A Study on the Factors Influencing Consumer Purchase Decision Under the Live-Streaming Sales Model

In recent years,with the rapid development and popularization of Internet information technology,many new media platforms have risen rapidly,and major e-commerce companies have begun to explore the mode of livestreaming.Especially during the COVID-19 pandemic,due to the lockdown,live-streaming has become an important means of economic development in many places.Owing to its remarkable characteristics of timeliness,entertainment,and interactivity,it has become the latest and trendiest sales mode of e-commerce channels,reflecting huge economic potential and commercial value.This article analyzes two models and their characteristics of live-streaming sales from a practical perspective.Based on this,it outlines consumer purchasing decisions and the factors that affect consumer purchasing decisions under the live-streaming sales model.Finally,it discusses targeted suggestions for using the live-streaming sales model to expand the consumer market,hoping to promote the healthy and steady development of the live-streaming sales industry.

Production Chain Length and PPI-CPI Divergence:Analysis Based on the Global Input-output Price Model

Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.

The Prediction for the Consumer Price Index of Residents in Perspective of Time Series Method in Case of Chongqing

The consumer price index (CPI) measures the relative number of changes in the price level of consumer goods and services over time, reflecting the trend and degree of changes in the price level of goods and services purchased by residents. This article uses the ARMA model to analyze the fluctuation trend of the CPI (taking Chongqing as an example) and make short-term predictions. To test the predictive performance of the model, the observation values from January to December 2023 were retained as the reference object for evaluating the predictive accuracy of the model. Finally, through trial predictions of the data from May to August 2023, it was found that the constructed model had good fitting performance.

Trust beyond Technology Algorithms: A Theoretical Exploration of Consumer Trust and Behavior in Technological Consumption and AI Projects

In an era dominated by artificial intelligence (AI), establishing customer confidence is crucial for the integration and acceptance of AI technologies. This interdisciplinary study examines factors influencing customer trust in AI systems through a mixed-methods approach, blending quantitative analysis with qualitative insights to create a comprehensive conceptual framework. Quantitatively, the study analyzes responses from 1248 participants using structural equation modeling (SEM), exploring interactions between technological factors like perceived usefulness and transparency, psychological factors including perceived risk and domain expertise, and organizational factors such as leadership support and ethical accountability. The results confirm the model, showing significant impacts of these factors on consumer trust and AI adoption attitudes. Qualitatively, the study includes 35 semi-structured interviews and five case studies, providing deeper insight into the dynamics shaping trust. Key themes identified include the necessity of explainability, domain competence, corporate culture, and stakeholder engagement in fostering trust. The qualitative findings complement the quantitative data, highlighting the complex interplay between technology capabilities, human perceptions, and organizational practices in establishing trust in AI. By integrating these findings, the study proposes a novel conceptual model that elucidates how various elements collectively influence consumer trust in AI. This model not only advances theoretical understanding but also offers practical implications for businesses and policymakers. The research contributes to the discourse on trust creation and decision-making in technology, emphasizing the need for interdisciplinary efforts to address societal challenges associated with technological advancements. It lays the groundwork for future research, including longitudinal, cross-cultural, and industry-specific studies, to further explore consumer trust in AI.

Producer/Consumer通信模式在ControlNet上的实现

本文主要介绍了Producer/Consumer通信模式的传送原理,以及它是如何通过CTDMA算法在ControlNet上实现的,并说明了ControlNet的组态及网络中的Keeper所发挥的作用。另外,根据使用ControlNet的经验,介绍了在使用ControlNet时应该注意的一些问题。

Forecasting Model Based on Information-Granulated GA-SVR and ARIMA for Producer Price Index

The accuracy of predicting the Producer Price Index(PPI)plays an indispensable role in government economic work.However,it is difficult to forecast the PPI.In our research,we first propose an unprecedented hybrid model based on fuzzy information granulation that integrates the GA-SVR and ARIMA(Autoregressive Integrated Moving Average Model)models.The fuzzy-information-granulation-based GA-SVR-ARIMA hybrid model is intended to deal with the problem of imprecision in PPI estimation.The proposed model adopts the fuzzy information-granulation algorithm to pre-classification-process monthly training samples of the PPI,and produced three different sequences of fuzzy information granules,whose Support Vector Regression(SVR)machine forecast models were separately established for their Genetic Algorithm(GA)optimization parameters.Finally,the residual errors of the GA-SVR model were rectified through ARIMA modeling,and the PPI estimate was reached.Research shows that the PPI value predicted by this hybrid model is more accurate than that predicted by other models,including ARIMA,GRNN,and GA-SVR,following several comparative experiments.Research also indicates the precision and validation of the PPI prediction of the hybrid model and demonstrates that the model has consistent ability to leverage the forecasting advantage of GA-SVR in non-linear space and of ARIMA in linear space.

Understanding Credit Risk in Internet Consumer Finance:An Empirical Analysis with a Focus on the Young Generation

In recent years,internet finance has garnered increasing attention from the public.Online lending,emerging within the framework of Internet finance as a pivotal component,has witnessed substantial growth.While online credit,within the realm of Internet finance,presents numerous advantages over traditional lending,it concurrently exposes a plethora of credit risk issues.This study aims to facilitate the effective utilization of online credit tools by the young generation within the context of Internet finance.Additionally,it seeks to ensure the overall stability of the Internet finance environment and mitigate risks for the youth.Given the significance of understanding credit risk management for college students in the age of internet finance,this paper adopts the logistic model to evaluate credit risk in internet consumer finance and provides pertinent recommendations from the perspective of the young generation.

Consumer attitudes towards the mountain product label: Implications for mountain development

To protect and promote the originality and authenticity of mountain foodstuffs, the European Union set Regulation No 1151/2012 to create the optional quality term "mountain product". Our research aimed at exploring the attractiveness of the mountain product label for consumers, considering both attitude towards the label itself and purchase intentions. We propose a model to investigate relationships between four latent constructs-mountain attractiveness, mountain food attractiveness, attitude towards the mountain product label, and purchase intention-which have been tested, thus confirming the statistical relevance of the relationships. All 47 items selected for describing the latent constructs are suitable for this purpose. Ridge and LASSO results also show that 17 items of the first three constructs are relevant in explaining purchase intentions. Some contextual variables, such as age, income, geographical origin of consumers, and knowledge of mountain products and mountains for tourism purposes, can positively influence consumers’ behavior. These findings could support the design of mountain development strategies, in particular marketing actions for both the product and the territory.

Defects of Traditional Marketing Model and New Consumer Experience Requirements in the Context of"New Retail"

With the concept of"new retail"and the rapid development of"new retail"format,the defects of traditional marketing models such as advertising marketing,direct marketing and e-commerce marketing are becoming more and more obvious,which has seriously hindered the further development of the consumer retail industry.At the same time,under the background of"new retail",the industry demand based on the improvement of consumer experience is increasingly characterized by consumer entertainment,consumer autonomy,consumer personalization,and consumer socialization,which provides ideas and reference for the construction of new marketing models in the consumer retail industry.

Research on Consumers' WeChat Shopping Behavior Based on TAM Model

In the era when online shopping economy and online economy increasingly dominate social consumption,WeChat shopping has increasingly become a way that everyone accepts and is willing to try.This study applied Technology Acceptance Model commonly used in the field of information technology and rational behavior theory to the field of consumer behavior,and used the perceived ease of use and perceived usefulness in the technology acceptance model to explain consumers'willingness to use WeChat shopping.At the same time,the moderating effect of consumer innovativeness was also studied.The empirical results show that the main effect of perceived ease of use and usefulness is significant,and the moderating effect of consumer innovativeness is not significant.Based on the research results,the study puts forward the corresponding countermeasures and suggestions.

Comparison among the Consumption Structures of Different Income Groups of Urban Residents in Guangxi Based on ELES Model

According to the household consumption data of urban residents in Guangxi Statistical Yearbook in the year 2009, the ELES (Extended Linear Expenditure System) is used to analyze the consumption structure, the propensity to consume, and the consumer flexibility of urban residents in Guangxi Zhuang Autonomous Region of China in the year 2008. Result shows that urban residents in Guangxi has relatively low propensity to consume. And their consumption, especially the middle and low-income families, is mostly concentrated in food, cloth, lodging and other basic necessities of life, which account for more than a half of their income. Based on this, corresponding suggestions are put forward to enlarge the consumption demand of urban residents in Guangxi, such as increasing the regulation of income redistribution, minimizing the gap between the rich and the poor, enhancing the overall consumption level, cultivating the consumption hot spots for the urban residents, and actively guiding the enjoyable consumption.

Consumer Preferences for Water Supply at Njala University, Njala Campus in Southern Sierra Leone

Suppliers of potable water would benefit from a sustainable business as long as consumers continue to prefer their brand. Some of the reasons for choosing a particular brand include water quality, cost of the finished product, reliability of supply, and supplier ethics. These important determinant factors form the basis of this work. The objective is to delineate consumer preferences for water supplied to the Njala campus community, in southern Sierra Leone, and the underlying determinant factors. A list of questions administered to 140 respondents, are used to help achieve the objective. The results of water quality tests are also used to determine if quality has anything to do with consumer preference. The Oxfam Delagua water testing kit is customized to incubate and enhance counting of fecal and no-fecal coliform bacteria in water samples. Bacterial contamination is the major concern in the study area. The survey results reveal the consumers prefer package water for drinking. Treated water from Tia River is only used for other domestic purposes. The consumers do not trust the quality of water supplied from Tia River, albeit filtration and disinfection at the University’s treatment center. This distrust is confirmed by the bacterial test. None of the campus water sources meet recommended guidelines for drinking water. The consumers are, however, willing to shift preference from package to tap drinking water if treatment comes with quality assurance. The university could benefit through economic gratification, customer protection, and reduced plastic waste from package drinking water.

Comprehensive Assessment and Promotion Policy of Producer Services' Competitiveness in Beijing City:A Comparative Analysis among Beijing,Tianjin,Shanghai,Guangzhou and Shenzhen

The five central cities-Beijing,Tianjin,Shanghai,Guangzhou and Shenzhen-of the three most important strategic regions in China,namely Beijing-Tianjin-Hebei metropolitan region,the Yangtze River Delta and the Pearl River Delta,are taken as a comparative analysis on urban producer services' competitiveness,especially focusing on the comparative advantages and disadvantages of producer services in Beijing.Firstly,based on an integrated indicator system including one objective hierarchy,four standard hierarchies and 35 indicator hierarchies,the study applies factor analysis model and analytic hierarchy process model reformed by entropy technology to measure the comprehensive competitiveness of producer services in the above five cities.Secondly,Beijing has comparative advantages of capital resource,industrial base,scientific research resource and market scale,since it takes the first place of the five cities in the comprehensive competitiveness of producer services,the competitiveness of industrial development,business environment and living environment,only inferior to Shanghai in the competitiveness of talent capital.Thirdly,Beijing has comparative disadvantages in the level of producer services development,urban innovation capability and living environment.Finally,five proposals are put forth to enhance the competitiveness of producer services in Beijing,namely perfecting the system of laws and statutes,supporting the development of industry association,implementing scientific development planning,introducing preferential fiscal and taxation policies and strengthening human capital reserve.

Preliminary Risk Assessment Posed by Formaldehyde Residues in Clothing to Vietnamese Consumers

The assessment of potential health risks posed by formaldehyde in clothing to consumers is of increasing concern worldwide. Because of this, it is necessary to develop an exposure model that can realistically mimic clothes wearing conditions. This study aims to preliminarily develop a health risk assessment model for formaldehyde in clothing, and then to assess the potential health risk posed by formaldehyde in textiles to adults and infants in Vietnam using the model. Finally, this study aims to examine the plausibility of the adopted permissible values for formaldehyde in cloth- ing in Vietnam. In the model, two exposure factors for dermal exposure and overall exposure routes, i.e. sweat type and perspiration area, were considered. The margins of exposure (MOE) were calculated to estimate the health risks from worst case and average exposures. The assessment shows that acute exposure via inhalation can pose health risks to Vietnamese consumers in both cases. In regards to chronic exposure, dermal exposure is about four (for infants) and seven (for adults) times higher than exposure via inhalation, but no risks were found for average exposure. If a MOE of 100 is defined as ‘safe’ used, dermal and total chronic exposure to worst case cause potential risks, whereas no health risks were found for exposure to average case. With the model, the adopted Vietnamese permissible values for formaldehyde in clothing were assessed as not posing a health risk to Vietnamese consumers, hence they are accepted.

Bayesian Network Model of Product Information Diffusion and Reasoning of Influence

Information diffusion on social media has become a key strategy in people’s daily interactions. This paper studies consumers’ participation in the product information diffusion, and analyzes the complexity of information diffusion which is affected by many factors. Prior investigations of information diffusion have primarily focused on the composition of diffusion networks with independent factors and the intricacy of the process has not been completely evaluated. The majority of prior investigations have focused on strategies and the moving forces in social media processes and the determination of influential seed nodes, with few evaluations conducted about the factors affecting consumers’ choices in information diffusion. In this study, a Bayesian network model of product information diffusion was created to examine the links between factors and consumer deportment. It revealed how those factors had an impact on each other and on consumer deportment choice. The innovation of the thesis is reflected in the exploration and analysis of the specific communication path of product information diffusion, which provides a better marketing idea and practical method for the development of mobile e-commerce. The research findings can help identify the quantitative relationships between the factors affecting the process of product information diffusion and user behavior.

Experimental Investigation and Development of Artificial Neural Network Model for the Properties of Locally Produced Light Weight Aggregate Concrete

The developments in the field of construction raise the need for concrete with less weight. This is beneficial for different applications starting from the less load applied to foundations and soil till the reduction of carnage capacity required for lifting precast units. In this paper, the production of light weight concrete from light local weight aggregate is investigated. Three candidate materials are used: crushed fired brick, vermiculite and light exfoliated clay aggregate (LECA). The first is available as the by-product of brick industry and the later two types are produced locally for different applications. Nine concrete mixes were made with same proportions and different aggregate materials. Physical and mechanical properties were measured for concrete in fresh and hardened states. Among these measured ones are unit weight, slump, compressive and tensile strength, and impact resistance. Also, the performance under elevated temperature was measured. Results show that reduction of unit weight up to 45%, of traditional concrete, can be achieved with 50% reduction in compressive strength. This makes it possible to get structural light weight concrete with compressive strength of 130 kg/cm2. Light weight concrete proved also to be more impact and fire resistant. However, as expected, it needs separate calibration curves for non-destructive evaluation. Following this experimental effort, the Artificial Neural Network (ANN) technique was applied for simulating and predicting the physical and mechanical properties of light weight aggregate concrete in fresh and hardened states. The current paper introduced the (ANN) technique to investigate the effect of light local weight aggregate on the performance of the produced light weight concrete. The results of this study showed that the ANN method with less effort was very efficiently capable of simulating the effect of different aggregate materials on the performance of light weight concrete.