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The purpose of this paper is to describe and explore the current state of internet regulation through content filters in Swedish public libraries.

Data was collected through an electronic survey directed to library managers of Sweden’s 290 main municipal libraries. 164 answers were returned, yielding a 57% response rate. The analysis comprises descriptive statistics for quantitative data and an activity theory approach with focus on contradictions for qualitative counterparts.

In total, 33% of the responding libraries report having content filters; 50% have not; and a surprising 18% do not know. There is a strong correlation between internet misuse and positive attitudes towards filters, and, reversely, between lack of misuse and lack of active stances concerning filters. Rather than seeing this as weakness, the authors suggest that there is strength in a context-bound flexibility open to practical experience and weighting of values, ethics, legislation and local circumstances. More troublesome indications concern the high deferral of decision-making to local authorities (municipalities) whereby libraries are left with limited insight and influence.

The situation calls for professional organisations to address political mandate questions, and educational programs to strengthen future information professionals’ knowledge of IT in general; filter issues in specific; and local authority decision-making. The study highlights the need of adequate information professional competences and mandates to decide on and oversee internet regulation.

To the best of the authors’ knowledge, this is the first internationally published study on content filters in Swedish public libraries.

The purpose of this paper is to review current knowledge, research and thinking about the difficulties facing public libraries offering internet access to their users in ensuring legally compliant and non-offensive use of this facility whilst still adhering to the professional value of freedom of access to information.

A range of recently published sources (1997-2013) relating to the technical and organisational measures used to manage public internet access primarily in public libraries in the UK with some limited international examples were reviewed and analysed. This work was undertaken as the underpinning research for an AHRC-funded project, MAIPLE (Managing Access to the internet in Public Libraries).

The provision of public internet access is a well-established component of the role of public libraries, but is seen as a potential problem due to the possibility of misuse, and it appears that simplistic technical solutions have disappointed. Legislation increases the need for more effective solutions that can provide a balance between the need for legal compliance, a welcoming environment for users, and the protection of key freedoms. A range of measures are being adopted worldwide in response to this dilemma.

Research exploring internet access in public libraries and its management in the UK is numerically small and much of it dates back to the start of the twenty-first century. This review presents a comprehensive analysis of the available literature and is of relevance to practitioners and academics in the fields of public librarianship.

Building information modeling (BIM) is mostly limited to the design phase where two parallel processes exist, i.e. creating 2D-drawings and BIM. Towards the end of the design process, BIM becomes obsolete as focus shifts to producing static 2D-drawings, which leads to a lack of trust in BIM. In Scandinavia, a concept known as Total BIM has emerged, which is a novel “all-in” approach where BIM is the single source of information throughout the project. This paper's purpose is to investigate the overall concept and holistic approach of a Total BIM project to support implementation and strategy work connected to BIM.

Qualitative data were collected through eight semi-structured interviews with digitalization leaders from the case study project. Findings were analyzed using a holistic framework to BIM implementation.

The Total BIM concept was contingent on the strong interdependences between commonly found isolated BIM uses. Four main success factors were identified, production-oriented BIM as the main contractual and legally binding construction document, cloud-based model management, user-friendly on-site mobile BIM software and strong leadership.

A unique case is studied where BIM is used throughout all project phases as a single source of information and communication platform. No 2D paper drawings were used on-site and the Total BIM case study highlights the importance of a new digitalized construction process.

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

The purpose of this paper is to discuss how enterprises can effectively perceive and use the digital opportunities brought about by digital technologies and dynamic environments and how they can enhance their capabilities to realize digital transformation and adapt to the development of the digital economy era.

Based on the windows of opportunity theory and strategic cognition theory, this paper conducts an empirical analysis of the questionnaire data of 268 enterprises and discusses the influence of external windows of opportunity and internal windows of opportunity on the digital transformation of enterprises, as well as the action mechanism of strategic cognition and entrepreneurship.

The results show that both the external windows of opportunity and the internal windows of opportunity have significant positive effects on the digital transformation of enterprises. Strategic cognition plays a partial mediating role in the external windows of opportunity and the internal windows of opportunity influencing the enterprise digital transformation process. Entrepreneurship plays a positive regulatory role in the process of external windows of opportunity and internal windows of opportunity influencing strategic cognition.

This paper deepens the relationship between internal and external windows of opportunity and enterprise digital transformation and contributes a new theoretical cognition. This paper integrates the strategic cognition theory to clarify the complex process mechanism of digital transformation using external situational opportunities and internal capabilities. This paper introduces entrepreneurship into the path mechanism of digital transformation and expands the characteristics of the study of digital transformation antecedents to the individual level within the enterprise.

This study aims to report the design, development and evaluation of a digital quality assurance application aimed at improving and ensuring the quality of assessment programmes in higher education.

The application was developed using a design-based research (DBR) methodology. The application’s design was informed by a literature search and needs assessment of quality assurance stakeholders to ensure compliance with daily practices and accreditation requirements. Stakeholders from three study programmes evaluated the application.

As part of the development of the application, module- and programme-level dashboards were created to provide an overview of the programme’s outcomes, assessment methods, assessment metrics, self-evaluated quality indicators and assessment documents. The application was evaluated by stakeholders at the module and programme levels. Overall, the results indicated that the dashboards aided them in gaining insight into the assessment programme and its alignment with underlying assessments.

Visualisation of the assessment programme’s structure and content identifies gaps and opportunities for improvement, which can be used to initiate a dialogue and further actions to improve assessment quality.

The application developed facilitates a cyclical and transparent assessment quality assurance procedure that is continuously available to various stakeholders in quality assurance.

A recommendation algorithm is typically applied to speculate on users’ preferences based on their behavioral characteristics. The purpose of this paper is to provide a systematic review of recommendation systems by collecting related journal articles from the last five years (i.e. from 2014 to 2018). This paper aims to study the correlations between recommendation technologies and e-learning systems.

The paper reviews the relevant articles using five assessment aspects. A coding scheme was put forward that includes the following: the metrics for the e-learning system, the evaluation metrics for the recommendation algorithms, the recommendation filtering technology, the phases of the recommendation process and the learning outcomes of the system.

The research indicates that most e-learning systems will adopt the adaptive mechanism as a primary metric, and accuracy is a vital evaluation indicator for recommendation algorithms. In existing e-learning recommender systems, the most common recommendation filtering technology is hybrid filtering. The information collection phase is an important process recognized by most studies. Finally, the learning outcomes of the recommender system can be achieved through two key indicators: affections and correlations.

The recommendation technology works effectively in closing the gap between the information producer and the information consumer. This technology could help learners find the information they are interested in as well as send them a valuable message. The opportunities and challenges of the current study are discussed; the results of this study could provide a guideline for future research.

Clinical notes typically contain medical jargons and specialized words and phrases that are complicated and technical to most people, which is one of the most challenging obstacles in health information dissemination to consumers by healthcare providers. The authors aim to investigate how to leverage machine learning techniques to transform clinical notes of interest into understandable expressions.

The authors propose a natural language processing pipeline that is capable of extracting relevant information from long unstructured clinical notes and simplifying lexicons by replacing medical jargons and technical terms. Particularly, the authors develop an unsupervised keywords matching method to extract relevant information from clinical notes. To automatically evaluate completeness of the extracted information, the authors perform a multi-label classification task on the relevant texts. To simplify lexicons in the relevant text, the authors identify complex words using a sequence labeler and leverage transformer models to generate candidate words for substitution. The authors validate the proposed pipeline using 58,167 discharge summaries from critical care services.

The results show that the proposed pipeline can identify relevant information with high completeness and simplify complex expressions in clinical notes so that the converted notes have a high level of readability but a low degree of meaning change.

The proposed pipeline can help healthcare consumers well understand their medical information and therefore strengthen communications between healthcare providers and consumers for better care.

An innovative pipeline approach is developed to address the health literacy problem confronted by healthcare providers and consumers in the ongoing digital transformation process in the healthcare industry.

The purpose of this paper is to investigate the contribution of a project management approach to develop a tool to support the management of Brazilian stricto sensu graduate programs (SS-GP). The Adaptive approach was chosen by applying the Project Management Life Cycle (PMLC) method.

The study corresponds to the concept of applied research. The qualitative approach was used. The research strategy was the action research, where participants cooperate to understand their environment, identify problems and seek a solution, simultaneously producing and using the knowledge produced.

The results showed one possible way to apply a contingency project management approach to develop the tool. In addition, indicated that its application facilitated the project work, especially when finding a solution for the project’s development and when dealing with the changes inherent to the uncertainties about the problem.

The lack of more updated information and the limitation of time and resources led to the reduction of the environment scope and of the number of functionalities developed.

To contribute to the generation of knowledge and expertise to support the management of SS-GP in activities such as providing information to the CAPES evaluation system, academic production analysis, collaborative researcher network analysis and post-graduation program monitoring and evaluation.

To fill a gap pointed out by several studies, that it is not possible to automatically generate input lists to be processed by ScriptSucupira tool, based on filtered criteria, comprising the entire universe of the Brazilian SS-PG. The creators of ScriptSucupira also declared to ignore the existence of an artifact similar to that.

This paper purposed a multi-facet sentiment analysis system.

Hence, This paper uses multidomain resources to build a sentiment analysis system. The manual lexicon based features that are extracted from the resources are fed into a machine learning classifier to compare their performance afterward. The manual lexicon is replaced with a custom BOW to deal with its time consuming construction. To help the system run faster and make the model interpretable, this will be performed by employing different existing and custom approaches such as term occurrence, information gain, principal component analysis, semantic clustering, and POS tagging filters.

The proposed system featured by lexicon extraction automation and characteristics size optimization proved its efficiency when applied to multidomain and benchmark datasets by reaching 93.59% accuracy which makes it competitive to the state-of-the-art systems.

The construction of a custom BOW. Optimizing features based on existing and custom feature selection and clustering approaches.