Risk Assessment of Live-Streaming Marketing Based on Hesitant Fuzzy Multi-Attribute Group Decision-Making Method Article Swipe
Changlu Zhang
,
Yuchen Wang
,
Jian Zhang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/jtaer20020120
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/jtaer20020120
(1) Background: With the deep integration of e-commerce and video technology, live-streaming marketing has emerged globally and maintained rapid growth. However, most of the current research on live-streaming e-commerce marketing focuses on merchants’ sales strategies and consumers’ purchase intentions, and there is relatively little research related to the risks of live-streaming e-commerce marketing. Nevertheless, with the development of live-streaming e-commerce marketing and its integration with technologies such as artificial intelligence and virtual reality (VR), live-streaming e-commerce marketing still faces challenges such as unclear subject responsibility, difficulty in verifying the authenticity of marketing information, and uneven product quality. It also harbors problems such as the ethical misbehavior of AI anchors and the excessive beautification of products by VR technology. (2) Methods: This study systematically analyzes the scenarios of live-streaming marketing to elucidate the mechanisms of risk formation. Utilizing fault tree analysis (FTA) and risk checklist methods, risks are identified based on the three core elements of live-streaming marketing: “people–products–scenes”. Subsequently, the Delphi method is employed to refine the initial risk indicator system, resulting in the construction of a comprehensive risk indicator system comprising three first-level indicators, six second-level indicators, and 16 third-level indicators. A hesitant fuzzy multi-attribute group decision-making method (HFMGDM) is then applied to calculate the weights of the risk indicators and comprehensively assess the live-streaming marketing risks in live broadcast rooms of three prominent celebrity anchors in China. Furthermore, a detailed analysis is conducted on the risks associated with the six secondary indicators. Based on the risk evaluation results, targeted recommendations are proposed. This study aims to enhance consumers’ awareness of risk prevention when conducting live-streaming transactions and pay attention to related risks, thereby safeguarding consumer rights and fostering the healthy and sustainable development of the live-streaming marketing industry. (3) Conclusions: The results show that the top five risk indicators in terms of weight ranking are: Ethical Risk of the AI Anchor (A4), VR Technology Promotion Risk (F3), Anchor Reputation (A1), Product Quality (D1), and Logistics Distribution Service Quality (D2). The comprehensive live-streaming marketing risk of each live broadcast room is Y > L > D. Based on the analysis results, targeted recommendations are provided for anchors, MCN institutions, merchants, supply chains, and live-streaming platforms to improve consumer satisfaction and promote sustainable development of the live-streaming marketing industry.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/jtaer20020120
- https://www.mdpi.com/0718-1876/20/2/120/pdf?version=1748761077
- OA Status
- gold
- Cited By
- 1
- References
- 38
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4410969271
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4410969271Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/jtaer20020120Digital Object Identifier
- Title
-
Risk Assessment of Live-Streaming Marketing Based on Hesitant Fuzzy Multi-Attribute Group Decision-Making MethodWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-06-01Full publication date if available
- Authors
-
Changlu Zhang, Yuchen Wang, Jian ZhangList of authors in order
- Landing page
-
https://doi.org/10.3390/jtaer20020120Publisher landing page
- PDF URL
-
https://www.mdpi.com/0718-1876/20/2/120/pdf?version=1748761077Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/0718-1876/20/2/120/pdf?version=1748761077Direct OA link when available
- Concepts
-
Group decision-making, Computer science, Group (periodic table), Fuzzy logic, Operations research, Artificial intelligence, Marketing, Business, Engineering, Psychology, Organic chemistry, Chemistry, Social psychologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
38Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4410969271 |
|---|---|
| doi | https://doi.org/10.3390/jtaer20020120 |
| ids.doi | https://doi.org/10.3390/jtaer20020120 |
| ids.openalex | https://openalex.org/W4410969271 |
| fwci | 7.48143426 |
| type | article |
| title | Risk Assessment of Live-Streaming Marketing Based on Hesitant Fuzzy Multi-Attribute Group Decision-Making Method |
| biblio.issue | 2 |
| biblio.volume | 20 |
| biblio.last_page | 120 |
| biblio.first_page | 120 |
| topics[0].id | https://openalex.org/T14139 |
| topics[0].field.id | https://openalex.org/fields/14 |
| topics[0].field.display_name | Business, Management and Accounting |
| topics[0].score | 0.9958999752998352 |
| topics[0].domain.id | https://openalex.org/domains/2 |
| topics[0].domain.display_name | Social Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1403 |
| topics[0].subfield.display_name | Business and International Management |
| topics[0].display_name | E-commerce and Technology Innovations |
| topics[1].id | https://openalex.org/T10609 |
| topics[1].field.id | https://openalex.org/fields/33 |
| topics[1].field.display_name | Social Sciences |
| topics[1].score | 0.9771000146865845 |
| topics[1].domain.id | https://openalex.org/domains/2 |
| topics[1].domain.display_name | Social Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/3312 |
| topics[1].subfield.display_name | Sociology and Political Science |
| topics[1].display_name | Digital Marketing and Social Media |
| topics[2].id | https://openalex.org/T10068 |
| topics[2].field.id | https://openalex.org/fields/18 |
| topics[2].field.display_name | Decision Sciences |
| topics[2].score | 0.9435999989509583 |
| topics[2].domain.id | https://openalex.org/domains/2 |
| topics[2].domain.display_name | Social Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1802 |
| topics[2].subfield.display_name | Information Systems and Management |
| topics[2].display_name | Technology Adoption and User Behaviour |
| is_xpac | False |
| apc_list.value | 1000 |
| apc_list.currency | CHF |
| apc_list.value_usd | 1082 |
| apc_paid.value | 1000 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 1082 |
| concepts[0].id | https://openalex.org/C20701700 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6488906145095825 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q388791 |
| concepts[0].display_name | Group decision-making |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.6433850526809692 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C2781311116 |
| concepts[2].level | 2 |
| concepts[2].score | 0.451670378446579 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q83306 |
| concepts[2].display_name | Group (periodic table) |
| concepts[3].id | https://openalex.org/C58166 |
| concepts[3].level | 2 |
| concepts[3].score | 0.44609761238098145 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q224821 |
| concepts[3].display_name | Fuzzy logic |
| concepts[4].id | https://openalex.org/C42475967 |
| concepts[4].level | 1 |
| concepts[4].score | 0.3725464344024658 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q194292 |
| concepts[4].display_name | Operations research |
| concepts[5].id | https://openalex.org/C154945302 |
| concepts[5].level | 1 |
| concepts[5].score | 0.3326456546783447 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[5].display_name | Artificial intelligence |
| concepts[6].id | https://openalex.org/C162853370 |
| concepts[6].level | 1 |
| concepts[6].score | 0.32472914457321167 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q39809 |
| concepts[6].display_name | Marketing |
| concepts[7].id | https://openalex.org/C144133560 |
| concepts[7].level | 0 |
| concepts[7].score | 0.28916722536087036 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q4830453 |
| concepts[7].display_name | Business |
| concepts[8].id | https://openalex.org/C127413603 |
| concepts[8].level | 0 |
| concepts[8].score | 0.1289220154285431 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[8].display_name | Engineering |
| concepts[9].id | https://openalex.org/C15744967 |
| concepts[9].level | 0 |
| concepts[9].score | 0.12658002972602844 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[9].display_name | Psychology |
| concepts[10].id | https://openalex.org/C178790620 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q11351 |
| concepts[10].display_name | Organic chemistry |
| concepts[11].id | https://openalex.org/C185592680 |
| concepts[11].level | 0 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[11].display_name | Chemistry |
| concepts[12].id | https://openalex.org/C77805123 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q161272 |
| concepts[12].display_name | Social psychology |
| keywords[0].id | https://openalex.org/keywords/group-decision-making |
| keywords[0].score | 0.6488906145095825 |
| keywords[0].display_name | Group decision-making |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.6433850526809692 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/group |
| keywords[2].score | 0.451670378446579 |
| keywords[2].display_name | Group (periodic table) |
| keywords[3].id | https://openalex.org/keywords/fuzzy-logic |
| keywords[3].score | 0.44609761238098145 |
| keywords[3].display_name | Fuzzy logic |
| keywords[4].id | https://openalex.org/keywords/operations-research |
| keywords[4].score | 0.3725464344024658 |
| keywords[4].display_name | Operations research |
| keywords[5].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[5].score | 0.3326456546783447 |
| keywords[5].display_name | Artificial intelligence |
| keywords[6].id | https://openalex.org/keywords/marketing |
| keywords[6].score | 0.32472914457321167 |
| keywords[6].display_name | Marketing |
| keywords[7].id | https://openalex.org/keywords/business |
| keywords[7].score | 0.28916722536087036 |
| keywords[7].display_name | Business |
| keywords[8].id | https://openalex.org/keywords/engineering |
| keywords[8].score | 0.1289220154285431 |
| keywords[8].display_name | Engineering |
| keywords[9].id | https://openalex.org/keywords/psychology |
| keywords[9].score | 0.12658002972602844 |
| keywords[9].display_name | Psychology |
| language | en |
| locations[0].id | doi:10.3390/jtaer20020120 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S27967161 |
| locations[0].source.issn | 0718-1876 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 0718-1876 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Journal of theoretical and applied electronic commerce research |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/0718-1876/20/2/120/pdf?version=1748761077 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Journal of Theoretical and Applied Electronic Commerce Research |
| locations[0].landing_page_url | https://doi.org/10.3390/jtaer20020120 |
| locations[1].id | pmh:oai:doaj.org/article:63c2c69d817b4b3087bd672c67485a46 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Journal of Theoretical and Applied Electronic Commerce Research, Vol 20, Iss 2, p 120 (2025) |
| locations[1].landing_page_url | https://doaj.org/article/63c2c69d817b4b3087bd672c67485a46 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5066919154 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-2382-649X |
| authorships[0].author.display_name | Changlu Zhang |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I78675632 |
| authorships[0].affiliations[0].raw_affiliation_string | School of Management Science and Engineering, Beijing Information Science & Technology University, Beijing 100192, China |
| authorships[0].affiliations[1].raw_affiliation_string | Beijing Key Lab of Big Data Decision Making for Green Development, Beijing 100192, China |
| authorships[0].institutions[0].id | https://openalex.org/I78675632 |
| authorships[0].institutions[0].ror | https://ror.org/04xnqep60 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I78675632 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Beijing Information Science & Technology University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Changlu Zhang |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Beijing Key Lab of Big Data Decision Making for Green Development, Beijing 100192, China, School of Management Science and Engineering, Beijing Information Science & Technology University, Beijing 100192, China |
| authorships[1].author.id | https://openalex.org/A5108137949 |
| authorships[1].author.orcid | https://orcid.org/0009-0003-5256-4318 |
| authorships[1].author.display_name | Yuchen Wang |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].raw_affiliation_string | Beijing Key Lab of Big Data Decision Making for Green Development, Beijing 100192, China |
| authorships[1].affiliations[1].institution_ids | https://openalex.org/I78675632 |
| authorships[1].affiliations[1].raw_affiliation_string | School of Management Science and Engineering, Beijing Information Science & Technology University, Beijing 100192, China |
| authorships[1].institutions[0].id | https://openalex.org/I78675632 |
| authorships[1].institutions[0].ror | https://ror.org/04xnqep60 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I78675632 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Beijing Information Science & Technology University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Yuchen Wang |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Beijing Key Lab of Big Data Decision Making for Green Development, Beijing 100192, China, School of Management Science and Engineering, Beijing Information Science & Technology University, Beijing 100192, China |
| authorships[2].author.id | https://openalex.org/A5100680433 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-8824-8574 |
| authorships[2].author.display_name | Jian Zhang |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].raw_affiliation_string | Beijing Key Lab of Big Data Decision Making for Green Development, Beijing 100192, China |
| authorships[2].affiliations[1].institution_ids | https://openalex.org/I78675632 |
| authorships[2].affiliations[1].raw_affiliation_string | School of Management Science and Engineering, Beijing Information Science & Technology University, Beijing 100192, China |
| authorships[2].institutions[0].id | https://openalex.org/I78675632 |
| authorships[2].institutions[0].ror | https://ror.org/04xnqep60 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I78675632 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Beijing Information Science & Technology University |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Jian Zhang |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Beijing Key Lab of Big Data Decision Making for Green Development, Beijing 100192, China, School of Management Science and Engineering, Beijing Information Science & Technology University, Beijing 100192, China |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/0718-1876/20/2/120/pdf?version=1748761077 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Risk Assessment of Live-Streaming Marketing Based on Hesitant Fuzzy Multi-Attribute Group Decision-Making Method |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T14139 |
| primary_topic.field.id | https://openalex.org/fields/14 |
| primary_topic.field.display_name | Business, Management and Accounting |
| primary_topic.score | 0.9958999752998352 |
| primary_topic.domain.id | https://openalex.org/domains/2 |
| primary_topic.domain.display_name | Social Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1403 |
| primary_topic.subfield.display_name | Business and International Management |
| primary_topic.display_name | E-commerce and Technology Innovations |
| related_works | https://openalex.org/W2184221808, https://openalex.org/W2740147593, https://openalex.org/W2547800031, https://openalex.org/W4247431094, https://openalex.org/W3200324093, https://openalex.org/W2352386950, https://openalex.org/W4230573045, https://openalex.org/W2352120478, https://openalex.org/W2014786470, https://openalex.org/W2077860847 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | doi:10.3390/jtaer20020120 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S27967161 |
| best_oa_location.source.issn | 0718-1876 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 0718-1876 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Journal of theoretical and applied electronic commerce research |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/0718-1876/20/2/120/pdf?version=1748761077 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Journal of Theoretical and Applied Electronic Commerce Research |
| best_oa_location.landing_page_url | https://doi.org/10.3390/jtaer20020120 |
| primary_location.id | doi:10.3390/jtaer20020120 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S27967161 |
| primary_location.source.issn | 0718-1876 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 0718-1876 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Journal of theoretical and applied electronic commerce research |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/0718-1876/20/2/120/pdf?version=1748761077 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Journal of Theoretical and Applied Electronic Commerce Research |
| primary_location.landing_page_url | https://doi.org/10.3390/jtaer20020120 |
| publication_date | 2025-06-01 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W4386963079, https://openalex.org/W3208008611, https://openalex.org/W6805667158, https://openalex.org/W3155914460, https://openalex.org/W2797963859, https://openalex.org/W4306796170, https://openalex.org/W2931299015, https://openalex.org/W4282570256, https://openalex.org/W4391326518, https://openalex.org/W4283814535, https://openalex.org/W4206722727, https://openalex.org/W4380632202, https://openalex.org/W4399781820, https://openalex.org/W4386807258, https://openalex.org/W2804548084, https://openalex.org/W3030616540, https://openalex.org/W2123195536, https://openalex.org/W2974846222, https://openalex.org/W2951628043, https://openalex.org/W2898549912, https://openalex.org/W2779610776, https://openalex.org/W4362733326, https://openalex.org/W4362667528, https://openalex.org/W2116365436, https://openalex.org/W2040121225, https://openalex.org/W1965239040, https://openalex.org/W3012795991, https://openalex.org/W6852979914, https://openalex.org/W4407929077, https://openalex.org/W3011402052, https://openalex.org/W4223475609, https://openalex.org/W4377108281, https://openalex.org/W4211007335, https://openalex.org/W2002574279, https://openalex.org/W2083199031, https://openalex.org/W2920005441, https://openalex.org/W4380679953, https://openalex.org/W4205632731 |
| referenced_works_count | 38 |
| abstract_inverted_index.A | 192 |
| abstract_inverted_index.L | 344 |
| abstract_inverted_index.Y | 342 |
| abstract_inverted_index.a | 176, 230 |
| abstract_inverted_index.16 | 189 |
| abstract_inverted_index.AI | 107, 311 |
| abstract_inverted_index.D. | 346 |
| abstract_inverted_index.It | 97 |
| abstract_inverted_index.VR | 116, 314 |
| abstract_inverted_index.as | 67, 81, 102 |
| abstract_inverted_index.by | 115 |
| abstract_inverted_index.in | 86, 172, 218, 227, 301 |
| abstract_inverted_index.is | 41, 162, 200, 233, 341 |
| abstract_inverted_index.of | 6, 22, 49, 57, 90, 106, 113, 126, 133, 154, 175, 207, 222, 261, 285, 303, 309, 336, 374 |
| abstract_inverted_index.on | 26, 31, 149, 235, 245, 348 |
| abstract_inverted_index.to | 46, 129, 164, 203, 257, 271, 366 |
| abstract_inverted_index.(1) | 0 |
| abstract_inverted_index.(2) | 118 |
| abstract_inverted_index.(3) | 290 |
| abstract_inverted_index.MCN | 358 |
| abstract_inverted_index.The | 292, 331 |
| abstract_inverted_index.and | 8, 16, 35, 39, 61, 70, 93, 109, 141, 188, 211, 268, 278, 282, 325, 363, 370 |
| abstract_inverted_index.are | 146, 252, 354 |
| abstract_inverted_index.for | 356 |
| abstract_inverted_index.has | 13 |
| abstract_inverted_index.its | 62 |
| abstract_inverted_index.pay | 269 |
| abstract_inverted_index.six | 185, 241 |
| abstract_inverted_index.the | 3, 23, 47, 55, 88, 103, 110, 124, 131, 150, 159, 166, 173, 205, 208, 214, 236, 240, 246, 280, 286, 296, 310, 349, 375 |
| abstract_inverted_index.top | 297 |
| abstract_inverted_index.> | 343, 345 |
| abstract_inverted_index.Risk | 308, 317 |
| abstract_inverted_index.This | 120, 254 |
| abstract_inverted_index.With | 2 |
| abstract_inverted_index.aims | 256 |
| abstract_inverted_index.also | 98 |
| abstract_inverted_index.are: | 306 |
| abstract_inverted_index.core | 152 |
| abstract_inverted_index.deep | 4 |
| abstract_inverted_index.each | 337 |
| abstract_inverted_index.five | 298 |
| abstract_inverted_index.live | 219, 338 |
| abstract_inverted_index.most | 21 |
| abstract_inverted_index.risk | 134, 142, 168, 178, 209, 247, 262, 299, 335 |
| abstract_inverted_index.room | 340 |
| abstract_inverted_index.show | 294 |
| abstract_inverted_index.such | 66, 80, 101 |
| abstract_inverted_index.that | 295 |
| abstract_inverted_index.then | 201 |
| abstract_inverted_index.tree | 138 |
| abstract_inverted_index.when | 264 |
| abstract_inverted_index.with | 54, 64, 239 |
| abstract_inverted_index.(A1), | 321 |
| abstract_inverted_index.(A4), | 313 |
| abstract_inverted_index.(D1), | 324 |
| abstract_inverted_index.(D2). | 330 |
| abstract_inverted_index.(F3), | 318 |
| abstract_inverted_index.(FTA) | 140 |
| abstract_inverted_index.(VR), | 73 |
| abstract_inverted_index.Based | 244, 347 |
| abstract_inverted_index.based | 148 |
| abstract_inverted_index.faces | 78 |
| abstract_inverted_index.fault | 137 |
| abstract_inverted_index.fuzzy | 194 |
| abstract_inverted_index.group | 196 |
| abstract_inverted_index.rapid | 18 |
| abstract_inverted_index.risks | 48, 145, 217, 237 |
| abstract_inverted_index.rooms | 221 |
| abstract_inverted_index.sales | 33 |
| abstract_inverted_index.still | 77 |
| abstract_inverted_index.study | 121, 255 |
| abstract_inverted_index.terms | 302 |
| abstract_inverted_index.there | 40 |
| abstract_inverted_index.three | 151, 182, 223 |
| abstract_inverted_index.video | 9 |
| abstract_inverted_index.Anchor | 312, 319 |
| abstract_inverted_index.China. | 228 |
| abstract_inverted_index.Delphi | 160 |
| abstract_inverted_index.assess | 213 |
| abstract_inverted_index.little | 43 |
| abstract_inverted_index.method | 161, 198 |
| abstract_inverted_index.refine | 165 |
| abstract_inverted_index.rights | 277 |
| abstract_inverted_index.risks, | 273 |
| abstract_inverted_index.supply | 361 |
| abstract_inverted_index.system | 180 |
| abstract_inverted_index.uneven | 94 |
| abstract_inverted_index.weight | 304 |
| abstract_inverted_index.Ethical | 307 |
| abstract_inverted_index.Product | 322 |
| abstract_inverted_index.Quality | 323, 329 |
| abstract_inverted_index.Service | 328 |
| abstract_inverted_index.anchors | 108, 226 |
| abstract_inverted_index.applied | 202 |
| abstract_inverted_index.chains, | 362 |
| abstract_inverted_index.current | 24 |
| abstract_inverted_index.emerged | 14 |
| abstract_inverted_index.enhance | 258 |
| abstract_inverted_index.ethical | 104 |
| abstract_inverted_index.focuses | 30 |
| abstract_inverted_index.growth. | 19 |
| abstract_inverted_index.harbors | 99 |
| abstract_inverted_index.healthy | 281 |
| abstract_inverted_index.improve | 367 |
| abstract_inverted_index.initial | 167 |
| abstract_inverted_index.product | 95 |
| abstract_inverted_index.promote | 371 |
| abstract_inverted_index.ranking | 305 |
| abstract_inverted_index.reality | 72 |
| abstract_inverted_index.related | 45, 272 |
| abstract_inverted_index.results | 293 |
| abstract_inverted_index.subject | 83 |
| abstract_inverted_index.system, | 170 |
| abstract_inverted_index.thereby | 274 |
| abstract_inverted_index.unclear | 82 |
| abstract_inverted_index.virtual | 71 |
| abstract_inverted_index.weights | 206 |
| abstract_inverted_index.(HFMGDM) | 199 |
| abstract_inverted_index.However, | 20 |
| abstract_inverted_index.Methods: | 119 |
| abstract_inverted_index.analysis | 139, 232, 350 |
| abstract_inverted_index.analyzes | 123 |
| abstract_inverted_index.anchors, | 357 |
| abstract_inverted_index.consumer | 276, 368 |
| abstract_inverted_index.detailed | 231 |
| abstract_inverted_index.elements | 153 |
| abstract_inverted_index.employed | 163 |
| abstract_inverted_index.globally | 15 |
| abstract_inverted_index.hesitant | 193 |
| abstract_inverted_index.methods, | 144 |
| abstract_inverted_index.problems | 100 |
| abstract_inverted_index.products | 114 |
| abstract_inverted_index.provided | 355 |
| abstract_inverted_index.purchase | 37 |
| abstract_inverted_index.quality. | 96 |
| abstract_inverted_index.research | 25, 44 |
| abstract_inverted_index.results, | 249, 351 |
| abstract_inverted_index.targeted | 250, 352 |
| abstract_inverted_index.Logistics | 326 |
| abstract_inverted_index.Promotion | 316 |
| abstract_inverted_index.Utilizing | 136 |
| abstract_inverted_index.attention | 270 |
| abstract_inverted_index.awareness | 260 |
| abstract_inverted_index.broadcast | 220, 339 |
| abstract_inverted_index.calculate | 204 |
| abstract_inverted_index.celebrity | 225 |
| abstract_inverted_index.checklist | 143 |
| abstract_inverted_index.conducted | 234 |
| abstract_inverted_index.elucidate | 130 |
| abstract_inverted_index.excessive | 111 |
| abstract_inverted_index.fostering | 279 |
| abstract_inverted_index.indicator | 169, 179 |
| abstract_inverted_index.industry. | 289, 378 |
| abstract_inverted_index.marketing | 12, 29, 60, 76, 91, 128, 216, 288, 334, 377 |
| abstract_inverted_index.platforms | 365 |
| abstract_inverted_index.prominent | 224 |
| abstract_inverted_index.proposed. | 253 |
| abstract_inverted_index.resulting | 171 |
| abstract_inverted_index.scenarios | 125 |
| abstract_inverted_index.secondary | 242 |
| abstract_inverted_index.verifying | 87 |
| abstract_inverted_index.Reputation | 320 |
| abstract_inverted_index.Technology | 315 |
| abstract_inverted_index.artificial | 68 |
| abstract_inverted_index.associated | 238 |
| abstract_inverted_index.challenges | 79 |
| abstract_inverted_index.comprising | 181 |
| abstract_inverted_index.conducting | 265 |
| abstract_inverted_index.difficulty | 85 |
| abstract_inverted_index.e-commerce | 7, 28, 51, 59, 75 |
| abstract_inverted_index.evaluation | 248 |
| abstract_inverted_index.formation. | 135 |
| abstract_inverted_index.identified | 147 |
| abstract_inverted_index.indicators | 210, 300 |
| abstract_inverted_index.maintained | 17 |
| abstract_inverted_index.marketing. | 52 |
| abstract_inverted_index.marketing: | 156 |
| abstract_inverted_index.mechanisms | 132 |
| abstract_inverted_index.merchants, | 360 |
| abstract_inverted_index.prevention | 263 |
| abstract_inverted_index.relatively | 42 |
| abstract_inverted_index.strategies | 34 |
| abstract_inverted_index.Background: | 1 |
| abstract_inverted_index.development | 56, 284, 373 |
| abstract_inverted_index.first-level | 183 |
| abstract_inverted_index.indicators, | 184, 187 |
| abstract_inverted_index.indicators. | 191, 243 |
| abstract_inverted_index.integration | 5, 63 |
| abstract_inverted_index.intentions, | 38 |
| abstract_inverted_index.misbehavior | 105 |
| abstract_inverted_index.sustainable | 283, 372 |
| abstract_inverted_index.technology, | 10 |
| abstract_inverted_index.technology. | 117 |
| abstract_inverted_index.third-level | 190 |
| abstract_inverted_index.Conclusions: | 291 |
| abstract_inverted_index.Distribution | 327 |
| abstract_inverted_index.Furthermore, | 229 |
| abstract_inverted_index.authenticity | 89 |
| abstract_inverted_index.construction | 174 |
| abstract_inverted_index.consumers’ | 36, 259 |
| abstract_inverted_index.information, | 92 |
| abstract_inverted_index.intelligence | 69 |
| abstract_inverted_index.merchants’ | 32 |
| abstract_inverted_index.safeguarding | 275 |
| abstract_inverted_index.satisfaction | 369 |
| abstract_inverted_index.second-level | 186 |
| abstract_inverted_index.technologies | 65 |
| abstract_inverted_index.transactions | 267 |
| abstract_inverted_index.Nevertheless, | 53 |
| abstract_inverted_index.Subsequently, | 158 |
| abstract_inverted_index.comprehensive | 177, 332 |
| abstract_inverted_index.institutions, | 359 |
| abstract_inverted_index.beautification | 112 |
| abstract_inverted_index.live-streaming | 11, 27, 50, 58, 74, 127, 155, 215, 266, 287, 333, 364, 376 |
| abstract_inverted_index.systematically | 122 |
| abstract_inverted_index.comprehensively | 212 |
| abstract_inverted_index.decision-making | 197 |
| abstract_inverted_index.multi-attribute | 195 |
| abstract_inverted_index.recommendations | 251, 353 |
| abstract_inverted_index.responsibility, | 84 |
| abstract_inverted_index.“people–products–scenes”. | 157 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.93068667 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |