基于县长及其相关政府官员的直播带货数据,运用空间分类、核密度、区位商、类型划分等方法对中国县域政府官员的直播带货水平的空间差异及驱动力进行分析。研究发现：①从产品类型看,“多种型”占比最多,达62.92%;“单一型”占比次之,为32.51%;“两种型”与“三种型”占比最低,两者合计仅占4.57%。从省际差异看,隶属湖南、河南与山西等省的县域直播带货产品种类多且带货量大,而四川、青海、西藏等省区的种类较少。从主播类型看,“政府官员+主持人”最多,“政府官员+明星”最少。②从助农活跃度看,“昙花一现”式助农官员较多,比例高达66.87%。场次大于4的助农官员非常少,占比仅为1.05%。从参与人数看,多数县域为1~2人,少数为3~5人的组合型。数量超过5人的县域单元仅4个,分别是内蒙古乌拉特后旗、山西汾西县、甘肃靖远县与宁夏中宁县。从官员职级看,不同职级官员参与直播活动的次数差异不大,且职级高低与直播带货参与度并没有直接的关系。③从助农效益看,空间格局整体呈“两大核心区,多个增长极”的集聚特征,不仅形成以新疆昭苏县与河南光山县为核心的两大高水平密度圈,而且在湖北郧西、江西莲花、福建长泰以及湖南安仁等县形成多个增长极。④从产品区位商看,具有地理标志产品的县域单元,政府官员参与直播带货的频数较高、活跃度强且经济效益较高,但不同的地理标志产品亦有直播效益的差异。其中,瓜果蔬菜类县域单元的政府官员参与度更频繁且直播带货的销售额更高,而粮食油料类、禽畜蛋类的参与频数低且直播销售的带动效应不强。⑤从影响因素看,主要因子为直播规模与直播频率、地理品牌资源优势、官员受教育程度,次要因子为直播电商发育水平、相关产业基础实力以及互联网营商环境,一般作用因子为信息化水平、政府支持力和科技创新能力等。
Based on the data of Douyin ecommerce livestreaming marketing hosted by county government officials,this article uses the spatial classification,the kernel density,the location quotient,and the method of type partition to analyze the spatial pattern and influencing factors of Douyin livestreaming marketing hosted by county government officials. The results show that: 1) From the perspective of frequency and product types of Douyin livestreaming marketing,county government officials mainly sold the multi-type agricultural products and the proportion of multi-type reached 62.92%. 32.51% Douyin livestreaming marketing hosted by county government officials was about single-type agricultural product,4.57% was about two-type and three-type agricultural products. It had a wide range of agricultural products of Douyin livestreaming marketing in the counties of Hunan,Henan and Shanxi provinces. From the anchor type,the combination of county government official and professional host was the common mode,the combination of county government official and movie star was the least mode. 2) From the active degree of Douyin livestreaming marketing hosted by county government officials,most activities were just a passing fad. In 1138 county-level administrative units,66.87% only hosts one Douyin livestreaming marketing activity,1.05% hosts over four activities. Additionally,in terms of participant numbers,the majority of counties have 1 or 2 officials engaged in sales activities and a small number of counties have 3-5 officials participating in such activities. There were only four counties with more than five officials in livestreaming activities,namely Urad Rear Banner of Inner Mongolia Autonomous Region,Fenxi County of Shanxi,Jingyuan County of Gansu,and Zhongning County in Ningxia Hui Autonomous Region. From the perspective of official rank,there was not much difference in the frequency of participation in livestreaming activities among officials at different ranks,and the rank was not directly related to the degree of participation in livestreaming sales. 3) From the perspective of revenue of livestreaming sales,the overall spatial pattern showed a clustering feature of "two core areas and multiple growth poles",which not only formed two high-level density circles centered around Zhaosu County in Xinjiang Uygur Autonomus Region and Guangshan County in Henan Province,but also distributed several growth poles such as Yunxi County in Hubei Province,Lianhua County in Jiangxi Province,Changtai County in Fujian Province,Anren County in Hunan Province. 4) From the perspective of locational quotient of different types of products,government officials in the counties with national products of geographical indication participated in livestreaming sales activities with higher frequency,better participation enthusiasm and higher economic benefits. However,different types of geographical indication products led to different benefits in livestreaming sales activities. Specifically,government officials in the counties with geographical indication products of fruits and vegetables were more frequently involved in livestreaming sales activities and promoted huge economic benefits,while officials in the counties with grain,oil,livestock and eggs participated in live activities with in a small amount and the driving effect of livestreaming sales was not significant. 5) From the perspective of influencing factors,the main factors were the scale and frequency of livestreaming activities,the number of national products of geographical indication and the educational background of officials. The secondary factors were the level of livestreaming ecommerce,the industrial foundation and the context of internet marketing,and some factors such informatization level,government policy and the level of technological innovation capability did not have significant explanatory power.
[1] 马芳芳,丁志伟. 中国抖音直播带货行业发展的空间分异及影响因素[J]. 经济地理,2021,41(12):22-32.
[2] 丁志伟,马芳芳,张改素. 基于抖音粉丝量的中国城市网络关注度空间差异及其影响因素[J]. 地理研究,2022,41(9):2548-2567.
[3] 张英浩,汪明峰,汪凡,等. 中国直播电商发展的空间差异与影响机理研究[J]. 地理科学,2022,42(9):1555-1565.
[4] 徐智邦,王中辉,周亮,等. 中国“淘宝村”的空间分布特征及驱动因素分析[J]. 经济地理,2017,37(1):107-114.
[5] Utz S,Kerkhof P,van den Bos J. Consumers rule:How consumer reviews influence perceived trustworthiness of online stores[J]. Electronic Commerce Research and Applications,2012,11(1):49-58.
[6] Yoo J,Kim M.The effects of online product presentation on consumer responses:A mental imagery perspective[J]. Journal of Business Research,2014,67(11):2464-2472.
[7] Benedicktus R L,Brady M K,Darke P R,et al.Conveying trustworthiness to online consumers:Reactions to consensus,physical store presence,brand familiarity,and generalized suspicion[J]. Journal of Retailing,2010,86(4):322-335.
[8] Koo W,Cho E,Kim Y K.Actual and ideal self-congruity affecting consumers’ emotional and behavioral responses toward an online store[J]. Computers in Human Behavior,2014,36:147-153.
[9] 丁志伟,韩明珑,张改素,等. 县域尺度下中原城市群C2C淘宝店铺服务质量的空间分异及其影响因素[J]. 经济地理,2019,39(5):143-154.
[10] 彭珏,何金廖. 电商粉丝经济的地理格局及其影响因子探析——以抖音直播带货主播为例[J]. 地理科学进展,2021,40(7):1098-1112.
[11] 苏康传,杨庆媛,吴江,等. 重庆市乡村空间商品化格局特征、驱动机制及发展模式[J]. 经济地理,2022,42(7):167-177.
[12] 王明杰,颜梓晗,余斌,等. 电子商务专业村空间格局演化及影响因素研究——基于2015—2020年中国淘宝村数据[J]. 地理科学进展,2022,41(5):838-853.
[13] 陈延斌,殷冠文,王少慧. 山东省电子商务发展水平的地域特征及影响因素[J]. 经济地理,2022,42(1):135-143.
[14] 宋周莺,虞洋,祝巧玲,等. 中国县域网络购物空间格局及其影响因素[J]. 地理研究,2019,38(12):2997-3009.
[15] 杨忍,陈燕纯,龚建周. 转型视阈下珠三角地区乡村发展过程及地域模式梳理[J]. 地理研究,2019,38(3):725-740.
[16] 刘晓阳,丁志伟,黄晓东,等. 中国电子商务发展水平空间分布特征及其影响因素——基于1915个县(市)的电子商务发展指数[J]. 经济地理,2018,38(11):11-21,38.
[17] 唐红涛,郭凯歌,张俊英. 电子商务与农村扶贫效率:基于财政投入、人力资本的中介效应研究[J]. 经济地理,2018,38(11):50-58.
[18] 江璇,杨帆,林耿. 行动者网络视角下批发市场新电商模式[J]. 地理科学进展,2018,37(7):976-985.
[19] 王志盼,张清凌,宋小青,等. 基于位置大数据的中国跨境电商时空格局变化及其影响机制[J]. 经济地理,2022,42(1):44-52.
[20] Luo M,Sima F.Research on the online marketing strategy and the trend of developing of “Internet celebrity live broadcast” for shoes and clothes enterprises[J]. The Frontiers of Society,Science and Technology,2020,2(13):54-59.
[21] Liu L,Aremu E O,Yoo D.Brand marketing strategy of live streaming in mobile era:A case study of Tmall platform[J]. Journal of East Asia Management,2020,1(1):65-87.
[22] Yu Z,Zhang K.The determinants of purchase intention on agricultural products via public0interest live streaming for farmers during COVID-19 pandemic[J]. Sustainability,2022,DOI:10.3390/su142113921.
[23] Struzek D,Dickel M,Randall D,et al.How live streaming church services promotes social participation in rural areas[J]. Interactions,2019,27(1):64-69.
[24] 邓喆. 政府官员直播“带货”:政务直播+助农的创新发展、风险挑战与长效机制[J]. 中国行政管理,2020(10):80-85.
[25] Guo W,Sun N. Unprofessional or admirable? Determinants of purchasing behavior in government officials’ livestreamed shopping[J]. International Journal of Environmental Research and Public Health,2022,https://doi.org/10.3390/ijerph192013073.
[26] 傅泽. 数字经济背景下电商直播农产品带货研究[J]. 农业经济,2021(1):137-139.
[27] 李利文,袁凤欣. 基层治理创新视域下官员直播带货何以持续?——基于40个案例的模糊集定性比较分析[J]. 电子政务,2023(4):68-79.
[28] 马亮,马菊,史晓姣. 领导干部直播带货:驱动因素、关键特征与发展进路[J]. 兰州大学学报:社会科学版,2021,49(5):143-152.
[29] Hou F,Guan Z,Li B,et al.Factors influencing people’s continuous watching intention and consumption intention in live streaming:Evidence from China[J]. Internet Research,2020,30(1):141-163.
[30] Wang Z,Li J,Chen P.Factors influencing Chinese flower and seedling family farms’ intention to use live streaming as a sustainable marketing method:An application of extended theory of planned behavior[J]. Environment,Development and Sustainability,2022,24(3):4299-4322.
[31] 郭红东,曲江. 直播带货助农的可持续发展研究[J]. 人民论坛,2020(20):74-76.
[32] 王志和. “直播+电商”如何助力乡村振兴[J]. 人民论坛,2020(15):98-99.
[33] 林春,谭学通. 中国县域普惠金融的时空格局及影响因素[J]. 经济地理,2021,41(6):126-135.
[34] 王盈盈,谢漪,王敏. 精准扶贫背景下农村电商关系网络与地方营造研究——以广东省五华县为例[J]. 世界地理研究,2017,26(6):119-130.
[35] 罗婉琳,王芳,丁志伟. 中国红色景区抖音网络关注度的空间差异及其影响因素[J]. 经济地理,2023,43(3):198-210.
[36] 赵芮,赵恒,丁志伟. 基于网络关注度的中国沙漠型A级景区空间格局及其影响因素分析[J]. 中国沙漠,2022,42(5):101-113.
