Online Shopping Research Articles

The Impact of Different Types of Short Video-Linked Advertisements on Consumer Avoidance Behavior: A Case Study of Douyin Advertisements

With the rapid growth of the Internet, short videos have become increasingly significant in the advertising industry. Advertising linked to short videos has progressively emerged as a primary marketing strategy. However, certain categories of customers cannot be accurately targeted with advertisements, leading to dissatisfaction among some viewers of short videos. Consequently, ads associated with videos often result in consumer avoidance behavior. This article investigates and analyzes the impact of different types of short video-linked advertisements on consumer avoidance behavior, drawing on a variety of previous studies. The findings highlight the demographic traits and behaviors of consumers who tend to avoid product-related marketing in short videos. In an effort to address this issue, the study also provides comprehensive solutions and strategies to mitigate consumer avoidance and improve the effectiveness of short video advertisements. Moreover, the growth of online shopping has influenced consumer behavior and preferences, further emphasizing the need for effective advertisement strategies. By understanding the factors that contribute to ad avoidance and tailoring advertisements to meet consumer needs better, advertisers can enhance viewer satisfaction and engagement. This research contributes to the broader understanding of advertising dynamics in the digital age and offers practical insights for marketers aiming to optimize their short video advertising campaigns.

Analysis of the Digital Transformation Path of Chinese E-commerce Companies

Digital technology has revolutionized China’s e-commerce sector, changing company operations and client relationships. This article analyzes the impact of digital transformation on online purchasing patterns. This article concentrated on the important of cloud computing, AI, and big data have become essential to online retail tactics. Digitalization is fueling economic development and innovation in China as its digital economy grows and impacts GDP. Digital technologies enable e-commerce and other industrial sectors to interact easily, improving operational efficiency and market reach. Moving from isolated firm models to connected platforms is a sign of a more responsive and integrated economy. This integration fosters a value model of co-creation in which stakeholders (including companies) collaborate to develop product and service offerings, improving customer experience and operational productivity. The route to digital maturity is not without challenges. E-commerce companies struggle with inefficient logistics, costly digital transformation, and a dearth of competent digital workers, as this study shows. Companies must make dramatic organizational and technological adjustments to overcome these constraints and maximize digital technologies. The analysis concludes that China’s e-commerce market will depend on enterprises’ digital adoption. E-commerce enterprises must embrace ongoing learning and development and remove digital integration barriers to compete in today’s dynamic online industry. The study illuminates digital transformation and how it will impact e-commerce.

ANALYSIS OF CONSUMER BEHAVIOR IN SHOPPING CHANNEL PREFERENCES IN A DUAL CHANNEL SUPPLY CHAIN STRUCTURE

Physical stores and online stores are one way that companies can continue to survive amidst competition by increasing profits from these two channels. Clothing is one of the textile commodities that is widely traded through physical stores and also online stores. This research identifies the factors that have the most significant influence on consumer preferences in choosing physical stores or online stores. Determining the factors involved adopts the results of previously conducted research. Based on existing research, there are several factors, namely Financial Risk (FR), Performance Risk (PerR), Psychological Risk (PsyR), Perceived Risk (PR), Environment Quality (EQ), Service Quality (SQ), Internet Experience (IE ), and Switching Intention (SI). From these variables, 8 hypotheses were formed. All hypotheses from the model were processed using Structural Equation Modeling with SmartPLS 3 software, it was found that H1, H2, H3, H4, H5, and H7 were accepted. H6 and H8 are rejected.

Research on the Development of Logistics Performance of E-Commerce Enterprises and its Influencing Mechanism on Customer Satisfaction

With the booming development of e-commerce industry, logistics performance has become one of the key factors of competitiveness for e-commerce enterprises, directly related to the customer satisfaction and market position of the enterprises. Under the background of digitalization and intelligentization, online shopping has become one of the main ways of daily shopping for consumers. As an important link in the transaction chain of e-commerce, logistics efficiency and quality directly affect the shopping experience and loyalty of consumers. This paper conducts an in-depth analysis of the current situation of logistics performance of e-commerce enterprises, the mechanism analysis of how it affects customer satisfaction, and explores solutions to the problem. Through the mechanism analysis, it is found that e-commerce enterprises can improve logistics performance by enhancing logistics speed, improving logistics service quality, reducing costs and increasing efficiency, strengthening green logistics, and enhancing cross-border e-commerce logistics capabilities. This can improve customer satisfaction, and the paper proposes suggestions such as optimizing logistics networks, enhancing logistics service training, fine-tuning management, promoting environmentally friendly packaging, optimizing transportation methods, and improving cross-border e-commerce logistics networks.

Business and Customer-Based Chatbot Activities: The Role of Customer Satisfaction in Online Purchase Intention and Intention to Reuse Chatbots

In the online shopping context, brands aim to achieve a high level of profit by providing better customer satisfaction by using various artificial intelligence tools. They try creating a satisfactory customer experience by creating a system that provides never-ending customer support by using dialog-based chatbots, especially in the field of customer service. However, there is a lack of research investigating the impact of business and customer-based chatbot activities together on online purchase intention and the intention to reuse chatbots. This research considers the use of chatbots as a marketing tool from both customer and business perspectives and aims to determine the factors that affect the customers’ intention to purchase online and reuse chatbots. Accordingly, the impact on customer satisfaction with chatbot usage, which is based on chatbots’ communication quality and customers’ motivations to use chatbots, on online purchase intention and intention to reuse chatbots was examined. Through an online questionnaire with two hundred and ten participants, employing structural equation modeling, we revealed that customer satisfaction with chatbot usage has a greater impact on the intention to reuse chatbots than on online purchase intentions. In addition, chatbot communication quality has a greater impact on customer satisfaction with chatbot usage than customers’ motivation to use chatbots. To solidify these findings, confirmatory factor analysis, along with reliability and validity assessments, were implemented within the analytical framework to provide robust support for the study’s hypotheses. These findings not only provide empirical evidence and implications for companies in online shopping but also extend the understanding of AI tools in marketing, highlighting their subtle impact on consumer decision-making in the dynamic digital marketplace.

Miracle in the evening: Explaining the boundary condition of consumer's self-control on purchase intention of near-expired products

Due to consumers' misunderstanding of product expiration dates, huge amounts of food waste and retail losses have been recognized as a worldwide problem. This research explores a solution to mitigate such waste and losses in the consumer purchase decision-making process of near-expiry products. Drawing from the literature on expiration date-based pricing (EDBP) and self-control, we propose that consumers' purchase intention for near-expiry products vary depending on the time of day (morning vs. evening). The results from mixed methodologies, including an analysis of actual sales data from an online retailer (Study 1) and randomized controlled experimental studies (Studies 2 and 3), reveal that consumers are less sensitive to near-expiry products when purchasing EDBP products in the evening compared to the morning. Furthermore, we examine how self-control mediates the interaction effects of the nearness of the expiration date and the time of day on the purchase intention of near-expiry EDBP products. A novel perspective on understanding consumers’ dynamic evaluations of sales promotions over time and managerial implications for promotional strategies to promote products approaching their expiration date are discussed.

Leveraging Artificial Intelligence in Supply Chain Execution in E-commerce

Modern perspective of consumer satisfaction has changed due to the proliferation of online businesses. E-commerce has opened up a whole new world to the consumers. The consumers can now get what they want, when they want, delivered at their doorstep. While the ease of online shopping has increased consumerism and consumer demand, it poses significant challenges for the e-commerce players as the consumers are seldom willing to shell out money for availing the convenience of doorstep deliveries. Under such circumstances, the e-commerce players are left with little choices but to significantly enhance their supply chain efficiencies through the improvement of logistics and the delivery services they offer to their customers. Artificial Intelligence or AI, as it is popularly known, is altering the ways and means of these e-commerce businesses. It is changing the manner in which supply chains are managed. Through the use of smart algorithms, data analysis, and automation, it is possible for businesses to employ AI effectively for the optimization of their supply chain management involving inventory and logistics management, demand forecasting, and customer service. This article focuses on logistics management and the application of AI to optimize costs and efficiency in first mile, middle mile and last mile delivery.

Interactivity, humanness, and trust: a psychological approach to AI chatbot adoption in e-commerce

This study aims to investigate the impact of interactivity and perceived humanness on trust toward AI chatbots in the e-commerce setting. Moreover, this study also aims to examine the mediation effect of trust toward AI chatbots in the relationship between interactivity and intention to adopt AI chatbots for e-commerce as well as in the relationship between perceived humanness and intention to adopt chatbots for e-commerce. This study used a time lag approach to collect the data from 343 customers from the southern region of China. The data were collected online through a questionnaire designed in Chinese language using a survey firm. The findings of this study indicated that there is a significant impact of interactivity and humanness on the trust toward chatbots. Moreover, the findings of this study indicated that there is a significant mediating effect of trust toward chatbots in the relationships of interactivity and perceived humanness to adopt chatbots for e-commerce. In addition, this study found a significant moderating influence on the perceived enjoyment of using chatbots in e-commerce settings. This study provides a unique perspective of expectation-confirmation theory for adopting emerging technologies for online shopping and also provides insights for designers and business firms to develop businesses to facilitate the AI chatbot feature for e-commerce.

Commercialized “Smudge Sticks” Used as Incense in the Netherlands: An Inventory of Plants and Trends Behind a New Age Fashion

Incense is essential in religious ceremonies, even in relatively new religious and spiritual movements such as New Age and Neopaganism. These garner little attention from ethnobotanists, although they trigger an international trade in wild-harvested plants. In this paper, we studied the botanical ingredients of smudge sticks (dried plant bundles burned for purification) in the Netherlands, and people’s motivations to use them posing the following questions: what plant species are included in smudge sticks? what are they used for? and are exotic plants preferred over native Dutch plant species? We visited online and physical shops in Dutch cities, acquiring a total of 29 different smudge sticks containing at least 15 species. We held semi-structured interviews with 11 users, vendors, and herbal experts, and collected data from 33 questionnaires. Salvia apiana L. was most frequently found, along with North American species of the genus Artemisia. The rise of the New Age movement resulted in North American ritual plant species being easily available in (online) shops in the Netherlands and smudge sticks being used for personal protection and cleansing. Despite the smudge sticks’ commercial demand, there is no data regarding the pressure on wild populations of species used in these bundles. For the preservation of these species it is crucial that scientific monitoring of their harvest is undertaken in the future.

Understanding Gen Z’s Online Purchase Behavior through their Hedonic and Utilitarian Motivation

The COVID-19 pandemic ushered in lockdowns, limiting consumer movement to their homes and preventing consumers from shopping in brick-and-mortar stores. Consequently, consumers were reliant on e-commerce to manage their daily purchases of goods and services. This exacerbated the use of e-commerce and fast-tracked the growth of the digital economy. In this study, Gen Z’s consumer motivation is investigated using hedonic and utilitarian motivation and the Unified Theory of Acceptance and Use of Technology (UTAUT). Consumer motivation remains a crucial part of consumer behavior studies given its prominence in influencing consumer action, consumer decision-making and preferences. In particular, the effects of hedonic and utilitarian motivation on online purchase behavior were investigated. This study utilized a quantitative approach through the deployment of a survey questionnaire online. The data from 156 respondents was analyzed using SmartPLS 4.0 utilizing Partial-Least Squares Structural Equation Modelling. Approximately 44% of the respondents started shopping online for the first time during the pandemic (i.e., 2020 and 2022). The results indicated that the Gen Z respondents were motivated by utilitarian and hedonic motivation when shopping online, in particular by Idea Shopping motivation and Efficiency motivation. Additionally, Social Influence and Facilitating Conditions were significant factors in influencing Behavioural Intention, and Behavioural Intention influenced Purchase Behaviour. The evidence suggests that the respondents were not novice online shoppers but rather experienced online shoppers.

Exploring E-Customer Satisfaction Using e-SERVQUAL Among Online Shoppers

When interacting with a company's products and services, customer satisfaction is an overall feeling of contentment that a client is experiencing. Previous studies have shown an increase in revenue when a company prioritizes customer satisfaction with its products or services. Around 70 percent of Malaysians are dynamic online consumers, with most of them shopping via websites. e-SERVQUAL assesses the efficacy and efficiency of a website in facilitating shopping, purchase, and delivery processes. It encompasses the pre-purchase and post-purchase phases. The e-SERVQUAL dimensions (privacy, website design, responsiveness, reliability, usability, and information quality) are elements that impact e-customer satisfaction. A total of 100 respondents at Bandar Utama City Centre who shop online participated in the survey. According to the data, males outnumber females among the respondents. The survey comprised three sections: A, B, and C. Section A comprised the demographic information of the respondents, Section B concentrated on the e-SERVQUAL aspects, and Section C addressed e-customer satisfaction. The data was examined utilizing the Statistical Package for the Social Sciences (SPSS). The results indicated that the majority of respondents expressed satisfaction with the quality. However, website design improvements should be made to encourage more online shopping. The recommendation in this study is beneficial to online service providers and future studies on e-SERVQUAL should be extended to another dimension to explore more aspects of determining quality service in an online setting.

Digital Disruption in Indian Retail: Trends, Opportunities, And Challenges

This research paper examines the significant growth and transformation of the Indian Retail Industry, now ranked as the fifth-largest globally. This expansion is driven by rising incomes, shifting middle-class lifestyles, and improved digital connectivity. In this competitive environment, Indian consumers increasingly demand personalized and exceptional services. Digital transformation is identified as a key success factor, enabling retailers to adapt to changing customer behaviors. The surge in online shopping, propelled by smartphone usage, has reshaped the consumer-retailer dynamic, necessitating robust online presences and investments in data analytics for better customer insights. Transparency in supply chains and real-time inventory management have become essential for effective retail operations. The paper highlights key digital transformation trends, such as digitized in-store experiences and workforce empowerment, while acknowledging challenges like change management, skill shortages, and data security risks. Retailers are advised to implement change management strategies, develop talent acquisition plans, and invest in cybersecurity to ensure sustainable growth.

Unified Cart Systems: A Paradigm Shift in E-commerce User Experience

This article examines the impact of unified cart systems on e-commerce platforms, focusing on their role in enhancing user experience and driving business performance. Unified cart systems, which enable customers to purchase products across multiple categories in a single transaction, represent a significant innovation in e-commerce. Through a comprehensive analysis of existing literature and industry case studies, this article explores the benefits of unified cart systems, including seamless customer experiences, increased conversion rates, and improved cross-selling opportunities. The article also addresses the challenges in implementing these systems, such as integration complexity and security concerns, and proposes best practices for successful deployment. Our findings suggest that unified cart systems can significantly improve e-commerce performance metrics and provide a competitive advantage in the digital marketplace. This article contributes to the growing body of literature on e-commerce innovations and provides practical insights for businesses looking to optimize their online retail strategies.

Conceptualizing the Implications of Artificial Intelligence (AI) Tools and Personalization Marketing on Consumer Purchase Intention: Insights from the Malaysian E-Commerce Market

Artificial intelligence (AI) has emerged as a powerful tool, enabling online retailers to offer highly personalized shopping experiences tailored to individual preferences and behaviors. As e-commerce continues to grow in Malaysia, understanding the influence of AI and personalization marketing on consumer purchase intentions has become increasingly important for businesses seeking to remain competitive. However, the rapid adoption of AI also raises concerns about data privacy, ethical AI usage, and compliance with emerging data protection regulations, such as Malaysia’s Personal Data Protection Act (PDPA). This study aims to explore the potential impact of artificial intelligence (AI) and personalization marketing on consumer purchase intention within the Malaysian e-commerce market. By reviewing previous literature and theoretical frameworks, the study explores how the use of AI tools including predictive analytics automation, and personalization experiences might influence consumer behavior in online shopping environments. The study adopts a quantitative approach, in which quota sampling will be used for the participant selection. A self-administered questionnaire with a five-point Likert scale will be employed to gather data from e-commerce users in Malaysia. The findings from this study have important implications for both e-commerce businesses and policymakers in Malaysia. For businesses, understanding which aspects of AI and personalization most influence consumer purchase intentions can help them strategically implement these technologies to enhance customer engagement and drive sales. For policymakers, the study highlights the need to consider ethical and legal issues, such as data privacy and policy issues, in the growing use of AI in the e-commerce market.

Predicting user behavior on s-commerce platforms: a novel model

PurposeThis study investigates the influence of the wisdom of the crowd (WSC), trust and perceived value on consumer purchase intentions within social commerce (s-commerce) platforms. By constructing a novel theoretical model, the research aims to delineate the interrelationships among these variables, addressing an emerging area in social interactions and information technology.Design/methodology/approachTo empirically test and validate the proposed model, the study collected data from 442 Facebook users familiar with online shopping. The analysis employed Structural Equation Modeling – Partial Least Squares (SEM-PLS) to test the hypotheses and examine the relationships between WSC, trust, perceived value and purchase intentions.FindingsThe findings confirm that WSC significantly influences trust, perceived value and the intention to purchase on s-commerce platforms. Both perceived value and trust are substantial determinants of purchase intentions. Notably, the PLS analysis revealed that WSC accounts for 36.8% of the variance in trust and 33.1% of the variance in perceived value related to purchasing decisions on s-commerce platforms.Originality/valueThis research contributes uniquely to the ongoing discourse on s-commerce adoption by integrating WSC as a pivotal factor in understanding perceived value and consumer adoption intentions. It provides a fresh perspective on how collective intelligence affects consumer behavior in digital marketplaces, enriching the theoretical and practical understanding of s-commerce dynamics.

Factors Influencing Customers’ Online Shopping Behavior in Malaysia During the COVID-19 Pandemic

The article presents an overview of the arguments and rebuttals made in the scientific discourse regarding Malaysia's expanding online shopping trend, particularly in light of the COVID-19 epidemic. This scientific decision is significant since the widespread usage of COVID-19 has altered consumer purchasing behavior and how firms operate globally by reducing potential risks such as making the wrong purchase or falling prey to online fraud. This study aims to determine the impact of perceived risk, trust, and product diversity on consumers' decisions to purchase things online in Malaysia's Klang Valley. The study utilized a quantitative survey methodology, selecting 327 sample sizes from a targeted demographic of online shoppers using Krejcie and Morgan tables. SPSS was used for descriptive and inferential analyses. The study found that product variety, trust, and perceived risk significantly predict consumers' online buying behavior in Malaysia during the COVID-19 pandemic. Trust and product variety moderately influence online purchasing, while perceived risk has a negative impact. In contrast to perceived risk (standardized coefficient = -.252), which has a negative and moderate impact, the results indicate that product variety (standardized coefficient =.571) and trust (standardized coefficient =.461) have an average influence on customers' online purchase behaviors. The study supports all hypotheses (H1, H2, and H3), indicating that trust, perceived risk, and product variety significantly influence consumers' online purchasing behaviors in Malaysia during the COVID-19 pandemic. The study emphasizes the need for a comprehensive understanding of online consumer factors and their implications for e-commerce vendors, suggesting the inclusion of marketing professionals in marketing strategy formulation.

Product recommendation for online sales systems based on transaction sessions

The advancement of information technology has influenced and accelerated the growth of many economic fields and industries, including e-commerce. This is one area of information technology that has rapidly developed and gained widespread popularity due to the significant benefits it offers to the community. Today, the need for online shopping is increasing because of its convenience and timesaving, especially for busy people. Historical session data plays an important role in helping sales systems recommend orders to customers that suit their personal preferences. This study proposes models for recommending products on online sales systems based on transaction sessions using memory-based collaborative filtering methods, including user-based and item-based, and model-based collaborative filtering methods including SVD and KNN. The experimental results show that the SVD model has a better rating prediction performance than other techniques. Therefore, it is probably proposed for product recommendations on online sales systems.

Channel structures of third-party platforms

The growing prominence of third-party (3P) platforms in the online retail sector has made the selection of an appropriate channel structure strategy a critical concern for manufacturers, 3P platforms, and retailers operating within this environment. We construct a Stackelberg game model with the manufacturer as the leader, evaluating four channel structures: (A) reselling and retailer agency selling, (B) agency selling and retailer agency selling, (C) reselling and agency selling, and (D) reselling, agency selling, and retailer agency selling. The supply chain can adopt two pricing strategies: uniform pricing (UP) and differential pricing (DP). Research indicates that expanding the number of channels may not always enhance profitability for suppliers and supply chain participants. Under strategy UP, the 3P platform opts for structure B, whereas the retailer favors structure C. Incorporating agency selling is advantageous for the manufacturer; however, structure A represents the least beneficial option for the supply chain. Under strategy DP, a substantial portion of the pareto optimal region is present. Intense competition and reduced agency fees lead both the supply chain as a whole and individual member to prefer structure A. The addition of a reselling or retailer agency channel boosts the manufacturer's profits, and benefits the 3P platform, while structure D emerges as the least favorable option for the retailer. Furthermore, under strategy DP, structure C is rendered obsolete, signifying the retailer's essential role in the supply chain to the advantage of all involved parties. Our study advances the scholarly understanding of sales models and platform economies by offering valuable insights into the decision-making processes of manufacturers, third-party (3P) platforms, and retailers regarding channel structure choices in a 3P platform environment.

Multi-Channel Supply Chains Considering Live Streaming Sales and Spillover Effects

Abstract: With the rapid development of e-commerce, an increasing number of companies, such as Huawei, Apple, and Adidas, are no longer confined to offline physical stores for product sales. They leverage third-party e-commerce platforms or establish online stores on their official websites. Modern consumers have access to various purchasing channels, including e-commerce platforms, offline stores, and manufacturer direct sales. In recent years, a new e-commerce model, live streaming sales, has emerged. In live streaming sales, professional salespersons or key opinion leaders (KOLs) showcase product performance, aiming to sell products online. Unlike traditional online channels, live streaming sales alleviate new consumers' uncertainty about product information through real-time interaction or comments from KOLs. Live streaming has been adopted by e-commerce giants worldwide, such as Taobao, JD.com, and Amazon, due to its significant sales revenue potential. Additionally, channels with KOLs may generate negative or positive spillover effects on other channels. These effects are crucial parameters for exploring the impact of seller profits in the multi-channel supply chain under live streaming conditions. Both domestic and international research have focused on live streaming sales, multi-channel sales, and spillover effects, with many studies yielding significant economic and social benefits. However, challenges faced by multi-channel supply chains, including complex channel management, difficulty in information synchronization, brand consistency issues, and increased costs, need to be addressed. To overcome these challenges, recommendations include integrating channel resources, optimizing channel experience, establishing cross-channel data analysis systems, strengthening supply chain coordination, continuous innovation and improvement, and strengthening brand building.

‘There’s Nothing Strange’: Language Policy and Racialisation at Warehouse Workplaces

ABSTRACT Sweden is a country where racial/ethnic power relations reflect and reinforce the marginalisation of groups of people. Research has shown that language makes part of such racialised processes through makings of the Swedish language into the norm and a consequent stigmatisation of the ‘non-Swedish’ others. This article explores the role of language in racialisation at the workplace level of online retail warehousing. The empirical material comprises interviews (n = 24) and focus groups (n = 15 groups, tot. of 49 participants) with managers, team leaders, and workers at three online retail warehouses in Sweden, with an emphasis on the perceptions of a Swedish language policy that had been implemented in one of the warehouses. The policy had been implemented to promote inclusion and to create opportunities for workers whose primary language was not Swedish. The article shows that the language policy can be understood as racialising, even though that was not its purpose.