Search results

Identifying the frontiers of a specific research field is one of the most basic tasks in bibliometrics and research published in leading conferences is crucial to the data mining research community, whereas few research studies have focused on it. The purpose of this study is to detect the intellectual structure of data mining based on conference papers.

This study takes the authoritative conference papers of the ranking 9 in the data mining field provided by Google Scholar Metrics as a sample. According to paper amount, this paper first detects the annual situation of the published documents and the distribution of the published conferences. Furthermore, from the research perspective of keywords, CiteSpace was used to dig into the conference papers to identify the frontiers of data mining, which focus on keywords term frequency, keywords betweenness centrality, keywords clustering and burst keywords.

Research showed that the research heat of data mining had experienced a linear upward trend during 2007 and 2016. The frontier identification based on the conference papers showed that there were five research hotspots in data mining, including clustering, classification, recommendation, social network analysis and community detection. The research contents embodied in the conference papers were also very rich.

This study detected the research frontier from leading data mining conference papers. Based on the keyword co-occurrence network, from four dimensions of keyword term frequency, betweeness centrality, clustering analysis and burst analysis, this paper identified and analyzed the research frontiers of data mining discipline from 2007 to 2016.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.

China has established 14 marine economic development demonstration zones in 2018, which has become an important step in exploring the high-quality development of the marine economy. The paper statistically analyzes the documents related to the field of marine economy and special economic zones (SEZs) and strives to find out the hot spots, intersections and related development contexts of the two in the research direction, so as to provide some ideas for later research.

By taking the bibliographic information data of “Marine Economy” and “Special Economic Zone” in the Web of Science database as a sample, the paper applies the Citespace bibliometric tool to analyze the evolution of disciplinary distribution, research country, author collaboration and research hotspot trends in the two fields.

It can be found from the paper results that the current research on marine economy and SEZs involves the intersection of many disciplines. China and the United States are the leaders in this field. However, there is more extensive cooperation between authors from different countries, but the cooperation depth needs to be strengthened. At the same time, compared with the terrestrial economy, the trend of its research hotspots is lagging to a certain extent. Moreover, there is still no systematic and professional research paradigm on marine economy.

At present, there are a few research studies on marine economic development demonstration areas or marine SEZs, and related bibliographical references are incomplete, which leads to insufficient samples, and bibliometric methods cannot fully reveal the general research rules and development trends in this field.

The research on the marine economic development demonstration area is still in its infancy. The paper jointly analyzes the literature in the two fields of marine economy and SEZs, aims to find the intersection and related research hotspots of the two, and provides references for the future research of marine development demonstration areas, which is of certain practical significance.

Crowdfunding (CF) has become an increasingly popular means of financing for entrepreneurs and has attracted significant attention from both researchers and practitioners in recent years. The purpose of this study is to investigate the core content and knowledge diffusion paths in the CF field. Specifically, we aim to identify the main topics and themes that have emerged in this field and to trace the evolution of CF knowledge over time.

This study employs co-word clustering and main path analysis (MPA) to examine the historical development of CF research based on 1,528 journal articles retrieved from the Web of Science Core Collection database.

The results of the analysis reveal that CF research focuses on seven themes: sustainability, entrepreneurial finance, entrepreneurship, fintech, social entrepreneurship, social capital, and microcredits. The analysis of the four main paths reveals that equity CF has been the dominant topic in the past years. Recently, CF research has tended to focus on topics such as fintech, the COVID-19 pandemic, competition, Brexit, and policy response.

To the authors' best knowledge, this is the first attempt to explore knowledge diffusion dynamics in the CF field. Overall, the study offers a structure for analyzing the paths through which knowledge is diffused, enabling scholars to effectively manage a large volume of research papers and gain a deeper understanding of the historical, current, and future trends in the development of CF.

Among the growing interest towards market segmentation and targeted marketing, the current study adopted a scientometric approach to examine the literature on wine selection and preferences. The current review specifically attempts to shed light on the research that explores the determinants of wine preferences at multiple levels of analysis.

CiteSpace was used to compute a Document Co-Citation Analysis (DCA) on a sample of 114,048 eligible references obtained from 2,846 publications downloaded from Scopus on 24 May 2021.

An optimized network of 1,505 nodes and 4,616 links was generated. Within the network, impactful publications on the topic and thematic domains of research were identified. Specifically, two thematic macro-areas were identified through a qualitative analysis of papers included in the 7 major clusters. The first one - “Methods of Wine Making” - included clusters #0, #3, #5, #6 and #18. The second one - “Consumers' Attitudes and Preferences Towards Wine” - included clusters #1 and #2. The first thematic macro-area included more technical aspects referring to the process of wine making, while the second thematic macro-area focused more on the factors influencing individuals' preferences and attitudes towards wine. To reflect the aims of the current paper, publications giving light to the “Consumers' Attitudes and Preferences Towards Wine” macro-area were analyzed in detail.

The resulting insights may help wine makers and wine sellers optimize their work in relation to market segments and to the factors influencing individuals' purchasing behaviors.

This paper analyses how entrepreneurs recognise and exploit entrepreneurial opportunities following a sustainable approach that respects the equilibrium among environmental, social and commercial purposes, and how their personality affects this process. The main personality traits focused in this study are narcissism, locus of control and sustainability orientation.

This single case study involves Essentia Dimora Rurale, a small agritourism business, located in Molise (Italy), characterised by a sustainable business model that generates value for the local environment, thus revitalising abandoned territories. Data are collected using qualitative and quantitative methods and are analysed using the Gioia methodology.

The Essentia Dimora Rurale's approach is rooted in the concept of sustainability and the development of tourism in the territory. The preservation of traditional values and the creation of a network allow the firm to prosper and survive. The personalities of the two sibling entrepreneurs fuel the process, and the authors show that each personality trait plays a different role in each phase of the firm's growth.

From a theoretical point of view, the study contributes to entrepreneurial, sustainability and personality literature. However, using a single case study can represent a limit for the research.

Various practical implications are recognised concerning several stakeholders, such as the owners and the entities linked to the regional promotion and tourism sectors.

The novelty of the research relies on the importance of entrepreneur opportunity identification, particularly in sustainable firms. Moreover, the authors fill the literature gap investigating the impact of three personality traits in this process.

This study aims to provide an in-depth understanding of investors’ cognition and decision-making process with regard to internet financial products. The objective is to effectively guide users’ rational investments.

First, based on grounded theory, this study develops a tool for measuring users’ perceived value (PV) of internet financial products via in-depth interviews. Then, after comprehensively considering users’ environmental, individual and psychological characteristics, this study proposes a theoretical model of internet financial product investment decisions based on the PV of users. Finally, an empirical study is conducted on 693 valid sample data from e-commerce and online banking financial platforms.

The empirical results suggest that network externalities influence users’ financial behavior by herding (HE) (imitating others and discounting their own information) and PV. PV and HE are key factors in users’ investment decisions with regard to internet financial products. Moreover, users’ self-efficacy (SE) and platform type play moderate roles in the influence mechanism.

The research conclusions provide valuable references for designing financial products and establishing regulatory rules, which will help the internet financial industry to grow soundly and innovatively.

This study uncovers the mediating effect of HE and PV between network externalities and users’ investment intentions in the context of internet financial products. In addition, the moderating effect of users’ SE and platform types is revealed.

The purpose of this paper is to provide an outline of the major contributions in the literature on the determination of the least distance in data envelopment analysis (DEA). The focus herein is primarily on methodological developments. Specifically, attention is mainly paid to modeling aspects, computational features, the satisfaction of properties and duality. Finally, some promising avenues of future research on this topic are stated.

DEA is a methodology based on mathematical programming for the assessment of relative efficiency of a set of decision-making units (DMUs) that use several inputs to produce several outputs. DEA is classified in the literature as a non-parametric method because it does not assume a particular functional form for the underlying production function and presents, in this sense, some outstanding properties: the efficiency of firms may be evaluated independently on the market prices of the inputs used and outputs produced; it may be easily used with multiple inputs and outputs; a single score of efficiency for each assessed organization is obtained; this technique ranks organizations based on relative efficiency; and finally, it yields benchmarking information. DEA models provide both benchmarking information and efficiency scores for each of the evaluated units when it is applied to a dataset of observations and variables (inputs and outputs). Without a doubt, this benchmarking information gives DEA a distinct advantage over other efficiency methodologies, such as stochastic frontier analysis (SFA). Technical inefficiency is typically measured in DEA as the distance between the observed unit and a “benchmarking” target on the estimated piece-wise linear efficient frontier. The choice of this target is critical for assessing the potential performance of each DMU in the sample, as well as for providing information on how to increase its performance. However, traditional DEA models yield targets that are determined by the “furthest” efficient projection to the evaluated DMU. The projected point on the efficient frontier obtained as such may not be a representative projection for the judged unit, and consequently, some authors in the literature have suggested determining closest targets instead. The general argument behind this idea is that closer targets suggest directions of enhancement for the inputs and outputs of the inefficient units that may lead them to the efficiency with less effort. Indeed, authors like Aparicio et al. (2007) have shown, in an application on airlines, that it is possible to find substantial differences between the targets provided by applying the criterion used by the traditional DEA models, and those obtained when the criterion of closeness is utilized for determining projection points on the efficient frontier. The determination of closest targets is connected to the calculation of the least distance from the evaluated unit to the efficient frontier of the reference technology. In fact, the former is usually computed through solving mathematical programming models associated with minimizing some type of distance (e.g. Euclidean). In this particular respect, the main contribution in the literature is the paper by Briec (1998) on Hölder distance functions, where formally technical inefficiency to the “weakly” efficient frontier is defined through mathematical distances.

All the interesting features of the determination of closest targets from a benchmarking point of view have generated, in recent times, the increasing interest of researchers in the calculation of the least distance to evaluate technical inefficiency (Aparicio et al., 2014a). So, in this paper, we present a general classification of published contributions, mainly from a methodological perspective, and additionally, we indicate avenues for further research on this topic. The approaches that we cite in this paper differ in the way that the idea of similarity is made operative. Similarity is, in this sense, implemented as the closeness between the values of the inputs and/or outputs of the assessed units and those of the obtained projections on the frontier of the reference production possibility set. Similarity may be measured through multiple distances and efficiency measures. In turn, the aim is to globally minimize DEA model slacks to determine the closest efficient targets. However, as we will show later in the text, minimizing a mathematical distance in DEA is not an easy task, as it is equivalent to minimizing the distance to the complement of a polyhedral set, which is not a convex set. This complexity will justify the existence of different alternatives for solving these types of models.

As we are aware, this is the first survey in this topic.

The purpose of this study is to analyze the environmental efficiency level and trend of the transportation sector in the upper–mid–downstream of the Yangtze River Economic Belt and the JingJinJi region in China and assess the effectiveness of policies for protecting the low-carbon environment.

This study uses the meta-frontier slack-based measure (SBM) approach to evaluate environmental efficiency, which targets and classifies specific regions into regional groups. First, this study employs the SBM with the undesirable outputs to construct the environmental efficiency measurement models of the four regions under the meta-frontier and group frontiers, respectively. Then, this study uses the technology gap ratio to evaluate the gap between the group frontier and the meta-frontier.

The analysis reveals several key findings: (1) the JingJinJi region and the downstream of the YEB had achieved the overall optimal production technology in transportation than the other two regions; (2) significant technology gaps in environmental efficiency were observed among these four regions in China; and (3) the downstream region of the YEB exhibited the lowest levels of energy consumption and excessive CO₂ emissions.

To evaluate the differences in environmental efficiency resulting from regions and technological gaps in transportation, this study employs the meta-frontier model, which overcomes the limitation of traditional environmental efficiency methods. Furthermore, in the practical, the study provides the advantage of observing the disparities in transportation efficiency performed by the Yangtze River Economic Belt and the Beijing–Tianjin–Hebei regions.

The entrepreneurial capability (EC) environment refers to the general social and economic settings of a given local/regional entrepreneurship environment. The primary purpose of this study is to uncover key indicators of the EC milieu and test these components empirically within the context of the Association of South East Asian Nations (ASEAN)-5 economies to elucidate the current state of their EC environments, at the regional and national levels. To this end, the aim of this study is twofold. First, this work endeavors to explicate the determinants of EC, with aims of elucidating its association to commercial opportunities in (ASEAN)-5 economies, namely, Indonesia, Malaysia, the Philippines, Singapore and Thailand. Next, this study applies the developed theory, including the identified determinants of EC to empirically test the efficiency and imperative coefficients of variables that have an impact on perceived entrepreneurial capabilities within a given environment.

This research applies two frontier models, namely, the consistent estimation of fixed-effects and linear transformation stochastic frontier models, to assess the coefficients of significant EC variables for the panel sample. Data corresponding to the assessed variables were retrieved from the databases of the Global Entrepreneurship Monitor (GEM) – 2016 and the World Competitiveness Yearbook (WCY) – 2016, for the period, 2010-2016.

The attained results suggest that factors corresponding to the variables “Entrepreneurship as a good career choice” and “perceived opportunities” have played a significantly positive role on the EC environment of ASEAN 05, although findings suggest both factors may still be improved upon. Conversely, the “fear of failure rate” factor was shown to have exerted a negative impact on the efficiency of the EC environment of ASEAN 05. Other important variables – such as intellectual property rights, university education and knowledge transfer rate – were shown to generate a positive impact on the EC environment of these economies.

This study makes an important contribution to the entrepreneurship literature and can stimulate policymakers to rethink the EC settings of ASEAN-05 in their pursuit of an innovation-driven region.