Short video excerpts from TV shows are a tool that producers/broadcasters use to promote their programs. This study examines how video highlights that are presented online for free viewing, which can be analogous to product samples for entertainment goods, affect TV audience ratings. We investigate whether a displacement effect exists, i.e., the substitution of goods due to the availability of other

A large volume of customer reviews is generated from time to time and customer requirements are presented between lines of online opinions. Many studies about online opinions mainly focus on the extraction of customer sentiment, but practical concerns regarding the integration into new product design are far from extensively discussed. To enlighten designers about how consumers differ geographically

In the Bitcoin system, large numbers of miners invest massive computing resources in the blockchain mining process in pursuit of Bitcoin rewards, which are comprised of a fixed amount of system-generated new block reward and a variable amount of user-submitted transaction fees. Here, transaction fees serve as the important tuner for the Bitcoin system to define the priorities in users’ transaction

Few studies have investigated the mechanism underlying the connection between votes and review helpfulness. A within-subject experiment with a between-group factor of personality traits was adopted to measure participants’ neural response in the processing of votes regarding review helpfulness. The results showed that a larger feedback-related negativity (FRN) and smaller P300 were induced when their

It has become a popular research topic how data on Internet queries are used to make reliable predictions about changes in the marketplace. In this study we analyze the relationship between the online search volume of IPO or initial public offering stocks and their post-IPO stock returns. We obtain the online search data sets of the NAVER, one of the largest online search services in Korea, and the

Logistics services and product prices are two factors that influence consumers’ buying behavior. In recent years, research on decision and coordination of competing supply chains has attracted growing attention. However, the research of competing supply chains with substitutable products under logistics services and product prices has not been studied in the literature. We consider four decision variables

Web assurance seals are actions taken by e-commerce vendors to increase their trustworthiness and alleviate consumers’ concerns. In their essence, web assurance seals are a product of negotiations, adoptions, and settlements among various groups of interests (e.g., seal authorities, vendors, consumers, or governmental institutions). However, previous research has hitherto used a unilateral research

The review of online products or services is becoming a major factor in the user’s purchasing decisions. The popularity and influence of online reviews attract spammers who intend to elevate their products or services by writing positive reviews for them and lowering the business of others by writing negative reviews. Traditionally, the spam review identification task is seen as a two-class classification

In recent years, the rapid development of e-commerce has brought great convenience to people. Compared with traditional business environment, e-commerce is more dynamic and complex, which brings many challenges. Data mining technology can help people better deal with these challenges. Traditional data mining technology cannot effectively use the massive data in the electricity supplier, it relies on

With the advent of Internet big data era, recommendation system has become a hot research topic of information selection. This paper studies the application of deep learning and distributed expression technology in e-commerce product advertising recommendation. In this paper, firstly, from the semantic level of advertising, we build a similarity network based on the theme distribution of advertising

With the popularity of the sharing economy, ride-hailing services have greatly affected people’s travel and become a new travel mode for urban residents. However, the lack of effective industry regulation has resulted in serious operational problems and growing difficulties in the furthering development of ride-hailing services in China. Therefore, it is necessary to study the regulation strategies

This study offers a systematic review of academic research on platforms in management, business and economics. By using two visualization tools named VOSviewer and CiteSpace, we analyzed 619 articles on platform research with associated 23,093 references from the Web of Science database. We have discerned the most impact publications, authors, journals, institutions and countries in the platform research

In knowledge-intensive crowdsourcing (KI-C), estimating proper participants is an important way to ensure tasks crowdsourcing outcomes. Participants’ attributes (PAs) act as the main decision factors which are viewed as criteria for evaluating and estimating potential participants. Actually, multiple interdependent PAs have effect on participant estimation. It is an initial and vital work in estimating

Online apparel industry is suffering from a major issue of return, with a high rate of return for apparels that are sold online it becomes necessary to investigate the probable reasons of return in online apparel industry. The objective of the study is to develop a multi-criterion approach for evaluation of various factors that are responsible for the return of apparels purchased online in context

In recent years, we have witnessed a flourish of social commerce services. Online users can easily share their experiences on products or services with friends. Social recommender systems are employed to tailor right products for user needs. However, existing recommendation methods try to consider the social information to improve the recommendation performance while they do not differ the impact of

There is a need to understand how to: spread product information to maximum range, identifying influential users, and analyze how they are intrinsically connected in a social network. In this paper, we collected tweets of Huawei Mate 9 to analyze users’ information behavior such as tweeting, forwarding, and commenting on tweets. We applied independent cascade model to this empirical Twitter diffusion

Customer engagement has been considered to be one of the most important goals of social media marketing. Many companies have conducted social media marketing, particularly through Facebook, by managing their brand fan pages. Compared with other approaches in social media marketing, sweepstakes-based marketing has been successful in gaining customers’ attention and in fostering engagement with customers

Microlending has grown rapidly and now benefits around 250 million people globally, half who would otherwise not have access to credit. Use of social credit systems for microlending risk assessment is most pronounced in Asia, as most Western countries tightly regulate personal information available to lenders. In most of the developing world, geography, social structure, disease, climate and culture

The booming of social media facilitates the popularity of social commerce. In social commerce communities, relationship building is rather crucial. In this study, we consider both swift guanxi and relationship commitment to explore the interpersonal relationship building process in social commerce. Collecting 972 valid responses of social commerce community members, we identify four bond-based antecedents

There have been significant efforts to understand, describe, and predict the social commerce intention of users in the areas of social commerce and web data management. Based on recent developments in knowledge graph and inductive logic programming in artificial intelligence, in this paper, we propose a knowledge-graph-based social commerce intention analysis method. In particular, a knowledge base

Group-buying often fails even when there are satisfactory quantities as not enough consumers join in the required time, which can waste seller, purchaser, and platform operator time resources; therefore, the group buying features require further research. Over a 3 weeks period, around 700 million click-stream records from 1,061,770 users from a stable and continuous time series were allocated to groups

This paper examines a unique selling strategy, group buying on a social E-commerce platform. We proposed a framework on how to design a group buying strategy in the presence of different social network attributes (different structures, different referral costs, and different network externalities) to examine the following questions: (1) How will the group buying threshold depend on consumer referrals

The impact of place-of-origin on price premium for agricultural products in the online marketplace has received limited attention in the existing literature. This study draws from the elaboration likelihood model and investigates whether place-of-origin affects price premium. Moreover, this study explores how other cues [seller’s reputation, positive word-of-mouth (WOM) volume, and WOM valence] moderate

The emergence of cross-border e-commerce has brought new opportunities to traditional enterprises. This paper discusses the partner selection of cross-border e-commerce companies in the B2B mode. It constructs a theoretical model of partner selection of cross-border e-commerce enterprises based on literature review. Through the mathematical analysis of an asymmetric evolutionary game model, it is considered

Customer recognition provides an opportunity to the customers to think about services in service companies. Classifying customers into different categories based on their satisfaction helps these insurance companies to better manage their capital that results in more profit. Researchers have used different categorization methods to identify and classify customers based on their level of satisfaction

Electronic coupon (e-coupon) is one of the most important marketing tools in B2C e-commerce. To improve the e-coupon redemption rate and reduce marketing costs, it is crucial to retarget customers who have received e-coupons and have higher propensity to redeem their coupons. Using log data and transactional data to extract the features of past purchase behavior, past coupon redemption behavior and

User-generated content (UGC) is influential in reducing customer perceived risk and determining online store sales. E-sellers spend huge costs and efforts to improve UGC for it serves as a convenient and persuasive alternative for marketing and advertising purposes. Considering that consumers may set lower and/or upper limits (i.e., psychological thresholds) in which the good is expected to be, and

Based on daily data of 749 active online P2P lending platforms in Chinese market, this study explores the key factors affecting the net cash inflow rate of the platform which is vital for its operation and survival from the perspective of reputation, structure design and FinTech ecosystem. Internal governance issues of P2P lending platforms are further discussed according to the model results. A positive

A salient characteristic of the current digital economy is the prevalence of digital products. It may be largely attributed to the rapid growth of digital media which grant users tremendous control over various digital content. However, a number of studies in consumer psychology reported that digital products may lead to reduced perceptions of control as the virtual format inhibits sense of ownership

Along with the quick development of e-commerce, different payment schemes are provided to online consumers to improve their shopping experience. Currently, the payment schemes can be divided into two categories, one is pay-to-order, and the other is pay-on-delivery. Payment scheme directly affects consumers’ behavior and e-tailer’s pricing decision in e-commerce. In this paper, we characterize the

Advances in information technologies and e-commerce enable e-business firms to collect detailed consumers’ data and send Internet-based targeted advertising to their potential consumers accurately, thereby performing B2C sales. However, the perfect targeting for an e-business firm is always a challenge due to the asymmetric information between the firm and consumers. This essay starts by setting up

In order to improve the accuracy of e-commerce decision-making, this paper proposes an investment decision-making support model in e-commerce based on deep learning calculation to support the company. Investment decision-making system is not only an important means of enterprise investment and financing, but also an important way for investors to make profits. It also plays an important role in macroeconomic

Presently, significance of deep learning techniques starts to overlook the world of E-commerce with their endless customizable online shopping experience to the users. Though huge data is streaming constantly during online commerce, data imbalance problem is still unaddressed due to insufficient analytical algorithms to handle huge datasets for smooth outliers. This leads to high congestion in the

Collaborative filtering plays an important role in predicting consumer preferences in the electronic market. Most of the users purchased the products in the electronic market with the help of the Internet of Things (IoT) and Social Networks. Predicting consumer preference with the consumer’s history is a vital challenge in the recommendation systems. The researchers propose varieties of collaborative

Commodity information must be matched to HSCode so as to be quickly through customs for export. So it is particularly important to identify entity name in the commodity title of e-commerce platform quickly and accurately. Aim at the problem, an approach based on TWs-LSTM is proposed to identify the entity name of commodity. In this paper, we apply TFIDF algorithm to manipulate text corpus of the commodity

The Internet of Things (IoT) plays an important role in helping the hotel industry increase customer satisfaction while maintaining affordable costs. IoT consumers review and rate the hotels online. The ratings are based on the Value, Apartment, Site, Sanitation, Front Desk, Facility, Professional Provision, Internet, and Packing. Traditional systems that predict hotel ratings with minimum accuracy

This paper studies the online shopping situation where retailer faces uncertain demand and uncertain consumer valuations. We compare the suitability and effectiveness of two return freight policies, consumer affording return freight (C-Policy) and retailer paying return freight (R-Policy). Moreover, we explore the effect of non-defective returns, and the retailer’s optimal decisions on retail price

Sentiment analysis of online reviews is an important way of mining useful information from the Internet. Despite several advantages, the accuracy of sentiment analysis based on a domain dictionary relies on the comprehensiveness and accuracy of the dictionary. Instead of creating a domain dictionary, we propose an approach for online review sentiment classification, which uses a conditional random

Several factors like returns, undelivered and damaged goods, exchange, and environmental concern make reverse logistics (RL) inevitable in an E-commerce supply chain. In spite of understanding the importance of RL in current business scenario, most of the companies concentrate on forward logistics, while reverse flow from customer to upstream business is not receiving much interest. Considering this

This study juxtaposes brand engagement and behaviors of substantive interest in the context of eservices and utilizes Bayesian networks for an exploratory, data-driven approach. Enlisting a behavioral focus, it investigates the item-to-item relationships between brand engagement, attitudes, and conspicuous behaviors both online and offline. Two Bayesian networks were constructed from samples of city