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In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.

In spite of the merits of artificial intelligence (AI) in marketing and social media, harm to consumers has prompted calls for AI auditing/certification. Understanding consumers’ approval of AI certification entities is vital for its effectiveness and companies’ choice of certification. This study aims to generate important insights into the consumer perspective of AI certifications and stimulate future research.

A literature and status-quo-driven search of the AI certification landscape identifies entities and related concepts. This study empirically explores consumer approval of the most discussed entities in four AI decision domains using an online experiment and outline a research agenda for AI certification in marketing/social media.

Trust in AI certification is complex. The empirical findings show that consumers seem to approve more of non-profit entities than for-profit entities, with the government approving the most.

The introduction of AI certification to marketing/social media contributes to work on consumer trust and AI acceptance and structures AI certification research from outside marketing to facilitate future research on AI certification for marketing/social media scholars.

For businesses, the authors provide a first insight into consumer preferences for AI-certifying entities, guiding the choice of which entity to use. For policymakers, this work guides their ongoing discussion on “who should certify AI” from a consumer perspective.

To the best of the authors’ knowledge, this work is the first to introduce the topic of AI certification to the marketing/social media literature, provide a novel guideline to scholars and offer the first set of empirical studies examining consumer approval of AI certifications.

This study was steered to establish how buyer–supplier collaboration's commitment attributes serve as an antecedent for procurement performance in large manufacturing entities in Tanzania.

A parallel, concurrent, mixed method was used in the study. Quantitatively, 52 firms were surveyed from Temeke Municipality, Tanzania, using questionnaire that specified 1 procurement manager and 1 store manager from those firms, totaling a sample size of 104 respondents. Qualitatively, expressive opinions to supplement the numeric data were gathered from supply chain managers using the saturation principle. Explanatory design analyzed the existing cause–effect relationship, and the null hypotheses were tested using binary logistic regression at p values < 0.05 and ExpB > 1.

Fidelity and enthusiasm to suggest improvements to suppliers and the duration of the collaboration antecede the procurement performance of the manufacturing firms in Tanzania, while devotion to invest resources and initiatives on joint problem solving have no significant impact.

The causality between buyer–supplier collaboration and procurement performance has been revealed. Since there might be third party logistics in collaborations, future research should center on their moderating effect.

A framework has been developed for liberating procurement performance in the context of large manufacturing firms in Tanzania.

Based on Transaction Cost Economics and Resource Dependency Theories, the study revealed the root cause of procurement performance in the context of Tanzanian manufacturing firms, while also considering commitment to buyer–supplier collaboration as a prerequisit for the commendable target.

This study aims to highlight the growth and development of Indo-German collaborative research over the past three decades. Moreover, this study encompasses an in-depth examination of funding acknowledgements to gain valuable insights into the financial support that underpins these collaborative endeavours. Together with this paper, the authors provide an openly accessible data set of Indo-German research papers for further and reproducible research activities (the “Indo-German Literature Dataset”).

The data were retrieved from the Web of Science (WoS) database from the year 1990 till the 30th of November 2022. A total of 36,999 records were retrieved against the used query. Acknowledged entities were extracted using a named entity recognition (NER) model specifically trained for this task. Interrelations between the extracted entities and scientific domains, lengths of acknowledgement texts, number of authors and affiliations, number of citations and gender of the first author, as well as collaboration patterns between Indian and German funders were examined.

The study reveals a consistent and increasing growth in the publication trend over the years. The study brings to light that Physics, Chemistry, Materials Science, Astronomy and Astrophysics and Engineering prominently dominate the Indo-German collaborative research. The USA, followed by England and France, are the most active collaborators in Indian and German research. Largely, research was funded by major German and Indian funding agencies, international corporations and German and American universities. Associations between the first author’s gender and acknowledged entity were observed. Additionally, relations between entity, entity type and scientific domain were discovered.

The study paves the way for enhanced collaboration, optimized resource utilization and societal advantages by offering a profound comprehension of the intricacies inherent in research partnerships between India and Germany. Implementation of the insights gleaned from this study holds the promise of cultivating a more resilient and influential collaborative research ecosystem between the two nations.

The study highlights a deeper understanding of the composition of the Indo-German collaborative research landscape of the past 30 years and its significance in advancing scientific knowledge and fostering international partnerships. Furthermore, the authors provide an open version of the original WoS data set. The Indo-German Literature Data set consists of 22,844 papers from OpenAlex and is available for related studies like literature studies and scientometrics.

The main issue in the mass customization of apparel products is how to efficiently produce products of various sizes. A parametric pattern-making system is one of the notable ways to rectify this issue, but there is a lack of information on the parametric design itself and its application to the apparel industry. This study compares and analyzes three types of parametric clothing pattern CAD (P-CAD) software currently in use to identify the characteristics of each, and suggest a basic guideline for efficient and adaptable P-CAD software in the apparel industry.

This study compared three different types of P-CAD software with different characteristics: SuperALPHA: PLUS(as known as YUKA), GRAFIS and Seamly2D. The authors analyzed the types and management methodologies of each software, according to the three essential components that refer to previous studies about parametric design systems: entities, constraints and parameters.

The results demonstrated the advantages and disadvantages of methodology in terms of three essential components of each software. Based on the results, the authors proposed five strategies for P-CAD development that can be applied to the mass customization of clothing.

This study is meaningful in that it consolidates and organizes information about P-CAD software that has previously been scattered. The framework used in this study has an academic value suggesting guidelines to analyze P-CAD systems.

In recent years, the frequency and severity of cybersecurity incidents have prompted customers to seek out specialized insurance products. However, this has also presented insurers with operational challenges and increased costs. The assessment of risks for health systems and cyber–physical systems (CPS) necessitates a heightened degree of attention. The significant values of potential damages and claims request a solid insurance system, part of cyber-resilience. This research paper focuses on the emerging cyber insurance market that is currently in the process of standardizing and improving its risk analysis concerning the potential insured entity.

The authors' approach involves a quantitative analysis utilizing a Likert-style questionnaire designed to survey cyber insurance professionals. The authors' aim is to identify the current methods used in gathering information from potential clients, as well as the manner in which this information is analyzed by the insurers. Additionally, the authors gather insights on potential improvements that could be made to this process.

The study the authors elaborated it has a particularly important cyber and risk components for insurance area, because it addresses a “niche” area not yet proper addressed in specialized literature – cyber insurance. Cyber risk management approaches are not uniform at the international level, nor at the insurer level. Also, not all insurers can perform solid assessments, especially since their companies should first prove that they are fully compliant with international cyber security standards.

This research has concentrated on analyzing the current practices in terms of gathering information about the insured entity before issuing the cyber insurance policy, level of details concerning the cyber security posture of the insured entity and way such information should be analyzed in a standardized and useful manner. The novelty of this research resides in the analysis performed as detailed above and the proposals in terms of information gathered, depth of analysis and standardization of approach made. Future work on the topic can focus on the standardization process for analyzing cyber risk for insurance clients, to improve the proposal based also on historical elements and trends in the market. Thus, future research can further refine the standardization process to analyze in more depth the way this can be implemented and included in relevant legislation at the EU level.

Proposed improvements include proposals in terms of the level of detail and the usefulness of an independent centralized approach for information gathering and analysis, especially given the re-insurance and brokerage activities. The authors also propose a common practical procedural approach in risk management, with the involvement of insurance companies and certification institutions of cyber security auditors.

The study investigates the information gathered by insurers from potential clients of cyber insurance and the way this is analyzed and updated for issuance of the insurance policy.

The tender documents, an essential data source for internet-based logistics tendering platforms, incorporate massive fine-grained data, ranging from information on tenderee, shipping location and shipping items. Automated information extraction in this area is, however, under-researched, making the extraction process a time- and effort-consuming one. For Chinese logistics tender entities, in particular, existing named entity recognition (NER) solutions are mostly unsuitable as they involve domain-specific terminologies and possess different semantic features.

To tackle this problem, a novel lattice long short-term memory (LSTM) model, combining a variant contextual feature representation and a conditional random field (CRF) layer, is proposed in this paper for identifying valuable entities from logistic tender documents. Instead of traditional word embedding, the proposed model uses the pretrained Bidirectional Encoder Representations from Transformers (BERT) model as input to augment the contextual feature representation. Subsequently, with the Lattice-LSTM model, the information of characters and words is effectively utilized to avoid error segmentation.

The proposed model is then verified by the Chinese logistic tender named entity corpus. Moreover, the results suggest that the proposed model excels in the logistics tender corpus over other mainstream NER models. The proposed model underpins the automatic extraction of logistics tender information, enabling logistic companies to perceive the ever-changing market trends and make far-sighted logistic decisions.

(1) A practical model for logistic tender NER is proposed in the manuscript. By employing and fine-tuning BERT into the downstream task with a small amount of data, the experiment results show that the model has a better performance than other existing models. This is the first study, to the best of the authors' knowledge, to extract named entities from Chinese logistic tender documents. (2) A real logistic tender corpus for practical use is constructed and a program of the model for online-processing real logistic tender documents is developed in this work. The authors believe that the model will facilitate logistic companies in converting unstructured documents to structured data and further perceive the ever-changing market trends to make far-sighted logistic decisions.

This study aims to focus on public policy concerning the implementation of public procurement policies in Nigeria and Ghana toward achieving value for money in the procurement of goods, services and works. It specifically analyzes some major administrative challenges Nigeria and Ghana are faced with in the administration/implementation of public procurement policies toward achieving value for money. It looks at the relationship between the state (regulatory authorities) and substate (procurement entities) in the public sectors of Nigeria and Ghana.

A comparative case study approach is adopted, where the two countries are compared in terms of achieving value for money. Data was collected from multiple sources, including in-depth interviews. The use of official documents and direct observations at the procurement regulatory authorities and entities’ premises.

This study found Nigeria often used the four Es – economy, efficiency, effectiveness and equity while Ghana mainly used the traditional five rights (right quantity, right quality, right price, right place and right time) as their criteria for ensuring value for money. The major administrative challenges found include corruption, low capacity of procurement personnel and poor knowledge of the procurement laws.

It recommends effective collaboration between government and civil society groups in the fight against corruption in procurement-related activities, with the implication that there is a need for periodic training for public procurement officials.

It adds to the field of public procurement in terms of value for money in the procurement of goods, services and works in developing countries context.

Ethiopia has enacted laws on transparency and disclosure of information in state-owned enterprises (SOEs). However, these laws are not strict enough, with the transparency and disclosure practices disappointing in the country. Thus, this study aims to investigate the legal framework governing transparency and disclosure in SOEs.

This study uses doctrinal, qualitative and comparative approaches. Domestic legal texts are appraised based on the organization for economic co-operation and development Guideline on Corporate Governance of State-owned Enterprises, the World Bank Toolkit on Corporate Governance of State-owned Enterprises and best national practices. This approach has been further corroborated by qualitative analysis of the basic principles of transparency and disclosure.

The finding reveals that the laws on transparency and disclosure do not comply with global practices and are inadequate to ensure transparency and discourse in SOEs. They fail to establish appropriate disclosure frameworks and practices at the SOE and state-ownership entity levels. They also indiscriminately subject enterprises to multiple auditing functions and conflicting responsibilities.

To the author’s knowledge, this study is the first legal literature on transparency and disclosure in Ethiopian SOEs. This study assists the state as owner in reforming the laws and uplifting SOEs from their current unpleasant condition. It can also become a reference for future research.

The purpose of this paper is to examine Robert Pagès' 1948 conception of “auto-document” as a possible forerunner to the neo-documentalist conception of “documentality” as offered in Bernd Frohmann’s 2012 article “The Documentality of Mme Briet’s Antelope.”

This paper is conceptual and historical.

Robert Pagès' concept of the “auto-document” in his 1948 article proposed an understanding of documents that depends on the “uniqueness” of a document. His article proposed a post-Otletian theory of documents similar to a discussion of documents by Bernd Frohmann in 2012 with the concept of “documentality.” Further attention to Pagès work and to Frohmann’s works could result in new understandings of Briet’s works, could illuminate other works and authors understood as belonging to neo-documentation and could yield new understandings of documents and information from the perspective of documentality as a new philosophy of information and documents.

Further attention to Pagès' work and to Frohmann’s works could yield new understandings of documents and the relation of documentary types across natural and sociocultural domains and bring renewed attention to documentality as a new philosophy of information and documents.

Attention to these issues could broaden the study of documents and documentation, increase the historical understanding of Suzanne Briet’s works and bring light to other works in neo-documentation, particularly in regard to the concept of documentality as a new philosophy of documentation and information.

Attention to these issues could broaden the study of documents and documentation to include more broadly animal and other natural entities and our relationships to them. The works cited also illuminate an empirical science understanding of documents, documentary evidence and information.

This is one of the first papers commenting on Robert Pagès’ works and brings renewed attention to Bernd Frohmann’s works, as well as to neo-documentation and its concept and philosophy of documentality, as a new philosophy of information and documents.