Search results for "online store"

showing 7 items of 7 documents

HTTP-level e-commerce data based on server access logs for an online store

2020

Abstract Web server logs have been extensively used as a source of data on the characteristics of Web traffic and users’ navigational patterns. In particular, Web bot detection and online purchase prediction using methods from artificial intelligence (AI) are currently key areas of research. However, in reality, it is hard to obtain logs from actual online stores and there is no common dataset that can be used across different studies. Moreover, there is a lack of studies exploring Web traffic over a longer period of time, due to the unavailability of long-term data from server logs. The need to develop reliable models of Web traffic, Web user navigation, and e-customer behaviour calls for …

Web serverDatabaseaccess logComputer Networks and CommunicationsComputer sciencebusiness.industry020206 networking & telecommunicationselectronic commerce02 engineering and technologyE-commerceWeb trafficcomputer.software_genreWeb trafficWeb serveronline store0202 electrical engineering electronic engineering information engineeringKey (cryptography)020201 artificial intelligence & image processingHTTP trafficUnavailabilitybusinesscomputerData ArticleComputer Networks
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Application of neural network to predict purchases in online store

2016

A key ability of competitive online stores is effective prediction of customers’ purchase intentions as it makes it possible to apply personalized service strategy to convert visitors into buyers and increase sales conversion rates. Data mining and artificial intelligence techniques have proven to be successful in classification and prediction tasks in complex real-time systems, like e-commerce sites. In this paper we proposed a back-propagation neural network model aiming at predicting purchases in active user sessions in a Web store. The neural network training and evaluation was performed using a set of user sessions reconstructed from server log data. The proposed neural network was abl…

Web usage miningService strategyRecallArtificial neural networkWeb miningbusiness.industryComputer scienceneural networklog file analysisE-commerceServer logMachine learningcomputer.software_genreartificial intelligenceSet (abstract data type)Web miningonline storeKey (cryptography)e-commerceWeb storeArtificial intelligencebusinesscomputer
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Empiirinen tutkimus brändikokemuksen vaikutuksesta verkkokauppaympäristöjen käyttäjäkokemukseen ja käyttöaikeeseen

2015

Tutkielmassa tarkasteltiin brändikokemuksen vaikutusta verkkokauppaympäristöjen käyttäjäkokemukseen ja käyttöaikeeseen. Brändikokemusta tarkasteltiin kahden ulottuvuuden kautta: brändityytyväisyyden ja brändiluottamuksen. Käyttäjäkokemusta tarkasteltiin käytännöllisten (frustraation, kompetenssin ja hallinnan tunteen) ja esteettisten (kauneuden ja mielikuvituksettomuuden) tunteiden näkökulmista. Brändikokemuksen vaikutusta verkkokauppaympäristöjen käyttäjäkokemukseen ja käyttöaikeeseen tutkittiin kahdessa kokeellisessa tutkimuksessa. Tutkimukset toteutettiin osana Jyväskylän yliopiston käyttäjäpsykologian laboratoriossa tehtyä verkkokauppaympäristöjen käyttäjäkokemusta käsittelevää tutkimus…

bränditbrandsverkkokauppauser experienceonline storeluottamusteknologiaasiakaskokemusempirical researchemotional stateEmpiirinen tutkimuskäyttäjäkokemus
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The Effects of Individual Values on Online Shopping Spending

2019

Although individual values have been found as important antecedents of human behaviour, their effects on online shopping behaviour remain poorly understood. In this study, we aim to address this gap in prior research by examining the effects of individual values on both total online shopping spending and the specific types of online shopping spending in terms of orders made (1) with traditional computers versus mobile devices, (2) from businesses versus other consumers, and (3) from domestic versus foreign online stores. The examination is based on the data from 565 Finnish online shoppers, which was collected via an online survey between February 2019 and March 2019 and is analysed by usin…

foreign online storesostokäyttäytyminenverkkokauppabusiness-to-consumerAdvertisingmobiilikauppakuluttajakäyttäytyminendomestic online storesonline shopping spendingmobile online shoppingarvot (käsitykset)individual valuesconsumer-to-consumeronline surveyBusinessConsumer-to-businessFinlandsurvey-tutkimus
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The Cross-Channel Effects of In-Store Customer Experience in the Case of Omnichannel Fashion Retailing in Finland

2023

Although omnichannel retailing has emerged as a popular research topic in academic research, there are still gaps in our understanding of this phenomenon. One such gap concerns omnichannel customer experience and particularly the cross-channel or spillover effects of how customer experience in one channel may affect customer behaviour not only in that specific channel but also in the other channels of the same retailer. In this study, we aim to address this gap by examining how customer experience in the offline channel affects customer behaviour in both the offline and the online channel, more specifically how in-store customer experience affects both brick-and-mortar store and online stor…

kivijalkaliikkeetvähittäiskauppaomnichannel fashion retailingasiakastyytyväisyysostokäyttäytyminenverkkokauppacustomer satisfactionbrick-and-mortar store visit intentionvaateliikkeetonline store visit intentionasiakaskokemusmonikanavaisuusin-store customer experienceFinland
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Identifying the Sales Patterns of Online Stores with Time Series Clustering

2018

Electronic commerce, especially in the business-to-consumer (B2C) context, has for years been a popular research topic in information systems (IS). However, the prior research on the topic has traditionally been dominated by the consumer focus instead of the business focus of online stores. For example, whereas various segmentations exist for online consumers based on their purchase behaviour, no such segmentations have been developed for online stores based on their sales patterns. In this study, our objective is to address this gap in prior research by identifying the most typical sales patterns of online stores operating in the B2C context. By using self-organising maps (SOM) to analyse …

verkkokauppa (verkkoliiketoiminta)Series (mathematics)Computer scienceverkkokauppabusiness-to-consumercomputer.software_genreB2Conline storesklusteritsegmentointisales patternsSegmentationData miningCluster analysiscomputertime series clustering
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Identifying the Sales Patterns of Online Stores with Self-Organising Maps on Time Series Data

2018

Electronic commerce, especially in the business-to-consumer (B2C) context, has for years been a popular research topic in information systems (IS). However, the prior research on the topic has traditionally been dominated by the consumer focus instead of the business focus of online stores. For example, whereas various segmentations exist for online consumers based on their purchase behaviour, no such segmentations have been developed for online stores based on their sales patterns. In this study, our objective is to address this gap in prior research by identifying the most typical sales patterns of online stores operating in the B2C context. By using self-organising maps (SOM) to analyse …

verkkokauppa (verkkoliiketoiminta)verkkokauppaaikasarjatbusiness-to-consumerkotitaloudetneuroverkotB2Conline storesself-organising mapssegmentointikuluttajakauppamyyntimallitsales patternskuluttajat
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