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Social media have attracted attention as an information channel for content generated in heterogeneous internet services. Focusing on social media platforms, the purpose of this paper is to examine the factors behind social transmission with content crossover from other services through hypertext link (URL). The authors investigate the effects of source influence and peer referrals on diffusion outcome and address their variations in the case of content crossover.

The authors use a Poisson regression model due to the discrete nature of the dependent variable. The authors conduct an empirical study using 233 million real transaction data generated by 1,203,196 Korean users of Twitter.

Source influence and peer referral have a positive impact on cascade size in the content dissemination process. In the case of content crossover, the impact of source influence decreases. However, the impact of peer referrals increases in the process of external content dissemination.

The authors demonstrate source and peer effects on content diffusion and that these effects vary when shared content is linked from an external service by a URL.

The findings indicate that firms that wish to diffuse information through social media or enter the social media with new services to provide new ways of creating and sharing content should understand the nature of the social transmission process.

Given the growing popularity of social media, particularly SNSs with online social networks as information channels, the authors first consider online social transmission as a user-driven diffusion process. Based on social factors in the diffusion process, the authors derive source and peer effects on the social transmission process.

With the increasing influence of online consumer reviews (OCRs) on a consumer's decision making, online sellers have begun to embed the OCRs in their advertisements (OEAs). This study has the following two research objectives: first, to investigate the effects of two types of (OCRs vs OEAs) on consumers' purchase intention from an informational influence perspective; second, to investigate the effects of OCRs from a credibility perspective.

The data for this study are obtained from a two‐way factorial experimental research design. The factors included are the type of OCRs and the trust level of online shopping malls. In addition, PLS test is used to understand the underlying effects of trust in online shopping malls, credibility of OCRs/OEAs, and consumers' purchase intentions.

The results show that OCRs are more influenced by trust in online shopping malls than OEAs. The greater the perceived credibility of OCRs among potential consumers, the higher is the purchase intention. When the trust in online shopping malls is high, consumers' purchase intentions influenced by OCRs are more favorable than those influenced by OEAs.

This study is an initial consumer endorsement research that uses OCRs to extend the trust transfer theory and extends the interpersonal online trust perspective. For practitioners, this study is useful in determining which type of OCRs is useful for marketing, depending on the trust in online shopping malls. Moreover, the results of this study could aid in the development of an e‐commerce strategy using OCRs.

Bankruptcy is a financial failure of a business or an organization. Different kinds of bankruptcy prediction techniques are proposed to predict it. But, they are restricted as techniques in predicting the bankruptcy and not addressing the associated activities like acquiring the suitable data and delivering the results to the user after processing it. This situation demands to look for a comprehensive solution for predicting bankruptcy with intelligence. The paper aims to discuss these issues.

To model Business Intelligence (BI) solution for BP the concept of reference model is used. A Reference Model for Business Intelligence to Predict Bankruptcy (RMBIPB) is designed by applying unit operations as hierarchical structure with abstract components. The layers of RMBIPB are constructed from the hierarchical structure of the model and the components, which are part of the reference model. In this model, each layer is designed based on the functional requirements of the Business Intelligence System (BIS).

This reference model exhibits the non functional software qualities intended for the appropriate unit operations. It has flexible design in which techniques are selected with minimal effort to conduct the bankruptcy prediction. The same reference model for another domain can be implemented with different kinds of techniques for bankruptcy prediction.

This model is designed using unit operations and the software qualities exhibited by RMBIPB are limited by unit operations. The data set which is applied in RMBIPB is limited to Indian banks.

A comprehensive bankruptcy prediction model using BI with customized reporting.

Social relationships on the internet through the emergence of Web 2.0 applications created new opportunities for business. This is mainly because of the growth of social networking sites, which has also developed e‐commerce. The current development in e‐commerce opened a new stream, entitled social commerce, which is using social technologies to create an environment for generating social interactions. These social interactions can drive online social support in e‐commerce, which in turn is creating trust and an increased intention to use social commerce.

This research used social support theory and related theories on intention to use to propose a theoretical framework for the adoption of social commerce.

The model predicts that forums and communities, ratings, reviews, referrals and recommendations are helping to introduce new business plans for e‐vendors. The model also shows trust is an on‐going issue in e‐commerce and can be built through social commerce constructs.

There is limited research in the area of social commerce which this study seeks to redress. This study proposes a new model which can be extended by other constructs. However, the research needs to empirically test the constructs of the proposed model and their relationship.

This paper introduces social commerce constructs, namely; recommendations and referrals, forums and communities and rating and reviews. The bases of the model proposed in this research are IT adoption and literature in the area such as PU and intention to buy or trust. These highlight the key role of ICT in the behaviour of online customers. This can be a development for e‐commerce adoption models and the results signify that IS has a reference discipline for the behaviour of online consumers. This is an issue in marketing where not enough attention is paid to the importance of IT and IS.

India’s retail sector is going through a significant transitional period with the internet as a new distribution channel becoming more common. Given the barriers to adoption, the purpose of this paper is to understand the role played by trusting beliefs when engaging with an online retailer. In the Indian market, online vending is expected to increase at a rate of 35 per cent per annum, and by understanding trusting beliefs retailers will be able to develop their market share by developing appropriate and/or innovative strategies.

The work is based on a sample of more than 200 internet customers in India. In understanding the data and the relationships that emerged from the modelling, the authors used a range of tools to analyse the data, including CFA and structural equation modelling. The authors also used descriptive statistics to provide a holistic overview of response profiles.

The study reveals that trusting beliefs are negatively influenced by an uncertainty avoidance culture and positively influenced by a firm’s image and a customer’s price awareness. Moreover, purchase intentions (PIs) are significantly enhanced by trusting beliefs in an online environment. Hence, it leads us to conclude that PIs can be augmented by facilitating and ensuring good quality service by placing special emphasis on timeliness, accuracy and conditions of the order, security and privacy paradigms, aftersales services, etc.

As can be seen, the internet is an emergent tool for retailers in India. By understanding trusting beliefs, retailers will be able to better understand customers’ behaviour and thus design management strategies accordingly. Although this is likely to take more than a decade, as internet retailing becomes embedded it may have a detrimental effect on the historical channel to market, thus altering the country’s retail landscape which is currently dominated by small retailers.

The work’s findings are insightful for those seeking to maximize the opportunities presented by the internet as a channel to market. The works shows how the channel is influenced and thus how it can be managed. In making the contribution the authors provide guidance in terms of operational activity to engage with potential customers.

This paper examines trusting beliefs when using the internet as a channel to market and in doing so it makes a new contribution because it establishes links with culture and other factors. For the research venue the authors use a developing market and therefore the findings are applicable to markets with similar characteristics.