本文關(guān)鍵詞：北京市非標(biāo)準(zhǔn)住宿產(chǎn)品滿意度研究　出處：《北京交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

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【摘要】：Airbnb作為共享經(jīng)濟(jì)下非標(biāo)準(zhǔn)住宿的開(kāi)山鼻祖,目前市值已經(jīng)達(dá)到255億美元,不僅自身發(fā)展迅速,更為我國(guó)的創(chuàng)業(yè)者開(kāi)辟了非標(biāo)準(zhǔn)住宿的道路。2015年,國(guó)務(wù)院頒發(fā)的相關(guān)意見(jiàn)提到要積極發(fā)展客棧民宿、短租公寓和長(zhǎng)租公寓。有了政策的支持,非標(biāo)準(zhǔn)住宿在國(guó)內(nèi)的發(fā)展日趨火爆。盡管非標(biāo)準(zhǔn)住宿市場(chǎng)前景看好,但目前的非標(biāo)準(zhǔn)住宿產(chǎn)品也存在著一定的問(wèn)題,如個(gè)性化本是非標(biāo)準(zhǔn)住宿產(chǎn)品的靈魂,但產(chǎn)品與服務(wù)趨同現(xiàn)象已經(jīng)在悄然蔓延,與此同時(shí),過(guò)度與不當(dāng)?shù)脑O(shè)計(jì)違反了住宿服務(wù)的基本規(guī)律,反而會(huì)降低客人的體驗(yàn)感等,這些都嚴(yán)重影響對(duì)非標(biāo)準(zhǔn)住宿產(chǎn)品的滿意程度。而隨著互聯(lián)網(wǎng)在我國(guó)日新月異的發(fā)展,旅游企業(yè)早已融入到了互聯(lián)網(wǎng)大潮中,無(wú)時(shí)不在的客戶評(píng)價(jià),既是客戶需求的真實(shí)反映,更是企業(yè)改革的方向,當(dāng)企業(yè)將客戶的評(píng)價(jià)融入到企業(yè)的發(fā)展、內(nèi)部的變革和效益的增長(zhǎng)時(shí),它將會(huì)在市場(chǎng)經(jīng)濟(jì)的作用下獲得豐厚的回報(bào)。而本文針對(duì)非標(biāo)準(zhǔn)住宿產(chǎn)品的滿意度研究就可以幫助旅游企業(yè)找到客戶對(duì)于住宿產(chǎn)品滿意或者不滿意的內(nèi)容,以便于企業(yè)有針對(duì)性地改善產(chǎn)品與服務(wù),做到精準(zhǔn)網(wǎng)絡(luò)營(yíng)銷,提高顧客滿意度,增強(qiáng)顧客忠誠(chéng)度和增強(qiáng)口碑效應(yīng)。本文通過(guò)對(duì)利用網(wǎng)絡(luò)爬蟲(chóng)技術(shù)抓取攜程網(wǎng)上北京市的所有非標(biāo)準(zhǔn)住宿產(chǎn)品的評(píng)論,借助軟件ROSTCM6及一定的編程及人工處理將通過(guò)網(wǎng)絡(luò)爬蟲(chóng)技術(shù)抓取的用戶評(píng)論進(jìn)行分詞等并構(gòu)建出了本文的關(guān)鍵詞詞庫(kù),并基于此,構(gòu)建了非標(biāo)準(zhǔn)住宿產(chǎn)品滿意度評(píng)價(jià)指標(biāo)體系,并通過(guò)關(guān)鍵詞賦分、指標(biāo)權(quán)重分配等將文本評(píng)論進(jìn)行量化處理,根據(jù)設(shè)計(jì)的算法計(jì)算出非標(biāo)準(zhǔn)住宿產(chǎn)品各評(píng)價(jià)指標(biāo)、維度以及整體的滿意度得分。通過(guò)計(jì)算數(shù)據(jù)可知,北京市的非標(biāo)準(zhǔn)住宿產(chǎn)品顧客滿意度整體偏低,顧客尤其是對(duì)非標(biāo)準(zhǔn)住宿產(chǎn)品的設(shè)施不滿意,并且對(duì)服務(wù)的滿意度較低。本文最后利用雷達(dá)圖分析法對(duì)計(jì)算出的數(shù)值進(jìn)行分析,同時(shí)借助UCNET軟件對(duì)代表性指標(biāo)進(jìn)行了網(wǎng)絡(luò)中心度分析,找出了影響北京市非標(biāo)準(zhǔn)住宿產(chǎn)品顧客滿意度的因素如配套設(shè)施、客房服務(wù)、衛(wèi)生等,并據(jù)此提出了相應(yīng)的改善建議如制定相關(guān)行業(yè)規(guī)范、相關(guān)企業(yè)注重個(gè)性化服務(wù)以及加強(qiáng)基礎(chǔ)設(shè)施建設(shè)等,以期幫助非標(biāo)準(zhǔn)住宿企業(yè)提高顧客滿意度。本文的創(chuàng)新點(diǎn)在于通過(guò)設(shè)計(jì)用戶評(píng)論挖掘系統(tǒng)框架,將游客評(píng)論進(jìn)行量化,并對(duì)相應(yīng)數(shù)據(jù)進(jìn)行了處理,得出的結(jié)論更有說(shuō)服力。
[Abstract]:Airbnb, the founder of non-standard accommodations in the shared economy, has reached $25.5 billion, not just by itself. In 2015, the relevant opinions issued by the State Council mentioned the need to actively develop hostel, short rental apartment and long rental apartment. Although the prospect of non-standard accommodation market is promising, there are some problems in the current non-standard accommodation products, such as individuation is the soul of non-standard accommodation products. But the convergence of products and services has spread quietly, at the same time, excessive and improper design violates the basic rules of accommodation services, but will reduce the experience of guests and so on. These have seriously affected the satisfaction of non-standard accommodation products. With the rapid development of the Internet in China, tourism enterprises have already been integrated into the Internet tide, customer evaluation at all times. It is not only the true reflection of customer demand, but also the direction of enterprise reform, when enterprises integrate customer evaluation into the development of enterprises, internal changes and growth of efficiency. It will be in the role of the market economy to obtain rich returns. And this study on the satisfaction of non-standard accommodation products can help tourism enterprises find customer satisfaction or dissatisfaction with the content of accommodation products. In order to facilitate the enterprise to improve the products and services, to achieve accurate network marketing, improve customer satisfaction. This paper reviews the use of web crawler technology to capture all non-standard accommodation products in Ctrip online in Beijing. With the help of software ROSTCM6 and certain programming and manual processing, the user comments grabbing through web crawler technology are segmented and the key word library of this paper is constructed, and based on this. A non-standard residential product satisfaction evaluation index system is constructed, and the text comments are quantified through keyword scoring, index weight distribution and so on. According to the algorithm designed to calculate the non-standard accommodation product evaluation indicators, dimensions and overall satisfaction score. Through the calculation of data, we can see that the customer satisfaction of non-standard accommodation products in Beijing is on the low side. Customers, especially the facilities of non-standard accommodation products are not satisfied, and the satisfaction of the service is low. Finally, this paper uses radar map analysis method to analyze the calculated values. At the same time, with the help of UCNET software, the network center degree of the representative indicators is analyzed, and the factors that affect the customer satisfaction of non-standard accommodation products in Beijing, such as supporting facilities, room service, sanitation and so on, are found out. Based on this, the author puts forward the corresponding improvement suggestions, such as formulating relevant industry norms, paying attention to individualized service and strengthening infrastructure construction, etc. In order to help non-standard residential enterprises to improve customer satisfaction. The innovation of this paper is to design the framework of user comment mining system to quantify the tourist comments and to deal with the corresponding data. The conclusions are more convincing.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F719.2

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