Skip to Main Content

Food Theory HOSP105 & Theory of Food COOK105

Research in the fast lane!

Because many of our journals are collected together in aggregated databases, adding and mixing several titles and publishers, searching is usually a matter of entering words and phrases that describe your topic, at least in the beginning.

Once you find an article or two that seems promising, you can proceed to refine the search process by working with the information provided, about the article.

Information about the article includes the author, source, abstract, subject terms, author supplied keywords, geographic identifiers, and NAICS codes, among other elements.  Keep in mind that most articles you encounter will only have some of these elements.

Example 1:
Authors: Armando Maria Corsi , Simone Mueller, and Larry Lockshin
Source: Cornell Hospitality Quarterly
Abstract: While menu items and menu design have been explored in the food-service sector, there is still a lack of information about the role played by product elements in a wine list from a consumer’s perspective. This study aims to fill this gap using a novel research method, choice modeling with latent class analysis for segmentation, which has not been used previously in menu research. The goal is to provide a better understanding of the way consumers choose wine in an on-premises setting and to identify possible segments based on how consumers respond to different types of information provided on the menu. The study was conducted in Australia, using an online representative panel of 1,258 respondents in May 2009, in a market similar to the United States with regard to on-premises wine consumption. The main results show that grape varietals are key choice drivers, followed by the awards obtained by a wine and its price. Less important but about equal in weight were a wine’s region of origin and tasting notes (i.e., a description of its sensory characteristics). The least important choice factor is food-matching suggestions. A segmentation analysis revealed the existence of seven segments, which are distinctive with regard to wine preferences based on the attributes analyzed in this study. However, as much as these groups diverge in the way they behave, they do not differ on the basis of their sociodemographic and attitudinal characteristics, confirming similar findings of other studies.
Author Supplied Keywords: on-premises wine sales, wine list, discrete choice analysis
Author: The name of the author(s) can be incorporated in a refined search to see what else they have written on the same or related topic(s).  In these refining searches, it may be helpful to return to the MEGA search box on the library's homepage.  The MEGA box is a federated search feature, in that it acts as an "all-in-one" search vehicle, searching close to 60 percent of the library's collections at once.  Through this method, we discover that author Armando Maria Corsi is a contributing writer to several articles on wine markets, marketing and consumer preferences.
Source: In our example, we discovered the Cornell Hospitality Quarterly through the Full-Text Journal list. (See the Title Searching box for this method) When you are searching a large aggregated collection, by click on the source link (from the information sheet about the article), you can often search within the issues of that single publication.  This is useful if, for example, you discover that a journal has dedicated an entire issue to a particular theme or topic that interests you.
Abstract: You can also pick up useful and unique phrasing within article abstracts, and use Geographic Terms to focus results on a particular geography.  The unique phrasing in this abstract relates to the authors' novel research method: choice modeling with latent class analysis for segmentation. You may want to see how this method is discussed and applied in similar and related settings.  Interesting results emerge with this type of a search: "choice modeling" and food. Furthermore, the abstract provides an easy way for you to branch out and expand your research project, taking it in new directions.  The abstract under investigation also refers to grape varietals, wine awards, price pointswine regions, tasting notes, and food-matching suggestions. Any of these attributes may be of interest to you as well, and worthy of further exploration.
Author-Supplied Keywords: These words are added by the author(s) of the article, and sometimes capture discipline-specific language. The following phrases may yield useful results: on-premises wine sales and discrete choice analysis
Example 2:
Subject Terms: chocolate products industry, rebranding (marketing), retail stores, marketing, chocolate candy
NAICS/Industry Codes: 
311351 Chocolate and Confectionery Manufacturing from Cacao Beans
311352 Confectionery Manufacturing from Purchased Chocolate
424450 Confectionery Merchant Wholesalers
For the Gateway to Bliss article, I have only included the article information elements we have not yet discussed.
Subject Terms are standardized words and phrases that are applied in the same way across the entire collection, and supplied by information science professionals.  They may help pull together like-minded articles, where keywords are less precise. In an economy of words, they attempt to capture the essence of an article. In this example, the focus of the article rebranding company names in a local chocolate producing industry.  You may want to investigate rebranding in the chocolate industry more broadly.
NAICS/Industry Codes: The North American Industry Classification System (NAICS) uses a system of numbers to classify industry.  It is another entry point, worth exploring, into the search process.  For example, 311351 is the numerical representation for "Chocolate and Confectionery Manufacturing from Cacao Beans."  While this search will capture industry news, it begs for refinement.  Stories range widely from climate change, manufacturing processes, to chemical balancing within this industry sector.  These first page results even include a SWOT analysis for the Hershey Company!
chat loading...