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The purposes of this paper are to highlight those topics of forensic accounting that have received little or no attention in the forensic accounting research that has been published in forensic accounting research journals; discover what research methods have been most commonly used; and identify research methods that have been infrequently used.

This is a descriptive research study that explores the topics and methods used in forensic accounting research published in forensic accounting journals.

Fraud and quantitative methods make up the largest percentage of topics and research methods published in forensic accounting journals.

Limited to forensic accounting journals. Results suggest forensic accounting researchers are using mimetic topics and methods of accounting research. The absence of diversity in forensic accounting research topics and methods has the potential to compromise the overall contribution of forensic accounting research.

This paper identifies gaps in topics and research methods in forensic accounting research to encourage research in diverse topics using diverse methods that will be valuable to forensic accountants.

This original research is the first to survey and classify research published in forensic accounting journals according to topic and method.

Recent attention to the developments focusing on the educational services has been noteworthy, with the educational environment specifically the smart campus emerging both as a domain and as an opportunity. As a domain worthy of exploration, a number of research efforts are being conceptualized around smart campus initiatives. The existing bouquet of research publications on smart campus provides a testimony of the enthusiasm and also exposes the heterogeneous attempts the domain has witnessed to date. The available evidence is still inadequate to provide clarity on the thrust areas of research around smart campus.

Given the understanding, this study intends to decode the domain to get an early impression of the focus of the research concentration around smart campus. Thereby the study resorts to an automated text-mining approach using Python on contents shortlisted systematically, and published between the period 2010 and May 2022, from select databases.

Based on the analysis it was possible to identify eight themes (i.e. smart campus characteristics, smart campus stakeholders, smart campus frameworks, smart campus technologies, smart campus infrastructure, smart campus evaluation, smart learning environment and smart campus applications) characterizing research efforts within the smart campus literature.

The themes around the smart campus showcase the thrust areas receiving attention. These characterize extant research endeavours in the smart campus domain and can offer useful pointers to researchers going forward. This awareness can also be beneficial to institutional leadership and technology providers intending to implement smart campus initiatives, contributing to the development of the educational environment.

A gap between research and practice is commonly perceived throughout accounting academia. However, empirical evidence on the magnitude of this detachment remains scarce. The authors provide new evidence to the ongoing debate by introducing a novel topic-based approach to capture the research-practice gap and quantify its extent. They also explore regional differences in the research-practice gap.

The authors apply the unsupervised machine learning approach Latent Dirichlet allocation (LDA) to compare the topical composition of 2,251 articles from six premier research, practice and bridging journals from the USA and Europe between 2009 and 2019. The authors extend the existing methods of summarizing literature and develop metrics that allow researchers to evaluate the research-practice gap. The authors conduct a plethora of additional analyses to corroborate the findings.

The results substantiate a pronounced topic-related research-practice gap in accounting literature and document its statistical significance. Moreover, the authors uncover that this gap is more pronounced in the USA than in Europe, highlighting the importance of institutional differences between academic communities.

The authors objectify the debate about the extent of a research-practice gap and stimulate further discussions about explanations and consequences.

To the best of the authors' knowledge, this is the first paper to deploy a rigorous machine learning approach to measure a topic-based research-practice gap in the accounting literature. Additionally, the authors provide theoretical rationales for the extent and regional differences in the research-practice gap.

This bibliometric study provides an overview of research related to digital transformation (DT) in the tourism industry from 2013 to 2022. The goals of the research are as follows: (1) to identify the development of academic papers related to DT in the tourism industry, (2) to analyze dominant research topics and the development of research interest and research impact over time and (3) to analyze the change in research topics during the pandemic.

In this study, the authors processed 3,683 papers retrieved from the Web of Science and Scopus. The authors performed different types of bibliometric analyses to identify the development of papers related to DT in the tourism industry. To reveal latent topics, the authors implemented topic modeling based on latent Dirichlet allocation with Gibbs sampling.

The authors identified eight topics related to DT in the tourism industry: City and urban planning, Social media, Data analytics, Sustainable and economic development, Technology-based experience and interaction, Cultural heritage, Digital destination marketing and Smart tourism management. The authors also identified seven topics related to DT in the tourism industry during the Covid-19 pandemic; the largest ones are smart analytics, marketing strategies and sustainability.

To identify research topics and their development over time, the authors applied a novel methodological approach – a smart literature review. This machine learning approach is able to analyze a huge amount of documents. At the same time, it can also identify topics that would remain unrevealed by a standard bibliometric analysis.

The Accounting Information Systems (AIS) research field emerged around 30 years ago as a subfield of accounting but is at risk to develop further as an isolated discipline. However, given the importance of digitalization and its relevance for accounting, an amalgamation of the parent research field of accounting and the subfield of accounting information systems is pivotal for continuing relevant research that is of high quality. This study empirically investigates the distance between AIS research that is included in accounting literature and AIS research that prevails in dedicated AIS research outlets.

To understand which topics define AIS research, all articles published in the two leading AIS journals since 2000 were analyzed. Based on this topical inventory, all AIS studies that were published in the top 16 accounting journals, also since 2000, are identified and categorized in terms of topic, subtopic and research methodology. Next, AIS studies published in the general accounting field and AIS studies published in the AIS field were compared in terms of topics and research methodology to gain insights into the distance between the two fields.

The coverage of AIS topics in accounting journals is, to no small extent, concentrated around the topics “information disclosure”, “network technologies” and “audit and control”. Other AIS topics remain underrepresented. A possible explanation might be the focus on archival studies in accounting outlets, but other elements might play a role. The findings suggest that there is only a partial overlap between the parent accounting research field and the AIS subfield, in terms of both topic and research methodology diversity. These findings suggest a considerable distance between both fields, which might hold detrimental consequences in the long run, if no corrective actions are taken.

This is the first in-depth investigation of the distance between the AIS research field and its parent field of accounting. This study helped develop an AIS classification scheme, which can be used in other research endeavors. This study creates awareness of the divergence between the general accounting research field and the AIS subfield. Given the latter's relevance to the accounting profession, isolation or deterioration of the AIS research must be avoided. Some actionable suggestions are provided in the paper.

Knowledge organization (KO) has been advancing at a progressively rapid pace under the influence of information technology. This study aims to explore the topics, characteristics, and trends of KO research in the 21st century.

The full text of 4,360 KO-related articles published from 2000 to 2021 is collected. Through content analysis, this study identifies the topics, research methods, and application areas of each article, and the statistics are presented through a series of visualizations.

In total, 13 main topics, 105 sub-topics, 16 research methods, and 57 application areas are identified. Notably, classification has always been an important topic, while linked data, automated techniques, and ontology have become popular topics recently. Significant changing features have also occurred. The versatile use of research methods has increased, with empirical research becoming the mainstream. Application areas show a trend of refinement from subject areas to specific scenarios. Construction techniques present a combination of automated techniques, crowdsourcing, and experts.

KO has evolved and diversified due to technological developments. This study is the first to focus on the continuous changing features over an extended, 21-year period, as opposed to sampling a few years. It also provides clues and insights for researchers and practitioners interested in KO to understand how it has changed in the Semantic Web and big data context.

The paper attempts to address the following research questions (RQs): RQ1: What are the main research topics within PSS research? RQ2: What are future trends for PSS research?

Twenty years of research (1999–2018) on product-service systems (PSS) produced a significant amount of scientific literature on the topic. As the PSS field is relatively new and fragmented across different disciplines, a review of the prior and relevant literature is important in order to provide the necessary framework for understanding current developments and future perspectives. This paper aims to review and organize research contributions regarding PSS. A machine-learning algorithm, namely Latent Dirichlet Allocation, has been applied to the whole literature corpus on PSS in order to understand its structure.

The adopted approach resulted in the definition of eight distinct and representative topics able to deal adequately with the multidisciplinarity of the PSS. Furthermore, a systematic review of the literature is proposed to summarize the state-of-the-art and limitations in the identified PSS research topics. Based on this critical analysis, major gaps and future research challenges are presented and discussed.

On the basis of the results of the topic landscape, the paper presents some potential research opportunities on PSSs. In particular, challenges, transversal to the eight research topics and related to recent technology trends and digital transformation, have been discussed.

Examining research topics in a specific area such as accounting is important to both novice and veteran researchers. The present study aims to identify the research topics in the area of accounting and to investigate the research trends by finding hot and cold topics from all those identified ones in the field.

A new dependency-based method focusing on noun phrases, which efficiently extracts research topics from a large set of library data, was proposed. An AR(1) autoregressive model was used to identify topics that have received significantly more or less attention from the researchers. The data used in the study included a total of 4,182 abstracts published in six leading (or premier) accounting journals from 2000 to May 2019.

The study identified 48 important research topics across the examined period as well as eight hot topics and one cold topic from the 48 topics.

The research topics identified based on the dependency-based method are similar to those found with the technique of latent Dirichlet allocation latent Dirichlet allocation (LDA) topic modelling. In addition, the method seems highly efficient, and the results are easier to interpret. Last, the research topics and trends found in the study provide reference to the researchers in the area of accounting.

The selection of the research topic and design crucially determines the success of conducting a research. Thus, the purpose of this paper is to explore the process by which undergraduate students select their research topic and design, as viewed from the lens of motivation theory proposed by Ryan and Deci (2000), which focuses on motivational propensity and consistency.

A longitudinal narrative inquiry was employed to address the gap. In total, 10 Indonesian graduates from different educational backgrounds were purposively selected. The interview focused on their longitudinal experiences from the freshman period to skripsi (undergraduate thesis) supervision period. Data analysis included inductive thematic analysis, member checking by the researchers, and cross-checking by the participants.

The motivational propensity and consistency in selecting research topic and design are highly dynamic. Specifically, autonomy, high curiosity, self-reflection of past interest and perceived competence, and library research become the major factors toward the manifestation of intrinsic motivation in the selected topics and designs. Meanwhile, friends’ preferences, lecturer’s expertise and suggestion, and unclear input from the relevant previous courses result in the manifestation of various types of external motivation.

Therefore, the implementation of dialogic discussion might be more effective when tensions prevail between the department, academic advisor or skripsi supervisors, and students with respect to the selected topics and designs. Moreover, the provision of constructive tasks like case studies, group discussion, and/or research proposal writing can be applied in research methodology course to enhance their repertoire about research topic and design. Autonomy and self-reflection should become the driving objectives.

The exploration of the issue has to be intensively oriented toward prescriptive handbook development in selecting research topic and design. This study sheds light on the explanation of the actual cyclical process of the undergraduate students’ motivational propensity and consistency generated from internal and external regulations, as viewed from the lens of motivation theory.

The purpose of this study is to discover the distribution and trends of existing Offsite construction (OSC) literature with an intention to highlight research niches and propose the future outline.

The paper adopted literature reviews methodology involving 1,057 relevant documents published in 2008-2017 from 15 journals. The selected documents were empirically analyzed through a topic-modeling technique. A latent Dirichlet allocation model was applied to each document to infer 50 key topics. A machine learning for language toolkit was used to get topic posterior word distribution and word composition.

This is an exploratory study, which identifies the distribution of topics and themes; the trend of topics and themes; journal distribution trends; and comparative topic, themes and journal distribution trend. The distribution and trends show an increase in researcher’s interest and the journal’s priority on OSC research. Nevertheless, OSC existing literature is faced with; under-researched topics such as building information modeling, smart construction and marketing. The under-researched themes include organizational management, supply chain and context. The authors also found an overload of similar information in prefabrication and concrete topics. Furthermore, the innovative methods and constraints themes were found to be overloaded with similar information.

The naming of the themes was based on our own interpretation; hence, the research results may lack generalizability. Therefore, a comparative study using different data processing is proposed. The study also provides future research outline as follows: studying OSC topics from dynamic evolution perspective and identifying the new emerging topics; searching for effective strategies to enhance OSC research; identifying the contribution of countries, affiliation and funding agency; and studying the impact of these themes to the adoption of OSC.

This study is of values to the scholars, as it could stimulate research to under-researched areas.

This paper justifies a need to have a broad understanding of the nature and structure of existing OSC literature.