Search Results (8)

Online paid advertising is a dynamic form of online marketing that requires precision and a quick response to market changes. Automated tools are used to greatly simplify the process of creating and managing Pay-Per-Click (PPC) campaigns. The purpose of this research is to evaluate the impact of implementing an automated PPC management tool (Dotidot) on campaign performance in a travel agency compared with standard Google Ads campaigns. A structured multi-criteria procedure is first applied to select the most suitable tool for the Czech and Slovak markets. The core contribution of the paper is the observational case study of Dotidot and its performance comparison. The subject of the research is a comparative analysis of three PPC automated tools: Conviu, Dotidot, and BlueWinston. The significance of this topic lies in highlighting the relatively new possibilities of digital marketing and choosing the right tool for using automation. This research can also stimulate other researchers in this field and expand knowledge. The analysis is carried out using the method of systematic comparison based on established criteria, the result of which is a recommendation of the preferred tool and a brief discussion of its implementation options. The analyzed tools are used mainly on the Czech and Slovak markets and are oriented towards e-commerce (electronic commerce). In addition to e-commerce, a case study of the use of digital promotion in sports organizations is also presented. The research results in a systematic comparison of Conviu, Dotidot, and BlueWinston tools according to predefined criteria. The research also includes a brief discussion on the possibilities of implementing the recommended tool in practice, as well as an assessment of its benefits and limitations. Full article

Online advertising is a marketing approach that uses numerous online channels to target potential customers for businesses, brands, and organizations. One of the most serious threats in today’s marketing industry is the widespread attack known as click fraud. Traffic statistics for online advertisements are artificially inflated in click fraud. Typical pay-per-click advertisements charge a fee for each click, assuming that a potential customer was drawn to the ad. Click fraud attackers create the illusion that a significant number of possible customers have clicked on an advertiser’s link by an automated script, a computer program, or a human. Nevertheless, advertisers are unlikely to profit from these clicks. Fraudulent clicks may be involved to boost the revenues of an ad hosting site or to spoil an advertiser’s budget. Several notable attempts to detect and prevent this form of fraud have been undertaken. This study examined all methods developed and published in the previous 10 years that primarily used artificial intelligence (AI), including machine learning (ML) and deep learning (DL), for the detection and prevention of click fraud. Features that served as input to train models for classifying ad clicks as benign or fraudulent, as well as those that were deemed obvious and with critical evidence of click fraud, were identified, and investigated. Corresponding insights and recommendations regarding click fraud detection using AI approaches were provided. Full article

Network data maps constitute a practical visual data-classification tool in structuring complex research literature endowed with multiple economic, social, and psychological relationships, as happens with the evolution of digital entrepreneurship as a research topic in the COVID-19 era. Has the digitalization process, accelerated by COVID-19, influenced entrepreneurship by strengthening digital entrepreneurship worldwide? Is innovation the most-cited keyword in the digital entrepreneurship-related literature published in the SCOPUS database from 2001 onwards? Does pay-per-click as an instrument for digital entrepreneurship management foster sustainable development? To answer these questions, we combine a software tool for constructing and visualizing bibliometric networks, VOSviewer version 1.6.18, with the SCOPUS bibliographic data tool to investigate the keyword ‘digital entrepreneurship.’ As a result, we obtained 2154 documents in the SCOPUS database for 2001–2022 in all 27 subject areas, of which 1055 documents were from BMA (Business, Management, and Accounting) and EEF (Economics, Econometrics, and Finance) areas. Regarding the keyword ‘pay-per-click,’ we obtained 63 papers for 2005–2022 from BMA and EEF subject areas. We find that there is a growing interest in researching digital entrepreneurship led by authors from the European Union and followed by the United States; innovation is the most-cited keyword in documents related to digital entrepreneurship, and researchers worldwide are giving more importance to the process of digitalization compared to the link between educational, economic, and technological factors and digital entrepreneurship. Regarding ‘pay-per-click,’ we find that the literature published on this topic is broadly based on the US, and given the small number of publications on this issue, it is a research area with great potential to investigate and publish about it. Full article

This paper investigates consumers’ willingness to pay (WTP) for click-and-collect grocery services. In particular, we analyze whether the time-pressed are willing to pay higher fees. We exploit a survey among 572 customers of two Belgian supermarket chains—both users and non-users. We test our model for three (increasingly narrow) samples: all respondents, respondents with a non-zero WTP, and current users. Our key finding relates to the latter sample. Surprisingly, if we use the WTP measure put forward in the literature, the answer to our research question is ‘no’: we find no significant relationship between users’ perceived time pressure and the maximum service cost per order they are willing to pay. However, on closer scrutiny this ‘no’ in fact means ‘yes’: our finding implies that in the face of increasing fees the time-pressed are willing to maintain their current, higher order frequency for as long as the other users. The maximum total cost they are willing to incur over a given period is thus higher. This said, the absence of a relationship between time pressure and the WTP per order does limit the opportunities for e-grocers to price discriminate, as is suggested in the literature. A further complication is that we find no clear pattern between perceived time pressure and the use of specific time slots. Full article

As digitalization is gradually transforming reality into Big Data, Web search engines and recommender systems are fundamental user experience interfaces to make the generated Big Data within the Web as visible or invisible information to Web users. In addition to the challenge of crawling and indexing information within the enormous size and scale of the Internet, e-commerce customers and general Web users should not stay confident that the products suggested or results displayed are either complete or relevant to their search aspirations due to the commercial background of the search service. The economic priority of Web-related businesses requires a higher rank on Web snippets or product suggestions in order to receive additional customers. On the other hand, web search engine and recommender system revenue is obtained from advertisements and pay-per-click. The essential user experience is the self-assurance that the results provided are relevant and exhaustive. This survey paper presents a review of neural networks in Big Data and web search that covers web search engines, ranking algorithms, citation analysis and recommender systems. The use of artificial intelligence (AI) based on neural networks and deep learning in learning relevance and ranking is also analyzed, including its utilization in Big Data analysis and semantic applications. Finally, the random neural network is presented with its practical applications to reasoning approaches for knowledge extraction. Full article

Sponsored search advertising has grown rapidly since the last decade and is now a significant revenue source for search engines. To ameliorate revenues, search engines often set fixed or variable reserve price to in influence advertisers’ bidding. This paper studies and compares two pricing mechanisms: the generalized second-price auction (GSP) where the winner at the last ad position pays the larger value between the highest losing bid and reserve price, and the GSP with a posted reserve price (APR) where the winner at the last position pays the reserve price. We show that if advertisers’ per-click value has an increasing generalized failure rate, the search engine’s revenue rate is quasi-concave and hence there exists an optimal reserve price under both mechanisms. While the number of advertisers and the number of ad positions have no effect on the selection of reserve price in GSP, the optimal reserve price is affected by both factors in APR and it should be set higher than GSP. Full article

With an increasing pervasiveness, prevalence and severity of cybercrimes, various metrics, measures and statistics have been developed and used to measure various aspects of this phenomenon. Cybercrime-related data, metrics, and information, however, pose important and difficult dilemmas regarding the issues of reliability, validity, comparability and practical utility. While many of the issues of the cybercrime economy are similar to other underground and underworld industries, this economy also has various unique aspects. For one thing, this industry also suffers from a problem partly rooted in the incredibly broad definition of the term “cybercrime”. This article seeks to provide insights and analysis into this phenomenon, which is expected to advance our understanding into cybercrime-related information. Full article

There is considerable excitement about the notion of 'Web 2.0', particularly among Internet businesspeople. In contrast, there is an almost complete lack of formal literature on the topic. It is important that movements with such energy and potential be subjected to critical attention, and that industry and social commentators have the opportunity to draw on the eCommerce research literature in formulating their views. This paper assesses the available information about Web 2.0, with a view to stimulating further work that applies existing theories, proposes new ones, observes and measures phenomena, and tests the theories. The primary interpretation of the concept derives from marketers, but the complementary technical and communitarian perspectives are also considered. A common theme derived from the analysis is that of 'syndication' of content, advertising, storage, effort and identity. Full article