A Visualization Method of the Economic Input–Output Table: Mapping Monetary Flows in the Form of Sankey Diagrams

Chong, Chinhao; Zhang, Xi; Kong, Geng; Ma, Linwei; Li, Zheng; Ni, Weidou; Yu, Eugene-Hao-Chen

doi:10.3390/su132112239

Cited by 10 publications

(5 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After obtaining the answers to the research questions, they are presented in a Sankey diagram. Some publications that visualize Sankey diagrams include [19], [20]. For this purpose, the remainder of this paper is structured as follows.…”

Section: Introductionmentioning

confidence: 99%

Supply chain strategy during the COVID-19 terms: sentiment analysis and knowledge discovery through text mining

Zuhanda

Anisa

Desniarti

et al. 2023

IJEECS

View full text Add to dashboard Cite

The coronavirus pandemic has affected not only health but also the economy. The use of big data in finding information can be used to gain profits that logistics companies can utilize to survive during the pandemic. This study conducted text-mining research on service consultant sites in the logistics sector. This study aims to present frequency diagrams, analyze sentiment using the National Research Council (NRC) lexicon, present bigrams, and seek knowledge about strategies to minimize shipping costs and maintain inventories of manufactured goods. The words "supply", "chain", and "COVID-19" are words that are used frequently throughout the article. The results of this study showed that the words that often appear from word excavation are the words "supply", "chain", "logistics", "kpis," and "inventory". Then emotion trust becomes an emotional word that often appears in articles. The words "Supply" and "pandemic" are the words that seem the most positive and negative words, respectively. The words "COVID-19", "safety stock", and "inventory management" are words that often appear together. The result of discovery knowledge is that logistics consultants offer emotions of trust and provide many insights on minimizing shipping costs and maintaining inventory during a pandemic.

show abstract

Section: Introductionmentioning

confidence: 99%

Supply chain strategy during the COVID-19 terms: sentiment analysis and knowledge discovery through text mining

Zuhanda

Anisa

Desniarti

et al. 2023

IJEECS

View full text Add to dashboard Cite

show abstract

“…The input–output model, originating from economics, is applied in the field of embodied carbon due to the advantages of coping with the complicated network data structures [ 63 ]. There are several key nodes of empirical studies and cases studies on CF accounting in the co-citation network.…”

Section: Resultsmentioning

confidence: 99%

Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis

Han

Tan

Chen

et al. 2022

IJERPH

View full text Add to dashboard Cite

Reducing the effect of mankind’s activities on the climate and improving adaptability to global warming have become urgent matters. The carbon footprint (CF), derived from the concept of ecological footprint, has been used to assess the threat of climate change in recent years. As a “top to bottom” method, input–output analysis (IOA) has become a universally applicable CF assessment tool for tracing the carbon footprint embodied in economic activities. A wide range of CF studies from the perspective of the IOA model have been presented and have made great progress. It is crucial to have a better understanding of what the relevant research focuses on in this field, yet so far a systematic synopsis of the literature is missing. The purpose of this paper is to explore the knowledge structure and frontier trends in respect of the IOA model applied to CF research using scientometric visualization analysis. The main findings of this paper are as follows. (1) Published articles show a two-stage increase in the period 2008 to 2021, and present a complex academic network of countries, authors, and institutions in this important domain. (2) The classic studies are mainly divided into three categories: literature reviews, database application introduction, and CF accounting in different scales. (3) The research hotspots and trends show that the research scales tend to be more microscopic and applications of models tend to be more detailed. In addition, supply-chain analysis and driver-factor analysis will probably become the main research directions in the future.

show abstract

“…13, No. 1, March 2024: 63-72 66 connections between the attractions and tourist sentiments, for mapping input-output flow or linkage between two related or juxtaposed concepts [23].…”

Section: Methodsmentioning

confidence: 99%

Artificial intelligence assisted insights into Bali’s destination image: sentiment and thematic analyses of TripAdvisor reviews

Susanto,

Gunawan,

Widarnandana

2024

IJAAS

View full text Add to dashboard Cite

<p><span>This study applies sentiment and thematic content analyses based on natural language processing (NLP) to gain valuable insights into the perceived image of Bali as a tourist destination. This study addresses the gap in how to realize the benefits of big data analytics in applied research, by using more approachable tools for researchers with limited programming skills and coding experience. A total of 6,800 TripAdvisor reviews of Bali’s top 12 tourist attractions between May 2019 and April 2023 were scrapped. The authors used Bardeen.ai for data mining and Atlas.ti for qualitative data analyses. Sentiment analysis revealed an overwhelmingly positive sentiment (70.4%) towards Bali’s tourist attractions, indicating a positive destination image. Post-pandemic tourists tend to express more positive sentiments in their reviews compared to pre-pandemic. Thematic content analysis indicated that positive sentiments are strongly related to satisfaction, positive experiences, enjoyment, and excitement, while environmental concerns and dissatisfaction are potentially harmful to Bali’s destination image. The study provides valuable insights into tourists’ emotional sentiments, perceptions, and thematic patterns of behavior, which can inform tourism marketers and destination strategists, and contribute to the larger discussion of utilizing big data analytics in tourism marketing research.</span></p>

show abstract

A Visualization Method of the Economic Input–Output Table: Mapping Monetary Flows in the Form of Sankey Diagrams

Cited by 10 publications

References 37 publications

Supply chain strategy during the COVID-19 terms: sentiment analysis and knowledge discovery through text mining

Supply chain strategy during the COVID-19 terms: sentiment analysis and knowledge discovery through text mining

Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis

Artificial intelligence assisted insights into Bali’s destination image: sentiment and thematic analyses of TripAdvisor reviews

Contact Info

Product

Resources

About