Liesl Riddle, PhD

Cases
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Surveying the Turkish Clothing Industry

Riddle, Liesl. 2003. In Kate Gillespie, Jean-Pierre Jeannet, and H. David Hennessey (eds.) Global Marketing: An Interactive Approach. NY: Houghton-Mifflin.

Gretchen Renner had escaped to the serenity of a small tea garden overlooking the Bosphorous Sea, which separates the European and Asian sides of Istanbul. As she sipped a glass of strong tea, she fought the urge to abandon her thesis research project and return to the United States.

Before arriving in Istanbul, Gretchen had been excited about the project. She had designed a survey to measure Turkish clothing firm owners’ use and satisfaction with the services offered by the Textile Association of Istanbul (TAI). This association offers marketing, export-counseling, and educational services aimed to encourage producers to pursue export opportunities.

Two months before coming to Turkey, a Turkish friend told Gretchen that she must apply for a research visa from the Turkish government. Foreigners planning to conduct research projects in Turkey must possess a government-approved research visa to display to government officials and potential research participants. Foreigners conducting research projects without a research visa in Turkey risk arrest and deportation. Gretchen was surprised that the research visa application must be completed prior to arrival in Turkey. She waited four months to receive the visa, inconveniently postponing her trip.

Once in Turkey, Gretchen sought a list of Turkish clothing firm owners from which she could draw a representative sample for her survey. Although TAI was supportive of Gretchen’s project, they hesitated to share their membership list. Gretchen spent months developing relationships with key officials at TAI, conducting interviews and collecting information. TAI officials readily shared information about the organization’s history, structure, and services. Yet, each time she asked about the list, she was denied access. Some of Gretchen’s contacts claimed that releasing the information compromised the firms’ privacy. Others maintained that no precedent existed for releasing the list to a non-TAI employee. Additionally, several of her close contacts explained to her that she could not have the list because she was not Turkish. Finally, with no explanation, TAI supplied the list of names.

Problems then emerged during survey pretesting. The questionnaire was administered via the telephone by interviewers employed by Itimat, a well-known Istanbul market research firm. During this pretesting, Gretchen and her interviewers discovered it was difficult to circumvent gatekeepers, such as secretaries and receptionists, to interview Turkish clothing firm owners.

Hoping to increase response rates, Gretchen sent potential respondents a pre-survey fax, introducing herself, the survey’s objectives, and Itimat. But, respondents voiced concerns about the fax. Most complained that no high-level Itimat executive had signed the fax; it had been signed only by Gretchen and an Itimat interview supervisor. Others were suspicious of Gretchen’s authenticity. The Turkish media reported that several Europeans recently had posed as academic researchers to expose child labor practices in Turkish clothing factories. Because of Gretchen’s German name and the unknown name of her university, many suspected that Gretchen was actually an industrial spy.

Even when Gretchen or the interviewers gained access to firm owners, few agreed to participate in the survey. One scoffed,

“If you really valued my opinion, you would set an appointment and discuss this with me in person. I am a very busy person; I don’t have time to just talk on the phone about such things.”

But, face-to-face interviews would be more time-consuming than telephone interviews. First, it would take time to get past the gatekeepers to make appointments with potential respondents. Second, because the firms were widely dispersed and Istanbul is a very large and traffic-congested city, Gretchen and her team of four Itimat interviewers could complete only ten surveys daily. Gretchen needed to complete 300 surveys.
Gretchen’s research funding was dwindling, and she must return home in six weeks.

Looking toward the Asian side of Istanbul, Gretchen wondered how she could successfully complete her research project in the remaining time.

Discussion Questions:

1. What cultural factors might contribute to the obstacles Gretchen encountered while attempting to execute the survey? How might Hofstede’s dimensions of culture explain Gretchen’s difficulties?

2. Why do you think Gretchen finally received the list of Turkish clothing exporters from TAI? If they had not supplied the list, where else could Gretchen have looked to find a suitable list?

3. How should Gretchen proceed with the survey? Do you think the benefits of the face-to-face option outweigh the costs? Or, could changes be made to the telephone survey to increase response rates? Are there other survey options that Gretchen should consider instead?

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Selector’s European Dilemma

In Global Marketing: An Interactive Approach. Gillespie, Kate, Jean-Pierre Jeannet, and H. David Hennessey (eds.). 2001. NY: Houghton-Mifflin.

Ken Barbarino, CEO of Selector Inc., was ecstatic. The president of Big Burger, one of Selector’s largest clients, had arranged for Ken to meet with the vice president of Big Burger’s European operations. “Selector is going global,” Ken smiled to himself.
Selector was a market research firm that provided market analyses to restaurant and retail chains. Selector’s products helped clients select optimal geographic locations for successful chain expansion.

Although Big Burger was an international restaurant chain, currently Big Burger only utilized Selector’s services for its U.S. operations. Specifically, Selector provided Big Burger’s real estate team with trade-area profiles for prospective Big Burger locations. Since Big Burger was a quick-service hamburger restaurant, most of its customers were drawn from the homes and businesses within a two-mile radius around each location. Selector’s trade-area profiles provided Big Burger with an overview of the individuals, households, and businesses within a potential location’s trade area.

Selector had invested in a deep warehouse of U.S. demographic, business, and consumer-behavior data, and their reports were extremely detailed. For example, Selector’s trade-area profile not only described proximal households according to their composition, annual income, and type of residence but they also reported the number of dollars these households spent on quick-serve hamburgers last year. They also listed a count of the total number of businesses and employees in the two-mile radius as well as the percent of businesses and employees within each two-digit standard industry code (SIC code). These trade-area profiles enabled Big Burger’s real estate team to discern if there was enough demand in the trade area to support a successful Big Burger location.

Ken waltzed into the office of Selector’s Research Director, Katrina Walsh. “Guess what? Selector’s going global!” he exclaimed. Ken told Katrina that the president of Big Burger asked Selector to provide trade-area profiles for their prospective European locations. The president had arranged for Ken to meet with Big Burger’s vice president of European operations in two weeks to demonstrate the trade-area profiles can be used to assess potential European Big Burger locations. Big Burger had provided Ken with the addresses of six potential sites: two in London, one in Madrid, and four in Berlin so that Selector could create examples of their trade-area profiles for these sites. Katrina was excited about the international project and assured Ken she would acquire the European data that was needed to generate the trade-area profiles.

Katrina contacted Selector’s data vendors in search of European demographic, business, and consumer behavior data. She quickly learned that acquiring the data at a small, precise level of geography would be a greater challenge than she had anticipated.
In the United States, the U.S. Census Bureau aggregates the data it collects into a set of standard hierarchical geographical units (see Table 1). To protect individual privacy, data is released at the Zip+4 level and higher. The standardization of the Census Bureau’s geographic order and the degree of detail within the Zip+4 level enable companies like Selector to extract precise data for a geographic area, such as a two-mile radius around a particular location, since the Census Bureau units are typically small enough to fit within that area.

Table 1: U.S. Statistical Territorial Units: Lowest Five Geographies Available from the U.S. Census
Statistical Unit Total Number Approximate Number of Households
METROPOLITAN STANDARD UNIT 316 30,245
ZIP CODE 41,940 3,167
CENSUS TRACT 62,276 1,551
BLOCK GROUP 229,466 420
ZIP+4 28,000,000 10

But, as Katrina learned from her data vendors, European countries were geographically organized in a different way. All members of the European Union were organized according to the Nomenclature of Territorial Units for Statistics (NUTS), devised by the Statistical Office of the European Communities (Eurostat) in 1988. There were several design challenges associated with the NUTS program since the countries possessed divergent geographic organizational systems and were reticent to abandon their existing geographic hierarchies. Five NUTS levels were created. The geography of most EU countries are divided into NUTS Levels 1-3. Some countries, further divide their geographic data into NUTS Levels 4 and 5.

Despite the efforts of the NUTS system, disparities in population and area still exist between similar NUTS levels across countries. For example, the largest geographic unit, NUTS Level 1, includes British government office regions, German länder, and Finish ahvenanmaa. But the Southeast government office region of England possesses over 17 million inhabitants, while the Finish ahvenanmaa, Åhland, only includes 25,000 people. These disparities also exist at lower levels of geography. Greater London, Berlin, and the Spanish provinces of Madrid and Barcelona—all NUTS Level 3 geographies—are comprised of populations exceeding 3 million people, while several NUTS Level 3 regions in Germany, Belgium, Austria, Finland, and Greece included less than 50,000 people. Even the smaller NUTS Levels differed greatly according to area: some Level 5 geographies could be as small as a square 50 meters while others could comprise an entire town.

Katrina also discovered that it would be challenging to acquire data at a two-mile radius around a specific address in Europe. NUTS data—even those at Levels 4 and 5—were much larger than the two-mile radius level of geography that Big Burger needed. Even a simple comparison of the NUTS level that a prospective site resided in would not be comparable across national boundaries within the European Union.
With ten days left to go before Ken’s meeting with Big Burger, Katrina wondered how she would generate trade-area profiles for Big Burger’s six European prospective locations.

Discussion Questions:

1. What assumptions have Ken and Katrina made in their response to Big Burger’s request for European trade-area data?

2. How can Katrina utilize the available European data—if at all?

3. What should be included on the trade-area profiles for Big Burger’s six European locations?

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