JTAER, Vol. 18, Pages 2163-2187: COVID-19 and Supply Chain Disruption Management: A Behavioural Economics Perspective and Future Research Direction

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18040109

Authors: Chase Smith Hajar Fatorachian

The COVID-19 pandemic has been one of the most severe disruptions to normal life, impacting how businesses operate. The academic literature in the areas of supply chain and operations management has been trying to explain how this has affected decision-making in businesses. However, the existing literature has predominantly overlooked organisational culture and behavioural economic theories. This paper contends that considering the decisions made in supply chain disruption management involve groups and the individuals within them, the relevance of behavioural economic concepts becomes paramount. As such, the objective of this paper is to conduct an integrative literature review, utilising the purposive sampling method to explore the dearth of academic work connecting behavioural economic theories and organisational culture to supply chain disruption management. Additionally, the paper aims to offer guidelines for future research in this domain. Enhancing our comprehension of these domains concerning supply chain disruption management would empower firms to better anticipate their parties’ decisions, refine their decision-making models, and cultivate stronger relationships with suppliers and customers.

JTAER, Vol. 18, Pages 2142-2162: Enhancing Traceability in Wine Supply Chains through Blockchain: A Stackelberg Game-Theoretical Analysis

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18040108

Authors: Yuxuan Kang Xianliang Shi Xiongping Yue Weijian Zhang Samuel Shuai Liu

Blockchain technology has been adopted to improve traceability and authenticity in wine supply chains (WSCs). However, whether through outsourcing or self-implementation of a blockchain-based wine traceability system (BTS), there are significant costs involved, as well as concerns regarding consumer privacy. Motivated by observations of real-world practice, we explore the value of blockchain in enhancing traceability and authenticity in WSCs through a Stackelberg game-theoretical analysis. By comparing the equilibrium solutions of the scenarios with and without blockchain, we uncover the value of blockchain in tracing wine products. Our findings show that blockchain adoption can increase WSC prices under certain conditions. We derive the threshold for a third-party BTS service fee that determines blockchain adoption for tracing wine products and reveal the moderating effect of consumer traceability preferences and privacy concerns. Furthermore, the investigation of who should lead the implementation of BTS finds that the equal cost sharing between the manufacturer and the retailer results in no difference in BTS implementation leadership. Otherwise, the manufacturer always benefits from taking the lead in the implementation of BTS, and the retailer should undertake a leadership role in BTS implementation if they need to bear higher costs.

JTAER, Vol. 18, Pages 2107-2124: Analysis of Online Platforms’ Free Trial Strategies for Digital Content Subscription

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18040106

Authors: Li Chen

Adopting subscription models has become a popular trend in e-commerce. Digital content platforms often use free trials to attract potential subscribers. However, rigorous research on platforms’ free trial strategies is lacking. Our paper aims to fill this gap using a horizontal duopoly framework. We investigate both the scenario of market symmetry and of market asymmetry. We study the benchmark case with no free trial for each scenario and derive equilibrium results with free trial promotion. We find that the platform will not benefit from free trials unless consumers’ learning rate exceeds a threshold. When a free trial is introduced in market symmetry, a higher rate of consumers’ learning leads to a higher price of subscription and a shorter free trial length. In addition, when the network effect is incorporated, the platform will introduce a lower subscription price and a shorter free trial length. Under market asymmetry, our results show that the platform faces a higher threshold of consumers’ learning rate. Additionally, it will offer a higher price and a longer period of free trial compared with those under the market symmetry scenario. Overall, our study provides useful managerial insights for online content platforms when considering their subscription strategies.

JTAER, Vol. 18, Pages 2125-2141: Empowering the Online Media System: The Innovative Route of Effective Digital Government Response in China

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18040107

Authors: Zipeng Li Qingguo Meng

Studies on the Chinese government’s online response present diverse voices and perspectives, but consensus cannot be reached. The literature has constantly ignored the construction of an online media mechanism, which includes professional positions and standardized procedures that were designed inside the online media to process information and facilitate an effective government response. Does the reconstruction of an online media mechanism benefit the effectiveness of government response? If so, how? From the perspective of the media mechanism, what are the influential factors for the effectiveness of government response and how do they work to exert this impact? Engaging with the media system dependence theory, I conducted semi-structured, in-depth interviews with the editor at the Beijing Municipal Government Website and official document drafters at prestigious research institutions. In conversation with the political system theory, multinomial logistic regression was used to analyze the daily government response data covering the period from 2019 to 2020. This article argues that the innovations in the mechanism inside the online media system can outsource some information management functions from the political system to the online media system. These innovations also assist in partial power transfer from the political system to the media system to achieve an effective government response. The political system faces dual pressure, including content pressure and time pressure, regarding its online response.

JTAER, Vol. 18, Pages 2092-2106: Investigation of Web-Based Eye-Tracking System Performance under Different Lighting Conditions for Neuromarketing

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18040105

Authors: Doğuş Yüksel

The increasing popularity of neuromarketing has led to the emergence of various measurement methods, such as webcam-based eye-tracking technology. Webcam-based eye-tracking technology is noteworthy not only for its use in laboratories but also for its ability to be applied to participants online in their natural environments through a link. However, the complexity of e-commerce interfaces necessitates high performance in eye-tracking methods. This complexity and the applicability of webcam-based eye-tracking technology in various environments have raised research questions about how its performance changes depending on the type and location of lighting. To answer these questions, experiments were conducted with 30 users in two different experimental environments illuminated by artificial and natural methods, with the lighting from the left, right, and front. Participants were asked to focus on targets located in specially prepared graphics for the experiment. In the heatmaps obtained in the eye-tracking tests, the distance and angular difference between the focal point and the target point were measured using the polar coordinate system. The findings indicate that measurements taken with lighting coming from the center were more efficient in both natural and artificial lighting types and measurements taken under natural lighting performed 24% better than artificial ones. Web camera-based eye-tracking technology is a promising method. However, detailed statistical analyses have demonstrated that for complex interfaces like e-commerce, the position and type of lighting are crucial parameters.

JTAER, Vol. 18, Pages 2077-2091: Individualization in Online Markets: A Generalized Model of Price Discrimination through Learning

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18040104

Authors: Rasha Ahmed

This paper builds a theoretical framework to model individualization in online markets. In a market with consumers of varying levels of demand, a seller offers multiple product bundles and prices. Relative to brick-and-mortar stores, an online seller can use pricing algorithms that can observe a buyer’s online behavior and infer a buyer’s type. I build a generalized model of price discrimination with Bayesian learning where a seller offers different bundles of the product that are sized and priced contingent on the posterior probability that the consumer is of a given type. Bayesian learning allows the seller to individualize product menus over time as new information becomes available. I explain how this strategy differs from first- or second-degree price discrimination models and how Bayesian learning over time affects equilibrium values and welfare.

JTAER, Vol. 18, Pages 2057-2076: Detecting Fraudulent Transactions Using Stacked Autoencoder Kernel ELM Optimized by the Dandelion Algorithm

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18040103

Authors: Fatima Zohra El Hlouli Jamal Riffi Mhamed Sayyouri Mohamed Adnane Mahraz Ali Yahyaouy Khalid El Fazazy Hamid Tairi

The risk of fraudulent activity has significantly increased with the rise in digital payments. To resolve this issue there is a need for reliable real-time fraud detection technologies. This research introduced an innovative method called stacked autoencoder kernel extreme learning machine optimized by the dandelion algorithm (S-AEKELM-DA) to detect fraudulent transactions. The primary objective was to enhance the kernel extreme learning machine (KELM) performance by integrating the dandelion technique into a stacked autoencoder kernel ELM architecture. This study aimed to improve the overall effectiveness of the proposed method in fraud detection by optimizing the regularization parameter (c) and the kernel parameter (σ). To evaluate the S-AEKELM-DA approach; simulations and experiments were conducted using four credit card datasets. The results demonstrated remarkable performance, with our method achieving high accuracy, recall, precision, and F1-score in real time for detecting fraudulent transactions. These findings highlight the effectiveness and reliability of the suggested approach. By incorporating the dandelion algorithm into the S-AEKELM framework, this research advances fraud detection capabilities, thus ensuring the security of digital transactions.

JTAER, Vol. 18, Pages 2007-2032: What Do You Need to Know? A Systematic Review and Research Agenda on Neuromarketing Discipline

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18040101

Authors: Prakash Singh Ibrahim Alhassan Lama Khoshaim

The neuromarketing phenomenon has led to a makeover in the marketing area, and its application in the business world has generated a better insight into understanding diverse consumer behavior. This comprehensive study delves into the multifaceted world of neuromarketing. Employing a systematic literature review approach and reviewing 51 articles from the Web of Science database, the study aims to provide a holistic view of the neuromarketing field, offering valuable insights and directions for future research and practical application in the business and academic world. The key results of this study are classified into six distinct research themes: 1. Evolution of Neuromarketing, 2. Neuromarketing Definitions and Neuromarketing Tools, 3. Neuromarketing in Practice, 4. Social Value of Neuromarketing, 5. Neuromarketing and Consumer Behavior, and 6. Neuromarketing for Sustainable Business Development. The results of the study are based on the 4W framework (What, Where, Why, and How) and the TCCM framework (Themes, Contexts, Characteristics, and Methodology). The study underscores the significance of neuromarketing to businesses and serves as a provocative call to action for businesses to study its potential which traditional marketing techniques may overlook. This study is notable for its investigation of theoretical evolution, definitions, tools, practices, social value, and influence on consumer behavior within the discipline. Its contribution unfolds to sustainable business development, where neuromarketing can facilitate sustainable products and practices by understanding consumer behavior. This study presents valuable insights and sets the stage for future research through theoretical advancements in neuromarketing. It further acts as a foundational resource for marketers and researchers in augmenting their theoretical and practical acumen.

JTAER, Vol. 18, Pages 2033-2056: Integrating Non-Positional Numbering Systems into E-Commerce Platforms: A Novel Approach to Enhance System Fault Tolerance

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18040102

Authors: Victor Krasnobayev Oleksandr Kuznetsov

In the dynamic landscape of electronic commerce, the robustness of platforms is a critical determinant of operational continuity and trustworthiness, necessitating innovative approaches to fault tolerance. This study pioneers an advanced strategy for enhancing fault tolerance in e-commerce systems, utilizing non-positional numbering systems (NPNS) inspired by the mathematical robustness of the Chinese Remainder Theorem (CRT). Traditional systems rely heavily on positional numbering, which, despite its ubiquity, harbors limitations in flexibility and resilience against computational errors and system faults. In contrast, NPNS, characterized by their independence, equitability, and residue independence, introduce a transformative potential for system architecture, significantly increasing resistance to disruptions and computational inaccuracies. Our discourse extends beyond theoretical implications, delving into practical applications within contemporary e-commerce platforms. We introduce and elaborate on new terminologies, concepts, and a sophisticated classification system for fault-tolerance mechanisms within the framework of NPNS. This nuanced approach not only consolidates understanding but also identifies underexplored pathways for resilience in digital commerce infrastructure. Furthermore, this research highlights the empirical significance of adopting NPNS, offering a methodologically sound and innovative avenue to safeguard against system vulnerabilities. By integrating NPNS, platforms can achieve enhanced levels of redundancy and fault tolerance, essential for maintaining operational integrity in the face of unforeseen system failures. This integration signals a paradigm shift, emphasizing proactive fault mitigation strategies over reactive measures. Conclusively, this study serves as a seminal reference point for subsequent scholarly endeavors, advocating for a shift towards NPNS in e-commerce platforms. The practical adaptations suggested herein are poised to redefine stakeholders’ approach to system reliability, instigating a new era of confidence in e-commerce engagements.

JTAER, Vol. 18, Pages 1990-2006: Achieving Sales Forecasting with Higher Accuracy and Efficiency: A New Model Based on Modified Transformer

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18040100

Authors: Qianying Li Mingyang Yu

With the exponential expansion of e-commerce, an immense volume of historical sales data has been generated and amassed. This influx of data has created an opportunity for more accurate sales forecasting. While various sales forecasting methods and models have been applied in practice, existing ones often struggle to fully harness sales data and manage significant fluctuations. As a result, they frequently fail to make accurate predictions, falling short of meeting enterprise needs. Therefore, it is imperative to explore new models to enhance the accuracy and efficiency of sales forecasting. In this paper, we introduce a model tailored for sales forecasting based on a Transformer with encoder–decoder architecture and multi-head attention mechanisms. We have made specific modifications to the standard Transformer model, such as removing the Softmax layer in the last layer and adapting input embedding, position encoding, and feedforward network components to align with the unique characteristics of sales forecast data and the specific requirements of sales forecasting. The multi-head attention mechanism in our proposed model can directly compute the dot product results in a single step, addressing long-term time-dependent computation challenges while maintaining lower time complexity and greater interpretability. This enhancement significantly contributes to improving the model’s accuracy and efficiency. Furthermore, we provide a comprehensive formula representation of the model for the first time, facilitating better understanding and implementation. We conducted experiments using sales datasets that incorporate various factors influencing sales forecasts, such as seasons, holidays, and promotions. The results demonstrate that our proposed model significantly outperforms seven selected benchmark methods, reducing RMSLE, RMSWLE, NWRMSLE, and RMALE by approximately 48.2%, 48.5%, 45.2, and 63.0%, respectively. Additionally, ablation experiments on the multi-head attention and the number of encoder–decoders validate the rationality of our chosen model parameters.