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The purpose of this paper is to identify the leading topics and developmental trends of archival information resource research in China by visualizing the intellectual structure and evolution patterns of archival information resource research.

This study took China National Knowledge Infrastructure (CNKI) as the data source and extracted keywords from relevant articles in archival information resource research as the sample. First, the frequency and co-occurrence of keywords were calculated by using SCI2. Second, this study analyzed the co-word network indicators by using Pajek. Then, topic community detection was conducted by using a VOS viewer, as well as the visualization of intellectual structures. Next, this study developed a graphical mapping of the evolution of research topics over time by using Cortext.

The research topics of archival information resources in China were unbalanced but distinct. Researchers focus on the construction and utilization of archival information resource, which consist of five evident research directions. The phenomena of fusion and differentiation coexist in research topic evolution. There were both continuities of traditional research and innovations in emerging research. The archival information resource research tended to be systematized and extended, reflecting the vertical and horizontal extension of the research content.

Based on a large number of previous studies, this study adopted quantitative methods to reveal the intellectual structure and evolution patterns of archival information resource research in China, providing guidance for researchers and institutions to grasp research status and developmental trends.

The Spanish Flu 1918–1920 saw a high degree of excess mortality among young and healthy adults. The purpose of this paper is a further exploration of the hypothesis that high mortality risk during The Spanish Flu in Copenhagen was associated with early life exposure to The Russian Flu 1889–1892.

Based on 37,000 individual-level death records in a new unique database from The Copenhagen City Archives combined with approximate cohort-specific population totals interpolated from official censuses of population, the author compiles monthly time series on all-cause mortality rates 1916–1922 in Copenhagen by gender and one-year birth cohorts. The author then analyses birth cohort effects on mortality risk during The Spanish Flu using regression analysis.

The author finds support for hypotheses relating early life exposure to The Russian Flu to mortality risk during The Spanish Flu. Some indications of possible gender heterogeneity during the first wave of The Spanish Flu – not found in previous studies – should be a topic for future research based on data from other countries.

Due to lack of individual-level death records with exact dates of birth and death, previous studies on The Spanish Flu in Denmark and many other countries have relied on data with lower birth cohort resolutions than the one-year birth cohorts used in this study. The analysis in this paper illustrates how archival Big Data can be used to gain new insights in studies on historical pandemics.

This study aims to understand how Big Data foster a greater acceptance of performance management systems (PMS) discourses in health care.

This paper focusses on the case of head and neck cancer treatment and prevention and benefits from the analysis of archival sources and 19 interviews with physicians in the field. It uses the framework of the Middle Range theory (MRT) to understand whether, in the case of head and neck cancer, Big Data may favour the enactment of PMS discourses in health care, in turn benefiting from any improvement in PMS.

This study setting unveils the changing pathway known as reorientation through boundary management. Medical professionals internalized and even mobilized PMS discourses, showing the premises for evolutionary changes in the future, when the current limitations will be dealt with.

This paper offers new theoretical, practical and policymaking insights into how new technologies can foster positive PMS discourses among actors who usually resist them. This value also extends to different fields and contexts.

This paper aims to focus on a highly significant yet under-recognised concern: the huge growth in the volume of digital archival information and the implications of this shift for information professionals.

Though data loss and format obsolescence are often considered to be the major threats to digital records, the problem of scale remains under-acknowledged. This paper discusses this issue, and the challenges it brings using a case study of a set of Second World War service records.

TNA’s research has shown that it is possible to digitise large volumes of records to replace paper originals using rigorous procedures. Consequent benefits included being able to link across large data sets so that further records could be released.

The authors will discuss whether the technical capability, plus space and cost savings will result in increased pressure to retain, and what this means in creating a feedback-loop of volume.

The work also has implications in terms of new definitions of the “original” archival record. There has been much debate on challenges to the definition of the archival record in the shift from paper to born-digital. The authors will discuss where this leaves the digitised “original” record.

Large volumes of digitised and born-digital records are starting to arrive in records and archive stores, and the implications for retention are far wider than simply digital preservation. By sharing novel research into the practical implications of large-scale data retention, this paper showcases potential issues and some approaches to their management.

The aim of this study is to provide a conceptual framework to explain how museums sustain intellectual capital and promote value co-creation moving from designing virtual environments to introducing and managing Big Data.

This study is based on archival and qualitative data considering the literature related to the introduction of virtual environments and Big Data within museums.

Museums contribute to sustaining intellectual capital and in promoting value co-creation developing a Big Data-driven strategy and innovation.

By introducing and managing Big Data, museums contribute to creating a community by improving knowledge within cultural ecosystems while strengthening the users as active participants and the museum’s professionals as user-centred mediators.

As audience-driven and knowledge-oriented organisations moving from designing virtual environments to following a Big data-driven strategy, museums should select organisational and strategic choices for driving change.

The purpose of this article is to examine the ways in which self-tracking data have meaning and value in and after the life of the creator, including how such data could become part of the larger historical record, curated in an institutional archive. In doing so, the article expands upon existing shared interests among researchers working in the areas of self-tracking, human–computer interaction and archival science.

A total of 18 people who had self-tracked for six months or more were recruited for the study. Participants completed a survey which gathered demographic data and characteristics vis-à-vis their self-tracking behavior. In-person semi-structured interviews were then conducted to ascertain the beliefs of the participants regarding the long-term use and value of personal quantified-self data.

The findings reveal the value that people place on self-tracking data, their thoughts on proper modes for accessing their archive once it moves from the private to the public space, and how to provide fidelity within the system such that their experiences are represented while also enabling meaning making on the part of subsequent users of the archive.

Today’s quantified-self data are generally embedded in systems that create a pipeline from the individual source to that of the corporate warehouse, bent on absorbing and extracting insight from a totality of big data. This article posits that new opportunities for knowing and for design can be revealed when a public interest rationale is appended to rich personalized collections of small data.

Archival research is a much under-rated and under-utilized method of research in management studies. Yet multi-disciplinary undertakings being observed in recent times, such as in knowledge management (KM) systems, business history and social network studies, among others, indicate that there is a lot of potential to be explored. The purpose of this paper is to highlight this point and make a case for its inclusion in the researcher’s toolkit in the future.

The authors follow a two-stage method here: the first stage being an improvised process to benchmark articles for this review; while the second stage involves content analysis and synthesis of the same.

The authors have dealt with the intricacies of the archival research methodology by minutely examining the fieldwork steps, proxies generation, other related processes of triangulation, etc. With the discussion on “multi-disciplinary undertakings,” the authors offer not only a selective bibliography of works that have effectively harvested this family of methods, but also critique the nuances involved. Finally, coming into more contemporary concerns and developments, the authors undertake an in-depth look at technological applications in the domain of KM, in case study mode. Methodological richness leads to substantive granularity. As such, the authors argue that archival methods contribute to the robustness, contextuality and holism of any research endeavor, more so in the study of business and organizations.

This paper is based on the literature review.

This paper makes a case for archival method’s contribution toward the robustness, contextuality and holism of any research endeavor, more so in the study of business and organizations.

This paper re-positions the method of archival research as a viable and sophisticated tool for researchers to employ effectively in singular or mixed method studies.

The advances and continuous development of technology have been identified as significant influences on the accounting profession (AICPA, 1998). In the last twenty years, both academia and the accounting profession have been giving much attention to the demand and opportunity for audits to be performed automatically, continuously and in nearly real time. This paper presents a comprehensive review of continuous auditing research by providing an overview of the emergence and growth of the continuous auditing literature and classifying the extant continuous auditing research on the basis of four research characteristics indicated by a newly developed research taxonomy.

This study aims to explore the implementation of artificial intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It contributes to the extant literature with a fresh perspective, expanding the discussion on AI adoption by investigating how it influences the perceptions of digital archival expertise.

In this study a two-phase data collection consisting of four online focus groups was held to gather the opinions of international archives and digital preservation professionals (n = 16), that participated on a volunteer basis. The qualitative analysis of the transcripts was performed using template analysis, a style of thematic analysis.

Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.

The volunteer basis of this study meant that the sample was not representative or generalisable.

Although the results of this research are not generalisable, they shed light on the challenges prospected by the implementation of AI in the archives and for the digital curation professionals dealing with this change. The evolution of the characterisation of digital archival expertise is a topic reserved for future research.