Exploring Trust in Online Ride-sharing Platform in China: A Perspective of Time and Location

Trust is a key issue to be considered deliberately in the online ride-sharing platform to reduce risk and ensure transactions. In this paper, trust-in-platform is explored from these two perspectives to fill the research gaps. A ride-sharing platform in China was investigated. Results show that trust-in-platform in economically developing districts is slightly higher than that in economically developed districts. At the same time, trust-in-platform level differs in time, trust-in-platform levels are obviously lower between 19’o clock and 23’o clock. Moreover, machine learning is employed to predict the relationships between time/location and trust-in-platform. The result is that recall is 78.3%, precision is 57.3%, and F1 is 66.2%. The result shows trust-in-platform has an obvious correlation with time and location, thus further consolidates the findings. This study contributes to the existing knowledge on trust in the ride-sharing platforms and has practical implications for platform operators

Stochastic Portfolio Selection Problem with Reliability Criteria

Portfolio selection focuses on allocating the capital to a set of securities such that the profit or the risks can be optimized. Due to the uncertainty of the real-world life, the return parameters always take uncertain information in the realistic environments because of the scarcity of the a priori knowledge or uncertain disturbances. This paper particularly considers a portfolio selection process in the stochastic environment, where the return parameters are characterized by sample-based correlated random variables. To decrease the decision risks, three evaluation criteria are proposed to generate the reliable portfolio selection plans, including max-min reliability criterion, percentile reliability criterion, and expected disutility criterion. The equivalent linear (mixed integer) programming models are also deduced for different evaluation strategies. A genetic algorithm with a polishing strategy is designed to search for the approximate optimal solutions of the proposed models. Finally, a series of numerical experiments are implemented to demonstrate the effectiveness and performance of the proposed approaches

Have market-oriented reforms decoupled China's CO₂ emissions from total electricity generation? An empirical analysis

Achieving the decoupling of electric CO2 emissions from total electricity generation is important in ensuring the sustainable socioeconomic development of China. To realize this, China implemented market-oriented reforms to its electric power industry at the beginning of 2003. This study used the Tapio decoupling index, the Laspeyres decomposition algorithm, and decoupling-related data from 1993 to 2012 to evaluate the effect of these reforms. Several conclusions can be drawn based on the empirical analysis. (1) The reforms changed the developmental trend of the decoupling index and facilitated its progress towards strong decoupling. (2) The results forecasted through fitting the curve to the decoupling index indicate that strong decoupling would be realized by 2030. (3) Limiting the manufacturing development and upgrading the generation equipment of the thermal power plants are essential for China to achieve strong decoupling at an early date. (4) China should enhance regulatory pressures and guidance for appropriate investment in thermal power plants to ensure the stable development of the decoupling index. (5) Transactions between multiple participants and electricity price bidding play active roles in the stable development of the decoupling index

An Investigation on Factors Affecting Stock Valuation Using Text Mining for Automated Trading

Predicted price-to-book value ratios (P/BV) are widely used for the valuation of listed common stocks. However, with the application of automated trading system (ATS), the existing indicators that are applied in the method are losing their effectiveness in the Chinese market. Combining qualitative research with the text mining method, this study explores and validates those ignored factors to improve the accuracy of the stock valuation. On the basis of the principal of the existing valuation method, we clarify the scope of the factors that affects the P/BV ratio prediction. Through semi-structured interviews that are designed with six first-level factors which are taken from the literature, we then excavate some second-level factors. After that, with three corpuses including samples form Sina.com.cn, Xueqiu.com, and CSDN.net, four first-level factors and thirteen second-level factors have been verified step by step through the Latent Dirichlet Allocation (LDA) model. In the process, two other new factors and three sub-factors are also found. Furthermore, based on the factor correlation that was found in a data analysis, a factor relationship model was built. The results can be used in a stock valuation in future work as the basis of the indicator system for the prediction of P/BV ratio

The Depression and Adsorption Mechanism of Polyglutamic Acid on Chalcopyrite and Pyrrhotite Flotation Systems

The rejection of pyrrhotite and pyrite has become a long-standing problem in the copper ore industry. This paper describes the first successful depression and adsorption mechanism of a novel and non-hazardous reagent, polyglutamic acid (PGA), on pyrrhotite in the selective flotation of chalcopyrite with xanthate as the collector, making use of various laboratory-scale measurement techniques. The addition of PGA inhibited the flotation of pyrrhotite much more strongly than that of the chalcopyrite in a wide pH range. The prior addition of PGA achieved an improved selective flotation of chalcopyrite from pyrrhotite at pH 8, at which the grade and recovery of chalcopyrite in concentrate were over 80%. Surface measurement techniques including XPS spectral, IR spectral, zeta potential, and reagent adsorption analyses indicated that the PGA interacted differently with the two minerals, and had much greater affinity towards pyrrhotite than chalcopyrite. The presence of PGA blocked the electrochemical activity of the collector on the pyrrhotite surface and thus depressed its flotation, whereas the adsorption of the collector and its oxidation to dixanthogen were more effective on the chalcopyrite surface, indicating a weaker interaction of PGA with chalcopyrite. Our results suggest that the application of PGA could replace the toxic inorganic depressants in flotation technology, and could significantly reduce the environmental impacts of processing

Peroxymonosulfate Activation by Iron Sulfide Minerals for Degradation of Various Thiol Collectors in Mineral Processing Wastewater: Performance, Mechanism, and Structure–Activity Relationship

The quantity of mineral processing wastewater (MPW) is large and contains residual thiol collectors, which easily cause environmental pollution. Herein, we systematically investigated the catalytic performances and underlying mechanisms of iron sulfide minerals (pyrite, marcasite, and pyrrhotite) for the activation of peroxymonosulfate (PMS) to treat MPW containing various thiol collectors (ethyl xanthate (EX), butyl xanthate (BX), diethyldithiocarbamate (DDTC)). Density functional theory (DFT) calculation results indicated that electron-rich Fe atoms in pyrite and marcasite acted as electron donors for PMS adsorption and cleavage, while pyrrhotite with electron-deficient Fe atoms has no PMS adsorption site. In particular, pyrite has stronger reactivity in comparison with marcasite due to more electron transfer and the lower thermodynamic and kinetic energy barrier of the reaction. Meanwhile, the efficient electron transfer of pyrite with strong F–S covalent bonds facilitated the regeneration of Fe(II), thus improving the catalytic performance. As a result, pyrite exhibited the highest total organic carbon (TOC) removal efficiency for real MPW, which was 1.12-fold and 1.63-fold of that on marcasite and pyrrhotite, respectively. This study highlights the structure–activity relationship of iron sulfide minerals and provides new insights into the PMS activation mechanism of sulfur-containing catalysts for MPW treatment