J. Theor. Appl. Electron. Commer. Res., Volume 17, Issue 3 (September 2022) – 18 articles

Many manufacturers and retailers have already opened online stores to sell their products. Thus, manufacturers are competing as sellers, and retailers are transforming into dual-channel retailers (DCRs). Such an expansion in business scope and the wide spread of lenient return policies trigger tremendous return volume that requires great deal of logistical efforts. The service levels offered within online stores greatly affect channels’ demand. However, they also influence the channel choice of return for online customers, if applicable, when their purchases are unsatisfactory. Therefore, this paper studies the optimal service level for a centralized DCR. In addition, it examines the optimal levels for a decentralized two-echelon system through the implementation of Nash and Stackelberg theoretical frameworks. Important properties of optimal solutions and vital managerial insights have been devised through analytical and sensitivity analysis. It is found that a DCR may have the following tradeoff: decrease service level to increase the reward from the physical store or increase service level to enhance competitiveness of the online store. The optimal decision depends greatly on how sensitive the customers’ return behavior is to service level. In addition, as the exogenous price increases, the change in the retailer’s offered level depends significantly on the different rates of return. Full article

Online markets offer sellers access to buyers’ information and, thus, the potential to alter prices and products accordingly. In light of this, we undertook an empirical analysis to test for individualization on Amazon.com. We collect data from individuals recruited to shop for household items. Our results indicate evidence of individualization of search results and net prices (via coupons). We found, contrary to what was expected, that demographic, geolocation, and account information play an insignificant role in individualization of search results. Thus, we conclude that individualization is based on more dynamic information, e.g., online browsing behavior. This highlights the fact that sellers’ need for (and use of) buyer information goes beyond the simple information accessible from the buyers’ accounts to a more rigorous monitoring of buyers’ online behavior. Full article

With the rapid development of the retail industry and its transition to omni-channel, a critical challenge that how to fulfill customer orders by choosing the proper channels arises for the retailers. In omni-channel retailing, customers can make a purchase online or offline, and the online customers are offered the options of home delivery or collection at a specified store, delivering immediately or during an appointed time window, and accepting split delivery or not. For the effective execution of omni-channel retailing in such a circumstance, this paper proposes an intuitive order fulfillment policy, aiming to gain lower service cost and higher customer satisfaction, as a reference for the retailers’ operation management. Via experimental analyses under various service costs and demand forecasts, their influences on channel selection and the policy performance are illustrated. Furthermore, the comparison of the performances of the omni-channel with independent channels quantitatively reveals one crucial reason for the surge of omni-channel. Full article

In recent years, the relationship between digital transformation and innovation became very popular topics, attracting extensive attention, and inspiring a number of documents. Although much literature discusses the intersection of both fields, most works offer neither a complete nor a truly objective overview of the current state of research. Therefore, there is a need for a comprehensive and objective review of research themes to analyze the intersection. For this purpose, based on the literature collected from the Web of Science (WoS) database published between 1994 and 2021, co-word analysis was carried out to explore research themes and identify the most salient themes in digital transformation and innovation research. The results of scientific output show that digital transformation and innovation is attracting increasing academic interest of scholars from many countries and different fields. The distribution of high-frequency keywords shows that the research in this field is multidisciplinary, including not only many economic and management fields, but also many classical theories and research methods. The clustering results of keywords reveal five clusters of themes: diffusion and adoption of technology and innovation, digital innovation management, digital transformation management, digital platform and ecosystem, and digital entrepreneurship and economy. According to the results of strategic diagram and performance analysis, digital innovation management and digital transformation management are the mainstream of research, while digital platform and ecosystem and digital entrepreneurship and economy have strong development potential. This study provides a snapshot of the thematic development of digital transformation and innovation research, enabling researchers to better master the current situation and suggesting the development trend in the future. Full article

A plethora of studies have examined the emerging technology of blockchain and its applications in accounting, management, and enterprise resource planning systems (ERPs). Blockchain technology (BT) can change the architecture of today’s ERPs and overcome the limitations of these centralized systems. The aim of this study is twofold. First, this paper defines and analyzes the deployment of an innovative architecture of a Blockchain as an Ecosystem (BaaE) platform proposing a conceptual model of the Triple Entry Accounting (TEA) transforming the current accounting practices. Second, the paper explores the integration of cost management, supply chain, and inventory management on BT providing the significant challenges and benefits and suggesting an agenda for future research. The authors conduct an exploratory qualitative analysis of an extensive body of literature, from 81 journals. The paper’s innovative contribution and primary objective is to explore, address, and employ this emerging BaaE platform technology that could potentially be integrated with TEA. Further, the study examines the theoretical, technical, and business aspects regarding TEA, since there is limited research evidence in this field. Additionally, the study tries to identify the implications of BaaE in the area of cost management, supply chain, and inventory management from an ecosystem perspective. This effort can assist organizations and practitioners in understanding and further examining this emerging technology. Full article

This paper reports an extension of schema incongruity theory to a service form of fast-moving consumer goods (FMCG) distributed via a digital platform. According to this theory, an FMCG brand’s service form would be incongruent compared to its traditional form available via supermarkets. Based on the relevancy and expectancy dimensions, the level of incongruence for such a service was classed as moderately incongruent. The study used qualitative research to investigate whether the moderate incongruence appealed to modern-day customers. The findings revealed that a subscription to receive a regular supply of the FMCG test brand appealed to the respondents. The moderate incongruity employed in this study was of an optimal stimulation level, enabling respondents to see the added values offered. The values recognised included convenience, family bonding, health and variety. The study observed schema incongruity theory operating for the service form of the FMCG brand. As the study used a qualitative methodology, the findings are specific to the brand and context tested. However, the high interest observed suggests schema incongruity theory could serve as a framework for using a digital distribution system to market service forms of FMCG brands. Full article

A loyalty program is a type of incentive to reward customers’ perceived value and enhance their purchasing behavior. The key to the success of a loyalty program is to allow customers to more actively participate in the program. One possible solution is to allow customers to sell out idle loyalty points and buy in the points that they need. On the basis of a call auction, this study designs a peer-to-peer exchange mechanism for customers to realize the above trade. In addition, a blockchain-based system is developed to support the issuance, redemption, and exchange of loyalty points. In this study, Hyperledger Fabric is adopted as the underlying blockchain technology because it has some features that are beneficial to a cross-organizational coalition loyalty program. This study also proposes a feasible multi-host deployment scheme for the Hyperledger Fabric blockchain network that is suitable for our application scenario. Finally, some implementation results are given to demonstrate the system process from the perspective of the application layer. The mechanism proposed in this study is helpful to improve the likelihood of successfully exchanging points, thus accelerating the circulation and use of loyalty points. Full article

Considering consumer fairness concerns, this paper investigates an e-commerce platform’s selling scheme choice when it adopts a wholesale selling scheme or an agency selling scheme to create a contract with a manufacturer. We find that the intensity of the fairness concerns and the platform fee are key factors affecting the platform’s optimal selling scheme choice. Specifically, when these two factors are relatively high or low, the wholesale selling scheme outperforms the agency selling scheme in terms of the e-commerce platform’s profit. Otherwise, the e-commerce platform should adopt the agency selling scheme. Moreover, when these two factors are sufficiently large or small, the wholesale selling scheme will yield a win-win result for the players of the e-commerce supply chain. Interestingly, we find that, considering fairness-minded consumers, a larger platform fee may be harmful to the platform. We also extend the baseline model to consider the consumer heterogeneity of fairness concerns, proportional platform fee, fairness concern about the manufacturer’s profit, and endogenous platform fee. We find that the main insights remain qualitatively unchanged under these model extensions. Full article

The emergence of short videos has provided a new way for advertisers to place online video advertisements. On short video platforms, the quality of advertisements is the main factor that attracts consumers. This study constructs a model based on advertisers’ advertising behavior and formulates their optimal advertising quality strategies. We then expand on the quality strategy by considering advertisers’ pricing factors. In addition, we compare advertisement placement on short video platforms and on general video platforms and analyze how advertisers should choose their advertisement placement strategies. Our research shows that advertisers should improve the quality of their advertisements to gain more profit when the platform is operating well, so that users become more willing to buy and products become more profitable. In addition, advertisers should present their advertisements in the shortest possible duration and show them after a longer program. Users’ price sensitivity negatively affects advertisers’ optimal advertising quality strategies and profits. Furthermore, advertisers’ choice of platform mainly depends on the advertising nuisance cost to users and the platform’s cost of entry. Finally, we find an optimal budget allocation scheme for small companies joining short video platforms to invest in bidding and designing advertisements. Full article

The application of big data targeted advertising in the green supply chain makes the green marketing of products more accurate and effective. This paper applies game theory to study the decisions and coordination issues of a green supply chain in which the online retailer conducts big data targeted advertising. A centralized model and two Stackelberg game models (an online-retailer-led decentralized model and a manufacturer-led decentralized model) were constructed and solved. The zero wholesale price-side-payment contract and greedy wholesale price-side-payment contract were introduced into the green supply chain for coordination. The study found that: (1) the increase in demand attenuation coefficient, green sensitivity coefficient, and big data targeted advertising sensitivity coefficient will be beneficial to the growth of total consumer demand, supply chain profit, and environmental benefit; (2) supply chain coordination is necessary because greenness, demand, supply chain profit, and environmental benefit under the centralized model are higher than those under two decentralized models; (3) two contracts can achieve the coordination of the green supply chain, and the profits of the manufacturer and online retailer under the contract are greater than those under the decentralized model. The results can provide insights for promoting green supply chain operations. Full article

The holiday atmosphere abounds in marketing campaigns. The present research examines how the holiday atmosphere of a brand logo influences consumers’ merchandise-related nostalgic preference. Across three studies, the authors find that when consumers are exposed to brand logos with a strong (vs. weak) holiday atmosphere, they prefer nostalgic products (Study 1). This effect occurs because consumers exposed to a strong (vs. weak) holiday atmosphere generate more childhood imagery, resulting in significantly more choices of nostalgic products (Study 2). Additionally, the paper finds that the effect of the holiday atmosphere of a brand logo on merchandise-related nostalgic preference—here, the preference for products of nostalgic brands—does not occur for non-traditional holidays (Study 3). These findings make important contributions to the literature on holiday marketing, logo design and nostalgic marketing. Full article

Customer response models have gained popularity due to their ability to significantly improve the likelihood of targeting the customers most likely to buy a product or a service. These models are built using databases of previous customers’ buying decisions. However, a smaller number of customers in these databases often bought the product or service than those who did not do so, resulting in unbalanced datasets. This problem is especially significant for online marketing campaigns when the class imbalance emerges due to many website sessions. Unbalanced datasets pose a specific challenge in data-mining modelling due to the inability of most of the algorithms to capture the characteristics of the classes that are unrepresented in the dataset. This paper proposes an approach based on a combination of random undersampling and Support Vector Machine (SVM) classification applied to the unbalanced dataset to create a Balanced SVM (B-SVM) data pre-processor resulting in a dataset that is analysed with several classifiers. The experiments indicate that using the B-SVM strategy combined with classification methods increases the base models’ predictive performance, indicating that the B-SVM approach efficiently pre-processes the data, correcting noise and class imbalance. Hence, companies may use the B-SVM approach to more efficiently select customers more likely to respond to a campaign. Full article

Online grocery shopping in Germany has shown a strong growth in the past years and is expected to further develop in the future, especially through the influence of COVID-19. The main purpose of this study was to examine six theoretical customer-oriented factors and their influence on consumer online grocery purchase intentions. Additionally, this study compares consumer perceptions before and since the COVID-19 outbreak. Since the health crisis is very recent, the research on its impact on online grocery purchasing behavior is limited. A total of 402 valid questionnaires were collected in Germany. The data were analyzed using the software SPSS IBM 28. The results indicate that perceived risk still has a negative influence on purchase intentions, thus remaining relevant in online grocery shopping. However, the consumers’ perceived risk is considered lower compared to the pre-COVID-19 scenario. Moreover, perceived usefulness, perceived ease of use, perceived trust, convenience, as well as situational factors were found to have a positive relationship with purchase intention, both before the COVID-19 crisis and since then. The COVID-19 pandemic shows a strong reduction in perceived risk, while the remaining characteristics increase at moderate levels. Online grocery businesses could use the insights of this study to reduce perceived risks as well as successfully communicate the benefits of online shopping to consumers. Full article

Negative reviews on e-commerce platforms are posted to express complaints about unsatisfactory experiences. However, the exact knowledge of how online consumers post negative reviews still remains unknown. To obtain an in-depth understanding of how users post negative reviews on e-commerce platforms, a big-data-driven approach with text mining and sentiment analysis is employed to detect various behavioral patterns. Specifically, using 1,450,000 negative reviews from JD.com, the largest B2C platform in China, the posting patterns from temporal, perceptional and emotional perspectives are comprehensively explored. A massive amount of consumers across four sectors in recent 10 years is split into five levels to reveal group discrepancies at a fine resolution. The circadian rhythms of negative reviewing after making purchases are found, suggesting stable habits in online consumption. Consumers from lower levels express more intensive negative feelings, especially on product pricing and customer service attitudes, while those from upper levels demonstrate a stronger momentum of negative emotion. The value of negative reviews from higher-level consumers is thus unexpectedly highlighted because of less emotionalization and less biased narration, while the longer-lasting characteristic of these consumers’ negative responses also stresses the need for more attention from sellers. Our results shed light on implementing distinguished proactive strategies in different buyer groups to help mitigate the negative impact due to negative reviews. Full article

Although 3D models are today indispensable in various industries, the adequate pricing of 3D models traded on online platforms, i.e., virtual 3D assets, remains vague. This study identifies relevant price determinants of virtual 3D assets through the analysis of a dataset containing the characteristics of 135.384 3D models. Machine learning algorithms were applied to derive a virtual 3D asset price prediction tool based on the analysis results. The evaluation revealed that the random forest regression model is the most promising model to predict virtual 3D asset prices. Furthermore, the findings imply that the geometry and number of material files, as well as the quality of textures, are the most relevant price determinants, whereas animations and file formats play a minor role. However, the analysis also showed that the pricing behavior is still substantially influenced by the subjective assessment of virtual 3D asset creators. Full article

Online shopping has intensified in the last decade. The COVID-19 pandemic has imposed circulation limitations and more restrictive behaviors on consumers due to fears of contracting the virus, boosting online grocery shopping. This study aims to assess the relationship between the online food purchasing experience during the pandemic and the intention to purchase food online after the pandemic. The sample of this quantitative study is composed of 358 Portuguese consumers who carried out grocery shopping online during the pandemic and was collected through an online questionnaire. First, a cross-sectional description of the variables was applied to this sample and then an analytical cross-sectional survey was carried out using the partial least squares method. Due to health concerns, food and beverage consumption behaviors changed positively during the pandemic compared to before. Healthier consumer behavior towards food and beverages during the pandemic, compared to before the pandemic, may influence a greater propensity for online grocery shopping. Sociodemographic characteristics (age, education, income) were also determinants of the propensity to shop online during the pandemic. Specifically, the results of this study demonstrate a positive influence of young male consumers, with higher levels of education and income, regarding the online supermarket shopping experience. The results also demonstrate that a good online shopping experience during the pandemic can positively influence online shopping intentions after the pandemic. This study makes it possible to identify determinants of the online food shopping experience, serving as guidance and preparation for strategic marketing for retail grocery companies that wish to position themselves online. It also helps marketers and policymakers understand the potential influence of sociodemographic characteristics such as age, income, and education on building a relationship with consumers. Finally, the relationship between personal characteristics and the online grocery shopping experience requires further substantiation and this study contributes to this gap in the literature. Full article

In practice, several e-commerce platforms offering online channels not only act as resellers but also serve as the marketplace. However, the existing literature rarely explores the impact of the offline service effort strategy with the showrooming effect on the platform’s optimal sales mode. Considering a supply chain consisting of a manufacturer and a platform, we examine the interplay between the manufacturer’s offline service effort strategy and the platform’s online sales modes. We derive conditions under which each of the four scenarios (adopting the service effort strategy under the agency or reselling modes, not adopting the service effort strategy under the agency or reselling modes) emerges in equilibrium. Our results show that the service effort strategy with the showrooming effect can induce the platform’s sales mode selection. Specifically, when the referral fee is low and the showrooming effect is moderate, the platform may choose the agency mode instead of the reselling mode, while when the referral fee is sufficiently high and the showrooming effect is moderate, the platform may adopt the reselling mode instead of the agency mode. Furthermore, when the competition intensity and showrooming effect are sufficiently small, the service effort strategy will be beneficial to the manufacturer and the platform, creating a win-win situation. When the competition intensity or showrooming effect is sufficiently large, the service effort strategy may cause a prisoner’s dilemma for the manufacturer and the platform. In addition, the supply chain consisting of a manufacturer, an offline store and an online platform is also studied in the extension section, and we find that our main results are valid. Full article

In the context of developing the digital platform economy, trade-in programs have become an effective strategy for e-commerce platforms to stimulate consumption. Many head e-commerce platforms have launched their own trade-in programs. However, the existing research on trade-in programs is still stuck in the traditional trade-in model. The purpose of this study is to explore whether there is a new and more beneficial trade-in program. In this paper, we construct the Stackelberg game model between a brand owner and a B2C e-commerce platform under two trade-in programs and use optimization theory to obtain the equilibrium results of the model. The results indicate that the performance improvement of the new-generation product will promote the increase in two-generation products’ price under traditional trade-in programs, the price of the new-generation product will increase, and the price of the previous-generation product will decrease under new trade-in programs. The brand owner always prefers traditional trade-in to new trade-in. However, the e-commerce platform prefers traditional trade-in to new trade-in just when the previous-generation product is durable enough and the performance improvement of a new-generation product is small enough; otherwise, it prefers new trade-in to traditional trade-in. These findings are beneficial to the operational practices of e-commerce platforms and brand owners. Full article