IEEETransactions on Services Computingand INFORMSService Scienceissued a joint call for papers targeting the bridging of service perspectives from business (e.g., service science, services marketing and information systems) to services computing. The intent was to advance transdisciplinary research agendas that could generate advances that go beyond the sum of independent research streams. As with all transdisciplinary research ideals, these efforts are extremely difficult, as pioneers need to overcome significant barriers, including different vocabularies, different research methods and differences in each field's historical evolution. This special section provides a snapshot of research efforts that begin to break down barriers. We offer special thanks to those authors who took the risk of having their manuscripts processed by an esteemed set of invited guest editors who have expertise from across the services spectrum.

Humans spend 90% of their lives inside buildings, but often the Heating, Ventilation, and Air Conditioning (HVAC) systems of commercial buildings do not properly maintain occupant comfort. Use of feedback through comfort voting applications has been shown to improve the quality of service, but the effects of application feedback and user interface design has not been investigated. In this work, we present several methods of feedback that use data presentation and environmental interaction in comfort voting applications. Through a 40 week user study of 61 University employees across 3 buildings, we show that feedback systems can be used to increase user satisfaction with thermal conditions from 33.9% to 93.3% and reduce energy consumption up to 18.99% compared to a system without voting. In addition, we find that by including a drifting control strategy, we find energy savings up to 37% can be realized without a significant reduction in satisfaction.

Various types and massive amounts of data are being collected through physical and social sensing. In many cases of data use, the results and value of data analytics are conveyed to specific beneficiaries (e.g., individuals and organizations) within a service system, such as a transportation, energy supply, or healthcare service system. Thus, data-use can be directed and improved based on considerations of the relevant service system. In this paper, we suggest that effective use of data analytics can be guided by the question, “How does data analytics contribute to the creation of a smarter service system?” To facilitate answers to this question, we define a smart service system from a data application perspective, and propose a specific approach, serviceoriented data analytics, based on eight case studies related to smart service systems. We introduce an ongoing case study to demonstrate the applicability and utility of our proposals.

Despite the growing prominence and capabilities of self-driving cars, little is known about human interaction with such autonomous vehicles. We are studying human interaction with multiple levels of automation and navigation in a simple driving simulator to discover principles for interaction design that encourage effective partnership between people and automated vehicles. We have conducted two experiments so far. In the first, participants completed driving tasks based on two different factors: automated versus manual control and navigation in low-level versus high-level language, which were combined via a factorial design into four conditions for each participant in the form of different driving scenarios. Performance was measured by travel time, frequency of driving and navigational errors, and levels of user satisfaction. The second iteration had all automated driving, with participants merely supervising while we gave varying amounts of verbal input.

System administrators work with many different tools to manage and fix complex hardware and software infrastructure in a rapidly paced work environment. Through extensive field studies, we observed that they often build and share custom tools for specific tasks that are not supported by vendor tools. Recent trends toward web-based management consoles offer many advantages but put an extra burden on system administrators, as customization requires web programming, which is beyond the skills of many system administrators. To meet their needs, we developed A1, a spreadsheet-based environment with a task-specific system-administration language for quickly creating small tools or migrating existing scripts to run as web portlets. Using A1, system administrators can build spreadsheets to access remote and heterogeneous systems, gather and integrate status data, and orchestrate control of disparate systems in a uniform way. A preliminary user study showed that in just a few hours, system administrators can learn to use A1 to build relatively complex tools from scratch.

Computer system administrators are the unsung heroes of the information age, working behind the scenes to configure, maintain, and troubleshoot the computer infrastructure that underlies much of modern life. However, little can be found in the literature about the practices and problems of these highly specialized computer users. We conducted a series of field studies in large corporate data centers, observing organizations, work practices, tools, and problem-solving strategies of system administrators. We found system administrators operate within large-scale, complex environments that present significant technical, social, cognitive, and business challenges. In this paper, we describe system administrator tool use in critical, high-cost, labor-intensive work through observational, survey, and interview data. We discuss our findings concerning administrator needs for coordinating work, maintaining situation awareness, planning and rehearsing complex procedures, building tools, and supporting complicated interleaved workflows.

A common method for finding information in an organization is to use social networks---ask people, following referrals until someone with the right information is found. Another way is to automatically mine documents to determine who knows what. Email documents seem particularly well suited to this task of "expertise location", as people routinely communicate what they know. Moreover, because people explicitly direct email to one another, social networks are likely to be contained in the patterns of communication. Can these patterns be used to discover experts on particular topics? Is this approach better than mining message content alone? To find answers to these questions, two algorithms for determining expertise from email were compared: a content-based approach that takes account only of email text, and a graph-based ranking algorithm (HITS) that takes account both of text and communication patterns. An evaluation was done using email and explicit expertise ratings from two different organizations. The rankings given by each algorithm were compared to the explicit rankings with the precision and recall measures commonly used in information retrieval, as well as the d' measure commonly used in signal-detection theory. Results show that the graph-based algorithm performs better than the content-based algorithm at identifying experts in both cases, demonstrating that the graph-based algorithm effectively extracts more information than is found in content alone.

With widespread access to e-mail, the world-wide web, and other information sources, people now use computers more for managing information than for managing applications. To support how people naturally and routinely organize information, computers ought to be able to reflect the categories, relationships, and cues that people rely on when thinking about and remembering facts. Toward this end, we created an Information Programming Toolkit (IPtk) that collects application-independent properties, indexes documents along many dimensions to create a personal record of information use, and provides convenient means for information access. The IPtk enables the development of smart user interfaces that automatically tailor information to a user's history and context of information use.

Peripheral information is information that is not central to a person's current task, but provides the person the opportunity to learn more, to do a better job, or to keep track of less important tasks. Though peripheral information displays are ubiquitous, they have been rarely studied. For computer users, a common peripheral display is a scrolling text display that provides announcements, sports scores, stock prices, or other news. In this paper, we investigate how to design peripheral displays so that they provide the most information while having the least impact on the user's performance on the main task. We report a series of experiments on scrolling displays aimed at examining tradeoffs between distraction of scrolling motion and memorability of information displayed. Overall, we found that continuously scrolling displays are more distracting than displays that start and stop, but information in both is remembered equally well. These results are summarized in a set of design recommendations.

Attentive systems pay attention to what users do so that they can attend to what users need. Such systems track user behavior, model user interests, and anticipate user desires and actions. Because the general class of attentive systems is broad — ranging from human butlers to web sites that profile users — we have focused specifically on attentive information systems, which observe user actions with information resources, model user information states, and suggest information that might be helpful to users. In particular, we describe an implemented system, Simple User Interest Tracker (Suitor), that tracks computer users through multiple channels — gaze, web browsing, application focus — to determine their interests and to satisfy their information needs. By observing behavior and modeling users, Suitor finds and displays potentially relevant information that is both timely and non-disruptive to the users' ongoing activities.

We describe a new method and implementation for managing information through the use of physical objects.In today's networked world, the trend is toward working in a global virtual environment.To transfer information, users are responsible for finding an appropriate storage location, naming the information, selecting the transport mechanism, and setting the access permissions.Much of the time, these burdens are needless and, in fact, stand in the way of productive use of the networked environment.In many circumstances, a physical floppy disk is the ideal medium for transferring information, as it eliminates these complications.Our Informative Things approach provides a "floppy-like" user interface that gives the impression of storing information on physical objects.In reality, our system stores information in the network, associating pointers to information with objects in the physical world.By hiding these details, we simplify information management.By linking the physical and virtual worlds, we leverage users' highly-developed ability to work in the real world.

Agents can personalize otherwise impersonal computational systems. The World Wide Web presents the same appearance to every user regardless of that user's past activity. Web Browser Intelligence (WBI, pronounced "WEB-ee") is an implemented system that organizes agents on a user's workstation to observe user actions, proactively offer assistance, modify web documents, and perform new functions. WBI can annotate hyperlinks with network speed information, record pages viewed for later access, and provide shortcut links for common paths. In this way, WBI personalizes a user's web experience by joining personal information with global information to effectively tailor what the user sees. Keywords Agents, World wide web, User models. INTRODUCTION One goal of networked computing is to provide all users access to the world's vast information resources. This trend toward a single, global database clearly shows its potential in the World Wide Web. Tens of thousands of institutions, hundreds o...