Marketing in Online Businesses:The Case of Migrant Entrepreneurial Businesses in the UK

The study presents an empirical investigation of the marketing activities undertaken by online businesses owned by migrant entrepreneurs and is framed by the theoretical lens of entrepreneurial marketing. Key informant interviews are undertaken with 22 entrepreneurs operating online businesses in the UK and augmented by other sources of data. The study finds that the resources available to the entrepreneurs are shaped by their migrant heritage and that they draw on these resources to market their online businesses. The study also finds that, consistent with notions from entrepreneurial marketing, the online nature of their businesses allow the entrepreneurs to meet their own needs and preferences, which are also shaped by their migrant heritage. The study is important since it provides empirical evidence and a theoretically grounded understanding of how online businesses offer migrant entrepreneurs the opportunity to break out of the low growth, low margin, vacancy chain openings and enter high growth, high margin, post-industrial sectors

Is adaptation of e-advertising the way forward?

E-advertising is a multi-billion dollar industry that has shown exponential growth in the last few years. However, although the number of users accessing the Internet increases, users don’t respond positively to adverts. Adaptive e-advertising may be the key to ensuring effectiveness of the ads reaching their target. Moreover, social networks are good sources of user information and can be used to extract user behaviour and characteristics for presentation of personalized advertising. Here we present a two-sided study based on two questionnaires, one directed to Internet users and the other to businesses. Our study shows that businesses agree that personalized advertising is the best way for the future, to maximize effectiveness and profit. In addition, our results indicate that most Internet users would prefer adaptive advertisements. From this study, we can propose a new design for a system that meets both Internet users’ and businesses’ requirements

Newspaper vs. Online Advertising – Is There a Niche for Newspapers in Modern Advertising Markets?

Newspapers have experienced declining circulation figures and declining advertising revenues for several years. In particular, declining advertising figures put a threat on newspapers – this is especially severe in the US where 73% of their revenues are generated through advertising. On the advertising side many companies have expanded their advertising expenditure towards online. Consequently, there are concerns about online advertising substituting newspaper advertising – in the same way as it has been feared for many years for the readership side. Both possible effects might put a threat on the further existence of (print) newspapers. However, though the internet – compared to newspapers – offers a variety of advantages for advertising companies, substitution tendencies cannot be generalized. In particular, we argue that newspaper advertising offers great benefits for the retailing industry. Consequently, we believe that retail advertising offers a niche for regional and local newspapers that can be expected to represent a sustainable segment of complementarity within the otherwise predominantly substitutional advertising markets. The paper substantiates this argument by applying the economic theory of advertising – in particular the differentiation between persuasive/complementary and informative advertising. The latter one presents the reason for retailers to continue advertising in newspapers. Subsequently, we conclude that no complete substitution between newspaper and online advertising can be expected to take place on the advertising side in the foreseeable future. The authors like to thank the participants of the EMMA-conference in Moscow (June 2011) and the members of the research group ‘Markets & Competition’ as well as Anna Lund Jepsen for helpful comments on an earlier version of this paper.: Media economics, advertising, competition, complementation, substitution, online

Beyond Keywords and Relevance: A Personalized Ad Retrieval Framework in E-Commerce Sponsored Search

On most sponsored search platforms, advertisers bid on some keywords for their advertisements (ads). Given a search request, ad retrieval module rewrites the query into bidding keywords, and uses these keywords as keys to select Top N ads through inverted indexes. In this way, an ad will not be retrieved even if queries are related when the advertiser does not bid on corresponding keywords. Moreover, most ad retrieval approaches regard rewriting and ad-selecting as two separated tasks, and focus on boosting relevance between search queries and ads. Recently, in e-commerce sponsored search more and more personalized information has been introduced, such as user profiles, long-time and real-time clicks. Personalized information makes ad retrieval able to employ more elements (e.g. real-time clicks) as search signals and retrieval keys, however it makes ad retrieval more difficult to measure ads retrieved through different signals. To address these problems, we propose a novel ad retrieval framework beyond keywords and relevance in e-commerce sponsored search. Firstly, we employ historical ad click data to initialize a hierarchical network representing signals, keys and ads, in which personalized information is introduced. Then we train a model on top of the hierarchical network by learning the weights of edges. Finally we select the best edges according to the model, boosting RPM/CTR. Experimental results on our e-commerce platform demonstrate that our ad retrieval framework achieves good performance

Stochastic Query Covering for Fast Approximate Document Retrieval

We design algorithms that, given a collection of documents and a distribution over user queries, return a small subset of the document collection in such a way that we can efficiently provide high-quality answers to user queries using only the selected subset. This approach has applications when space is a constraint or when the query-processing time increases significantly with the size of the collection. We study our algorithms through the lens of stochastic analysis and prove that even though they use only a small fraction of the entire collection, they can provide answers to most user queries, achieving a performance close to the optimal. To complement our theoretical findings, we experimentally show the versatility of our approach by considering two important cases in the context of Web search. In the first case, we favor the retrieval of documents that are relevant to the query, whereas in the second case we aim for document diversification. Both the theoretical and the experimental analysis provide strong evidence of the potential value of query covering in diverse application scenarios

Determinants in the on-line distribution of digital content: an exploratory analysis

This article shows the phases – and discusses the results – of an empirical analysis addressing the legal business models that are adopted online to distribute digital content