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With the exponential growth of smart handheld devices and social communities, mobile commerce, social commerce and proximity commerce are also created in the last decades. Recently, the newer commerce model is online to offline (O2O) commerce and various kinds of creative service models have been proposed. It becomes a major research topic since re...
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... the changing commerce environment, there are lots of online to offline and offline to online interactions different from traditional bricks-and-mortar and E-commerce. This paper adjusts the service model in the previous research [4] and focuses on mobile commerce, proximity commerce and social commerce then proposes the O2O commerce service model in Fig.1. The top area represents the real-world marketing service model (Offline). ...
Citations
... This study underscores the importance of offline service quality in the overall success of O2O e-commerce, offering strategies for improvement that are vital for businesses operating in this model. Tsai et al. (2015) investigated the effectiveness of an O2O commerce service framework applied to proximity commerce. Their research demonstrates the significant impact of strategic factors, such as the proximity between kiosks and stores, on consumer engagement and transaction behaviours, offering valuable insights for optimizing O2O commerce strategies. ...
This bibliometric study comprehensively analyses the scholarly landscape surrounding Online-to-Offline (O2O) commerce from 2006 to 2023. Through a systematic review of existing literature with a bibliometric analysis approach, this research identifies pivotal themes, methodologies, and findings that characterize the evolution and impact of O2O strategies across various sectors. The study begins by tracing the conceptual foundation of O2O commerce, emphasizing its role in integrating digital and physical consumer experiences in response to the changing dynamics of consumer behaviour and market demands. It highlights the strategic adoption of O2O models by e-commerce entities and brick-and-mortar stores, aiming to create a seamless shopping journey by leveraging the strengths of both online and offline platforms. The analysis focuses on the strategic implications for businesses, including the decision-making processes regarding market coverage, delivery costs, and inventory management to enhance profitability and sustainability. The research further delves into consumer behaviour, examining factors influencing the preference for online or offline purchasing, such as demographic characteristics, product types, price levels, and perceived service quality. The findings reveal a dynamic evolution of O2O strategies, underpinned by a growing emphasis on customer engagement, technological innovation, and the strategic management of online and offline synergies. The research underscores the transformative potential of O2O commerce in bridging the gap between digital and physical marketplaces, enhancing consumer experiences, and fostering sustainable business practices. In conclusion, this bibliometric study sheds light on the multifaceted dimensions of O2O commerce, offering valuable insights for academics, practitioners, and policymakers interested in the strategic integration of digital and physical retail environments. It calls for continued research and innovation to harness the full potential of O2O models in meeting the complex needs of consumers and businesses in the digital era.
... The online-to-offline concept was first proposed to increase e-commerce opportunities by combining offline services and e-services. Then this concept was adapted to the challenges in the world of education, especially when the COVID-19 pandemic occurred [11]. The conventional way of learning in online learning has changed [12]. ...
... (1) CGB adopts an innovative business model which combines the advantages of "online + offline e-commerce model" (Tsai et al., 2015) and "presale + group buying business model" (Zhu et al., 2022;Posselt & Gerstner, 2005). The former reduces costs and transportation losses by self-built logistics network and self-pickup points. ...
The Community-Group-Buying Points (CGBPs) flourished during COVID-19, safeguarding the daily lives of community residents in community lockdowns, and continuing to serve as a popular daily shopping channel in the Post-Epidemic Era with its advantages of low price, convenience and neighborhood trust. These CGBPs are allocated on location preferences however spatial distribution is not equal. Therefore, in this study, we used point of interest (POI) data of 2,433 CGBPs to analyze spatial distribution, operation mode and accessibility of CGBPs in Xi'an city, China as well as proposed the location optimization model. The results showed that the CGBPs were spatially distributed as clusters at α = 0.01 (Moran's I = 0.44). The CGBPs operation mode was divided into preparation, marketing, transportation, and self-pickup. Further CGBPs were mainly operating in the form of joint ventures, and the relying targets presented the characteristic of 'convenience store-based and multi-type coexistence'. Influenced by urban planning, land use, and cultural relics protection regulations, they showed an elliptic distribution pattern with a small oblateness, and the density showed a low-high-low circular distribution pattern from the Palace of Tang Dynasty outwards. Furthermore, the number of communities, population density, GDP, and housing type were important driving factors of the spatial pattern of CGBPs. Finally, to maximize attendance, it was suggested to add 248 new CGBPs, retain 394 existing CGBPs, and replace the remaining CGBPs with farmers' markets, mobile vendors, and supermarkets. The findings of this study would be beneficial to CGB companies in increasing the efficiency of self-pick-up facilities, to city planners in improving urban community-life cycle planning, and to policymakers in formulating relevant policies to balance the interests of stakeholders: CGB enterprises, residents, and vendors.
... Although ensembles learning approaches regularly win deep learning contests such as Kaggle, enhancing techniques have established as a legit contender in many of the challenges. Gaussian boosting [2], Artificial neural [3], severe gradient enhancing [4], light gradient boosting [5], histogram gradient boosting [6], and CatBoost [7] are some of the boosting and other basic methods we investigated. We also looked into different baselines such as random forest [8], tree-based bagging regressor [9], and linear regression models (LSTM, Support Vector Machine). ...
Forecasting delivery schedule has always been a basis of urban logistics, but fine-tuning accuracy is now vital for successful outcomes. People's everyday demands have indeed been satisfied by Internet meal online delivery services across the globe; for example, platform-to-consumer and steakhouse deliveries in India hit an all-time high of 290 billion orders in 2021 (Purvis et al. in Sustain Sci 14:681–695 [1]). From of the time a client places an order until it arrives at their door, restaurants must provide correct info about when their meal will be distributed. Offering an estimated time that is longer than the real delivery date would discourage consumers from purchasing, while giving a rough guesstimate that is less than the real delivery will boost the number of people who contact our customer service. The major purpose of this study is to propose and provide a Online Food Delivery Assistant (OFDA) establish essential factors for forecasting food delivery batch sizes, as well as to provide a framework for making reliable forecasts. The key impacts and problems of delivery operations in India's various industries are examined and contrasted.KeywordsOnline food deliveryBrand loyaltyTrustUsabilityApplication quality
... O2O commerce and conventional e-commerce are distinct in several ways. O2O commerce is first and foremost location-based (Tsai et al., 2015), concentrating on regional retail and life service sectors including restaurants, lodging, and entertainment. Along with the actual transactions, O2O commerce frequently uses both online and offline channels (Huang et al., 2020;Lin et al., 2019). ...
Purpose: With the unique feature of O2O, consumers are now able to check the profile of the services and products online and then consume them in offline venues or vice versa. This study provides motivation and practical implications about online-to-offline (O2O) distribution channels and investigates the relationship between economic values, service consistency and brand identity attractiveness in the O2O distribution channel. Then identify the impact of brand identity attractiveness on the performance (reputation and reuse intention). Research design, data, and methodology: Structural equation modeling (SEM) has been used to investigate the relationship between economic value and brand identity attractiveness, which affects the reputation and reuse intention of services in O2O. Results: Empirical results show the positive and significant impact of economic value and service consistency on brand identity attractiveness which results the positive and significant impact on performance (reputation and reuse intention) in O2O. Conclusion: In the O2O distribution channel, economic value is an important aspect for the attractive image and brand identity. On the other side, brand identity attractiveness is important for the bright future of O2O services, continuous growth, achieving the distinct goal, keeping good promises with customers, and a better reputation of O2O services in distribution channels.
... As digitization continues and channels increase, multichannel retailing is moving to omnichannel retailing. Omnichannel is a popular strategy or technique that allows consumers to use multiple sales channels to make a single transaction, providing real-time, seamless, consistent, and personalized customer experience by channel integration [4][5][6]. Compared with the multichannel phase, omnichannel involves more channels, but the different channels become blurred as the natural borders between channels begin to disappear [7]. Online-to-offline (O2O) commerce is a specific form of omnichannel retailing, which emphasizes utilizing the online channel to drive offline sales [4,8,9]. ...
... Compared with the multichannel phase, omnichannel involves more channels, but the different channels become blurred as the natural borders between channels begin to disappear [7]. Online-to-offline (O2O) commerce is a specific form of omnichannel retailing, which emphasizes utilizing the online channel to drive offline sales [4,8,9]. In O2O commerce, consumers make purchases online and then consume offline. ...
... However, O2O services exist not only in the food industry but also in other local retail and service sectors, such as beauty [20], furniture [21], and hotels [22]. Business models are changing due to technological advancements [4], allowing numerous new O2O scenarios to emerge. Since there is no universal model to understand consumer behavior in a general O2O context, stakeholders may not know which theory or model can help them develop market strategies when new O2O scenarios emerge. ...
Online-to-offline (O2O) commerce is a specific form of omnichannel retailing, wherein consumers search and purchase online and then consume offline. There are many different O2O models, and new O2O businesses are emerging during the COVID-19 pandemic; they can be categorized into two types of O2O services: to-shop and to-home. However, few studies have focused on consumer behavior in a comprehensive O2O scenario, and no study has attempted to compare the differences between to-shop and to-home consumers. Therefore, this study aimed to propose a universal model to predict consumers’ continued intention to use O2O services and to compare the differences between to-shop and to-home O2O in terms of factors influencing consumer behavior. A cross-sectional survey was conducted, and the PLS-SEM was used for data analysis. The basic SEM results indicated that habit, performance expectancy, confirmation, and offline facilitating conditions are the main predictors. The multigroup analysis showed differences between to-shop and to-home consumers regarding hedonic motivation, price value, and perceived risk. The study suggests that marketers and designers in various O2O scenarios can use the framework to build their business plans and develop different marketing strategies or sub-platforms for to-shop and to-home consumers.
... In the past few decades, the spread of the Internet and the emergence of electronic commerce (e-commerce) or online shopping have changed the way consumers think and live in an unprecedented trend [1]. With the exponential growth of mobile devices (mainly smartphones) in the last decade, mobile commerce (m-commerce) has emerged, once again changing consumer behavior patterns and dramatically changing the landscape of traditional e-commerce [2]. It means that consumers can make purchases using their smartphones anytime, anywhere. ...
... Rampell [6] first proposed the concept of O2O in 2010 and illustrated that the key to O2O is to find consumers online and bring them into offline channels. Tsai et al. [2] argued that O2O commerce provides a seamless purchasing experience between online and offline commerce by any connected device, while Xiao et al. [19] stated that O2O commerce brings offline business activities to online channels which are used to promote offline businesses. Some researchers have distinguished between online-to-offline and offline-toonline commerce [20][21][22]. ...
... There are several differences between O2O commerce and traditional e-commerce. First, O2O commerce is location-based [2] and focuses on local retail and life service industries [19,26], such as restaurants, hotels, and entertainment. Second, the transactions in O2O commerce typically involve both online and offline channels [27,28]. ...
Online-to-offline (O2O) commerce is a popular business model which links offline business activities with online channels. Consumer behavior in O2O commerce is more complex than in other traditional business models as both online and offline channels are involved. Despite the growing number of publications focused on this issue, no review paper has discussed the current research trends and factors influencing consumer behavior in O2O commerce. Therefore, this review aimed to synthesize literature on O2O commerce from 2015 to April 2022, focusing on consumer behavior. A set of inclusion and exclusion criteria was developed for searching and screening articles from two dominant databases (i.e., WOS and Scopus), and 53 eligible articles were included in this review. A thematic review approach using ATLAS.ti 9 software was conducted. Quantitative results presented the research trends of O2O commerce. Qualitative analyses generated eight main clusters of factors which influence consumers' O2O behavior: (1) service and product quality, (2) technical and utilitarian factors, (3) emotional and hedonic factors, (4) trust and risk, (5) price and cost (6), social factors, (7) online content, and (8) habit. This paper also highlighted promising future research directions. The findings are expected to benefit the sustainable management and the future research of O2O commerce.
... Furthermore, in the sharing economy, users rely heavily on the collective comments and acts of other users to make decisions [20]. Similar to trust in the host community, trust in the user community is another type of institution-based trust that is important but has been overlooked in the literature. ...
... From the perspective of individual users, this study proposes privacy concerns as a situational factor under which trust is transferred and explores how privacy concerns affect the relationship between trust in the user community and trust in the SA platform and the relationship between trust in the user community and trust in the host community. Our study not only extends the research on privacy concerns and the privacy calculus model [20] to the context of SA but also makes contributions to the existing research on trust and trust transfer [18]. ...
Sharing accommodation (SA) has gained rapid growth in the last decade. To offer better service to users, the platform and hosts have to extensively collect and utilize confidential user data and information. With the extensive collection and utilization of personal user information, there are potential problems of data abuse and leakage, which makes users’ privacy concerns an important and unavoidable issue for repeated purchases and the sustainable development of SA. Privacy concerns are thus not only an important antecedent of purchase behaviors, but also an important conditional variable that will have impacts on the formation of trust and user purchase behaviors. However, the moderating effect of privacy concerns on trust formation has rarely been examined in the SA literature. To fill this knowledge gap, drawing on trust transfer theory and trust literature, this study builds a theoretical model to examine the relationships of three types of institution-based trust (i.e., trust in the SA platform, trust in the user community, and trust in the host community) and their effects on continuous use intention. Moreover, this study explores the moderating effect of privacy concerns on institution-based trust transfer in the context of SA. We then collected data through a questionnaire survey from experienced users of two reputable SA platforms in China, and empirically tested the research model with 470 valid responses. The results show that trust in the user community positively affects trust in the SA platform and trust in the host community; trust in the SA platform and trust in the host community positively affect users’ continuous use intention. Meanwhile, privacy concerns negatively moderate the relationship between trust in the user community and trust in the SA platform, as well as the relationship between trust in the user community and trust in the host community. The findings confirm the moderating role of privacy concerns in the trust transfer process, complementing existing research on trust transfer theory and trust.
... In the digital context, companies face challenges, such as difficulty in the speed with which information, questions, benefits and logistics need to be accessible to the consumer (Tsai et al., 2015). It is understood that the use of social media can minimize these challenges, for the dissemination of products and services in a fast and directed way to the target audience (Leite & Azevedo, 2017), which leads to the perception that the traditional means of marketing, in time, will be replaced by the digital (Malar, 2016). ...
... O2O makes use of internet technology and is recognized as an e-commerce "business model that matches offline vendors to customers through an Internet-based platform or smartphone application" (Hwang & Kim, 2018). It provides a "seamless shopping experience between online commerce and offline bricks-and-mortar, using a connected device or digital technology" (Tse-Ming, Wen-Nan, Yu-Tin, & Seng-Cho, 2015). It uses digital technologies and processes to enable a "two-way flow of information, interactions and transactions, from the online to the physical world" (Latini, 2019). ...
The growing digital footprint in emerging markets has bolstered the demand for quality and real-time customer experience through multiple retail platforms. Retail markets in emerging economies are increasingly experimenting with Online-to-Offline (O2O) commerce. This study aims at identifying various factors influencing the adoption and success of O2O business models in emerging markets. A strategic TOPICS framework is proposed to determine and evaluate the multi-dimensional factors that impact O2O retailers. This paper provides insights for potential e-commerce retailers in emerging markets diversifying into O2O commerce. The conclusion offers insights that could help redefine the future of O2O commerce in emerging markets.
