Purpose: To improve the academic integrity of online examinations, digital proctoring systems have recently been implemented in higher education institutions (HEIs). The paper aims to understand how digital proctoring has been practised in higher education (HE) and proposes future research directions for studying digital proctoring in HE. Design/methodology/approach: A systematic literature review was conducted. The PRISMA procedure was adapted for the literature search. The topics were identified by topic modelling techniques from 154 relevant publications in seven databases. Findings: Seven widely discussed topics in literature were identified, including solutions for detecting cheating and student authentication, challenges/issues of uptakes and students' performance in different proctoring environments. Research limitations/implications: This paper provides insights for academics, policymakers, practitioners and students to understand the implementation of digital proctoring in academia, its adoption by HEIs, impacts on students' and educators' performance and the rapid increase in its use for digital exams in HEIs, with particular emphasis on the impacts of the systems on digitalising examinations in HE. Originality/value: This review paper has systematically and critically described the state-of-the-art literature on digital proctoring in HE and provides useful insights and implications for future research on digital proctoring, and how academic integrity in online examinations can be enhanced, along with digitalising HE.

Artificial Intelligence (AI) must be directed at humane ends. The development of AI has produced great uncertainties of ensuring AI alignment with human values (AI value alignment) through AI operations from design to use. For the purposes of addressing this problem, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we first discuss the AI value alignment from the relevant AI studies. Second, we briefly present what are material values and technological mediation and reflect on the AI value alignment through the lenses of these theories. We conclude that a set of finite human values can be defined and adapted to the stable life tasks that AI systems will be called upon to accomplish. The AI value alignment can also be fostered between designers and users through technological mediation. Upon that foundation, we propose a set of common principles to understand the AI value alignment through phenomenological theories. This paper contributes the unique knowledge of phenomenological theories to the discourse on AI alignment with human values.

Artificial Intelligence (AI) must be directed at humane ends. The development of AI has produced great uncertainties of ensuring AI alignment with human values (AI value alignment) through AI operations from design to use. For the purposes of addressing this problem, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we first discuss the AI value alignment from the relevant AI studies. Second, we briefly present what are material values and technological mediation and reflect on the AI value alignment through the lenses of these theories. We conclude that a set of finite human values can be defined and adapted to the stable life tasks that AI systems will be called upon to accomplish. The AI value alignment can also be fostered between designers and users through technological mediation. Upon that foundation, we propose a set of common principles to understand the AI value alignment through phenomenological theories. This paper contributes the unique knowledge of phenomenological theories to the discourse on AI alignment with human values.

Artificial Intelligence (AI) must be directed at humane ends. The development of AI has produced great uncertainties of ensuring AI alignment with human values (AI value alignment) through AI operations from design to use. For the purposes of addressing this problem, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we first discuss the AI value alignment from the relevant AI studies. Second, we briefly present what are material values and technological mediation and reflect on the AI value alignment through the lenses of these theories. We conclude that a set of finite human values can be defined and adapted to the stable life tasks that AI systems will be called upon to accomplish. The AI value alignment can also be fostered between designers and users through technological mediation. Upon that foundation, we propose a set of common principles to understand the AI value alignment through phenomenological theories. This paper contributes the unique knowledge of phenomenological theories to the discourse on AI alignment with human values.

Artificial Intelligence (AI) must be directed at humane ends. The development of AI has produced great uncertainties of ensuring AI alignment with human values (AI value alignment) through AI operations from design to use. For the purposes of addressing this problem, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we first discuss the AI value alignment from the relevant AI studies. Second, we briefly present what are material values and technological mediation and reflect on the AI value alignment through the lenses of these theories. We conclude that a set of finite human values can be defined and adapted to the stable life tasks that AI systems will be called upon to accomplish. The AI value alignment can also be fostered between designers and users through technological mediation. Upon that foundation, we propose a set of common principles to understand the AI value alignment through phenomenological theories. This paper contributes the unique knowledge of phenomenological theories to the discourse on AI alignment with human values.

Introduction. This paper investigates the effects of information avoidance, information overload, health literacy on individuals’ shared health decision making.Methods. A research model is proposed based on sound theoretical background. Data from 155 respondents was collected via an online survey. Analysis. Partial Least Squares Structural Equation Modelling (PLS-SEM) was applied to analyse the data. Results. The findings suggest that information overload and information avoidance both exhibit negative effects on an individual’s shared health decision making behaviour, while health literary possess positive effects. We also find that information avoidance has a positive impact on information avoidance. Moreover, health literacy is negatively related to both information overload and information avoidance.Conclusions. The paper enhances both theoretical and empirical understanding of the effects of individuals’ health literacy, information overload and information avoidance on their shared health decision making behaviour. The results indicate that sufficient health literacy enables individuals to engage in their health decision making process and sharing their concerns with their physicians. However, information overload and information avoidance trigger negative effects which lead to individuals less involved in shared health decision making. Our results advocate more efforts to improve individual health literary as the means to mitigate the negative effects of information overload and information avoidance towards shared health decision making.

Purpose: The purpose of this paper is to demonstrate and evaluate the prioritization and categorization method (PCM), which facilitates the active participation of process stakeholders (managers, owners, customers) in process assessments. Stakeholders evaluate processes in terms of effectiveness, efficiency and relevance against certain contextual business and industry factors. This collective evaluation serves as a foundation for the management decision-making process regarding process improvement and redesign. Design/methodology/approach: The PCM is examined based on a case study at Ericsson. In total, 55 stakeholders, representing different organizational levels and functions, assessed eight core processes. Follow-up interviews and feedback after the evaluation sessions were collected for triangulation purpose. Findings: The PCM helps Ericsson evaluate its processes within business context and industry environments. The results show that, to realize seamless end-to-end processes in the eight assessed processes, Ericsson has to make a greater effort to improve its process structures, governance and culture for fulfilling the needs of future business. Ericsson Steering Group is satisfied with the insights provided and has decided to train more stakeholders to use PCM. Research limitations/implications: This research is based on a single case within a specific organizational setting. The results may not be necessary generalizable to other business and industry settings. Organizations need to configure PCM in consideration of their own processes and business contingencies to explore and fulfil their process improvement purposes. Originality/value: This paper presents a new context-aware, easy-to-use and holistic method for business process management (BPM), the PCM. The method requires the active engagement of stakeholders, it focusses on developing dynamic BPM capabilities and fully embeds organizational contingencies and contextual factors in the decision-making regarding BPM. This paper contributes a novel method to explorative BPM.