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In late 1999, one of the authors of this book began a consulting engagement with Cisco Systems, helping them prepare to open a Web-based conversation with the networking professionals (NPs) who installed, configured, and maintained Cisco s equipment on customer sites Cisco realized that there was plenty of room for improvement in its ability to support these thousands of technicians in the field, even though it already had one of the most advanced and sophisticated customer support operations anywhere Cisco presented itself to the world as the leader of the migration to the Net Its marketing slogan was, Are you ready So it figured it needed to make itself readier by learning and applying the practice of virtual community The original vision inside the company was to provide a space where NPs could meet, share war stories, and suggest solutions for problems not covered in Cisco s extensive online documentation.

A solution of Score(b) = X (y - Xb) = 0 is simply bML = (X X)-1X y. Hence the ordinary least squares (OLS) estimator can be viewed as a solution of the ML estimation problem. Note that multicollinearity means the inverse of (X X) matrix cannot be found and near multicollinearity means that standard errors of regression coef cients are large, the inverse of (X X) matrix cannot be reliably found, and the numerical inverse given by the computer cannot be trusted. Hence statistical inference based on usual t values cannot be trusted. Nonlinear Regression Now we consider estimation methods more general than multiple regression. Nonlinear regression simply means that y is related to the regressors by a nonlinear relationship: y = g(x, q) + e, where x contains xi for i = 1, 2, . . . , p, regressors and q represents the nonlinear regression parameters, which need not equal p in number. Assume that there are t = 1, 2, . . . , T, observations for y and each regressor xi. If the vector of errors e follows the multivariate normal density, only the mean and variance matter. Let the density function of errors be denoted by f(e) = f [y - g(x, q)]. Clearly, the density function is a function of the data on y and x and of the parameter vector q:

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Exploring the Globalization Supplier Landscape There are no big, absolutely safe, nobody ever got red for buying IBM vendors in the translation and localization space Most are small players, and there are a few medium-sized enterprises The translation industry thinks of itself in functional terms, splitting the market in to multilanguage and singlelanguage vendors (MLVs and SLVs) The biggest differences between the two are in scale (large vs small), in the number of languages that each handles (many vs one), and in where the work gets done This last point is key: Whether you use an MLV or SLV, it still takes just as many steps to translate something from one language to another An MLV takes on the project management tasks that an SLV usually leaves with the customer Table 91 lists the typical steps in a translation work ow.

Often, the problems encountered in the field were unknown to the customer service representatives who answered email and phone queries The people using the equipment in unique situations were the sole owners of knowledge about how to resolve those situations The NP community site would establish a space where those people could meet as a last resort and find the elusive answers to their questions under Cisco s URL The NP community was not meant to be a place to ask Cisco support questions But Cisco s customer support staff, on hearing the idea, recognized it as a potential learning resource for them They could learn from conversations between Cisco equipment users how to improve the company s documentation and support.

Multilanguage Vendors MLVs are larger multinational translation vendors such as Berlitz, Bowne Global, or Lionbridge They directly employ a wider variety of skill sets than do smaller SLVs, thus offering publishing, site engineering, localization, and even testing in addition to translation services These MLVs break the translation job into smaller processes and functions that they can automate or scale to meet demand All things being equal, MLVs are likely to have more resources at their disposal for executing projects, both online and off Pro: MLVs are the closest the industry gets to one-stop shopping For example, they might offer a variety of European or Asian languages plus engineering, publishing, and testing services to create an effective Web presence in a given market Their scale lets you have a single point of contact for managing all translation and localization services, including contracts and scheduling as well as any problems.

You should note that MLVs frequently use SLVs as subcontractors and as shock absorbers when their work load gets too high Con: MLVs also tend to be more expensive and less responsive than are their smaller single-language brethren Added services such as extensive.

The team working to develop the community interface and processes began to see how the conversations among expert users of the products could serve as a valuable pipeline into the minds of the customers for all of the company s product developers and marketers..

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