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

A comparison of social media marketing between B2B, B2C and mixed business models

This paper explores the implicit assumption in the growing body of literature that social media usage is fundamentally different in business-to-business (B2B) companies than in the extant business-to-consumer (B2C) literature. Sashi’s (2012) customer engagement cycle is utilized to compare B2B, B2C, Mixed B2B/B2C and B2B2C business model organizational practices in relation to social media usage, importance, and its perceived effectiveness as a communication channel. Utilizing 449 responses to an exploratory panel based survey instrument, we clearly identify differences in social media marketing usage and its perceived importance as a communications channel. In particular we identify distinct differences in the relationship between social media importance and the perceived effectiveness of social media marketing across business models. Our results indicate that B2B social media usage is distinct from B2C, Mixed and B2B2C business model approaches. Specifically B2B organizational members perceive social media to have a lower overall effectiveness as a channel and identify it as less important for relationship oriented usage than other business models

Towards Economic Models for MOOC Pricing Strategy Design

MOOCs have brought unprecedented opportunities of making high-quality courses accessible to everybody. However, from the business point of view, MOOCs are often challenged for lacking of sustainable business models, and academic research for marketing strategies of MOOCs is also a blind spot currently. In this work, we try to formulate the business models and pricing strategies in a structured and scientific way. Based on both theoretical research and real marketing data analysis from a MOOC platform, we present the insights of the pricing strategies for existing MOOC markets. We focus on the pricing strategies for verified certificates in the B2C markets, and also give ideas of modeling the course sub-licensing services in B2B markets

An Architecture for Information Commerce Systems

The increasing use of the Internet in business and commerce has created a number of new business opportunities and the need for supporting models and platforms. One of these opportunities is information commerce (i-commerce), a special case of ecommerce focused on the purchase and sale of information as a commodity. In this paper we present an architecture for i-commerce systems using OPELIX (Open Personalized Electronic Information Commerce System) [11] as an example. OPELIX provides an open information commerce platform that enables enterprises to produce, sell, deliver, and manage information products and related services over the Internet. We focus on the notion of information marketplace, a virtual location that enables i-commerce, describe the business and domain model for an information marketplace, and discuss the role of intermediaries in this environment. The domain model is used as the basis for the software architecture of the OPELIX system. We discuss the characteristics of the OPELIX architecture and compare our approach to related work in the field

Digital Marketing for Sustainable Growth: Business Models and Online Campaigns Using Sustainable Strategies

t: In recent years, digital marketing has transformed the way in which companies communicate with their customers around the world. The increase in the use of social networks and how users communicate with companies on the Internet has given rise to new business models based on the bidirectionality of communication between companies and Internet users. Digital marketing, new business models, online advertising campaigns, and other digital strategies have gathered user opinions and comments through this new online channel. In this way, companies have started to see the digital ecosystem as not only their present, but also as their future. From this long-term perspective, companies are concerned about sustainability and the growth of their business models. There are new business models on the Internet that support social causes, new platforms aimed at supporting social and sustainable projects, and digital advertising campaigns promoting sustainability. The overarching aim of this Special Issue was to analyze the development of these new strategies as well as their influence on the sustainability of digital marketing strategies. Therefore, we aimed to analyze how companies adopt these new technologies in a digital environment that is increasingly concerned with the sustainability of business models and actions on the Internet

Web Data Extraction, Applications and Techniques: A Survey

Web Data Extraction is an important problem that has been studied by means of different scientific tools and in a broad range of applications. Many approaches to extracting data from the Web have been designed to solve specific problems and operate in ad-hoc domains. Other approaches, instead, heavily reuse techniques and algorithms developed in the field of Information Extraction. This survey aims at providing a structured and comprehensive overview of the literature in the field of Web Data Extraction. We provided a simple classification framework in which existing Web Data Extraction applications are grouped into two main classes, namely applications at the Enterprise level and at the Social Web level. At the Enterprise level, Web Data Extraction techniques emerge as a key tool to perform data analysis in Business and Competitive Intelligence systems as well as for business process re-engineering. At the Social Web level, Web Data Extraction techniques allow to gather a large amount of structured data continuously generated and disseminated by Web 2.0, Social Media and Online Social Network users and this offers unprecedented opportunities to analyze human behavior at a very large scale. We discuss also the potential of cross-fertilization, i.e., on the possibility of re-using Web Data Extraction techniques originally designed to work in a given domain, in other domains.Comment: Knowledge-based System