6 resultados para Web Search Behaviour
em Brock University, Canada
Resumo:
This study examines the efficiency of search engine advertising strategies employed by firms. The research setting is the online retailing industry, which is characterized by extensive use of Web technologies and high competition for market share and profitability. For Internet retailers, search engines are increasingly serving as an information gateway for many decision-making tasks. In particular, Search engine advertising (SEA) has opened a new marketing channel for retailers to attract new customers and improve their performance. In addition to natural (organic) search marketing strategies, search engine advertisers compete for top advertisement slots provided by search brokers such as Google and Yahoo! through keyword auctions. The rationale being that greater visibility on a search engine during a keyword search will capture customers' interest in a business and its product or service offerings. Search engines account for most online activities today. Compared with the slow growth of traditional marketing channels, online search volumes continue to grow at a steady rate. According to the Search Engine Marketing Professional Organization, spending on search engine marketing by North American firms in 2008 was estimated at $13.5 billion. Despite the significant role SEA plays in Web retailing, scholarly research on the topic is limited. Prior studies in SEA have focused on search engine auction mechanism design. In contrast, research on the business value of SEA has been limited by the lack of empirical data on search advertising practices. Recent advances in search and retail technologies have created datarich environments that enable new research opportunities at the interface of marketing and information technology. This research uses extensive data from Web retailing and Google-based search advertising and evaluates Web retailers' use of resources, search advertising techniques, and other relevant factors that contribute to business performance across different metrics. The methods used include Data Envelopment Analysis (DEA), data mining, and multivariate statistics. This research contributes to empirical research by analyzing several Web retail firms in different industry sectors and product categories. One of the key findings is that the dynamics of sponsored search advertising vary between multi-channel and Web-only retailers. While the key performance metrics for multi-channel retailers include measures such as online sales, conversion rate (CR), c1ick-through-rate (CTR), and impressions, the key performance metrics for Web-only retailers focus on organic and sponsored ad ranks. These results provide a useful contribution to our organizational level understanding of search engine advertising strategies, both for multi-channel and Web-only retailers. These results also contribute to current knowledge in technology-driven marketing strategies and provide managers with a better understanding of sponsored search advertising and its impact on various performance metrics in Web retailing.
Resumo:
One hundred and thirty-three parents of students new ~o ~ive independent schools in Ontario wer. surveyed to inve~tigate school choice behaviour. Paren~s were asKed to indicate their reasons for changing schooling, ~he criteria for selection o~ a school and the nature of the search process. Parents were also asKed to ranK speci~ic precipitants for change and criteria for choice. Spearman RanK Correla.tion tests were run comparing precipitants for change and criteria for choice for the entire sample and sub-groups based on socioeconomic status, gender of the child and family size. No signl~icant differences were found between the various $ub-groups, however, there was a strong positive correlation between precipitants for change and criteria for choice.Chi sq,uare tests were run compa.ring the number of information sources utilized in the search process, and a comparison was made between the importance of the va.rious sources of information. The majority of parents were classified as ac~ive searchers, researching one alternative more carefully than others. Socioeconomic status was the only factor to have a sign ific:ant- effect on the ranKing of information sources.
Resumo:
A feature-based fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, when targeting time series data, the fitness function is based on a sum-of-errors involving the values of the fluctuating signal. While this approach is successful in many instances, its performance can deteriorate in the presence of noise. This thesis explores a fitness measure determined from a set of statistical features characterizing the time series' sequence of values, rather than the actual values themselves. Through a series of experiments involving symbolic regression with added noise and gene regulatory network models based on the stochastic 'if-calculus, it is shown to successfully target oscillating and non-oscillating signals. This practical and versatile fitness function offers an alternate approach, worthy of consideration for use in algorithms that evaluate noisy or stochastic behaviour.
Resumo:
Background: The purpose of this study was to examine the relationships between physical activity and healthy eating behaviour with the participant's motives and goals for each health behaviour. Methods: Participants (N 121; 93.2% female) enrolled in commercial weightloss programs at the time of data collection, completed self-reported instruments using a web-based interface that were in accordance with Deci and Ryan's (2002) Self-Determination Theory (SDT). Results: Multiple linear regression models revealed that motivation and goals collectively accounted for between 0.21 to 0.29 percent and 0.03 to 0.16 percent of the variance in physical and healthy eating behaviours in this sample. In general, goals regarding either behaviour did not appear to have strong predictive relationships with each health behaviour beyond the contributions of motives. Discussion: Overall, findings from this study suggest that motives seem to mattermore than goals for both physical activity and healthy eating behaviour in clientele of commercial weight-loss programs. Therefore commercial weight-loss program implementers may want to consider placing more attention on motives I than goals for their clientele when designing weight-loss and weight-maintenance initiatives.
Resumo:
This thesis introduces the Salmon Algorithm, a search meta-heuristic which can be used for a variety of combinatorial optimization problems. This algorithm is loosely based on the path finding behaviour of salmon swimming upstream to spawn. There are a number of tunable parameters in the algorithm, so experiments were conducted to find the optimum parameter settings for different search spaces. The algorithm was tested on one instance of the Traveling Salesman Problem and found to have superior performance to an Ant Colony Algorithm and a Genetic Algorithm. It was then tested on three coding theory problems - optimal edit codes, optimal Hamming distance codes, and optimal covering codes. The algorithm produced improvements on the best known values for five of six of the test cases using edit codes. It matched the best known results on four out of seven of the Hamming codes as well as three out of three of the covering codes. The results suggest the Salmon Algorithm is competitive with established guided random search techniques, and may be superior in some search spaces.
Resumo:
Given the significant growth of the Internet in recent years, marketers have been striving for new techniques and strategies to prosper in the online world. Statistically, search engines have been the most dominant channels of Internet marketing in recent years. However, the mechanics of advertising in such a market place has created a challenging environment for marketers to position their ads among their competitors. This study uses a unique cross-sectional dataset of the top 500 Internet retailers in North America and hierarchical multiple regression analysis to empirically investigate the effect of keyword competition on the relationship between ad position and its determinants in the sponsored search market. To this end, the study utilizes the literature in consumer search behavior, keyword auction mechanism design, and search advertising performance as the theoretical foundation. This study is the first of its kind to examine the sponsored search market characteristics in a cross-sectional setting where the level of keyword competition is explicitly captured in terms of the number of Internet retailers competing for similar keywords. Internet retailing provides an appropriate setting for this study given the high-stake battle for market share and intense competition for keywords in the sponsored search market place. The findings of this study indicate that bid values and ad relevancy metrics as well as their interaction affect the position of ads on the search engine result pages (SERPs). These results confirm some of the findings from previous studies that examined sponsored search advertising performance at a keyword level. Furthermore, the study finds that the position of ads for web-only retailers is dependent on bid values and ad relevancy metrics, whereas, multi-channel retailers are more reliant on their bid values. This difference between web-only and multi-channel retailers is also observed in the moderating effect of keyword competition on the relationships between ad position and its key determinants. Specifically, this study finds that keyword competition has significant moderating effects only for multi-channel retailers.