Decision support and intelligent systems in the textile and apparel supply chain: An academic review of research articles

This article provides a comprehensive review of research articles related to the application of decision support and intelligent systems in the textile and apparel supply chains. Data were obtained from 77 articles published from 1994 to 2009 in 35 journals. The articles were categorized according to their applicability into three basic sectors – textile production, apparel manufacture, and distribution/sales. They were further categorized into 16 subsectors based on their operational and management/control processes. A comprehensive list of categorized journal articles identified in this study provides insights and relevant references for both researchers and practitioners on the application of decision support and intelligent systems to various stages of a textile and apparel supply chain. In light of the developed classification framework, we identify gaps in extending the use of the decision support and artificial intelligent systems in the industry and suggest potential and applicable research areas for further consideration in this subject area.     

Visual analysis of machine learning methods in the field of ergonomics — Based on Cite Space V

To analyze the research hotspots on the application of machine learning methods in the field of ergonomics, we collected 1141 articles related to machine learning methods in the field of ergonomics from 2014 to 2021 on the Web of Science (WoS) database. Then we used Cite Space V 6.1. R2 to generate network maps and analyze the authors, institutions, countries, co-cited literature, and keywords. Results show that the correlation between authors in the formed author co-occurrence network is not strong, which indicates low cooperation among authors. In the analysis of research institutions, the University of Southampton is the most frequently cited literature in the United Kingdom. However, the US is leading in the country's co-occurrence network. “System” and “Model” are the top two cited keywords, while “Methodology” and “Decision-making” were active from 2015 to 2018, with a longer development time. Other keywords, including “Musculoskeletal disorders”, “Performance”, “Low back pain”, “Health”, and “Risk Factors”, are the most frequently cited keywords and have a high betweenness centrality. “Validation” and “Prediction” have recently become popular keywords in this field. Therefore, we conclude that the application of machine learning methods in the field of ergonomics will continue to increase year by year and that the development of machine learning methods in the field of ergonomics is gaining importance due to its cross-disciplinary nature. In ergonomics, machine learning methods will be further developed and widely used.     

Electronic supply chains: Status & perspective

The area of e-commerce based supply chains (or e-supply chains) has received significant attention in the last two decades. Despite the high level of activity, the most recent reviews on this topic date back to the beginning of this century. In this paper, we analyzed the state of e-supply chain research published during January 2000–January 2015 AD, covering 165 articles from 47 ISI indexed journals. The analysis is performed using a five-dimensional framework comprising Topic-of-Study, Unit-of-Analysis, Research Perspective, Industry Type, and Research Method. Within these dimensions, Topic-of-Study plays a pivotal role, whereas the other four dimensions are analyzed around its sub-classification scheme. Our main objective is to establish a broader interdisciplinary understanding of the e-supply chain research domain, and to identify trends and gaps in contemporary e-supply chain theory and practice. The findings indicate that problems are addressed from different perspectives with varying levels of interest from researchers belonging to several academic disciplines including business, economics, engineering and social sciences. Our analysis also identified two distinct periods (2000–2006 and 2007 onwards) with different foci of research attention. The problems that received significant attention in the earlier period include innovation, adoption and barriers, and supply chain integration; while in the latter period, the focus seemed to have shifted towards supply chain integration and collaboration issues. Problems that received minimum interest across the two periods include customer relationship, economic and environmental impact.     

Speech emotion recognition research: an analysis of research focus

This article analyses research in speech emotion recognition (“SER”) from 2006 to 2017 in order to identify the current focus of research, and areas in which research is lacking. The objective is to examine what is being done in this field of research. Searching on selected keywords, we extracted and analysed 260 articles from well-known online databases. The analysis indicates that SER research is an active field of research, dozens of articles being published each year in journals and conference proceedings. The majority of articles concentrate on three critical aspects of SER, namely (1) databases, (2) suitable speech features, and (3) classification techniques to maximize the recognition accuracy of SER systems. Having carried out association analysis of the critical aspects and how they influence the performance of the SER system in term of recognition accuracy, we found that certain combination of databases, speech features and classifiers influence the recognition accuracy of the SER system. We have also suggested aspects of SER that could be taken into consideration in future works based on our review.     

Fragmentation or cohesion? Visualizing the process and consequences of information system diversity, 1993–2012

In information systems (IS) literature, there is ongoing debate as to whether the field has become fragmented and lost its identity in response to the rapid changes of the field. The paper contributes to this discussion by providing quantitative measurement of the fragmentation or cohesiveness level of the field. A co-word analysis approach aiding in visualization of the intellectual map of IS is applied through application of clustering analysis, network maps, strategic diagram techniques, and graph theory for a collection of 47,467 keywords from 9551 articles, published in 10 major IS journals and the proceedings of two leading IS conferences over a span of 20 years, 1993 through 2012. The study identified the popular, core, and bridging topics of IS research for the periods 1993–2002 and 2003–2012. Its results show that research topics and subfields underwent substantial change between those two periods and the field became more concrete and cohesive, increasing in density. Findings from this study suggest that the evolution of the research topics and themes in the IS field should be seen as part of the natural metabolism of the field, rather than a process of fragmentation or disintegration.     

What does existing NeuroIS research focus on?

NeuroIS is a research field in which neuroscience theories and tools are used to better understand information systems phenomena. At present, NeuroIS is still an emerging field in information systems, and the number of available studies is limited. Because researchers who plan or execute NeuroIS research need to understand the status of the existing empirical research published in relevant journals, we have analyzed 78 empirical articles and put forward an integrative framework for understanding what existing NeuroIS research focuses on. Our framework is built upon stimulus–organism–response theory, which explains that stimulus factors can affect users’ psychological processes, which further lead to their responses. Then, we review the collected articles and summarize their findings to give more details of NeuroIS studies. Through this literature review, we identify several opportunities for future NeuroIS research in terms of influencing factors, measurement instruments, and subjects. We believe that our work will provide some meaningful insight for future NeuroIS research.     

1989-2020年中国互动行为研究特征与演进趋势——基于CiteSpace知识图谱分析

借助CiteSpace软件,选取CNKI中文核心期刊、CSSCI来源期刊和中国硕博士学位论文全文数据库,对1989-2020年间我国互动行为1198篇文献分析发现:(1)我国互动行为领域研究经历了萌芽期、稳步上升期和快速增长期;(2)文献发表的期刊较为丰富,核心作者群贡献较小且着眼于不同情境下的互动行为研究,尚未形成广泛的学术共识;(3)研究机构主要集中在高校和研究院所等机构,大部分处于相对独立的研究状态,科研能力差异不大;(4)研究视角趋向多元化和多学科交叉,弗兰德斯互动分析系统、师生言语互动、新手型教师和互动仪式链等可能成为未来的研究热点。后疫情时代下互动行为的形式、途径和频率等迅速发生改变,研究趋势也将随之发生转变。     

Review of supply chain performance measurement systems: 1998–2015

In today’s competitive business environment, supply chain performance is one of the most critical issues in various industries. It is argued that supply chain performance measurement is fundamental to efficient supply chain management. Over the past two decades, several frameworks and systems have been developed to meet this need. This study reviews the literature in the field of supply chain performance measurement and assembles an overview of those systems, approaches, techniques and criteria. For this purpose, 83 of 374 related articles from 1998 to 2015 were selected for final review using the Scopus and ISI databases. Findings disclose that performance measurement in supply chain contexts is still a fruitful area of research. The study also provides an overview of the performance measures employed in supply chain systems. These findings present a solid basis for future academic and practitioner work in the field of supply chain performance measurement.     

Information systems outsourcing: A literature analysis

Outsourcing has become one of the strategies adopted by businesses to manage their IS. During the last few years, the use of outsourcing has resulted in an increase in the volume of literature devoted to it. We decided therefore to analyse the literature with the aim of identifying the main topics, the methodologies most often applied and the authors and countries that have contributed most to the area of IS outsourcing. We also intended to offer suggestions on improving research in this field. The paper thus provides a review of articles about IS outsourcing published in the most prestigious journals of the IS area and journals of Management or Business.     

Analysis of keyword networks in MIS research and implications for predicting knowledge evolution

New concepts and ideas build on older ones. This path dependence in knowledge evolution has promoted research to identify important knowledge elements, research trends, and opportunities by analyzing publication data. In our study, keyword networks formed from published academic articles were analyzed to examine how keywords are associated with each other and to identify important keywords and their change over time. Based on MIS publication data from 1999 to 2008, our analysis provided several notable findings. First, while the MIS field has changed rapidly, resulting in many new keywords, the connectivity among them is highly clustered. Second, the keyword networks show clear power-law distribution, which implies that the more popular a keyword, the more likely it is selected by new researchers and used in follow-on studies. In addition, a strong hierarchical structure is identified in the network. Third, the network-based perspective reveals interdisciplinary keywords which are different from popular ones and have the potential to lead research in the MIS field.     

Citation analysis and bibliometric approach for ant colony optimization from 1996 to 2010

To build awareness of the development of ant colony optimization (ACO), this study clarifies the citation and bibliometric analysis of research publications of ACO during 1996-2010. This study analysed 12,960 citations from a total of 1372 articles dealing with ACO published in 517 journals based on the databases of SCIE, SSCI and AH&CI, retrieved via the Web of Science. Bradford Law and Lotka’s Law, respectively, examined the distribution of journal articles and author productivity. Furthermore, this study determines the citation impact of ACO using parameters such as extent of citation received in terms of number of citations per study, distribution of citations over time, distribution of citations among domains, citation of authors, citation of institutions, highly cited papers and citing journals and impact factor of 12,960 citations. This study can help researchers to better understand the history, current status and trends of ACO in the advanced study of it.     

Innovation research in information systems: A commentary on contemporary trends and issues

There is a need to unify the different strands of innovation research in information systems (IS) literature. We analyze 113 articles published over the past 15 years in top 10 IS journals. We classify the literature by (a) using the overall process spectrum of conceptualization from its innovation to its diffusion and (b) using the various theories of innovation referred to and validated in the articles. We identify that innovation diffusion theory is the most popular theory used by researchers. We conclude that future research must focus on the conceptualization and the generation phase of innovation through exploratory or empirical studies.     

区块链文献主题发现及演化研究

对区块链文献进行统计及可视化研究有助于发现区块链的研究热点、研究领域和演化趋势。在中国知网检索主题为“区块链”的核心期刊论文,获取文献1 216篇,对这些文献的发文量、发文机构、作者共现、重要文献引用情况等进行统计分析,了解区块链研究现状;利用CiteSpace进行可视化分析,从关键词、时区分布等展现区块链的研究热点和演化情况;从区块链思想、核心技术和应用领域等三个维度进行讨论。研究表明：区块链文献近年呈爆发趋势,涉及学科多样化;热点主题主要集中于智能合约、金融科技、数字货币、电子政务等领域;区块链应用已经延伸到多个学科和领域,成为下一代信息革命的主要支撑技术,促进了新兴技术的融合与发展。     

企业档案信息化研究文献统计分析

企业档案信息化是企业档案工作的重要组成部分,文章以知网期刊文献为样本,从学科类别、研究层次、期刊名称、发表年度、作者、作者单位、关键词等方面,对历年来有关企业档案信息化研究文献进行统计分析。     

Exploring the Ordered Weighted Averaging Operator Knowledge Domain: A Bibliometric Analysis

Ordered weighted averaging (OWA) operator has been received increasingly widespread interest since its appearance in 1988. Recently, a topic search with the keywords “ordered weighted averaging operator” or “OWA operator” on Web of Science (WOS) found 1231 documents. As the publications about OWA operator increase rapidly, thus a scientometric analysis of this research field and discovery of its knowledge domain becomes very important and necessary. This paper studies the publications about OWA operator between 1988 and 2015, and it is based on 1213 bibliographic records obtained by using topic search from WOS. The disciplinary distribution, most cited papers, influential journals, as well as influential authors are analyzed through citation and cocitation analysis. The emerging trends in OWA operator research are explored by keywords and references burst detection analysis. The research methods and results in this paper are meaningful for researchers associated with OWA operator field to understand the knowledge domain and establish their own future research direction.     

代码搜索与API推荐文献分析

代码搜索和API推荐算法能够帮助开发者有效实现编程任务。截至目前,研究者们发表了一系列相关文献。尽管一些学者对该研究领域的背景和研究现状进行了阐述,但是研究者对该领域中的一些基本领域知识还 缺乏了解,如最高产的作者、机构和国家,影响力较大的作者和文献,以及流行的热点研究等。借助经典的文献分析框架,在构建该研究领域文献数据仓库的基础上,首次对该领域的研究进行了基础文献分析和合作模式探索。 一方面,基础文献分析的结果表明,近几年越来越多的研究者开始关注该领域的研究,最高产的作者是Cristina Videira Lopes,University of California at Irvine是发表相关文献最多的机构,大部分文献来自美国,根据领域H因子计算得到的最有影响力的作者是Denys Poshyvanyk。另一方面,合作模式的分析结果显示,Tao Xie,Cristina Videira Lopes 和 Denys Poshyvany是该领域最活跃的三位作者,推荐算法性能的提升及其在软件工程任务中的应用是目前该领域最流行的研究主题。     

MIS research strategies

Different strategies for conducting empirical research in the Management Information Systems (MIS) field are discussed. Strategies employed in 532 MIS articles published in 15 journals during the 1970–1979 time period are analyzed. The trends are analyzed over the ten year period with respect to the differences between articles authored by practitioners and academic, differences between articles that are cited frequently versus infrequently, and the relationship with the type of research conducted.The analysis points out that more than two thirds of published MIS research by either academicians or practitioners had utilized non-empirical approaches and focused on a single variable. Case studies are the most commonly employed empirical strategy and most studies do not measure the impact of independent variables on the process of using developing, or operating information systems. The analysis suggests that MIS journal articles employing empirical research strategies are cited more frequently than nonempirical ones.     

中文歧义研究25年——以《中文信息学报》论文为例

过去的25年间中文信息处理领域的歧义研究取得了长足进步,涌现出大量科研成果。该文试图以中国中文信息学会会刊《中文信息学报》刊载的论文为例,着重从研究对象和研究方法两个方面观察探讨歧义研究的进展、特点和大体趋势。文章分时间段从多个角度对中文歧义研究进行定量统计分析,述评结合,针对歧义研究的现状提出了建议。     

Application of evolutionary computation for rule discovery in stock algorithmic trading: A literature review

Despite the wide application of evolutionary computation (EC) techniques to rule discovery in stock algorithmic trading (AT), a comprehensive literature review on this topic is unavailable. Therefore, this paper aims to provide the first systematic literature review on the state-of-the-art application of EC techniques for rule discovery in stock AT. Out of 650 articles published before 2013 (inclusive), 51 relevant articles from 24 journals were confirmed. These papers were reviewed and grouped into three analytical method categories (fundamental analysis, technical analysis, and blending analysis) and three EC technique categories (evolutionary algorithm, swarm intelligence, and hybrid EC techniques). A significant bias toward the applications of genetic algorithm-based (GA) and genetic programming-based (GP) techniques in technical trading rule discovery is observed. Other EC techniques and fundamental analysis lack sufficient study. Furthermore, we summarize the information on the evaluation scheme of selected papers and particularly analyze the researches which compare their models with buy and hold strategy (B&H). We observe an interesting phenomenon where most of the existing techniques perform effectively in the downtrend and poorly in the uptrend, and considering the distribution of research in the classification framework, we suggest that this phenomenon can be attributed to the inclination of factor selections and problem in transaction cost selections. We also observe the significant influence of the transaction cost change on the margins of excess return. Other influenced factors are also presented in detail. The absence of ways for market trend prediction and the selection of transaction cost are two major limitations of the studies reviewed. In addition, the combination of trading rule discovery techniques and portfolio selection is a major research gap. Our review reveals the research focus and gaps in applying EC techniques for rule discovery in stock AT and suggests a roadmap for future research.