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Innovating higher education teaching and learning is challenging due to structural, cultural, and resource-related reasons, and research indicates that university innovation benefits from a bottom-up approach as well as strategic alignment with university objectives. In this paper, we investigate such bottom-up innovation processes within higher education as supported by a specific tool: the University Innovation Canvas (UIC). Adapted from the Business Model Canvas and Lean Canvas, the UIC is designed to promote educational technology innovation and foster alignment of the innovation process with strategic objectives of the university: namely, sustainability and user orientation. An evaluation of the UIC based on interview and questionnaire data shows that its usage differs between innovation teams (on paper vs. digital, individual vs. collaborative, co-located vs. remotely, and synchronous vs. asynchronous). UIC usability is linked with these differences and with teams' experience in realizing innovations. Overall, the UIC is perceived to be useful by (particularly, less-experienced) innovation teams and is successful at supporting sustainable and user-oriented innovations, as 14/15 innovations are still in use after up to four years since completion. To maximize its potential, more effort needs to be devoted to improving understanding of the UIC and supporting different workflows of innovation teams in the future. [ABSTRACT FROM AUTHOR]

Numerous natural dyes were used to dye mediaeval Islamic paper from the tenth to the nineteenth century, using a variety of techniques. The objective of this research is to develop an analytical method using high performance liquid chromatography with diode array detection (HPLC–DAD) to identify natural dyes in forty historical Islamic paper manuscripts from two collections. In addition, novel information was obtained from original treatises containing recipes for dyeing paper and the chronological use of dyes in dyeing mediaeval Islamic paper between the tenth and seventeenth centuries. The results show that thirty-four of the forty manuscripts examined contained dyes. Six natural dyes were detected, including henna, madder, lac, safflower, turmeric, and weld. This is the first study aimed at developing a method for determining various natural dyes in Islamic paper from a wide historical and geographical range in the mediaeval time and to fill significant gaps in the technical and historical knowledge of papermaking. [ABSTRACT FROM AUTHOR]

Hypothesis Descriptions are a type of manuscript dedicated to the formal description of a hypothesis, as introduced in an accompanying editorial and an examplary Hypothesis Description for the Enemy Release Hypothesis that is used in invasion biology. This questionnaire provides a template for such a Hypothesis Description manuscript. The template's format was designed for simplicity to facilitate adoption, and it can be easily extended to capture additional information, e.g. instructions for falsification or generalization, taxonomic or geographic scope, etymology, or relevant information in other research fields or other languages. The template reflects the recommended structure for a Hypothesis Description manuscript in that each of its sections provides the title for a section in a Hypothesis Description manuscript and indicates whether that section is mandatory or optional. Four sections - Keywords (mandatory), Conflicts of interest (optional), Acknowledgments (optional) and References (mandatory) - are in this template filled in for the template itself but should otherwise be adjusted for the hypothesis at hand. Comments to guide authors who work on a Hypothesis Description manuscript are provided as well. [ABSTRACT FROM AUTHOR]

In the ever-evolving landscape of organisational optimisation, the integration of business process management (BPM) and knowledge management (KM) emerges as a critical challenge. Beyond the opportunity to expedite the improvement of the organisation's operations, this integration serves as a gateway to unlocking the full potential of organisational knowledge and digital transformation. With its comprehensive evaluation of the dimensions of research on BPM and KM, this article aims to unveil predominant topics and evolving trends within this intersection. By doing so, it seeks to catalyse meaningful advancements in organisational management practices, underscoring the relevance and importance of this topic to the audience. The authors conducted a rigorous research process. Using bibliographic analysis, they selected 359 publications from the Scopus database. They employed performance analysis and scientific mapping methods to extract meaningful insights facilitated by MS Excel and VOSviewer applications. Additionally, they conducted an in-depth analysis of 37 publications chosen through bibliographic coupling analysis. The findings highlight a significant gap in the scholarly discourse on BPM and KM, which is evident in the limited research outcomes and minimal influence on decision-making processes. This study reiterates the need for increased dedication to this research realm, particularly in areas identified in the future research agenda recommendations, to stimulate significant advancements in organisational management practices. This paper stands out from the up-to-date reviews by offering a unique contribution to the BPM and KM integration field. While these reviews often focus on specific niches within the broader domain, this study takes a holistic approach. It provides a comprehensive overview of the existing literature on integrating BPM and KM, delving into the quantity and quality of existing research. It also identifies emerging themes and potential directions for future scholarship, ensuring a robust understanding of the integrative landscape of BPM and KM. [ABSTRACT FROM AUTHOR]

This paper explores the artificial intelligence (AI) concept for complex engineering design processes in the shipping industry. It is driven by the computer technologies advancement for fast and concurrent tasks processing, machine learnability, and data-centric approach. While AI has been adopted in many industries, it is still lacking the structured approaches for practical implementation. This is especially on the generality of the methodologies and explaining AI to the non-technical members and their preparedness. Therefore, this work proposed a conceptual framework to systematically extract, represent and visualize the ship design knowledge, to develop and deploy the machine learning (ML) models, and to demonstrate the AI-based ship design processes. Comparisons to the generic ship design model were made and discussed to highlight the improvements observed. It is found that while the conventional algorithmic approach procedures were faster in terms of execution time, the stepwise empirical models were often limited by the dataset and the design assumptions with restricted estimation capabilities for solving the nonlinear ship design problems. The findings presented the impact in improving the existing processes and effectively reducing its cycle. Additionally, the approach emphasised on the validated ship design data thus its generalization for fast and wide adoptions at scales. [ABSTRACT FROM AUTHOR]

Purpose: "The purpose of this paper is to review the literature on service innovation during the past two decades and provide an analysis of sources of publication, citations and authorship using bibliometric analysis techniques (VOSviewer)." This paper aims to assesses the important trends, enhance the academic debate, identify research gaps and propose future directions and a research agenda. Design/methodology/approach: This paper examines 176 articles in English language published from 2002 to 2022 from the Scopus database by adopting the bibliometric technique using VOSviewer software. This paper analyzes the different levels and boundaries of service innovation using bibliometric analysis of "service innovation research" using VOSviewer software. The methodology analyzes the number of citations, co-citations, keywords, authors, journals and countries. Findings: The review of the past 20 years indicates a substantial growth in the number of good research publications on service innovation. The UK, the USA, Sweden and Australia dominate this research area with the most articles published to date under the subject area of "Business management." The review highlighted that most of the studies on service innovation focused on products, companies and processes in the services industry. The most critical factors behind service innovation failure are improper management and lack of knowledge. The citation analysis revealed various research implications and directions for the future. Research limitations/implications: This study focuses only on service innovation and excludes research on performance management and control. Thus, future studies may explore this area of research in future studies. Only research articles were analyzed; conference papers, reports, manuals and white papers from practice were excluded. Research implications indicate that future studies on service innovation would be essential for organizational excellence, not process excellence. Originality/value: This paper provides a comprehensive overview of the current status and essential trends of research on service innovation. This study identifies the research gaps and provides a clear research agenda for understanding the various elements of service innovation. [ABSTRACT FROM AUTHOR]

Vernacular architecture offers valuable technological and typological solutions rooted in knowledge systems that connect environmental, social, economic, and cultural contexts. This paper introduces the Heritage for People Platform, a collaborative digital tool developed under the VerSus+ project (Creative Europe Program), aimed at organising and disseminating vernacular architectural knowledge with a focus on sustainable practices that are both culturally and environmentally conscious. The platform builds upon lessons learned from similar projects, offering key improvements such as the adoption of a Case-Based Reasoning methodology, which organises examples by geographic location, materials, and intervention types. A structured classification system based on sustainability principles and strategies enables cross-disciplinary research and comparison. The design process was highly participatory, incorporating user feedback at every stage to ensure the platform is accessible to a wide range of users, including designers, scholars, craftspeople, and the general public. A cross-device, user-centered approach further broadens its accessibility. The platform provides a public, web-based geospatial repository where users can create, update, and explore a dynamic collection of artefacts, design models, people, and institutions from across the globe. This tool marks a significant advance in promoting and preserving both physical and intangible heritage, with strong educational and practical applications for sustainable architecture. The paper details the theoretical framework and real-world potential of the platform as a critical resource for promoting sustainability in the built environment. [ABSTRACT FROM AUTHOR]

This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model (IKM). The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge flow networks. The IKM model enhances the preferential attachment and growth observed in scale-free BA networks, while incorporating three adjustment parameters to simulate the selection of connection targets and the types of nodes involved in the network evolution process Using the PageRank algorithm to calculate the significance of nodes within the knowledge flow network. To compare its performance, the BA and DMS models are also employed for simulating the network. Pearson coefficient analysis is conducted on the simulated networks generated by the IKM, BA and DMS models, as well as on the actual network. The research findings demonstrate that the IKM model outperforms the BA and DMS models in replicating the institutional field knowledge flow network. It provides comprehensive insights into the evolution mechanism of knowledge flow networks in the scientific research realm. The model also exhibits potential applicability to other knowledge networks that involve knowledge organizations as node units. This study has some limitations. Firstly, it primarily focuses on the evolution of knowledge flow networks within the field of physics, neglecting other fields. Additionally, the analysis is based on a specific set of data, which may limit the generalizability of the findings. Future research could address these limitations by exploring knowledge flow networks in diverse fields and utilizing broader datasets. The proposed IKM model offers practical implications for the construction and analysis of knowledge flow networks within institutions. It provides a valuable tool for understanding and managing knowledge exchange between knowledge organizations. The model can aid in optimizing knowledge flow and enhancing collaboration within organizations. This research highlights the significance of meso-level studies in understanding knowledge organization and its impact on knowledge flow networks. The IKM model demonstrates its effectiveness in replicating institutional field knowledge flow networks and offers practical implications for knowledge management in institutions. Moreover, the model has the potential to be applied to other knowledge networks, which are formed by knowledge organizations as node units. [ABSTRACT FROM AUTHOR]

Background: As evidence related to the COVID-19 pandemic surged, databases, platforms, and repositories evolved with features and functions to assist users in promptly finding the most relevant evidence. In response, research synthesis teams adopted novel searching strategies to sift through the vast amount of evidence to synthesize and disseminate the most up-to-date evidence. This paper explores the key database features that facilitated systematic searching for rapid evidence synthesis during the COVID-19 pandemic to inform knowledge management infrastructure during future global health emergencies. Methods: This paper outlines the features and functions of previously existing and newly created evidence sources routinely searched as part of the NCCMT's Rapid Evidence Service methods, including databases, platforms, and repositories. Specific functions of each evidence source were assessed as they pertain to searching in the context of a public health emergency, including the topics of indexed citations, the level of evidence of indexed citations, and specific usability features of each evidence source. Results: Thirteen evidence sources were assessed, of which four were newly created and nine were either pre-existing or adapted from previously existing resources. Evidence sources varied in topics indexed, level of evidence indexed, and specific searching functions. Conclusion: This paper offers insights into which features enabled systematic searching for the completion of rapid reviews to inform decision makers within 5–10 days. These findings provide guidance for knowledge management strategies and evidence infrastructures during future public health emergencies. [ABSTRACT FROM AUTHOR]

The current work highlights the evolution in knowledge management for sustainable entrepreneurship research by analyzing the key trends and major concepts. Additionally, the knowledge structures of such research themes were analyzed and mapped. Moreover, this paper seeks to present a research agenda concerning the study subject. It employed an integrated bibliometric approach and systematic review of knowledge management and sustainable entrepreneurship research by conducting two main procedures, namely domain analysis (i.e., key trends and evolution) and knowledge structures analysis (i.e., intellectual, social, and conceptual structure). A total of 233 documents were obtained from Scopus and Web of Science datasets and analyzed using both R 4.1.2 and VOSviewer software. The findings demonstrated that the contributors (i.e., the authors, nations, journals, and institutions) produced a discernible evolution in the body of knowledge on the themes of knowledge management and sustainable business within the designated period. Furthermore, science mapping approaches deeply grasp the social, conceptual, and intellectual structures of such research themes. This current work is considered one of the first attempts to systematically review, analyze, and visualize the scientific productions on knowledge management and sustainable entrepreneurship. The findings of the current work also offer a solid understanding and insights into the potential directions for the research agenda in these disciplines. [ABSTRACT FROM AUTHOR]

Recently, frequent flood disasters in China have seriously threatened economic development and public safety. This paper addresses the need for a dynamic urban flood emergency knowledge management system in emergency management departments and the lack of systematic knowledge among emergency managers regarding urban flood control. A multimodal knowledge graph-based urban flood emergency knowledge management model was constructed to enhance the decision-making capabilities of emergency management departments, improve the efficiency of public emergency evacuation, and reduce losses from urban flood disasters by analyzing the shortcomings of the existing emergency management system. An intelligent and dynamic flood emergency knowledge management model was built. This paper integrates multimodal knowledge graph technology to establish a multimodal emergency knowledge management framework for urban flood control. It develops and simulates the proposed model's application scenarios for urban flood emergency evacuation using the Flocking algorithm on the NetLogo platform. Through simulation experiments, the practicality and effectiveness of the model in real flood disaster situations were examined, particularly in simulating crowd evacuation behavior. The study found that the model significantly improves the accuracy of information and decision-making speed during emergency responses and supports emergency management departments in conducting targeted and personalized emergency decisions. This research provides a scientific basis for emergency management departments to optimize their emergency response strategies to flood disasters and serves as a reference and example for the application of multimodal knowledge graph technology in emergency management. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to explore and describe how companies manage the level of standardisation of improvement practices in a multisite context. It seeks to explain the managerial strategies applied to change the standardisation level in manufacturing companies with multiple production sites worldwide. Design/methodology/approach: This paper reports from a case based on data collected through semistructured interviews, participant observations and company documents from a large multinational producing company and, specifically, from of the largest production sites in the company. The research design resembles a grounded theory approach by being reflexive and open to emerging themes. The standardisation strategy was analysed at a company that strived to increase the standardisation of problem-solving practices within about 20 production sites as part of their corporate lean programme. Findings: Several managerial tools were applied at the corporate level to increase the standardisation level of problem-solving practices, such as developing standards and a company-specific toolbox aligned with an in-house maturity model. In addition, deploying change leaders and global implementation targets enabled audits and progress. However, consequences at the production-site level became minor adaptations of standards, the design of training models as a “roll-out”, and a resource-demanding implementation process. Originality/value: This paper empirically demonstrates strategic tools that corporate management teams apply to influence the company’s standardisation level of practices. The study describes the purpose and consequences of the design of the toolbox, maturity model, training model, and implementation targets, which aims to simplify the complex task of managing standardisation in a corporate group. By applying a knowledge-based view, four processes (i.e. adaptation, integration, upskilling, and learning) were identified to improve the management strategies in multisite contexts. [ABSTRACT FROM AUTHOR]

In the current dynamic context companies are forced to explore all the necessary ways to determine new solutions of adaptation and innovation to the needs and requirements of the market. This paper seeks to delineate the connections and potential media effect existing between knowledge dynamics, customer knowledge management and open innovation offering new perspectives for organizations to develop open innovation processes. Subsequently, the paper interprets and explores these connections through a bibliometric analysis using VOSviewer and a critical interpretation of the semantic links between main concepts. This study fills a significant gap in the literature by exploring the link between these fundamental concepts, and introducing the concept of knowledge dynamics. It should be emphasized that the present study is limited to qualitative data analysis, which requires further exploration and validation of the empirical study through future quantitative investigations. [ABSTRACT FROM AUTHOR]

This paper explores the relationship between transactive memory systems (TMS) and organizational performance through a bibliometric analysis. The analysis examines publications in the Web of Science database from 1975 to 2023, focusing on those that connect TMS with knowledge and performance in an organizational context. The results reveal a growing interest in TMS research, particularly since 2010. The analysis identifies key concepts such as team performance, knowledge management, and intellectual capital. It highlights the increasing importance of managing intangible resources like knowledge in the digital age. The findings suggest a strong link between well-developed TMS and improved organizational performance. TMS facilitates knowledge sharing, expertise utilization, and team coordination, ultimately leading to better outcomes like innovation, efficiency, and creativity. The paper concludes that TMS represents a strategic management resource, especially for knowledge-intensive organizations. It emphasizes the need for further research to fully understand the potential of TMS in supporting such organizations. [ABSTRACT FROM AUTHOR]

Anantharaja, K.; Krishnan, P.; Menaga, M.; Abuthagir Iburahim, S.; Hemaprasanth, K.P.; Swain, S.K.; Rani, B.; Panigrahi, A., and Routray, P., 2024. Global trends of biofloc research in the aquaculture sector: A metadata scientometric analysis. Journal of Coastal Research, 40(1), 167–178. Charlotte (North Carolina), ISSN 0749-0208. Biofloc technology is a sustainable tool for aquaculture production. This study is the first of its kind to provide insights into the quantitative visualization of global biofloc research trends in the aquaculture sector for the last two decades based on metadata analysis. The metadata on biofloc research retrieved during the period 1999–2021 from Web of Science was analysed. The results indicate that Brazil is the most active contributor to biofloc research—followed by China, Mexico, the United States, and India—in terms of number of publications; however, Israel holds the highest average citations per paper. The most cited paper in biofloc research has been cited 513 times, and Avnimelech from Technion Israel institute of Technology is the author of the most cited paper (513 citations) in biofloc research. The most widely studied species are shrimp and tilapia, specifically Penaeus vannamei and Oreochromis niloticus. The journal Aquaculture published a maximum number of research papers on biofloc (153 papers), followed by Aquaculture Research (96 papers) and Aquaculture International (47 papers). The trend analysis revealed that the topics related to disease resistance, different carbon sources, and microbial community are emerging in recent times. This study highlights the trends in biofloc research for its further advancements to guide researchers and policymakers to expedite the adoption of robust aquaculture practices to promote inclusive and sustainable economic growth. [ABSTRACT FROM AUTHOR]

Green innovation is an important driver for the sustainable development of the real economy and the realization of a green transformation. Previous studies have paid less attention to the relationship between dividend payments and the persistence of green innovation and neglected the mechanism of knowledge management on the relationship between the two. Using Chinese listed non-financial companies from 2007 to 2022, this paper empirically investigates the effect and mechanism of dividend payment on corporate green innovation persistence based on two perspectives: principal–agent theory and incentive theory, using Tobit and negative binomial models. It was found that there is a non-linear inverted U-shaped relationship between dividend payments and the persistence of green innovation. Dividend payments influence the persistence of green innovation through agency costs and knowledge management capabilities. Both independent director networks and knowledge spillovers have a positive impact on the relationship between the two. Based on firms' characteristics, the inverted U-shaped relationship between dividend payment and green innovation persistence is found to be more significant for non-state-owned firms and high-tech firms. Depending on the shareholder type, the inverted U-shaped curve between dividend payments for shareholding managers and green innovation persistence is the steepest. This study enriches the relevant literature on green innovations. In addition, it provides companies with a reference for formulating appropriate dividend policies, improving knowledge management capabilities, and improving the persistence of green innovation at a firm level. [ABSTRACT FROM AUTHOR]

Ontologies are essential for the management and integration of heterogeneous datasets. This paper presents OntoBuilder, an advanced tool that leverages the structural capabilities of semantic labeled property graphs (SLPGs) in strict alignment with semantic web standards to create a sophisticated framework for data management. We detail OntoBuilder's architecture, core functionalities, and application scenarios, demonstrating its proficiency and adaptability in addressing complex ontological challenges. Our empirical assessment highlights OntoBuilder's strengths in enabling seamless visualization, automated ontology generation, and robust semantic integration, thereby significantly enhancing user workflows and data management capabilities. The performance of the linked data tools across multiple metrics further underscores the effectiveness of OntoBuilder. [ABSTRACT FROM AUTHOR]

Managing modern, web-based, distributed applications effectively is a complex task that requires coordinating several aspects, including understanding the relationships among their components, the way they interact, the available hardware, the quality of network connections, and the providers hosting them. A distributed application consists of multiple independent and autonomous components. Managing the application involves overseeing each individual component with a focus on global optimization rather than local optimization. Furthermore, each component may be hosted by different resource providers, each offering its own monitoring and control interfaces. This diversity adds complexity to the management process. Lastly, the implementation, load profile, and internal status of an application or any of its components can evolve over time. This evolution makes it challenging for a Quality of Service (QoS) manager to adapt to the dynamics of the application's performance. This aspect, in particular, can significantly affect the QoS manager's ability to manage the application, as the controlling strategies often rely on the analysis of historical behavior. In this paper, the authors propose an extension to a previously introduced QoS manager through the addition of two new modules: (i) an associative memory module and (ii) an event forecast module. Specifically, the associative memory module, functioning as a cache, is designed to accelerate inference times. The event forecast module, which relies on a Weibull Time-to-Event Recurrent Neural Network (WTTE-RNN), aims to provide a more comprehensive view of the system's current status and, more importantly, to mitigate the limitations posed by the finite number of decision classes in the classification algorithm. [ABSTRACT FROM AUTHOR]

Knowledge Management (KM) plays a pivotal role in contemporary businesses, facilitating the identification, management, and utilization of existing knowledge for organizational benefit. This article underscores the indispensability of effective KM processes in the insurance industry, which is undergoing profound digital transformation. Through a systematic review utilizing the PRISMA framework, we meta-analyzed 85 high-quality scientific papers sourced from prominent databases spanning 2008 to 2022. Our examination centers on the diverse implementation processes of KM worldwide, emphasizing the integration of information technologies to enhance data collection, analysis, processing, and distribution within insurance companies. The objective of this review is twofold: to devise efficient methods for implementing KM systems in the insurance sector and to delineate practical research directions in this domain. [ABSTRACT FROM AUTHOR]

This paper presents the topic review (TR), a novel semi-automatic framework designed to enhance the efficiency and accuracy of literature reviews. By leveraging the capabilities of large language models (LLMs), TR addresses the inefficiencies and error-proneness of traditional review methods, especially in rapidly evolving fields. The framework significantly improves literature review processes by integrating advanced text mining and machine learning techniques. Through a case study approach, TR offers a step-by-step methodology that begins with query generation and refinement, followed by semi-automated text mining to identify relevant articles. LLMs are then employed to extract and categorize key themes and concepts, facilitating an in-depth literature analysis. This approach demonstrates the transformative potential of natural language processing in literature reviews. With an average similarity of 69.56% between generated and indexed keywords, TR effectively manages the growing volume of scientific publications, providing researchers with robust strategies for complex text synthesis and advancing knowledge in various domains. An expert analysis highlights a positive Fleiss' Kappa score, underscoring the significance and interpretability of the results. [ABSTRACT FROM AUTHOR]

Following the knowledge-based and intellectual capital-based view of firms, where knowledge is at the center of corporate strategic management, this paper aims to examine the role of Green Intellectual Capital (GIC) in the environmental and financial dimensions of corporate performance. To do so, a methodological framework was developed to evaluate the progress of GIC and corporate environmental performance by utilizing information and data from sustainability reports. Also, the Return of Equity (ROE) indicator was used to assess corporate financial performance. The proposed methodology was applied in a sample of 80 firms to examine the mediator role of GIC in the relationship between financial and environmental performance. The findings show a positive relationship between GIC (as a result of Green Relational Capital (GRC) and Green Organizational Capital (GOC)) and financial performance (ROE), as well as a significant positive relationship between environmental performance and the components of Green Intellectual Capital. Finally, a nonlinear U-shaped relationship between environmental and financial performance is identified. [ABSTRACT FROM AUTHOR]

Early studies on sustainability establish social, economic, and environmental improvement as the ultimate goal worldwide. This is true for nations or companies with significant economic and technological resources that apply indicators, data, and methodologies to manage harmonious, sustainable development; however, little is known about the management, integration, and measurement of unified social, economic, and environmental dimensions to achieve sustainable actions for agriculture. Therefore, under a qualitative-quantitative approach combining the knowledge management paradigm, sustainability criteria, and the log-linear statistical test, this paper investigates actions for sustainability around planting–harvesting–first disposal of the coffee circuit based on the tacit-explicit traditional knowledge of 55 members of its productive ecosystem from Guerrero, Mexico. The results show a statistical integration between environmental, economic, and social data with 0.000 (p < 0.05); a partial association on its effects with 0.209, 0.068, and 0.000, respectively (p > 0.05); the creation of on-site banks, training and assistance, and a state network for exchanging experiences as the conjectural actions that can show effects with 0.002, while the remaining were over >0.05 (p > 0.05). Governments, organizations, and researchers could extrapolate the model for sustainable agriculture management in the coffee-growing regions and for other crops. [ABSTRACT FROM AUTHOR]

Introduction: Climate change and weather variability pose significant challenges to small-scale crop production systems, increasing the frequency and intensity of extreme weather events. In this context, data modeling becomes a crucial tool for risk management and promotes producer resilience during losses caused by adverse weather events, particularly within agricultural insurance. However, data modeling requires access to available data representing production system conditions and external risk factors. One of the main problems in the agricultural sector, especially in small-scale farming, is data scarcity, which acts as a barrier to effectively addressing these issues. Data scarcity limits understanding the local-level impacts of climate change and the design of adaptation or mitigation strategies to manage adverse events, directly impacting production system productivity. Integrating knowledge into data modeling is a proposed strategy to address the issue of data scarcity. However, despite different mechanisms for knowledge representation, a methodological framework to integrate knowledge into data modeling is lacking. Methods: This paper proposes developing a methodological framework (MF) to guide the characterization, extraction, representation, and integration of knowledge into data modeling, supporting the application of data solutions for small farmers. The development of the MF encompasses three phases. The first phase involves identifying the information underlying the MF. To achieve this, elements such as the type of knowledge managed in agriculture, data structure types, knowledge extraction methods, and knowledge representation methods were identified using the systematic review framework proposed by Kitchemhan, considering their limitations and the tools employed. In the second phase of MF construction, the gathered information was utilized to design the process modeling of the MF using the Business Process Model and Notation (BPMN). Finally, in the third phase of MF development, an evaluation was conducted using the expert weighting method. Results: As a result, it was possible to theoretically verify that the proposed MF facilitates the integration of knowledge into data models. The MF serves as a foundation for establishing adaptation and mitigation strategies against adverse events stemming from climate variability and change in small-scale production systems, especially under conditions of data scarcity. Discussion: The developed MF provides a structured approach to managing data scarcity in small-scale farming by effectively integrating knowledge into data modeling processes. This integration enhances the capacity to design and implement robust adaptation and mitigation strategies, thereby improving the resilience and productivity of small-scale crop production systems in the face of climate variability and change. Future research could focus on the practical application of this MF and its impact on small-scale farming practices, further validating its effectiveness and scalability. [ABSTRACT FROM AUTHOR]

By applying systematic literature review technique, this paper focuses on the existing research on materialistic values. Although materialistic values have widely been discussed in the literature, this stream of literature lacks in the context of work setting. To the best of our knowledge, reviews focusing on materialistic values haven't been conducted in the organizational context. Initial search returned a total of 1,191 articles, out of which 209 articles were thoroughly analyzed based on their relevance to the topic. After studying the antecedents, correlates and consequences of materialistic values within literature, the paper identifies three important theoretical and empirical gaps in the literature. Firstly, the literature on materialistic values is vaguely scattered and needs consolidation. Secondly, most of research on materialistic values is a-theoretical in nature. Thirdly, literature on materialistic values lacks within the organizational setting. To fill these gaps, this paper consolidates the literature into theoretical frameworks and proposes theoretical foundations for the future researchers. In addition, the paper points towards some fertile areas largely missing in existing literature. In the end, some managerial implications and limitations of the study are discussed. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore the impact of knowledge vulnerabilities on knowledge risks and to analyse their intricate connections within the knowledge management systems. It is a new topic in knowledge management which is requested by the accelerated process of digitalization and the exponential development of the AI programs. There is a lack of research in this area and efforts should be made to bridge the knowledge gap. The method we use is based on a critical analysis of knowledge vulnerabilities and knowledge risks within a generic organization and of designing tree-diagrams able to illustrate the connections between them, and the possible adverse consequences for the firm's performance. The method of treediagrams has been extensively used in risk analysis of the complex technological systems of airplanes and nuclear reactors. Also, it is used in the risk management applied to other domains like climate change and earthquakes. It is the first paper to investigate these phenomena and to conceptualize such kind of diagrams. [ABSTRACT FROM AUTHOR]

This paper presents a framework for implementing improvement science in a district or educational organization. Findings from interviews with 17 experienced educational improvers indicate critical elements for a school district to effectively support and build the capacity of individuals and teams situated at multiple levels in the district in organizing, implementing, and sustaining improvement science methods. Utilizing a systems-thinking approach, this study conceptualizes how to institutionalize improvement science across an educational organization. To institutionalize the use of improvement science, district leaders must center schools and integrate the work in existing structures, offer support, and create coaching, growth management, and knowledge management plans. [ABSTRACT FROM AUTHOR]

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Practical implications: 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. Originality/value: 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. [ABSTRACT FROM AUTHOR]

Purpose: Drawing on resource and capability theory, this study aimed to analyze the relationship between the dynamic capabilities (DC), the knowledge management (KM) process (KMP) and results in customers and people. More specifically, the study argues that the KM process mediates the relationship between DC and the results outlined above. In addition, a predictive analysis is carried out that demonstrates the relevance of the KM process in the model. Design/methodology/approach: The study sample is made up of 118 Spanish organizations that have some kind of recognition of excellence awarded by the European Foundation for Quality Management (EFQM). Partial least squares methodology is used to validate the research model, the hypothesis testing and the predictive analysis. Findings: The results show that organizations which leverage the DC through the KMP improve customer and people outcomes. Moreover, the predictive power is higher when the KMPmediates the relationship between the DC and the results. Originality/value: There is no consensus in the literature on the relationship between DC, KM and performance. Moreover, there are also not enough papers that study KM or DC through the dimensions that define these constructs or variables. Given this need, this work considers the KMP according to the stages of knowledge creation, storage, transfer and application. Similarly, DC is dimensioned in sensing, learning, integrating and coordinating capabilities. These, as reconfigurators of knowledge assets, influence the KMP. Accordingly, the empirical model connects these knowledge domains and analyses their link to outcomes. [ABSTRACT FROM AUTHOR]

By facilitating the capture, organization, and dissemination of knowledge within and beyond the institution, knowledge management (KM) in higher education institutions (HEIs) fuels innovation, enhances research impact, and strengthens collaboration, ultimately leading to the creation of new knowledge and its valuable exchange. However, there is still much to explore in terms of the enablers of knowledge creation, sharing, and transfer. Therefore, this paper aims to identify the enablers of effective KM in the Polytechnique University of Leiria, which serves as a benchmark for other higher education institutions due to its leadership role in RUN-EU, a consortium of European universities. To achieve this, a narrative analysis based on information from SCOPUS and the institute's website, focusing on innovation, research, and development strategies, is proposed. The findings suggest that for KM initiatives to be successful, they need to be strategically designed, culturally supported, technologically enabled, and integrated into existing workflows. [ABSTRACT FROM AUTHOR]

In response to the growing interest in innovation performance within dynamic business landscapes, this study aims to fill the gap in comprehensive review studies by examining the factors influencing sustainable innovation performance. Employing a Systematic Review approach, this study elucidates the contributions of prior research and identifies key factors impacting sustainable innovation performance. Various software tools such as Publish/Perish, VOSviewer, and bibliometrics are utilized for the Systematic Review analysis. The research conducted searches in the Scopus scientific database, spanning articles from 1998 to 2023. The findings highlight four predominant themes: knowledge management, research and development, product innovation, and product development. This synthesis of literature provides valuable insights into the complex dynamics shaping sustainable innovation performance within evolving business contexts, facilitating further exploration and understanding in this research domain. This paper's significance lies in its contribution to enhancing comprehension of the factors driving sustainable innovation performance, thereby aiding practitioners and scholars in navigating and leveraging innovation within contemporary business environments. It offers a foundation for the development of sustainable policies and practices in harnessing innovation to enhance business performance, addressing the ever-changing dynamics of the business environment effectively. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The current article delves into the concept of green knowledge management (GKM), aiming to elucidate the intricate web of intellectual connections within the literature already published on this subject. The significance and value of this pursuit lie in its endeavor to pinpoint the most pivotal works in the field and to elucidate the overarching research directions that have been pursued. Through this process, the ability to centralize and encapsulate the knowledge within the GKM domain is achieved. Employing bibliometric analysis tools, the apparently elusive or intangible body of the literature on GKM is given structure and form through the creation of bibliometric analysis maps, which are then scrutinized through the discerning eyes of the author. Consequently, this paper seamlessly integrates the benefits of systematic literature review methodologies with those of computer-aided software, thereby efficiently processing a substantial volume of data on GKM and transforming it into tangible representations of this specialized literary niche. Thus, this undertaking serves as an open invitation to the advancement of the GKM field, providing a solid foundational platform for further research endeavors. In essence, it serves as a stepping stone towards the development of a GKM encyclopedia, offering a comprehensive repository of knowledge and insights for scholars and practitioners alike. [ABSTRACT FROM AUTHOR]

Purpose: After the pandemic digital technologies have increasingly become the focus of companies' innovation management processes. This trend has led to a rapid expansion of the field, with a growing number of research papers on various facets of this topic being published in academic journals. However, the proliferation of literature in the field has complicated the ease with which practitioners and academics can stay up to date with the latest developments and build on recent findings in their respective work. In order to succeed within the field of digital innovation management a strong grasp of the newest trends is required to not fall behind competitors, and to be able to develop cutting edge research. To address this challenge, this paper aims to answer the research question: What are the most common themes in post-pandemic digital innovation management literature? Design/methodology/approach: To answer this question, this study conducted a systematic literature review of 148 academic papers published between 2020 and 2023. The identified trends were subsequently organized into a framework that provides a comprehensive understanding of the field. Findings: The identified trends can be classified as either catalysts or new opportunities. Catalysts are trends that companies can implement to make their digital innovation management more efficient. The four identified catalysts are: the use of artificial intelligence as a vital part of innovating, educating leaders and employees, incorporating digital knowledge management practices, and collaborating with innovation networks. The articles also point to three trends classified as new opportunities that digital innovation management can enable, such as more sustainable initiatives, better foreign aid, and a transition to platformization. Originality: This study summarizes the research direction of digital innovation management and synthesizes important key developments leading up to the year 2023, which researchers and practitioners should be aware of. [ABSTRACT FROM AUTHOR]

This paper presents the outcomes of the "Training for Sustainable Employment of Youth and Young Adults" project, originally developed with the assistance of a consortium of institutions in six countries. These countries comprised five EU member states, Portugal, Italy, Romania, the Czech Republic, and Spain, and an EU candidate, Turkey. The main objective of the project was to analyse the gap between the needs of employers and the skill sets of youth and young adults, in order to assess the training needs of young people to equip them to be sustainably employed. In addition, the project set out to create a course programme that contained targeted training to meet the identified training needs of both employers and young people. The data collection was performed using a focus group (n = 144) and an online survey aimed at a convenience sample of the target groups (n = 244) in the six participating countries. The data were analysed qualitatively and quantitatively. The findings indicated six main competencies to develop in training: flexibility, inclusivity, diversity, and wellbeing; innovation and knowledge management; mobilisation of human resources; international orientation; entrepreneurship; and presentation. In conclusion, this study illustrated the need for a course programme to be established, structured around the six categories that correspond to the main topics obtained through the consortium's research. Therefore, the main gain of the project study was the creation of a course programme, focused on improving young people's inclusion in the job market and meeting companies' needs for skilled employees. [ABSTRACT FROM AUTHOR]

Data releasing and sharing between several fields has became inevitable tendency in the context of big data. Unfortunately, this situation has clearly caused enormous exposure of sensitive and private information. Along with massive privacy breaches, privacy-preservation issues were brought into sharp focus and privacy concerns may prevent people from providing their personal data. To meet the requirements of privacy protection, such a problem has been extensively studied. However, privacy protection of sensitive information should not prevent data users from conducting valid analyses of the released data. We propose a novel algorithm in this paper, named Data Release under Adjustable Privacy-utility Equilibrium (DRAPE), to address this problem. We handle the privacy versus utility tradeoff in the data release problem by breaking sensitive associations among variables while maintaining the correlations of nonsensitive variables. Furthermore, we quantify the impact of the proposed privacy-preserving method in terms of correlation preservation and privacy level, and thereby develop an optimization model to fulfil data privacy and data utility constraints. The proposed approach is not only able to provide a better privacy levels control scheme for data publishers, but also provides personalized service for data requesters with different utility requirements. We conduct experiments on one simulated dataset and two real datasets, and the simulation results show that DRAPE efficiently achieves a guaranteed privacy level while simultaneously effectively preserving data utility. [ABSTRACT FROM AUTHOR]

The 21st century is an era of rapid development of high-tech industry. Through continuous collection and sharing of data, IoT technology connected by things has penetrated into every aspect of human life. Modern organizations find that they increasingly rely on knowledge and information sharing and interconnection to enhance their innovation and development capabilities. Therefore, this paper studies the strategic decision-making of knowledge sharing among employees on the IoT platform drawing on evolutionary game theory, this paper constructs a three-party game model composed of "organization-knowledge sharers-knowledge seekers" from the perspective of stakeholders, and discusses the strategic choice of organization and employee behavior under the dynamic decision mechanism and when the game reaches equilibrium and stability. Moreover, this paper uses MATLAB 2016a to simulate the model. The results show that under the premise of higher organizational rewards, synergistic benefits, high-shared extra income, knowledge-sharing preferences, incentive preferences of the organization, the system is easier to reach the ideal state. With the smaller cost of sharing and incentive, organization and employees are more willing to be motivators and sharers, while the incentive degree of organization should be controlled within a reasonable range. This paper can provide specific theoretical and practical guidance for the practice of organizational knowledge management. [ABSTRACT FROM AUTHOR]

This paper examines the quantitative relationship between knowledge management and technological innovation and their influence on sustainable development. Organizations have increasingly focused on knowledge management processes, recognizing their importance for maintaining competitiveness and sustainability. The purpose of our study was to shed light on the impact of knowledge management processes on a firm's sustainability and innovation. Specifically, we investigated the relationship between knowledge acquisition, knowledge storage, knowledge transfer, and knowledge application and their effects on product/service innovation, process innovation, radical innovation, and incremental innovation. Using data from 272 questionnaires completed by top managers from companies operating in Greece, we provide strong evidence of a positive relationship between knowledge acquisition, storage, and application on product innovation whereas knowledge acquisition, storage, and transfer have a statistically significant effect on process innovation. Furthermore, we found a strong positive relationship between knowledge transfer and radical innovation. Finally, all four knowledge management processes have a strong positive impact on incremental innovation. The strength of these statistically significant results is reinforced by the magnitude of the corresponding estimated coefficients. The robustness of our results was further confirmed through the estimation of a Structural Equation Model (SEM) with the application of the Partial Least Squares (PLS) technique. [ABSTRACT FROM AUTHOR]

Purpose: The COVID pandemic has prompted B2B and industrial marketing scholars to understand more about how external disruptions impact parties involved in B2B transactions. This paper aims to adopt an ecosystem perspective to conceptually classify the interactions between actors involved in B2B ecosystems. Design/methodology/approach: This conceptual paper presents a framework across multiple levels of ecosystem interactions (at micro, meso and macrolevels) to illustrate how value cocreation and knowledge flows (as mechanisms underlying B2B relationships) are related to firm performance. Findings: Based on this framework, this paper offers propositions and several research questions about the effects of disruptions and how they propagate among these essential business ecosystem elements. Originality/value: This conceptual framework underscores the vital role of relationships and interactions in shaping B2B ecosystems, especially during disruptive periods. With a greater understanding of how these interactions operate across levels (micro, meso and macro), scholars and practitioners may be better able to navigate disruptive periods. [ABSTRACT FROM AUTHOR]

Human–computer interaction, Artificial Intelligence, and the multilingualism of digital culture open up unexpected scenarios in the contemporary design of cultural spaces with the creation of artifacts in which the analogic and digital dimensions come together to enhance the experience. Sensors and devices track user movement in the real world and translate the inputs into commands through hand gestures, speech recognition, head movements, tangible interfaces, or a combination of these elements. Through theorical models, concepts and tools, the paper reports the evolution of "User Experience" applied to personalized enjoyment and use of cultural places. The functional-performance survey of tools and technologies for perception, narrative and augmented interaction revealed models that highlight the diversity and richness of tangible and intangible cultural heritage through new forms of interaction and knowledge transfer. In this direction, new technological tools make it possible to detect, track and evaluate the personalized user experience by processing or producing large amounts of data. Therefore, on one hand the paper explores the limitations dictated by data management and user privacy in using such systems and, on the other, it prefigures new scenarios for amplifying and personalizing the user experience. [ABSTRACT FROM AUTHOR]

Development challenges in the domain of superconducting magnets are concentrated on technical problems in the current literature. Organizational, domain-specific challenges are often seen as secondary but must be considered with new holistic development approaches like Model-Based Systems Engineering (MBSE) becoming more popular. This work quantifies the domain challenges and gives the foundation to derive success criteria for design support in the future. A systematic literature review has been conducted to identify the overall domain challenges, and extensive interviews in the CERN technology department have been carried out to identify the development challenges on a practical level. Problems in knowledge management have been identified as a major challenge in the development process and the general literature. The paper concludes by picking up the most important challenges from the interviews and literature and puts them into the context of the authors' knowledge of electrical magnet design. [ABSTRACT FROM AUTHOR]

The article focuses on the importance of knowledge management and the risks associated with knowledge within organizations, particularly in the context of public security. Topics include the development of a model for building awareness of knowledge risks, the classification of security knowledge threats, and findings from a survey of Czech and Polish respondents regarding their perceptions of knowledge benefits and risks.

In October 2021, the Secure Knowledge Management (SKM) Conference convened many of scholars and practitioners to discuss and share ideas about the use and development of AI for SKM and cybersecurity. Over the past half-decade, numerous federal funding agencies such as the National Science Foundation (NSF), National Academies of Science (NAS), and National Security and Technology Council (NSTC) have noted the significant role that Artificial Intelligence (AI)-enabled analytics techniques such as deep learning, machine learning, network science, generative models, reinforcement learning, text analytics, and other techniques could play for Secure Knowledge Management (SKM), and more broadly, cybersecurity. Papers in each theme had a component of AI that was based in one or more of the major themes of extant AI-enabled cybersecurity and SKM research summarized in the previous section. [Extracted from the article]

This paper lays out the conceptual groundwork for a long-term project examining ethical issues raised when addressing the value of knowledge to a knowledge economy. The project includes a series of papers on specific topics that interrelate to the subjects of knowledge, ethics and organizations. While some of the planned articles for the project will have a practical focus, others, such as this one, will be conceptual in nature. The following outlines selected key concepts for an ethics of knowledge and their relationship with cognate areas of inquiry and practice. [ABSTRACT FROM AUTHOR]

With 500+ papers and 20+ books spanning many scientific disciplines, Mark Burgin has left an indelible mark and legacy for future explorers of human thought and information technology professionals. In this paper, I discuss his contribution to the evolution of machine intelligence using his general theory of information (GTI) based on my discussions with him and various papers I co-authored during the past eight years. His construction of a new class of digital automata to overcome the barrier posed by the Church–Turing Thesis, and his contribution to super-symbolic computing with knowledge structures, cognizing oracles, and structural machines are leading to practical applications changing the future landscape of information systems. GTI provides a model for the operational knowledge of biological systems to build, operate, and manage life processes using 30+ trillion cells capable of replication and metabolism. The schema and associated operations derived from GTI are also used to model a digital genome specifying the operational knowledge of algorithms executing the software life processes with specific purposes using replication and metabolism. The result is a digital software system with a super-symbolic computing structure exhibiting autopoietic and cognitive behaviors that biological systems also exhibit. We discuss here one of these applications. [ABSTRACT FROM AUTHOR]

Lung neuroendocrine neoplasms (LNENs) are lesions originating from diffuse endocrine cells within the bronchial walls and lung parenchyma. In recent years, there have been significant advances in the diagnosis and therapy of these neoplasms. This paper reviews recent developments in these areas, focusing on the latest research and treatment strategies. In the context of diagnosis, new imaging technologies including high-resolution computed tomography (CT), high-resolution and positron emission tomography-computed tomography (PET-CT) imaging, are providing more precise information on tumor spread and evaluation of metabolic activity. Advances in the field of molecular biomarkers allow a more personalized approach to the diagnosis of LNENs. In the therapeutic area, new targeted drugs and immunotherapy are showing promise in the treatment of LNENs. The development of molecular therapies such as tyrosine kinase inhibitors and somatostatin analogs, is opening up new treatment perspectives, increasing the efficacy of therapy, and improving patient quality of life. The paper also focuses on important research directions and clinical advances in the diagnosis and therapy of LNENs, presenting the current state of knowledge about these rare tumors. The conclusions aim to provide a synthetic view of the latest developments in the field, encouraging further research and improving treatment strategies for LNENs. [ABSTRACT FROM AUTHOR]

Business simulation games have become popular in higher education and business environments. The paper aims to identify the primary research trends and topics of business simulation games research using a systematic and automated literature review with the motivation of research (learning driven and domain driven). Based on these findings, the future development of business simulation games research projected papers that research business simulation games were extracted from Scopus. Second, the research timeline, main publication venues and citation trends have been analysed. Third, the most frequent words, phrases, and topics were extracted using text mining. Results indicate that the research on business simulation games has stagnated, with the most cited papers published in the 2000s. There is a balance between learning-driven and domain driven-research, while technology-driven research is scarce, indicating that the technology used for business simulation games is mature. We project that the research on business simulation games needs to be directed in the area of new technologies that could improve communication with and among the users (virtual reality, augmented reality, simulation games) and technologies that could improve the reasoning and decision-making complexity in business simulation games (artificial intelligence). [ABSTRACT FROM AUTHOR]

Copyright of Raumforschung und Raumordnung is the property of Oekom Verlag GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There are growing concerns about making our work matter in society and organizations, narrowing the theory–practice gap by doing research that has impact. In this paper, we suggest that there is more at stake than the issue of relating theory to practice, that we need to consider how we generate knowledge and think about its relevance. We argue that at the heart of such an endeavor lie critical ontological and epistemological considerations: first, the need to rethink our self–Other relationships—the nature of the relationship between ourselves as scholars and community members; and second, the need to generate more situated and relational forms of knowing-from-within that address social and environmental issues. Drawing on the work of critical sociologist Michael Burawoy, we elaborate four approaches to generating knowledge within organization and management studies (OMS), arguing that a public organization and management studies approach offers one way of making our work matter, requiring us to move from being spectators of the world to becoming actively engaged with multiple Others in generating knowledge and action. We discuss both the challenges and opportunities of a public OMS, offering examples of how we can become more actively engaged. [ABSTRACT FROM AUTHOR]

This paper shows a systematic literature review using HistCiteTM in the context of factor market misallocation in China. Four key research streams are identified: government intervention; misallocation explanation; market distortion and regional factor distortion. Further, the paper identifies three emerging research streams: endogeneity; legislation relating to factors of production; and knowledge management. Factor markets misallocation has been a lasting problem since the market‐oriented reform implemented by the Chinese Government. The academic literature review mainly focuses on the misallocation under Chinese national situation. [ABSTRACT FROM AUTHOR]