Search results

Google commands approximately 70 per cent of search market share worldwide, resulting in businesses investing heavily in search engine advertising on Google to target potential customers. Recently, Google changed the way in which content and ads were displayed on the search engine results page. This reshuffling of content and ads is expected to affect the advertisers who advertise on Google and/or use it to drive traffic to their websites. The purpose of this study is to analyze the impact of these changes on various stakeholders.

Data have been collected from various sources on the internet including blogs and discussion forums. Netnography has been used as it allows a detailed evaluation of the consumers’ needs, wants and choices in a virtual space.

The average cost-per-click for ads on the top positions is expected to increase. Advertisers whose ads usually occupy the lower positions would be adversely affected. To counter this, more emphasis should be placed on ad extensions and on product listing ads. In addition, organizations would benefit from increased efforts on search engine optimization.

A variety of coping strategies have been developed that can help marketers to successfully navigate through the change, including the use of ad extensions and the use of product listing ads.

This practice-focused paper offers guidelines for digital marketers to use sponsored search more effectively as part of their arsenal in light of some important changes recently made by Google. The potential of netnography as a research methodology has also been expanded by using it in a novel setting and in drawing up actionable insights.

The aim of this paper is to examine the impact of three main technologies on converting browsers into customers: impact of review rating (location rating and service rating), recommendation and search listings.

This paper estimates conversion rate model parameters using a quasi-likelihood method with the Bernoulli log-likelihood function and parametric regression model based on the beta distribution.

The results show that a high rank in search listings, a high number of recommendations and location rating have a significant and positive impact on conversion rates. However, service rating and star rating do not have a significant effect on conversion rate. Furthermore, room price and hotel size are negatively associated with conversion rate. It was also found that a high rank in search listings, a high number of recommendations and location rating increase online hotel bookings. Furthermore, it was found that a high number of recommendations increase the conversion rate of hotels with low ranks.

The findings show that hotels’ location ratings are more important than both star and service ratings for the conversion of visitors into customers. Thus, hotels that are located in convenient locations can charge higher prices. The results may also help entrepreneurs who are planning to open new hotels to forecast the conversion rates and demand for specific locations. It was found that a high number of recommendations help to increase the conversion rate of hotels with low ranks. This result suggests that a high numbers of recommendations mitigate the adverse effect of a low rank in search listings on the conversion rate.

This paper contributes to the understanding of the drivers of conversion rates in online channels for the successful implementation of hotel marketing.

The purpose of this paper is to conceptualize a model for sponsored search advertising by incorporating a number of factors which affect the performance of these ads.

The authors draw upon the professional experience and practitioner as well as academic literature to build and analyze the model. Propositions have been forwarded to delineate the various relationships at work in a sponsored search process.

The extant literature on this topic has so far been unable to provide a holistic overview. The paper offers propositions for explaining the role of various factors like the ad rank, branding, role of ad extensions and how impact of these factors may be sensitive to the device used for search.

This work is derived primarily from practice. It is hope that after due empirical validation, advertisers, users as well as search engines will benefit from this stream of research.

This is one of the first works to analyze a sponsored search ad at a micro level. It brings into focus one of the largely unexplored facets of sponsored search advertising.

The user interface, in broad terms, is the medium through which the user and the information come together. The types of searches a public access catalog (PAC) can perform are defined by the indexing strategy and retrieval software. The way the user's interest is communicated to the retrieval software and the way the results are communicated to the user is, by a more narrow definition, the interface software. Both the kinds of searches that can be performed by a variety of CD‐ROM PACs and how their workstations are used to accomplish the searches are considered.

Web‐snippet clustering has recently attracted a lot of attention as a means to provide users with a succinct overview of relevant results compared with traditional search results. This paper seeks to research the building of a web‐snippet clustering system, based on a mixed clustering method.

This paper proposes a mixed clustering method to organise all returned snippets into a hierarchical tree. The method accomplishes two main tasks: one is to construct the cluster labels and the other is to build a hierarchical tree.

Five measures were used to measure the quality of clustering results. Based on the results of the experiments, it was concluded that the performance of the system is better than current commercial and academic systems.

A high performance system is presented, based on the clustering method. A divisive hierarchical clustering algorithm is also developed to organise all returned snippets into a hierarchical tree.

This paper aims to study how buyers' gender and risk proclivity, and the time remaining in an internet auction, influence whether buyers buy at fixed prices or bid.

The study is based on a simulated internet auction. Participants choose between bidding in an auction and buying at a fixed price. Data are analyzed using a logistic regression model. The results from the laboratory study are validated with data from eBay.com.

Female participants’ odds of choosing the buy‐it‐now (BIN) option are higher than their odds of bidding in an auction (BID) when less time is remaining in an auction. Contrarily, for males, when less time is remaining, BID is preferred over BIN. Unexpectedly, when substantial time is remaining, males have greater odds of choosing BIN over BID except when they are high risk‐seekers. Simulation results correspond closely with eBay data.

The paper shows that not only do gender differences manifest themselves in ways that are to be expected, such as females being more risk‐averse than males, but that competitiveness among males may lead to an uncharacteristic choice to buy at fixed prices if substantial time is remaining in an auction. Furthermore, the latent competitive nature of females is revealed by secondary research. Finally, the research validates laboratory results with field data to practice methodological triangulation.

A comparison of determinants of bidding versus buying at fixed prices is missing from the extant literature. The present study fills this gap.

This paper aims to present the Modelery, a platform for collaborative repository to support model-based software development. The Modelery is a Web platform, composed both by a Web page and Web services for interoperability.

By performing a study in the existing platforms, it was possible to achieve a set of issues to tackle. The issues enabled the possibility to define a set of requirements that allowed the authors to design a new platform, and to perform a model-driven software development process, which started from the requirements until reaching the final software solution.

With this work, it was possible to perform a survey on the currently available artifacts repositories, categorize them and identify their shortcomings. This was essential to define the set of requirements for a new platform to overcome the identified issues. This process leads to a platform able to improve the currently available solutions, and validated in the scientific community. In this paper, the authors also explore the applications of the repository. First, they use the Modelery to replace an older model’s repository. Second, they have enabled the communication between other tools and the Modelery via Web services.

This work presents a new Web repository for software artifacts aimed at supporting researchers and software developers. The presented platform is an improvement over other platforms on the integration of artifacts repository, social functionalities and scientific publications integration. The authors conclude this paper by comparing the achieved platform in terms of functionalities, against the other analyzed platforms.