Purpose: The purpose of this paper is to investigate the impact of website quality on online impulse buying behavior (OIBB) in China, and assess the moderating roles of sales promotion and credit card use.Design/methodology/approach: An online and personal survey from 1,161 online shoppers belonging to three big cities of China – Beijing, Shanghai, and Nanjing – was conducted. A random sampling technique was utilized for data collection. Data were analyzed using validity and reliability tests, confirmatory factor analysis, and structural equation modeling.Findings: Three major findings discovered are: first, the website quality positively affects the OIBB; second, the sales promotion significantly influences OIBB and acts as a strong moderator on the relationship between website quality and online impulse buying; and third, the online impulse purchases are positively influenced by use of credit card, and the use of credit card enhances the relationship between website quality and online impulse buying.Research limitations/implications: First, the website quality positively affects the OIBB; second, the sales promotion significantly influences OIBB and acts as a strong moderator in the relationship between website quality and online impulse buying; and third, online impulse purchases are positively influenced by credit card use. Moreover, credit card use enhances the relationship between website quality and online impulse buying.Originality/value: This research is the first to investigate the relationship between website quality and OIBB in China, with sales promotion and credit card use as moderators.

Purpose: The current study aims to investigate the impact of various types of motivational factors on consumers' behavior regarding the purchase and consumption of organic food. A favorable attitude among consumers may translate into positive purchase intention and actual buying behavior. For this, variables have been extracted from well-established theories, i.e. self-determination theory (SDT) and theory of planned behavior (TPB), to address the issue more proficiently.Design/methodology/approach: A self Administered close-ended questionnaire was distributed to twelve hundred and sixty-five consumers using purposive sampling technique. Seven hundred and eighty-seven responses were retained after preliminary analysis. Partial least squares structural equation modeling (PLS-SEM) was applied using SmartPLS 3 to analyze validity and reliability. Furthermore, 5,000 boot-strapping method was used to test hypotheses.Findings: The findings of the study suggested that two of the SDT variables [external regulations (ER) and integrated regulation (IR)] lead to a significant impact on “consumers” attitudes, while the effects of intrinsic motivation (IM) and introjected regulation (INR) appeared to be insignificant. All the variables extracted from TPB (attitude, subjective norm, perceived behavioral control, purchase intention, and buying behavior) appeared to have a significant impact, while the trust was found to moderate the relationship between attitude (ATT) and purchase intention (PI). Moreover, the values of Q-square depicted that the combined model had more predictive relevance (BB = 0.153; PI = 0.211), as compared to the TPB model (BB = 0.147; PI = 0.186).Originality/value: Marketers can make use of the study's findings to develop marketing strategies by considering particularly extrinsic motivational influences. Hence, advertising could be used to emphasize extrinsic benefits such as increasing individual self-esteem through social status (positive consequences) and appealing to consumers' desire for communal or societal approval. Such campaigns should also consider external regulatory factors, such as the fear of having hazardous effects on the individual's health due to the use of inorganic and processed food. Furthermore, policymakers can develop a sense of trust in the legitimacy of organic labeling by educating consumers about various organic certifications.

A huge amount of data, generated by Internet of Things (IoT), is growing up exponentially based on nonstop operational states. Those IoT devices are generating an avalanche of information that is disruptive for predictable data processing and analytics functionality, which is perfectly handled by the cloud before explosion growth of IoT. Fog computing structure confronts those disruptions, with powerful complement functionality of cloud framework, based on deployment of micro clouds (fog nodes) at proximity edge of data sources. Particularly big IoT data analytics by fog computing structure is on emerging phase and requires extensive research to produce more proficient knowledge and smart decisions. This survey summarizes the fog challenges and opportunities in the context of big IoT data analytics on fog networking. In addition, it emphasizes that the key characteristics in some proposed research works make the fog computing a suitable platform for new proliferating IoT devices, services, and applications. Most significant fog applications (e.g., health care monitoring, smart cities, connected vehicles, and smart grid) will be discussed here to create a well‐organized green computing paradigm to support the next generation of IoT applications.

Order increases, supply chain disruptions, changing customer behavior, store closures, and more that have been caused by the coronavirus epidemic (COVID-19) will undoubtedly affect the online commerce forms of business. The coronavirus pandemic has a significant impact on digitalization and customer experience and well-being in mobile commerce. Since the beginning of the coronavirus pandemic, online sales and the number of online shoppers using wireless internet-enabled devices have increased tremendously. The article develops, an experimental study that captures COVID-19 and digital commerce’s impact in terms of customers’ experience and well-being during the pandemic period. The study explores the synergy between technology evolution and the effects of the COVID-19 pandemic on customers’ behavior based on survey data collection and the technology acceptance model (TAM). The results reveal that, for millennials, digital commerce seems to be the typical way of shopping and paying in the pandemic period since the oldest generations adopted in a smaller proportion the use of mobile devices for shopping and payments. Besides, retailers are confronted with great challenges raised by millennials’ expectations. The result confirms four of the six hypotheses based on the technology acceptance model (TAM). As a result, it shows that the easiness of use, trust, mobility, and customer involvement influences the behavioral intention of the customer to use mobile commerce, and that usefulness and customization does not influence the behavioral intention.

First, the purpose of this study is to examine the impact of situational variables, scarcity and serendipity, on online impulse buying (OIB) in Chinese social commerce (SC) environment. Second, the study further assesses the moderating role of five dimensions of hedonic shopping value. Data were gathered from 671 online shoppers who come from two metropolitan cities of China, Beijing, and Shanghai. Structure equation modeling utilized was generated by AMOS 23 version to test the study hypotheses. The results confirm that situational factors positively influence the online impulse buying among Chinese online shoppers in SC environment. Four dimensions of hedonic shopping value (social shopping, relaxation shopping, adventure shopping and idea shopping) positively moderate the relationship between serendipity and OIB; value shopping is insignificant with moderation effect. The finding is helpful to the online retailers and SC web developers by recommending them to take the scarcity and serendipity in their consideration. These factors have the potential to motivate the consumers to initiate the hedonic shopping aptitude to urge to buy impulsively. Unlike the previous work which remained unsuccessful in incorporating all factors into one study, this study has incorporated irrational and unplanned consumption along with rational and planned one in the same research.