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Nature’s contribution to people (NCP) is a concept that specifically recognizes the relationship of “humans and the natural environment” similarly to concepts of “cultural landscapes” and consistent to “heritage.” These concepts are essential in incorporating a diverse range of stakeholders from different scales, which is important for policy and practice. The paper aims to review the existing peer-reviewed papers in the Philippines, using meta-analysis and systematic review. We addressed the significant interlinkages that help facilitate the transition and strengthen the correlation of cultural ecosystem services (CES) and NCP in a cultural landscape setting.

To distinguish and support claims for NCP from CES, we conducted a meta-analysis and systematic review based on the 30-existing peer-reviewed articles on the Philippine cultural ES in the lenses of “heritage” and “cultural landscape.”

The results generated a few numbers of the Philippine CES studies, yet it has increased cumulatively year by year consistent with previous international studies. We found that most studies are focused on topics associated with “Indigenous People, Ancestral Domains, Protected Areas/Landscapes, and Indigenous and Local Knowledge” on the linkages concurrently distinguishing NCP to CES, and may signify stronger economic valuation in uncovering the sociocultural dimensions of these scholarships through its relational values in the lenses of cultural landscape and heritage.

The authors limited the search to peer-reviewed journal articles published from online databases and did not consider Philippine University based and local publications to have a systematic review. This is to prevent underestimating the vast amount of CES literature and avoid gray literature that is not peer-reviewed; hence, being able to analyze and produce focused, yet, credible data.

In a generalizing perspective, NCP 1, 6, 8, 12, 13, 15, 16, 17 and 18 have the most realized positive correlations of the reporting categories to the Philippine CES studies. The majority of the context-specific perspective NCP has strong conceptual claims in the existing Philippine CES literature through the studies’ variables aside from NCP 3, 4, 5, 7, 8 and 11 that are still mostly in the nature of generalizing perspective.

In conclusion, our results imply that the previous and existing CES studies in the Philippines harbor more attributes presented by the NCP reporting categories. This is deemed more suitable, and may signify stronger economic valuation in uncovering the sociocultural dimensions of these scholarships through its relational values in the lenses of cultural landscape and heritage.

The purpose of this paper is to identify the historical trends and status of the national development of artificial intelligence (AI) from a nationwide perspective and to enable governments at different administrative levels to promote AI development through policymaking.

This paper analyzed 248 Chinese AI policies (36 issued by the state agencies and 212 by the regional agencies). Policy bibliometrics, policy instruments and network analysis were used to reveal the AI policy patterns. Three aspects were analyzed: the spatiotemporal distribution of issued policies, the policy foci and instruments of policy contents and the cooperation and citation among policy-issuing agencies.

Results indicate that Chinese AI development is still in the initial phase. During the policymaking processes, the state and regional policy foci have strong consistency; however, the coordination among state and regional agencies is supposed to be strengthened. According to the issuing time of AI policies, Chinese AI development is in accordance with the global situation and has witnessed unprecedented growth in the last five years. And the coastal provinces have issued more targeted policies than the middle and western provinces. Governments at the state and regional levels have emphasized familiar policy foci and played the role of policymakers, along with regional governments that also functioned as policy executors as well. According to the three-dimension instruments coding, the authors found an uneven structure of policy instruments at both levels. Furthermore, weak cooperation appears at the state level, while little cooperation is found among regional agencies. Regional governments cite state policies, thus leading to the formation of top-down diffusion, lacking bottom-up diffusion.

The paper contributes to the literature by characterizing policy patterns from both external attributes and semantic contents, thus revealing features of policy distribution, contents and agencies. What is more, this research analyzes Chinese AI policies from a nationwide perspective, which contributes to clarifying the overall status and multi-level relationships of policies. The findings also benefit the coordinated development of governments during further policymaking processes.

With the aid of bibliometric analysis, this study aims to show the state-of-the-art of research on the digital divide and identifies new areas for further investigation.

Performance analysis and science mapping were used in the study to analyse a sample of 3,571 studies that were published between 2018 and 2022. The “Title-Keyword-Abstract” search option was used to collect the anticipated publications data from the Scopus database. The gathered data were analysed using the common bibliometric indices to evaluate the research landscape. The science mapping tactics made use of the VOSviewer and Biblioshiny software.

The performance and science mapping analysis shows that recent research on the digital divide has not been sufficiently exposed and examined. The analysis discovered emerging topics, prolific authors and nations, affiliations, a network of collaboration among authors, countries and institutions, bibliographic coupling and keyword co-occurrence.

This work presents a state-of-the-art that has significant theoretical and practical ramifications for the existing digital divide literature. The methodologies and database used in the current study are more extensive.

This article examines strategic management research across Latin America from 1990 to 2023, addressing four critical inquiries: the themes prevalent in strategic discussions, the leading countries in strategic management (SM) publications, the defining characteristics of strategic research in major Latin American economies and the reflection on whether Latin America is a region that generates or follows the knowledge of the Global North.

Utilizing co-occurrence analysis, this study maps the terrain of SM research in the region, analyzing 4,963 articles indexed in the Scopus database. The authors employed a co-occurrence analysis to map SM research in Latin America, analyzing 4,963 articles from the Scopus database.

Predominant themes include the theoretical underpinnings of strategy, sustainable development, innovation, tourism and international trade. Brazil, Mexico, Colombia and Chile have emerged as leaders in research volume and thematic diversity, particularly in sustainable development and innovation.

By identifying patterns, behaviors and trends in SM research, the authors uncover methods and tools that, once contextualized for the region, can significantly enhance organizational performance.

This investigation is a pioneering effort, providing a focused analysis on SM research within Latin America. It highlights significant contributions since 1990 across the region's main economies. This study represents one of the first comprehensive mappings of this academic field within Latin America. This is the first article, to the authors’ knowledge, developed to map the intellectual structure of the SM field in Latin America through an analysis of co-occurrences, with emphasis on the region's main economies.

The purpose of this paper is to consider the interface of research methodology paradigms (which are commonly conventionally perceived as being juxtaposed when conducting research) through the application of textual analytical software.

The argument develops matrices and applies these to the human resource (HR) context of individual and career group sense-making so as to better understand the inherent career dynamics and sense-making in a sample derived from a French media agency context.

The paper’s findings comprise a range of insights from the respondent managers (n = 26). The results suggest that a better understanding of methodologies facilitates the development of theories based on textual data analysis.

The limits of the approach are important. Indeed, it is necessary to make compromises and arrangements with epistemological orthodoxy. Indeed, at first and to be able to process the data with the Alceste© and Tropes©, the interviews were recorded, transcribed and considered as “definitive”. This potentially contradicts the methods of collecting data prescribed by the thematic analysis or the method of cognitive maps. These two interpretive approaches imply a process of co-construction of the results that would not theoretically rely solely on a recording.

It provides insights on how, and to what extent, can data analytical software packages facilitate a better understanding of paradigm (interpretive-positivistic) interoperation and commensurability.

Importantly, the study provides a novel means by which to study the important HR issue of career perception and trajectory.

The methodology-driven approach shows that there is potent scope to map and develop valuable and complementary data perspectives on research issues by interfacing paradigms and textual data analysis tools.

This study aims to present a new rapid enhancement digital elevation model (DEM) framework using Google Earth Engine (GEE), machine learning, weighted interpolation and spatial interpolation techniques with ground control points (GCPs), where high-resolution DEMs are crucial spatial data that find extensive use in many analyses and applications.

First, rapid-DEM imports Shuttle Radar Topography Mission (SRTM) data and Sentinel-2 multispectral imagery from a user-defined time and area of interest into GEE. Second, SRTM with the feature attributes from Sentinel-2 multispectral imagery is generated and used as input data in support vector machine classification algorithm. Third, the inverse probability weighted interpolation (IPWI) approach uses 12 fixed GCPs as additional input data to assign the probability to each pixel of the image and generate corrected SRTM elevations. Fourth, gridding the enhanced DEM consists of regular points (E, N and H), and the contour interval is 5 m. Finally, densification of enhanced DEM data with GCPs is obtained using global positioning system technique through spatial interpolations such as Kriging, inverse distance weighted, modified Shepard’s method and triangulation with linear interpolation techniques.

The results were compared to a 1-m vertically accurate reference DEM (RD) obtained by image matching with Worldview-1 stereo satellite images. The results of this study demonstrated that the root mean square error (RMSE) of the original SRTM DEM was 5.95 m. On the other hand, the RMSE of the estimated elevations by the IPWI approach has been improved to 2.01 m, and the generated DEM by Kriging technique was 1.85 m, with a reduction of 68.91%.

A comparison with the RD demonstrates significant SRTM improvements. The suggested method clearly reduces the elevation error of the original SRTM DEM.

This study aims to undertake a theoretical and technical exploration of the literature on Work Readiness (WR) through the implementation of a systematic literature review and bibliometric analysis. The present study addresses seven distinct research questions: (1) an examination of the descriptive features characterizing the literature on WR, (2) an analysis of trends in annual scientific publications related to WR, (3) the identification of the most pertinent and high-impact sources contributing to WR, (4) the delineation of the globally cited articles exerting the most influence on WR, (5) the determination of the most relevant countries associated with WR, (6) an evaluation of the outcomes derived from Bradford’s Law of Scattering and Lotka’s Law of scientific productivity in the context of WR, and (7) the identification of the prevailing research avenues that hold significance for future studies on WR.

The present study employed Systematic Literature Review (SLR) and bibliometric analysis mapping techniques to analyze 521 articles extracted from the Scopus database. The analysis utilized Biblioshiny software and VOSviewer software as the primary tools.

The findings reveal that WR constitutes a steadily expanding subject discipline, showcasing a notable 9.12% annual growth in scientific production spanning from 1975 to 2023. Australia, the USA, and Canada emerged as the most productive countries within the field of WR, as evidenced by their cumulative scientific production. The thematic map of keyword analysis suggests several burgeoning pathways for future researchers in the WR domain, including workplace learning, functional capacity evaluation, graduate WR, digital literacy, blended learning, resilience, and curriculum.

This study contributes to the WR discourse by providing a comprehensive literature review. The findings of this study hold significance for graduates, universities, employers, the higher education industry, and the broader community.

The growing interest on ecosystems on both managerial and academic side reflects a vibrant field of study, nevertheless, the subject is very heterogeneous and in particular concerning a particular form of ecosystems: collaborative ecosystems, the purpose of this study is to shed light on these.

The definition gap existent and the multiplicity of fields and composite studies on collaborative ecosystems have made it necessary to conduct a systematic literature review of the phenomenon, a bibliometric analysis and content analysis.

The research offers an overview of the phenomenon, three main cluster categories emerged: ecosystem, competition and open innovation; this cluster offers a comprehensive schematization of the research topics.

Limitations of this research are that the investigation has been confined to specific keywords related to collaborative ecosystems that led to a strict selection of papers to be analyzed and in having confined the investigation to publications in the managerial area. Further research will be able to expand the selection of keywords or use more strings and proceed to a comparative analysis of results. Another limitation is the small number of databases assessed (only Scopus and Web of Science) and have confined the analysis to specific clusters that emerged from the quantitative analysis of papers.

By proposing a taxonomy of collaborative ecosystems, the paper highlights what solutions and architectures an ecosystem manager must consider when developing collaborative ecosystems, what factors he or she must pay attention to in order to ensure their development and survival, and what elements determine the development of an ecosystem, in particular, the management of innovation and knowledge and the scarcity of resources in a hyper-competitive environment.

A combination of research methods was used to identify the intellectual structure of collaborative ecosystems. In addition, we propose a taxonomy for collaborative ecosystems, opening the study to new lines of investigation and providing a new research agenda.

Previous literature reviews mainly focus on green supply chain, however, there is surprisingly little effort made in the systematic literature review to focus on a specific function of green supply chain, i.e. green procurement (GP). Regarding research methodology, most reviews are qualitative and inductive generalizations. Quantitative methods such as bibliometrics have started to be applied in recent years. This paper responds to this trend by counting the largest amount of literature with 238 articles in the last 24 years from 2000 to 2023 to visually analyze different theoretical perspectives and research topics into a comprehensive framework and identify future research directions and opportunities in the GP field.

Based on CiteSpace and in-depth content analysis, this paper attempts to visually analyze 238 valid papers to identify key literature and analyze the evolution of research hot spots and frontier development trends.

Combined with the visualization results and the content analysis of key references, we identify key literature and examine the evolution of research hotspots and frontier development trends. The bibliometric analysis mainly includes knowledge mapping to identify key themes, co-occurrence and clustering analysis of keywords, cooperation networks in researchers' countries. An overall GP research model is presented and our research suggests future avenues for GP research, such as low carbon, digitalization, servitization and ecosystem perspectives.

Firstly, in terms of time and volume of literature, we have counted the most comprehensive and up-to-date literature in the field of GP research, which is conducive to further expanding and enriching GP research. Secondly, this study clearly describes the theoretical evolution of GP research from bilateral and multilateral to ecosystem perspectives, and constructs a new and comprehensive research framework of “driver-practice-outcome”. Thirdly, based on the bibliometric analysis results, our research suggests future avenues for GP research, such as low-carbon, digitalization, servitization, and ecosystem perspectives, which can contribute to expanding our understanding of GP development.

This paper aims to use text mining methods to explore the similarities and differences between countries’ national digital transformation (DT) and Industry 4.0 (I4.0) policies. The study examines the applicability of text mining as an alternative for comprehensive clustering of national I4.0 and DT strategies, encouraging policy researchers toward data science that can offer rapid policy analysis and benchmarking.

With an exploratory research approach, topic modeling, principal component analysis and unsupervised machine learning algorithms (k-means and hierarchical clustering) are used for clustering national I4.0 and DT strategies. This paper uses a corpus of policy documents and related scientific publications from several countries and integrate their science and technology performance. The paper also presents the positioning of Türkiye’s I4.0 and DT national policy as a case from a developing country context.

Text mining provides meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, aligned with their geographic, economic and political circumstances. Findings also shed light on the DT strategic landscape and the key themes spanning various policy dimensions. Drawing from the Turkish case, political options are discussed in the context of developing (follower) countries’ I4.0 and DT.

The paper reveals meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, reflecting political proximities aligned with their geographic, economic and political circumstances. This can help policymakers to comparatively understand national DT and I4.0 policies and use this knowledge to reflect collaborative and competitive measures to their policies.

This paper provides a unique combined methodology for text mining-based policy analysis in the DT context, which has not been adopted. In an era where computational social science and machine learning have gained importance and adaptability to political and social science fields, and in the technology and innovation management discipline, clustering applications showed similar and different policy patterns in a timely and unbiased manner.