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The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

This paper aims to design a hybrid model of knowledge-based performance management system (KBPMS) for facilitating Lean Six-Sigma (L6s) application to increase contractor productivity without compromising human safety in Indonesian upstream oil field operations that manage ageing and life extension (ALE) facilities.

The research design applies a pragmatic paradigm by employing action research strategy with qualitative-quantitative methodology involving 385 of 1,533 workers. The KBPMS-L6s conceptual framework is developed and enriched with the Analytical Hierarchy Process (AHP) to prioritize fit-for-purpose Key Performance Indicators. The application of L6s with Human Performance Modes analysis is used to provide a statistical baseline approach for pre-assessment of the contractor’s organizational capabilities. A comprehensive literature review is given for the main pillars of the contextual framework.

The KBPMS-L6s concept has given an improved hierarchy for strategic and operational levels to achieve a performance benchmark to manage ALE facilities in Indonesian upstream oil field operations. To increase quality management practices in managing ALE facilities, the L6s application requires an assessment of the organizational capability of contractors and an analysis of Human Performance Modes (HPM) to identify levels of construction workers’ productivity based on human competency and safety awareness that have never been done in this field.

The action research will only focus on the contractors’ productivity and safety performances that are managed by infrastructure maintenance programs for managing integrity of ALE facilities in Indonesian upstream of oil field operations. Future research could go toward validating this approach in other sectors.

This paper discusses the implications of developing the hybrid KBPMS- L6s enriched with AHP methodology and the application of HPM analysis to achieve a 14% reduction in inefficient working time, a 28% reduction in supervision costs, a 15% reduction in schedule completion delays, and a 78% reduction in safety incident rates of Total Recordable Incident Rate (TRIR), Days Away Restricted or Job Transfer (DART) and Motor Vehicle Crash (MVC), as evidence of achieving fit-for-purpose KPIs with safer, better, faster, and at lower costs.

This paper does not discuss social implications

This paper successfully demonstrates a novel use of Knowledge-Based system with the integration AHP and HPM analysis to develop a hybrid KBPMS-L6s concept that successfully increases contractor productivity without compromising human safety performance while implementing ALE facility infrastructure maintenance program in upstream oil field operations.

Upon the realization of the need for guideline in cross-organizational data integration, in an exploratory manner, this study developed a public data governance framework, specifically, the governance for integrated public data (GIPD) framework and identified the influential factors of its successful implementation. This framework was then subjected to an analysis of a real data integration case in the South Korean public sector to test its efficacy.

To develop the GIPD framework, the authors conducted an extensive meta study, focus group interviews and the analytic hierarchy process involving field experts. Further, the authors performed topic modeling on documents from Korean research and development data integration projects, and compared the extracted factors to those of the GIPD to illustrate the latter's usefulness in a real case.

Legislation, policy goals and strategies, operation organization, decision-making council, financial support size and objective, system development and operation, data integration, data generation, system/data standardization and master data management were derived as the 10 important factors in implementing the GIPD framework. The illustrative case of Korea revealed that decision-making council, financial support size and objective, legislation, data generation and data integration were insufficient.

Although this study reveals important findings, it has a few limitations. First, the potential factors for data governance might vary depending on the attribute of the “interviewee” (such as their career or experience period) and the goal and area of GIPD framework building. Second, the inherent limitation of topic modeling in determining topics from groups of extracted keywords means that topics may be interpreted in various ways, depending on the perspective of the expert.

This study is highly significant in that it provides a starting point for discussions on the issue of data integration among public institutions. Therefore, although this study examined public data governance based on R&D data, it will contribute to providing a sufficient guideline for any type of inter-institutional data governance framework, what to discuss and how to discuss between institutions.

The findings are expected to provide a roadmap to formulate practical guidelines on inter-institutional data cooperation and a diagnostic matrix to improve the existing data governance system, especially in the public sector, from the existing practice of empirical analysis using a mixed methodology approach.

Recent archiving and curatorial practices took advantage of the advancement in digital technologies, creating immersive and interactive experiences to emphasize the plurality of memory materials, encourage personalized sense-making and extract, manage and share the ever-growing surrounding knowledge. Audiovisual (AV) content, with its growing importance and popularity, is less explored on that end than texts and images. This paper examines the trend of datafication in AV archives and answers the critical question, “What to extract from AV materials and why?”.

This study roots in a comprehensive state-of-the-art review of digital methods and curatorial practices in AV archives. The thinking model for mapping AV archive data to purposes is based on pre-existing models for understanding multimedia content and metadata standards.

The thinking model connects AV content descriptors (data perspective) and purposes (curatorial perspective) and provides a theoretical map of how information extracted from AV archives should be fused and embedded for memory institutions. The model is constructed by looking into the three broad dimensions of audiovisual content – archival, affective and aesthetic, social and historical.

This paper contributes uniquely to the intersection of computational archives, audiovisual content and public sense-making experiences. It provides updates and insights to work towards datafied AV archives and cope with the increasing needs in the sense-making end using AV archives.

Starting from the status quo, the paper outlines perspectives and challenges for the connection and interlinking of digitised and digital archival data. The following topics are addressed: Where are fields of action and what are the means of archives? Which functional and technical requirements are to be considered, and what is the role of portal infrastructures linking together various different institutions?

Considering needs of users and general framework conditions, the paper examines new approaches emerging in Germany. It outlines recent projects and considerations aiming to improve services and visibility of archives within the national data infrastructure in Germany.

Cross-connections are no new phenomenon, but change their appearance significantly in a digital context. In this respect, both smaller and bigger archives profit from participation in larger digital networks. Furthermore, archives need to keep in mind to reflect the quality of their digital (meta)data regularly and to offer or join systems that functionally and technically support cross-connection and interlinking of data.

The paper endeavours to show the importance of digital cross-connections and the role of portal infrastructures for visibility, online-distribution and use of digital archival metadata and data.

Firms are increasingly pressured to comply with mandatory supply chain transparency (SCT) regulations. Drawing on information processing theory (IPT), this study aims to show how blockchain technology can address information uncertainty and equivocality in assuring regulatory compliance in an interorganizational network (ION).

IPT is applied in a single case study of an ION in the mining industry that aimed to implement blockchain to address mandatory SCT regulations. The authors build on a rich proprietary data set consisting of interviews and substantial secondary material from actors along the supply chain.

The case shows that blockchain creates equality between actors, enables compliance and enhances efficiency in an ION, reducing information uncertainty and equivocality arising from conflict minerals regulation. The system promotes engagement and data sharing between parties while protecting commercial sensitive information. The lack of central authority prevents larger partners from taking control. The system provides mineral provenance and a regulation-compliant record. System cost analysis shows that the system is efficient as it is inexpensive relative to volumes and values of metals transacted. Issues were identified related to collecting richer human rights data for assurance and compliance with due diligence regulations.

The authors provide some of the first evidence in the operations and supply chain management literature of the specific architecture, costs and limitations of using blockchain for SCT. Using an IPT lens in an ION setting, the authors demonstrate how blockchain-based systems can address two key IPT challenges: environmental uncertainty and equivocality.

Prior literature has widely established that the design of storage locations impacts order picking task performance. The purpose of this study is to investigate the performance impact of unit loads, e.g. pallets or rolling cages, utilized by pickers to pack products after picking them from storage locations.

An empirical analysis of archival data on a manual order picking system for deep-freeze products was performed in cooperation with a German brick-and-mortar retailer. The dataset comprises N = 343,259 storage location visits from 17 order pickers. The analysis was also supported by the development and the results of a batch assignment model that takes unit load selection into account.

The analysis reveals that unit load selection affects order picking task performance. Standardized rolling cages can decrease processing time by up to 8.42% compared to standardized isolated rolling boxes used in cold retail supply chains. Potential cost savings originating from optimal batch assignment range from 1.03% to 39.29%, depending on batch characteristics.

This study contributes to the literature on factors impacting order picking task performance, considering the characteristics of unit loads where products are packed on after they have been picked from the storage locations. In addition, it provides potential task performance improvements in cold retail supply chains.

The PICCH research project contributes to opening a dialogue between cultural heritage archives and users. Hence, the users are identified and their information needs, the search strategies they apply and the search challenges they experience are uncovered.

A combination of questionnaires and interviews is used for collection of data. Questionnaire data were collected from users of three different audiovisual archives. Semi-structured interviews were conducted with two user groups: (1) scholars searching information for research projects and (2) archivists who perform their own scholarly work and search information on behalf of others.

The questionnaire results show that the archive users mainly have an academic background. Hence, scholars and archivists constitute the target group for in-depth interviews. The interviews reveal that their information needs are multi-faceted and match the information need typology by Ingwersen. The scholars mainly apply collection-specific search strategies but have in common primarily doing keyword searching, which they typically plan in advance. The archivists do less planning owing to their knowledge of the collections. All interviewees demonstrate domain knowledge, archival intelligence and artefactual literacy in their use and mastering of the archives. The search challenges they experience can be characterised as search system complexity challenges, material challenges and metadata challenges.

The paper provides a rare insight into the complexity of the search situation of cultural heritage archives, and the users’ multi-facetted information needs and hence contributes to the dialogue between the archives and the users.

This study evaluates how publicly available archival documents shaped online discussions about allegations that thousands of children were kidnapped during the 1950s in Israel, known as the Yemenite children’s affair. It examines if access to historical records leads to more informed and rational public discourse, especially on social media.

Using content analysis, this study examines Facebook posts from media outlets, politicians, NGOs and public groups between 2016 and 2021 to understand how the Israeli State Archives’ release of over 300,000 documents affected support of the kidnapping.

Despite extensive archival information debunking the kidnapping theory, public opinion and discourse largely continued to support it. This suggests a complex interaction between information availability, preexisting beliefs, echo chambers and group allegiances, suggesting that access to factual data alone may not effectively challenge established beliefs in online public settings.

Since data were collected only from Facebook, our conclusions cannot be generalized to other platforms. The study relies only on publicly accessible data and does not establish causality between exposure to information and shifts in opinion. Our findings show that disclosing archival information does not significantly benefit public political discourse on contentious topics but also point to the advantages of mediating information by politicians, NGOs and journalists.

As a unique case study, this research contributes to understanding the role of historical archives in digital-age public discourse. It highlights their potential and limitations in facilitating informed debate and deliberation, emphasizing the complexity of influencing established beliefs with factual data.

The purpose of this study is to identify the business strategies that entrepreneurs have formulated to establish the business with the intention of scaling up in the information technology (IT) sector in Chile, given that they have managed to scale up sustainably at an average annual rate of 73.3% and an average annual employee growth rate of 37% for four consecutive years after an establishment period of 25 months.

Three methodological steps were used to identify which strategic initiatives are relevant to the establishment of small- and medium-sized enterprises (SMEs) on the path to scaling up. The first part consisted of identifying the literature and defining the research propositions and research questions. The second part was to prepare, collect and analyse the data to conduct the research by applying, transcribing, reviewing and coding the sources of evidence to explore how SMEs are able to develop strategic initiatives for the start-up process. The final stage was to validate the research proposal to identify potential strategic initiatives identified during the multi-case study.

As a result of the data analysis and empirical findings, three deliberate strategic initiatives were identified: staying engaged with customers, delivering successful business solutions and articulating social capital. However, in crisis situations, entrepreneurs readjust their strategies based on their management skills and an emergent strategic initiative was identified as securing the financial structure and revolutionising change. While this research was not designed to identify personal attributes, it did highlight the importance of adaptation and learning as a skill to drive the business model for scaling up during the establishment of their business.

It is clear that the study focused on Chile and cannot be replicated in other regions or sectors due to the characteristics of the sample itself, but it provides empirical evidence that there are cycles prior to scale up that need to be understood. The findings were empirically validated during the establishment phase, but the deliberate and emergent strategic initiatives that consolidated the SME to prepare for its scale-up process are not evident in the theory.

The IT sector will continue to grow and change after the pandemic, and the global economy will use more digital systems, creating new ways of working with the use of IT. This context will impact on SMEs where strategies, whether deliberate or emergent, will need to be part of the new business models, and therefore, caution should be exercised when using the results of this study. Public and private institutions should educate and guide entrepreneurs for the potential scaling up of their SMEs without having to wait 42 months, according to Global Entrepreneurship Monitor 2021-2022 (Hill et al., 2022). Scaling up can begin as early as 25 months after establishment, breaking the paradigm of the theory that the SME must be established in a period of 3.5 years. This period cannot be generalised as business opportunities in the IT sector are faster. The research also contributes by reporting that contingency planning is relevant during the establishment phase.

Educational institutions and the public sector have made efforts to change business cultures regarding the importance of strengthening entrepreneurship, but teaching the emergent strategies that often challenge SME creation is not yet widespread in educational formats. This is a challenge not only for institutions but also for entrepreneurs trying to anticipate the constant changes in the global economy. This research provides an opportunity to create more dynamic business models with more conscious risk planning.

Although the literature has confirmed the findings, this research has provided a pre-scaling picture that links these two important stages on the axis of deliberate and emergent strategies. The findings confirm the importance of correctly embedding five strategic initiatives for the establishment of the SME if it is to continue on its journey towards business scale-up. However, there is a lack of empirical evidence in emerging economies on how entrepreneurs have found the right path to scale-up.