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The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems.

Preferred reporting items of systematic reviews and meta-analyses guidelines have been used for a thorough insight into associated aspects of e-learning that complement the e-learning pedagogies and processes. The aspects of e-learning systems have been reviewed comprehensively such as personalization and adaptivity, e-learning and semantics, learner profiling and learner categorization, which are handy in intelligent content recommendations for learners.

The adoption of semantic Web based technologies would complement the learner’s performance in terms of learning outcomes.

The evaluation of the proposed framework depends upon the yearly batch of learners and recording is a cumbersome/tedious process.

E-Learning systems may have diverse and positive impact on society including democratized learning and inclusivity regardless of socio-economic or geographic status.

A preliminary framework of an ontology-based e-learning system has been proposed at a modular level of granularity for implementation, along with evaluation metrics followed by a future roadmap.

Process mining (PM) has emerged as a leading technology for gaining data-based insights into organizations’ business processes. As processes increasingly cross-organizational boundaries, firms need to conduct PM jointly with multiple organizations to optimize their operations. However, current knowledge on cross-organizational process mining (coPM) is widely dispersed. Therefore, we synthesize current knowledge on coPM, identify challenges and enablers of coPM, and build a socio-technical framework and agenda for future research.

We conducted a literature review of 66 articles and summarized the findings according to the framework for Information Technology (IT)-enabled inter-organizational coordination (IOC) and the refined PM framework. The former states that within inter-organizational relationships, uncertainty sources determine information processing needs and coordination mechanisms determine information processing capabilities, while the fit between needs and capabilities determines the relationships’ performance. The latter distinguishes three categories of PM activities: cartography, auditing and navigation.

Past literature focused on coPM techniques, for example, algorithms for ensuring privacy and PM for cartography. Future research should focus on socio-technical aspects and follow four steps: First, determine uncertainty sources within coPM. Second, design, develop and evaluate coordination mechanisms. Third, investigate how the mechanisms assist with handling uncertainty. Fourth, analyze the impact on coPM performance. In addition, we present 18 challenges (e.g. integrating distributed data) and 9 enablers (e.g. aligning different strategies) for coPM application.

This is the first article to systematically investigate the status quo of coPM research and lay out a socio-technical research agenda building upon the well-established framework for IT-enabled IOC.

Experts may adjust their assessments through communication and mutual influence, and this dynamic evolution relies on the spread of internal trust relationships. Due to differences in educational backgrounds and knowledge experiences, trust relationships among experts are often incomplete. To address such issues and reduce decision biases, this paper proposes a probabilistic linguistic multi-attribute group decision consensus model based on an incomplete social trust network (InSTN).

In this paper, we first define the new trust propagation operators based on the operations of Probability Language Term Set (PLTS) with algebraic t-conorm and t-norm, which are combined with trust aggregation operators to estimate InSTN. The adjustment coefficients are then determined through trust relations to quantify their impact on expert evaluation. Finally, the particle swarm algorithm (PSO) is used to optimize the expert evaluation to meet the consensus threshold.

This study demonstrates the feasibility of the method through the selection of treatment plans for complex cases. The proposed consensus model exhibits greater robustness and effectiveness compared to traditional methods, mainly due to the effective regulation of trust relations in the decision-making process, which reduces decision bias and inconsistencies.

This paper introduces a novel probabilistic linguistic multi-attribute swarm decision consensus model based on an InSTN. It proposes a redefined trust propagation and aggregation approach to estimate the InSTN. Moreover, the computational efficiency and decision consensus accuracy of the proposed model are enhanced by using PSO optimization.

We have come to a point where the common way to characterise what is taking place presently, or, better yet, for the past almost two years, is with the term ‘pandemic’. The task of this chapter is to bring to awareness certain critical reflections with the hope of disturbing the normalised discourse which excepts the authentic meaning of pandemic, a meaning which affects the totality of the human existence. Following the thoughts of Agamben, Baudrillard, and Heidegger, the hypothesis that this chapter is advancing revolves around the idea that the term ‘pandemic’ has been appropriated by biological thinking excepting its authentic meaning, that is, the ultimate reality of the human existence which is death.

This article proposes that survival can be a legitimate organizational goal, challenging a common view that dismisses it as unambitious or contrary to innovation. Drawing parallels from nature and survival strategies across various systems, it advocates that organizations, much like living organisms, should prioritize survivability (i.e. ability to survive) to ensure long-term success. Contrary to being seen as limiting, survival, when understood in its broad sense, can encompass and enhance performance goals such as growth. The article outlines the ERP factors —efficiency, resilience and prominence—as key to achieving survivability, offering a framework for organizations to manage resources, adapt to external forces and balance visibility to thrive amidst challenges.

Conceptual framework.

This model introduces the significance of survivability as an organizational goal.

This article argues for the consideration of survival as an overarching organizational goal, challenging the prevalent view that dismisses it as unambitious or contrary to innovation.

This aims to explore the relationship between the agile methods barriers in large-scale contexts and the benefits for business, team and product and process, exploring the organizational readiness (OR) mediating role.

We propose a theoretical model through survey-based research, applying partial least square structural equation modelling.

We confirmed that OR mediating effect on the relationship between agile methods barriers and team benefits. We operationalized OR in a broader context that embeds the strategic alignment of large-scale agile implementation, considering variables such as organizational structure and culture.

The data are cross-sectional rather than longitudinal, which limits temporal interpretations of the associations between agile methods and organizational issues.

The findings offer a way forward for organizations already using or planning to implement agile management to understand the pathway towards achieving the expected benefits. Our study also unveils the importance of looking at OR when implementing such a complex change in management from traditional to large-scale contexts.

Our results show the significant and positive influence of agile method on all three benefit variables (team, business, product and processes). Furthermore, we identified the significant and positive mediating role of OR on the relationship between agile method and team benefits.

Productivity is often cited as a key barrier to the adoption of metal laser-based powder bed fusion (ML-PBF) technology for mass production. Newer generations of this technology work to overcome this by introducing more lasers or dramatically different processing techniques. Current generation ML-PBF machines are typically not capable of taking on additional hardware to maximise productivity due to inherent design limitations. Thus, any increases to be found in this generation of machines need to be implemented through design or adjusting how the machine currently processes the material. The purpose of this paper is to identify the most beneficial existing methodologies for the optimisation of productivity in existing ML-PBF equipment so that current users have a framework upon which they can improve their processes.

The review method used here is the preferred reporting items for systematic review and meta-analysis (PRISMA). This is complemented by using an artificial intelligence-assisted literature review tool known as Elicit. Scopus, WEEE, Web of Science and Semantic Scholar databases were searched for articles using specific keywords and Boolean operators.

The PRIMSA and Elicit processes resulted in 51 papers that met the criteria. Of these, 24 indicated that by using a design of experiment approach, processing parameters could be created that would increase productivity. The other themes identified include scan strategy (11), surface alteration (11), changing of layer heights (17), artificial neural networks (3) and altering of the material (5). Due to the nature of the studies, quantifying the effect of these themes on productivity was not always possible. However, studies citing altering layer heights and processing parameters indicated the greatest quantifiable increase in productivity with values between 10% and 252% cited. The literature, though not always explicit, depicts several avenues for the improvement of productivity for current-generation ML-PBF machines.

This systematic literature review provides trends and themes that aim to influence and support future research directions for maximising the productivity of the ML-PBF machines.

The article aims to give an overview of the history and the achieved status of information science in the German Democratic Republic (GDR) with an emphasis on the organisation of information science and practice in the GDR and on the theoretical foundations of information science.

Primarily, this article is based upon critical literature studies, especially German-language books and journal articles, but the empirical basis also includes some unpublished sources (e.g. letters from information scientists from the GDR).

There are interesting results concerning the roots of information science in cybernetics, philosophy and the practical area of documentation. The naming of this knowledge field as “informatics”, “informatics of science” or “information and documentation science” is partly very distinct from Western conceptions. We found different theoretical foundations for information science including the approaches of Bonitz, Engelbert, Koblitz and Groß and Fuchs-Kittowski. In the GDR, information science and information practice were centralised, but through the information system science and technology, they were consistently accessible at all levels of professional work. With German reunification, information practice and its institutions, as well as GDR’s information science efforts, disappeared.

The article gives hints on the importance on and the survival of some GDR approaches in contemporary information science, but those developments should be analysed in much more detail.

This is the first overview article on the state and entire development of information science in the GDR.

To address the shortcomings of existing academic user information needs identification methods, such as low efficiency and high subjectivity, this study aims to propose an automated method of identifying online academic user information needs.

This study’s method consists of two main parts: the first is the automatic classification of academic user information needs based on the bidirectional encoder representations from transformers (BERT) model. The second is the key content extraction of academic user information needs based on the improved MDERank key phrase extraction (KPE) algorithm. Finally, the applicability and effectiveness of the method are verified by an example of identifying the information needs of academic users in the field of materials science.

Experimental results show that the BERT-based information needs classification model achieved the highest weighted average F1 score of 91.61%. The improved MDERank KPE algorithm achieves the highest F1 score of 61%. The empirical analysis results reveal that the information needs of the categories “methods,” “experimental phenomena” and “experimental materials” are relatively high in the materials science field.

This study provides a solution for automated identification of academic user information needs. It helps online academic resource platforms to better understand their users’ information needs, which in turn facilitates the platform’s academic resource organization and services.

The aim of this paper is to propose a basis upon which accounting reporting can be developed to reflect real values and the real economy. It aims to address the environmental considerations discussed in the UN debate (Bebbington and Unerman, 2020) and the concern for a “better life-world”, which is the theme of this special issue.

Addressing the task involves the application of the philosophy of pragmatic constructivism (which explains how people can relate to their reality in ways that lead to successful action) and the philosophical concept of the “good life” (which establishes the values to be pursued through action and so defines action success). Also, it outlines the necessary characteristics of measurement frameworks if they are to be effective in the development and control of human practices to achieve desired values.

This paper proposes a conceptual framework for guiding the measurement of how a sustainable good life has improved and/or deteriorated as a result of organisational activities. It outlines a system of concepts on basic and instrumental values for analysing the condition of maintaining a sustainable good life in real terms. This is related to the financial results and societal regulations to analyse and adjust controls according to the real economic goals. Also, it provides a system of value measurands to produce valid information about the development of a sustainable good life. The measurand makes accounting reporting reflect the conditions of the good life that constitute the real economy instead of merely the financial economy driven by shareholder capitalism. Providing tools to analyse whether the existing practices of business and social regulations promote or counteract the real economic goals of producing a sustainable good life means the measurement system proposed makes the invisible hand of the market visible.

The mechanism proposed to enable accounting reporting to reflect real values and the real economy is a new conceptual framework that will allow accounting to more fully realise its potential to contribute to a “better world”. In aiming to serve a sustainable good life, accounting reporting will inherently foster ethical social practices.