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The purpose of this paper is to outline a variety of related methods for helping with criminal (cold) case investigations. Despite the best efforts of police investigations, many cases around the world run out of leads and go cold. While many police departments around the world have developed specialist groups and task forces, academics have also been developing new methods that can assist with investigations.

Cold cases, by their very nature, typically comprise incomplete data sets that many traditional statistical methods are not suited to. Groups of researchers have therefore developed temporal, dynamic analysis methods to offer new insights into criminal investigations. These methods are combined into a timeline toolkit and are outlined in the current paper.

Methods from the timeline toolkit have already been successfully applied to many cold cases, turning them back into current cases. In this paper, two real-world cold cases are analysed with methods from the timeline toolkit to provide examples of how these methods can be applied in further cold cases.

Methods from the timeline toolkit provide a novel approach to investigating current and cold cases. This review provides academics and practitioners with a guide to begin using and developing these methods and forming successful collaborations with police departments and cold case task forces. The methods are also suitable for wider groups and to use in their investigations.

While behaviour sequence analysis (BSA) is popular, it is not without limitations, namely, the level of detail required and time taken to run analyses; therefore, this paper aims to outline a novel method, using 30 serial homicide cases as a worked example.

Temporal analysis methods are becoming increasingly popular in applied forensic and criminological research. In recent years, BSA has become a widely used approach.

Waypoint sequencing provides a streamlined version of the traditional BSA approach, allowing for fewer behaviours to be included and providing a clearer overview of the main behaviours of interest.

Waypoint sequencing is shown in the current paper through serial killer research to show how to conduct the analyses and how it is effective in current investigations by expediting the process and allowing quicker analysis to facilitate current investigations.

The current research provides a novel approach to sequence analysis that is more useful in applied settings as it requires fewer behaviours or events than traditional BSA.

The purpose of this paper is to introduce counterfactual analysis and reasoning to the study of accounting history. The counterfactual focus is the institutionalisation of public accountancy in the UK.

The study adopts a counterfactual research design using Ferguson and Bunzl and asks a “what if” question of an event of importance to accounting historians in order to create a plausible counterfactual outcome that is grounded in rationality and causal analysis. The specific counterfactual question relates to the royal charter granted to public accountants practicing in Edinburgh in 1854. The counterfactual outcome is compared to the actual timeline of public accountancy institutionalisation in the UK.

The “alternative” history reveals uncertainties that confronted public accountants in the past and provides a basis for suggesting that the current fractured and inefficient state of institutionalised public accountancy in the UK has its origins at least partially in the 1854 royal charter. It also suggests that attempts to register and unify public accountants in the UK have been hindered by nineteenth century royal charters.

The study argues that counterfactual analysis is a useful historical tool with which to understand the consequences of historical decisions made in the professional project of British public accountancy. In addition, the study reveals the potential for counterfactual analysis to illumine the consequences of decisions in other areas of accounting and auditing history.

This study is the first counterfactual analysis in the accounting history literature and therefore provides a template for further studies and improved research design.

This study aimed to examine the research hotspots and evolution paths in the field of health information behavior (HIB) in China and abroad, and conduct comparative analysis to better understand its development trajectory globally.

A keyword search of the relevant literature included in the China National Knowledge Infrastructure (CNKI) database and Web of Science (WoS) core collection database was conducted, using the visualized analysis tool CiteSpace V for bibliometric analyses.

The common research hotspots in China and abroad can be divided into related research on HIB, research on its influencing factors and health information research. Among these, health information-seeking behavior has been the focus of domestic and foreign scholars. From the subdivision perspective, the focus of Chinese and foreign research hotspots differs. In terms of evolutionary path, the initial stage of HIB research in China and abroad revolves around health information and health information-seeking behavior, followed by the influencing factors of HIB; however, the research breakthrough point is the reverse. Then, domestic and foreign research was conducted on different types of HIBs. Regarding the selection of research objects, Chinese and foreign research objects were increasingly diversified.

This study also has several limitations. First, the literature sample only selected the literature in the WoS and CNKI databases, and there may be many HIB-related works published in other databases. Therefore, future research should include other databases. Second, in terms of language, this study selected only Chinese and English literature, but in many countries, important research results on certain topics are usually published in native language, and future research should expand the language selection. Third, this study only conducted national and institutional collaboration network analysis, keyword co-occurrence analysis, cluster analysis and timeline chart analysis.

The implication of practice can be divided into the following three points. (1) Analyzing the domestic and foreign literature on HIB and identifying highly cooperative institutions and countries in the field of HIB can reveal the research situation of HIB and help researchers establish new research networks in the future. (2) Analyzing the research hotspots and evolutionary paths of HIB at home and abroad is helpful for quickly understanding the development context of this field and grasping the emerging research directions such as HIB of people in close contact with patients, health information exchange behavior, health information avoidance behavior and health information discontinuation behavior, which can help researchers to explore the future research direction in this field, so as to determine the topic and fill the research gap. (3) Combining the analysis of HIB-related research at home and abroad is helpful for professionals to understand the characteristics and rules of HIB of users, consumers and other groups to further optimize and improve health information services.

Comparing and summarizing the research status of HIB in China and globally, and presenting the findings visually, will help researchers better grasp the research overview and hotspot changes in this field, as well as provide a follow-up reference.

The purpose of this paper is to present a comprehensive analysis of the current status and development of the digital journalism field from 1987 to 2021 using the Dimensions database.

Using the Dimensions.ai database, 1734 articles were identified through search strategies which were published from 1987 to 2021. The downloaded results were analysed using specific parameters with the help of bibliometric and science mapping tools: Biblioshiny, VOSviewer and CiteSpace. The key contributions of the present comprehensive bibliometric study of the digital journalism field can be seen in terms of the following aspects: (1) Publication analysis from the perspectives of publication growth, key journals, contributing authors, institutions and countries done through Biblioshiny package. (2) Citation network analysis from the perspective of co-citation structure of papers, authors, countries and institutions done through VOSviewer. (3) Timeline analysis and keywords burst detection to identify hotspots and research trends in digital journalism with the help of CiteSpace.

The first paper with the keyword digital journalism was published in the year 1989. From 2011 onwards, there has been growth in digital journalism literature. The most popular journal in digital journalism studies is Digital Journalism, Journalism, Journalism Practice, Journalism Studies. Lewis, S.C. has contributed the most number of papers in digital journalism. Further, authors from the countries the USA, Spain, Brazil and UK have contributed immensely. The citation network of authors, institutions and countries contributing to digital journalism studies has also been explored in the study. Through burst analysis, hot topics in digital journalism were identified.

The paper provides a complete overview of the growth of digital journalism literature published from 1987 to 2021. The originality of this work lies in the triangulation of Biblioshiny, VOSviewer and CiteSpace software to present various aspects of bibliometric study. Findings of the study can help the researchers to identify areas as well as journals, authors, institutions working actively in the field of digital journalism.

Although the business model field of study has been a focus of attention for both researchers and practitioners within the past two decades, it still suffers from concern about its identity. Accordingly, this paper aims to clarify the intellectual structure of business model through identifying the research clusters and their sub-clusters, the prominent relations and the dominant research trends.

This paper uses some common text mining methods including co-word analysis, burst analysis, timeline analysis and topic modeling to analyze and mine the title, abstract and keywords of 14,081 research documents related to the domain of business model.

The results revealed that the business model field of study consists of three main research areas including electronic business model, business model innovation and sustainable business model, each of which has some sub-areas and has been more evident in some particular industries. Additionally, from the time perspective, research issues in the domain of sustainable development are considered as the hot and emerging topics in this field. In addition, the results confirmed that information technology has been one of the most important drivers, influencing the appearance of different study topics in the various periods.

The contribution of this study is to quantitatively uncover the dominant knowledge structure and prominent research trends in the business model field of study, considering a broad range of scholarly publications and using some promising and reliable text mining techniques.

This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.

This study used CiteSpace to conduct a bibliometric analysis of 1,213 tourism forecasting articles.

The results show that tourism forecasting research has experienced three stages. The institutional collaboration includes transnational collaboration and domestic institutional collaboration. Collaboration between countries still needs to be strengthened. The authors’ collaboration is mainly based on on-campus collaboration. Articles with high co-citation are primarily published in core tourism journals and other relevant publications. The research content mainly pertains to tourism demand, revenue management, hotel demand and tourist volumes. Ex ante forecasting during the COVID-19 pandemic has broadened existing tourism forecasting research. The future forecasting research focuses on the rational use of big data, improving the accuracy of models and enhancing the credibility of forecasting results.

This paper uses CiteSpace to analyze tourism forecasting articles to obtain future research trends, which supplements existing research and provides directions for future research.

本文旨在分析旅游预测领域的研究重点、演化过程和未来的研究方向。

本研究使用 CiteSpace 软件对 1213 篇旅游预测文章进行了文 献计量学分析。

结果表明, 旅游预测研究经历三个阶段。机构合作包含国际机构合作和 国内机构合作, 需要持续加强国家之间的合作, 作者之间的合作多以校内合作为 主。高引用文章不仅发表在旅游领域的核心期刊还发表在其他专业的核心期刊上。 旅游预测研究的主要内容为旅游需求、收入管理、酒店需求和游客量。新冠疫情 期间的事前预测拓宽了现有的旅游预测研究。未来预测的研究重点在于合理利用 大数据, 提高模型的准确定以及提高预测结果的可信度。

本文使用 CiteSpace 分析旅游预测文章得到未来研究趋势, 既是对 现有研究的补充, 又为今后的研究提供方向。

Este artículo pretende analizar los aspectos más destacados de la investigación, el proceso evolutivo y las futuras orientaciones de la investigación en el campo de la previsión turística.

Este estudio utilizó CiteSpace para realizar un análisis bibliométrico de 1213 artículos sobre previsión turística.

Los resultados muestran que la investigación sobre previsión turística ha experimentado tres etapas. La colaboración institucional incluye la colaboración transnacional y la colaboración institucional nacional. La colaboración entre países aún debe reforzarse. La colaboración entre autores se basa principalmente en la colaboración dentro del campus. Los artículos con una alta cocitación se publican principalmente en las principales revistas de turismo y en otras publicaciones relevantes. El contenido de la investigación se refiere principalmente a la demanda turística, el revenue management, la demanda hotelera y los volúmenes turísticos. La previsión previa y durante la pandemia de la COVID-19 ha ampliado la investigación existente sobre previsión turística. La futura investigación sobre previsiones se centra en el uso racional de los big data, la mejora de la precisión de los modelos y el aumento de la credibilidad de los resultados de las previsiones.

Este artículo utiliza CiteSpace para analizar artículos de previsión turística con el fin de obtener futuras tendencias de investigación, lo que complementa la investigación existente y proporciona orientaciones para futuras investigaciones.

The purpose of this paper is to demonstrate the technical feasibility of implementing multi-view visualization methods to assist auditors in reviewing the integrity of high-volume accounting transactions. Modern enterprise resource planning (ERP) systems record several thousands of transactions daily. This makes it difficult to find a few instances of anomalous activities among legitimate transactions. Although continuous auditing and continuous monitoring systems perform substantial analytics, they often produce lengthy reports that require painstaking post-analysis. Approaches that reduce the burden of excessive information are more likely to contribute to the overall effectiveness of the audit process. The authors address this issue by designing and testing the use of visualization methods to present information graphically, to assist auditors in detecting anomalous and potentially fraudulent accounts payable transactions. The strength of the authors ' approach is its capacity for discovery and recognition of new and unexpected insights.

Data were obtained from the SAP enterprise (ERP) system of a real-world organization. A framework for performing visual analytics was developed and applied to the data to determine its usefulness and effectiveness in identifying anomalous activities.

The paper provides valuable insights into understanding the use of different types of visualizations to effectively identify anomalous activities.

Because this study emphasizes asset misappropriation, generalizing these findings to other categories of fraud, such as accounts receivable, must be made with caution.

This paper provides a framework for developing an automated visualization solution which may have implications in practice.

This paper demonstrates the need to understand the effectiveness of visualizations in detecting accounting fraud. This is directly applicable to organizations investigating methods of improving fraud detection in their ERP systems.

The Journal of Intellectual Capital (JIC) celebrated its 20th anniversary in 2020. Therefore, the present study aims to provide a general overview of the history and key trends in this journal during 2000–2019.

Two types of citation and textual data during a 20-year journal period were retrieved from the Scopus database. The citation structures and contents were explored based on a combination of bibliometric analysis, altmetric analysis and text mining. The journal themes and trends of their changes were analyzed through citation bursts, mapping and topic modeling. To make a better comparison, the text mining process for the topic modeling of the IC field was performed in addition to the topic modeling of JIC.

Bibliometric analysis indicated that JIC has experienced a remarkable growth in terms of the number of publications and citations over the last 20 years. The results indicated that JIC plays a significant role among IC researchers. Additionally, a large number of researchers, institutes and countries have made contributions to this journal and cited its research papers. Altmetric analysis showed that JIC has been shared in different social media such as Twitter, Facebook, Wikipedia, Mendeley, Citeulike, news and blogs. Text mining abstract of JIC articles indicated that “measurement,” “financial performance” and “IC reporting” have the relative prevalence with increasing trends over the past 20 years. In addition, “research trends” and “national and international studies” had a stable trend with low thematic share.

The findings have important implications for the JIC editorial team in order to make informed decisions about the further development of JIC as well as for IC researchers and practitioners to make more valuable contributions to the journal.

Using bibliometric analysis, altmetric analysis and text mining, this study provided a systematic and comprehensive analysis of JIC. The simultaneous use of these methods provides an interesting, unique and suitable capacity to analyze the journals by considering their various aspects.

Value stream mapping (VSM) is a visualization tool to identify and eliminate waste and widely applied in manufacturing, transportation, construction, service and other industries, especially in the Industrial 4.0 technology era. The purpose of this paper is to review and analyze the VSM literature to identify the advances and hotspots of VSM literature.

Taking the VSM literature collected from the Web of Science Core Collection database as the research samples, this research used the bibliometric and keyword co-occurrence analysis to analyze the publication trend, research topics and their contents of VSM from concept integration, application sectors and technology expansion.

With the development of research, the latest research integrates conceptual integration, application departments and technology expansion to develop more complex research designs. It can be integrated with simulation, six sigma, big data, Internet of Things and other technologies to expand the analysis and design ability of VSM, which enhances the adaptability of VSM to various scenarios.

This research contributes to VSM literature by conducting a systematic review based on the citation structure within VSM research and identifies the established and emerging areas of research on VSM.