Previous Issue
Volume 17, September
 
 

J. Theor. Appl. Electron. Commer. Res., Volume 17, Issue 4 (December 2022) – 29 articles

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
Review
Order-Picking Efficiency in E-Commerce Warehouses: A Literature Review
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1812-1830; https://doi.org/10.3390/jtaer17040091 - 07 Dec 2022
Viewed by 168
Abstract
With the vigorous development of e-commerce, efficient order picking in e-commerce warehouses has attracted the attention of many scholars. To analyze the issues about order-picking efficiency currently being studied by relevant scholars in e-commerce warehouses, this paper reviews the literature on the application [...] Read more.
With the vigorous development of e-commerce, efficient order picking in e-commerce warehouses has attracted the attention of many scholars. To analyze the issues about order-picking efficiency currently being studied by relevant scholars in e-commerce warehouses, this paper reviews the literature on the application of order-picking strategy and efficiency optimization direction from 2020 to 2022. That mainly falls into two categories of picking systems: “picker-to-parts” and “parts-to-picker”. In the “picker-to-parts” picking system, more attention is paid to the picking strategies of storage assignment and order batching and the integration of multiple picking strategies. In contrast, in the “parts-to-picker” picking system, the main attention is on the man-machine cooperation in the Mobile Robot Fulfillment System (RMFS) and the Automated Storage and Retrieval System (AS/RS), as well as the coordination of the picking station. Further, this paper proposes future research directions for two categories of picking systems: further studying the order splitting strategy and order delivery issues; considering the dynamic uncertainties; combining the automated picking system with different picking strategies, and so on. Full article
(This article belongs to the Special Issue Supply Chain Digitalization)
Show Figures

Figure 1

Article
Human Services or Non-Human Services? How Online Retailers Make Service Decisions
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1791-1811; https://doi.org/10.3390/jtaer17040090 - 07 Dec 2022
Viewed by 186
Abstract
With the development of Internet technology, online shopping has become increasingly popular. Owing to the improvement of living standards, the quality of e-service has become one of the important criteria for online shopping, with online shopping consultation being one of the key services. [...] Read more.
With the development of Internet technology, online shopping has become increasingly popular. Owing to the improvement of living standards, the quality of e-service has become one of the important criteria for online shopping, with online shopping consultation being one of the key services. At the same time, the emergence of new technologies such as Artificial Intelligent (AI) has allowed online retailers to increase the availability of non-human online shopping consultation services. Therefore, this paper investigates the service decision problem between human and non-human online shopping consultation services for online retailers in the online duopoly market. By constructing a Hotelling improvement model and applying it in a new way, considering consumer preferences for human services, this paper explores the impact of the optimal service level of human online shopping consultation services and consumers’ sensitivity to the service level of human services on online retailers’ pricing, service decisions, etc. Our research results show that consumers’ sensitivity to the service level of human online shopping consultation services has an impact on the demand and profit of online retailers. In addition, human online shopping consultation services are not always beneficial to the profitability. Furthermore, when two online retailers compete, the utility of the non-human online retailer’s service to consumers can influence the service decisions of the other online retailer. Full article
(This article belongs to the Section e-Commerce Analytics)
Show Figures

Figure 1

Article
Strategic Business Mode Choices for E-Commerce Platforms under Brand Competition
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1769-1790; https://doi.org/10.3390/jtaer17040089 - 06 Dec 2022
Viewed by 219
Abstract
Relying on the rapid development of information and internet technologies, e-commerce has boomed over the past decade. As a link between manufacturers and consumers, the e-commerce platform has a crucial position in the online retailing market. The e-commerce platform not only provides an [...] Read more.
Relying on the rapid development of information and internet technologies, e-commerce has boomed over the past decade. As a link between manufacturers and consumers, the e-commerce platform has a crucial position in the online retailing market. The e-commerce platform not only provides an online marketplace through which the manufacturers directly sell products to consumers but also purchases and resells manufacturers’ products to consumers. Therefore, when the e-commerce platform provides services to manufacturers, it is faced with the selection of two sales methods: reselling or marketplace. Using a game theoretic model, we focus on the strategic interactions between an e-commerce platform and two brand manufacturers in four different business modes. The results show that the e-commerce platform profits more when both brand manufacturers directly sell products through the online marketplace. From the two brand manufacturers’ points of view, using the e-commerce platform as a reseller is always more profitable than directly selling, no matter which business mode they are in. The above findings have important implications for the selling decisions of the e-commerce platform and brand manufacturers. Furthermore, an interesting and counterintuitive result is that the new brand manufacturer benefits more than the existing brand manufacturer when consumers’ acceptance of the new brand products is becoming lower. When production costs are low, only the two brand manufacturers can achieve a mutually beneficial situation by selling products to the e-commerce platform. Moreover, the competition among brand manufacturers is beneficial to the e-commerce platform. Our research provides a theoretical basis for brand manufacturers and the e-commerce platform to make more rational decisions, and it updates the existing knowledge about brand competition and e-commerce platform’s business mode choices. Full article
Show Figures

Figure 1

Article
The Impact of Government Behavior on the Development of Cross-Border E-Commerce B2B Export Trading Enterprises Based on Evolutionary Game in the Context of “Dual-Cycle” Policy
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1741-1768; https://doi.org/10.3390/jtaer17040088 - 05 Dec 2022
Viewed by 366
Abstract
In 2020, the COVID-19 pandemic had a major impact on China’s foreign trade. Therefore, the Chinese government has proposed a “dual cycle” policy to promote economic development. In 2021, China’s cross-border e-commerce B2B exports accounted for 60 percent. Therefore, this paper studies the [...] Read more.
In 2020, the COVID-19 pandemic had a major impact on China’s foreign trade. Therefore, the Chinese government has proposed a “dual cycle” policy to promote economic development. In 2021, China’s cross-border e-commerce B2B exports accounted for 60 percent. Therefore, this paper studies the impact of government actions on the development of cross-border e-commerce B2B export enterprises under the background of “dual cycle” policy. First, the policies related to the cross-border e-commerce industry in the “dual circulation” policy are screened, and the LDA topic model is used to classify them, i.e., sorting by topic intensity as “fiscal policy”, “tax policy”, “customs clearance policy”, “payment policy” and “talent policy”. After that, based on the analysis results of the LDA topic model, a theoretical basis for the impact of different policies on cross-border e-commerce B2B export companies is established; then an evolutionary game model between the government and cross-border e-commerce B2B export enterprises is constructed. This article also carried out experiments to verify our analysis. The simulation results show that: (1) The government’s appropriate increase in subsidies, tax incentives, infrastructure investment, talent introduction and cultivation, optimized payment system, and supervision can promote enterprises to participate in cross-border e-commerce B2B export trading; (2) excessive government supervision reduces enterprises’ enthusiasm to participate in cross-border e-commerce B2B export trading; (3) the government’s subsidies, tax incentives, and supervision strength have the greatest impact on whether enterprises participate in cross-border e-commerce B2B export trading, followed by the government’s investment in cross-border e-commerce infrastructure, the introduction and cultivation of cross-border e-commerce talents, and the improvement of the payment system. Finally, this paper puts forward relevant policy recommendations to promote the development of cross-border e-commerce B2B export enterprises. Full article
(This article belongs to the Section e-Commerce Analytics)
Show Figures

Figure 1

Article
TipScreener: A Framework for Mining Tips for Online Review Readers
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1716-1740; https://doi.org/10.3390/jtaer17040087 - 05 Dec 2022
Viewed by 329
Abstract
User-generated content explodes in popularity daily on e-commerce platforms. It is crucial for platform manipulators to sort out online reviews with repeatedly expressed opinions and a large number of irrelevant topics in order to reduce the information processing burden on review readers. This [...] Read more.
User-generated content explodes in popularity daily on e-commerce platforms. It is crucial for platform manipulators to sort out online reviews with repeatedly expressed opinions and a large number of irrelevant topics in order to reduce the information processing burden on review readers. This study proposes a framework named TipScreener that generates a set of useful sentences that cover all of the information of features of a business. Called tips in this work, the sentences are selected from the reviews in their original, unaltered form. Firstly, we identify information tokens of the business. Second, we filter review sentences that contain no tokens and remove duplicates. We then use a convolutional neural network to filter uninformative sentences. Next, we find the tip set with the smallest cardinality that contains all off the tokens, taking opinion words into account. The sentences of the tip set contain a full range of information and have a very low repetition rate. Our work contributes to the work of online review organizing. Review operators of e-commerce platforms can adopt tips generated by TipScreener to facilitate decision makings of review readers. The convolutional neural network that classifies sentences into two classes also enriches deep learning studies on text classification. Full article
(This article belongs to the Section Digital Marketing and the Connected Consumer)
Show Figures

Figure 1

Article
Can I Trust My Phone to Replace My Wallet? The Determinants of E-Wallet Adoption in North Cyprus
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1696-1715; https://doi.org/10.3390/jtaer17040086 - 02 Dec 2022
Viewed by 254
Abstract
E-wallets and mobile payment systems provide fast, secure, and convenient payment in transactions services while minimizing the need for human interaction. However, the adoption of the technology has had varying levels of success. Using a sample of 300 respondents, the study randomly assigned [...] Read more.
E-wallets and mobile payment systems provide fast, secure, and convenient payment in transactions services while minimizing the need for human interaction. However, the adoption of the technology has had varying levels of success. Using a sample of 300 respondents, the study randomly assigned participants into three conditions and provided different information on how they would be reimbursed by their bank in case of fraud. In the three conditions, this study analyzed how prior consumer knowledge about e-wallet technology along with perceived usefulness, perceived ease of use, and trust may be related to the attitudes on the use of e-wallets, which subsequently relates to the intentions to use this technology. The findings suggest that consumer knowledge about e-wallet technology relates to perceived usefulness, perceived ease of use, and trust, which are known to influence attitude and behavioral intention to adopt and use new technologies such as the e-wallet. In addition, the results displayed that those respondents who were assured of immediate reimbursement in case of fraud may have higher intention to adopt e-wallets when compared to those who were informed of delayed reimbursement or those given no information. While the ANOVA results provided tentative support for the hypothesis that assurance of reimbursement will improve the intention to use e-wallet, the subsequent ANCOVA findings demonstrate that when prior consumer knowledge is taken into consideration and groups are compared with this factor in the equation, the group differences disappear. Full article
Show Figures

Figure 1

Article
The Whole Is More than Its Parts: A Multidimensional Construct of Values in Consumer Information Search Behavior on SNS
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1685-1695; https://doi.org/10.3390/jtaer17040085 - 02 Dec 2022
Viewed by 218
Abstract
The notion of consumer values has been a key factor in understanding consumer behavior and has attracted the attention of various scholars in e-commerce. The aims of this study are to conceptualize a multidimensional construct of consumer information value (CIV) on social network [...] Read more.
The notion of consumer values has been a key factor in understanding consumer behavior and has attracted the attention of various scholars in e-commerce. The aims of this study are to conceptualize a multidimensional construct of consumer information value (CIV) on social network sites (SNS), to examine the construct empirically, and to investigate the nature of its relationships with consumer information search behavior, i.e., the use of information channels on SNS. Quantitative research was conducted using a representative sample of 612 Facebook users. The use of a higher-order construct and structural equation modeling procedures reveals that the following five value constructs—Economic, Psychological, Social, Functional and Hedonic values—are significant facets of the CIV. It suggests that the CIV model is a powerful tool that directly explains consumer information search behavior and has better explanatory power than the sum of its parts. Full article
Show Figures

Figure 1

Article
The Long-Term Risk Familiarity Effect on Courier Services’ Digital Branding during the COVID-19 Crisis
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1655-1684; https://doi.org/10.3390/jtaer17040084 - 01 Dec 2022
Viewed by 270
Abstract
The explosion of e-commerce creates new opportunities for courier companies to thrive, making the industry one of the success stories, due to its sustainability and resilience during the pandemic. As customers become more familiar with COVID-19, they adopt new online purchasing behaviors toward [...] Read more.
The explosion of e-commerce creates new opportunities for courier companies to thrive, making the industry one of the success stories, due to its sustainability and resilience during the pandemic. As customers become more familiar with COVID-19, they adopt new online purchasing behaviors toward branding preferences. The purpose of this paper is to analyze the impact of risk familiarization on courier companies’ digital branding. This paper investigates the application of the psychometric paradigm by Fischhoff ho suggested risk novelty as a key factor for the level of risk perception. Five big companies with global trading activities were selected and analyzed on a three-period time: the year before, the first year, and the second year of the COVID-19 pandemic, by using passive crowdsourcing data. The results indicate that after the first year of the pandemic, online customers’ risk perception of COVID-19 hazards decreased, and consumers returned to their pre-COVID-19 behavior regarding brand preference. However, the dramatic escalation of new infections caused by new COVID-19 mutations reversed their online purchasing attitude from non-branded to branded preferences. The outcomes of the research can be used by scientists and supply chain risk managers to redefine risk mitigation strategies, COVID-related information marketing strategies and innovation investments within the industry. The research further introduces dynamic simulation modeling to be used as a risk management tool in favor of courier companies’ proper resource allocation and digital optimization. Full article
(This article belongs to the Special Issue Supply Chain Digitalization)
Show Figures

Figure 1

Article
Location Optimization of Offline Physical Stores Based on MNL Model under BOPS Omnichannel
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1633-1654; https://doi.org/10.3390/jtaer17040083 - 01 Dec 2022
Viewed by 240
Abstract
With the continuous upgrading of consumer demand and retail modes, more and more retailers are switching to an omnichannel retail mode. In order to study the location problem of offline physical stores of online retail enterprises that plan to implement the BOPS (Buy [...] Read more.
With the continuous upgrading of consumer demand and retail modes, more and more retailers are switching to an omnichannel retail mode. In order to study the location problem of offline physical stores of online retail enterprises that plan to implement the BOPS (Buy Online and Pickup in Store) omnichannel retail model, this paper considers consumers’ choice behavior under the omnichannel retail model; uses the MNL (Multinomial Logit) model to depict customers’ choice behavior between the online channel, BOPS channel, and offline physical channel; and constructs a location optimization model of offline physical stores with the goal of minimizing the enterprise’s cost. According to the characteristics of the model, an improved genetic algorithm was designed; the algorithm was improved on chromosome selection mode, crossover, and mutation rules. Finally, an example is calculated, and the physical store location scheme of a retail enterprise and the vehicle routing optimization scheme under the two-level distribution network are obtained, which verifies the effectiveness of the model and algorithm and provides a scientific reference for the physical store location decision of online retail enterprises planning to implement the BOPS omnichannel retail model. The impact of freight, return rate, and service level of physical stores on the location of offline physical stores is analyzed. The results show that in the process of expanding offline physical stores to implement the BOPS omnichannel retail model, online retail enterprises can reduce enterprise costs by improving the freight level and service level of the physical store. The higher the return rate of the online channel, the more necessary it is to expand offline physical stores, and the lower the enterprise cost. At the same time, management suggestions are put forward for the enterprise operation under the BOPS omnichannel retail mode. Full article
(This article belongs to the Special Issue Multi-Channel Retail and Its Applications in the Future of E-Commerce)
Show Figures

Figure 1

Article
Use of Blockchain Technology to Manage the Supply Chains: Comparison of Perspectives between Technology Providers and Early Industry Adopters
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1616-1632; https://doi.org/10.3390/jtaer17040082 - 01 Dec 2022
Viewed by 277
Abstract
Following the interest in blockchain technology (BCT) business solutions and the nascent stage of technology in supply chain (SC) practices, this research compares views from business practitioners who are experienced in real cases of BCT adoption with the views of technology consultants proficient [...] Read more.
Following the interest in blockchain technology (BCT) business solutions and the nascent stage of technology in supply chain (SC) practices, this research compares views from business practitioners who are experienced in real cases of BCT adoption with the views of technology consultants proficient in the complexities of BCT to analyze the benefits and challenges BCT holds for SCs. Based on the comparison of the two sides, the joint views that both adopters and technology consultants share is the ability that BCT holds to speed up processes across SCs through decentralized data access, thus decreasing human errors and reducing paperwork. However, technology consultants perceive the need to increase BCT awareness levels of businesses, to prevent BCT implementation just for reasons such as ‘recordkeeping’ and to reduce misconceptions in areas such as cryptocurrency applications. The findings also revealed that technology consultants insist on the careful evaluation and definition of records to be kept on BCT platforms prior to the adoption process, in order to avoid unnecessary data input. Currently, according to early industry adopters’ cases, most business attempts of BCT adoption use private networks, so technology consultants promote business entities on developing plans towards open-access public networks. Full article
(This article belongs to the Section Digital Business Organization)
Show Figures

Figure 1

Article
Integrating Blockchain for Health Insurance in Indonesia with Hash Authentication
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1602-1615; https://doi.org/10.3390/jtaer17040081 - 29 Nov 2022
Viewed by 423
Abstract
The use of blockchain has received great attention in its adoption as a financial instrument in cryptocurrencies. This phenomenon needs to be considered in the sense not only as a form of financial transactions but also in other fields such as health, which [...] Read more.
The use of blockchain has received great attention in its adoption as a financial instrument in cryptocurrencies. This phenomenon needs to be considered in the sense not only as a form of financial transactions but also in other fields such as health, which is also a challenge for modern society. In addition, several government policies have also supported the provision of health services as a form of improving people’s living standards in the form of insurance. In this study, we try to design the system by using UML diagram and simulate the use of DApps offered by the Vexanium Ecosystem. For example, three basic activities between patients, doctors, and insurance will be simulated in the form of the transaction ledger. This method allows us to speed up the authentication process that previously needed to be performed for a long time with bureaucracy becoming the rule in smart contracts in a matter of minutes. The evaluation of this method will then be compared with eight existing blockchain projects. The result in healthcare processes is cost savings through increased automation, speed, standardization, and efficiency. All of this can be a preliminary analysis of its application in Indonesia, particularly related to the authentication and recording of medical records. Full article
Show Figures

Figure 1

Article
The Legitimacy of a Sharing Economy-Enabled Digital Platform for Socioeconomic Development
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1581-1601; https://doi.org/10.3390/jtaer17040080 - 27 Nov 2022
Viewed by 337
Abstract
A sharing economy based on improved ICT is an emerging economic−technological concept. Sharing economy-enabled digital platforms in China have changed patterns of consumption, exploited under-utilized resources, and increased employment. Previous studies on sharing economy-enabled digital platforms mainly focused on the positive and negative [...] Read more.
A sharing economy based on improved ICT is an emerging economic−technological concept. Sharing economy-enabled digital platforms in China have changed patterns of consumption, exploited under-utilized resources, and increased employment. Previous studies on sharing economy-enabled digital platforms mainly focused on the positive and negative effects, users’ perception and behavioral intention, and the business model, but few studies have addressed these platforms for socioeconomic development from the perspective of legitimacy. This study applied legitimacy to analyze a typical sharing economy-enabled digital platform in China for socioeconomic development via a longitudinal interpretive case study. A process model of variation and evolution of an online car-hailing platform for socioeconomic development was inductively derived, allowing elucidation of the complexities and interplay of regulative challenges, normative challenges, and cognitive challenges in each developmental phase, resulting in improving and enriching the way people go out, optimizing resource allocation, increasing employment, and undertaking social responsibility. The findings of this case study provide a comprehensive and supported framework and demonstrate a successful model for managers and other peer organizations for future business efforts in the sharing economy. Full article
(This article belongs to the Section Digital Business Organization)
Show Figures

Figure 1

Article
Analysis of OTT Users’ Watching Behavior for Identifying a Profitable Niche: Latent Class Regression Approach
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1564-1580; https://doi.org/10.3390/jtaer17040079 - 23 Nov 2022
Viewed by 281
Abstract
Over-the-top (OTT) firms must overcome the hurdle of the competitive Korean media market to achieve sustainable growth. To do so, understating how users enjoy OTT and analyzing usage patterns is essential. This research aims to empirically identify a profitable niche in the Korean [...] Read more.
Over-the-top (OTT) firms must overcome the hurdle of the competitive Korean media market to achieve sustainable growth. To do so, understating how users enjoy OTT and analyzing usage patterns is essential. This research aims to empirically identify a profitable niche in the Korean OTT market by applying market segmentation theory. In addition, it investigates an effective content strategy to convert free users into paying customers belonging to profitable niche segments. The latent class regression model was applied to Korean Media Panel Survey data to divide Korean OTT customers into submarkets. According to an empirical analysis, Korean OTT users can be divided into three submarkets based on their OTT usage patterns, with the third segment serving as a profitable niche market. An additional analysis of the profitable niche market revealed that bundling content, such as foreign content, original content, and movies, is a crucial content strategy for increasing paying subscribers in a profitable niche segment. Full article
Show Figures

Figure 1

Article
Return Policy Selection Analysis for Brands Considering MCN Click Farming and Customer Disappointment Aversion
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1543-1563; https://doi.org/10.3390/jtaer17040078 - 18 Nov 2022
Viewed by 395
Abstract
In order to solve the problem of separation between consumer purchase and product experience in online sales, live streaming e-commerce came into being. However, the interaction of streamers is easy to cause consumers’ impulse consumption, which leads to the soaring return rate. In [...] Read more.
In order to solve the problem of separation between consumer purchase and product experience in online sales, live streaming e-commerce came into being. However, the interaction of streamers is easy to cause consumers’ impulse consumption, which leads to the soaring return rate. In this context, how to make reasonable return policies to avoid the loss is an important issue for brands. This paper studies return policy selection for brands. We mainly focus on MCN (multi-channel network) click farming and customer disappointment aversion in the situations that the return-freight insurances are paid by brands or consumers or brands and MCN jointly. Three leader-follower models with brands as leaders and platforms and MCN as followers are established. To solve the above bilevel models, we discuss the conditions under which the upper and lower models are both convex and, based on these theoretical results, we give the optimal strategies for all members. Then, through numerical experiments, we analyze the impacts of customer disappointment aversion level, MCN’s ability, commission rate, brand’s return-freight insurance purchasing ratio, and other factors on each member’s optimal decision. The results show that the return policy in the situation of return-freight insurance paid by brand is suitable for a market with the high level of customer disappointment aversion; the return policy in the situation of return-freight insurance paid by consumers is applicable to the case of low customer disappointment aversion and high commission rate; the return policy in the situation of return-freight insurance paid by brand and MCN jointly is suitable for the case of low MCN capability and can effectively restrain the click farming from MCN. Full article
Show Figures

Figure 1

Article
Machine Learning to Develop Credit Card Customer Churn Prediction
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1529-1542; https://doi.org/10.3390/jtaer17040077 - 16 Nov 2022
Viewed by 372
Abstract
The credit card customer churn rate is the percentage of a bank’s customers that stop using that bank’s services. Hence, developing a prediction model to predict the expected status for the customers will generate an early alert for banks to change the service [...] Read more.
The credit card customer churn rate is the percentage of a bank’s customers that stop using that bank’s services. Hence, developing a prediction model to predict the expected status for the customers will generate an early alert for banks to change the service for that customer or to offer them new services. This paper aims to develop credit card customer churn prediction by using a feature-selection method and five machine learning models. To select the independent variables, three models were used, including selection of all independent variables, two-step clustering and k-nearest neighbor, and feature selection. In addition, five machine learning prediction models were selected, including the Bayesian network, the C5 tree, the chi-square automatic interaction detection (CHAID) tree, the classification and regression (CR) tree, and a neural network. The analysis showed that all the machine learning models could predict the credit card customer churn model. In addition, the results showed that the C5 tree machine learning model performed the best in comparison with the three developed models. The results indicated that the top three variables needed in the development of the C5 tree customer churn prediction model were the total transaction count, the total revolving balance on the credit card, and the change in the transaction count. Finally, the results revealed that merging the multi-categorical variables into one variable improved the performance of the prediction models. Full article
Show Figures

Figure 1

Article
AutoML Approach to Stock Keeping Units Segmentation
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1512-1528; https://doi.org/10.3390/jtaer17040076 - 15 Nov 2022
Viewed by 429
Abstract
A typical retailer carries 10,000 stock-keeping units (SKUs). However, these numbers may exceed hundreds of millions for giants such as Walmart and Amazon. Besides the volume, SKU data can also be high-dimensional, which means that SKUs can be segmented on the basis of [...] Read more.
A typical retailer carries 10,000 stock-keeping units (SKUs). However, these numbers may exceed hundreds of millions for giants such as Walmart and Amazon. Besides the volume, SKU data can also be high-dimensional, which means that SKUs can be segmented on the basis of various attributes. Given the data volumes and the multitude of potentially important dimensions to consider, it becomes computationally impossible to individually manage each SKU. Even though the application of clustering for SKU segmentation is common, previous studies do not address the problem of parametrization and model finetuning, which may be extremely tedious and time-consuming in real-world applications. Our work closes the research gap by proposing a solution that leverages automated machine learning for the automated cluster analysis of SKUs. The proposed framework for automated SKU segmentation incorporates minibatch K-means clustering, principal component analysis, and grid search for parameter tuning. It operates on top of the Apache Parquet file format, an efficient, structured, compressed, column-oriented, and big-data-friendly format. The proposed solution was tested on the basis of a real-world dataset that contained data at the pallet level. Full article
Show Figures

Figure 1

Article
The Insights, “Comfort” Effect and Bottleneck Breakthrough of “E-Commerce Temperature” during the COVID-19 Pandemic
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1493-1511; https://doi.org/10.3390/jtaer17040075 - 14 Nov 2022
Viewed by 363
Abstract
The impact of the COVID-19 pandemic on fresh food e-commerce has led to a loss of consumers, and “e-commerce temperature” is seen as an important means of alleviating consumer dissatisfaction and retaining consumers. To explore the connotation and effect of it, and to [...] Read more.
The impact of the COVID-19 pandemic on fresh food e-commerce has led to a loss of consumers, and “e-commerce temperature” is seen as an important means of alleviating consumer dissatisfaction and retaining consumers. To explore the connotation and effect of it, and to break through possible “comfort” bottlenecks, we used online reviews of the Jingdong fresh food platform as research data, mined the characteristics of “e-commerce temperature” with the help of the LDA topic model, and evaluated the mechanism of “e-commerce temperature” on consumer satisfaction during the pandemic by using quasi-natural experiments and Word2vec-based sentiment analysis. The results show that “e-commerce temperature” has five connotations of logistics commitment, humanized delivery, health pledge, pandemic perseverance, and consumer care, which can effectively mitigate the loss of consumer satisfaction. Interestingly, we found that the “e-commerce temperature” has a limited “comfort” effect. Additionally, further social network analysis shows that the bottleneck is mainly due to the consumers’ psychological gaps when comparing the usual e-commerce services, and cretailers can repair them through financial compensation and spiritual solace. The study explores e-commerce service quality at different pandemic stages with the help of text mining techniques, enriches the theory of e-commerce research, and alleviates the Hawthorne bias in traditional empirical studies. This study also provides a reference for e-retailers to improve service quality and respond to emergencies in a changing post-pandemic era. Full article
(This article belongs to the Section Digital Marketing and the Connected Consumer)
Show Figures

Figure 1

Article
Positioning and Web Traffic of Colombian Banking Establishments
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1473-1492; https://doi.org/10.3390/jtaer17040074 - 04 Nov 2022
Viewed by 514
Abstract
The use of digital technologies has become one factor that significantly impacts business results in the financial industry. This study seeks to characterize the positioning and web traffic of Colombian banking establishments through analysis of the classification of their website, taking as reference [...] Read more.
The use of digital technologies has become one factor that significantly impacts business results in the financial industry. This study seeks to characterize the positioning and web traffic of Colombian banking establishments through analysis of the classification of their website, taking as reference the metrics related to web traffic and the attractiveness of the content and relevance for users as the bounce rate. The study presents a quantitative approach, non-experimental design, and descriptive scope. With a sample of 28 banking establishments, it is intended to contribute to the body of literature on bank marketing based on a systematic analysis of indicators. The findings of the study made it possible to elucidate that a good part of the websites of the banking establishments is well positioned, in addition to presenting low bounce rates. It is also possible to show that a significant portion of this traffic comes from individuals between 18 and 34 years of age and of the female gender. Likewise, traffic to the website is derived to a greater extent from direct access to the establishment’s portal or search engines. Full article
(This article belongs to the Special Issue Digital Resilience and Economic Intelligence in the Post-Pandemic Era)
Show Figures

Figure 1

Article
Green Communication for More Package-Free Ecommerce Returns
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1450-1472; https://doi.org/10.3390/jtaer17040073 - 04 Nov 2022
Viewed by 530
Abstract
The existing packed mail-based return mode in ecommerce has a considerable negative impact on the natural environment. In contrast, a package-free return mode accepts unpacked ecommerce returns using return points in-store and is a more eco-friendly service. On the basis of the push–pull–mooring [...] Read more.
The existing packed mail-based return mode in ecommerce has a considerable negative impact on the natural environment. In contrast, a package-free return mode accepts unpacked ecommerce returns using return points in-store and is a more eco-friendly service. On the basis of the push–pull–mooring (PPM) framework, this study aims to identify key factors in green communication that contribute to consumers switching from mail return services to package-free return services. A scenario-based online survey was conducted. Structural equation modeling was used to test the hypotheses. Push factors (consumer dissatisfaction) and a mooring factor (mail return habit) only manifested weak effects on switching intention. Regarding pull factors (service convenience and green value), in contrast to previous research, the effect of green value on switching intention was found to be much weaker than the effect of service convenience. Convenience was found to be the key factor in green communication. Our research adds value to green communication and the PPM framework. It updates existing knowledge concerning the role of consumer dissatisfaction, perceived green value, and perceived convenience of return service in green communication. This study also explains why the mooring factor of habit fails to predict switching intention. Full article
(This article belongs to the Special Issue Multi-Channel Retail and Its Applications in the Future of E-Commerce)
Show Figures

Figure 1

Article
How Generation X and Millennials Perceive Influencers’ Recommendations: Perceived Trustworthiness, Product Involvement, and Perceived Risk
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1431-1449; https://doi.org/10.3390/jtaer17040072 - 01 Nov 2022
Cited by 1 | Viewed by 831
Abstract
Previous literature has found underlying differences in purchasing behaviors, consumption habits, and Internet and social media usage between Generation X and Millennials. The activities and how users engage with consumer advice made by popular social media personalities can differ according to their age. [...] Read more.
Previous literature has found underlying differences in purchasing behaviors, consumption habits, and Internet and social media usage between Generation X and Millennials. The activities and how users engage with consumer advice made by popular social media personalities can differ according to their age. Recent studies have shown that trust in the message transmitted by influencers is a critical factor in explaining the impact of consumer recommendations on their followers. However, so far there is little evidence of the possible variation according to the generational cohort to which they belong. This paper attempts to fill this gap by reviewing theoretical contributions on the relationships between perceived trustworthiness, perceived risk, product involvement, and purchase intention. Next, we proposed an exploratory model that analyzes the differences through partial least squares structural equation modeling (PLS-SEM) with multigroup analysis. The resulting hypotheses were tested on a sample of 116 Millennial and 135 Generation X influencer followers. The results confirmed moderating effects of the generational cohort on message credibility and purchase intention, as well as on Millennials’ risk perception. Additionally, social norm and gender were analyzed, and heterogeneity was found according to the level of social norm of the followers. Full article
(This article belongs to the Section Digital Marketing and the Connected Consumer)
Show Figures

Figure 1

Article
Research on the Coordination of Quality Behavior of Supply 3 Chain of E-Commerce Platform under C2B Model of High-Grade E-Commerce Based on Differential Game
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1409-1430; https://doi.org/10.3390/jtaer17040071 - 27 Oct 2022
Viewed by 519
Abstract
With the increasing demands of consumers for product grade, the C2B model of high-grade e-commerce emerges as required. In order to solve the problem of coordination and cooperation between e-commerce platforms and manufacturers, and to further develop the C2B model of high-grade e-commerce, [...] Read more.
With the increasing demands of consumers for product grade, the C2B model of high-grade e-commerce emerges as required. In order to solve the problem of coordination and cooperation between e-commerce platforms and manufacturers, and to further develop the C2B model of high-grade e-commerce, this paper studies the coordination of supply chain interests by establishing a differential game model considering product grade factors. By comparing the equilibrium solutions of differential games under different decision-making situations, a cooperative coordination mechanism is proposed. Next, the equilibrium solution is further analyzed by means of numerical simulation. Finally, the influence of several important parameters on the equilibrium solution is discussed through sensitivity analysis. It is found that (1) the supply chain parties have optimal quality behavior in the centralized decision-making situation, and the overall benefit is the greatest. (2) Compared with the Nash non-cooperative game, the optimal quality behavior of the dominant party remains unchanged, and the optimal quality behavior of the following party is enhanced after both parties move from the Stackelberg master-slave game, and the optimal profits of both parties, as well as the overall increase. (3) The cooperative coordination model can coordinate the quality behavior of both sides of the supply chain when the benefit distribution coefficient is within a specific range. Full article
(This article belongs to the Section Digital Marketing and the Connected Consumer)
Show Figures

Figure 1

Article
Multichannel Digital Marketing Optimizations through Big Data Analytics in the Tourism and Hospitality Industry
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1383-1408; https://doi.org/10.3390/jtaer17040070 - 24 Oct 2022
Viewed by 1039
Abstract
The tourism sector increasingly relies on technology to acquire new clients in a world overflowing with information. So, the main question that needs to be answered is:What digital marketing strategy should be adopted to attract customers and built digital brand name by incorporating [...] Read more.
The tourism sector increasingly relies on technology to acquire new clients in a world overflowing with information. So, the main question that needs to be answered is:What digital marketing strategy should be adopted to attract customers and built digital brand name by incorporating websites and social media big data? The authors of this research utilize web analytics and big data to build an innovative methodology in an effort to address this issue. After the data collection, statistical analysis was implemented, followed by a fuzzy cognitive map and an agent-based simulation model in order to illustrate the usage of social media and user experience in multichannel marketing. The findings suggest that, in contrast to the websites of other industries, such as logistics, where customers want to finish their inquiries as quickly as possible and leave the webpage, it is advantageous for tourism websites to keep customers’ attention moreon their website in order to increasevisibility. Additionally, the research further highlights the importance of personalization and user-engagement content to e-WOM, suggesting to tourism businesses to encourage posts made by customers and employees. Full article
(This article belongs to the Special Issue Multi-Channel Retail and Its Applications in the Future of E-Commerce)
Show Figures

Figure 1

Article
Competitive Policy for Online Retailers’ Intrusion in E-Commence
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1361-1382; https://doi.org/10.3390/jtaer17040069 - 21 Oct 2022
Viewed by 411
Abstract
In recent years, online retail has developed rapidly. However, as consumer demands become increasingly sophisticated, the traditional online retail model has encountered difficulties with respect to meeting consumers’ needs. As a result, numerous retailers with offline physical stores have emerged in the online [...] Read more.
In recent years, online retail has developed rapidly. However, as consumer demands become increasingly sophisticated, the traditional online retail model has encountered difficulties with respect to meeting consumers’ needs. As a result, numerous retailers with offline physical stores have emerged in the online retail industry. This paper constructs a game model for the invasion of the market by e-commerce retailers with offline physical stores in a context in which a traditional, online-only incumbent retailer is already in the market. Compared with the new entrant, the incumbent has the advantage of an established good reputation, and consumers prefer the products of the incumbent. This research shows that as consumers’ product valuations increase, the following three situations may occur: a partially covered market, a multiple-equilibrium market or a fully covered market. In a partially covered market, the incumbency advantage does not affect the entrant. In a multiple-equilibrium market or fully covered market, the incumbency advantage impacts the profits of the entrant. However, in a fully covered market, if the incumbency advantage is too large, the profits of both retailers are damaged. Finally, this paper finds that offline physical stores can provide positive benefits to entrants. When consumers are highly sensitive to services, opening offline physical stores is an effective intrusion strategy that entrants can use to overcome the incumbency advantage. Full article
(This article belongs to the Section e-Commerce Analytics)
Show Figures

Figure 1

Article
Measuring Using Disruptive Technology in the Supply Chain Context: Scale Development and Validation
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1336-1360; https://doi.org/10.3390/jtaer17040068 - 19 Oct 2022
Viewed by 604
Abstract
The concept of disruptive technology has been in our lives for many years, and it is essential to measure their utilization levels to survive in the global competitive environment, to benefit from their contributions to supply chains, to examine their relations with supply [...] Read more.
The concept of disruptive technology has been in our lives for many years, and it is essential to measure their utilization levels to survive in the global competitive environment, to benefit from their contributions to supply chains, to examine their relations with supply chain operations and to compare them with average state of the industry. The aim of this study is to develop and validate a measurement instrument for supply chain management practices in the disruptive technology field. Accordingly, the study was carried out in five steps and the sample size consists of 47 companies as pilot data and 426 companies for the main data. These steps consist of item generation and purification, pilot test, initial identification of dimensionality, dimensionality confirmation and convergent validity assessment. As a result of the study, a new scale with a single factor structure was developed. The study ends with the evaluation of the findings. Correcting the lack of a measurement tool developed in this field in the literature is the theoretical contribution of the study. Furthermore, this study enables supply chain leaders to compare their utilization level of disruptive technology with the industries in which they operate, to associate it with operations and to enhance technology investments in practice. Full article
(This article belongs to the Special Issue Supply Chain Digitalization)
Show Figures

Figure 1

Article
Blockchain-Driven Optimal Strategies for Supply Chain Finance Based on a Tripartite Game Model
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1320-1335; https://doi.org/10.3390/jtaer17040067 - 16 Oct 2022
Viewed by 556
Abstract
Applying blockchain to supply chain financing is an effective way to solve the problems of financing difficulties, high financing costs, and slow financing for small and medium-sized enterprises (SMZEs). Using evolutionary game theory, this study constructs a tripartite game model and analyzes the [...] Read more.
Applying blockchain to supply chain financing is an effective way to solve the problems of financing difficulties, high financing costs, and slow financing for small and medium-sized enterprises (SMZEs). Using evolutionary game theory, this study constructs a tripartite game model and analyzes the influence of blockchain technology on the evolutionary stability strategies for financial institutions (FIs), core enterprises (CEs), and SMZEs, in which the default losses of CEs and SMZEs are assumed to be dynamic. The results of this study are as follows: (1) When CEs and SMZESs’ default losses are lower than some critical value, they tend to break their promises. (2) When accounts receivable are greater than some critical value, CEs cannot repay on time because they can make a relatively large profits from delayed repayment, whereas SMZEs can be constrained to be trustworthy. Finally, the results using numerical simulation show that both relatively large default losses and enough large, trustworthy income sources can make CEs and SMZEs tend to keep their promises; in turn, CEs would be non-paying and the SMZEs tend to be trustworthy for relatively large accounts receivable. The results provide theoretical support for realizing healthy and sustainable development for supply chain finance. Full article
(This article belongs to the Special Issue Blockchain Commerce Ecosystem)
Show Figures

Figure 1

Review
Factors Influencing Solvers’ Behaviors in Knowledge-Intensive Crowdsourcing: A Systematic Literature Review
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1297-1319; https://doi.org/10.3390/jtaer17040066 - 12 Oct 2022
Cited by 1 | Viewed by 612
Abstract
Solver participation plays a critical role in the sustained development of knowledge-intensive crowdsourcing (KI-C) systems. Extant theory has highlighted numerous factors that influence solvers’ participation behaviors in KI-C. However, a structured investigation and integration of significant influential factors is still lacking. This study [...] Read more.
Solver participation plays a critical role in the sustained development of knowledge-intensive crowdsourcing (KI-C) systems. Extant theory has highlighted numerous factors that influence solvers’ participation behaviors in KI-C. However, a structured investigation and integration of significant influential factors is still lacking. This study consolidated the state of academic research on factors that affect solver behaviors in KI-C. Based on a systematic review of the literature published from 2006 to 2021, this study identified five major solver behaviors in KI-C. Subsequently, eight solver motives and seventeen factors under four categories, i.e., task attributes, solver characteristics, requester behaviors, and platform designs, were identified to affect each of the solver behaviors. Moreover, the roles of solver motives and the identified factors in affecting solver behaviors were demonstrated as well. We also suggested a number of areas meriting future research in this study. Full article
(This article belongs to the Section Digital Marketing and the Connected Consumer)
Show Figures

Figure 1

Article
Digital Economy and the Upgrading of the Global Value Chain of China’s Service Industry
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1279-1296; https://doi.org/10.3390/jtaer17040065 - 01 Oct 2022
Viewed by 841
Abstract
China’s service trade competitiveness is weak, and the service industry occupies a low position in the GVC (Global Value Chain); therefore, promoting the upgrade of the GVC of China’s service industry is worth studying. Under the new situation of the continuous integration of [...] Read more.
China’s service trade competitiveness is weak, and the service industry occupies a low position in the GVC (Global Value Chain); therefore, promoting the upgrade of the GVC of China’s service industry is worth studying. Under the new situation of the continuous integration of the digital economy and the real economy, the digital economy has injected new momentum into the mid-to-high end of the GVC of China’s service industry. Based on the panel data of the service industry sub-sectors, the mediating effect model is constructed, and the system GMM (Generalized Method of Moments) is used to empirically determine whether the digital economy can significantly improve the participation and position of China’s service industry in the GVC, and promote the upgrading of the GVC of China’s service industry. This conclusion still holds after replacing the independent variable measurement indicator, adding control variables, considering changes in industry trends, and using quantile regression and other robustness tests. The promotion effect of the digital economy on the upgrading of the GVC of China’s service industry shows heterogeneity in different service objects and service industries with different factor intensities, indicating that the digital economy will affect the internal structure of the upgrading of the GVC of China’s service industry. The results of the mediation test found that the service trade cost, multilateral resistance to service trade, service industry structure, financial development level, human capital and service export complexity are the mechanisms for the digital economy to enable the upgrading of the GVC of China’s service industry. This study improves the analysis of the impact factors of the GVC in the service industry, enriches the theory of the GVC, and improves the research content of digital economy theory. This study also provides a reference for other developing countries similar to China on how to promote the upgrading of the GVC of the service industry in the process of digital economy development. Full article
Article
Predicting Conversion Rates in Online Hotel Bookings with Customer Reviews
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1264-1278; https://doi.org/10.3390/jtaer17040064 - 30 Sep 2022
Viewed by 656
Abstract
E-commerce in the hospitality and tourism field has already ranked No. 2 among all online shopping categories worldwide. However, customers’ visits to a hotel booking website cannot guarantee the generation of sales, while the conversion rate is regarded as the indicator that effectively [...] Read more.
E-commerce in the hospitality and tourism field has already ranked No. 2 among all online shopping categories worldwide. However, customers’ visits to a hotel booking website cannot guarantee the generation of sales, while the conversion rate is regarded as the indicator that effectively assesses the e-commerce website performance. This study aimed to investigate the influential factors of conversion rates from both affective content and the communication style of customer’s online reviews. The affective content was evaluated with eight emotional dimensions (i.e., joy, sadness, anger, fear, trust, disgust, anticipation, and surprise) in Plutchik’s emotion wheel, and the communication style perspective was assessed with linguistic style matching (LSM). In total, 111,926 customer reviews from 641 hotels in five cities in the U.S. were collected for the analysis. Results indicated that LSM and four emotions have significant impacts on hotel conversion rates. This research contributes to the knowledge body of customers’ conversion behaviors on hotel booking websites and offers pertinent practical implications. Full article
Show Figures

Figure 1

Article
Research on Supervision Mechanism of Big Data Discriminatory Pricing on the Asymmetric Service Platform—Based on SD Evolutionary Game Model
by and
J. Theor. Appl. Electron. Commer. Res. 2022, 17(4), 1243-1263; https://doi.org/10.3390/jtaer17040063 - 23 Sep 2022
Viewed by 617
Abstract
Big data discriminatory pricing behavior of service platforms frequently occurs, which affects the legitimate rights and interests of consumers as well as the healthy development of the platform economy. The SD (System Dynamics) evolutionary game model characterizing the game relationship of a big [...] Read more.
Big data discriminatory pricing behavior of service platforms frequently occurs, which affects the legitimate rights and interests of consumers as well as the healthy development of the platform economy. The SD (System Dynamics) evolutionary game model characterizing the game relationship of a big platform, small platform, and government is constructed together with its equilibrium solutions in order to analyze the regulatory dilemma and governance mechanism against big data discriminatory pricing of service platforms. This paper finds that government punishment on the behavior of big data discriminatory pricing plays a decisive role. When the government punishment is large enough, both platforms tend towards fair pricing; when the government punishment is insufficient, the big platform always tends towards discriminatory pricing. The supply chain of the service platform falls into the regulatory dilemma of big data discriminatory pricing behavior. Due to the hidden characteristics of big data discriminatory pricing and technical challenges in authentication and proof, a third party is introduced for supervision, and an SD evolutionary game model with a collaborative supervision mechanism of the government and the third party is constructed. The results show that positive supervision of the third party can effectively regulate the big data discriminatory pricing behavior of the big platform, which has specific implications for the design of the supervision mechanism against big data discriminatory pricing of service platforms. Full article
Show Figures

Figure 1

Previous Issue
Back to TopTop