科技部專題研究計畫主持人
MOST-109-2410-H-017-012 -SSS
以社會–技術系統觀點探討社群媒體分析與市場機會雙元辨識:以市場 導向與知識管理為基礎
Examining Social Media Analytics and Market Opportunity Recognition with a Socio-technical System View: Based on Market Orientation and Knowledge Management Perspectives
科技部
Ministry of Science and Technology
國立高雄師範大學
National Kaohsiung Normal Univeristy
譚大純
David DC Tarn
國立高雄師範大學事業經營學系
Department of Business Management, National Kaohsiung Normal Univeristy
譚大純
教授
0929752505
dctarn@nknu.edu.tw
計畫執行期間起:2020-08-01
計畫執行期間迄:2021-07-01
2021-04-01
2021-05-16
台灣服務業與金融業
2
002,003
05
社群媒體分析;市場機會辨識;社會─技術系統觀點;市場導向;知識管理
Social media analytics; Market opportunity recognition; Socio-technical system; Market Orientation; Knowledge management
中文結案摘要 本研究嘗試引用社會-技術系統為基礎,分別以市場導向(社會層面)與知識管理(技術層面),探討社群媒體分析對市場機會辨識之效果。本研究欲達成下列目的: 1. 以社會-技術系統之雙面向為基礎,完整建構社群媒體分析架構。 2. 整合市場機會「發掘」或「創造」之爭點,以雙元觀點探討機會辨識行為。 3. 重新檢視機會辨識驅動因子:(1)先驗知識,(2)社會網絡,及(3)組織警覺性,及其對機會辨識之影響。 4. 探討社群媒體分析對市場機會辨識之效果,以及辨識驅動因子在關係中之調節作用。 本研究擬回答下列研究問題:「若以社會-技術系統(市場導向、知識管理)為觀點,社群媒體分析取向對市場機會辨識(發掘與創造)分別具有何種效果?其中辨識驅動因子(先驗知識、社會網絡,與組織警覺)是否具中介作用?」 本研究計以下構念:(1)市場機會辨識(發掘、創造);(2)社群媒體分析之社會/對象層面(市場導向觀點,包括員工、顧客、競爭者、夥伴生成分析等四構念);(3)社群媒體分析之技術/任務層面(知識管理觀點,包括描述性、診斷性、預測性與處方性分析等四構念);(4)辨識驅動因子:先驗知識(內隱化、外顯化)、社會網絡(弱套繫、強套繫)與組織警覺性(外控覺察、自我競爭)。 本研究以調查法蒐集資料。透過專家訪談與前測後形成正式量表後,以天下650大服務業與100大金融業為母體普查之。樣本以敘述統計、相關分析、迴歸分析等進行分析。 220份企業樣本之實證研究,本研究獲得下列發現: 1. 顧客與競爭者生成內容分析取向對其市場機會發掘具正向效果。 2. 描述性與診斷性分析取向對其市場機會發掘具正向效果。 3. 顧客與競爭者生成內容分析屬高度取向者,其(1)描述性與(2)診斷性分析對其市場機會發掘之效果較屬低度取向者為高。 4. 員工與夥伴生成內容分析取向對其市場機會創造具正向效果。 5. 預測性分析與處方性分析取向對其市場機會創造具正向效果。 6. 夥伴生成內容分析屬高度取向者,其處方性分析對其市場機會創造之效果較屬低度取向者為高。 7. 社群媒體形成之知識外顯化取向對機會發掘具正向效果。 8. 社群媒體形成之知識內隱化取向對機會創造具正向效果。 9. 社群媒體形成之弱套繫取向對機會發掘具正向效果。 10. 社群媒體形成之強套繫取向對機會創造具正向效果。 11. 外控覺察取向對機會發掘具正向效果。 12. 自我競爭取向對機會創造具正向效果。 13. 員工與夥伴內容分析取向對機會創造之正向影響中,(1)知識內隱化、(2)強套繫關係與(3)自我競爭具有正向中介效果。 14. 顧客與競爭者內容分析取向對機會發掘之正向影響中,(1)知識外顯化與(2)弱套繫關係具有正向中介效果。 15. 描述性與診斷性分析取向對市場機會發掘之正向影響中,外控察覺具有正向中介效果。 16. 預測性與處方性分析取向對市場機會創造之正向影響中,知識內隱性具有正向中介效果。
Social media analytics (SMA) is a growing mechanism to acquire market knowledge in order to recognize potential market opportunities for business organizations. Accordingly, this study attempts to employ a socio-technical system view, which is consisted of market orientation perspective (the socio sub-system) and knowledge management perspective (the technical sub-system), to construct firm’s SMA framework in order to explore its association with market opportunity recognition (MOR). Thus, this study attempts to achieve the following objectives. 1. To construct a solid SMA framework with a socio-technical system view. 2. To integrate the divergent perspectives of opportunity discovery versus opportunity creation (OD vs. OC) in the past arguments to re-examine MOR issues with a new duality perspective. 3. To specify and re-examine three major MOR drivers (ORD) in the literature: firms’ (1) prior knowledge, (2) social network, and (3) organizational alertness, as well as their impacts on MOR of the firms. 4. To examine the effect of SMA on MOR, as well as to clarify the moderating effect of ORD on the association between DA and MOR. Thus, this study proposes to respond the next research questions: What impacts does SMA determine on the firms’ MOR behaviors based on a socio-technical system? Does ORD have a moderating effect on the association between SMA and MOR? The empirical survey is planned to select Top 650 services providers and Top 100 financial services of 2021 in Taiwan (ranked by Common Wealth Magazine) as the population. The collected observations will be analyzed with statistical techniques. The evidences from 220 observations of the empirical survey indicate the next findings. 1. The firm’s degrees of customer-generated and competitor-generated content analytics have positive effects on OD. 2. The firm’s degrees of descriptive and diagnostic analytics have positive effects on OD. 3. Firms with higher degrees of customer-generated and competitor-generated content analytics have greater effects of descriptive and diagnostic analytics on OD than those with lower degrees. 4. The firm’s degrees of employee-generated and partner-generated content analytics have positive effects on OC. 5. The firm’s degrees of predictive and prescriptive analytics have positive effects on OC. 6. Firms with higher degrees of employee-generated and partner-generated content analytics have greater effects of predictive and prescriptive analytics on OC than those with lower degrees. 7. Firms’ degree of explicit knowledge of SMA has a positive effect on OD. 8. Firms’ degree of tacit knowledge of SMA has a positive effect on OC. 9. Firms’ degree of weak ties of SMA has a positive effect on OD. 10. Firms’ degree of strong ties of SMA has a positive effect on OC. 11. Firms’ degree of external-alertness of SMA has a positive effect on OD. 12. Firms’ degree of self-alertness of SMA has a positive effect on OC. 13. Firms’ degrees of tacit knowledge, strong ties, and self-alertness of SMA mediate on the positive effects of employee-generated and partner-generated content analytics on OC. 14. Explicit knowledge and weak ties of SMA mediate on the positive effects of customer-generated and competitor-generated content analytics on OD.
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