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In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on subject searching.

The methodology is based on a semi-structured interview within which the participants are asked to conduct both a controlled search task and a free search task. The sample comprises eight PhD students in several humanities disciplines at Linnaeus University, a medium-sized Swedish university from 2020.

Most humanities PhD students in the study have received training in information searching, but it has been too basic. Most rely on web search engines like Google and Google Scholar for publications' search, and university's discovery system for known-item searching. As these systems do not rely on controlled vocabularies, the participants often struggle with too many retrieved documents that are not relevant. Most only rarely or never use disciplinary bibliographic databases. The controlled search task has shown some benefits of using controlled vocabularies in the disciplinary databases, but incomplete synonym or concept coverage as well as user unfriendly search interface present hindrances.

The paper illuminates an often-forgotten but pervasive challenge of subject searching, especially for humanities researchers. It demonstrates difficulties and shows how most PhD students have missed finding an important resource in their research. It calls for the need to reconsider training in information searching and the need to make use of controlled vocabularies implemented in various search systems with usable search and browse user interfaces.

In this paper, the authors suggest that Central Americans can use entrepreneurship to solve economic uncertainty in their home country and that entrepreneurship can contribute to reducing the number of undocumented migrants to the USA.

The authors first illustrate the context of Central American illegal migration to the USA from a transitional entrepreneurship perspective, the authors address the economic drivers of illegal migration from Central America, which results in marginalization in the USA. Second, the authors build a theoretical model that suggests that Central Americans can improve their entrepreneurial abilities through the entrepreneurial cognitive adjustment mechanism.

Central Americans at risk of illegally migrating to the USA have high entrepreneurial aptitudes. Entrepreneurship can help them avoid the economic uncertainty that drives Central Americans to illegally migrate to the USA and become part of a marginalized community of undocumented immigrants. This conceptual paper introduces an entrepreneurial cognitive adjustment mechanism as a tool for Central Americans to reshape their personalities and increase their entrepreneurial abilities in their home countries. In particular, entrepreneurial intentions reshape the personality characteristics of individuals (in terms of high agreeableness and openness to experiences, as well as low neuroticism) through the entrepreneurial cognitive adjustment mechanism, which consists of reflective action in sensemaking, cognitive frameworks in pattern recognition and coping in positive affect.

This paper studies Central Americans at risk of illegal migration using the lens of transitional entrepreneurship, which advances the understanding of the antecedents to marginalized immigrant communities in the USA and suggests a possible solution for this phenomenon. Besides, the authors build a cognitive mechanism to facilitate the transitional process starting from entrepreneurial intention to reshaping individuals' personality, which further opens individuals' minds to entrepreneurial opportunities. Since entrepreneurial intention applies the same way to all entrepreneurs, the authors' aim of constructing the entrepreneurial intention unfolding process will go beyond transitional entrepreneurship and contribute to intention-action knowledge generation (Donaldson et al., 2021). Moreover, the conceptual study contributes to public policy such that international and local agencies can better utilize resources and implement long-term solutions to the drivers of illegal migration from Central America to the USA.

This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.

VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.

The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.

The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.

The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.

Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.

This paper aims to clarify how organizations manage their participation in networks to share and jointly create knowledge but also risk unwanted knowledge spillovers at the same time. As formal governance, trust and observation are less applicable in informal networks, the authors need to understand how members address the need to protect knowledge by informal practices. The study aims to investigate how the application of knowledge protection practices affects knowledge sharing in networks. The insights are relevant for organizational and network management to control knowledge risks but harvest the benefits of network engagement.

The authors opted for an exploratory study based on 60 semi-structured interviews with members of 10 networks. In two rounds, network managers, representatives and members of the networks were interviewed. The second round of interviews was used to validate the intermediate findings. The data were complemented by documentary analysis, including network descriptions.

Through analyzing and building on the theory of psychological contracts, two informal practices of knowledge protection were found in networks of organizations: exclude crucial topics and share on selected topics and exclude details and share a selected level of detail. The authors explored how these two practices are enacted in networks of organizations with psychological contracts.

Counter to intuition that the protection of knowledge can be strengthened only at the expense of knowledge sharing and vice versa, networks benefitted from more focused and increased knowledge sharing while reducing the risk of losing competitive knowledge by performing these knowledge protection practices.

This paper discusses the effects of enabling conditions of project knowledge management in building volatile organizational memory. The theoretical rationale underlies a recursive relationship among enabling conditions of project knowledge management, organizational learning and memory.

This research employs a qualitative descriptive single case study approach to examine a mobile application development project undertaken by a major software company in Brazil. The analysis focuses on the project execution using an abductive analytical framework. The study data were collected through in-depth interviews and company documents.

Based on the research findings, the factors that facilitate behavior and strategy in managing project knowledge pose a challenge when it comes to fostering organizational learning. While both these factors play a role in organizational learning, the exchange of information from previous experience could be strengthened, and the feedback from the learning process could be improved. These shortcomings arise from emotional tensions that stem from power struggles within knowledge hierarchies.

Based on the research, it is recommended that project-structured organizations should prioritize an individual’s professional experience to promote organizational learning. Organizations with well-defined connections between their projects and strategies can better establish interconnections among knowledge creation, sharing and coding.

The primary contribution is to provide a comprehensive view that incorporates the conditions required to manage project knowledge, organizational learning and memory. The findings lead to four propositions that relate to volatile memory, intuitive knowledge, learning and knowledge encoding.

The maritime industry, a linchpin of global trade, has embarked on a transformative journey catalysed by the relentless advance of digitalisation. There is a discernible gap in the literature concerning the specific consequences of digitalisation within the maritime sector. This research aims to examine the current body of literature on the influence of digitalisation in human resource development (HRD) on the competitive advantage of organisations and its potential within the maritime industry.

This research paper conducts a comprehensive bibliometric analysis.

The findings of this research explore the literature landscape encompassing digitalisation in HRD, its influence on HR operations, learning and development, performance management, employee experience, and strategic alignment within maritime organisations.

This research provides valuable recommendations for maritime organisations and HRD practitioners seeking to leverage digitalisation to gain a competitive edge. Thus, the maritime industry can adopt digital HRD practices to streamline operations, improve performance, and align HR strategies with broader organisational goals.

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

Although scholars have been studying human resource management (HRM) and open innovation (OI), yet there is less attention to this relationship in the context of small-and medium-sized enterprises (SMEs). This paper aims to bring some insights about the human side of inbound open innovation (INOI) in SMEs. The goal is to better understand the role of organizational trust (OT) and developmental culture (DC) in the interactions between commitment-based HRM (C-HRM) and INOI.

The present study employs partial least squares-structural equation modeling to investigate the interrelationships among constructs, utilizing data gathered from a sample of 206 SMEs.

The study's empirical results indicate that the presence of OT serves as a complementary factor in mediating the relation between C-HRM and INOI. Furthermore, the analysis shows that there exists a moderating influence of DC in the relationship between C-HRM and INOI.

The role of HRM practices is important in developing OT and consequently foster INOI in SMEs. To achieve INOI, SMEs need a DC that induces C-HRM toward an OI approach.

This study adds to the understanding of the interactions between C-HRM practices and INOI in SMEs. The comprehension of the mediating function of OT and the moderating effect of DC serve to enhance the scholarly understanding of the human dimension of OI research.