Online Retail Store Community Engagement and Its Impact on Purchase Intentions in the Context of Online Reviews

Consumers want to engage with the retail store community in the shopping context. This study examines how consumers’ perceptions of source credibility and perceived usefulness of online reviews impact an intention to engage with the online retail store community and purchase intentions. The study also identifies differences when reviews are posted by customers versus store employees. Results show that the proposed relationships within the structural model are significant and reviews posted by store employees are seen as more credible, whereas reviews posted by other customers are perceived to be more useful. Theoretical and managerial implications are discussed.

The Role Of Big Data In The Formation Of Supply Chain Platforms For New Forms Of Online Retail

In the context of internet age, data is growing explosively in the Chinese retail industry. However, there is insufficient research of the theoretical frameworks and interaction relationships between big data, supply chain platforms, and online retail. Through a literature review, an empirical case study survey of Alibaba, and grounded theory, this paper explores how big data helps shape supply chain platforms able to support new forms of online retail. The theoretical framework was validated by testing the reliability and the open coding to process of the case study materials. The results identify the overall antecedents to the formation of the supply chain platform and reveal significant positive effects between big data and new retail. The findings help firms build big-data driven supply chain platforms better able to support new forms of online retail.

Online-Retail Supply Chain Optimization with Credit Period and Selling Price-Dependent Demand

Credit payment strategies have been implemented widely in the online retail industry. This work studies an online-retail supply chain involving credit period and selling price-dependent demands. The participants of the supply chain form a Stackelberg game where the supplier as a follower sells products to the customers through an online platform provider, who as a leader provides a credit period to customers and charges the supplier based on the quantity of goods sold. We study and compare the supply chains when the online platform provider adopts the cash payment and credit payment strategies, respectively, to investigate the effects of the credit period, the selling price and the default risk on supply chain system performance. We also investigate these supply chains under both the centralized and decentralized settings and provide an example to illustrate a simple allocation mechanism to coordinate the decentralized supply chain. Finally, an extension of the supply chain with credit payment is given.

Development on advanced technologies – design and development of cloud computing model

Big Data has been created from virtually everything around us at all times. Every digital media interaction generates data, from computer browsing and online retail to iTunes shopping and Facebook likes. This data is captured from multiple sources, with terrifying speed, volume and variety. But in order to extract substantial value from them, one must possess the optimal processing power, the appropriate analysis tools and, of course, the corresponding skills. The range of data collected by businesses today is almost unreal. According to IBM, more than 2.5 times four million data bytes generated per year, while the amount of data generated increases at such an astonishing rate that 90 % of it has been generated in just the last two years. Big Data have recently attracted substantial interest from both academics and practitioners. Big Data Analytics (BDA) is increasingly becoming a trending practice that many organizations are adopting with the purpose of constructing valuable information from BD. The analytics process, including the deployment and use of BDA tools, is seen by organizations as a tool to improve operational efficiency though it has strategic potential, drive new revenue streams and gain competitive advantages over business rivals. However, there are different types of analytic applications to consider. This paper presents a view of the BD challenges and methods to help to understand the significance of using the Big Data Technologies. This article based on a bibliographic review, on texts published in scientific journals, on relevant research dealing with the big data that have exploded in recent years, as they are increasingly linked to technology

The impact of the psychological marketing factors (tricks) on consumer's buying decisions

Psychology has an essential role in consumer behaviour comprehension and shaping of the appropriate marketing activities, especially in advertising, sales promotion and brand loyalty building. Applying distinct psychological marketing factors (tricks) has had a long history in traditional and even online retail commerce. Their impact on consumer buying decisions has been researched for decades (since the 1970s). However, consumers in Croatia have been able to experience these factors since the 1990s. The survey in this study collected data about the influence of prices, advertising, sales promotion, retail atmosphere, and packaging from 256 respondents. The analysis pointed out that only 9 (out of 26) researched psychology marketing tricks positively influence consumer buying decisions. Low prices and discounts were evaluated as the most critical factors (tricks), followed by a pleasant store ambience, music, and memorable promotional jingles respectively. Celebrity endorsement and appealing to scarcity were considered the least important factors. The research determined that younger consumers (aged below 30), women, , students and respondents with higher family income are more prone to being triggered by the psychology marketing tricks

Online Shopping : An analysis of contributing factors in TAM

There has been an exceptional augmentation of online shopping as it provides convenience comfort to customers. The propagation of online shopping has kindled pervasive research to explore which aspects drives consumers for online shopping from consumer and technology oriented view. Online shopping, especially, an online retail sale is becoming increasingly popular. Greatest issue with information technologies is to identify the factors that influence consumers to adopt such systems. Various researchers have added different factors and over the years, the original TAM has been expanded. Hence, the present study has been carried out to explicate most widely accepted factors of technology acceptance model (TAM).

A Survey on Hybrid Recommendation Systems

As India is moving fast towards digital economy, E-commerce industry has been on rise. Many platforms such as Amazon and Flipkart provide their customers with a shopping experience better than actual physical stores. Several E-commerce websites use different methods to improve the customer engagement and revenue. One such technique is the use of personalized recommendation systems which uses customer’s data like interests, purchase history, ratings to suggest new products which they may like. Recommendation systems are used by E-commerce websites to suggest new products to their users. The products can be suggested based on the top merchants on the website, based on the interests of the user or based the past purchase pattern of the customer. Recommender systems are machine learning based systems that help users discover new products. Due to the recent pandemic situation of 2020 and 2021, many of the local retail stores have been trying to shift their business to online platforms such as dedicated websites or social media. The proposed methodology based on Machine Learning aims to enable local online retail business owners to enhance their customer engagement and revenue by providing users with personalized recommendations using past data using methods such as Collaborative Filtering and Content-Based Filtering.

Shopping mall vs Online Retail- Consumer shopping preference in the city of Bengaluru

Ever since the first fully enclosed and climate controlled mall opened in the United States in 1956 It has caught the fancy of consumers. It revolutionized the way retail was looked at. With everything available under one roof, customers thronged the air-conditioned environments to shop in comfort. Slowly they evolved into a recreation space, with multiplex, food courts, gaming zones which ensured that there was something for everyone in a mall. The replicas were erected all across the world, and embraced with much gusto, as malls became the symbol of urbanization and aspirations for developing nations. In the last two decades or so, India has seen a massive boom in no. and size of a shopping mall. It seemed malls are here to stay even though the high value shoppers were decreasing steadily and the only places you could see crowds were the food courts and the multiplexes, or some large lifestyle stores. The mid and smaller size stores renting out exorbitantly priced floor spaces were starting to wear deserted looks. Then the Covid-19 pandemic hit and forced millions to their homes for months. With shops and malls closed, the online retail exploded and became one of the biggest happening of the last two years. Sitting in comforts of their homes, people were buying food, clothes, electronics, furniture from all over the country, offered to them at an eye watering discount which the physical stores could never match. So has the consumer preference changed in favour of online shopping or malls are still favoured once the lockdown is lifted ?Given the Strong commercial impact that malls have had on Indian retail economy, an attempt was made to understand shopping preference of the consumers in the city of Bengaluru through a questionnaire survey collecting 120 responses. The analysis revealed that consumers still prefer offline shopping for clothes, shoes and accessories. While online shopping is preferred for household items. Groceries, Beauty & cosmetics, Electronics were equally preferred through online or offline mode. Participants were also inclined towards having more open public spaces and sports related facilities in the mall indicating that in Bengaluru malls are also places to socialise and spend quality time together rather than mere shopping spaces. Keywords: E-Commerce, Retailing, Consumer Behaviour, Shopping Preferences, Shopping malls