Plan de acciones de Responsabilidad Social Corporativa para los grupos de

Transaction log analysis (TLA), as a research approach, has several advantages. First, as discussed previously, the captured data represent a record of events as they actually occurred, without the reframing and recall errors prevalent in many other data collection methods. Using transaction logs, the quality of your data will not be dependent on the study participant’s memory of the interaction or on his or her ability to describe the interaction. Second, it draws on large volumes of data collected from a great number of users. It can be conducted at a large scale and thus may be more representative of larger populations than some more intensive methods. Third, it can be used both to build quantitative models and to assist in qualitative interpretations of qualitative models (Borgman et al., 1996). Finally, it is appropriate to both experimental and field study research designs. Transaction logs can be captured during experimental sessions; usually, client-side logs are captured so that more control can be exerted on which data elements are included in the data set. Transaction logs can also be captured “in the wild” (e.g., from the server supporting a particular Web site).

Server-side logs also have several other advantages. Relatively few resources are required to gather log data, provided appropriate logging programs are available. Because interpersonal interactions are minimized during the data collection process, server-side logs are relatively objective in their representations of user behaviors. Because recording of transaction data occurs in the background, data capture is unobtrusive.

Client-side transaction logs differ significantly from server-side logs in that use of client-side logs can be very resource-intensive. Researchers must recruit participants, install and test logging programs on the participants’ machines, and (sometimes) collect data from a variety of machines and users (Kelly, 2006a, 2006b; Yun et al., 2006). Additionally, client-side logging programs are not as readily available to researchers. Some (e.g., Kelly, 2006a, 2006b) have used logging programs developed for the spyware3 market, and others (e.g., Yun et al., 2006) have developed customized applications or browsers to log client-side events. At the same time, client-side logging provides the opportunity to collect data sets that include details of user actions across a variety

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of applications and Web sites, whereas server-side logs are restricted to server-based events. Laboratory-based transaction log analysis studies (e.g., Card et al., 2001) may fall anywhere along the continuum between client-side and server-side TLA methods with respect to advantages and limitations in sample size and are not discussed in detail here. It should be noted, however, that laboratory-based designs differ notably from other types of TLA in that they are generally highly controlled, task-based approaches, rather than naturalistic field studies, and may augment the transaction logs with other data such as think-aloud protocols or eye tracking.4

When using transaction log analysis, it is important to be aware of the limitations represented by the data set. First, it must be recognized that information about the context in which events recorded in a log file occurred is not collected. Log files do not collect information about the experiential context of the event such as user motives, intentions, and satisfaction with results. The only way to overcome this limitation is to combine the capture of transaction logs with other types of data collection methods. For example, study participants may be interviewed, may respond to questionnaires, or may be asked to think aloud during their interactions with the information system. Unfortunately, combining data collection methods means that you sacrifice the unobtrusiveness and large scale with which studies can be conducted if they rely solely on transaction logs (Jansen, 2006). At the same time, the addition of context and data not accessible through transaction logs often outweighs these limitations.

There are also technical limitations with respect to how data are collected in the case of both server-side and client-side transaction logs. A major concern with server-side log files is that they do not capture page requests that are fulfilled by means of file copies cached on local machines or proxy servers. It has been estimated that as many as 45 percent of page requests are fulfilled from cached content (Nicholas, 2000). The proportion of page requests fulfilled from cached content will vary depending on a number of Web site structure, size, and use factors. There is not a formula to predict how much and which content will be retrieved from cached copies (Fieber, 1999). Thus researchers should be cautious about the conclusions they draw from server-side log studies.

Another challenge to using server-side log files is that unless servers artificially maintain a connection with the client, require logins, or send cookies, it is difficult to distinguish individual system users (Marchionini, 2002). While it may be appropriate to some research questions to identify groups of users by characteristics of viewed content (e.g., Keegan et al., 2006), researchers must generally rely on identifying user sessions through a combination of the date and time stamp and IP addresses. Furthermore, identified IP addresses may relate to use by an individual, by more than one individual on a shared or public machine, or by a proxy server.

Another limitation of transaction log data is that it can be very cumbersome to process and analyze large volumes of data. Processing and manipulating large volumes of data is becoming less of a concern with the development of tools that can be used to work with transaction log data. Furthermore, abundant use of transaction logs in research and private industry provides precedents with respect to data handling and processing. Also, with continuing interest in transaction log analysis, it is likely that some of the technology-related challenges associated with this method will at least be mitigated. For example, Jansen (2006) has recently developed a tool, the Wrapper, that can be used in remote naturalistic studies.

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The unobtrusiveness of transaction log capture raises some concerns about the ethical issues associated with collecting and using data without informing participants. Some researchers may believe that transaction logs captured from a large, often international audience (as in studies of Web server logs) ensure anonymity for the people being studied; however, the courts do not agree.5 _{Client-side log studies entail extensive}

contact and interaction between researchers and participants, so informed consent can easily be obtained. Both researchers who use client-side logging methods and those who use server-side log files need to be careful with respect to how personal information, including query strings, is handled, so that their study participants’ privacy can be maintained.