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無線感測網路（ZIGBEE）文獻發展的趨勢、類別與熱點之探討－使用文獻內容書目對與共現字以發掘研究問題的機會
EXPLORING AMONG TRENDS, CLUSTERS AND HOT TOPICS OF WIRELESS SENSOR NETWORKS (ZIGBEE) - USING BIBLIOGRAPHIC COUPLING AND CO-WORD FOR RESEARCH QUESTIONS
魏淑娟
朝陽科技大學產業策略發展博士候選人
李尚嬪
朝陽科技大學幼兒保育系助理教授級專案教師
陳悅琴
朝陽科技大學企管管理系副教授
賴奎魁
朝陽科技大學企業管理系特聘教授
Shu-Chuan Wei
Doctoral Candidate, Strategic Development of Taiwan’s Industry
Chaoyang University of Technology
Shang-Pin Li
Project Assistant Professor, Department of Early Childhood Development and Education
Chaoyang University of Technology
Yuen-Chin Chen
Associate Professor, Department of Business Administration
Chaoyang University of Technology
Kuei-Kuei Lai
Distinguished Professor, Department and Graduate Institute of Business Administration
Chaoyang University of Technology
摘要
無論是企業或學術界，不斷的創新是營運與學術生涯保鮮的根本。智慧街燈的發展是智慧城市中多議題中之一個有趣新興議題，在企業界與學術界永續發展的目標中，皆已投入甚多基礎與應用研究，研究成果首先皆已撰述論文或專利文件，投稿期刊或各國智慧財產專利局，歷經多位同儕盲目審查，經公開發表或取得核准且具排他權之著作權或專利。這些成果揭示與時俱進的新知識，為促進學術界與業界技術研發的快速擴散，皆已收錄在電子資料庫中，在學界，如WOS，Scopus，Elsevier；在業界如各國專利資料庫，如USPTO，EDO等。這些電子資料庫在顯示各種領域系統化知識，且已儼然成為全人類社會的資產。然在智慧街燈的研究與開發中，含有多項次技術領域，本研究旨在探討無線感測網路（ZIGBEE）論文科學性論文文獻計量分析。過去文獻停留在傳統調查性之質性內容分析或計算前後數年前間比率的簡易計量分析，顯然對投入學術與產業研究者所需精確專業領域資訊，付之闕如。若能採用使用文獻內容書目對及共現字之科學性計量分析以發掘研究問題的機會，如文獻發展的趨勢、類別與熱點等變項分析，應可提供創造一個新的有效性的研究問題來增強研發前沿的機會。
本研究目的在建立一個探討文獻內容發展的趨勢分析模型，並使用CATAR內容分析模型做為發掘無線感測網路（ZIGBEE）文獻發展的趨勢、類別與熱點分析。本研究的第一階段採用檢全原則，建立相關鍵字，進行檢索WOS資料庫，接者使用檢準原則，經過篩與資料清洗以取得具高效信度茲分析資料集。再以統計分析，來建構文獻內容的概觀模型。再使用文獻書目對與共現字之相似以形成相似矩陣，再以數與構面觀念，使用奇異值分解（Singular Value Decomposition, SVD）進行相似矩陣分析，再使用階層式凝聚合之完全連鎖法（Hierarchical-Agglomerative-Complete Clustering）集群分析方法以進行文獻的主題集群分析，再以HHI來鑑別出研究主題的熱點。
分析結果揭出期刊、國家、年代之發展趨勢之競爭態勢。另也區分出七個主題群與七個共現字群，且兩者間有很強的共通性，少數個獨特性。是故；此研究架構與流程能發掘研究的前沿（Frontier）之內在與外在效度。
關鍵字：無線感測網路（ZIGBEE）、趨勢、類別、熱點、概觀分析、書目對、共現字
ABSTRACT
Continuous innovation is the foundation of both business and academic career preservation. The development of smart street lights is becoming one of the most interesting modernization tools in smart cities. A lot of basic and applied research has been invested in achieving sustainable development in business and academic circles. The results of these studies have been published in academic papers or patent documents, submitted to journals or intellectual property patent offices of various countries, and after blind review by many peers, they were published copyrights or the patents were approved with exclusive rights. These achievements revealed new knowledge that helped businesses to keep pace with the times. To promote the rapid diffusion of technology research and development, they have been included in the electronic databases of the academia, e.g., WOS, Scopus, and Elsevier, and in the industry, e.g., the national patent databases including USDTO and EDO. These electronic databases contain systematic knowledge in various fields and have become the assets of the entire human society. However, in the research and development of smart street lights, many technical fields can be found. The present study explores the bibliometric analysis of scientific papers on wireless sensor networks (ZIGBEE). In the past, the literature mainly focused on the traditional qualitative content analysis of investigative nature or simple quantitative analysis of calculating the ratio between the years and the years before and after, which lacked the accurate professional field information required by academic and industrial researchers. If the scientific quantitative analysis using bibliographic pairs and co-occurrence words of literature content can be used to explore opportunities for research problems, such as the analysis of variables including trends, categories, and hot topics of literature development, it could provide a new and effective research problem to enhance opportunities at the forefront of R&D.
The CATAR content analysis model was used to explore the trends, categories, and hot topics in the development of the wireless sensor network (ZIGBEE) literature. The first stage of this research adopted the principle of verification, established relevant keywords, searched the WOS database, and used the principle of verification to obtain a data set with high reliability after screening and data cleaning. Statistical analysis was then used to construct an overview model of the literature content. After, the similarities between bibliographic pairs and co-occurring words were identified to form a similarity matrix, and then reduce the variation.
Additionally, the number and aspect concept and the SVD (Singular Value Decomposition) were employed to conduct a similarity matrix analysis. Next, the Agglomerative Hierarchical Clustering method was used to perform a subject cluster analysis of the literature. Finally, the HHI was utilized to identify the hot topics of research themes.
The analysis results showed the competitive situation of the development trends of journals, countries, and years. In addition, seven theme groups and seven co-occurring word groups were distinguished, and it was found that there is a strong commonality between the two; however, a few are unique. Therefore, this research structure and the process could explore the internal and external validity of the research frontier.
Keywords: ZIGBEE, Trends, Clusters, Hot Topics, Overview Analysis, Bibliographic Coupling, Co-Word
建構社群產品購買討論與購後認知失調內容結構－以美妝產品為例
CONSTRUCTING KNOWLEDGE STRUCTURES OF CONSUMERS’ PURCHASE DISCUSSION AND RELATED COGNITIVE DISSONANCE FOR COSMETIC PRODUCTS IN VIRTUAL COMMUNITY
李來錫
國立屏東大學資訊管理系副教授
李羿晴
國立屏東大學資管系碩士班研究生
Lai-Hsi Lee
Associate Professor, Department of Information Management
National Pingtung University
Yi-Qing Lee
Graduate Student, Department of Information Management
National Pingtung University
摘要
隨著網路普及，有越來越多的虛擬社群開始分享使用各種產品的心得，消費者在購買前也會根據網友的分享資訊，再進行產品採購，因此這些分享資訊就成為相當重要的採購資訊。如果能夠將這些購買資訊加以整理，並以知識化概念呈現，將可以了解消費者對於美妝產品購買資訊的關聯程度，並協助廠商了解消費者相關行為。研究利用系統抽樣的方式抽取美妝YouTuber影片中的留言，共蒐集有效樣本2479筆，並用正規化概念分析整理出內容包含「產品名稱」、「產品品質」、「價格」、「購買地點」、「產品特色」、「使用情況」六種購買資訊之知識概念圖。研究結果顯示，除了「產品名稱」在留言時經常被提起外，「產品特色」和「使用情況」的資訊也經常被社群成員提出來分享。另外，本研究進一步進行消費者的認知失調研究，結果顯示最容易造成社群成員的認知失調起因為化妝成果，因此建議管理者可以加強將產品試用成果展示內容，以降低消費者的認知失調。
關鍵字：虛擬社群、正規化概念分析、認知失調
ABSTRACT
With the e-commerce expansion, people love to share and read purchase experience in virtual community. Those shared reviews become important resource of purchase information. If the information can be constructed by conceptual knowledge structure, it might help to understand consumers' perception and behavior toward purchase information. This study extracted discussion content from YouTubers’ channels and collected a total of 2,479 valid samples by systematic sampling. The knowledge structure of purchase information was produced into six classified items by formal concept analysis, including "Product Name", "Product Quality", "Price", "Purchase Location", "Product Features", and "Usage Conditions". The result shows that not only the "Product Name" is often mentioned in the comments, but also the items of "Product Features" and "Usage Conditions" are also mentioned frequently by community members. The study also conducts the further studies on cognitive dissonance for those who left purchase message. The findings show that main reason which most easily to cause cognitive dissonance is the "makeup performance". It is suggested that the pre-test of products should be well presented to reduce the possible cognitive dissonance.
Keywords: Virtual Community, Formal Concept Analysis, Cognitive Dissonance
探索人工智慧即服務產業的競爭優勢與策略
AN EMPIRICAL STUDY OF THE COMPETITIVE ADVANTAGE AND STRATEGY IN AIAAS INDUSTRY
林采一
國立陽明交通大學經營管理研究所在職專班碩士生
唐瓔璋
國立陽明交通大學經營管理研究所榮譽退休教授
王郁玫
靜宜大學企業管理學系助理教授
Tsai-I Lin
Master, Institute of Business and Management,
National Yang Ming Chiao Tung University
Ying-Chan Tang
Emeritus Professor, Institute of Business and Management,
National Yang Ming Chiao Tung University
Yu-Mei Wang
Assistant Professor, Department of Business Administration,
Providence University
摘要
面對超級競爭的市場環境，各企業尋求數位轉型與創新，AIaaS的商業模式應運而生。本研究欲了解原先雲端運算產業中提供IaaS、PaaS與SaaS商業模式的企業，面臨AI浪潮所帶來的產業競爭與環境改變，如何運用資源發展合適的經營策略並維持競爭優勢。研究對象以雲端運算服務產業中的公司為主，分析AIaaS產業族群的發展，與各公司的競爭優勢和策略。本研究利用Standard & Poor Compustat Capital IQ資料庫蒐集SIC Code為7370、7372、7374的公司，剔除資料遺漏或離群值，共篩選出110家企業，以修改後的杜邦恆等式10個財務指標作為企業績效的觀察變數。藉由因素分析的方法，萃取出「品牌資產管理能力」、「研發創新管理能力」、「客戶關係管理能力」、「產品銷售管理能力」和「資金利用管理能力」五大能力構面；再以每家企業所得之因素分數進行集群分析，並使具有相似資源構型的企業分類，得出「客戶管理導向」、「資產管理導向」、「均衡發展導向」和「穩健金流導向」四大策略群組；最後以構面縮減的方式得出AIaaS的策略主軸。本研究利用有形的財務資料推論無形的企業資源構型，找出競爭優勢與經營策略，希冀給相關產業業者在AI發展中找到利基點。
關鍵字：人工智慧、雲端運算、競爭優勢、資源構型、杜邦恆等式
ABSTRACT
Companies seek digital transformation and innovation in a hyper-competitive market environment, and the AIaaS business model has emerged. This study investigates how companies that initially provided IaaS, PaaS, and SaaS business models in the cloud computing industry face industrial competition and environmental changes brought about by the AI wave and how to use resources to develop appropriate business strategies to maintain competitive advantages. The samples of this study are companies in the cloud computing service industry and use the Standard & Poor Compustat Capital IQ database to collect companies with SIC Code 7370, 7372, 7374. By eliminating omissions or outliers, a total of 110 companies are selected. The ten financial indicators of the revised DuPont identity are used as the companies' performance. Using the method of factor analysis, the five capability aspects of "brand asset management capability," "R&D innovation management capability," "customer relationship management capability," "product sales management capability," and "fund utilization management capability" are extracted. The factor scores obtained by each company are analyzed in clusters, and companies with similar resource configurations are classified to obtain four major categories: "customer management orientation," "asset management orientation," "balanced development orientation," and "stable cash flow orientation" as strategy groups. Finally, the two axes of the AIaaS strategy are obtained by discriminant analysis. This study uses tangible financial data to infer the intangible corporate resource configuration, find out competitive advantages and business strategies, and find niche points for related industries in the development of AI.
Keywords: Artificial Intelligence, Cloud Computing, Competitive Advantage, Resource Configuration, DuPont Identity
給錢還是給關心？經濟不利或文化不利學生就學扶助措施效益分析－以經濟不利或文化不利學生身份別為干擾變項
FINANCIAL AIDS OR LIVING SUPPORT? LONGITUDINAL STUDY ON EDUCATION ASSISTANCE FOR SOCIOECONOMICALLY DISADVANTAGED STUDENTS AND ITS RELATIONSHIP WITH ACADEMIC PERFORMANCE - THE MODERATING ROLE OF STUDENTS’ BACKGROUND
留淑芳
國立高雄科技大學國際企業系副教授
鄭兆宏
國立高雄科技大學國際企業系副教授
Shu-Fang Liu
Associate Professor, Department of International Business,
National Kaohsiung University of Science and Technology
Zhao-Hong Cheng
Associate Professor, Department of International Business,
National Kaohsiung University of Science and Technology
摘要
就學輔助措施乃協助經濟不利學生及文化不利學生的重要方式。本研究目的在分析經濟不利學生及文化不利學生參與就學輔助措施（學雜費減免、獎助學金、社團參與及課後輔導）對學業表現影響差異。本研究蒐集四波追蹤資料共計有效樣本5,895筆，針對就學輔導措施影響經濟不利學生及文化不利學生之學習成效進行縱斷面分析，進一步比較不同身分別學生的差異。潛在曲線成長模型（Latent growth curve modeling）分析結果發現：(1)短期內，各種輔助措施顯著影響學生學習成績表現；(2)長期而言，課輔參與對學生學期成績變動呈正向關聯，獎助學金與學期成績變動則是負向關係；(3)經濟不利學生及文化不利學生身份別對於就學輔助措施對學期成績的影響具有顯著干擾效果。本研究結果可作為未來學術及實務建議。
關鍵字：經濟不利及文化不利學生、就學扶助措施、縱斷面研究、潛在曲線成長模型
ABSTRACT
Education assistance is an important mean to support socioeconomically disadvantaged students. The study aims to investigate the relationship between various assistances means (i.e., scholarships, tuition and miscellaneous fees exemption, extracurricular involvement and after-class tutoring) and the students’ academic performance by applying a longitudinal approach with four-wave panel sample data collected from 5,895 socioeconomically disadvantaged students. Data analysis was performed using the latent growth curve modeling (LGCM). In addition, different students’ background and their academic performances are further investigated. The main findings are as follows: (1) In the short term, various education assistances affect students’ academic performance; (2) In the long run, after-class tutoring is positively related to change in students’ semester grades, while scholarships are negatively related to change in semester grades; (3) The effect of assistance means on students’ academic performances is moderated by students’ different backgrounds. The study provides practical suggestions for both practitioners and future studies based on the results.
Keywords: Socioeconomically Disadvantaged Students, Education Assistance, Longitudinal Study, Latent Growth Curve Modeling (LGCM)
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