E-commerce Transaction Volume Research Articles

New technologies in small business models: use of electric vehicles in last-mile delivery for fast-moving consumer goods

PurposeThe share of fast-moving consumer goods (FMCG) in e-commerce has increased, particularly after COVID-19, alongside the growing volume of e-commerce transactions. The increased number of orders necessitates the optimization of delivery operations. This situation has made using different technologies in last-mile delivery processes necessary. Currently, used electric vehicles (EVs) play a significant role in integrating these technologies into delivery operations. Adapting to new technologies emerges as a critical need for small enterprises to survive in the face of advancing technologies. In this context, the main purpose of this paper is to examine and identify attitudes of small businesses toward EVs’ usage in last-mile delivery for FMCG.Design/methodology/approachThe theoretical frameworks commonly used in studies investigating new technologies, namely the theory of planned behavior (TPB) and technology acceptance model (TAM) have been employed. The analysis of the study was conducted using partial least squares-structural equation modeling (PLS-SEM) and the Smart PLS software package.FindingsWhen examining the results of the study, a significant and positive relationship was found between compatibility and enjoyment with perceived usefulness. Furthermore, a significant and positive relationship was identified between attitude toward use, perceived behavioral control and perceived usefulness. Ultimately, a strong relationship was found between intention, which is a precursor to active usage and attitude. Based on the obtained data, it can be concluded that EVs can be actively used in last-mile delivery in the future.Originality/valueIn FMCG processes in Türkiye, EVs are limitedly used in last-mile delivery operations. However, there are very few studies on the use of EVs in FMCG. Therefore, it is expected that the current research will contribute to the literature by providing information on the factors that influence the acceptance of EV usage and their implications. The TAM and TPB models were used in the current study.

ÇOKLU REGRESYON MODELİNE GÖRE E-TİCARET İŞLEM HACMİNİ ETKİLEYEN FAKTÖRLER (TÜRKİYE ÖRNEĞİ)

The widespread use of the internet in the 21st century, thanks to the developments in information technologies, has affected not only daily life but also economic activities. With the spread of the internet, business owners have turned to internet marketing system instead of traditional marketing. Additionally, purchase and sale transactions have been moved from the real world to the virtual world, and the increase in the number of users in the electronic environment has made the sales process popular for businesses and the purchasing process for consumers. This study discusses the development process of e-commerce and the factors affecting e-commerce with a time series analysis. In this context, first, the historical development of e-commerce and then the situation of e-commerce in Turkey and in the world are presented using numerical data. Lastly, the factors affecting e-commerce are discussed. The scientific dimension of the study was created by bringing together the findings obtained from domestic and foreign literature. In this study, factors such as Per Capita Gross Domestic Product (PCGDP), the number of internet users, social media prevalence, inflation, and the Covid-19 pandemic, which may affect the e-commerce transaction volume in Turkey, were put forward for the years 2010-2021. By creating a multiple linear regression model in which these factors are independent variables, the degree of effectiveness of the factors affecting the e-commerce volume has been presented and interpreted. This study aims to fill the gap in the literature and guide future research on similar issues.

Pilot Policies and Innovation Vitality: Empirical Evidence from China's National E-commerce Demonstration Cities

A national e-commerce demonstration city is a city with a relatively popular application of e-commerce and a high annual e-commerce transaction volume, with the aim of reducing energy consumption and developing a green economy. It is an attempt by China to actively explore a unique modernization path with Chinese characteristics. We believe that in the new era, the transformation of urban e-commerce can increase innovation vitality, create more opportunities for people to achieve prosperity, and become an important new practical approach to promote common prosperity. Based on the policy experiment of national e-commerce demonstration city pilot construction as the main entry point of the project, this paper explores the process and development facts of China's innovation policy pilot construction, combines theoretical and empirical analysis, and uses multidimensional data and multiple econometrics methods to analyze and evaluate the innovation vitality of urban e-commerce transformation region influenced by mechanism and policy. Our research finds that the transformation of urban e-commerce plays a crucial role in activating urban innovation vitality and enhancing the market drivers of innovation vitality. We must unwaveringly consolidate and develop the public sector of the economy and expand financing and market access mechanisms, which will help to enhance innovation vitality and gradually improve the ability of market participants to achieve prosperity, thus facilitating the exploration and realization of the road to common prosperity.

Comprehensive Evaluation and Promotion Strategy of Agricultural Digitalization Level

The development of digitalization is a crucial aspect of agricultural progress, and expediting the establishment of digital systems is a significant driving force behind high-quality agricultural advancements in the current era. Utilizing data from 16 cities within Shandong Province in China between 2014 and 2020, we created an assessment system to measure the degree of agricultural digitalization, utilized the entropy technique to assess the level of digitalization, scrutinized the general trends and time-dependent features of each city, and then utilized the obstacle degree model to pinpoint the primary hindrances to digitalization in agriculture. Lastly, the ESDA method was utilized to examine the differences in spatial distribution among regions and the spatial characteristics of agricultural digitalization at different stages and levels. Overall, the degree of agricultural digitalization can be categorized into three stages: deceleration and upswing (2014–2015), steady fluctuation (2016–2017), and high-level upswing (2018–2020). From the perspective of obstacles, the main hurdles to agricultural digitalization are e-commerce transaction volume and the total amount of telecommunication business. To accelerate the development of the entire agricultural industry chain, it is required to leverage the strengths of high-value areas and reinforce the coordination mechanism among various departments while hastening the construction of rural infrastructure in low-value areas. Additionally, it is necessary to improve inter-regional communication and cooperation to nurture different regional development models in line with local conditions.

Effect of Research and Development (R&D) Investment, E-Commerce Company Employee, and E-Commerce Transaction Volume on Economic Growth in Indonesia 2010Q1 – 2020Q4

This study aims to analyze the effect of R&D investment, the volume of e-commerce transactions, and e-commerce companies employee on economic growth in Indonesia for the period 2010Q1 – 2020 Q4. The analytical method used in this study is OLS (Ordinary Least Square) anda method using time series data in the form of quarterly from 2010 to 2020. In conducting this research the author uses the help of the E-views 9 analysis tool. The results of this study are that the variables of R&D investment, e-commerce companies employee, and the volume of e-commerce transactions have a partial or joint effect on economic growth in Indonesia in 2010 Q1 to 2020 Q4.

Pengaruh Investasi Research And Development (R&D), Karyawan Perusahaan E-Commerce, dan Volume Transaksi Terhadap Pertumbuhan Ekonomi Di Indonesia 2010q1 – 2020q4

This study aims to analyze the effect of R&D investment, the volume of e-commerce transactions, and e-commerce company employee on economic growth in Indonesia for the period 2010Q1 – 2020 Q4. The analytical method used in this study is OLS (Ordinary Least Square) method using time series data in the form of quarterly from 2010 to 2020. In conducting this research, the author uses the help of the E-views 9 analysis tool. The results of this study are that the variables of R&D investment, e-commerce company employee, and the volume of e-commerce transactions have a partial or joint effect on economic growth in Indonesia in 2010 Q1 to 2020 Q4. This research is limited by several factors, among others; R&D investment, e-commerce company employee, and volume of e-commerce transactions. The results obtained from this research are expected to be one of the references in making policy directions based on the data presented to adjust the right policies, especially to achieve economic digitization in Indonesia.

Episode of Dual Neural Genetic Firefly (DNGF) Transmission Key Generation in New Normal Mode of COVID-19 Second Wave Telepsychiatry

The volume of E-commerce transactions had accelerated on huge scale due to COVID-19. Telemedicine comes under the segment of E-commerce, where the patients can get their treatments from isolates. Patients’ information security is a basic challenge in this COVID-19 telemedicine segment. The majority of the non-obtrusive and non-emergency patients are encouraged and treated distantly from their secludes without the inclusion of COVID-19 transmission. Anxiety, depressive disorders, stress, dementia, mood disorder, OCD, aggression, etc. are the critical mental challenges that have abruptly occurred during this COVID period. The present work focused on “New Normal Mode” of COVID-19 telepsychiatry so that the patients’ mental illness can be treated remotely in a secure way. An episode of dual neural-genetic firefly (DNGF) has been proposed on COVID-19 "New Normal Mode" 2nd wave telepsychiatry. The pool of transmission keys was generated with the help of firefly algorithm, neural perceptron, and genetic operations. Besides these, the proposed DNGF keys are effective to be used for different online psychiatric transactions. The objectivity of this paper is to generate a robust pool of transmission keys in order to nullify different types of intruding. It has effectively cleared Avalanche test and Strict Avalanche test. The outcome of parameterized functional security test has been recorded with adequacy. These were: 0.327933, 0.350467, 0.332533, 0.317867, and 0.350267 on the generated pool of DNGF. The correlation coefficient between the key generation time and parameterized functional security has been found to be r_{GT,FS} = - 0.53404. Distinctive mathematical arranged examinations were directed on the proposed key pool. It has shown better reasonability on the part of the COVID-19 2nd wave telepsychiatry, which is a component of E-commerce.

Impact of Covid-19 Pandemic on Financial Inclusion and Digital Adoption

Digitalization is an inevitable fact due to increasing technology and the environment that challenges the status-quo of the traditional transactional systems. Especially during the Covid-19 pandemic, the adoption rate of eCommerce and digital transactions has increased significantly. In this research paper, we used eCommerce data of Hungary, Austria, Greece, and Sweden and their DESI index for 2017 to 2020 in order to understand the background of events which shows that the covid-19 pandemic had a significant impact on people’s perception of the day-by-day transactions and that the economic development of a country has a profound impact on the financial inclusion metrics and digitalization appetite of their citizens. Our main findings show that curfews during the pandemic significantly influence the volume of eCommerce transactions and DESI Index rankings are substantially linked with real-life matters.

An Empirical Study on the Prediction of E-Commerce Sales by Optimizing Grey Neural Network Model

E-commerce is the main component of the new economy. In recent years, with the rapid development of the Internet, e-commerce shows great vitality. According to the requirements of the 13th five year plan, China’s e-commerce needs to be fully integrated into all areas of the national economy, and the e-commerce transaction volume is planned to reach 40 trillion yuan by 2020. However, the transaction volume of e-commerce is an important embodiment of the development level of e-commerce. Therefore, through scientific and reasonable algorithm, we can predict the transaction volume of e-commerce, which will reveal the depth of e-commerce development. Through the prediction of e-commerce transaction volume, enterprises and governments will conduct quantitative supervision on market development, which has become an inevitable requirement of e-commerce development. This paper first analyzes the basic theory of grey neural network. Then, the neural network prediction model is optimized.

The era of digital transformation: Visualizing the geography of e-commerce usage in Turkey

It is noteworthy that volumes of e-commerce usage are spread over the population of the world, and the amount of transactions is quite high. In this sense, Turkey's situation is different from other countries. Although the volume of internet usage is similar to that of the world, the volume of e-commerce transactions is quite low. However, there is a stable increase in the e-commerce usage in Turkey. Between 2016 and 2020, the average annual growth rate of e-commerce usage has grown by 31% across the country. Considering the great increase in the e-commerce usage in Turkey, this study aims to visualize spatial distribution of the share of e-commerce usage over the provinces of Turkey. Findings of the research point out that the e-commerce usage shows a heterogeneous spatial distribution across Turkey. Due to the low population, in particular provinces (such as Kayseri and Karabük in Central Anatolia, Aydın in Aegean Region, and Van in East Anatolia), there is an expanding distortion around these cities regarding the ratio of e-commerce usage.

Intelligent evaluation model of e-commerce transaction volume based on the combination of k-means and SOM algorithms

Intelligent evaluation model of e-commerce transaction volume based on the combination of k-means and SOM algorithms

A CONCEPTUAL STUDY ON CAR-SHARING SERVICES BASED ON SHARING ECONOMY

Sharing is indicated as an alternative form of distribution to the exchange of goods and gift-giving. It encourages a sense of community, saves resources and creates specific synergies. Many factors such as the increase in the use of internet services and smartphones, globalization and urbanization, increasing e-commerce transaction volume, the reliance on online payments, the global economic recession, changes in general attitudes and more attention to sustainability in consumption have led to the development of the sharing economy in recent years. The sharing economy has given the possibility to the people to use the resources efficiently and to distribute them to where it is much needed when they are sitting idle. The shared mobility, which is one of the central areas in sharing economy, is having a growth in the last decade, due to the increased urbanization, high cost of ownership and changes in consumption habits. Even though there are different modes of shared mobility services, the most common one in Turkey is car-sharing. In this conceptual study on car-sharing services based on the sharing economy, a comprehensive literature review is conducted. In these regards, firstly the concept and importance of sharing economy is emphasized and then shared mobility services, and types are discussed individually. Lastly, car-sharing services and their types are examined. With this study, it is aimed to make a total contribution to the sharing economy literature on car-sharing services.

Intelligent evaluation model of e-commerce transaction volume based on the combination of k-means and SOM algorithms

Due to the lack of steps to process sensitive data in the traditional intelligent evaluation model of e-commerce transaction volume, which leads to poor evaluation effect, an intelligent evaluation model of e-commerce transaction volume based on the combination of k-mean and SOM algorithm is proposed. Taking system intelligent clustering as the core, the transaction volume data in the web log is collected through the collection system. The desensitisation rule is used to establish the data transmission model of trading volume. The detection of sensitive data adopts signal detection technology and analytical processing. Based on k-means algorithm, data desensitisation is accomplished to achieve data denoising and a clustering evaluation model is established to complete data mining and analysis. The experimental results show that the model has a good denoising effect, and the ROC curve is closer to the upper left corner with an AUC value of 0.9712, which verifies the effectiveness and superiority of the model.

Forecasting of e-commerce transaction volume using a hybrid of extreme learning machine and improved moth-flame optimization algorithm

The rapid development of e-commerce has resulted in optimization of the industrial structure of Chinese enterprises and has improved the Chinese economy. E-commerce transaction volume is an evaluation index used to determine the development level of e-commerce. This study proposed a model for forecasting e-commerce transaction volume. First, a hybrid moth–flame optimization algorithm (HMFO) was proposed. The convergence ability of the HMFO algorithm was analyzed on the basis of test functions. Second, using data provided by the China Internet Network Information Center, factors influencing e-commerce transaction volume were analyzed. The input variables of the e-commerce transaction volume prediction model were selected by analyzing correlation coefficients. Finally, a hybrid extreme learning machine and hybrid-strategy-based HMFO (ELM-HMFO) method was proposed to predict the volume of e-commerce transactions. The prediction results revealed that the root mean square error of the proposed ELM-HMFO model was smaller than 0.5, and the determination coefficient was 0.99, which indicated that the forecast e-commerce transaction volume was satisfactory. The proposed ELM-HMFO model can promote the industrial upgrading and development of e-commerce in China.

The Study of Influencing Factors of Mobile E-commerce Software Use Intention-based on TAM and TRA

With the wide popularity of mobile devices, e-commerce software in the mobile client forms a larger consumer market, which makes the volume of e-commerce transactions having a wide range of growth. As the consumers have a frequent contact with mobile devices, which makes consumers pay more attention to security and entertainment of the e-commerce software. Past mobile e-business research typically focus on the related factors about transaction process, like interface design, services and user experience, but seldom study the factors about consumers. On the basis of the TAM, this paper not only added perceived security and perceived entertainment, but also the consumers’ personality factors like subjective norm in TRA, into the model. The study shows that PU, PEU, PS and PE all will have direct or indirect effects on use attitude and use intention, and subjective norms and use attitude will directly affect the consumers' use intention. Through the empirical analysis we found that e-commerce operators not only make the consumers experience more of usefulness and ease of use, security, and entertainment in the technology and services, but also improve the popularity with the aid of the mainstream media propaganda and star power to enhance the public's normative beliefs, which will ultimately affect the user behavior of the consumers.

Research on Economic Growth and Information Exchange Based on B2B E-Commerce

This paper studies the relationship between B2B e-commerce transaction volume and GDP by using co- integration relation test and Engel-Granger test methods. The result shows that long-term stable co-integration relationship does not exist: B2B causes the growth of GDP, but GDP is not reason for the increase of B2B transactions. Meanwhile, this article also aims to study the influence on B2B e-commerce information retrieval and communication, and then extract different B2B e-commerce mode of information retrieval and communication mode so as to improve the efficiency of information retrieval and communication, making the business flow, logistics, cash flow more smooth .

跨境电商小额贸易在国际贸易实务传统教学中的融合

跨境电子商务已成为中国电子商务市场交易的新增长点，2013年和2014年，跨境电商交易额增速远高于外贸增速，2014年交易额突破4万亿大关。跨境电子商务市场在快速增长的同时对物流、支付、结算等环节提出更高的要求。本文探讨了在跨境电商与传统国际贸易实务当中的联系与区别，在教学中将其融合进去，与时俱进。 Cross-border electric commerce has become a new growth point of Chinese e-commerce market. In 2013 and 2014, the growth of cross-border e-commerce transaction volume was much higher than that of foreign trade and transaction, and in 2014 it exceeded four trillions. The rapid growth of cross-border e-commerce market at the same time put forward higher requirements on the logistics, payment, settlement and other aspects. This paper explores the links and differences between cross-border e-commerce and traditional International trade practice, and cross-border electric commerce should be integrated into traditional International trade practice teaching and advance with the times.

Analysis of Security Issue in C2C E-Commerce Based on Game Theory

With the increasing volume of E-commerce transactions in China, trust issue in E-commerce is increasingly prominent, which has been one major bottleneck of the sound development of E-commerce in China. This thesis aims to analyze the reasons for the lack of trust in E-commerce by starting with C2C E-commerce platform, and to analyze the main factors influencing the trust conduct of transaction bodies and put forward suggestions for improving credit system through the use of the static game theory.

The Improvement of a Prediction Study of Transactions Based on E-Commerce Site Search Data

The search behavior of E-commerce consumers is conscious. And their shopping is another kind of consciousness behavior. In the shopping process of e-commerce website, these two consciousness behavior were joined together. So, the phenomenon reflects some trends and patterns, reflect the relationship between e-commerce site search volume and trading volume. This paper will attempt to establish the model of a theoretical framework, which explored the first - lag relationship between the amount of e-commerce site search and e-commerce transaction volume, by stepwise method which obtain comprehensive search index, and then which complete the empirical analysis, obtain the prediction result. The results showed that: there are a higher correlation between the search data and trading volume of e-commerce site; after adding a synthesis of the search index, the model fit increased to 0.901, which significantly improve the prediction result of the model. At the same time, the model has a stronger timeliness, which can more timely predict e-commerce transactions.

The Forecast Model of China’s B2B E-Commerce Transactions

Since the Internet users in China increased gradually, we use the Bass model to forecast the number of the Internet users in china in the following years, and establish the model to forecast the B2B e-commerce transaction volume of China. With the estimation of model parameters, we analysis the reasons of the E-commerce development in china, and give some policies or proposals which might be help for the high-speed development of the E-commence in China.