本文選題：獎賞激勵 + 任務(wù)導(dǎo)向　； 參考：《渤海大學(xué)》2017年碩士論文

【摘要】：隨著經(jīng)濟(jì)的快速發(fā)展和科學(xué)技術(shù)的不斷進(jìn)步,企業(yè)間的競爭愈演愈烈。企業(yè)的創(chuàng)新不僅依賴自身知識資源的整合,而且還需要吸收外部的優(yōu)質(zhì)知識資源。近年來,互聯(lián)網(wǎng)技術(shù)使大眾參與企業(yè)創(chuàng)新成為可能,眾包社區(qū)作為聯(lián)結(jié)企業(yè)和大眾的中介平臺應(yīng)運(yùn)而生。由于眾包社區(qū)能夠獲取高質(zhì)量的知識,眾包社區(qū)紛紛建立。但用戶間活躍度低,不愿意進(jìn)行知識共享,使得眾包社區(qū)的發(fā)展?fàn)顩r并不樂觀。為了提高眾包社區(qū)的任務(wù)量和提供企業(yè)優(yōu)質(zhì)信息,需要發(fā)掘眾包社區(qū)用戶知識共享的關(guān)鍵影響因素。本文以眾包社區(qū)用戶為研究對象,采用主成分分析法提取出影響眾包社區(qū)用戶知識共享的關(guān)鍵因素,引入關(guān)系嵌入為調(diào)節(jié)變量,建立理論模型,研究眾包社區(qū)用戶知識共享機(jī)制。其中將關(guān)系嵌入分為信任、關(guān)系強(qiáng)度和承諾三個(gè)維度,提出研究假設(shè),進(jìn)行實(shí)證分析。本文得出以下結(jié)論:第一,獎賞激勵、任務(wù)導(dǎo)向和興趣參與是影響眾包社區(qū)用戶知識共享的關(guān)鍵因素,且對知識共享有顯著的正向影響。第二,對具有不同程度關(guān)系嵌入性的眾包社區(qū)而言,獎賞激勵、任務(wù)導(dǎo)向和興趣參與對知識共享的影響是不同的。關(guān)系嵌入負(fù)向調(diào)節(jié)獎賞激勵與知識共享的關(guān)系、正向調(diào)節(jié)任務(wù)導(dǎo)向與知識共享的關(guān)系、正向調(diào)節(jié)興趣參與與知識共享的關(guān)系。預(yù)期的創(chuàng)新點(diǎn)如下:第一,發(fā)現(xiàn)影響眾包社區(qū)用戶知識共享的關(guān)鍵因素。第二,豐富關(guān)系嵌入調(diào)節(jié)作用的研究。第三,構(gòu)建眾包社區(qū)用戶知識共享的概念模型。
[Abstract]:With the rapid development of economy and the progress of science and technology, the competition between enterprises is becoming more and more fierce. The innovation of enterprises not only depends on the integration of their own knowledge resources, but also needs to absorb external high quality knowledge resources. In recent years, Internet technology has made it possible for the masses to participate in enterprise innovation, and the crowdsourcing community as an intermediary platform connecting enterprises and the public has emerged as the times require. Because crowdsourcing communities can acquire high-quality knowledge, crowdsourcing communities have been established. However, the low activity among users and their reluctance to share knowledge make the development of crowdsourcing community not optimistic. In order to improve the task quantity of crowdsourcing community and provide high quality information, we need to explore the key factors of user knowledge sharing in crowdsourcing community. In this paper, we take crowdsourcing community users as the research object, use principal component analysis to extract the key factors that affect the knowledge sharing of crowdsourcing community users, introduce the relationship embedding as adjustment variables, and establish a theoretical model. This paper studies the mechanism of user knowledge sharing in crowdsourcing community. The relationship embedding is divided into three dimensions: trust, relationship strength and commitment. The main conclusions are as follows: first, reward motivation, task orientation and interest participation are the key factors that affect the knowledge sharing of users in crowdsourcing community, and have a significant positive impact on knowledge sharing. Second, for crowdsourcing communities with different degrees of relational embeddedness, the effects of reward incentives, task-orientation and interest participation on knowledge sharing are different. The relationship is embedded in the relationship between reward incentive and knowledge sharing, the relationship between task orientation and knowledge sharing, and the relationship between interest participation and knowledge sharing. The expected innovations are as follows: first, the key factors affecting the knowledge sharing of crowdsourcing community users are found. Second, the study of rich relationship embedded regulation. Thirdly, construct the conceptual model of user knowledge sharing in crowdsourcing community.
【學(xué)位授予單位】：渤海大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F273.1

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本文編號：1916910