Network consumption demand analysis and structure optimization based on big data Article Swipe
Juanxia Zhao
,
Chunhong Zhu
,
Yanmin Huang
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/1800/1/012013
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/1800/1/012013
By studying the role and architecture of big data analysis, it is clear that it has a huge supporting role in analyzing customer behavior trajectory, discovering customer consumption habits and preferences, improving online consumption experience and promoting business decision-making. The big data analysis combined with scenario analysis can avoid the misreading of data analysis; strengthen the prediction ability of big data analysis, so as to create a truly satisfying customer experience. Based on the analysis and structure optimization of big data network consumption demand, the whole process network consumption experience theoretical model includes the experience demand model and experience behavior model. In order to deal with a large number of various types of data effectively, enterprises need to master the technology and ability of big data analysis. For online consumption platform enterprises, the most important consideration in the process of delivering customer experience is the customer group and customer needs and motivation, as well as customer perception of product and service experience process.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/1800/1/012013
- OA Status
- diamond
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- OpenAlex ID
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https://openalex.org/W3135548701Canonical identifier for this work in OpenAlex
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https://doi.org/10.1088/1742-6596/1800/1/012013Digital Object Identifier
- Title
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Network consumption demand analysis and structure optimization based on big dataWork title
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articleOpenAlex work type
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enPrimary language
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2021Year of publication
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2021-02-01Full publication date if available
- Authors
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Juanxia Zhao, Chunhong Zhu, Yanmin HuangList of authors in order
- Landing page
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https://doi.org/10.1088/1742-6596/1800/1/012013Publisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.1088/1742-6596/1800/1/012013Direct OA link when available
- Concepts
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Big data, Consumption (sociology), Computer science, Process (computing), Service (business), Consumer behaviour, Product (mathematics), Customer intelligence, Data science, Customer retention, Marketing, Service quality, Business, Data mining, Geometry, Social science, Sociology, Mathematics, Operating systemTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2022: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.whole | 86 |
| abstract_inverted_index.create | 66 |
| abstract_inverted_index.demand | 96 |
| abstract_inverted_index.habits | 29 |
| abstract_inverted_index.master | 119 |
| abstract_inverted_index.model. | 101 |
| abstract_inverted_index.number | 109 |
| abstract_inverted_index.online | 33, 129 |
| abstract_inverted_index.ability | 58, 123 |
| abstract_inverted_index.demand, | 84 |
| abstract_inverted_index.network | 82, 88 |
| abstract_inverted_index.process | 87, 139 |
| abstract_inverted_index.product | 159 |
| abstract_inverted_index.service | 161 |
| abstract_inverted_index.various | 111 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.analysis | 43, 47, 75 |
| abstract_inverted_index.behavior | 24, 100 |
| abstract_inverted_index.business | 38 |
| abstract_inverted_index.combined | 44 |
| abstract_inverted_index.customer | 23, 27, 70, 142, 146, 149, 156 |
| abstract_inverted_index.includes | 93 |
| abstract_inverted_index.platform | 131 |
| abstract_inverted_index.process. | 163 |
| abstract_inverted_index.scenario | 46 |
| abstract_inverted_index.studying | 2 |
| abstract_inverted_index.analysis, | 10, 62 |
| abstract_inverted_index.analysis. | 127 |
| abstract_inverted_index.analysis; | 54 |
| abstract_inverted_index.analyzing | 22 |
| abstract_inverted_index.important | 135 |
| abstract_inverted_index.improving | 32 |
| abstract_inverted_index.promoting | 37 |
| abstract_inverted_index.structure | 77 |
| abstract_inverted_index.delivering | 141 |
| abstract_inverted_index.experience | 35, 90, 95, 99, 143, 162 |
| abstract_inverted_index.misreading | 51 |
| abstract_inverted_index.perception | 157 |
| abstract_inverted_index.prediction | 57 |
| abstract_inverted_index.satisfying | 69 |
| abstract_inverted_index.strengthen | 55 |
| abstract_inverted_index.supporting | 19 |
| abstract_inverted_index.technology | 121 |
| abstract_inverted_index.consumption | 28, 34, 83, 89, 130 |
| abstract_inverted_index.discovering | 26 |
| abstract_inverted_index.enterprises | 116 |
| abstract_inverted_index.experience. | 71 |
| abstract_inverted_index.motivation, | 152 |
| abstract_inverted_index.theoretical | 91 |
| abstract_inverted_index.trajectory, | 25 |
| abstract_inverted_index.architecture | 6 |
| abstract_inverted_index.effectively, | 115 |
| abstract_inverted_index.enterprises, | 132 |
| abstract_inverted_index.optimization | 78 |
| abstract_inverted_index.preferences, | 31 |
| abstract_inverted_index.consideration | 136 |
| abstract_inverted_index.decision-making. | 39 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5072944873 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I198091727 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.47999998927116394 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile.value | 0.51152406 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |