Journal of Theoretical and Applied Electronic Commerce Research

19 pages, 451 KiB

Open AccessArticle

From Technology to Traffic: How Website Technological Sophistication, Brand Recognition, and Business Model Innovation Drive Consumer Traffic in Korean E-Commerce

by Si Yu, Yutong Liu and Eun-jung Hyun

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 2051-2069; https://doi.org/10.3390/jtaer19030100 - 8 Aug 2024

Viewed by 214

Abstract

As e-commerce continues to expand, understanding the factors that drive consumer traffic to business-to-consumer (B2C) websites is crucial. This study investigates the interplay between website technological sophistication, brand recognition, and business model innovation in influencing website traffic among Korean B2C companies. Drawing on [...] Read more.

As e-commerce continues to expand, understanding the factors that drive consumer traffic to business-to-consumer (B2C) websites is crucial. This study investigates the interplay between website technological sophistication, brand recognition, and business model innovation in influencing website traffic among Korean B2C companies. Drawing on data from 9003 companies across seven key sectors—finance, retail, healthcare, technology, food, education, and media—we employ Ordinary Least Squares (OLS) regression analysis to test our hypotheses. Our findings reveal that website technological sophistication is positively associated with monthly website visits. This relationship is particularly pronounced for companies with innovative business models, highlighting the synergistic effect of advanced website features and novel business strategies in attracting consumers. Conversely, the positive impact of website technological sophistication on traffic is less significant for well-established brands with high recognition levels, indicating that strong brand equity can mitigate the need for highly sophisticated websites. These results align with the Technology Acceptance Model (TAM), Innovation Diffusion Theory (IDT), and Signaling Theory (ST), providing a nuanced understanding of how technology, branding, and innovation intersect to drive online consumer behavior. Our study offers valuable insights for e-commerce firms seeking to optimize their digital presence and underscores the importance of investing in advanced website functionalities, particularly for lesser-known brands and companies with innovative business models. Future research should explore these dynamics in different cultural and industry contexts to enhance the generalizability of our findings. Full article

(This article belongs to the Topic Digital Marketing Dynamics: From Browsing to Buying)

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21 pages, 447 KiB

Open AccessArticle

Effect of E-Servicescape on Emotional Response and Revisit Intention in an Internet Shopping Mall

by Zeyu Li, Ana Belén Tulcanaza-Prieto and Chang Won Lee

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 2030-2050; https://doi.org/10.3390/jtaer19030099 - 5 Aug 2024

Viewed by 369

Abstract

This study aims to explore the effect of the e-servicescape on the emotional response and revisit intention of customers in an internet shopping mall (ISM) environment. The literature was reviewed on the e-servicescape, emotional response, and revisit intention in an internet shopping mall. [...] Read more.

This study aims to explore the effect of the e-servicescape on the emotional response and revisit intention of customers in an internet shopping mall (ISM) environment. The literature was reviewed on the e-servicescape, emotional response, and revisit intention in an internet shopping mall. A relevant model and hypothesis were established. For the empirical study, a survey form was developed and conducted on 150 customers with experience using a certain ISM. Reliability analysis and confirmatory factor analysis were performed using SPSS 27.0 and Amos 26.0 software, and the causal relationships were identified through structural equation modeling (SEM). Study results and implications were discussed and suggested. Among the factors of the e-servicescape in an ISM, aesthetics and surrounding elements did not have a significant effect on emotional responses, and spatial functionality showed a positive effect on emotional responses. Aesthetics had a weak negative effect on revisit intention. Surrounding elements and spatial functionality had no significant effect on revisit intention. The emotional response had a positive effect on revisit intention. This study identified the importance of the e-servicescape in the ISM environment and especially emphasized the importance of spatial functionality on the emotional response and aesthetics on revisit intention. This study presented several suggestions and implications to corporate managers regarding the development and management of the future ISM environment and other similar business settings. Full article

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30 pages, 1446 KiB

Open AccessArticle

Towards Frugal Innovation Capability in Emerging Markets within the Digitalization Epoch: Exploring the Role of Strategic Orientation and Organizational Ambidexterity

by Josephat Deusidedith Sengura, Renyan Mu and Jingshu Zhang

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 2000-2029; https://doi.org/10.3390/jtaer19030098 - 2 Aug 2024

Viewed by 456

Abstract

Digitalization has forced emerging market (EM) firms operating in resource-constrained environments to adopt market-driven strategies, particularly frugal innovation, to provide affordable, optimized processes and high-value solutions. However, understanding the mechanisms behind developing frugal innovation capability (FIC) at the firm level in diverse EMs [...] Read more.

Digitalization has forced emerging market (EM) firms operating in resource-constrained environments to adopt market-driven strategies, particularly frugal innovation, to provide affordable, optimized processes and high-value solutions. However, understanding the mechanisms behind developing frugal innovation capability (FIC) at the firm level in diverse EMs remains limited. From the perspective of the resource-based view, this study added to the existing body of knowledge by exploring how strategic orientation (entrepreneurial orientation (EO) and market orientation (MO)) and organizational ambidexterity (OA) impact the development of FIC in EMs. To empirically validate our theoretical predictions, this study used a cross-sectional survey to collect data from 386 valid respondents from Tanzanian manufacturing firms. The results demonstrate that both EO and MO have a strong and positive relationship with OA and the development of FIC in EMs. In addition, OA partially mediates the relationship of both EO and MO with the development of FIC. Furthermore, our results indicate that MO exerts a more significant impact on the development of FIC than EO in EMs. Managers of manufacturing firms in EMs can use these findings to review their strategic decisions and their exploitative and exploratory approaches to enhance supply chains, develop cost-effective technologies, and produce affordable offerings that cater to the preferences of price-conscious consumers in the digital age. Full article

(This article belongs to the Section Entrepreneurship, Innovation, FinTech Accounting and Industry 4.0)

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16 pages, 704 KiB

Open AccessArticle

Enhancing E-Business Communication with a Hybrid Rule-Based and Extractive-Based Chatbot

by Onur Dogan and Omer Faruk Gurcan

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1984-1999; https://doi.org/10.3390/jtaer19030097 - 1 Aug 2024

Viewed by 306

Abstract

E-businesses often face challenges related to customer service and communication, leading to increased dissatisfaction among customers and potential damage to the brand. To address these challenges, data-driven and AI-based approaches have emerged, including predictive analytics for optimizing customer interactions and chatbots powered by [...] Read more.

E-businesses often face challenges related to customer service and communication, leading to increased dissatisfaction among customers and potential damage to the brand. To address these challenges, data-driven and AI-based approaches have emerged, including predictive analytics for optimizing customer interactions and chatbots powered by AI and NLP technologies. This study focuses on developing a hybrid rule-based and extractive-based chatbot for e-business, which can handle both routine and complex inquiries, ensuring quick and accurate responses to improve communication problems. The rule-based QA method used in the chatbot demonstrated high precision and accuracy in providing answers to user queries. The rule-based approach achieved impressive 98% accuracy and 97% precision rates among 1684 queries. The extractive-based approach received positive feedback, with 91% of users rating it as “good” or “excellent” and an average user satisfaction score of 4.38. General user satisfaction was notably high, with an average Likert score of 4.29, and 54% of participants gave the highest score of 5. Communication time was significantly improved, as the chatbot reduced average response times to 41 s, compared to the previous 20-min average for inquiries. Full article

(This article belongs to the Topic Online User Behavior in the Context of Big Data)

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41 pages, 1005 KiB

Open AccessArticle

A Conceptual Approach to Understanding the Customer Experience in E-Commerce: An Empirical Study

by Paulo Botelho Pires, Mariana Prisco, Catarina Delgado and José Duarte Santos

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1943-1983; https://doi.org/10.3390/jtaer19030096 - 30 Jul 2024

Viewed by 520

Abstract

This study aimed to identify the constructs related to customer experience that underpin e-commerce, as well as their interconnections, to develop a comprehensive conceptual model based on theories-in-use. A quantitative approach was employed through a survey of 441 respondents. Data analysis was conducted [...] Read more.

This study aimed to identify the constructs related to customer experience that underpin e-commerce, as well as their interconnections, to develop a comprehensive conceptual model based on theories-in-use. A quantitative approach was employed through a survey of 441 respondents. Data analysis was conducted using partial least squares structural equation modeling. The research findings revealed that there are a total of 11 constructs: customer experience, customer satisfaction, customer loyalty, word-of-mouth, trust, perceived risk, security and privacy, web content, perceived price, perceived value, and service quality. Furthermore, twelve relationships were established between these constructs, which led to the development of a holistic conceptual model. The identified constructs and the relationships between them are hierarchized, which has practical implications for businesses. It allows them to concentrate on operational activities and formulate and implement strategies that are valued by consumers and supported by empirical evidence. The originality and value of this research lie in the conception and development of a comprehensive e-commerce model, which includes eleven constructs and twelve relationships. It also highlights the pivotal role of the customer experience. Full article

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21 pages, 1144 KiB

Open AccessArticle

Understanding How Streamer’s Self-Presentation in E-Commerce Live Streaming Affects Consumers: The Role of Persuasion Knowledge

by Shuangshuang Song, Ying Xu, Baolong Ma and Xin Zong

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1922-1942; https://doi.org/10.3390/jtaer19030095 - 30 Jul 2024

Viewed by 401

Abstract

In recent years, live streaming has become the mainstream way of online shopping in China. As the dominant player and performer in live streaming, streamers play a crucial role in consumers’ purchase decisions. Therefore, this study focuses on the self-presentation behavior of streamers [...] Read more.

In recent years, live streaming has become the mainstream way of online shopping in China. As the dominant player and performer in live streaming, streamers play a crucial role in consumers’ purchase decisions. Therefore, this study focuses on the self-presentation behavior of streamers in the context of e-commerce live streaming and explores the mechanism of its influence on consumers’ purchase intention from the perspective of persuasion knowledge. A total of 538 consumers from China participated in this anonymous survey. The results indicate that helpful and empathetic behaviors of streamers can significantly enhance consumers’ purchase intention, while derogatory, exaggerated, and flattering behaviors of streamers can significantly diminish consumers’ purchase intention. Persuasion knowledge played a mediating role and had a significant negative impact on purchase intention, while anticipated inaction regret weakened its effect on purchase intention. Full article

(This article belongs to the Topic Consumer Psychology and Business Applications)

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15 pages, 1275 KiB

Open AccessArticle

The Evolution of Price Discrimination in E-Commerce Platform Trading: A Perspective of Platform Corporate Social Responsibility

by Ying Ma, Xiaodong Guo, Weihuan Su and Guo Fu

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1907-1921; https://doi.org/10.3390/jtaer19030094 - 26 Jul 2024

Viewed by 424

Abstract

The widespread use of data in e-commerce has facilitated the implementation of different pricing strategies for platforms and merchants. However, the excessive use of algorithms for differential pricing has sparked discussions about fairness and price discrimination, disrupting the platform trading system. To address [...] Read more.

The widespread use of data in e-commerce has facilitated the implementation of different pricing strategies for platforms and merchants. However, the excessive use of algorithms for differential pricing has sparked discussions about fairness and price discrimination, disrupting the platform trading system. To address this challenge, we adopt an evolutionary game approach to analyze the evolutionary strategies of all parties from the perspective of platform CSR. It is based on a special type of e-commerce platform trading in which major merchants have data analytics capabilities. We construct an evolutionary game model considering reputation and punishment, explore the impact of different situations and factors on the system’s evolutionary stability strategy, and conduct its verification via simulation experiments. The results show that long-term reputation is the internal driving force for platforms to fulfill responsibilities. The joint punishment of collusion is the external binding force. Consumer complaints are key to restricting merchants’ integrity operation. Moreover, penalties imposed by e-commerce platforms can help eradicate price discrimination. This study provides a new perspective to solve price discrimination in the digital era. Measures based on reputation and punishment can guide platforms to fulfill other social responsibilities. Full article

(This article belongs to the Topic Consumer Psychology and Business Applications)

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14 pages, 869 KiB

Open AccessArticle

The Role of Service Quality Attributes and Perceived Value in US Consumers’ Impulsive Buying Intentions for Fresh Food E-Commerce

by Jee-Won Kang and Young Namkung

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1893-1906; https://doi.org/10.3390/jtaer19030093 - 23 Jul 2024

Viewed by 358

Abstract

Given the widespread adoption of fresh food e-commerce, this study aimed to explore the service quality attributes influencing utilitarian value, hedonic value, and impulsive buying behavior. A survey was conducted with 263 participants who had experience in purchasing fresh food online. Their responses [...] Read more.

Given the widespread adoption of fresh food e-commerce, this study aimed to explore the service quality attributes influencing utilitarian value, hedonic value, and impulsive buying behavior. A survey was conducted with 263 participants who had experience in purchasing fresh food online. Their responses were analyzed to test hypotheses using structural equation modeling. The findings reveal significant influences of information quality, ease of use, and problem resolution on utilitarian value. Additionally, ease of use, problem resolution, and trendiness were found to impact hedonic value. Problem resolution was a quality factor that affected both practical value and hedonic value, and its influence was found to be greater than that of other service quality factors. Hedonic value was also found to significantly affect impulsive buying behavior; however, utilitarian value did not exhibit a significant impact on impulsive buying behavior. The results provide useful theoretical and managerial implications in the field of fresh food e-commerce business. Full article

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24 pages, 3965 KiB

Open AccessArticle

Optimizing Reserve Decisions in Relief Supply Chains with a Blockchain-Supported Second-Hand E-Commerce Platform

by Yingjie Ju, Yue Wang, Jianliang Yang, Yu Feng and Yuheng Ren

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1869-1892; https://doi.org/10.3390/jtaer19030092 - 18 Jul 2024

Viewed by 465

Abstract

This paper develops a novel government reserve strategy, employing a blockchain-supported second-hand E-commerce platform, specifically designed to mitigate the depreciation and expiration of disaster relief supplies. Utilizing the newsvendor model and convex optimization techniques, this study evaluates the efficacy of a rotational strategy [...] Read more.

This paper develops a novel government reserve strategy, employing a blockchain-supported second-hand E-commerce platform, specifically designed to mitigate the depreciation and expiration of disaster relief supplies. Utilizing the newsvendor model and convex optimization techniques, this study evaluates the efficacy of a rotational strategy for optimal pre-positioning of supplies, considering the dynamic conditions of supply chain performance. Additionally, the paper demonstrates how blockchain technology significantly enhances the traceability of supplies, which is crucial for effective supply management. Empirical data analysis reveals that exceeding a critical price threshold on the platform not only augments the government’s optimal reserve levels but also substantially decreases operational costs. In scenarios where the supply chain is well coordinated, optimal reserve quantities are affected by variables such as the likelihood of disaster events, the success rate of sales, and a supply traceability index. This research extends the application of blockchain and E-commerce technologies within disaster management supply chains and offers new insights and practical approaches for improving E-commerce practices in this context. Full article

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21 pages, 1163 KiB

Open AccessArticle

Simultaneous or Sequential? Supplier Product Launch Strategy through E-Commerce Channels with Different Models

by Zhiwen Li, Baojiao Wang and Yeting Wu

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1848-1868; https://doi.org/10.3390/jtaer19030091 - 18 Jul 2024

Viewed by 509

Abstract

As the e-commerce landscape diversifies, suppliers are faced with the critical decision of how to effectively launch their products through e-commerce channels with varying business models. This study aims to explore the strategic considerations for a supplier launching products through two distinct e-commerce [...] Read more.

As the e-commerce landscape diversifies, suppliers are faced with the critical decision of how to effectively launch their products through e-commerce channels with varying business models. This study aims to explore the strategic considerations for a supplier launching products through two distinct e-commerce channels: one based on a direct sale model and the other on a reselling model. It builds a theoretical model to examine the supplier’s decision-making across three strategic options: a simultaneous launch through both channels, a sequential launch starting with the direct sale model followed by the reselling model, and vice versa. The equilibria of those options are derived through game analysis and further compared. The results reveal that for suppliers under a non-alliance pricing contract, a simultaneous product launch across both channels is the most advantageous approach. Conversely, in scenarios where an alliance pricing contract is in place, the optimal strategy shifts towards a sequential launch. The decision of which channel to ally with—whether the direct sale or the reselling model—hinges critically on the difference in service efficiency and the intensity of competition between the channels. This nuanced analysis highlights the importance of strategic flexibility and alignment with channel dynamics in maximizing product launch success in the evolving e-commerce environment. Full article

(This article belongs to the Collection Emerging Topics in Omni-Channel Operations)

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17 pages, 18435 KiB

Open AccessArticle

Dynamic Mining of Consumer Demand via Online Hotel Reviews: A Hybrid Method

by Weiping Yu, Fasheng Cui, Ping Wang and Xin Liao

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1831-1847; https://doi.org/10.3390/jtaer19030090 - 18 Jul 2024

Viewed by 521

Abstract

This study aims to dynamically mine the demands of hotel consumers. A total of 378,270 online reviews in the cities of Beijing, Chengdu, and Guangzhou in China were crawled using Python. Natural language processing (e.g., opinion mining and the BERT model) and an [...] Read more.

This study aims to dynamically mine the demands of hotel consumers. A total of 378,270 online reviews in the cities of Beijing, Chengdu, and Guangzhou in China were crawled using Python. Natural language processing (e.g., opinion mining and the BERT model) and an improved Kano model (containing One-dimensional, Attractive, Indifferent, and Must-be) were utilised to analyse online hotel reviews. The results indicate that the hotel attributes that consumers care about (e.g., Clean, Breakfast, and Front Desk) are dynamically fluctuating, and the attention and satisfaction of corresponding attributes will also change. This study classified consumer demand into eight types across cities and found that it changes over time. In addition, we also found that hotel attributes, satisfaction and attention, and consumer demands vary among different cities. Existing studies of capturing consumer demand are usually time-consuming and static, and the results are subjective. This study compared and analysed the consumer demands of hotels in different cities via a dynamic perspective, and used hybrid methods to improve the granularity of the analysis, expanding the general applicability of the Kano model. Hotel managers can refer to the results of this article to allocate resources for improvement and create competitive hotel services. Full article

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19 pages, 867 KiB

Open AccessArticle

The Impact of Travel Scenarios and Perceptions on Choice Behavior towards Multi-Forms of Ride-Hailing Services: Case of Nanjing, China

by Ke Lu and Yunlin Wei

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1812-1830; https://doi.org/10.3390/jtaer19030089 - 16 Jul 2024

Viewed by 472

Abstract

The travel behavior of urban residents has gradually changed in response to the widespread adoption of ride-hailing services. This paper explores the travel mode choices made by individuals utilizing multiple forms of ride-hailing services. Eight scenarios were established, which considered combinations of activity [...] Read more.

The travel behavior of urban residents has gradually changed in response to the widespread adoption of ride-hailing services. This paper explores the travel mode choices made by individuals utilizing multiple forms of ride-hailing services. Eight scenarios were established, which considered combinations of activity types (commute or recreation), travel periods (peak or off-peak), and price levels (discounted or normal rates for ride-hailing). Moreover, socio-psychological variables such as perceived value, behavioral intention, and subjective norm were integrated into the analysis. The findings reveal that consumers of ride-hailing services generally exhibit characteristics such as being younger in age, having higher income, lack of car ownership, and having greater experience in using ride-hailing services. Furthermore, the inclusion of socio-psychological variables significantly improved the model’s fitness. Travelers exhibit a preference for ride-hailing services in scenarios involving recreational activities, normal travel periods, and discounted ride-hailing prices. In conclusion, this study sheds light on the evolving travel behavior of urban residents in light of the widespread availability of ride-hailing services. The incorporation of socio-psychological factors is essential in comprehending and predicting travel mode choices. The insights derived from this research contribute to a nuanced understanding of the factors influencing the adoption of and preference for ride-hailing services among urban commuters. Full article

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19 pages, 1741 KiB

Open AccessArticle

Comparative Study on Barriers of Supply Chain Management MOOCs in China: Online Review Analysis with a Novel TOPSIS-CoCoSo Approach

by Shupeng Huang, Hong Cheng and Meiling Luo

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1793-1811; https://doi.org/10.3390/jtaer19030088 - 16 Jul 2024

Viewed by 556

Abstract

To enhance the effectiveness of supply chain talent education, higher education institutions and other organisations have started to develop and use Massive Open Online Courses (MOOCs) in their training programs. However, the problem is that the design and delivery of supply chain management [...] Read more.

To enhance the effectiveness of supply chain talent education, higher education institutions and other organisations have started to develop and use Massive Open Online Courses (MOOCs) in their training programs. However, the problem is that the design and delivery of supply chain management MOOCs can be inappropriately presented and, thus, ineffective, especially for educational teams with fewer teaching experiences of MOOCs. This eventually makes it hard for the students’ learning outcomes to meet the industrial requirements of supply chain experts. Motivated by such a problem, this paper aims to improve the design and delivery of supply chain management MOOCs to enhance student learning outcomes. To achieve this goal, the research method adopted in this paper is to analyse online reviews in a widely-used Chinese MOOC platform with a novel TOPSIS-CoCoSo approach, aiming to identify the barriers to supply chain management MOOCs and their potential solutions. The results of this study show that 16 barriers to MOOCs are identified from the online reviews and then ranked based on their severity of reducing learning outcomes. The perceptions of the severity of the barriers to students and lecturers are compared, and the solutions to the barriers are then discussed. In addition, our comparison indicates that although students and lecturers have similar perceptions of severity for the majority of the barriers, they have significant disagreements on certain barriers. The significance of this study is that it can inform lecturers in supply chain management or relevant disciplines to better design and deliver their MOOC content, as well as contribute to the existing literature by providing new methodological tools for educational analysis. Also, this study highlights the necessity of comparative study in the MOOC online review analysis. Full article

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17 pages, 1554 KiB

Open AccessArticle

Text Mining Based Approach for Customer Sentiment and Product Competitiveness Using Composite Online Review Data

by Zhanming Wen, Yanjun Chen, Hongwei Liu and Zhouyang Liang

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1776-1792; https://doi.org/10.3390/jtaer19030087 - 15 Jul 2024

Viewed by 394

Abstract

We aimed to provide a realistic portrayal of customer sentiment and product competitiveness, as well as to inspire businesses to optimise their products and enhance their services. This paper uses 119,190 pairs of real composite review data as a corpus to examine customer [...] Read more.

We aimed to provide a realistic portrayal of customer sentiment and product competitiveness, as well as to inspire businesses to optimise their products and enhance their services. This paper uses 119,190 pairs of real composite review data as a corpus to examine customer sentiment analysis and product competitiveness. The research is conducted by combining TF-IDF text mining with a time-phase division through the k-means clustering method. The study identified ‘quality’, ‘taste’, ‘appearance packaging’, ‘logistics’, ‘prices’, ‘service’, ‘evaluations’, and ‘customer loyalty’ as the commodity dimensions that customers are most concerned about. These dimensions should therefore serve as the primary entry point for improving the commodity and understanding customers. A review of customer feedback reveals that the composite reviews can be divided into three time stages. Furthermore, the sentiment expressed by customers can become increasingly negative over time. The product competitiveness based on the composite review can be characterised by four regional quadrants, such as ‘Advantage Area’, ‘Struggle Area’, ‘Opportunity Area’, and ‘Waiting Area’, and merchants can target these areas to improve product competitiveness according to the dimensional distribution. In the future, it will also be possible to take customer demographics into account in order to gain a deeper understanding of the customer base. Full article

(This article belongs to the Section e-Commerce Analytics)

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20 pages, 11158 KiB

Open AccessArticle

Quantitative Stock Selection Model Using Graph Learning and a Spatial–Temporal Encoder

by Tianyi Cao, Xinrui Wan, Huanhuan Wang, Xin Yu and Libo Xu

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1756-1775; https://doi.org/10.3390/jtaer19030086 - 15 Jul 2024

Viewed by 582

Abstract

In the rapidly evolving domain of finance, quantitative stock selection strategies have gained prominence, driven by the pursuit of maximizing returns while mitigating risks through sophisticated data analysis and algorithmic models. Yet, prevailing models frequently neglect the fluid dynamics of asset relationships and [...] Read more.

In the rapidly evolving domain of finance, quantitative stock selection strategies have gained prominence, driven by the pursuit of maximizing returns while mitigating risks through sophisticated data analysis and algorithmic models. Yet, prevailing models frequently neglect the fluid dynamics of asset relationships and market shifts, a gap that undermines their predictive and risk management efficacy. This oversight renders them vulnerable to market volatility, adversely affecting investment decision quality and return consistency. Addressing this critical gap, our study proposes the Graph Learning Spatial–Temporal Encoder Network (GL-STN), a pioneering model that seamlessly integrates graph theory and spatial–temporal encoding to navigate the intricacies and variabilities of financial markets. By harnessing the inherent structural knowledge of stock markets, the GL-STN model adeptly captures the nonlinear interactions and temporal shifts among assets. Our innovative approach amalgamates graph convolutional layers, attention mechanisms, and long short-term memory (LSTM) networks, offering a comprehensive analysis of spatial–temporal data features. This integration not only deciphers complex stock market interdependencies but also accentuates crucial market insights, enabling the model to forecast market trends with heightened precision. Rigorous evaluations across diverse market boards—Main Board, SME Board, STAR Market, and ChiNext—underscore the GL-STN model’s exceptional ability to withstand market turbulence and enhance profitability, affirming its substantial utility in quantitative stock selection. Full article

(This article belongs to the Topic Artificial Intelligence Applications in Financial Technology)

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22 pages, 10040 KiB

Open AccessArticle

Alone or Mixed? The Effect of Digital Human Narrative Scenarios on Chinese Consumer Eco-Product Purchase Intention

by Chaohua Huang, Tong Song and Haijun Wang

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1734-1755; https://doi.org/10.3390/jtaer19030085 - 9 Jul 2024

Viewed by 896

Abstract

Digital human narrative transportation has proven to be an effective green brand marketing strategy. However, there is still a lack of in-depth research on the relationship between the role of different digital human narrative scenarios in consumer perceptions and behaviors. This research examined [...] Read more.

Digital human narrative transportation has proven to be an effective green brand marketing strategy. However, there is still a lack of in-depth research on the relationship between the role of different digital human narrative scenarios in consumer perceptions and behaviors. This research examined the impact of digital human narrative scenarios on eco-product purchase intention through four studies. Study 1 found that anime-like (vs. human-like) digital human narratives led to more positive emotional arousal and higher eco-product purchase intention through the use of encephalography (EEG) experiments. Studies 2–4 examined the effect of digital human narrative scenarios on eco-product purchase intentions and explored the mediating role of narrative presence and the moderating role of narrative type. The results showed that mixed (vs. single) narratives lead to more positive consumer purchase intentions. In addition, sharing-oriented (vs. persuasion-oriented) narratives also led to a more positive perception of narrative presence. These findings provide insights for marketers using digital human narratives to promote eco-product consumption. Full article

(This article belongs to the Topic Consumer Psychology and Business Applications)

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17 pages, 1484 KiB

Open AccessArticle

Buyers’ Negative Ratings and Textual Comments on eBay: Reasons for Posting Ratings and Factors in Denouncing Sellers

by Xubo Zhang, Yanbin Tu, Mark H. Haney and Huawei Cheng

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1717-1733; https://doi.org/10.3390/jtaer19030084 - 4 Jul 2024

Viewed by 1089

Abstract

In this study, we use a dataset collected from eBay to analyze buyers’ negative feedback ratings and associated textual comments. By using text mining and sentiment analysis, we identify seven key reasons why buyers post negative ratings: communication problems, shipping issues, product defects, [...] Read more.

In this study, we use a dataset collected from eBay to analyze buyers’ negative feedback ratings and associated textual comments. By using text mining and sentiment analysis, we identify seven key reasons why buyers post negative ratings: communication problems, shipping issues, product defects, payment refund problems, customer service issues, fraud, and product packaging. These seven reasons can be classified into three categories: (1) sellers’ malicious fraudulence toward buyers, (2) factors likely under the control of sellers, and (3) factors not likely under the control of sellers. Drawing on these categories, we discuss how sellers can effectively reduce the likelihood that buyers post negative ratings. The most important things sellers can do to avoid negative ratings are to improve communications with buyers and to handle product shipping issues properly. In addition to posting the reasons for their negative ratings of sellers, the textual comments associated with negative feedback ratings may also include direct denouncements of sellers, such as buyers explicitly claiming a seller is a liar and warning other buyers to be cautious of the seller. We collectively call these actions buyers’ denouncements against sellers. These denouncements have significant negative impacts on sellers’ reputations. In this study, we use correlation analysis and logistic regression to investigate the factors that motivate buyers to denounce sellers. We find that, of the three categories of reasons why buyers post negative ratings, sellers’ malicious fraudulence toward buyers and factors likely under the control of sellers are more likely to lead to buyers’ denouncements of sellers, while factors not likely under the control of sellers are not likely to lead to buyers’ denouncements of sellers. In addition, buyers’ strong negative sentiment is also more likely to lead to their denouncement of sellers. Managerial implications of these findings are discussed. Full article

(This article belongs to the Section Digital Marketing and the Connected Consumer)

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18 pages, 913 KiB

Open AccessArticle

Determinants of Digitalization in Unorganized Localized Neighborhood Retail Outlets in India

by Biplab Bhattacharjee, Shubham Kumar, Piyush Verma and Moinak Maiti

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1699-1716; https://doi.org/10.3390/jtaer19030083 - 1 Jul 2024

Viewed by 773

Abstract

The increase in digital disruptions and changing preferences of different stakeholders has led to digital adoption in all hierarchies of business ecosystem. This study focused on the identification of the determinants of digitalization in unorganized small, localized retail outlets (Kirana stores) of an [...] Read more.

The increase in digital disruptions and changing preferences of different stakeholders has led to digital adoption in all hierarchies of business ecosystem. This study focused on the identification of the determinants of digitalization in unorganized small, localized retail outlets (Kirana stores) of an emerging economy. A theoretical model was constructed with certain modifications based on technology adoption models such as Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to study the impact on business performance in general and as an effect of pandemic. A survey of 285 Unorganized Localized Retail Outlets Stores from different regions of India was used to validate this theoretical model, and structural equation modeling was then further employed. The findings underscore that cost, compatibility, perceived ease of use, and perceived usefulness significantly affect the intention to digitalize. By addressing the post-pandemic impact of digitalization within an unorganized sector in an emerging economy, this study adds to the scant literature that exists in this context. Full article

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17 pages, 1117 KiB

Open AccessArticle

“Will You Buy It If They Recommend It?” Exploring the Antecedents of Intention to Purchase Podcaster-Endorsed Items

by Yi-Ting Huang and An-Di Gong

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1682-1698; https://doi.org/10.3390/jtaer19030082 - 1 Jul 2024

Viewed by 448

Abstract

The diverse content of and ease of listening to podcasts have made podcasts popular, particularly during the COVID-19 pandemic. Advertisers have begun to recognize their marketing potential and are now hiring podcasters to recommend their products. This study sought to determine the factors [...] Read more.

The diverse content of and ease of listening to podcasts have made podcasts popular, particularly during the COVID-19 pandemic. Advertisers have begun to recognize their marketing potential and are now hiring podcasters to recommend their products. This study sought to determine the factors influencing podcast commitment, parasocial interaction (PSI), and the intention to purchase podcaster-endorsed items. It was conducted in Taiwan with a sample size of 578 participants and an online questionnaire. Structural equation modeling and mediation analysis were applied to the collected data from the perspective of uses and gratifications theory. We found that podcast commitment is positively related to edutainment, storytelling transportation, and social engagement. Social engagement is positively related to PSI, while storytelling transportation has a negative relationship with PSI. Additionally, there is a strong positive correlation between podcast commitment and PSI and both factors positively influence the intention to purchase podcaster-endorsed items. PSI also significantly moderates the positive relationship between podcast commitment and the intent to buy podcaster-endorsed items. Full article

(This article belongs to the Section Digital Marketing and the Connected Consumer)

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22 pages, 2997 KiB

Open AccessArticle

Analyzing the Dynamics of Customer Behavior: A New Perspective on Personalized Marketing through Counterfactual Analysis

by Mona Ebadi Jalal and Adel Elmaghraby

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1660-1681; https://doi.org/10.3390/jtaer19030081 - 27 Jun 2024

Viewed by 598

Abstract

The existing body of research on dynamic customer segmentation has primarily focused on segment-level customer purchasing behavior (CPB) analysis to tailor marketing strategies for distinct customer groups. However, these approaches often lack the granularity required for personalized marketing at the individual level. Moreover, [...] Read more.

The existing body of research on dynamic customer segmentation has primarily focused on segment-level customer purchasing behavior (CPB) analysis to tailor marketing strategies for distinct customer groups. However, these approaches often lack the granularity required for personalized marketing at the individual level. Moreover, the analysis of customer transitions between different groups has largely been overlooked. This study addresses these gaps by developing an efficient framework that enables businesses to forecast customer behavior, assess the impact of various strategies on each customer separately, and analyze customer transition between segments. This can facilitate providing personalized marketing strategies, fostering a gradual transition toward a desired customer status, and enhancing the overall marketing precision. In this study, we employ time series feature vectors encompassing recency, frequency, monetary value, and lifespan, applying the K-means algorithm with a range of distance metrics for customer segmentation along with classification algorithms to predict customer behavior. Leveraging counterfactual analysis, we establish a solution for analyzing customer transitions between groups and evaluating personalized marketing strategies. Our findings underscore the superior performance of the Euclidean distance metric, closely followed by the Manhattan distance, in distinguishing the patterns in time series customer behavior, with logistic regression excelling in predicting customer status. This study enables decision-makers to forecast the impact of diverse marketing strategies on customer behavior which facilitates customer retention and engagement through well-informed decisions. Full article

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23 pages, 1932 KiB

Open AccessArticle

Is Smarter Better? A Moral Judgment Perspective on Consumer Attitudes about Different Types of AI Services

by Qingji Fan, Yan Dai and Xue Wen

J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 1637-1659; https://doi.org/10.3390/jtaer19030080 - 27 Jun 2024

Viewed by 603

Abstract

AI is considered a key driver of industrial transformation and a strategic technology that will shape future development. With AI services continuing to permeate various sectors, concerns have emerged about the ethics of AI. This study investigates the effects of different types of [...] Read more.

AI is considered a key driver of industrial transformation and a strategic technology that will shape future development. With AI services continuing to permeate various sectors, concerns have emerged about the ethics of AI. This study investigates the effects of different types of AI services (mechanical, thinking, and affective AI services) on consumers’ attitudes through offline and online AI service experiments. We also construct a model to explore the mediating roles of identity threat and perceived control. The findings reveal that mechanical AI services negatively affect consumers’ attitudes while thinking and affective AI services have a positive effect. Additionally, we explore how consumers’ attitudes vary across different service scenarios and ethical judgments (utilitarianism and deontology). Our findings could offer practical guidance for enterprises providing AI services. Full article

(This article belongs to the Topic Consumer Psychology and Business Applications)

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J. Theor. Appl. Electron. Commer. Res., Volume 19, Issue 3 (September 2024) – 21 articles

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