What Should Streamers Communicate in Livestream E-Commerce? The Effects of Social Interactions on Live Streaming Performance

Compared with traditional e-commerce, livestreaming e-commerce is characterized by direct and intimate communication between streamers and consumers that stimulates instant social interactions. This study focuses on streamers’ three types of information exchange (i.e., product information, social conversation, and social solicitation) and examines their roles in driving both short-term and long-term livestreaming performance (i.e., sales and customer base growth). We find that the informational role of product information (nonpromotional and promotional) is beneficial not only to sales performance, but also to the growth of the customer base. We also find that social conversation has a relationship-building effect that positively impacts both sales and customer base growth, whereas social solicitation has both a relationship-building and a relationship-straining effect that positively affects customer base growth but can hurt sales. Furthermore, our results show that streamers’ social interactions with consumers can stimulate consumer engagement in different ways, leading to different effects on livestreaming performance

Mutations in TUBB8 and Human Oocyte Meiotic Arrest

BACKGROUND Human reproduction depends on the fusion of a mature oocyte with a sperm cell to form a fertilized egg. The genetic events that lead to the arrest of human oocyte maturation are unknown. METHODS We sequenced the exomes of five members of a four-generation family, three of whom had infertility due to oocyte meiosis I arrest. We performed Sanger sequencing of a candidate gene, TUBB8, in DNA samples from these members, additional family members, and members of 23 other affected families. The expression of TUBB8 and all other β-tubulin isotypes was assessed in human oocytes, early embryos, sperm cells, and several somatic tissues by means of a quantitative reverse- transcriptase–polymerase-chain-reaction assay. We evaluated the effect of the TUBB8 mutations on the assembly of the heterodimer consisting of one α-tubulin polypeptide and one β-tubulin polypeptide (α/β-tubulin heterodimer) in vitro, on microtubule architecture in HeLa cells, on microtubule dynamics in yeast cells, and on spindle assembly in mouse and human oocytes. RESULTS We identified seven mutations in the primate-specific gene TUBB8 that were responsible for oocyte meiosis I arrest in 7 of the 24 families. TUBB8 expression is unique to oocytes and the early embryo, in which this gene accounts for almost all the expressed β-tubulin. The mutations affect chaperone-dependent folding and assembly of the α/β-tubulin heterodimer, disrupt microtubule behavior on expression in cultured cells, alter microtubule dynamics in vivo, and cause catastrophic spindle-assembly defects and maturation arrest on expression in mouse and human oocytes. CONCLUSIONS TUBB8 mutations have dominant-negative effects that disrupt microtubule behavior and oocyte meiotic spindle assembly and maturation, causing female infertility. (Funded by the National Basic Research Program of China and others.

Pit initiation on passivated metal surfaces: crystallographic orientation and environmental effects

The susceptibility to pitting corrosion of tin and zinc was found to be dependent on the crystallographic orientation of the surface in chloride solutions. For tin single crystals, the(111) face showed the lowest critical pitting potential among five differently oriented surfaces. The critical pitting potential of zinc single crystals decreased with the surface orientation in the following order: (1010) > (1120) > (0001). The critical pitting potentials for zinc and aluminum were found to be lower in chloride solutions than in bromide solutions. The effects of the solution pH, the presence of buffers, and halide ion species on the pitting of polycrystalline nickel were investigated in 1.0 M halide solutions. It was found that the critical pitting potential (Ecp) was independent of the pH of unbuffered solutions in the pH region of 4.5 to 10.5. However, Ecp was greatly increased at pH 12.5, and pitting corrosion was totally retarded at pH 14 in 1.0 M NaC1 solution. The addition of Na2CO3/NaHCO3 orNa3PO4/Na2HPO4 buffer to the pH 10.5 solution raised the critical pitting potential of nickel. Furthermore, Ecp was lower in the chloride solution than in the bromide solution. Using published thermodynamic data for halide complexes, potential-pH (E-pH) and halide concentration - pH (X-pH) diagrams were constructed for H20-halide-metal (Sn, Zn, Al and Ni) systems. With increasing halide concentration, the formation of halide complexes is thermodynamically favoured and the zone of passivity is diminished. These new diagrams are unique and useful in the understanding of pit initiation. A pitting theory is proposed, which emphasizes the change in local solution chemistry and the formation of halide complexes during the pit initiation process. Pits will be nucleated when conditions are met for the formation of stable halide complexes in the local region. This theory successfully accounts for the effects of the solution pH, buffers, halide ions and the crystallographic orientations of single crystals on pitting behavior. It may also explain other aspects such as the effects of temperature, alloying elements, and fluid flow on the pitting corrosion of metals.Applied Science, Faculty ofMaterials Engineering, Department ofGraduat

Focusing on Risk and Brand Perspective

The 4th industrial revolution is changing modern society dramatically from the way people used to live and the mode businesses used to operate. With the trend of digitalization and globalization, the conventional economic activities and financial systems are also deeply reshaped. The banking industry, playing a dominant role in financial systems, is also transformed from “the business of saving money” to “the business of money” and currently “the business of customers”. Nowadays, the bank industry faces two major challenges. On the one hand, brought by digitalization, the rapidly growing business volume challenges the bank’s customer risk estimation. In addition, the strengthened regulatory requirements also raised expectation for higher efficiency and accuracy. On the other hand, brought by globalization, banks also faced the challenge of obtaining a superior position from the local, foreign, and Fintech competitors. Therefore, this thesis focuses on strengthening the competitiveness of commercial banks by decreasing the risk brought by customers and increasing the brand value of banks. Specifically, this thesis addresses the following three main contributions: First of all, an accurate and efficient customer risk-level classifier is developed with neural network at the account opening service, which provides a first-gated risk assessment for customers. Experimental results showed that the proposed method achieved 96.7% accuracy, which surpasses existing methods. Such an automatic and labor-saving risk-level classifier is a crucial step to efficiently mitigate banks’ potential risks and losses, which also benefits the brand of banks. Secondly, to generate more connections with new customers, a bank-oriented study is developed to systematically investigate the impact of bank brand value from macro, meso, and micro levels with multi-variables regression analysis. The importance of the three levels of factors is numerically estimated respectively. Micro-level is found to play the most influential role. Consequently, a further investigation between the micro-level variables and bank brand value is explored. The findings guide the bank managers to optimize resource allocation. By grasping the core of the brand value development, banks can attract more customers so that obtain a superior position in the market. Thirdly, a comparison study of the top banks in China and Korea is conducted. As the key representatives of emerging economies and developed economies respectively from East Asia, both China and Korea show increased importance and influence on the global stage. The findings of this study show commonalities and heterogeneities of factors that contribute to a bank’s brand value in both markets, suggesting that customized strategy should be applied to fit the different economic realities of bank’s-based country.Chapter 1 Introduction 1 1.1 Background 1 1.2 Purpose of Research 4 1.3 Methodologies and Key Contributions 8 1.4 Organization of the Thesis 9 Chapter 2 The First Gate Customer Risk Assessment 12 2.1 Risk Assessment in the Retail Banking Business 12 2.1.1 External environment: digital economy and finance 12 2.1.2 Changes in the environment of banking business 15 2.1.3 Challenges to the banking business 16 2.2 Limitations of Existing Customer Risk Assessment Frameworks 18 2.3 First Gate Risk Assessment: Procedures in Account Opening Service 25 2.4 Automatic Customer Risk-level Classifier with the Neural Network at the Account Opening Service 30 2.4.1 Data collection and preprocessing 33 2.4.2 Feature extraction 35 2.4.3 2-staged NN-based customer’s risk classification model 45 2.5 Experimental Results and Analysis 49 2.5.1 Overall performance 52 2.5.2 Comparison with other machine learning algorithms 52 Chapter 3 Strengthen the Brand in the Banking Business 55 3.1 The Role of Brand in Banking Business 55 3.2 Customer-oriented Brand Studies in the Banking Business 58 3.3 Bank-oriented Brand Studies 60 3.4 Bank Core Competence Model 62 3.5 Importance Analysis with Multi-variable Linear Regression 72 3.5.1 Data collection 72 3.5.2 Data preprocessing: principal component analysis 74 3.5.3 Multivariable regression analysis 78 3.5.4 Multicollinearity problem: stepwise regression 79 3.6 Results and Analysis 80 3.6.1 PCA based factor analysis in three levels 80 3.6.2 Analysis of the benchmark regression 83 3.6.3 Stepwise regression with Micro level variables 85 3.6.4 Comparison between banks in Korea and China 88 Chapter 4 Discussion and Implication 93 4.1 Implications of Bank’s Risk Assessment 93 4.2 Implications of Bank’s Brand Value 95 4.3 The Implication of Brand Value Improvement with Strengthened Risk Control are Inseparable in Bank Business 98 Chapter 5 Conclusion 101Docto

The Impact of Environmental Protection Investment on Provincial Carbon Emissions in China: Empirical Analysis Based on Two-way Fixed Effects Model

In confront of global climate change, promoting carbon emission reduction and sustainable development has come to be acknowledged internationally. On the basis of panel data from 30 Chinese provinces from 2009 to 2020, this paper undertakes an empirical investigation into the connection between carbon emission intensity and investment in environmental protection. The findings demonstrate that investment in environmental protection has a nonlinear inverted U-shaped relationship with carbon emission intensity, that is, with the increase of environmental protection investment, its effect on carbon emission has changed from promoting to inhibiting. And the influence degree varied in different regions, with the influence in western and central regions being significantly stronger than that in eastern regions. The government should take full account of local conditions and formulate policies of environmental protection investment in accordance with local conditions

Short-Term Photovoltaic Power Output Prediction Based on <i>k</i>-Fold Cross-Validation and an Ensemble Model

Short-term photovoltaic power forecasting is of great significance for improving the operation of power systems and increasing the penetration of photovoltaic power. To improve the accuracy of short-term photovoltaic power forecasting, an ensemble-model-based short-term photovoltaic power prediction method is proposed. Firstly, the quartile method is used to process raw data, and the Pearson coefficient method is utilized to assess multiple features affecting the short-term photovoltaic power output. Secondly, the structure of the ensemble model is constructed, and a k-fold cross-validation method is used to train the submodels. The prediction results of each submodel are merged. Finally, the validity of the proposed approach is verified using an actual data set from State Power Investment Corporation Limited. The simulation results show that the quartile method can find outliers which contributes to processing the raw data and improving the accuracy of the model. The k-fold cross-validation method can effectively improve the generalization ability of the model, and the ensemble model can achieve higher prediction accuracy than a single model

Capturing Associations and Sustainable Competitiveness of Brands from Social Tags

With the explosion of social media, consumers&rsquo; minds have become important assets in brand competitions. Determining a brand&rsquo;s competitive structure based on consumers&rsquo; desires is particularly important to effectively establish a brand and maintain sustainable competitiveness. The traditional methods of determining brand competitiveness are costly and time-consuming. In this study, we propose an efficient, systematical, highly automated, and real-time method to determine brand competitiveness based on consumers&rsquo; brand associations with the brand&rsquo;s social tags. Using a set of 45 brands in the automobile industry and around 50,000 social tags, we compared our brand competitiveness determination method with data provided by Interbrand and directly elicited survey data, finding a significant correlation and a better predictive power in consumers&rsquo; perceived brand competitiveness than the traditional method. Our proposed method enables managers to create and maintain sustainable brand advantages in consumers&rsquo; minds