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The purpose of this paper is to review existing smart manufacturing (SM) maturity models' dimensions and maturity levels to assess their applicability and drawbacks. There are many maturity models available but many of them have not been validated or do not provide a useful guide or tool for applications. This gap creates the need for a review of the existing maturity model's applicability.

Nineteen peer-reviewed maturity models related to “Digital Transformation,” “Industry 4.0” or “Smart Manufacturing” were selected based on a systematic literature review and five consulting firm models were selected based on the author's industry knowledge. The chosen models were analyzed to determine 10 categories of dimensions. Then they are assessed on a 1–5 scale for how applicable they are in the 10 categories of dimensions.

The five “consulting firm” models have a first-mover advantage, are more widely used in industry and are more applicable, but some require payment, and they lack published details and validation. The 19 “peer reviewed” models are not as widely used, lack awareness in the industry and are not as easy to apply because of no web tool for self-assessment, but they are improving. The categories defined to characterize the models and facilitate comparisons for users include “Information Technology (IT) and Cyber-Physical System (CPS) and Data,” “Strategy and Organization,” “Supply Chain and Logistics,” “Products and Services,” “Culture and Employees,” “Technology and Capabilities,” “Customer and Market,” “Cybersecurity and Risk,” “Leadership and Management” and “Governance and Compliance.” The analyzed maturity models were particularly weak in the areas of cybersecurity, leadership and governance.

Researchers and practitioners can use this review with consideration of their specific needs to determine if a maturity model is applicable or if a new model needs to be developed. The review can also aid in the development of maturity models through the discussion of each of the dimension categories.

Compared to existing reviews of SM maturity models, this research determines comprehensive dimension categories and focuses on applicability and drawbacks.

In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects.

This study’s analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians’ theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures’ suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness.

This study’s results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity.

The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study’s results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.

This paper aims to present recently published resources on library instruction and information literacy. It provides an introductory overview and a selected annotated bibliography of publications organized thematically and detailing, study populations, results and research contexts. The selected bibliography is useful to efficiently keep up with trends in library instruction for academic library practitioners, library science students and those wishing to learn about information literacy in other contexts.

This article annotates 340 English-language periodical articles, dissertations, theses and reports on library instruction and information literacy published in 2022. The sources were selected from the EBSCO platform for Library, Information Science and Technology Abstracts (LISTA), Education Resources Information Center (ERIC), Elsevier SCOPUS and ProQuest Dissertations and Theses. Sources selected were published in 2022 and included the terms “information literacy,” “library instruction,” or “information fluency” in the title, subject terms, or author supplied keywords. The sources were organized in Zotero. Annotations were made summarizing the source, focusing on the findings or implications. Each source was then thematically categorized and organized for academic librarians to be able to skim and use the annotated bibliography efficiently.

The paper provides a brief description of 340 sources from 144 unique publications, and highlights publications that contain unique or significant scholarly contributions. Further analysis of the sources and authorship are provided.

The information is primarily of use to academic librarians, researchers, and anyone interested as a quick and comprehensive reference to literature on library instruction and information literacy published within 2022.

Service providers on highly competitive online outsourcing platforms employ various signals to entice buyers to make online purchases. One such signal—the solution exemplars—attracts attention through depictions of exemplary prior work completed by the service providers. Unfortunately, it is not known the extent to which solution exemplar characteristics affect sales performance nor is it clear how such signals perform in the presence of complementary signals such as service provider expertise. This paper explores these issues.

Extending signaling theory, the authors develop a model to explore the effects of solution exemplar characteristics (i.e. exemplar quantity, exemplar diversity and exemplar popularity) on sales performance under the moderating impact of service provider expertise. The authors test the model using proprietary data from ZBJ.com, a leading online outsourcing platform in China.

Exemplar quantity and exemplar popularity positively affect sales performance; exemplar diversity has no significant impact on sales performance and service provider expertise positively moderates the relationships between exemplar quantity, exemplar popularity and sales performance.

This work makes several significant contributions. First, the authors enrich the research on signals in online outsourcing by exploring the impact of solution exemplar characteristics on sales performance. Second, the authors analyze three solution exemplar characteristics: exemplar quantity, exemplar diversity and exemplar popularity. Third, this work shows that service provider expertise moderates the relationship between solution exemplar characteristics and sales performance. Important practical implications for both online outsourcing platforms and service providers are discussed.

Negative customer-to-customer interactions (NCCI) occurring in physical service encounters can have a detrimental effect on a focal customer’s experience. This paper aims to explore how the interplay between the physical servicescape and the presence and behavior of other customers can lead to NCCI. Moreover, through an examination of customers’ responsibility attribution, the paper underlines the need for service organizations to manage this interplay.

The authors rely on a mixed approach with two studies grounded in the Stimulus–Organism–Response paradigm. In a preliminary quantitative study, the authors test a model of the effects of NCCI on customers’ attribution and behavioral outcomes using partial least squares structural equation modeling. Next, in a qualitative study, they collect and explore NCCI incidents in eight service industries relying on the critical incident technique (CIT).

When experiencing NCCI, customers attribute at least partial responsibility for their negative experience to the service provider. The findings of the CIT study reveal three interplay mechanisms leading to NCCI: when other customers’ behavior is triggered by the physical servicescape; when other customers’ behavior is incongruent with the behavioral norms set by the physical servicescape; and when the physical servicescape is altered by other customers’ misbehavior.

This paper provides a comprehensive, empirically grounded, understanding of the interplay between the physical and social servicescape, focusing on the presence and behavior of the other customers and its effect on the customer experience.

Theoretically, the quality of representation is likely to be enhanced when more societal segments are included in formal political structures. An interesting question, however, is whether a similar correlation holds empirically outside established Western democracies. In the 2015 Egyptian parliament, women representation achieved an all-time high of 14.9% of total seats – nearly four times the historical Egyptian average. It is asked whether female legislators riding this unprecedent tide were different from their male colleagues in terms of their socio-economic backgrounds. But more importantly, the authors examine whether this increased representation led to any change in inclusion of more women’s issues in the legislative agenda, and how traditional topics are debated.

The authors conducted a content analysis of selected parliamentary scripts – generating on an original data set – to trace the topics and interventions raised by female MPs. The authors draw on the extensive literature on women’s representation, giving special attention to the structure versus agency dichotomy in this quest.

The authors conclude that female MPs were as active in parliamentary debates as to their male colleagues. Moreover, women did stress women issues more than men. The results indicate that the inclusion of traditionally under-represented groups does affect parliamentary agendas.

The authors conducted a content analysis of selected parliamentary scripts – generating on an original data set – to trace the topics and interventions raised by female MPs based on a case study of the 2015 Egyptian parliament.

The purpose of this short reflection is to allow for an informed use of both phenomenography and phenomenology in information studies and cognate fields.

The paper apprises uses of phenomenography found particularly in accounts of information literacy commonly describing phenomenography as distinct from phenomenology.

Both phenomenography and phenomenology continue to hold much credence in methods applied across scores of academic fields, with information studies being among those in the vanguard. Claims displaying differences of phenomenography from phenomenology are misleading and incomplete descriptions of phenomenology.

The paper presents newer materials on the origins of phenomenography and phenomenology to advocate for tighter relationships between and clearer applications of these methods in information studies and beyond.