Search results

Purpose — To develop methodologies to evaluate search engines according to an individual's preference in an easy and reliable manner, and to formulate user-oriented metrics to compare freshness and duplication in search results.

Design/methodology/approach — A personalised evaluation model for comparing search engines is designed as a hierarchy of weighted parameters. These commonly found search engine features and performance measures are given quantitative and qualitative ratings by an individual user. Furthermore, three performance measurement metrics are formulated and presented as histograms for visual inspection. A methodology is introduced to quantitatively compare and recognise the different histogram patterns within the context of search engine performance.

Findings — Precision and recall are the fundamental measures used in many search engine evaluations due to their simplicity, fairness and reliability. Most recent evaluation models are user oriented and focus on relevance issues. Identifiable statistical patterns are found in performance measures of search engines.

Research limitations/implications — The specific parameters used in the evaluation model could be further refined. A larger scale user study would confirm the validity and usefulness of the model. The three performance measures presented give a reasonably informative overview of the characteristics of a search engine. However, additional performance parameters and their resulting statistical patterns would make the methodology more valuable to the users.

Practical implications — The easy-to-use personalised search engine evaluation model can be tailored to an individual's preference and needs simply by changing the weights and modifying the features considered. A user is able to get an idea of the characteristics of a search engine quickly using the quantitative measure of histogram patterns that represent the search performance metrics introduced.

Originality/value — The presented work is considered original as one of the first search engine evaluation models that can be personalised. This enables a Web searcher to choose an appropriate search engine for his/her needs and hence finding the right information in the shortest time with the least effort.

This paper ranks university faculties, accounting doctoral programs, individual behavioral accounting researchers, and the most influential articles based on Google Scholar citations to publications in Advances in Accounting Behavioral Research (AABR). All articles published in AABR in its first 15 volumes are included and four citation metrics are used. The paper identifies the articles, authors, faculties, and doctoral programs that made the greatest contribution to the development of AABR. Such an analysis provides a useful basis for understanding the direction the journal has taken and how it has contributed to the literature (Meyer & Rigsby, 2001). The h-index and m-index for AABR indicates it compares favorably among its peers. Potential doctoral students with an interest in behavioral accounting research, “new” accounting faculty with an interest in behavioral accounting research, current behavioral accounting research faculty, department chairs, deans, and other administrators will find these results informative.

Much has been analyzed regarding the origins and the impact of rankings and metrics on policies, behaviors, and missions of universities. Surprisingly, little attention has been allocated to describing and analyzing the emergence of metrics as a new action field. This industry, fueled by the “new public management” policy perspectives that operate at the backstage of the contemporary pervasive “regime of excellence,” still remains a black box worth exploring in depth. This paper intends to fill this loophole. It first sets the stage for this new action field by stressing the differences between the policy fields of higher education in the United States and Europe, as a way to understand the specificities of the use of metrics and rankings on both continents. The second part describes the actors of the field, which productive organizations they build, what skills they combine, which products they put on the market, and their shared norms and audiences.

Purpose – Addresses labor control in fields where familiar organizational and occupational controls are weak, notably postindustrial arenas characterized by networks, heterogeneity, and change.Methodology/approach – Proposes that labor control operates via socio-technical networks composed of diverse ties to social actors, technologies, and typifications. Data from an interview-based study of early website production work is used to examine the impact of such a network.Findings – Socio-technical networks constrained web workers#x02019; actions but also offered opportunities for autonomous discretion. Some shifting between networked and hierarchical controls occurred in larger organizations.Research implications/limitations – The role of networks in the labor process is not well understood; this study provides a starting point.Social implications – Socio-technical networks are heterogeneous and lack common status metrics, making inequality among workers difficult to gauge and address. Further, since networked controls are decentralized, their pressures are not easily identified or resisted by workers.Originality/value – This chapter describes a form of labor control that may characterize some postindustrial fields more closely than traditional models. In addition, it contributes new insights on how work is shaped by technical networks and abstract typifications.

How do you efficiently design a global yet local user experience for Web sites? Arguably, the user-centered design approach has been one of the best methods in designing a successful user experience for Web services in the initial market, but why isn’t this process applied to international markets? This chapter makes a case for applying a user-centered design process to the international expansion of Web sites and discusses issues impacting the creation of a successful user experience for local audiences. Although this chapter primarily focuses on designing large scale Web services, many of the principles can be applied to any sites that undergo internationalization.

Organizational metrics – including rankings, ratings, and other forms of public assessment – are inextricably tied to uncertainty. Metrics are not only responses to uncertainty in the organizational environment, but they also create new forms of uncertainty within the organizations they evaluate. Given this, it is productive to consider these metrics in relation to the garbage can model of organizational decision making, a framework that was designed to provide insight into uncertain and ambiguous contexts. In this paper, the authors use the case of patient experience surveys to argue for the value of this model for understanding responses to metrics in particular conditions. Specifically, the authors demonstrate how the different features of the garbage can model manifest themselves within organizations managing numbers, and the authors then use these findings to discuss the measurement conditions that promote garbage can responses, the distinctive types of unintended consequences these responses might produce, and the implications of the garbage can model for the understanding of metrics more generally.