基于SEM和fsQCA的虚拟兴趣社区用户信息采纳的影响因素研究

doi:10.13998/j.cnki.issn1002-1248.24-0444

Abstract

Abstract:

[Purpose/Significance] Virtual communities of interest have rapidly become key sources of information that significantly influence users' decision making. Characterized by resource aggregation, active exchanges, and high interactivity, these communities foster a unique environment that encourages strong user engagement. Understanding the factors that influence information adoption in these settings is essential to meeting user needs and enhancing community management and services. Unlike traditional information contexts, virtual communities emphasize user trust, emotional support, and community identity, which are critical in shaping how users perceive and adopt information. This study aims to deepen the theoretical understanding of information adoption in virtual communities of interest by incorporating information ecology theory and applying both structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). This dual-method approach enables in-depth analysis of individual factors and reveals complex configurations that influence adoption behaviors, providing insights that go beyond what SEM alone can provide. [Method/Process] The research model is based on information ecology theory, which provides a holistic framework that captures the dynamic interplay between factors such as information quality, user support systems, community structures, and platform features. This theory is particularly suited to the study of virtual communities, where multiple interdependent factors create a unique decision-making environment. SEM is used to assess linear relationships between variables, evaluating the influence of information quality, emotional support, community identity, opinion leader participation, content interaction, source credibility, and platform usability on users' information adoption intentions. As a complement to SEM, fsQCA is used to explore configurations of multiple factors, identify pathways through which these factors collectively shape adoption intentions, and capture complex causal relationships that SEM does not address. [Results/Conclusions] The SEM analysis shows that information quality, emotional support, community identity, active participation of opinion leaders, and content interaction significantly increase users' adoption intentions, while information source credibility and platform usability do not. These findings suggest that community-driven aspects may be more important to users in this context than traditional credibility indicators. The fsQCA results further identify two primary modes that drive adoption intentions: a trust-driven mode, where adoption is supported by trust-related factors, and an experience-promoting mode, which focuses on user engagement within the community. Together, these modes comprise six distinct configurations, suggesting that users' adoption intentions are influenced by combinations of factors rather than isolated variables. This study thus highlights the unique value of fsQCA in uncovering the complex interplay of factors in virtual communities and providing detailed insights into user behavior. Future research could explore cultural differences in adoption behaviors and additional factors influencing user engagement in different types of virtual communities.

Key words: virtualcommunity of interest, information adoption, information ecology theory, structural equation modeling, fuzzy-set qualitative comparative analysis

CLC Number:

G252

Long HAN, Jincheng GUO, Yiting LU, Qun ZHOU. Factors Influencing User Information Adoption in Virtual Communities of Interest: A Study Based on SEM and fsQCA[J].Journal of library and information science in agriculture, 2024, 36(8): 82-95.

Figures/Tables 9

Fig.1

Table 1

Measurement items and sources of the scale"

变量	题项	题项内容	来源
信息质量	IQ1	我认为我在虚拟兴趣社区中获取的信息是准确的	LIAO等^[43]、VENKATESH等^[44]
	IQ2	我认为我在虚拟兴趣社区中获取的信息是全面的
	IQ3	我认为我在虚拟兴趣社区中获取的信息是及时更新的
	IQ4	我认为虚拟兴趣社区的信息表达方式清晰易懂
	IQ5	我认为虚拟兴趣社区的信息能够满足我的需求
信息源可信度	SC1	我认为虚拟兴趣社区中信息的来源是值得信赖的	HUO等^[45]
	SC2	我认为虚拟兴趣社区中信息发布者的专业知识对我有帮助
	SC3	我认为虚拟兴趣社区中的信息发布者是值得信赖的专家
	SC4	我认为虚拟兴趣社区的信息来源是权威的
情感支持	ES1	我觉得虚拟兴趣社区中的其他用户对我的问题给予了同理心和支持	CHIU等^[46]
	ES2	我觉得虚拟兴趣社区中的用户互动让我感受到情感上的支持或鼓励
	ES3	我认为在虚拟兴趣社区中，用户之间的互动帮助我减轻了信息获取时的压力或疑虑
	ES4	我觉得在虚拟兴趣社区中的交流让我产生了积极的情感体验，增加了对信息的信任
社区认同	SR1	我觉得自己与虚拟兴趣社区中的其他用户有共同的兴趣或目标	FANG等^[47]
	SR2	我觉得虚拟兴趣社区的价值观与我的想法相符
	SR3	我愿意在虚拟兴趣社区中更多地参与和分享信息
	SR4	我认为虚拟兴趣社区对我的观点表示了尊重和重视
社区意见领袖参与	OL1	我认为虚拟兴趣社区中的意见领袖对我有影响	蒋惠芳^[48]、吴娇娇^[49]
	OL2	我信任虚拟兴趣社区中具有较高影响力的用户提供的信息
	OL3	我经常关注虚拟兴趣社区中意见领袖发布的内容
社区内容互动	CI1	我经常参与虚拟兴趣社区的讨论和互动	范晓屏等^[50]
	CI2	我觉得虚拟兴趣社区的讨论帮助我更好地理解信息
	CI3	我认为通过与其他用户的互动，我对信息的信任度增强了
平台易用性	EU1	我觉得虚拟兴趣社区平台的界面设计简单明了，易于操作	ZLATOLAS等^[51]、郭瑞^[52]
	EU2	我能够在虚拟兴趣社区平台上快速找到自己所需的信息
	EU3	我觉得在虚拟兴趣社区平台上的操作过程流畅，没有不必要的障碍
信息采纳意愿	IA1	我愿意依据虚拟兴趣社区中获取的信息做出决策或采取行动	SUSSMAN^[11]
	IA2	我经常参考虚拟兴趣社区中的信息来解决实际问题
	IA3	我觉得虚拟兴趣社区中的信息对我来说有足够的可信度，因此愿意采纳
	IA4	我会向他人推荐虚拟兴趣社区中的有用信息或内容

Table 1

Table 2

Table 3

Table 4

Table 5

Fig.2

Table 6

Table 7

References 55

1	中国互联网络信息中心. 第53次中国互联网络发展状况统计报告[R]. 北京: 中国互联网络信息中心, 2021.
	China Internet Network Information Center. The 53rd Statistical Report on China's Internet Development[R]. Beijing: China Internet Network Information Center, 2021.
2	ARMSTRONG A, HAGEL J. The real value of online communities[M]//Knowledge and Communities. Amsterdam: Elsevier, 2000: 85-95.
3	FENG Y Y, LIU Z W, QIAN W J, et al. Research on the influence mechanism of gamification elements on users' willingness to continue using in interest-based virtual communities - Based on ECM-ISC model[C]//2019 16th International Conference on Service Systems and Service Management (ICSSSM). Piscataway, New Jersey: IEEE, 2019: 1-6.
4	孟笛. 虚拟社区国际研究综述——基于SSCI、A&HCI高被引文献的分析[J]. 图书情报工作, 2015, 59(18): 127-133.
	MENG D. International literature review of virtual community: Based on the analysis high cited documents from SSCI and A & HCI[J]. Library and information service, 2015, 59(18): 127-133.
5	AL-AZIM N A R ABD, GHARIB T F, HAMDY M, et al. Influence propagation in social networks: Interest-based community ranking model[J]. Journal of King Saud University - Computer and information sciences, 2022, 34(5): 2231-2243.
6	刘颖捷. 娱乐类网络社区的用户粘性研究[D]. 西安: 西北大学, 2017.
	LIU Y J. Research on user stickiness of entertainment network community[D]. Xi'an: Northwest University, 2017.
7	卢倩. 虚拟兴趣社区激励用户参与的策略及机制研究[D]. 南京: 南京大学, 2021.
	LU Q. Research on strategies and mechanisms of stimulating users' participation in virtual interest communities[D]. Nanjing: Nanjing University, 2021.
8	赵小建. 基于MOA理论模型的兴趣型虚拟社区知识共享行为研究[D]. 无锡: 江南大学, 2021.
	ZHAO X J. Research on knowledge sharing behavior of interest-oriented virtual community based on MOA theoretical model[D]. Wuxi: Jiangnan University, 2021.
9	张瑞, 涂凯, 黄炜. 中美网络兴趣型社区粉丝行为对比研究——基于扎根理论探索分析[J]. 现代情报, 2023, 43(8): 54-65.
	ZHANG R, TU K, HUANG W. Comparative study on fan behavior of Chinese and American in online interest-based communities - Research based on grounded theory[J]. Journal of modern information, 2023, 43(8): 54-65.
10	CHEN C D, KU E C S. Bridging indistinct relationships and online loyalty: Evidence from online interest-based communities[J]. Online information review, 2013, 37(5): 731-751.
11	SUSSMAN S W, SIEGAL W S. Informational influence in organizations: An integrated approach to knowledge adoption[J]. Information systems research, 2003, 14(1): 47-65.
12	宋雪雁, 王萍. 信息采纳行为概念及影响因素研究[J]. 情报科学, 2010, 28(5): 760-762, 767.
	SONG X Y, WANG P. Research on concept and effective factors of information adoption behavior[J]. Information science, 2010, 28(5): 760-762, 767.
13	陶晓波, 徐鹏宇, 樊潮, 等. 创新社区中新产品开发人员信息采纳行为的影响机理研究[J]. 管理评论, 2020, 32(10): 135-146.
	TAO X B, XU P Y, FAN C, et al. Research on the influence mechanism of information adoption behavior of new product developers in innovation community[J]. Management review, 2020, 32(10): 135-146.
14	郭爱芳, 陈佳凤, 郭静, 等. 虚拟创新社区用户相关特征对其创意采纳的影响——以戴尔“头脑风暴” 社区为例[J]. 中国科技论坛, 2018(8): 140-146.
	GUO A F, CHEN J F, GUO J, et al. The influence of user-related characteristics on the idea's adoption in virtual innovation community: An empirical study based on the dell's "idea storm" community[J]. Forum on science and technology in China, 2018(8): 140-146.
15	洪闯, 李贺, 毛太田. 开放式创新社区用户知识贡献的采纳机理研究[J]. 现代情报, 2020, 40(5): 33-40.
	HONG C, LI H, MAO T T. Study on the adoption mechanism of knowledge contribution from open innovation community users[J]. Journal of modern information, 2020, 40(5): 33-40.
16	王楠, 陈详详, 祁运丽, 等. 基于详尽可能性模型的用户创新社区创意采纳影响因素研究[J]. 中国管理科学, 2020, 28(3): 213-222.
	WANG N, CHEN X X, QI Y L, et al. The research on influence factors of user innovation community idea adoption based on elaboration likelihood model[J]. Chinese journal of management science, 2020, 28(3): 213-222.
17	李娟娟, 郭顺利. 认知视域下社会化问答社区用户知识采纳行为的影响因素——基于扎根理论的探索性分析[J]. 情报科学, 2022, 40(2): 91-98.
	LI J J, GUO S L. Influencing factors of users' knowledge adoption behavior in socialized Q & A community from cognitive perspective - An exploratory analysis based on grounded theory[J]. Information science, 2022, 40(2): 91-98.
18	付少雄, 陈晓宇, 邓胜利. 社会化问答社区用户信息行为的转化研究——从信息采纳到持续性信息搜寻的理论模型构建[J]. 图书情报知识, 2017, 34(4): 80-88.
	FU S X, CHEN X Y, DENG S L. Information behavioral transferring in a social Q & A community: A conceptual model for understanding mechanism from information adoption to sustained information seeking[J]. Documentation, information & knowledge, 2017, 34(4): 80-88.
19	费豪泽, 周斌, 刘鹏, 等. 社会化问答中回答者在线互动行为对信息采纳影响的实证分析[J]. 数字图书馆论坛, 2019(10): 45-54.
	FEI H Z, ZHOU B, LIU P, et al. An empirical analysis of the impact of answers' online interactive behavior on information acceptance in socialized question answering[J]. Digital library forum, 2019(10): 45-54.
20	ZHOU T. Understanding online health community users' information adoption intention: An elaboration likelihood model perspective[J]. Online information review, 2022, 46(1): 134-146.
21	ZHU Y P, JIANG H, ZHOU Z. Information adoption behavior in online healthcare communities from the perspective of personality traits[J]. Frontiers in psychology, 2022, 13: 973522.
22	唐旭丽, 张斌, 张岩. 在线健康社区用户的信息采纳意愿研究——基于健康素养和信任的视角[J]. 信息资源管理学报, 2018, 8(3): 102-112.
	TANG X L, ZHANG B, ZHANG Y. Explore users' information adoption intention in online health communities: A health literacy and trust perspective[J]. Journal of information resources management, 2018, 8(3): 102-112.
23	CHOU C H, WANG Y S, TANG T I. Exploring the determinants of knowledge adoption in virtual communities: A social influence perspective[J]. International journal of information management, 2015, 35(3): 364-376.
24	ZHU D H, CHANG Y P, LUO J J. Understanding the influence of C2C communication on purchase decision in online communities from a perspective of information adoption model[J]. Telematics and informatics, 2016, 33(1): 8-16.
25	LI R Z, HUANG Q, CHEN X Y, et al. Factors affecting smart community service adoption intention: Affective community commitment and motivation theory[J]. Behaviour & information technology, 2019, 38(12): 1324-1336.
26	涂瑞德, 操慧子, 明均仁. 虚拟学术社区用户采纳意愿的影响因素[J]. 图书馆论坛, 2020, 40(2): 10-16.
	TU R D, CAO H Z, MING J R. Influencing factors of virtual academic community users' adoption intention: An empirical research[J]. Library tribune, 2020, 40(2): 10-16.
27	HORTON F W. Information ecology[J]. Journal of systems management, 1978(9): 32-36.
28	XU Z C, XU Z L. Research on circulation mechanism of digital course resources from the perspective of information ecology theory[J]. Journal of cases on information technology, 2024, 26(1): 1-21.
29	娄策群, 周承聪. 信息生态链: 概念、本质和类型[J]. 图书情报工作, 2007, 51(9): 29-32.
	LOU C Q, ZHOU C C. Information ecochain: Concept, essence and types[J]. Library and information service, 2007, 51(9): 29-32.
30	冯献, 李瑾, 崔凯, 等. 基于信息生态视角的乡村居民公共数字文化服务采纳意愿影响因素分析[J]. 图书馆建设, 2022(4): 139-146.
	FENG X, LI J, CUI K, et al. Analysis on factors influencing rural residents' acceptance of public digital cultural services from the perspective of information ecology[J]. Library development, 2022(4): 139-146.
31	刘春明, 郝庆升, 周杨, 等. 电商平台中绿色农产品消费者信息采纳行为及影响因素研究——基于信息生态视角[J]. 情报科学, 2019, 37(7): 151-157.
	LIU C M, HAO Q S, ZHOU Y, et al. Consumer information acceptance behavior and influencing factors of green agricultural products in E-commerce platform - In the perspective of information ecology[J]. Information science, 2019, 37(7): 151-157.
32	JIANG G Y, LIU F, LIU W P, et al. Effects of information quality on information adoption on social media review platforms: Moderating role of perceived risk[J]. Data science and management, 2021, 1(1): 13-22.
33	徐嘉徽, 李全喜, 张健. 共享服务平台信息质量对消费者信息采纳行为的影响分析与提升对策研究[J]. 情报科学, 2019, 37(5): 148-154.
	XU J H, LI Q X, ZHANG J. The impact of information quality on customer information adoption behavior and information quality improvement in shared services platform[J]. Information science, 2019, 37(5): 148-154.
34	ERKAN I, EVANS C. The influence of eWOM in social media on consumers' purchase intentions: An extended approach to information adoption[J]. Computers in human behavior, 2016, 61: 47-55.
35	SARASON B R A S. Social support: an interactional view[M]. New York: J. Wiley & Sons, 1990.
36	DHOLAKIA U M, BAGOZZI R P, PEARO L K. A social influence model of consumer participation in network- and small-group-based virtual communities[J]. International journal of research in marketing, 2004, 21(3): 241-263.
37	LAZARSFELD P F, BERELSON B, GAUDET H. The people's choice: How the voter makes up his mind in a presidential campaign[M]. New York: Duell, Sloan and Pearce, 1944.
38	周密, 罗露阳, 刘伟. 在线知识问答社区中答案的内容特征和社区地位对答案采纳的影响机制研究[J]. 图书馆研究与工作, 2023(8): 45-54.
	ZHOU M, LUO L Y, LIU W. A study of the content characteristics of answers and community status on answer adoption in online knowledge question-and-answer communities[J]. Library science research & work, 2023(8): 45-54.
39	DURLAUF S N, IOANNIDES Y M. Social interactions[J]. Annual review of economics, 2010, 2: 451-478.
40	李宗伟, 张艳辉, 夏伟伟. 卖家反馈能否引发高质量的在线评论信息?——基于淘宝网的实证分析[J]. 中国管理科学, 2021, 29(5): 221-230.
	LI Z W, ZHANG Y H, XIA W W. Can seller feedback trigger high quality online reviews? - Based on the empirical analysis of Taobao[J]. Chinese journal of management science, 2021, 29(5): 221-230.
41	DAVIS F D. Perceived usefulness, perceived ease of use, and user acceptance of information technology[J]. MIS quarterly, 1989, 13(3): 319.
42	张秋霞. 信息生态视角下消费者选择跨境电商平台的影响因素研究[D]. 太原: 山西财经大学, 2020.
	ZHANG Q X. Research on influencing factors of consumers' choice of cross-border E-commerce platform from the perspective of information ecology[D]. Taiyuan: Shanxi University of Finance & Economics, 2020.
43	LIAO C C, PALVIA P, LIN H N. The roles of habit and web site quality in e-commerce[J]. International journal of information management, 2006, 26(6): 469-483.
44	VENKATESH V, BROWN S A. A longitudinal investigation of personal computers in homes: Adoption determinants and emerging challenges[J]. MIS quarterly, 2001, 25(1): 71.
45	HUO C G, ZHANG M, MA F C. Factors influencing people's health knowledge adoption in social media[J]. Library hi tech, 2018, 36(1): 129-151.
46	CHIU C M, HUANG H Y, CHENG H L, et al. Understanding online community citizenship behaviors through social support and social identity[J]. International journal of information management, 2015, 35(4): 504-519.
47	FANG Y H, CHIU C M. In justice we trust: Exploring knowledge-sharing continuance intentions in virtual communities of practice[J]. Computers in human behavior, 2010, 26(2): 235-246.
48	蒋惠芳. 社交电商意见领袖对消费者在线购买行为意向的影响研究[D]. 西安: 陕西师范大学, 2022.
	JIANG H F. Research on the influence of social E-commerce opinion leaders on consumers' online purchase intention[D]. Xi'an: Shaanxi Normal University, 2022.
49	吴娇娇. 社交平台中用户生成内容对消费者购买意愿的影响研究[D]. 南京: 东南大学, 2021.
	WU J J. Research on the influence of user-generated content on consumers' purchase intention in social platform[D]. Nanjing: Southeast University, 2021.
50	范晓屏, 马庆国. 基于虚拟社区的网络互动对网络购买意向的影响研究[J]. 浙江大学学报(人文社会科学版)预印本, 2009(1): 94-102.
	FAN X P, MA Q G. A study on the impact of interactivity on online purchasing intent based on virtual community[J]. Journal of Zhejiang University (humanities and social sciences), 2009(1): 94-102.
51	NEMEC ZLATOLAS L, WELZER T, HERIČKO M, et al. Privacy antecedents for SNS self-disclosure: The case of facebook[J]. Computers in human behavior, 2015, 45: 158-167.
52	郭瑞. 娱乐类移动短视频平台用户使用行为影响因素研究[D]. 郑州: 郑州大学, 2018.
	GUO R. Research on influencing factors of user's usage behavior of entertainment mobile short video platform[D]. Zhengzhou: Zhengzhou University, 2018.
53	RAGIN C C. Redesigning social inquiry: Fuzzy sets and beyond[M]. Chicago: University of Chicago Press, 2008: 44-68.
54	谭春辉, 王晓宇, 刁斐, 等. 基于fsQCA方法的社会化问答社区用户持续使用意愿影响机理研究[J]. 图书馆学研究, 2023(1): 74-86.
	TAN C H, WANG X Y, DIAO F, et al. A research on the influence mechanism of the user's continuous use intention in the social Q & A community based on the fsQCA method[J]. Research on library science, 2023(1): 74-86.
55	莫敏, 匡宇扬, 朱庆华, 等. 在线问诊信息用户采纳意愿的影响因素研究[J]. 现代情报, 2022, 42(6): 57-68.
	MO M, KUANG Y Y, ZHU Q H, et al. Research on the influencing factors of users' intention to adopt online medical consultation information[J]. Journal of modern information, 2022, 42(6): 57-68.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

描述性特征	类别	人数/个	所占百分比/%
性别	男	157	43.50
性别	女	204	56.50
年龄	18岁及以下	6	1.70
	19~26岁	187	51.80
	27~34岁	121	33.50
	35+	47	13.00
虚拟兴趣社区使用时间	1年及以下	12	3.30
	2~3年	84	23.20
	3~5年	164	45.40
	5年以上	101	28.10
虚拟兴趣社区使用频率	每天都会使用	296	82.00
	每周2~4次	51	14.10
	每月使用2~8次	14	3.90

变量名称	Cronbach's Alpha	组合信度CR
信息质量（IQ）	0.865	0.867
信息源可信度（SC）	0.807	0.811
情感支持（ES）	0.845	0.846
社区认同（SR）	0.83	0.831
社区意见领袖参与（OL）	0.863	0.863
社区内容互动（CI）	0.819	0.819
平台易用性（EU）	0.838	0.839
信息采纳意愿（IA）	0.895	0.896

变量	AVE	MD	EU	CI	OL	IC	SC	IQ	IA
SR	0.621	0.788
EU	0.635	0.383	0.797
CI	0.602	0.422	0.351	0.776
OL	0.612	0.463	0.452	0.412	0.782
ES	0.579	0.309	0.359	0.359	0.386	0.761
SC	0.519	0.433	0.453	0.492	0.475	0.372	0.720
IQ	0.566	0.493	0.472	0.400	0.358	0.306	0.517	0.752
IA	0.683	0.687	0.491	0.617	0.570	0.529	0.571	0.601	0.826

指标类别	适配度指标	判断标准	指标值	适配效果
绝对适配度指标	CMIN/DF	＜3	1.220	符合标准
	RMSEA	＜0.08	0.025	符合标准
	GFI	＞0.9（理想）；＞0.8（合理）	0.925	符合标准
	AGFI	＞0.8	0.908	符合标准
增值适配度指标	CFI	＞0.9	0.985	符合标准
	IFI	＞0.9	0.985	符合标准
	TLI	＞0.9	0.982	符合标准
简约适配度指标	PGFI	＞0.5	0.750	符合标准
简约适配度指标	PNFI	＞0.5	0.799	符合标准

变量	一致性	覆盖度
IQfz	0.738 2	0.855 9
~IQfz	0.621 7	0.614 5
SCfz	0.846 8	0.860 6
~SCfz	0.530 8	0.596 2
ESfz	0.775 9	0.855 2
~ESfz	0.607 6	0.628 3
SRfz	0.779 8	0.875 6
~SRfz	0.607 1	0.617 2
OLfz	0.853 7	0.835 0
~OLfz	0.531 2	0.626 3
CIfz	0.807 1	0.849 7
~CIfz	0.561 8	0.607 8
EUfz	0.823 1	0.835 8
~EUfz	0.542 8	0.610 3

Factors Influencing User Information Adoption in Virtual Communities of Interest: A Study Based on SEM and fsQCA

RichHTML

PDF (PC)

Abstract

Cite this article

share this article

Figures/Tables 9

References 55

Related Articles 8

Metrics

Comments

Recommended 0

前因条件	模式一			模式二
前因条件	H1	H2	H3	H4	H5	H6
信息质量（IQ）	〇		⊗	〇	〇	⊗
信息源可信度（SC）	●	●	●	〇		〇
情感支持（ES）		●	〇	●	●	●
社区认同（SR）			⊗	〇		⊗
社区意见领袖参与（OL）	●	●	●		●	〇
社区内容互动（CI）	●	●	●		●
平台易用性（EU）	〇	●		●	●	●
一致性	0.963	0.958	0.967	0.958	0.956	0.965
覆盖率	0.461	0.487	0.366	0.454	0.452	0.357
净覆盖率	0.041	0.025	0.041	0.058	0.033	0.021
总体一致性	0.946
总体覆盖率	0.693

[1]	FENG Li, GUO Bochi, GAO Mian. Optimizing the Path of Cultivating Intellectual Property Literacy among College Students through AIGC Empowerment [J]. Journal of library and information science in agriculture, 2026, 38(1): 58-70.
[2]	HUI Xiaomeng, CHEN Yuqing, HUI Lianghong. Modeling the Relationship Between Digital Nativity and Digital Citizenship: Based on the Analysis of SEM and fsQCA [J]. Journal of library and information science in agriculture, 2023, 35(3): 37-51.
[3]	LI Li, HAN Ping, ZHANG Hong, ZHANG Weijuan. Impacts of Heuristic-Systematic Clues on Health Information Adoption of Mobile Short Video Apps: Based on SEM and fsQCA [J]. Journal of library and information science in agriculture, 2023, 35(1): 73-86.
[4]	XING Fei, LIU Caihua, CHAI Xuefei, PENG Guochao. Influencing Factors of Elderly Users' Health Information Adoption Behavior Based on Social Platforms: Taking WeChat as an Example [J]. Journal of library and information science in agriculture, 2022, 34(7): 53-64.
[5]	LI Jiawen, QIN Qin, KE Qing. Empirical Research on the Influencing Factors of Users' Knowledge Hiding Behavior in Virtual Question-and-Answer Community [J]. Journal of library and information science in agriculture, 2022, 34(2): 48-62.
[6]	WU Qiyun. Research on the Optimal Allocation of Digital Library Collection Resource from the Perspective of Information Ecology Theory [J]. Journal of library and information science in agriculture, 2018, 30(9): 38-41.
[7]	Liu Liping. Research on Collaborative Innovation Service Model of Library Consortia based on Information Ecology Theory [J]. Journal of library and information science in agriculture, 2017, 29(8): 201-204.
[8]	LI Ming-zhen, WANG Zhen. Construction of Information Adoption Model in Digital Library Based on Personal Information World Theory [J]. Journal of library and information science in agriculture, 2016, 28(11): 9-12.