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The purpose of the study was to detect trends in human resource management (HRM) research presented in journals during the 2000–2020 timeframe. The research question is: How are the interests of researchers changing in the field of HRM and which topics have gained popularity in recent years?

The approach adopted in this study was designed to overcome all the limitations specific to the systematic literature reviews and bibliometric studies presented in the Introduction. The full texts of papers were analyzed. The text-mining tools detected first clusters and then trends, moreover, which limited the impact of a researcher's bias. The approach applied is consistent with the general rules of systematic literature reviews.

The article makes a threefold contribution to academic knowledge. First, it uses modern methodology to gather and synthesize HRM research topics. The proposed approach was designed to allow early detection of nascent, non-obvious trends in research, which will help researchers address topics of high value for both theory and practice. Second, the results of our study highlight shifts in focus in HRM over the past 19 years. Third, the article suggests further directions of research.

In this study, the approach designed to overcome the limitations of using systematic literature review was presented. The analysis was done on the basis of the full text of the articles and the categories were discovered directly from the articles rather than predetermined. The study's findings may, however, potentially be limited by the following issues. First, the eligibility criteria included only papers indexed in the Scopus and WoS database and excluded conference proceedings, book chapters, and non-English papers. Second, only full-text articles were included in the study, which could narrow down the research area. As a consequence, important information regarding the research presented in the excluded documents is potentially lost. Third, most of the papers in our database were published in the International Journal of Human Resource Management, and therefore such trends as “challenges for international HRM” can be considered significant (long-lasting). Another – the fourth – limitation of the study is the lack of estimation of the proportion between searches in HRM journals and articles published in other journals. Future research may overcome the above-presented limitations. Although the authors used valuable techniques such as TF-IDF and HDBSCAN, the fifth limitation is that, after trends were discovered, it was necessary to evaluate and interpret them. That could have induced researchers' bias even if – as in this study – researchers from different areas of experience were involved. Finally, this study covers the 2000–2020 timeframe. Since HRM is a rapidly developing field, in a few years from now academics will probably begin to move into exciting new research areas. As a consequence, it might be worthwhile conducting similar analyses to those presented in this study and compare their results.

The present study provides an analysis of HRM journals with the aim of establishing trends in HRM research. It makes contributions to the field by providing a more comprehensive and objective review than analyses resulting from systematic literature reviews. It fills the gap in literature studies on HRM with a novel research approach – a methodology based on full-text mining and a big data toolset. As a consequence, this study can be considered as providing an adequate reflection of all the articles published in journals strictly devoted to HRM issues and which may serve as an important source of reference for both researchers and practitioners. This study can help them identify the core journals focused on HRM research as well as topics which are of particular interest and importance.

This paper aims to contribute to the understanding of the concept of a trend and the discourse of trend analysis.

This paper concisely discusses the concept of trends, the value of trend analysis for strategic planning and hierarchical trend pyramids as a tool to scan and analyse trends.

The examples will be given of how specific mega, meso and micro trends are related within a hierarchic trend pyramid.

The tool of trend pyramids helps to structurally analyse and understand trends and developments. Such analysis and understanding are relevant for strategic foresight and scenario planning in leisure and tourism.

The literature on trend levels and pyramids is scarce and varies in interpretation. The aim of this paper is to integrate the various viewpoints into a useful instrument for the scanning and analysis of trends and developments.

International Journal of Emerging Markets (IJoEM) is a leading journal that publishes high-quality research focused on emerging markets. In 2020, IJoEM celebrated its fifteenth anniversary, and the objective of this paper is to conduct a retrospective analysis to commensurate IJoEM's milestone.

Data used in this study were extracted using the Scopus database. Bibliometric analysis, using several indicators, is adopted to reveal the major trends and themes of a journal. Mapping of bibliographic data is carried using VOSviewer.

Study findings indicate that IJoEM has been growing for publications and citations since its inception. Four significant research directions emerged, i.e. consumer behaviour, financial markets, financial institutions and corporate governance and strategic dimensions based on cluster analysis of IJoEM's publications. The identified future research directions are focused on emergent investments opportunities, trends in behavioural finance, emerging role technology-financial companies, changing trends in corporate governance and the rising importance of strategic management in emerging markets.

To the best of the authors' knowledge, this is the first study to conduct a comprehensive bibliometric analysis of IJoEM. The study presents the key themes and trends emerging from a leading journal considered a high-quality research journal for research on emerging markets by academicians, scholars and practitioners.

The purpose of this article was to provide an outline of the citation practices of “Evolving to a new dominant logic for marketing” by Vargo and Lusch (2004) to identify and discuss the most prominent research topics in which citations were used and to suggest future research based on the results of the analysis.

The authors used a comprehensive framework of citation practices based on iterations of previous literature to analyze the relevant literature, which they identified by accessing, systematically and rigorously, every available contribution matching a set of criteria. The authors then categorized these contributions and highlighted the main topics of research interest in each category.

The findings identify some of the factors in the continuous development of SDL, the way this new marketing logic permeated the scientific debate, the infusion of Vargo and Lusch (2004) into several contributions framed in the new logic or justified through it, and a general perception of a default reference. Additionally, the findings highlight the main topics of research interest in each category.

The analysis enabled the detection of the original paper's influence through advances in service studies, pollination into other fields of research and continuous scientific debate. The authors have highlighted several avenues for research and proposed future research directions.

This research analyzed the effects of the spread of the SDL cornerstone article and emphasized the advantage of using an in-depth approach to the analysis of studies through a framework applied to more than 4,600 studies.

This study aims to theoretically and experimentally investigate the literature on university–industry linkages (UILs) through a systematic literature review and bibliometric analysis. Seven research questions were addressed in the present study: (1) descriptive characteristics of the literature on UIL, (2) trends of annual scientific publications on UIL, (3) the most relevant and high-impact sources on UIL, (4) the most globally cited articles on UIL, (5) the most relevant countries on UIL, (6) outcomes of Bradford's Law of Scattering and Lotka's Law of scientific productivity and (7) the trending research areas and avenues for future studies on UIL.

Systematic literature review and bibliometric analysis mapping techniques were applied to the present study to analyze 907 articles extracted from the Scopus database. Analysis tools used were Biblioshiny software and VOSviewer software.

Findings show that the UIL is a progressively growing discipline with a record of a 5.71% average annual growth rate in scientific production each year from 1970 to 2023. The United States, China and the United Kingdom were the most productive countries in the field of UIL in terms of total scientific production and citations. Academic entrepreneurship, industrial ecology, social network analysis, active learning, engineering education, health economics, public health, university–industry relationships, communication, causal layered analysis and competitiveness are the potential avenues for future researchers in the field of UIL based on the thematic map of keywords analysis.

This study contributes to the debate on UIL by offering a comprehensive literature review. The findings of the current study will benefit graduates, universities, industries and the community at large.

The opioid epidemic in the USA, the new psychoactive substances emerging on the market and the recent increase in cocaine treatment demands in Western Europe, all emphasise the importance of monitoring the use and harms of drugs over time. To be informed about new consumption patterns, this study aims to study the trends among people entering treatment for substance use in Belgium.

Belgian data from the Treatment Demand Indicator collected between 2015 and 2019 were used. A reference group of treatment units was selected to allow for comparisons between the different years. Trend analysis was performed by using a joinpoint regression among different regions and groups of clients.

The drugs of choice that were most frequently mentioned among the 23,000 analysed treatment episodes were alcohol and cannabis. Both remained relatively stable over time. Heroin seemed to be decreasing significantly at the national level, but increased in Brussels. Benzodiazepines decreased significantly in Flanders and Brussels, but not in Wallonia. On the other hand, reports of crack cocaine increased significantly in the three regions with a more pronounced trend in Wallonia and Brussels. Substances such as fentanyl, methamphetamine, ketamine or volatile inhalants have been mentioned significantly more by people entering treatment in 2019, although their contribution to the total number is still limited.

To the best of the authors’ knowledge, this study is the first to evaluate trends for all drugs of choice at a national and regional level. These results might not only benefit national policymakers but also other countries with similar alcohol or drug use patterns.

Understanding farmers’ perceptions of how the climate is changing is vital to anticipating its impacts. Farmers are known to take appropriate steps to adapt only when they perceive change to be taking place. This study aims to analyse how African indigenous vegetable (AIV) farmers perceive climate change in three different agro-climatic zones (ACZs) in Kenya, identify the main differences in historical seasonal and annual rainfall and temperature trends between the zones, discuss differences in farmers’ perceptions and historical trends and analyse the impact of these perceived changes and trends on yields, weeds, pests and disease infestation of AIVs.

Data collection was undertaken in focus group discussions (FGD) (N = 211) and during interviews with individual farmers (N = 269). The Mann–Kendall test and regression were applied for trend analysis of time series data (1980-2014). Analysis of variance and least significant difference were used to test for differences in mean rainfall data, while a chi-square test examined the association between farmer perceptions and ACZs. Coefficient of variation expressed as a percentage was used to show variability in mean annual and seasonal rainfall between the zones.

Farmers perceived that higher temperatures, decreased rainfall, late onset and early retreat of rain, erratic rainfall patterns and frequent dry spells were increasing the incidences of droughts and floods. The chi-square results showed a significant relationship between some of these perceptions and ACZs. Meteorological data provided some evidence to support farmers’ perceptions of changing rainfall. No trend was detected in mean annual rainfall, but a significant increase was recorded in the semi-humid zone. A decreasing maximum temperature was noted in the semi-humid zone, but otherwise, an overall increase was detected. There were highly significant differences in mean annual rainfall between the zones. Farmers perceived reduced yields and changes in pest infestation and diseases in some AIVs to be prevalent in the dry season. This study’s findings provide a basis for local and timely institutional changes, which could certainly help in reducing the adverse effects of climate change.

This is an original research paper and the historical trends, farmers’ perceptions and effects of climate change on AIV production documented in this paper may also be representative of other ACZs in Kenya.

The emergence of machine learning has opened a new way for researchers. It allows them to supplement the traditional manual methods for conducting a literature review and turning it into smart literature. This study aims to present a framework for incorporating machine learning into financial statement fraud (FSF) literature analysis. This framework facilitates the analysis of a large amount of literature to show the trend of the field and identify the most productive authors, journals and potential areas for future research.

In this study, a framework was introduced that merges bibliometric analysis techniques such as word frequency, co-word analysis and coauthorship analysis with the Latent Dirichlet Allocation topic modeling approach. This framework was used to uncover subtopics from 20 years of financial fraud research articles. Furthermore, the hierarchical clustering method was used on selected subtopics to demonstrate the primary contexts in the literature on FSF.

This study has contributed to the literature in two ways. First, this study has determined the top journals, articles, countries and keywords based on various bibliometric metrics. Second, using topic modeling and then hierarchy clustering, this study demonstrates the four primary contexts in FSF detection.

In this study, the authors tried to comprehensively view the studies related to financial fraud conducted over two decades. However, this research has limitations that can be an opportunity for future researchers. The first limitation is due to language bias. This study has focused on English language articles, so it is suggested that other researchers consider other languages as well. The second limitation is caused by citation bias. In this study, the authors tried to show the top articles based on the citation criteria. However, judging based on citation alone can be misleading. Therefore, this study suggests that the researchers consider other measures to check the citation quality and assess the studies’ precision by applying meta-analysis.

Despite the popularity of bibliometric analysis and topic modeling, there have been limited efforts to use machine learning for literature review. This novel approach of using hierarchical clustering on topic modeling results enable us to uncover four primary contexts. Furthermore, this method allowed us to show the keywords of each context and highlight significant articles within each context.

Tropical wetland ecosystems are threatened by climate change but also play a key role in its mitigation and adaptation through management of land use and other drivers. Local-level assessments are needed to support evidence-based wetland management in the face of climate change. This study aims to examine the local communities’ knowledge and perception of climate change in Yala wetland, Kenya, and compare them with observed data on climate trends. Such comparisons are useful to inform context-specific climate change adaptation actions.

The study used a mixed methods approach that combined analysis of climate data with perceptions from the local community. Gridded data on temperature and rainfall for the period from 1981 to 2018 were compared with data on climate change perceptions from semi-structured questionnaires with 286 key informants and community members.

Majority of the respondents had observed changes in climate parameters – severe drought (88.5%), increased frequency of floods (86.0%) and irregular onset and termination of rains (90.9%) in the past 20 years. The perceptions corresponded with climate trends that showed a significant increasing trend in the short rains and the average maximum temperature, high incidence of very wet years and variability in onset and termination of rainfall between 1981 and 2018. Gender, age and education had little influence on knowledge and awareness of climate change, except for frequency of floods and self-reported understanding of climate change. The community perceived the wetland to be important for climate change adaptation, particularly the provision of resources such as grazing grounds during drought.

The study faced challenges of low sample size, use of gridded climate data and reproducibility in other contexts. The results of this study apply to local communities in a tropical wetland in Western Kenya, which has a bi-modal pattern of rainfall. The sample of the study was regional and may therefore not be representative of the whole of Kenya, which has diverse socioeconomic and ecological contexts. Potential problems have been identified with the use of gridded data (for example, regional biases in models), although their usefulness in data scarce contexts is well established. Moreover, the sample size has been found to be a less important factor in research of highly complex socio-ecological systems where there is an attempt to bridge natural and social sciences.

This study addresses the paucity of studies on climate change trends in papyrus wetlands of sub-Saharan Africa and the role of local knowledge and perceptions in influencing the management of such wetlands. Perceptions largely influence local stakeholders’ decisions, and a study that compares perceptions vs “reality” provides evidence for engagement with the stakeholders in managing these highly vulnerable ecosystems. The study showed that the local community’s perceptions corresponded with the climate record and that adaptation measures are already ongoing in the area.

This study presents a case for the understanding of community perceptions and knowledge of climate change in a tropical wetland under threat from climate change and land use change, to inform management under a changing climate.

This paper aims to study the temporal and spatial variation of vegetation and the influence of climate change on vegetation coverage in the Yellow River basin, China. The current study aimed to evaluate the role of a series of government-led environmental control projects in restoring the ecological environment of the Yellow River basin.

This paper uses unary linear regression, Mann–Kendall and wavelet analyses to study the spatial–temporal variations of vegetation and the response to climate changes in the Yellow River, China.

The results showed that for the past 17 years, not only the mean annual increase rate of the Normalized Difference Vegetation Index (NDVI) was 0.0059/a, but the spatial heterogeneity also yields significant results. The vegetation growth in the southeastern region was significantly better than that in the northwestern region. The variation period of the NDVI in the study area significantly shortened, and the most obvious oscillation period was half a year, with two peaks in one year. In addition, there are positive and negative effects of human activities on the change of vegetation cover of the Loess Plateau. The project of transforming cultivated land to forest and grassland promotes the increase of vegetation cover of the Loess plateau. Unfortunately, the regional urbanization and industrialization proliferated, and the overloading of grazing, deforestation, over-reclamation, and the exploitation and development of the energy area in the grassland region led to the reduction of the NDVI. Fortunately, the positive effects outweigh the negative ones.

This paper provides a comprehensive insight to analysis of the vegetation change and the responses of vegetation to climate change, with special reference to make the planning policy of ecological restoration. This paper argues that ecological restoration should be strengthened in areas with annual precipitation less than 450 mm.