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Background: This article presents a methodology to categorize scientific publications according to the targets of the 17 Sustainable Development Goals (SDGs) of the United Nations. For the above, a dataset with bibliographic and descriptive attributes of 2,379 articles from 2017 by co-authors affiliated to the Pontificia Universidad Católica de Chile, indexed in the Web of Science and Scopus databases, was used.

Methods: The methodology considered three relevant and consecutive milestones: establishment of the reading level that was applied for each publication record, which considers a proportional amount of information; assignment of one of the 18 categories identified for the analysis of the information, which include the 17 SDGs and the option “unclassified” and one of the 169 subcategories corresponding to the specific goals; and, finally, recording the status of the review process carried out, which allowed control of the progress and quality of the cross-review.

Results: The results show that 58.6% of the articles contribute to a primary target, of these 233 contribute to a secondary target; goals 3, 4, 9, and 11 are the most frequent in the process of assigning SDGs. There is an 81% increase in the use of alphanumeric targets when they are assigned as secondary targets. At the same time, cross-checking is shown to be beneficial when allowing the reclassification of 190 articles to some of the targets. Finally, it is established that levels 2 and 3 enabled better classification, given that the contents considered provide more information; however, it is significant that through level 1, 355 articles were categorized as “unclassified”.

Conclusions: It is concluded that the methodology allows for a conclusive, exhaustive, rigorous, extensive, and varied classification through the different milestones and actions carried out, providing strategic information for decision making and research management in the academy-society relationship.

This paper aims to identify and analyze the agtech classification and categorization systems in the Brazilian context.

The systematic literature review (SLR) was carried out according to the protocol of Kitchenham and Charters (2007). The classification systems found in literature were evaluated using the thinking aloud protocol, as proposed by Ericsson and Simon (1993). The responses obtained were evaluated through lexicographic analysis, described by Bécue-Bertaut (2019) and content analysis, described by Bardin (2011).

SLR identified four agtech classification systems. The model proposed by Dias, Jardim, and Sakuda (2019) was the one with the highest adherence to classify Brazilian agtechs. From the analysis of the systems found in literature, the authors proposed a new categorization model of agricultural startups (agtechs).

The study has limitations in relation to the theoretical and empirical validation of the model proposed by the authors. This limitation can be the subject of subsequent research.

The SLR study considers the evolution of the classification systems of a new agribusiness reality, the agtechs. In addition, there is a practical contribution in proposing a new classification system that attempts to address some of the limitations found in previous studies.

Agtechs are startups focused on developing solutions for agriculture and have shown a significant increase in recent years. However, there are few studies focused on this type of company. Even rarer are the studies that seek to classify and categorize them. The present work opens the horizon for future studies focused on this new reality.

Deployment of knowledge management systems (KMSs) suffers from low adoption in organizational reality that is attributed to a lack of perceivable added value for people in actual work situations. Poor task/technology fit in the process of knowledge retrieval appears to be a major factor influencing this issue. Existing research indicates a lack of re-contextualizing stored information provided by KMSs in a particular situation. Existing research in the area of organizational memory information systems (OMISs) has thoroughly examined and widely discussed the topic of re-contextualization. The purpose of this paper, thus, is to examine how KMS design can benefit from OMIS research on approaches for re-contextualization in knowledge retrieval.

This paper examines OMIS literature and inductively derives a categorization scheme for KMS according to their strategy of re-contextualizing knowledge. The authors have validated the scheme validated in a multiple case study that examines the differentiatory value of the scheme for approaches with various re-contextualization strategies.

The classification scheme allows a step-by-step selection of approaches for re-contextualization of information in KMS design and development derived from OMIS research. The case study has demonstrated the applicability of the developed scheme and shows that the differentiation criteria can be applied unambiguously.

Because of the chosen case study approach for validation, the validation results may lack generalizability.

The scheme enables an informed selection of KMSs appropriate for a particular OMIS use case, as the scheme’s attributes serve as design rationale for a certain architecture or constellation of components. Developers can not only select from various approaches when designing re-contextualizaton but also come up with rationales for each candidate because of structured representation. Hence, stakeholders can be supported in a more informed way and design KMSs more effectively along organizational change processes.

The paper addresses an identified need for systematic characterization of KMS approaches and systems intending to meet the objectives of OMISs. As such, it allows streamlining further research in this field, as approaches can be judged according to their originality and positioned relative to each other.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

Due to the young age of proptech, little is known about the dynamics of its expansion. In particular, there is limited agreement about a definition of “proptech,” while different categorizations are popping up. A severe lack of information emerges for the proptech scenario in Italy. The goal of this paper is to systematize multiple proptech maps in the attempt to create a framework for comparison of country-specific trends and an overarching definition of proptech. The research examines the evolutionary stage of the Italian digital real estate sector and compares it to the international context.

An in-depth analysis of 12 proptech maps at both national and international level was conducted based on online research. A list of Italian proptech companies was composed through multiple methods. A map was built for a cross-country comparison.

Each country or organization tends to develop its own categorization. This creates a multifaceted context where comparison and analysis are challenging. The Italian proptech sector seems underdeveloped compared to neighboring countries. Big room for improving the proptech business in this country still exists.

The results are valuable for proptech start-ups, business investors and well-established real estate actors to build on new entrepreneurial initiatives. The opportunity to advance proptech mapping and categorization emerges as a prospect for future research.

This research adds an overview of cross-country proptech categories and proposes the first analysis of Italian proptech. This will contribute to support entrepreneurial opportunities.

This study aims to systematically review the literature on the use of customer value for the evaluation of inter-organizational performance, with a wide perspective embracing different contexts and settings.

Searching within the Scopus and ISI Web of Science databases, a systematic literature review has been conducted analyzing 41 papers published between 1991 and 2020.

Categorization of customer value and inter-organizational performance measures were developed and the main differences among different settings were discussed.

The results presented in this study may be helpful for practitioners and managers who, in the completion of their activities, have to maintain strong and frequent relationships with other organizations. In fact, practitioners and managers interested in enhancing customer value and measuring inter-organizational performance may find an innovative perspective linking the two dimensions. They could find the categorizations presented in this study as a starting point for developing a performance evaluation framework suitable for evaluating their present business relationships. In fact, the categorizations provide a panorama of how scholars have measured until now inter-organizational performance through customer value, and therefore, they could choose the measures more appropriate for their situation.

No systematic literature review of the use of customer value for assessing inter-organizational performance has previously been undertaken, especially considering different settings.

This study aims to systematically review the existing literature and develop an understanding of work-life balance (WLB) and its relationship with other forms of work-related behavior and unearth research gaps to recommend future research possibilities and priorities.

The current study attempts to make a detailed survey of the research work done by the pioneers in the domain WLB and its related aspects. A total of 99 research work has been included in this systematic review. The research works have been classified based on the year of publication, geographical distribution, the methodology used and the sector. The various concepts and components that have made significant contributions, factors that influence WLB, importance and implications are discussed.

The paper points to the research gaps and scope for future research in the area of WLB.

The current study uncovered the research gaps regarding the systematic review and classifications based on demography, year of publication, the research method used and sector being studied.

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.