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T his study investigates the potential of using data about Web searches to predict an important macroeconomic statistic, specifically the number of unemployed workers in the U.S. Our underlying assumption is that people reveal useful information about their needs, wants, interests, and concerns via their Internet behavior, and that terms submitted to search engines reflect this information. Research indicates that the percentage of Web site visitors who are referred by search engines increased from 67% in 2001 to 88% in 2004 [4], so this data potentially offers a rich and timely source of information. The study finds that Web-based search data is associated with future unemployment data over the 77-week study period. This very preliminary result suggests search-term data might be useful in predicting other important macroeconomic statistics.A large proportion of job-related information gathering is conducted using the Internet [1, 10, 12]. Of the 54% of the U.S. population that uses the Internet, 16% engages in online job search activities [12]. There is evidence that unemployment duration has decreased among some Internet job seekers [9].The Internet is credited with overcoming information bottlenecks in key areas of the labor market, affecting how worker-firm matches are made, how labor services are delivered, and how local markets shape demand [1].

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The increasing availability of consumer feedback on the web provides a wealth of information that organizations can use for product and service improvement. Many consumer feedback sites allow users to enter both a quantitative rating and a qualitative critique. Previous research has used this information disjunctively. This work proposes an innovative approach that integrates the two types of information to identify words that are related to positive or negative consumer ratings. A case study shows that this approach does raise some issues not identified using existing analytical approaches.

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Purpose The purpose of this paper is to investigate how well hotel website load time performance compared against customer expectation benchmarks. In a competitive market, service interactions are important. As customers move to mobile devices, the time to load a website is a critical part of the service delivery. Long load times can lead to poor service experiences, customer frustration and lost business. Hotel website load times on both mobile and desktop devices were examined and compared to service expectations. Design/methodology/approach The study used an online service to assess and compare website load performance using both desktop and mobile devices for 259 international hotel company and sub-brand websites. Findings The time to load hotel websites was significantly slower on mobile devices compared to desktops. Load times on both platforms exceeded 3 s, which is considered best practice. Long load times represent a service gap and can cause dissatisfaction resulting in a potential customer abandoning the website for a competitor’s site, thus affecting sales. Research limitations/implications While the population for the study was robust in size and contained most of the major hotel companies worldwide, it was not exhaustive. Data also represent a snapshot and will change over time. Load times vary based on test location, access device and network traffic. Additionally, web page load times and customer expectations will change as technology evolves. Originality/value Increased use of mobile devices for hotel reservations increases the importance of mobile service delivery. This is the first known study to measure hotel website load times for mobile devices, and to examine both mobile and desktop performance against best practice. The results of this study highlight a service gap, which can lead to loss of business. Given the consistency of the results, the authors suspect that this is an issue that has not been recognized within the industry. This study is valuable because it exposes an issue of website design not generally addressed in the hospitality industry, even though tools are available to monitor site performance.

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