Importance-performance analysis for internet stores: a system based on publicly available panel data
Managing Intellectual Capital and Innovation for Sustainable and Inclusive Society: Proceedings of the MakeLearn and TIIM Joint International Conference 27–29 May 2015, Bari, Italy
We describe a new recommender system for the Russian interactive radio network FMhost. The underlying model combines collaborative and user-based approaches. The system extracts information from tags of listened tracks for matching user and radio station profiles and follows an adaptive online learning strategy based on user history. We also provide some basic examples and describe the quality of service evaluation methodology.
We describe a new recommender system for the Russian interactive radio network FMhost. The new recommender model combines collaborative and user-based approaches. The system extracts information from tags of listened tracks for matching user and radio station profiles and follows an adaptive online learning strategy based on user history. We also provide some basic examples and describe the quality of service evaluation methodology.
Measuring indirect importance of various attributes is a very common task in marketing analysis for which researchers use correlation and regression techniques. We have listed and illustrated some common problems with widely used latent importance measures. A more theoretically sound approach – the Shapley Value decomposition – was applied to a rich data set of US internet stores. The use of store-level data instead of respondent-level data allowed us to reveal the factors, which are powerful in explaining, why some stores have higher rates of willingness to make repeat purchases than the others. By confronting the indirect importance and performance measures for three different internet stores, we have revealed strengths, weaknesses, attributes that the company should bring customers’ attention to and attributes improvement of which is not of a high priority.
In this work the demand for the incoming tourism in the Russian Federation is modeling. The panel data for 16 countries - the basic sources of tourist streams - and the period with 2000 for 2009 are used. Modeling is spent separately for each of 10 tourist zones of Russia. In quality a determinant of demand there are considered a total national product in a country of origin, the exchange rate, transport charges, cost of residing, lag of the demand variable and the fictitious variables reflecting influence of shocks in quality a determinants of demand. The received estimations of dynamic models of demand correspond to expectations, are statistically significant and can be useful in practice of planning of development of entrance tourism in various municipal formations and regions of Russia.
Smoking is a problem, bringing signifi cant social and economic costs to Russiansociety. However, ratifi cation of the World health organization Framework conventionon tobacco control makes it possible to improve Russian legislation accordingto the international standards. So, I describe some measures that should be taken bythe Russian authorities in the nearest future, and I examine their effi ciency. By studyingthe international evidence I analyze the impact of the smoke-free areas, advertisementand sponsorship bans, tax increases, etc. on the prevalence of smoking, cigaretteconsumption and some other indicators. I also investigate the obstacles confrontingthe Russian authorities when they introduce new policy measures and the public attitudetowards these measures. I conclude that there is a number of easy-to-implementanti-smoking activities that need no fi nancial resources but only a political will.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.