Characterizing and Evaluating Users' Information Seeking Behavior in Social Tagging Systems

Social tagging systems in the Web 2.0 era present an innovative information seeking environment succeeding the library and traditional Web. The primary goals of this study were to, in this particular context: (1) identify the general information seeking strategies adopted by users and determine their effectiveness; (2) reveals the characteristics of the users who prefer different strategies; and (3) identify the specific traits of users' information seeking paths and understand factors shaping them. A representative social tagging system, Douban (http://www.douban.com/) was chosen as the research setting in order to generate empirical findings.Based on the mixed methods research design, this study consists of a quantitative phase and a qualitative phase. The former firstly involved a clickstream data analysis of 20 million clickstream records requested from Douban at the footprint, movement, and track levels. Limited to studying physical behavior, it was complemented by an online survey which captured Douban users' background information from various aspects. In the subsequent qualitative phase, a focus group gathered a number of experienced Douban users to help interpret the quantitative results.Major findings of this study show that: (1) the general strategies include encountering, browsing by resource, browsing by tag, browsing by user/group, searching, and monitoring by user/group; (2) while browsing by resource is the most popular strategy, browsing by tag is the most effective one; (3) users preferring different strategies do not have significantly different characteristics; and (4) on users' information seeking paths these exist two resource viewing patterns - continuous and sporadic, and two resource collecting patterns - lagged and instant, and they can be attributed to user, task, and system factors.A model was developed to illustrate the strategic and tactic layers of users' information seeking behavior in social tagging systems. It offers a deep insight into the behavioral changes brought about by this new environment as compared to the Web in general. This model can serve as the theoretical base for designing user-oriented information seeking interfaces for social tagging systems so that the general strategies and specific tactics will be accommodated efficiently

Are Mendeley's public groups effective aggregators of high-value papers? An analysis based on paper readerships

At present, Mendeley is the only academic social networking service that allows users to form interest groups. Sharing papers relevant to the group theme is one of the major activities of group members. In this study, we focused on Mendeley’s public groups, interested in their effectiveness in aggregating high-value academic papers. The value of the papers can be indicated with their readerships, a popular altmetric. Do the papers shared in groups have higher readerships than the ones that are not shared in groups? We obtained significant results for all of the 24 Mendeley disciplines examined. However, disciplinary differences exist: natural sciences and engineering present relatively higher levels of paper readership disparity than humanities and social sciences. Our findings suggest that exploring groups’ paper collections is a useful alternative method of information seeking, especially in natural sciences and engineering

How Do Bloggers Comment: An Empirical Analysis of the Commenting Network of a Blogging Community

The blog is one of the most familiar social media to Web users. Its social nature suggests that blogging is not only about writing and publishing bloggers’ experience and thoughts, but also about establishing social relationships and networks with others through various links including citations, blogrolls, comments, and trackbacks. We have a particular interest in comments, and develop a commenting model that considers both unidirectional and bidirectional commenting relationships. This paper presents a social network analysis of the commenting network of CSDN blogging community, the largest Chinese language IT blogging community in China. According to our findings, this is a sparse network, and the most noticeable nodes in it are a few central bloggers who possess a lot of incoming relationships. Each of them is surrounded by a number of ordinary bloggers who recognize the central blogger as their exclusive information source in a star topology. Our continuing study will focus on these central bloggers and examine their influences on the information diffusion in CSDN blogging community at the semantic level

ASYMMETRIC PRICING AND AIRLINE PERFORMANCE

We study the relation of asymmetric pricing with operating performance and stock returns of U.S. airlines. We construct two proxies to measure the degree of asymmetric pricing: Degree of Asymmetry (DOA) and Peer-adjusted DOA, and then simultaneously test how the direction and magnitude of asymmetric pricing affect airline performance. We find that raising air ticket price, regardless of whether the fuel cost is increasing or decreasing, is associated with significantly higher sales growth and stock returns than reducing price in the same scenario. However, raising price above industry peers is two-edged: it may increase profit margin, but at the cost of a slowdown in sales growth

Workforce management in periodic delivery operations

Service quality and driver efficiency in the delivery industry may be enhanced by increasing the regularity with which a driver visits the same set of customers. However, effectively managing a workforce of drivers may increase travel distance, a traditional metric of the vehicle routing problem (VRP). This paper evaluates the effect that workforce management has on routing costs, providing insight for managerial decision making. The analysis is presented in the context of the period vehicle routing problem (PVRP), an extension of the VRP with vehicle routes constructed to service customers according to preset visit frequencies over an established period of time. We develop models to apply workforce management principles. We show that multi-objective PVRP models can achieve a balance between workforce management and travel distance goals, through a computational study with standard PVRP test cases and real-world delivery data. With the proper parameters in place, workforce management principles may be successfully applied without sacrificing other operational objectives