Zeng, DiZuo, AlecTang, Wenzhu2023-09-082023-09-082023https://hdl.handle.net/2440/139414The widespread use of the internet, changes in consumer habits, and emerging technologies have greatly enriched the online market over the past few decades, in terms of variety, sales, and adoption rates. Exploring consumer behaviour patterns and business ecology within this rapidly evolving market is critical in improving scholarly understanding and policy formulation. This thesis takes an exploratory approach, innovatively studying the behaviour of consumers in three emerging online markets – from the perspective of data sources, research methods, and market selection. Specifically, this thesis explores the consumer behaviour patterns in the Daigou market, the e-commerce platform (infant formula), and the non-fungible token (NFT) market. The three articles employ independent data collection processes. The first article harnesses first-hand Daigou (parallel trade grey market) consumer order data shared by the industry. The second article examines public data from Taobao, a large e-commerce platform, and the third article uses NFT transaction data from a public blockchain (Ethereum). Firstly, this thesis investigates the market size of Daigou products exported from Australia to China and employs three spatial models to investigate the spillover effects of this emerging online shopping format between regions. The results indicate a positive relationship between the volume of Daigou and factors such as accessibility to similar goods online and offline, cross-border communication, population age, and education at the city level. However, bonding areas compete with the Daigou channel. Spatial regression modelling shows that the Daigou destination is concentrated around economic growth centres rather than dispersed. The estimated value of Daigou packages sent from Australia to China was approximately $111 million USD (752 million RMB) in 2017. Secondly, this thesis monitors one year of Taobao data and explores how consumer comments within an online market (import infant formula) participate in online price formation. This chapter innovatively uses Bidirectional Encoder Representation from Transformers (BERT) – one of the most advanced natural language processing (NLP) tools at the time of writing – to quantify a large amount of consumer text. This method overcomes the difficulties in identifying linguistic ambiguities and domain-specific prior knowledge. The study examines three aspects of comments: the number of comments, the sentiment index determined by BERT, and the themes of the comments. The econometric model reveals that both comment count and sentiment index play crucial roles. Additionally, certain comment themes are significantly linked with online price formation, indicating that major online retailers selling high-end products should prioritise providing excellent customer service. Thirdly, this thesis also explores the bargaining power in the NFT market, a new market based on blockchain technology with a few terabytes (TBs) of on-chain transaction data. The study visualises the trading network of the NFT market and finds that traders automatically cluster into three categories: the vast majority of traders are located in the core trading circle, some are in independent trading circles with little interaction with the mainstream, while others form a loosely connected, belt-like, random group of traders. It is found that those with higher bulk tendencies possess more bargaining power in the NFT market. The results have significant implications for NFT market participants and community builders. In conclusion, the widespread adoption of the internet, changing consumer habits, and new technologies have transformed the online market in terms of variety, sales, and adoption rates. This thesis integrates novel approaches to analysing online consumer behaviour by utilising interdisciplinary techniques and cutting-edge technologies. Integrating spatial modelling, NLP, and blockchain technology sheds light on the dynamics of emerging online markets, providing insights into consumer decision-making processes, market competition, and price formation mechanisms. The results have important implications for policymakers, market participants, and academics alike, as they can inform policymaking, business strategy, and further research in this rapidly evolving field.enconsumer behaviourmarket studybig dataDaigoue-commerceNFTInvestigating on line market consumer behaviour through spatial, big data and machine learning approaches: cases in Daigou, e-commerce platform and NFT crypto marketThesis