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A Study Of The Impact Of Data Intelligence On Software Delivery Performance, Yongdong Dong
A Study Of The Impact Of Data Intelligence On Software Delivery Performance, Yongdong Dong
Dissertations and Theses Collection (Open Access)
With the rise of big data and artificial intelligence, data intelligence has gradually become the focus of academia and industry. Data intelligence has two obvious characteristics: big data drive and application scene drive. More and more enterprises extract valuable patterns contained in data with prediction and decision analysis methods and technologies such as large-scale data mining, machine learning and deep learning and use them to improve the management and decision in complex practice, so as to promote changes of new business modes, organizational structures and even business strategies, and improve the operational efficiency of organizations. However, there are few studies …
The Effects Of Recommender System On Sales Promotion Of High-Value Products: Evidence From A Field Experiment In The Real Estate Industry, Lian Liu
Dissertations and Theses Collection (Open Access)
Real estate sales industry in China has long suffered the problem of inefficient matching of customers to projects. Inspired by the design of recommender systems, which have been widely used in the online retail industry, and are shown to facility customer-product matching and improve sales, we apply this system to the real estate sales industry using a novel approach. Instead of recommending products to customers, we suggest the best potential customers to salespeople with whom they will conduct sales with. Using city-wide sales data from the largest real estate sales company in China, we first develop a recommend system based …
The Valuation Of User-Generated Content: A Structural, Stylistic And Semantic Analysis Of Online Reviews, Noi Sian Koh
The Valuation Of User-Generated Content: A Structural, Stylistic And Semantic Analysis Of Online Reviews, Noi Sian Koh
Dissertations and Theses Collection (Open Access)
The ability and ease for users to create and publish content has provided vast amount of online product reviews. However, the amount of data is overwhelmingly large and unstructured, making information difficult to quantify. This creates challenge in understanding how online reviews affect consumers’ purchase decisions. In my dissertation, I explore the structural, stylistic and semantic content of online reviews. Firstly, I present a measurement that quantifies sentiments with respect to a multi-point scale and conduct a systematic study on the impact of online reviews on product sales. Using the sentiment metrics generated, I estimate the weight that customers place …