance. The level of control negatively moderates the relationship between the level of detail and perceived understanding. Further analyses revealed that the perceived competence and perceived integrity of AI systems positively and significantly influence the acceptance and purchase intentions of AI-based services.

This research offers service providers key insights into how tailored explanations and maintaining a balance between detail and control build consumer trust and enhance AI-based service outcomes.

This article elucidates the nuanced interplay between the level of detail and control over explanations for non-expert consumers in high-credence service sectors. The findings offer insights into the design of more consumer-centric explanations to increase the acceptance of AI-based services.