Using webcrawling of publicly available websites to assess E-commerce relationships

We investigate e-commerce success factors concerning their impact on the success of commerce transactions between businesses companies. In scientific literature, many e-commerce success factors are introduced. Most of them are focused on companies' website quality. They are evaluated concerning companies' success in the business-to- consumer (B2C) environment where consumers choose their preferred e-commerce websites based on these success factors e.g. website content quality, website interaction, and website customization. In contrast to previous work, this research focuses on the usage of existing e-commerce success factors for predicting successfulness of business-to-business (B2B) ecommerce. The introduced methodology is based on the identification of semantic textual patterns representing success factors from the websites of B2B companies. The successfulness of the identified success factors in B2B ecommerce is evaluated by regression modeling. As a result, it is shown that some B2C e-commerce success factors also enable the predicting of B2B e-commerce success while others do not. This contributes to the existing literature concerning ecommerce success factors. Further, these findings are valuable for B2B e-commerce websites creation

An Open Source Based Data Warehouse Architecture to Support Decision Making in the Tourism Sector

In this paper an alternative Tourism oriented Data Warehousing architecture is proposed which makes use of the most recent free and open source technologies like Java, Postgresql and XML. Such architecture's aim will be to support the decision making process and giving an integrated view of the whole Tourism reality in an established context (local, regional, national, etc.) without requesting big investments for getting the necessary software.Tourism, Data warehousing architecture

Effectiveness of Corporate Social Media Activities to Increase Relational Outcomes

This study applies social media analytics to investigate the impact of different corporate social media activities on user word of mouth and attitudinal loyalty. We conduct a multilevel analysis of approximately 5 million tweets regarding the main Twitter accounts of 28 large global companies. We empirically identify different social media activities in terms of social media management strategies (using social media management tools or the web-frontend client), account types (broadcasting or receiving information), and communicative approaches (conversational or disseminative). We find positive effects of social media management tools, broadcasting accounts, and conversational communication on public perception

The macro-environment for liquid biofuels in the US mass media, science and government

The purpose of this study is to investigate under which dimensions the macro-environment for liquid biofuels has been structured during time, respectively by science, mass media, and government in Germany, and how these three social expressions related to each other. Research was carried out on German official government documents, mass media news, and scientific papers on the topic ‘liquid biofuels’. Text Mining was used to extract knowledge from their content. The results indicate that in configurating the macro-environment for liquid biofuels there is some degree of proximity between media and government, less between media and science, and the least between government and scienc

A Regression Tree Based Exploration of the Impact of Information Technology Investments on Firm Level Productivity

The issue as to whether investments in information technology (IT) contribute significantly to organizational productivity has been of major concern for many years, and various studies have lead to seemingly contradictory results. In this paper, we analyze the relationship between IT investments and firm level productivity using regression trees (RT). Use of this data mining technique represents a novel approach to identifying elements of this relationship as most previous studies have primarily used econometrics-based techniques. While the use of traditional techniques has provided valuable results, our RT-based analysis revealed additional findings that were not identified in the previous studies. For example unlike the econometric-based studies that identify a uniform impact of IT investments on productivity, our RT-based analysis suggests that IT has an impact on productivity only when Non-IT Labor expenses are within the interior interval. Also, even within this range, the impact of IT is not uniform

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research