Business research method 8th edition

U O G IN TC O M ES RN A LE CHAPTER THE ROLE OF BUSINESS RESEARCH After studying this chapter, you should be able to Understand how research contributes to business success Know how to define business research Understand the difference between basic and applied business research Understand how research activities can be used to address business decisions Know when business research should and should not be conducted Appreciate the way that technology and internationalization are changing business research Chapter Vignette: “If It Quacks Like a Duck?” PR NEWSFOT O AFLAC “If you’re hurt and you miss work”: This is the tag line for one of the most popular U.S advertising campaigns—for AFLAC Insurance The tag line is accompanied by the familiar Pekin duck constantly reminding people with a loud “AFFLLAACKK!!” Recent polls show that the AFLAC duck has become one of America’s favorite icons, coming in second only to the Mars M&M’s characters But how has the duck’s favorable fan status affected AFLAC’s business performance? Certainly, AFLAC’s business strategy goes beyond creating the most popular duck since Donald! Throughout its thirty-year history, AFLAC, like other firms, has faced important business decisions about how to create brand awareness, how to build consumer knowledge of the brand, and how to build sales and loyalty Leading up to these decisions, the firm must first assess its current situation and its brand awareness relative to its competitors Approximately two dozen AFLAC duck commercials ago, research revealed that most consumers were unaware of AFLAC The vast majority of consumers would not list AFLAC when prompted to name insurance companies Instead, names like Allstate, State Farm, and Prudential proved more familiar Not surprisingly, these companies enjoyed greater market share Based on this research, AFLAC decided to invest in a national television campaign to build awareness of the brand name—“AFFLLAAACCK!!” The phonic similarity to “QUACK” proved successful Today, AFLAC has built great awareness of its name, but this hasn’t necessarily translated into business success Despite the tag line, fewer than 30 percent of consumers who recognize the name 93754_01_ch01_p001-017.indd 7/11/09 4:31:37 PM Chapter 1: The Role of Business Research know that AFLAC specializes in supplemental disability insurance This accounts for over three-fourths of AFLAC’s nearly $14 billion annual revenue Thus, while the initial research suggested the need for building awareness, their more recent research is addressing difficulties in creating the right knowledge of AFLAC What communication strategy is best for building knowledge? Can knowledge be built in the same way as awareness? Will knowledge lead to increased intentions to business with AFLAC? What role does the company play compared to the AFLAC sales associates in creating company image? All of these are questions that should be answered Business research will be directed toward answering these questions The information will then be used to try and erase the knowledge deficit faced by AFLAC If the answers are half as effective as those that led to the AFLAC duck, the company should enjoy tremendous success Thus, for AFLAC, as for many firms, research is an important tool in shaping business strategy.1 Introduction 93754_01_ch01_p001-017.indd Jelly Belly brand’s market research has capitalized on consumers’ desires to produce fifty varieties of jelly beans as well as recipes on how to create snacks with them © BEANBOOZLED COURTESY OF JELLY BELLY JELLY BEANS The recent history of AFLAC demonstrates the need for information in making informed decisions addressing key issues faced by all competitive businesses Research can provide that information Without it, business decisions involving both tactics and strategies are made in the dark We open with three examples illustrating how business decisions require intelligence and how research can provide that intelligence The following examples focus specifically on how research can lead to innovation in the form of new products, improvements in existing goods and services, or enhancements in employee relationships Imagine yourself in the role of business manager as you read these examples and think about the information needs you may have in trying to build success for your company Jelly Belly brand traditionally offered fifty official jelly bean flavors However, research input from customers has helped that number grow and now Jelly Belly even has a variety of specialty beans Consumers willingly submitted new flavor ideas as part of the Jelly Belly Dream Bean Contest (http://www.dreambeancontest.com) In return, the consumers received an opportunity to win prizes The company receives some really off-the-wall flavor ideas Among the strangest are flavors such as Dill Pickle, Rotten Egg, Taco, Burned Bacon, and Cream of Wheat.2 Top suggestions were put back on the Web so that people could vote for the flavor they most wanted to see introduced In 2008, the winning flavor was Acai Berry, which beat out other finalist flavors such as Sublime Chili Lime, Thai Iced Tea, and Mojito More recently, Jelly Belly is trying to capitalize on consumers’ desires for sports performance products Survey research suggests that consumers would respond favorably to food and drink products providing benefits that improve one’s ability to exercise.3 As a result, Jelly Belly has introduced Sport Beans Sport Beans contain added electrolytes, carbohydrates, and vitamins designed to provide added energy and alertness In addition, all the strange flavor suggestions also have spawned a new product offering for the entire jelly bean market Bean-Boozled Jelly Beans combines a traditional flavor with an exotic flavor that look identical, so consumers never know which one they are getting The product provides added value through the fun that comes with all the potential surprises A Skunk Spray bean looks exactly like a Licorice bean So, the bean lover never is sure when the bean will bamboozle! 7/11/09 4:31:38 PM U R V E Y COURTESY OF QUALTRICS.COM As a user of this book, you can take part in a real business research survey In each chapter, we’ll refer back to some aspect of this survey to illustrate key points about business research For instance, we can easily illustrate different types of survey approaches by referring back to some question contained in the T H I S ! survey In later chapters, your instructor will pro-vide you with a way to access not only the data from your particular class, but also data from all users This data can be used to illustrate some of the analytical approaches discussed in the closing chapters of the book For now, your instructor will provide you with instructions to access the h questionnaire via the Internet As a first step in this process, simply respond to the items in the questionnaire just as you would to any other research survey © GEORGE DOYLE S Successful companies are constantly scanning ideas in the hope of providing ways of adding value Jelly Belly’s Sports Beans and Bean-Boozled Beans offer two different ways of adding value.4 The coffee industry, after years of the “daily grind,” has proved quite dynamic over the past decade After years of steady decline, research on consumers’ beverage purchases show that coffee sales began rebounding around 1995 Telephone interviews with American consumers estimated that there were 80 million occasional coffee drinkers and million daily upscale coffee drinkers in 1995 By 2001, estimates suggested there were 161 million daily or occasional U.S coffee drinkers and 27 million daily upscale coffee drinkers.5 Coffee drinking habits have also changed In 1991 there were fewer than 450 coffeehouses in the United States Today, it seems like places such as Starbucks, Second Cup, The Coffee Bean & Tea Leaf, and Gloria Jean’s are virtually everywhere in the United States and Canada There are more than 15,000 thousand Starbucks locations around the world with the majority of these being wholly owned stores.6 While locating these outlets requires significant formal research, Starbucks also is researching new concepts aimed at other ways a coffee shop can provide value to consumers One concept that has survived testing thus far is the addition of free, in-store high-speed wireless Internet access Thus, you can have hot coffee in a hot spot! After Starbucks baristas began reporting that customers were asking clerks what music was playing in the stores, Starbucks began testing the sales of CDs containing their in-store music In 2009, Starbucks began a bundled pricing promotion offering a breakfast sandwich or pastry and a tall coffee drink for $3.95 in response to the declining economy The research that underlies the introduction of these value-added concepts could first include simply asking a consumer or a small group of consumers for their reaction to the concept Survey research and then actual in-store tests may follow So, the research underlying such decisions can be multilayered Often, business research is directed toward an element of an organization’s internal operations For example, DuPont utilizes research techniques to better understand their employees’ needs DuPont has ninety-four thousand employees worldwide and fifty-four thousand in the United States.7 The company has conducted four comprehensive work/life needs assessment surveys of its employees since 1985 This business research provides the company with considerable insight into employee work/life behavior and allows DuPont to identify trends regarding employee needs The most recent survey found that, as the company’s work force is aging, employees’ child care needs are diminishing, but elder care needs are emerging The survey found that 88 percent of respondents identified themselves as baby boomers About 50 percent of the employees say that they have— or expect to have—elder care responsibilities in the next three to four years, up from 40% in 1995 The surveys have shown that DuPont employees want to balance work and family responsibilities, feeling deeply committed to both aspects of their lives The latest research shows that company efforts to satisfy these desires have been successful Employee perception of support from management for work/life issues improved from the 1995 study and the results indicate employees feel less stress Support from colleagues is rated high, and women indicated they now have more 93754_01_ch01_p001-017.indd 7/11/09 4:31:39 PM Chapter 1: The Role of Business Research role models The study also reported that the feeling of management support is directly connected to employees’ efforts to make the company successful Employees who use the work/life programs are willing to “go the extra mile.” These examples illustrate the need for information in making informed business decisions Jelly Belly provides consumers with the incentive of free samples of jelly beans in return for ideas about desirable new bean flavors The statistics about coffee demonstrate how research can track trends that may lead to new business opportunities Starbucks’s research also illustrates how research can be used to examine new concepts in progressively more complex stages, setting the stage for a more successful product introduction DuPont’s ability to track employee attitudes allows them to adjust employee benefit packages to maximize satisfaction and reduce employee turnover These are only the tip of the iceberg when it comes to the types of business research that are conducted every day This chapter introduces basic concepts of business research and describes how research can play a crucial role in creating and managing a successful business The Nature of Business Research Business research covers a wide range of phenomena For managers, the purpose of research is to provide knowledge regarding the organization, the market, the economy, or another area of uncertainty A financial manager may ask, “Will the environment for long-term financing be better two years from now?” A personnel manager may ask, “What kind of training is necessary for production employees?” or “What is the reason for the company’s high employee turnover?” A marketing manager may ask, “How can I monitor my retail sales and retail trade activities?” Each of these questions requires information about how the environment, employees, customers, or the economy will respond to executives’ decisions Research is one of the principal tools for answering these practical questions Within an organization, a business researcher may be referred to as a marketing researcher, an organizational researcher, a director of financial and economic research, or one of many other titles Although business researchers are often specialized, the term business research encompasses all of these functional specialties While researchers in different functional areas may investigate different phenomena, they are similar to one another because they share similar research methods It’s been said that “every business issue ultimately boils down to an information problem.”8 Can the right information be delivered? The ultimate goal of research is to supply accurate information that reduces the uncertainty in managerial decision making Very often, decisions are made with little information for various reasons, including cost considerations, insufficient time to conduct research, or management’s belief that enough is already known Relying on seat-of-thepants decision making—decision making without research—is like betting on a long shot at the racetrack because the horse’s name is appealing Occasionally there are successes, but in the long run, intuition without research leads to losses Business research helps decision makers shift from intuitive information gathering to systematic and objective investigation Business Research Defined Business research is the application of the scientific method in searching for the truth about business phenomena These activities include defining business opportunities and problems, generating and evaluating alternative courses of action, and monitoring employee and organizational performance Business research is more than conducting surveys.9 This process includes idea and theory development, problem definition, searching for and collecting information, analyzing data, and communicating the findings and their implications This definition suggests that business research information is not intuitive or haphazardly gathered Literally, research (re-search) means “to search again.” The term connotes patient study and scientific investigation wherein the researcher takes another, more careful look at the data to discover all that is known about the subject Ultimately, all findings are tied back to the underlying theory The definition also emphasizes, through reference to the scientific method, that any information generated should be accurate and objective The nineteenth-century American humorist Artemus Ward claimed, “It ain’t the things we don’t know that gets us in trouble It’s the things we know that ain’t so.” In other words, research isn’t performed to support preconceived ideas 93754_01_ch01_p001-017.indd business research The application of the scientific method in searching for the truth about business phenomena These activities include defining business opportunities and problems, generating and evaluating ideas, monitoring performance, and understanding the business process 7/11/09 4:31:40 PM R E S E A R C H S N A P S H O T American consumers can be seen every day scouring nutrition labels Most likely, the item they show the most interest in recently is the amount of fat The Food and Drug Administration (FDA) is concerned that consumers get information that is not only accurate, but that also conveys the proper message to achieve a healthy diet But all fat is not created equal In particular, dieticians warn of the dangers associated with excess amounts of trans fats; diet nutrition labels break fats into saturated and unsaturated fats Among numerous factors that complicate the interpretation of the nutrition label, trans fat (hydrogenated) is technically a nonsaturated fat, but it acts more like a saturated fat when consumed So, where should it be placed? The FDA cannot address this problem intelligently without research addressing questions such as the following: © SUSAN VAN ETTEN If trans fats are listed as saturated fats, would consumers’ beliefs about their consumption become more negative? If the saturated fat amount includes a specific line indicating the amount of “saturated fat” that is really trans fat, would consumers become more confused about their diet? If all amounts of fat are given equal prominence on the label, will consumer attitudes toward the different types of fats be the same? Will consumers interpret foods free of trans fats as healthy? Making this even more complicated is the fact that some consumer segments, such as teenagers in this case, may actually use the nutrition labels to select the brands that are least nutritious rather than most nutritious So, they may actually seek out the one with the worst proportion of trans fats! The FDA specifically addressed trans fats in labeling regulations that took effect in 2006 Under these regulations, the FDA allows labels to claim zero trans fat as long as less than half a gram of hydrogenated oil per serving is contained Simple? Sources: “Health Labels are in the Eye of the Beholder,” Food Management 40 (January 2005), 80; Hunter, B T., “Labeling Transfat Is Tricky,” Consumers’ Research Magazine 86 (July 2003), 8–10; Weise, E., “Food Labels Now Required to Mention Trans Fat, Allergens,” USA Today (January 2, 2006), H1 © GEORGE DOYLE & CIARAN GRIFFIN Good Fat and Bad Fat but to test them The researcher must be personally detached and free of bias in attempting to find truth If bias enters into the research process, the value of the research is considerably reduced We will discuss this further in a subsequent chapter Our definition makes it clear that business research is designed to facilitate the managerial decision-making process for all aspects of the business: finance, marketing, human resources, and so on Business research is an essential tool for management in virtually all problem-solving and decision-making activities By providing the necessary information on which to base business decisions, research can decrease the risk of making a wrong decision in each area However, it is important to note that research is an aid to managerial decision making, never a substitute for it Finally, this definition of business research is limited by one’s definition of business Certainly, research regarding production, finance, marketing, and management in for-profit corporations like DuPont is business research However, business research also includes efforts that assist nonprofit organizations such as the American Heart Association, the San Diego Zoo, the Boston Pops Orchestra, or a parochial school Further, governmental agencies such as the Federal Emergency Management Agency (FEMA) and the Department of Homeland Security (DHS) perform many functions that are similar, if not identical, to those of for-profit business organizations For instance, the Food and Drug Administration (FDA) is an important user of research, employing it to address the way people view and use various food and drugs One such study commissioned and funded research to address the question of how consumers used the risk summaries that are included with all drugs sold in the United States.10 Therefore, not-for-profits and governmental agencies can use research in much the same way as managers at Starbucks, Jelly Belly, or DuPont While the focus is on for-profit organizations, this book explores business research as it applies to all institutions Applied and Basic Business Research applied business research Research conducted to address a specific business decision for a specific firm or organization One useful way to describe research is based on the specificity of its purpose Applied business research is conducted to address a specific business decision for a specific firm or organization The opening vignette describes a situation in which AFLAC may use applied research to decide how to best create knowledge of its supplemental disability insurance products 93754_01_ch01_p001-017.indd 7/11/09 4:31:40 PM Chapter 1: The Role of Business Research Basic business research (sometimes referred to as pure research) is conducted without a specific decision in mind, and it usually does not address the needs of a specific organization It attempts to expand the limits of knowledge in general, and as such it is not aimed at solving a particular pragmatic problem Basic research can be used to test the validity of a general business theory (one that applies to all businesses) or to learn more about a particular business phenomenon For instance, a great deal of basic research addresses employee motivation How can managers best encourage workers to dedicate themselves toward the organization’s goals? From such research, we can learn the factors that are most important to workers and how to create an environment where employees are most highly motivated This basic research does not examine the problem from any single organization’s perspective However, AFLAC, Starbucks, or DuPont’s management may become aware of such research and use it to design applied research studies examining questions about their own employees Thus, the two types of research are not completely independent, as basic research often provides the foundation for later applied research While the distinction between basic and applied is useful in describing research, there are very few aspects of research that apply only to basic or only to applied research We will use the term business research more generally to refer to either type of research The focus of this text is more on applied research—studies that are undertaken to answer questions about specific problems or to make decisions about particular courses of action or policies Applied research is emphasized in this text because most students will be oriented toward the day-to-day practice of management, and most students and researchers will be exposed to short-term, problem-solving research conducted for businesses or nonprofit organizations basic business research Research conducted without a specific decision in mind that usually does not address the needs of a specific organization It attempts to expand the limits of knowledge in general and is not aimed at solving a particular pragmatic problem The Scientific Method All research, whether basic or applied, involves the scientific method The scientific method is the way researchers go about using knowledge and evidence to reach objective conclusions about the real world The scientific method is the same in social sciences, such as business, as in physical sciences, such as physics In this case, it is the way we come to understand business phenomena Exhibit 1.1 briefly illustrates the scientific method In the scientific method, there are multiple routes to developing ideas When the ideas can be stated in researchable terms, we reach the hypothesis stage The next step involves testing the hypothesis against empirical evidence (facts from observation or experimentation) The results either support a hypothesis or not support a hypothesis From these results, new knowledge is generated the scientific method The way researchers go about using knowledge and evidence to reach objective conclusions about the real world EXHIBIT 1.1 A Summary of the Scientific Method Prior Knowledge Observation Hypotheses Hypothesis Test (Observation or Experimentation) Conclusion (New Knowledge) 93754_01_ch01_p001-017.indd 7/11/09 4:31:45 PM Part 1: Introduction In basic research, testing these prior conceptions or hypotheses and then making inferences and conclusions about the phenomena leads to the establishment of general laws about the phenomena Use of the scientific method in applied research ensures objectivity in gathering facts and testing creative ideas for alternative business strategies The essence of research, whether basic or applied, lies in the scientific method Much of this book deals with scientific methodology Thus, the techniques of basic and applied research differ largely in degree rather than in substance Managerial Value of Business Research product-oriented Describes a firm that prioritizes decision making in a way that emphasizes technical superiority in the product production-oriented Describes a firm that prioritizes efficiency and effectiveness of the production processes in making decisions In all of business strategy, there are only a few business orientations (see Exhibit 1.2) A firm can be product-oriented A product-oriented firm prioritizes decision making in a way that emphasizes technical superiority in the product Thus, research gathering information from technicians and experts in the field are very important in making critical decisions A firm can be production-oriented Production orientation means that the firm prioritizes efficiency and effectiveness of the production processes in making decisions Here, research providing input from workers, engineers, finance, and accounting becomes important as the firm seeks to drive costs down Production-oriented firms are usually very large firms manufacturing products in very large quantities The third is marketing-oriented, which focuses more on how the firm provides value to customers than on the physical product or production process With a marketing-oriented organization the majority of research focuses on the customer Research addressing consumer desires, beliefs, and attitudes becomes essential EXHIBIT 1.2 Business Orientations Product-Oriented Firm Example Prioritizes decision making that emphasizes the physical product design, trendiness or technical superiority The fashion industry makes clothes in styles and sizes that few can adopt Research focuses on technicians and experts in the field Production-Oriented Firm Example Prioritizes efficiency and effectiveness of the production processes in making decisions U.S auto industry’s assembly-line process is intent on reducing costs of production as low as possible Research focuses on line employees, engineers, accountants, and other efficiency experts Marketing-Oriented Firm Example Focuses on how the firm provides value to customers Well-known hotel chains are designed to address the needs of travelers, particularly business travelers Research focuses on customers marketing-oriented Describes a firm in which all decisions are made with a conscious awareness of their effect on the customer 93754_01_ch01_p001-017.indd We have argued that research facilitates effective management For example, Yoplait GoGurt illustrates the benefit of business research The company’s consumer research about eating regular yogurt at school showed that moms and kids in their “tweens” wanted convenience and portability Some brands, like Colombo Spoon in a Snap, offered the convenience of having a utensil as part of the packaging/delivery system However, from what Yoplait learned about consumers, they thought kids would eat more yogurts if they could “lose the spoon” and eat yogurt anywhere, anytime Moms and kids participating in a taste test were invited to sample different brand-on-the-go packaging shapes—long tubes, thin tubes, fat tubes, and other shapes—without being told how to handle the packaging One of the company’s researchers said, “It was funny to see the moms fidget around, then daintily pour the product onto a spoon, then into their mouths The kids instantly jumped on it They knew what to do.”11 Squeezing Go-Gurt from the tube 7/11/09 4:31:45 PM Chapter 1: The Role of Business Research was a big plus The kids loved the fact that the packaging gave them permission to play with their food, something parents always tell them not to Based on their research, Yoplait introduced Go-Gurt in a three-sided tube designed to fit in kids’ lunchboxes The results were spectacular, with more than $100 million in sales its first year on the market Yoplait realized that knowledge of consumers’ needs, coupled with product research and development, leads to successful business strategies As the Yoplait example shows, the prime managerial value of business research is that it provides information that improves the decision-making process The decision-making process associated with the development and implementation of a business strategy involves four interrelated stages: Identifying problems or opportunities Diagnosing and assessing problems or opportunities Selecting and implementing a course of action Evaluating the course of action Business research, by supplying managers with pertinent information, may play an important role by reducing managerial uncertainty in each of these stages Identifying Problems or Opportunities Before any strategy can be developed, an organization must determine where it wants to go and how it will get there Business research can help managers plan strategies by determining the nature of situations or by identifying the existence of problems or opportunities present in the organization Business research may be used as a scanning activity to provide information about what is occurring within an organization or in its environment The mere description of some social or economic activity may familiarize managers with organizational and environmental occurrences and help them understand a situation Consider these two examples: • • The description of the dividend history of stocks in an industry may point to an attractive investment opportunity Information supplied by business research may also indicate problems Employee interviews undertaken to characterize the dimensions of an airline reservation clerk’s job may reveal that reservation clerks emphasize competence in issuing tickets over courtesy and friendliness in customer contact Once business research indicates a problem or opportunity, managers may feel that the alternatives are clear enough to make a decision based on their experience or intuition However, often they decide that more business research is needed to generate additional information for a better understanding of the situation Diagnosing and Assessing Problems or Opportunities After an organization recognizes a problem or identifies a potential opportunity, business research can help clarify the situation Managers need to gain insight about the underlying factors causing the situation If there is a problem, they need to specify what happened and why If an opportunity exists, they may need to explore, refine, and quantity the opportunity If multiple opportunities exist, research may be conducted to set priorities Selecting and Implementing a Course of Action After the alternative courses of action have been clearly identified, business research is often conducted to obtain specific information that will aid in evaluating the alternatives and in selecting the best course of action For example, suppose Harley-Davidson is considering establishing a dealer network in either China or India In this case, business research can be designed to gather the relevant information necessary to determine which, if either, course of action is best for the organization 93754_01_ch01_p001-017.indd 7/11/09 4:31:45 PM 10 Part 1: Introduction Opportunities may be evaluated through the use of various performance criteria For example, estimates of market potential allow managers to evaluate the revenue that will be generated by each of the possible opportunities A good forecast supplied by business researchers is among the most useful pieces of planning information a manager can have Of course, complete accuracy in forecasting the future is not possible, because change is constantly occurring in the business environment Nevertheless, objective information generated by business research to forecast environmental occurrences may be the foundation for selecting a particular course of action Even the best plan is likely to fail if it is not properly implemented Business research may be conducted to indicate the specific tactics required to implement a course of action Evaluating the Course of Action evaluation research The formal, objective measurement and appraisal of the extent a given activity, project, or program has achieved its objectives performance-monitoring research Refers to research that regularly, sometimes routinely, provides feedback for evaluation and control of business activity © AGEFTOSTOCK/SUPERSTOCK Fun in the snow depends on weather trends, economic outlook, equipment, and clothing—all subjects for a business researcher 93754_01_ch01_p001-017.indd 10 After a course of action has been implemented, business research may serve as a tool to tell managers whether or not planned activities were properly executed and if they accomplished what they were expected to accomplish In other words, managers may use evaluation research to provide feedback for evaluation and control of strategies and tactics Evaluation research is the formal, objective measurement and appraisal of the extent a given activity, project, or program has achieved its objectives In addition to measuring the extent to which completed programs achieved their objectives or whether continuing programs are presently performing as projected, evaluation research may provide information about the major factors influencing the observed performance levels In addition to business organizations, nonprofit organizations and governmental agencies frequently conduct evaluation research Every year thousands of federal evaluation studies are undertaken to systematically assess the effects of public programs For example, the General Accounting Office has been responsible for measuring outcomes of the Employment Opportunity Act, the Job Corps program, and Occupational and Safety and Health Administration (OSHA) programs Performance-monitoring research is a specific type of evaluation research that regularly, perhaps routinely, provides feedback for the evaluation and control of recurring business activity For example, most firms continuously monitor wholesale and retail activity to ensure early detection of sales declines and other anomalies In the grocery and retail drug industries, sales research may use the Universal Product Code (UPC) for packages, together with computerized cash registers and electronic scanners at checkout counters, to provide valuable market-share information to store and brand managers interested in the retail sales volume of specific products United Airlines’ Omnibus in-flight survey provides a good example of performancemonitoring research for quality management United routinely selects sample flights and administers a questionnaire about inflight service, food, and other aspects of air travel The Omnibus survey is conducted quarterly to determine who is flying and for what reasons It enables United to track demographic changes and to monitor customer ratings of its services on a continuing basis, allowing the airline to gather vast amounts of information at low cost The 7/11/09 4:31:45 PM 660 undisguised questions Straightforward questions that assume the respondent is willing to answer uniform resource locator (URL) A Web site address that Web browsers recognize unit of analysis What or who should provide the data and at what level of aggregation it should be analyzed (organizations, strategic business units, departments, families, individuals ) univariate statistical analysis Tests of hypotheses involving only one variable unobtrusive methods Methods in which research respondents not have to be disturbed for data to be gathered unstructured question A question that does not restrict the respondents’ answers V validity The accuracy of a measure or the extent to which a score truthfully represents a concept value labels Unique labels assigned to each possible numeric code for a response variable piping software Software that allows variables to be inserted into an Internet questionnaire as a respondent is completing it variable Anything that varies or changes from one instance to another; variables can exhibit differences in value, usually in magnitude or strength, or in direction variance A measure of variability or dispersion Its square root is the standard deviation variate A mathematical way in which a set of variables can be represented with one equation 93754_29_glos_b_p648-660.indd 660 Glossary verification Quality-control procedures in fieldwork intended to ensure that interviewers are following the sampling procedures and to determine whether interviewers are cheating visible observation Observation in which the observer’s presence is known to the subject voice-pitch analysis A physiological measurement technique that records abnormal frequencies in the voice that are supposed to reflect emotional reactions to various stimuli W welcome screen The first Web page in an Internet survey, which introduces the survey and requests that the respondent enter a password or pin within-group error or variance The sum of the differences between observed values and the group mean for a given set of observations, also known as total error variance within-subjects design Involves repeated measures because with each treatment the same subject is measured World Wide Web (WWW) A portion of the internet that is a system of computer servers that organize information into documents called Web pages Z Z-test for differences of proportions A technique used to test the hypothesis that proportions are significantly different for two independent samples or groups 7/14/09 9:19:25 AM D O S ENDNOTES Chapter 1 Grapetime, Terry, “Vote for Me,” Marketing Research 16 (Winter 2004), 5; “AFLAC’s Quacking Duck Selected One of America’s Favorite Icons,” Best Review 105 (October 2004), 119; Gage, Jack, “Waddling Through,” Forbes 176 (August 15, 2005), 90 Keyo, Michelle “Web Site of the Week: Jelly Belly: Using Sampling to Build a Customer Database,” Inc Online (1996), http://www.inc.com, December 9, 1996 Penn, Catherine, “New Drinks Include a Health Benefit for 05,” Beverage Industry, 96 (January 2005), 45–54 Jelly Belly Candy Company (March 6, 2008) “April Fools’ Day: Bamboozle Someone with New Jelly Belly BeanBoozled Jelly Beans: A Fools Errand and Silly Celebrations.” Press release “U.S Coffee Makers Perky as Consumption Increases,” Nations Restaurant Business 36 (April 22, 2002), 34; “U.S Specialty Coffee Market in 30 Year Renaissance,” (December 15, 2000), http://www cnn.com Kafka, Peter, “Bean-Counter,” Forbes 175 (February 28, 2005), 78–80 Adapted from “DuPont Employee Survey Finds Eldercare Emerging as Key Work/Life Issues,” PR Newswire (January 2, 2001), 49–93 Garvin, Andrew P., “Evolve Approach to Serve Complex Market,” Marketing News (September 15, 2005), 22 Gibson, Lawrence D., “Quo Vadis Marketing Research?” Marketing Research 12 (Spring 2000), 36–41 10 Matthew, Arnold, “FDA Delays DTC Draft Guidance to Study How 11 12 13 14 15 Consumers Use Brief Summaries,” Medical Marketing and Media 39 (November 2004), 10 Reyes, Sonia, “Ian Friendly: Groove Tube,” BrandWeek (October 16, 2000), M111–M116 Garretson, Judith and Scot Burton, “The Role of Spokescharacters as Advertisement and Package Cues in Integrated Marketing Communications,” Journal of Marketing 69 (October 2005), 118–132 Clancy, Kevin J and Randy L Stone, “Don’t Blame the Metrics,” Harvard Business Review 83 (June 2005), 26–28 Honomichl, Jack, “Growth Stunt,” Marketing News (June 4, 2001), 144 “You Say Tomato, I Say Tomahto,” Express Magazine (Spring 2006), 19 Chapter 2 Collett, Stacy, “External Business Intelligence Can Be a Powerful Addition to Your Data Warehouse, but Beware of Data Overload,” Computerworld (April 15, 2002), 34; “Krispy Kreme to Open Stores in China,” Atlanta 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Cassidy, Hilary, “Many Paths to Cool, but big Gains for All,” Brandweek 46 (June 20, 2005), S53 Niemi, Wayne, “Schoenfeld to Leave as Vans CEO; As Its Deal with VF Corp Closes, the Skate Brand Gains a New President and a New Focus on Apparel,” Footwear News (July 5, 2004), McLaughlin, Lisa, “The New Roll Model,” Time 164 ( July 26, 2004), 74 Sayre, Shay, Qualitative Methods for Marketplace Research (Thousand Oaks, CA: Sage, 2001) Sayre, Shay, (2001); Morse, Janice M and Lyn Richards, Readme First for a User’s Guide to Qualitative Methods (Thousand Oaks, CA: Sage, 2002) See, for example, May, Carl, “Methodological Pluralism: British Sociology and the Evidence-Based State: A Reply to Payne et al.,” Sociology 39 (July 2005), 519–528; Achenbaum, A A., “When Good Research Goes Bad,” Marketing Research 13 (Winter 2001), 13–15; Wade, K R., “We Have Come Upon the Enemy: And They Are Us,” Marketing Research 14 (Summer 2002), 39; Neill, James, “Qualitative versus Quantitative Research: Key Points in a Classic Debate,” http://wilderdom.com/ research/QualitativeVersusQuantitative Research.html, accessed February 6, 2009 Babin, Barry J., William R Darden, and Mitch Griffin, “Work and/ or Fun: Measuring Hedonic and Utilitarian Shopping Value,” Journal of Consumer Research 20 (March 1994), 644–656 7/14/09 9:19:54 AM Endnotes 10 11 12 13 14 15 16 17 18 19 20 21 22 Stengal, J R., A L Dixon, and C T Allen, “Listening Begins at Home,” Harvard Business Review (November 2003), 106–116 Semon, Thomas T., “You Get What You Pay for: It May Be Bad MR,” Marketing News 36 (April 15, 2002), Thompson, Craig J., “Interpreting Consumers: A Hermeneutical Framework for Deriving Marketing Insights from the Tests of Consumers’ Consumption Stories,” Journal of Marketing Research 34 (November 1997), 438–455; Woodside, Arch G., H M Pattinson, and K E Miller, “Advancing Hermeneutic Research for Interpreting Interfirm New Product Development,” Journal of Business and Industrial Marketing 20 (2005) 364–379 Thompson, Craig J., “Interpreting Consumers: A Hermeneutical Framework for Deriving Marketing Insights from the Tests of Consumers’ Consumption Stories,” Journal of Marketing Research 34 (November 1997), 438–455 (see pp 443–444 for quotation) While we refer to a hermeneutic unit as being text-based here for simplicity, they can actually also be developed using pictures, videotapes, or artifacts as well Software such as Atlas-TI will allow files containing pictures, videos, and text to be combined into a hermeneutic unit Morse, Janice M and Lyn Richards (2002) See Feldman, Stephen P., “Playing with the Pieces: Deconstruction and the Loss of Moral Culture,” Journal of Management Studies 35 ( January 1998), 60–80 “Futurespeak,” American Demographics 26 (April 2004), 44 Louella, Miles, “Living Their Lives,” Marketing (UK) (December 11, 2003), 27–28 Reid, D M., “Changes in Japan’s Post-Bubble Business Environment: Implications for Foreign-Affiliated Companies,” Journal of International Marketing 7, no (1999), 38–63 Morse, Janice M and Lyn Richards (2002) Strauss, A L and J Corbin, Basics of Qualitative Research (Newbury Park, CA: Sage Publications, 1990) Glaser, B G., and Strauss, A L., The Discovery of Grounded Theory: Strategies for Qualitative Research (New York: Aldine Publishing Company, 1967) Geiger, S and D Turley, “Personal Selling as a Knowledge-Based Activity: Communities of Practice in the Sales Force,” Irish Journal of Management 26 (2005), 61–70 Beverland, M., “The Components of Prestige Brands,” Journal of Business Research 59 (February 2006) 251– 258; 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and STATUSA, “What Information Is Available under GLOBUS and NTBD?” and “GLOBUS & NTDB,” http://www.stat-usa.gov, accessed February 6, 2006 Based on Brown, Warren, “Pain at the Pump Doesn’t Faze NewCar Buyers,” Washington Post (January 29, 2006), http://www washingtonpost.com; Wells, Melanie, “Snowboarding Secrets,” Forbes (February 14, 2005), http://web5 infotrac.galegroup.com; Halliday, Jean, “Automakers Scrap SUVs, Tout Hybrids,” Advertising Age (September 26, 2005), http://web5 infotrac.galegroup.com Chapter “About In-Stat,” In-Stat, http:// www.instat.com/index.asp; Nissen, Keith, “In-Depth Analysis: The Media Phone Has Arrived!” In-Stat, http://www.instat.com/promos/09/ dl/media_phone_3ufewaCr.pdf Vascellaro, Jessica E., “Who’ll Give Me $50 for This Purse from Nana?” Wall Street Journal (December 28, 2005), http://online.wsj.com; “Survey Reveals Majority of Americans Receive Unwanted Gifts,” Survey.com news release (December 19, 2005), http://www survey.com Excerpts from Arlen, Michael J., Thirty Seconds (New York: Farrar, Straus and Giroux, Inc., 1979, 1980), 185–186.This material first appeared in the New Yorker However, the popularity of marketing research has affected the willingness of respondents to participate in surveys People are increasingly refusing to participate Tuckel, Peter and Harry O’Neill, “The Vanishing Respondent in Telephone Surveys,” (paper presented at the 56th annual conference of the American Association of Public Opinion Research [AAPOR], Montreal, Canada, May 17–20, 2001) Cull, William L., Karen G O’Connor, Sanford Sharp, and Suk-fong S.Tang, “Response Rates and Response Bias for 50 Surveys of Pediatricians,” Health Services Research (February 2005), downloaded from http://galenet.galegroup.com Lee, Eunkyu, Michael Y Hu, and Rex S Toh, “Respondent Noncooperation in Surveys and Diaries: An Analysis of Item Non-Response and Panel Attrition,” International Journal of Market Research (Autumn 2004), downloaded from http://web7.infotrac.galegroup.com Douglas Aircraft, Consumer Research (undated), p 13 For an interesting study of extremity bias, see Baumgartner, Hans and Jan-Benedict E M Steenkamp, “Response Styles in Marketing Research: A CrossNational Investigation,” Journal of Marketing Research (May 2001), 143–156 10 Turner, Charles F., Maria A Villarroel, James R Chromy, Elizabeth Eggleston, and Susan M Rogers, “Same-Gender Sex among U.S Adults: Trends across the Twentieth Century and during the 1990s,” Public Opinion Quarterly (Fall 2005), downloaded from http://web7.infotrac.galegroup.com 11 The term questionnaire technically refers only to mail and self-administered surveys, and the term interview schedule is used for interviews by telephone or face-to-face However, we will use questionnaire to refer to all three forms of communications in this book 12 Sobel, Bill, “Poll Reveals Men More Likely Than Women to Keep Their New Year’s Resolutions” (December 7/14/09 9:19:54 AM 664 13 14 15 16 17 29, 2008), http://www.sobelmedia com/2008/12/29/poll-reveals-menmore-likely-than-women-to-keeptheir-new-years-resolutions, accessed March 30, 2009 Ohlemacher, Stephen, “Study Finds That Marriage Builds Wealth,” Yahoo! News (January 18, 2006), http://news.yahoo.com; Charles Pierret, “The National Longitudinal Survey of Youth: 1979 Cohort at 25,” Monthly Labor Review (February 2005), 3–7 The Bureau of Business Practice, Profiles in Quality: Blueprints for Action from 50 Leading Companies (Boston: Allyn and Bacon, 1991), 113 Weisberg, Karen, “Change Maker,” Food Service Director (January 15, 2006), downloaded from http:// web7.infotrac.galegroup.com Gavin, David A., “Competing on the Eight Dimensions of Quality,” Harvard Business Review (November– December 1987), 101–8 Forelle, Charles, “Many Colleges Ignore New SAT Writing Test,” Wall Street Journal (December 7, 2005), http://online.wsj.com; “Kaplan’s New SAT Survey Results,” Kaplan Inc., College Admissions, Kaplan Web site, http://www.kaptest.com, accessed February 14, 2006 Endnotes 10 11 12 13 14 15 16 Chapter 10 Warwick, Donald T and Charles A Lininger, The Sample Survey: Theory and Practice (New York: McGrawHill, 1975), Lockley, L C., “Notes on the History of Marketing Research,” Journal of Marketing (April 1950), 733 Hof, Robert D., “The Power of Us,” BusinessWeek (June 20, 2005), http://web2.infotrac.galegroup.com For a complete discussion of conducting surveys in Hispanic neighborhoods, see Hernandes, Sigfredo A and Carol J Kaufman, “Marketing Research in Hispanic Barrios: A Guide to Survey Research,” Marketing Research (March 1990), 11–27 Curtin, Richard, Stanley Presser, and Eleanor Singer, “Changes in Telephone Survey Nonresponse over the Past Quarter Century,” Public Opinion Quarterly (Spring 2005), http://web3.infotrac.galegroup.com Cuneo, Alice Z., “Researchers Flail as Public Cuts the Cord,” Advertising Age (November 15, 2004), http:// web3.infotrac.galegroup.com See ibid.; and Jon Kamman, “Cell Phones Put Pollsters ‘in a Muddle,’” USA Today (December 31, 2003), http://www.usatoday.com Hembroff, Larry A., Debra Rusz, Ann Rafferty, Harry McGee, and Nathaniel Ehrlich, “The CostEffectiveness of Alternative Advance 93754_30_EN_p661-667.indd 664 17 18 19 20 21 22 Mailings in a Telephone Survey,” Public Opinion Quarterly (Summer 2005), http://web3.infotrac galegroup.com Brennan, Mike, Susan Benson, and Zane Kearns, “The Effect of Introductions on Telephone Survey Participation Rates,” International Journal of Market Research 47, no (2005), 65–74 Dillman, Don A., Mail and Internet Surveys: The Tailored Design Method (New York: John Wiley and Sons, 2000), 173 Schaefer, David R and Don A Dillman, “Development of a Standard E-Mail Methodology: Results of an Experiment,” Public Opinion Quarterly 62, no (Fall 1998), 378 Ibid For a complete discussion of fax surveys, see the excellent article by Dickson, John P and Douglas L Maclachlan, “Fax Surveys: Return Patterns and Comparison with Mail Surveys,” Journal of Marketing Research (February 1996), 108–113 Merriman, Joyce A., “Your Feedback Is Requested,” American Family Physician (October 1, 2005), http://web3.infotrac.galegroup com Dillmann, D A (2000), 369–372 Göritz, Anja S., “Recruitment for On-Line Access Panels,” International Journal of Market Research 46, no 4, (2004), 411–425 Fricker, Scott, Mirta Galesic, Roger Tourangeau, and Ting Yan, “An Experimental Comparison of Web and Telephone Surveys,” Public Opinion Quarterly (Fall 2005), http:// web3.infotrac.galegroup.com See Nielsen, Jakob, “Keep Online Surveys Short,” Alertbox (February 2, 2004), http://www.useit.com; “About Jakob Nielsen,” http:// www.useit.com, accessed February 21, 2006; and Nielsen Norman Group, “About Nielsen Norman Group,” http://www.nngroup.com, accessed February 21, 2006 See Kilbourne, Lawrene, “Avoid the Field of Dreams Fallacy,” Quirk’s Marketing Research Review (January 2005), 70, 72–73 Mary Lisbeth D’Amico, “Call Security,” Wall Street Journal (February 13, 2006), http://online wsj.com For an interesting empirical study, see Akaah, Ishmael P and Edward A Riordan, “The Incidence of Unethical Practices in Marketing Research: An Empirical Investigation,” Journal of the Academy of Marketing Sciences (Spring 1990), 143–152 Based on “Do-Not-Call List Reduces Telemarketing, Poll Finds,” Wall Street Journal (January 12, 2006), http://online.wsj.com Chapter 11 Four Seasons Hotel Chicago, http:// www.fourseasons.com/chicagofs/ dining.html; Mystery Shopping Providers Association, http:// www.mysteryshop.org; Michelson, M., “Taking the Mystery Out of Mystery Shopping,” Mystery Shopping Providers Association, www.mspa-eu.org/about/ MysteryShopping1.ppt Selltiz, Claire, Lawrence S Wrightsman, and Stuart W Cook, Research Methods in Social Relations (New York: Holt, Rinehart and Winston, 1976), 251 Campbell, Angus, Philip E Converse, and Willard L Rodgers, The Quality of American Life (New York: Russell Sage Foundation, 1976), 112 Although weather conditions did not correlate with perceived quality of life, the comfort variable did show a relationship with the index of wellbeing This association might be confounded by the fact that ventilation and/ or air-conditioning equipment is less common in less affluent homes Income was previously found to correlate with quality of life Abrams, Bill, The Observational Research Handbook (Chicago: NTC Business Books, 2000), 2, 105 Adapted with permission from the April 30, 1980, issue of Advertising Age Copyright © 1980 by Crain Communications, Inc “Inside TV Ratings,” Nielsen Media Research, http://www.nielsenmedia com, accessed February 21, 2009 “The Portable People Meter System,” Arbitron, http://www arbitron.com, accessed February 24, 2006 “About the PreTesting Company” and “Television,” PreTesting Company, http://www.pretesting com, accessed February 24, 2006 “Accurate Web Site Visitor Measurement Crippled by Cookie Blocking and Deletion,” Jupiter Media news release, (March 14, 2005), http://www.jupitermedia com; See also Johnson, Steve, “Who’s in Charge of the Web Site Ratings Anyway?” Chicago Tribune (February 26, 2006), sec 1, p 18 10 Kiley, David, “Google: Searching for an Edge in Ads,” BusinessWeek (January 30, 2006), downloaded from http://web3.infotrac.galegroup.com; See also Sanders, Pieter and Bram Lebo, “Click Tracking: A Fool’s Paradise?” Brandweek (June 6, 2005), http://web3.infotrac.galegroup.com 11 Neff, Jack, “Aging Population Brushes Off Coloring,” Advertising Age (July 25, 2005), downloaded from http://web5.infotrac.galegroup com 12 Stringer, Kortney, “Eye-Tracking Technology for Marketers,” Detroit Free Press (August 1, 2005), downloaded from http://galenet galegroup.com 13 Herbert B Krugman’s statement as quoted in “Live, Simultaneous Study of Stimulus, Response Is Physiological Measurement’s Great Virtue,” Marketing News (May 15, 1981), 1, 20 14 Based on “Mazda Turns to EyeTracking to Assist Revamp of European Site,” New Media Age (November 3, 2005), downloaded from http://galenet.galegroup com; and “Persuasion Is the New Focus,” Revolution (February 21, 2006), downloaded from the Media Coverage page of the Syzygy Web site, http://www.syzygy.co.uk 15 Adapted with permission from Rayner, Bruce, “Product Development, Now Hear This!” Electronic Business (August 1997) Chapter 12 Kohlhoff, C and R Steele, “Evaluating SOAP for High Performance Business Applications: Real-Time Trading Systems.” Proceedings of WWW2003, May 20–24, 2003, Budapest, Hungary, accessed from http://staff.it.uts.edu au/~rsteele/EvaluatingSOAP.pdf Based on McNatt, D Brian and Timothy A Judge, “Self-Efficacy Intervention, Job Attitudes, and Turnover: A Field Experiment with Employees in Role Transition,” Human Relations 61, no (June 2008), 783–810, Shadish, William R., Thomas D Cook, and Donald T Campbell, Experimental and Quasi Experimental Designs for Generalized Causal Inference (Geneva, IL: Houghton Mifflin, 2002) Ellingstad, Vernon and Norman W Heimstra, Methods in the Study of Human Behavior (Monterey, CA: Brooks/Cole, 1974) Anderson, Barry F., The Psychological Experiment: An Introduction to the Scientific Method (Belmont, CA: Brooks/Cole, 1971), 28, 42–44 Reitter, Robert N., “Comment: American Media and the SmokingRelated Behaviors of Asian Adolescents,” Journal of Advertising Research 43 (March 2003), 12–13 Lach, Jennifer, “Up in Smoke,” American Demographics 22 (March 2000), 26 Mitchell, Vincent-Wayne and Sarah Haggett, “Sun-Sign Astrology in Market Segmentation: An Empirical Investigation,” Journal of Consumer Marketing 14, no (1997), 113–131 Roethlisberger, F J and W J Dickson, Management and the Worker (Harvard University Press: Cambridge, MA, 1939) 7/14/09 9:19:54 AM Endnotes 10 Shiv, Baba, Ziv Carmon, and Dan Aneley, “Placebo Effects of Marketing Actions: Consumers May Get What They Pay for,” Journal of Marketing Research 42 (November 2005), 383–393 11 Tybout, Alice M and Gerald Zaltman, “Ethics in Marketing Research: Their Practical Relevance,” Journal of Marketing Research 21 (November 1974), 357–368 12 Peterson, Robert A., “On the Use of Students in Social Science Research: Evidence from a Second Order Meta Analysis,” Journal of Consumer Research 28 (December 2001), 450–461 13 Shadish, William R., Thomas D Cook, and Donald T Campbell (2002) 14 Reprinted with permission from Lee Martin, Geoffrey “Drinkers Get Court Call,” Advertising Age (May 20, 1991) Copyright © 1991 Crain Communications, Inc Chapter 13 Babin, Barry J and Jill Attaway, “Atmospheric Affect as a Tool for Creating Value and Gaining Share of Customer,” Journal of Business Research 49 (August 2000), 91–99; Verhoef, P C., “Understanding the Effect of Customer Relationship Management Efforts on Customer Retention and Customer Share Development,” Journal of Marketing 67 (October 2003), 30–45 Periatt, J A., S A LeMay, and S Chakrabarty, “The Selling Orientation-Customer Orientation (SOCO) Scale: Cross-Validation of the Revised Version,” Journal of Personal Selling and Sales Management 24 (Winter 2004), 49–54 Anderson, Barry F., The Psychology Experiment (Monterey, CA: Brooks/ Cole, 1971), 26 Kerlinger, Fred N., Foundations of Behavioral Research (New York: Holt, Rinehart and Winston, 1973) Cohen, Jacob, “Things I Have Learned (So Far),” American Psychologist 45 (December 1990), 1304–1312 Arnold, Catherine, “Satisfaction’s the Name of the Game,” Marketing News 38 (October 15, 2004), 39–45 Also, see http://www.theacsi.org In more advanced applications such as those involving structural equations analysis, a distinction can be made between reflective composites and formative indexes See Hair, J F., W C Black, B J Babin, R Anderson, and R Tatham, Multivariate Data Analysis, 6th ed (Upper Saddle River, NJ: Prentice Hall, 2006) Bart, Yakov, Venkatesh Shankar, Fareena Sultan, and Glen L Urban, “Are the Drivers and Role of 93754_30_EN_p661-667.indd 665 665 10 11 12 13 14 15 Online Trust the Same for All Web Sites and Consumers? A LargeScale Exploratory Study,” Journal of Marketing 69 (October 2005), 133–152 Cronbach, Lee J and Richard J Shavelson, “My Current Thoughts on Coefficient Alpha and Successor Procedures,” Educational and Psychological Measurement 64 (June 2004), http://epm.sagepub.com/cgi/ content/short/64/3/391 Hair et al (2006) Wells, Chris, “The War of the Razors,” Esquire (February 1980), Babin, Barry J., William R Darden, and Mitch Griffin, “Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value,” Journal of Consumer Research 20 (March 1994), 644–656 Hair et al (2006) Cox, Keith K and Ben M Enis, The Marketing Research Process (Pacific Palisades, CA: Goodyear, 1972); Kerlinger, Fred N., Foundations of Behavioral Research, 3rd ed (Ft Worth: Holt, Rinehart and Winston, 1986) Headley, Dean E., Brent D Bowen, and Jacqueline R Liedtke This case, originally titled “Navigating through Airline Quality,” was reviewed and accepted for publication by the Society for Case Research Chapter 14 Anhalt, Karen Nickel, “Whiskas Campaign Recruits a Tiny Tiger,” Advertising Age International (October 19, 1998), 41 Breeden, Richard, “Owners, Executives Cite Small Firms’ Advantages,” Wall Street Journal (January 3, 2006), http://online.wsj.com; “SMB State of the Union Study,” AllBusiness com (Winter 2005), news and press page, http://www.allbusiness.com/ press/barometer.pdf Likert, Rensis, “A Technique for the Measurement of Attitudes,” Archives of Psychology 19 (1931), 44–53 Osgood, Charles, George Suci, and Percy Tannenbaum, The Measurement of Meaning (Urbana: University of Illinois Press, 1957) Seven-point scales were used in the original work; however, subsequent researchers have modified the scale to have five points, nine points, and so on Menezes, Dennis and Norbert F Elbert, “Alternative Semantic Scaling Formats for Measuring Store Image: An Evaluation,” Journal of Marketing Research (February 1979), 80–87 Costanzo, Chris, “How Consumer Research Drives Web Site Design,” American Banker (April 19, 2005), http://galenet.galegroup.com “Technology Still Matters to Start-Ups Say Venture Capitalists and Other Industry Influencers,” Roeder-Johnson Corp news release (January 24, 2006), http://finance yahoo.com; “Importance of Unique Technology to Start-Up Companies: A Survey,” Roeder-Johnson Corp (January 2006), http://www roederjohnson.com Chapter 15 10 11 White, Joseph B., “The Price of Safety,” Wall Street Journal (December 5, 2005), http:// online.wsj.com; “J.D Power and Associates Reports: Premium Surround Sound Systems and HD Radio Garner High Consumer Interest Based on Their Market Price, while Consumers Prefer One-Time Fee over the Monthly Fee Associated with Satellite Radio,” J.D Power and Associates news release (August 18, 2005), http:// www.jdpower.com Smith, Robert, David Olah, Bruce Hansen, and Dan Cumbo, “The Effect of Quesionnaire Length on Participant Response Rate: A Case Study in the U.S Cabinet Industry,” Forest Products Journal (November– December 2003), http://galenet galegroup.com “Insurers Question Methods in U.S Treasury Survey on Terror Backstop,” A M Best Newswire (April 12, 2005), http://galenet galegroup.com “Mothers Misunderstand Questions on Feeding Questionnaire,” medical letter on the CDC and FDA (September 5, 2004), http://galenet galegroup.com Donahue, Amy K and Joanne M Miller, “Citizen Preferences and Paying for Police,” Journal of Urban Affairs 27, no (2005): 419–35 Weber, Nathan, “Research: A Survey Shows How Media Influence Our Decorating and Cooking Choices,” HFN, the Weekly Newspaper for the Home Furnishing Network (December 5, 2005), http:// galenet.galegroup.com Payne, Stanley L., The Art of Asking Questions (Princeton, NJ: Princeton University Press, 1951), 185 The reader who wants a more detailed account of question wording is referred to this classic book on that topic Roll, Charles W., Jr and Albert H Cantril, Polls: Their Use and Misuse in Politics (New York: Basic Books, 1972), 106–7 “Hilarious Republican Senate Leadership Survey,” The Misanthropic Principle: The Blog of a Bipolar Misanthrope, http:// misanthropicscott.wordpress com/2008/04/19/hilariousrepublican-senate-leadership-survey/, accessed March 9, 2009 Payne, Stanley L (1951), 102–3 Dillman, Don A., Mail and Internet Surveys: The Tailored Design Method 12 13 14 15 16 17 (New York: John Wiley and Sons, 2000), 357–61 Young, Sarah J and Craig M Ross, “Web Questionnaires: A Glimpse of Survey Research in the Future,” Parks & Recreation 35, no (June 2000), 30 Michel, Matt “Controversy Redux,” CASRO Journal, http://www decisionanalyst.com/publ_art/ contredux.htm, accessed February 8, 2001 Ghaleb Almekhlafi, Abdurrahman, “Preservice Teachers’ Attitudes and Perceptions of the Utility of WebBased Instruction in the United Arab Emirates,” International Journal of Instructional Media 32, no (2005): 269–84 Harzing, Anne-Wil, “Does the Use of English-Language Questionnaires in Cross-National Research Obscure National Differences?” International Journal of Cross Cultural Management 5, no (2005): 213–24 Cateora, Philip R., International Marketing (Homewood, IL: Richard D Irwin, 1990), 387–89 “Hospitals, Feds Design Survey to Identify Culture That Encourages Patient Safety,” Health Care Strategic Management (February 2005), http:// galenet.galegroup.com; “Hospital Survey on Patient Safety Culture,” Agency for Healthcare Research and Quality, http://www.ahrq.gov/qual/ hospculture, accessed March 7, 2006 Chapter 16 Jones, J M., “Debt, Money Woes Are Top Family Financial Problems,” Gallup Inc (March 6, 2009), http:// www.gallup.com Kinne, Susan and Tari D.Topolski, “Inclusion of People with Disabilities in Telephone Health Surveillance Surveys,” American Journal of Public Health 95, no (March 2005): 512–517 Brock, Sabra E., “Marketing Research in Asia: Problems, Opportunities, and Lessons,” Marketing Research (September 1989), 47 Yeganeh, Hamid, Zhan Su, Elie Virgile, and M Chrysostome, “A Critical Review of Epistemological and Methodological Issues in Cross-Cultural Research,” Journal of Comparative International Management (December 2004), http://web2 infotrac.galegroup.com Sigenman, Lee, Steven A.Tuch, and Jack K Martin, “What’s in a Name? Preference for ‘Black’ versus ‘African-American’ among Americans of African Descent,” Public Opinion Quarterly (Fall 2005), http://web2.infotrac.galegroup.com Rideout, Bruce E., Katherine Hushen, Dawn McGinty, Stephanie Perkins, and Jennifer Tate, “Endorsement of the New Ecological Paradigm in Systematic and E-Mail Samples of College Students,” 7/14/09 9:19:54 AM 666 10 11 12 13 14 Journal of Environmental Education (Winter 2005), http://web2.infotrac galegroup.com SurveySite, “What We Do: Quantitative Research,” http:// www.surveysite.com, accessed March 15, 2006 “Frequently Asked Questions about Conducting Online Research: New Methodologies for Traditional Techniques,” Council of American Survey Research Organizations (CASRO) (1998), http://www casro.org Mellinger, Gloria, “World Opinion Research Profiles,” Harris Interactive Inc (July 18, 2000) Ibid “Frequently Asked Questions about Conducting Online Research” (1998) “Internet Sampling Solutions,” Survey Sampling International, http://www.ssisamples.com, accessed March 15, 2006 Based on Gene Mueller, “It’s Hard to Figure Number of Anglers,” Washington Times (March 20, 2005), http://web3.infotrac.galegroup com; Atlantic Coastal Cooperative Statistics Program, “About Us: Committees,” http://www.accsp.org, accessed March 16, 2006; Atlantic States Marine Fisheries Commission, “About Us,” http://www.asmfc.org, accessed March 16, 2006 Material for this case is from Scientific Telephone Samples User’s Manual, Scientific Telephone Samples, Santa Ana, CA Endnotes Based on Gerdes, Geoffrey R., Jack K Walton II, May X Liu, Darrel W Parke, and Namirembe Mukasa,“Trends in the Use of Payment Instruments in the United States,” Federal Reserve Bulletin (Spring 2005), http://web2.infotrac galegroup.com Most of the statistical material in this book assumes that the population parameters are unknown, which is the typical situation in most applied research projects The reasons for this are related to the concept of degrees of freedom, which will be explained later At this point, disregard the intuitive notion of division by n, because it produces a biased estimate of the population variance In practice, most survey researchers will not use this exact formula A modification of the formula, Z ϭ (X Ϫ ␮)/S, using the sample standard deviation in an adjusted form, is frequently used Hayes, William L., Statistics (New York: Holt, Rinehart and Winston, 1963), 193 Wonnacott, Thomas H and Ronald J Wonnacott, Introductory Statistics, 2nd ed (New York: Wiley, 1972), 125 93754_30_EN_p661-667.indd 666 4 Askia, http://www.askia.com, accessed April 4, 2009 Sauerbeck, Laura R., Jane C Khoury, Daniel Woo, Brett M Kissela, Charles J Moomaw, and Joseph P Broderick, “Smoking Cessation after Stroke: Education and Its Effect on Behavior,” Journal of Neuroscience Nursing (December 2005), downloaded from http:// web1.infotrac.galegroup.com This section relies heavily on Interviewer’s Manual, rev ed (Ann Arbor, MI: Survey Research Center, Institute for Social Research, University of Michigan, 1976) Ibid., p 11 Ibid., pp 11–13 Reprinted by permission Oliver, Daniel G., Julianne M Serovich, and Tina L Mason, “Constraints and Opportunities with Interview Transcription: Towards Reflection in Qualitative Research,” Social Forces (December 2005), downloaded from http://web1 infotrac.galegroup.com, Viewpoint Learning, http://www viewpointlearning.com, accessed June 22, 2009 Ripley, Birch G “Confessions of an Industrial Marketing Research Executive Interviewer,” Marketing News (September 10, 1976), 20 Eng, Susanna and Gardner, Susan, “Conducting Surveys on a Shoestring Budget,” American Libraries, 36 (February 2005), 38-39 10 Chapter 19 http://www.tobii.com, Tobii, accessed April 17, 2009 Braunsberger, Karin, B R Buckler, and David J Ortinau, “Categorizing Cognitive Responses: An Empirical Investigation of the Cognitive Intent Congruency Between Independent Raters and Original Subject Raters,” Journal of the Academy of Marketing Science 33 (Fall 2005), 620–632 These imputation methods are beyond the scope of this text For more see Hair et al., Multivariate Data Analysis (Upper Saddle River, NJ: Prentice Hall, 2006), 39–73, 709–740 Pope, Jeffrey L., Practical Marketing Research (New York: AMACOM, 1981), 22 © 1998–1999 VNU Business Media Inc Used with permission Chapter 21 Chapter 20 Chapter 18 Chapter 17 Note that the derivation of this formula is (1) E ϭ ZSX; (2) E ϭ _ _ ZS/͙n ; (3)͙n ZS/E; (4) (n) ϭ (ZS/E) Based on Bialik, Carl, “A Survey Probes the Back Seats of Taxis, with Dubious Results,” Wall Street Journal (January 28, 2005), http://online.wsj com; “Taxis Hailed as Black Hole for Lost Cell Phones and PDAs, as Confidential Data Gets Taken for a Ride,” Pointsec Mobile Technologies news release (January 24, 2005), http://www.pointsec.com 11 12 13 Dolliver, Mark, “Plow Under Your Hops and Plant Some Vines,” Adweek 46 (July 25, 2005), 36–38 Fisher, Mark, “Beer Surges in Popularity—At the Expense of Wine,” Dayton Daily News (August 1, 2008), http://www.encyclopedia com/doc/1P2-16950875.html, accessed March 22, 2009 Kirsche, M L., “Targeting Boomers Could Boost Fizzling Out Beer Sales,” Drug Store News 27 (June 2005), 81 Longo, Don, “Drink Up,” Progressive Grocer 84 (October 15 2005), 52–58 “Oprah Again Tops American’s List of Favorite Personalities,” Wall Street Journal (February 3, 2006), http://online.wsj.com/article_print/ SB113889692780763347.html, accessed February 2, 2006 Rasmussen Reports, National Survey of 1,000 Adults (March 17–18 2009), http://www.rasmussenreports com/premium_content/econ_ crosstabs/march_2009/crosstabs_ aig_march_17_18_2009, accessed March 22, 2009 See Dubinsky, Alan J., Rajan Nataraajan, and Wen-Yeh Huang, “Consumers’ Moral Philosophies: Identifying the Idealist and the Relativist,” Journal of Business Research 58 (December 2005), 1690–1701; Deal, Ken, “Deeper into the Trees,” Marketing Research 17 (Summer 2005), 38–40 Adapted from Yavas, Ugur and Emin Babakus, “What Do Guests Look for in a Hotel? A Multi-Attribute Approach,” Services Marketing Quarterly 25, no (2003), 6–14 http://www.wineinstitute.org/ communications/statistics, accessed February 6, 2006 The data analysis tool must be added to the conventional Excel install by unpacking the data tool This can be done by clicking on tools and then clicking on add-ins and following the instructions See http://www microsoft.com for more instructions on how to accomplish this Iuso, Bill, “Concept Testing: An Appropriate Approach,” Journal of Marketing Research 12 (May 1975), 230 Diamon, Sidney, “Market Research Latest Target in Ad Claim,” Advertising Age (January 25, 1982), 52 Reprinted with permission by Crain Communications, Inc Adapted with permission from Prince, Melvin, Consumer Research for Management Decisions (New York: John Wiley and Sons, 1982), 163–166 Technically, the t-distribution should be used when the population variance is unknown and the standard deviation is estimated from sample data However, with large samples, the t-distribution approximates the Z-distribution, so the two will generally yield the same result See a comprehensive statistics text for a more detailed explanation A more complex discussion of the differences between parametric and nonparametric statistics appears in Appendix 22A Kranz, Rick, “Maybach, Rolls Models Are Far Below Predictions,” Automotive News 79 (October 18, 2004) In most cases, low p-values support hypotheses However, if the hypothesis is that the observations will be equal to the theoretical expectations for a given distribution (this would be the null case), then a high p-value would be desired to support the hypothesis Generally, this is not good form for a hypothesis Exceptions to this rule exist One of the most common is when a researcher compares some matrix of values with some alternative matrix of values with a goodness-of-fit test Particularly in advanced applications (beyond the scope of this book), the researcher may wish to test whether or not the two matrices are the same within sampling error In this case, the researcher would need an insignificant p-value (above α) to support the hypothesis Chapter 22 Vermeir, I and P Van Kenhove, “Gender Differences in Double Standards,” Journal of Business Ethics 81 (2008), 281–295 Vermeir and Van Kenhove (2008) Tests for complex experimental designs are covered in Appendix 22B The formula is not shown here but it can be found in most basic statistics books See, for example, Armstrong-Stassen, M., “Designated Redundant but Escaping Lay-Off: A Special Group of Lay-Off Survivors,” Journal of Occupational and Organizational Psychology 75 (March 2002), 1–13 This is the “statistical alternative” hypothesis Sukhdial, Ajay, Damon Aiken, and Lynn Kahle, “Are You Old School? A Scale for Measuring Sports Fans’ Old-School Orientation,” Journal of Advertising Research 42 (July/August 2002), 71–81 7/14/09 9:19:55 AM Endnotes 667 Chapter 23 Chapter 24 1 Greenhaus, J H and N J Beutell, “Sources of Conflict Between Work and Family Roles,” Academy of Management Review, 10, no (1985), 76 Boyar, S L., C P Maertz Jr., A W Pearson, and S Keough, “WorkFamily Conflict: A Model of Linkages Between Work and Family Domain Variables and Turnover Intentions,” Journal of Managerial Issues 15, no (2003), 175 Beutell, N J and U Wittig-Berman, “Predictors of Work-Family Conflict and Satisfaction with Family, Job, Career, and Life,” Psychological Reports 85 (1999), 893–903 For a discussion of the other measures of association, see the appendix to this chapter and J D Gibbons, Nonparametric Methods for Quantitative Analysis (New York: Holt, Rinehart and Winston, 1976) Bott, J P., D J Svyantek, S A Goodman, and D S Bernal, “Expanding the Performance Domain: Who Says Nice Guys Finish Last?” International Journal of Organizational Analysis, 11, no (2003), 137–152 Bagozzi, R P., “Salesforce Performance and Satisfaction as a Function of Individual Difference, Interpersonal and Situational Factors,” Journal of Marketing Research (November 1978), 517–531 Recall that the mean for a standardized variable is equal to For more on this topic, see Hair, J F., W C Black, B J Babin, R Tathum, and R Anderson, Multivariate Data Analysis, 6th ed (Upper Saddle River, NJ: Prentice Hall, 2006) 93754_30_EN_p661-667.indd 667 Goulding, Christina, “Romancing the Past: Heritage Visitors and the Nostalgic Consumer,” Psychology and Marketing 18 (June 2001), 565–592 Tesoriero, H W., “Babes in 80s Toyland,” Time 160 (November 11, 2002), 14 “Nostalgia, Education Hot Trends in Toys,” Mass Market Retailers 21 (February 23, 2004), 47, ThomsonGale Database Betts, Kate, “A 1950s State of Mind,” Time (April 15, 2004), Osborn, Suzanne Barry, “It’s Yesterday Once More: Companies Use Nostalgia to Entice Consumers,” Chain Store Age (June 2001), 32 Peterson, Karyn M., “Entertaining the Future: Licensing Execs on Last Year’s Lessons and the Challenge of What’s Next,” Playthings (February 1, 2009), http://www.playthings.com/ article/CA6635647.html, accessed April 20, 2009 See Holak, S L and W Havlena, “Feelings, Fun and Memories: An Examination of the Emotional Components of Nostalgia,” Journal of Business Research 42, no (1998), 217–226 Muehling, Darrel D and David E Sprott, “The Power of Reflection,” Journal of Advertising 33 (Fall 2004), 25–35 Holak, S L and W Havlena (1998) 10 When the actual regression model is illustrated as an explanation of the actual dependent variable in a population, Yi is used and an error term (ei) is included because the sample parameters cannot be expected to perfectly predict and explain the actual value of the dependent variable in the population 11 12 13 14 15 16 17 When we use a regression equation to represent its ability to predict sample values of the dependent variable from the estimated parameter coefficients, Yˆi is used to represent predicted values of Yi and no error term is included since the actual amount of error in any given observation is unknown School enrollment statistics can often be found using the Internet and either searching through government statistics or examining the Web site for the local school district or school board The constant term has disappeared since it is equal to when the regression coefficients are standardized For more on this topic, see Hair, J F., W C Black, B J Babin, and R Anderson, Multivariate Data Analysis (Upper Saddle River, NJ: Prentice Hall, 2010) Cox, A D., D Cox, and R D Anderson, “Reassessing the Pleasures of Store Shopping,” Journal of Business Research 58 (March 2005), 250–259 Closs, D J., M Swink, and A Nair, “The Role of Information Connectivity in Making Flexible Logistics Programs Successful,” International Journal of Physical Distribution & Logistics Management 35, no (2005), 258–277 Morrison, Mark, A Sweeney, and T Heffernan, “Learning Styles of On-Campus and Off-Campus Marketing Students: The Challenge for Marketing Educators,” Journal of Marketing Education 25 (December 2003), 208–217 Paul E Green, Ronald E Frank, and Patrick J Robinson, “Cluster Analysis in Test-Market Selection,” Management Science 13 (April 1967) Chapter 25 North, Tim, “Business Report Writing Tips,” http://www betterwritingskills.com, downloaded April 28, 2009 The original version of this chapter was written by John Bush, Oklahoma State University, and appeared in William G Zikmund, Business Research Methods (Hinsdale, IL: Dryden Press, 1984) “A Speech Tip,” Communication Briefings 14, no (1995), These guidelines, adapted with permission from Marjorie Brody (President, Brody Communications, 1200 Melrose Ave., Melrose Park, PA 19126), appeared in “How to Gesture when Speaking,” Communication Briefings 14, no 11 (1995), “Tips of the Month,” Communication Briefings 24, no (May 2005), Based on Bridis, Ted, “Study: Shoppers Naïve about Online Pricing,” Information Week ( June 1, 2005), downloaded from http://web2.infotrac.galegroup com; (APPC),”Annenberg Study Shows Americans Vulnerable to Exploitation in the Online and Offline Marketplace,” Annenberg Public Policy Center news release ( June 1, 2005), http://www annenbergpublicpolicycenter.org; Turow, Joseph, Lauren Feldman, and Kimberly Meltzer, “Open to Exploitation: American Shoppers Online and Offline,” APPC report, June 2005, downloaded from http:// www.annenbergpublicpolicycenter org 7/14/09 9:19:55 AM INDEX INDEX A Absolute causality, 59 Abstract level, 40 Accuracy coding data and, 474 in descriptive research, 57 of political polls, 430 of questionnaire, 337 of sampling, 388–389, 404–405 ACNielsen BASES system, 87 Claritas, 160, 166, 171, 178 PeopleMeter, 247–248 ScanTrack, 176–177 ACNielsen International, 14 Acquiescence bias, 192–193 Actionable variables, 120 Active data warehousing, 24 Active research, and right to privacy, 91–92 ADI (Area of Dominant Influence), 162 Administrative error, 194–195 Adrenaline, 251–252 Adult beverages, 485–486 Advance notification of mail surveys, 224 Advertising research, 177, 375–377 Advocacy research, 101 AFLAC Insurance, 2–3, 14 Agency for Health Care Research and Quality Hospital survey, 365–370 Aided-recall format, 347, 351 Airline industry, 10–11, 12, 312–313, 321 Alloy Eighth Annual College Explorer study, 318 Alpha (␣), 511 Alternative hypothesis, 510 Alternatives in research process, 62–63 Ambiguity in decision making, 53–54 in question wording, 345–346 of symptoms of business problem, 111 American Kennel Club, 397 American Marketing Association, Code of Ethics, 95, 100 Analysis of variance See ANOVA Anchoring effect, 350 Annenberg Public Policy Center, study by, 629–630 Anonymity of respondents, 212, 220, 230 ANOVA (analysis of variance) applied to regression, 571 description of, 541, 543 for factorial designs, 556–557 F-test and, 545–546 illustration of, 543–544 independent samples t-test and, 542 multivariate, 589, 590, 591 n-way, 589–590 partitioning variance in, 544–545 for randomized-block designs, 555–556 Appendix to research report, 617 Applied business research, 6, Arbitron Portable People Meter, 248–249 Area sample, 401 Arithmetic means of sample, 428 Askia software, 443 Assessment of problems or opportunities, Assumptions made in question wording, 347 Atlanta Braves case study, 637–638 ATLAS.ti software package, 138 Attitude, 315 Attitude measurement behavioral intention, 326–327 choosing scale for, 328–331 importance of, 315–316 rating scales, 317–326 techniques for, 316–317 Attribute, 303 Attribution theory, 38 Australia, brushfires in, 159 Authorization letters, 613 Availability of data, and need for research, 11–12 Average, figuring, 416 Average deviation, 419 B Back translation, 363 Backward linkage, 62 Balanced rating scale, 330 Ballistic theory, 45 Bar charts, 623–625 Basic business research, Basic experimental designs, 271, 278, 280–282 Behavioral differential, 327 Behavioral intention, measurement of, 326–327 Behavioral tracking, 25–26 Benchmarking, 201 Best-fit line, 568 Between-groups variance, 544–545 Between-subjects design, 273 Bias See also Response bias in decision making process, 83 of experimenter, 267 of observer, 243 order, 349 in quota sampling, 397 sample, 189 Bivariate statistical analysis, 509, 530, 532–534 “Blind” experimental administrator, 269 Blind monadic testing, 505 Blocking variables, 258 Blogs, 148, 170 Body language, 461 Body of research report, 615–617 Box and whisker plots, 501, 502 Briefing sessions, 445, 454 See also Debriefing sessions Bristol-Myers, 505 Brown-Forman distiller, 14–15 Budget for research Internet surveys and, 227 mail surveys and, 220 personal interviews and, 212 sampling method and, 405 scientific decision process and, 156 as source of conflict, 82 telephone interviews and, 215 Burt’s Bees, 318 Business-class airfare, 12 Business decisions, information required for, 3–5 See also Decision making process Business ethics, 88 Business-Facts, 160 Business.gov Web site, 616 Business intelligence, 19, 20 Business opportunity, 51 Business orientations, Business problem, 51 Business research definition of, 5–6 determination of need for, 11–13 flaws in, 16 functions of, 23 global, 14–15 managerial value of, 8–11 types of, 6, 7, 54 C Callbacks, 213, 217, 229 Calo Research Services, 448 Campbell’s Soup Company, 245–246 Carrefour, 65 Case studies, 140, 632–638 See also specific case studies Categorical variables, 119, 261 Category scales, 318, 319, 330 Causal inference, 57 Causal research, 16, 57–61, 71, 257 Causation, correlation, and covariance, 561–562 Celebrity endorsements, 491 Cell, 263 Cengage Learning, 31 Census, 387 Central-limit theorem, 425–429 Central location interviews, 217 Certainty, 52 See also Uncertainty CHAID (chi-square automatic interaction detection) software, 492 Change in business situations, 111 Change interviews, 115 Charts, display of data in, 498–499, 619–625 Cheating by interviewers, 194–195, 456 Check boxes, 358, 359 Checklist questions, 341 Children, as subjects, 92–93 China, consumer demand in, 166 Chi-square distribution, 642 Chi-square tests, 522–524, 530, 532–534, 559 Circular-flow process, 61, 62 Claritas (ACNielsen), 160, 166, 171, 178 Classificatory variables, 119 Click-through rate, 249–250 Client sponsors/users, rights and obligations of, 100–101 Climate change, attitudes toward, 350 Closed-ended questions See Fixed-alternative questions Cluster analysis, 597–599 Cluster sampling, 401, 402 Coca-Cola, 110 Code book, 477, 478 Code construction, 472 Codes, definition of, 468 Codes of ethics, 94–95 Coding data code construction, 472 data file, 471–472 description of, 70, 468 devising scheme for, 475–477 editing and, 477 error checking and, 478–479 fixed-alternative responses, 472–474 open-ended responses, 474–477 qualitative responses, 468–471 Coding process, facilitating when editing, 467–468 Coefficient alpha (␣), 306 Coefficient of determination (R2 ), 562 Coffee industry, 4, 73 Cohort effect, 276 Collages, 153 Commercial sources of data, 176–178 Communality values, 596 Communication process, 609–610 668 93754_31_Ind_668-674.indd 668 7/14/09 9:20:25 AM Index Communication technologies, 13–14 Comparative rating scales, 329 Completely randomized design, 283–284 Completeness of data, 21, 466–467 Complex experimental designs, 282–286 Composite measure, 303 Composite scales, 320, 596 Compromise design, 282 CompuStat, 29 Computer-assisted telephone interviews, 218, 474 Computerized survey data processing, 477–478 Computerized voice-activated telephone interviews, 218–219 Computer mapping, 500–501 Concept/construct, 40, 295 Conclusions and recommendations section of report, 617 Concomitant variation, 58 Conditional causality, 59 Confidence interval, 430, 434 Confidence interval estimates, 429–432, 520–521 Confidence level, 434, 511 Confidentiality, 91, 98–100 Confirmatory orientation, 53 Confirmatory research, exploratory research compared to, 136–137 Conflict between management and research, 81–85, 86 Conflict of interest, 100 Confound, 265–266 Confused “don’t know” answers, 467 Consistency, internal, 305–306, 310 Constancy of conditions, 270 Constants, 119 Constant-sum scale, 323 Construct definition of, 40, 296 hypothetical, 315, 317 Construct validity, 308 Consumer Assessment of Health Providers and Systems Hospital Survey, pretesting, 361 Consumer panels, 198, 250 Consumer Point, 160 Consumption patterns, 165, 177, 580 Content analysis, 246–247 Content providers, 32 Content validity, 307–308 Contingency tables, 488–489, 491 Continuous measures, 302–303 Continuous quality improvement stage of total quality management, 201 Continuous variables, 119 Contractors See Suppliers and contractors Contracts, research proposals as, 125–127 Contributory causality, 59 Contrived observation, 244, 245 Control groups, 261 Control of variables, establishing, 269–270 Convenience sampling, 396, 408 Convergent validity, 308–309 Conversational approach to qualitative research, 151–152 Cookies, 34 Cooperation Internet surveys and, 227 telephone surveys and, 216 COPPA (Children’s Online Privacy Protection Act), 92 Corporate Reputation Survey, 339 Corporate social responsibility, 318 Correlation covariance, causation, and, 561–562 partial, 586 Pearson product-moment, 564, 645 93754_31_Ind_668-674.indd 669 669 Correlation coefficient, 559, 561, 563 Correlation matrix, 562–564, 565 Correspondence rules, 295–296 Cost-benefit analysis, and need for research, 12–13 Costs See Budget for research Counterbalancing, 270 Counterbiasing statement, 345 Covariance, 559, 561–562 Cover letters for mail surveys, 222, 223 Criterion validity, 308 Critical values description of, 513–514 of F for ␣ ϭ 01, 644 of F for ␣ ϭ 05, 643 of Pearson correlation coefficient, 645 of T in Wilcoxon matched-pairs signed-rank test, 646 Criticism, research that implies, 82 Cross-checks of data, 163 Cross-functional teams, 85 Cross-sectional studies, 196–197 Cross-tabulations chi-square test, 530, 532–534 contingency tables, 488–489, 491 description of, 488–489 elaboration, refinement, and, 491–492 number of, 492 percentage, 490–491 quadrant analysis, 493 Cross-validation of research results, 15 Curb-stoning, 456 Current Population Survey, 55, 390 Customer discovery, 170 Customer relationship management (CRM), 23–24, 170–171 Custom research, 88 Cyclical business situations, 110–111 D Data characteristics of valuable, 19, 21 cross-checks of, 163 definition of, 19, 20 gathering, 69 input management, 25–28 Internet and, 31–32 processing and analyzing, 70 secondary, 161–163 sources of, 171–178 Data analysis computer programs for, 499–501 definition of, 70 interpretation of, 501–503 stages of, 462–463 Data archives, computerized, 28–30 Database marketing, 170–171 Databases, 24, 28–30 Data collection See Fieldwork Data conversion, 162 Data entry, 477 Data files, 470, 471–472 Data gathering stage of research, 69 Data integrity, 463, 465 Data mining, 169–170 Data processing, computerized, 477–478 Data-processing error, 194 Data quality, 21 Data reduction technique, 595–596 Data specialist company, 28 Data transformation description of, 493 index numbers, 496 problems with, 494–495 rank order, calculation of, 496–498 simple, 493–494 Data warehouses, 24–25, 472 Data warehousing, 24 Data wholesalers, 28 DDB SignBank, 241 Debriefing sessions, 93, 270–271 See also Briefing sessions Deception in research design, 93 Decision making, definition of, 52 Decision making process ambiguity in, 53–54 biases in, 83 certainty in, 52, 53 information for, 19 opportunities and problems in, 51–52, 53–54 research contribution to, 51 stages of, 9–11 uncertainty in, 52–53 Decision situation hypotheses, variables, and, 121 managerial, defining, 64 Decision statements description of, 108 influence of, on objectives and research design, 123 linking with objectives and hypotheses, 66 translating into research objectives, 116–118 Decision support systems (DSS), 23–24, 26, 79 Deductive reasoning, 44 Degrees of freedom (df ), 519 Deland Trucking Company, 107–108 Deliverables, 63 Demand characteristics, 267–269 Demand effect, 267 Demographic data Internet sampling and, 408 question wording and measurement scales for, 382–384 sources of, 177 Dependence techniques of multivariate data analysis ANOVA and MANOVA, 589–590 discriminant analysis, 590, 592 multiple regression, 584–586, 588–589 overview of, 583, 584, 592 Dependent variables, 120, 257, 263–264 Depository institutions, survey of, 412 Depth interviews, 150–151 Descriptive analysis, 486–487 Descriptive research deception in, 93 description of, 16, 55–57, 60, 71 results of, 61 Descriptive statistics, 413 Design of research See also Experimental design; Secondarydata research designs deception in, 93 definition of, 66 influence of decision statements on, 123 planning, 66–68 for surveys, 231–232 Destruction of test units, 389 Determinant-choice questions, 340 Deviation, 419 Diagnosis of problems or opportunities, Diagnostic analysis, 57 DIALOG, 28, 29 Dialog boxes, 230 Direct observation, 242–244 Director of research, 80–81 Discovery orientation, 53 Discrete measures, 301 Discriminant analysis, 590, 592 Discriminant validity, 308–309 Discussion guides for focus groups, 146–147 Disguised experiments, 268–269 Disguised questions, 196 Display of data, tabular and graphic, 498–499, 617–625 Disproportional stratified sampling, 400–401 Dissemination of faulty conclusions, 100 Distortion of data in charts, 620–621 Dog Ownership Survey, 397 Domain, 31 Do-not-call legislation, 91, 214, 236 “Don’t know” answers, editing and tabulating, 467–468 Door-in-the-face compliance technique, 447 Door-to-door interviews, 212–213, 232 Double-barreled questions, 346–347 Dow Jones News Retrieval, 28, 29 Downy-Q Quilt commercial, 506–507 Drinking-related behaviors, 262 Drop-down boxes, 358, 359 Drop-off method, 225 Dummy coding, 469–470 Dummy tables, 127–128 Dummy variables, 585 DuPont, 4–5, 14 E Editing data coding and, 467–468, 477 for completeness, 466–467 in field, 464 in-house, 464–466 overview of, 70, 463–464 pitfalls of, 468 during pretest stage, 468 questions answered out of order, 467 Edward Jones investment firms, 159 E-Lab, LLC, 255 Elaboration analysis, 492 Electronic data interchange (EDI), 30 Electronic interactive media, 208 Electronic toll collection case study, 131 E-mail surveys, 226 Emotion, and scientific decision process, 156 Empire Health Services, 201 Empirical level, 40–41 Empirical testing, 42, 43, 48 Entrapment, 245 Environmental scanning, 33, 165–166 Eos airline, 12 Equifax City Directory, 392–393 Error See also specific types of error designing experiment to minimize, 260–266 with direct observation, 243–244 in prediction, and regression analysis, 569 reporting, 98 in sample selection, training interviewers to avoid, 454 sources of, when studies are rushed, 82 Error checking in coding process, 478–479 Error trapping, 360 Estimation of parameters, 429–432 Ethical dilemma, 88 7/14/09 9:20:25 AM 670 Ethical issues in choosing focus group respondents, 145 client sponsors and, 100–101 in experimentation, 270–271 general rights and obligations, 90 in observation of humans, 245 as philosophical issues, 88–90 professionalism and, 102 researcher and, 94–100 research participants and, 90–94 in surveys, 233 Ethical perceptions, statistical tests on, 529–530 Ethnography, 138–139 Evaluation of course of action, 10–11 of questionnaires, 363 of secondary data, 163 Evaluation research, 10 Executive summary of research project, 614–615 Experiment See also Experimental design creating, 257 deception in, 93 definition of, 59–60 designing to minimize error, 260–266 ethical issues with, 270–271 self-efficacy intervention and job attitude, 257–260 Experimental condition, 258, 269 Experimental design basic, 271, 278, 280–282 complex, 282–286 diagramming, 278 factorial, 271, 284–286, 556–557 field experiments, 272–273 laboratory experiments, 271–272 quasi-experimental designs, 278–280 time series, 282 within-subjects and between-subjects, 273–274 Experimental groups, 261 Experimental treatment, 261–262 Experimental variables, 59 Experimenter bias, 267 Exploratory research confirmatory research compared to, 136–137 description of, 16, 54–55, 60, 71 misuses of, 154–156 objectives and, 64–65 results of, 61 External data, 172 External distributors, 27 External validity, 277–278 Extraneous variables controlling, 269–270 description of, 265, 266 internal validity and, 275–277 Extremity bias, 193 Eye-tracking monitor, 251 E-ZPass case study, 131 F Face validity, 307 Facial coding, 461 Fact-finding, 164–165 Factor analysis, 593–597 Factorial experimental designs, 271, 284–286, 556–557 Factor loading, 594 Factor rotation, 594–595 Fairfax County Public Library, 199 Fax surveys, 225–226 93754_31_Ind_668-674.indd 670 Index Federal Reserve survey, 412 Federal Trade Commission (FTC), 95–96, 214 FedWorld Web site, 175 Feedback, and personal interviews, 209–210 Field editing, 464 Field experiments, 272–273 Field in data file, 470 Field interviewing service, 444 Field notes, 152 Fieldwork Askia software and, 443 description of, 443–445 management of, 453–454 Fieldworkers, 444, 455–457 Filter questions, 350, 466 Financial databases, 29 FIX (Financial Information eXchange), 256 Fixed-alternative questions description of, 339, 363 precoding responses to, 472–474 recording responses to, 450 types of, 340–341 using, 339–340 FleetBoston bank, 113 Flowchart plan for questionnaire, 351 Focus blog, 148 Focus group interviews advantages of, 141–144 as diagnostic tools, 148 disadvantages of, 149–150 discussion guides for, 146–147 environment for sessions, 145 flexibility of, 143 nonverbal communications and, 242 online, 148–149 piggybacking and multiple perspectives, 143 scrutiny and, 143–144 speed and ease of, 142–143 uses of, 144 videoconferencing and, 148 Focus groups, 65, 144–146 FocusVision system, 148 Follow-up to mail surveys, 223 to research, 627 Follow-up questions, 448 Food and Drug Administration (FDA), Foot-in-the-door compliance technique, 447 Forced answering software, 360 Forced-choice rating scales, 330–331 Ford Motor Company, 33, 84, 110 Forecast analyst, 79 Forecasting sales, 167–168 Format of research reports, 611–617 Forward linkage, 61–62 Free-association techniques, 152–154 Frequency-determination questions, 340 Frequency distribution description of, 413–415 of sample means, 428 Frequency tables, 488 F-statistic, manual calculation of, 552–554 F-test, 545–546, 571–572, 590 Full enumeration method of sampling, 402 Funded business research, 127 Funnel technique, 349 Furnace employees, attitudes of, 314–315 G Gale Research Database, 31 Gallup Corporation, sampling by, 386 Garbage observation projects, 245–246 General linear model, 584 Geographical databases, 28 Geographic areas, estimating market potential for, 166–167 Geographic hierarchy in urbanized areas, 404 Geographic Information System (GIS), 87 Gestures during oral presentations, 626 Global business research description of, 14–15 mail surveys and, 225 personal interviews and, 214 questionnaires for, 362–363 sampling frames for, 393 sources of data for, 178–179 telephone interviews and, 219 Global information systems, 23 Global positioning satellite (GPS) systems, 25–26, 27, 105, 248 Goodness-of-fit, 522–524, 530, 532–534 Goods and services, question wording and measurement scales for, 378–382 Google, 32, 33, 171–172, 339 Government sources of data, 175 Grand mean, 544 Grants, peer review process for, 96 Graphical representations of data charts, 498–499, 619–625 descriptive analysis and, 500–501 in reports, 617–618 tables, 498–499, 618–619 Graphical user interface (GUI) software, 356 Graphic rating scales, 323–325, 360 Grounded theory, 139–140 Grouping variables, 536 H Hand washing, 244 Happy-face scale, 325 Harley-Davidson, 11, 153 Harm, protection of participants from, 94, 96 Harris Interactive Inc., 407–408 Harvard Cooperative Society case study, 37 Hawthorne effect, 268 Health club industry, 97 Healthy house, attitudes toward, 325 Heavy equipment case study, 122 Hermeneutics, 138 Hermeneutic unit, 138 Hidden observation, 240, 245 Hidden skip logic, 360 Hidden Valley Ranch, 273 Histograms, 487–488 History effect, 275–276 Home Depot, 19, 27 Horizon Research Services, 446 Host, 31 Human subjects review committee, 94, 96 Hypothesis See also Hypothesis testing clarity in, 121–123 decision situations, variables and, 121 decision statements, objectives, and, 66 definition of, 42 null, 510 testing, 7–8 variables and, 296 Hypothesis testing applications of, 526 chi-square test for goodnessof-fit, 522–524 as critical skill, 526 description of, 509 example of, 513–515 parametric compared to nonparametric, 517–518 procedure for, 509–510 of proportion, 525 significance levels and p-values, 510 simple regression and, 574 Type I and Type II errors, 515–516 univariate, using t-distribution, 521–522 Hypothetical constructs, 315, 317 I IBM, 19 Idealism, ethical, 89–90 Identification of problems or opportunities, Image profiles, 321 Implementation of course of action, 9–10 Importance-performance analysis, 493 Imputing missing value, 466 Incentives for fieldworkers, 457 to respond, 216, 222 Inconsistency, checking data for, 464–466 Independent samples t-test, 534–538, 542 Independent variables, 120, 257, 260–263, 491 Index measure, 303, 331 Index numbers, 496 Index of retail saturation, 168–169 Inductive reasoning, 44–45 Inferential statistics, 413 Information for business decisions, 3–5, 19 completeness of, 21, 466–467 definition of, 19, 20 valuable, characteristics of, 19, 21 Information technology, 33–34 Informed consent, 90–91, 94 In-house editing, 464–466 In-house interviewers, 444 In-house research, 76–77 Initial quality improvement stage of total quality management, 201 Input management, 25–28 In-Stat, 185–186 Instrumentation effect, 276 Integrity of data, 463, 465 Interaction effect, 260 Interactive help desk, 360 Interactive media, 32–33, 208 Interactive questionnaires, software to make, 360–361 Interdependence techniques of multivariate statistical analysis cluster analysis, 597–599 factor analysis, 593–597 multidimensional scaling, 599–600 overview of, 583, 584, 601 Internal and proprietary data, 171–172 Internal consistency, 305–306, 310 Internal records, 25 Internal Revenue Service, research proposal for, 124 Internal validity, 274–277, 278 Internet data access and, 31 data collection and, 31–32 description of, 30–31 navigating, 32 privacy issues with, 92, 102 research reports on, 626 as source of data, 172, 174 7/14/09 9:20:25 AM Index Internet 2, 34 Internet surveys advantages and disadvantages of, 227–230, 232 initial contact, 447 layout of, 356–360 sampling and, 406–409 Interpretation of data analysis, 501–503 Interquartile range, 501 Interrogative techniques, 114 Intersubjective certifiability, 135 Interval scale, 300 Interviewer bias, 193 Interviewer error, 194 Interviewer influence, 211–212 Interviewers briefing sessions for, 454 cheating by, 194–195, 456 instructions for, 352 training for, 445 Interviewing basic principles of, 452 required practices for, 452–453 total quality management for, 455 Interview process, 113–114 Interviews See also Fieldwork; Focus group interviews; Interviewers; Interviewing; Personal interviews; Telephone interviews change, 115 combining direct observation with, 244 depth, 150–151 door-to-door, 212–214 as interactive communication, 208 semi-structured, 151–152 shopping mall intercepts, 212–214, 232 terminating, 451 verification of, by reinterviewing, 457 Intranet, 34 Introduction section of research report, 615 Intuit, 188 Intuitive decision making, 83 Inverse relationship, 561 Investing behavior, and peer pressure, 294 iPhone, 34 Isolation of subjects, 269 Item nonresponse, 211, 466 J Jack Daniels, 14, 15 J D Power and Associates, 87, 335 Jelly Belly brand, 3–4, Job attitude, and self-efficacy intervention, 257–260 Jobs in business research director of research, 80–81 large firms, 79–80 mid-sized firms, 78–79 research generalist, 85 salaries for, 81 small firms, 78 Johnson & Johnson, 339 Judgment, determining sample size on basis of, 438 Judgment sampling, 396 K Kaplan, Inc., 205 Keying mail surveys, 225 Keyword search, 32 Kia Motors, 165 Kiosk interactive surveys, 230–231 Kish method of sampling, 402 Knowledge, definition of, 22 93754_31_Ind_668-674.indd 671 671 Knowledge management, 22 Krispy Kreme, 18–19 L Laboratory experiments, 271–272 Laddering, 150 Ladder of abstraction, 40, 41 Ladder scales, 324 Latent construct, 41–43 Layout for questionnaires Internet, 356–360 traditional, 352–356 Leading questions, 344–345 Legitimate “don’t know” answers, 467 Length of mail surveys, 221 of personal interviews, 210 of questionnaires, 233 of telephone interviews, 217 Letters of authorization, 613 cover, for mail surveys, 222, 223 of transmittal, 613, 614 Level of precision, determination of after data collection, 439 Level of scale measurement, and selection of statistical techniques, 517 Libraries, as sources of data, 172 Likert scales, 303, 318–319, 341 Limited research service companies, 88 Line graphs, 622–623 List brokers, 392 List-wise deletion, 467 Literature review, 65 Loaded questions, 344–345 Longitudinal studies, 197–198, 200 Love, as hypothetical construct, 317 M Macy’s, 110 Magnitude of error, 434 Mail surveys, 219–221, 232 Main effect, 259 Mall intercept interviews, 213–214, 232 Management conflict between research and, 81–85, 86 research as facilitating, 8–9 Managerial action standard, 123 Manager of decision support systems, 79 Manipulation definition of, 59 of independent variables, 260–263 Manipulation check, 275 Manual calculation of F-statistic, 552–554 Marginals, 489 Marginal tabulation, 488 Market-basket analysis, 169 Marketing Information Systems, Inc., 505 Marketing-oriented firms, Market segments, and descriptive research, 56 Market-share data, 176–177 Market tracking, 165 Mark-sensed questionnaires, 477 Marriott Corporation, 78, 79–80 Mars M&M characters, 55 Matching subjects, 265 Maturation effect, 276 Maxjet, 12 Mazda Motor Europe, 255 MBA degree, market for, 50–51 McDonald’s, 60, 373 Mean description of, 415–417 sample size for questions involving, 433–435 Mean absolute deviation, 419 Mean squared deviation, 420 Measurement See also Attitude measurement; Scale measurement concepts and, 295 criteria for evaluating, 305 operational definitions and, 295–296 overview of, 293–295 reliability of, 305–307, 309 sensitivity of, 309 validity of, 307–309 Measure of association, 559–560 Measures of central tendency mean, 415–417 median, 416, 418 mode, 416, 418 strengths and weaknesses of, 439 Measures of dispersion range, 418–419 standard deviation, 419–421 Mechanical observation, 247–249 Median, 416, 418 Median split, 494–495 Media phones, 185–186 Media sources of data, 175–176 Memory, questions that may tax, 347–348 Mere-measurement effect, 195, 196 Methodology, selection of, 67 Microsoft, 339 MINITAB, 499 Misrepresentation of research, 93, 98, 99, 620–621 Missing data, handling, 479 Mixed-mode surveys, 231 Mobile phone interviews, 214–215 Mobile surveys, 207 Mode, 416, 418 Model building, 166–169 Moderators of focus groups, 145–146 Moderator variables, 492 Monadic rating scales, 329 Money See Budget for research Moral standards, 88 Mortality effect, 277 Mr Peanut, 55 Multicollinearity, 588 Multidimensional scaling, 599–600 Multiple-grid questions, 352 Multiple regression analysis example of, 585 interpreting results of, 588–589 overview of, 584–585 purposes of, 600 R2 in, 586 regression coefficients in, 585–586 statistical significance in, 586, 588 Multistage area sampling, 402–404 Multivariate analysis of variance (MANOVA), 589, 590, 591 Multivariate statistical analysis classifying techniques of, 582–584 definition of, 509, 581 Music for mobile phones, 165 social networking sites and, 228 Mutually exclusive response alternative, 341 Mystery shoppers/diners, 238, 244 N National Assessment of Adult Literacy, 210 National Do Not Call Registry, 214, 215, 236 Negative relationship, 561 NeoTech Mobile-Trak, 248 Netflix, 136 Net promoter surveys, 188 Networking, 30 Neural networks, 169 Neuroco, 251 Neutral questions, asking, 449 No contacts, 190 Nominal scales, 297–298 Noninteractive media, 208 Nonparametric statistics, 517–518 Nonprobability sampling comparison of techniques of, 404 convenience, 396, 408 description of, 395 judgment (purposive), 396 quota, 396–397 snowball, 398 Nonrespondent error, 462 Nonrespondents, 190 Nonresponse error mail surveys and, 222 overview of, 189–191 sampling and, 394–395 Nonsampling error, 264, 393–395 Nonspurious association, 58–59 Nonverbal communications, 241–242 “No opinion” option, 467–468 Normal curve, area under, 640 Normal distribution, 421–424 Norman Estates wine, 56 Nostalgia, trend toward, 580–581 Nuisance variables, 264 Null hypothesis, 510 Numerical scales, 322 Nutrition labels, N-way ANOVA, 589–590 O Objectives decision statements and, 116–118, 123 defining, 63–66, 113–114 survey questions and, 363 writing, 120–121 Objectivity, by researchers, 98 Observable phenomena, 239 Observation, definition of, 239 Observation of human behavior complementary evidence and, 242 direct observation, 242–244 ethical issues in, 245 overview of, 241–242 Observation techniques content analysis, 246–247 direct, 242–244 in ethnography, 138–139 example of, 67–68 limitations of, 240 mechanical, 247–252 mystery shoppers/diners, 238, 244 nature of, 240 for physical phenomena, 245–246 in qualitative research, 152–153 Observer bias, 243 OLS See Ordinary least-squares method of regression analysis Olson Zaltman Associates, 449 One-group pretest-posttest design, 279 One-shot design, 279 One-tailed test, 521 One-way ANOVA, 541 Online focus groups, 148–149 Open-ended boxes, 358, 359 Open-ended response questions coding responses to, 474–477 description of, 338–339, 363 recording responses to, 450 Operational definition description of, 295–296 example of, 297 of target population, 390 7/14/09 9:20:25 AM 672 Operationalizing variables, 42–43 Optical scanning systems, 477 Opt-in lists, 409 Oral presentation of research results, 625–626 Order bias, 349 Ordinal scales, 299–300 Ordinary least-squares method of regression analysis equations, arithmetic behind, 578–579 hypothesis testing and, 574 interpreting regression output, 572–573 overview of, 569–570 plotting regression line, 573–574 statistical significance of model, 570–572 Organizational structure of business research, 77–80 Outlier, 501 Outside agencies, research by, 76, 77 Outside vendors, 27 Ownership, question wording and measurement scales for, 377–378 P Paging layout, 357 Paired comparisons, 327–328 Paired samples t-test, 538–540 Pair-wise deletion, 467 Panel samples, 406, 407–408 Pantry audits, 246 Parameter estimates, 429–432, 566–567 Parametric statistics, 517–518 Parlin, Charles Coolidge, 245–246 Partial correlation, 586 Participant-observation, 138 Participants, rights and obligations of, 90–94, 96 See also Respondents; Subjects Participation gaining for interview, 447 Internet surveys and, 227 personal interviews and, 211 in surveys, Partitioning variance in ANOVA, 544–545 Passive research, and right to privacy, 92 Path estimate, 566 Pearson product-moment correlation, 564, 645 Peer pressure, and investing behavior, 294 Peer review process, 96 Percentage cross-tabulations, 490–491 Percentage distribution, 413–414 Perceptual map, 600 Performance-monitoring research, 10 Personal interviews advantages of, 209–211, 232 description of, 209 disadvantages of, 211–212, 232 initial contact, 445 layout of pages from, 355–356 questions for, 341–342 Personnel See Jobs in business research Petabyte, 472 Phenomenology, 137–138 Philip Morris, 144 Photographs, sampling of, 388, 389 Physical phenomena, observation of, 245–246 Physiological reactions, measurement of, 251–252 Pie charts, 498, 621–622 Piggyback, 143 Pilot studies, 65 93754_31_Ind_668-674.indd 672 Index Pivot questions, 350 Placebo, 93, 269 Placebo effect, 269 Planning tools, research proposals as, 125 Plug value, 466 Point estimates, 429 Pointsec Mobile Technologies, 442 Political polls, accuracy of, 430 Pooled estimate of the standard error, 535 Population, 387 See also Target population Population distribution, 424–425, 426 Population element, 387 Population mean, calculation of, 428 Population parameters, 413 Population size, and sample size, 435, 439 Pop-up boxes, 358 Posttest-only control group design, 281–282 PowerPoint, 10/20/30 rule of, 626 Precoding fixed-alternative responses, 472–474 Preliminary tabulation, 362 Pretest of CAHPS Hospital Survey, 361 description of, 65 editing questionnaires and, 468 of questionnaires, 361–362 surveys and, 233 Pretesting effect, 276 Pretest-posttest control group design, 280–281 Previous research, investigation of, 65 Price promotions at bars, and intoxication, 262 Pricing decisions, 110–111 Primary sampling units, 393 Principles of good interviewing, 452–453 Privacy on Internet, 102 participant right to, 91–92, 101 PRIZM, 160, 171, 178 Probability, definition of, 415 Probability distribution, 415 Probability sampling cluster, 401, 402 comparison of techniques of, 405 description of, 395 multistage area, 402–404 proportional compared to disproportional, 400–401 sample size and, 438–439 simple random, 398–399 stratified, 400 systematic, 399 Probing definition of, 114 personal interviews and, 210 when no response given, 448–449, 450 Problem, definition of, 112 Problem definition business decision and, 112–116 description of, 108 gaps in performance and, 112 importance of, 108 quality of, 109–111 steps in process of, 112, 113 symptoms and, 116, 117 time spent on, 123 unit of analysis and, 119 variables and, 119–120 writing decision statements and objectives, 116–118 writing objectives and questions, 120–121 Procter & Gamble, 135 Producers of data, 173–178 Production-oriented firms, Product-oriented firms, Product usage, question wording and measurement scales for, 377–378 Projective techniques, 153 Propensity-weighting method, 408 Proportion definition of, 415 hypothesis test of, 525 sample size for, 435–438 Z-test for comparing, 540–541 Proportional stratified sampling, 400–401 Proposal See Research proposal Proposition, 42 Proprietary business research, 25 Protection of participants from harm, 94, 96 Pseudo-research, 96–97 Psychogalvanometer, 252 Psychology of consumption, 580 Public opinion research, 177 Pull technology, 33 Pupilometer, 252 Pure research, Purposive sampling, 396 Push buttons, 357 Push polls, 97 Push technology, 33, 34, 92 P-values, 510, 512 Q Quadrant analysis, 493 Qualitative analysis, 133 Qualitative data, 136 Qualitative research case studies, 140 conversations, 151–152 definition of, 133 depth interviews, 150–151 ethnography, 138–139 focus group interviews, 141–150 free-association/sentence completion method, 152–154 grounded theory, 139–140 misuses of, 154–156 orientations to, 137 phenomenology, 137–138 quantitative research compared to, 135–136, 156 techniques of, 141, 142 uses of, 133–134 Qualitative responses, coding, 468–471 Quality of data, 21 definition of, 199 Quality dimensions for goods and services, 202 Quantified electroencephalography (QEEG), 251 Quantitative data, 136 Quantitative research, 134–136, 156 Quasi-experimental designs, 278–280 Questionnaires See also Questions; Surveys about car features, 335 about climate change, 350 Agency for Health Care Research and Quality case study, 365–370 completeness of, and personal interviews, 211 constructing, 343–349 development stage for, 336 evaluation of, 363 flowchart plan for, 351 for global markets, 362–363 layout for, 352–361 mark-sensed, 477 McDonald’s Spanish language, 373 pretesting and revising, 361–362 quality and design considerations, 336–337 response rates to, 221–225 sample, 484 sample of completed page from, 451 self-administered electronic, 225–231 self-administered mail, 219–225 sequence of questions in, 349–351 software to make interactive, 360–361 travel case study, 371–372 types of, 195–196 wording and measurement scales for, 375–384 Questions ambiguity in wording of, 345–346 assumptions made in, 347 burdensome, and memory, 347–348 complexity of, 363 double-barreled, 346–347 filter, 350, 466 to generate variance, 348–349 language for, 343 leading and loaded, 344–345 multiple-grid, 352 neutral, asking, 449 objectives of research and, 363 open-ended compared to fixedalternative, 338–341, 363 pivot, 350 for probing, 450 repeating, 448–449 rules for asking, 447–448 sample codes for, 482–483 selection of statistical techniques and, 516 for self-administered, telephone, and personal interview surveys, 341–342 sensitive or potentially embarrassing, 363 skip, 354, 356, 466 Quota sampling, 396–398 R Radio buttons, 358, 359 Radio frequency identification (RFID) tags, 22, 23 Raising Cane’s case study, 131 Random, definition of, 398 Random digit dialing, 217 Random digits, table of, 639 Random error, and sample size, 432–433 Randomization, 264–265, 280 Randomized-block design, 284, 555–556 Randomness, definition of, 398 Random sampling nonsampling errors and, 393–395 simple, 398–399 of Web site visitors, 407 Random sampling error, 188, 203, 394, 438 Range, 418–419 Ranking preferences, 327–328, 331 Ranking task in attitude measurement, 316 Rank order, calculation of, 496–498 Rating scales advantages and disadvantages of, 326 balanced or unbalanced, 330 category, 318, 319, 330 category labels, 329–330 composite, 320, 596 constant-sum, 323 forced-choice, 330–331 7/14/09 9:20:25 AM Index graphic, 323–325, 360 Likert, 303, 318–319, 341 monadic compared to comparative, 329 numerical, 322 ranking scales compared to, 331 semantic differential, 320–321, 328, 341 simple attitude, 317 single measure compared to index measure, 331 Stapel, 322–323, 341 summated, 318–319 Thurstone, 325 Rating task in attitude measurement, 316 Ratio scales, 300–301 Raw data, 462 Raw regression estimates, 567 Real-time data capture, 229 Recording responses, 449–450 Records in data files, 470 Recruited ad hoc samples, 408 Refusals, 190 Regression analysis See also Multiple regression analysis equation for, 564, 566 errors in prediction, 569 ordinary least-squares method of, 569–574 overview of, 564 parameter estimate choices, 566–567 visual estimation of simple model, 567–568 Regression coefficients in multiple regression analysis, 585–586 Reinterviewing, verification by, 457 Relativism, ethical, 89–90 Relevance of data, 21, 35 of questionnaire, 336–337 Relevant, definition of, 120 Reliability of measurement, 305–307, 309 of sampling, 388–389 Reluctant “don’t know” answers, 467 Repeated measures, 263 Replication, 154 Reports format of, 611–617 graphic aids for, 617–625 on Internet, 626 oral presentation of, 625–626 tips for writing, 608 Representative samples Internet surveys and, 228 telephone interviews and, 217 Research, definition of, 5–6 Research analysts, 78 Research assistants/associates, 78–79 Research design See also Experimental design deception in, 93 definition of, 66 influence of decision statements on, 123 planning, 66–68 secondary-data, 161–163, 171–179 for surveys, 231–232 Researcher-dependent research, 133 Researchers as communicators, 609–610 rights and obligations of, 94–100 Research firms, largest, 79 Research follow-up, 627 Research generalist, 85 Research methodology section of report, 616 Research objectives, 63 See also Objectives 93754_31_Ind_668-674.indd 673 673 Research process alternatives in, 62–63 challenges in, 75–76 defining objectives, 63–66 drawing conclusions and preparing report, 70 gathering data, 69 overview of, 61–62 planning design, 66–68 processing and analyzing data, 70 sampling, 68–69 Research program strategy, 70–71 Research project, 70–71 Research proposal as anticipating research outcomes, 127–128 basic points addressed by, 126 as contract, 125–127 description of, 124 as planning tool, 125 Research questions, 121–123 Research reports See Reports Research suppliers, 86 Resources See Budget for research Respondent error definition of, 189 nonresponse error, 189–191 response bias, 191–194 Respondents See also Participants, rights and obligations of; Subjects anonymity of, 212, 220, 230 choosing for focus groups, 145 definition of, 186 Response bias, 191–194 Response latency, 243 Response rates description of, 221–222 Internet surveys and, 230 for mail surveys, increasing, 222–225 Responses, recording, 449–450 Results, presentation of, 98, 99 Results section of report, 616 Retail Forward, 87 Return on investment for research, 615 ReTweetability Index, 497 Reverse coding, 304 Reverse directory, 393 Reverse recoding, 319–320 Revising questionnaires, 361–362 Ringtones, 165 R J Reynolds, 110 Robot technology, 55 Roeder-Johnson Corporation, 333 Rolling Rock beer, 68 Royal Bee electric fishing reel, 236–237 Rule of parsimony, 595 S Sales, mixing with research, 95–96 Salesperson input, 25 Sample attrition, 277 Sample bias, 189 Sample distribution, 424–425, 426 Sample selection error, 194 Sample size determining on basis of judgment, 438 population size and, 435, 439 probability sampling and, 438–439 for proportions, 435–438 for questions involving means, 433–435 random error and, 432–433 Sample statistics, 413 Sample survey, 186 Sampling accuracy and reliability of, 388–389, 404–405 description of, 68–69, 387 Internet surveys and, 406–409 nonprobability, 395–398 pragmatic reasons for, 387 probability, 398–404, 408 random, 393–395, 398–399, 407 selection of method of, 404–406 sequential, 434 stages in, 391 stratified, 400, 438–439 target population, defining, 390, 408 training interviewers to avoid errors in, 454 verification of plan for, 455–456 Sampling distribution of sample mean, 424–425, 426, 427 Sampling frame error, 393, 394–395 Sampling frames, 391–393, 411 Sampling interval, 399 Sampling services, 392 Sampling units, 393 SAS, 499–500, 538, 595 Scale measurement determining which to use, 310 influence of, on multivariate data analysis, 583 interval scale, 300 nominal scale, 297–298 ordinal scale, 299–300 overview of, 296–297 ratio scale, 300–301 types of, 298, 299 Scales See also Rating scales; specific types of scales description of, 295 mathematical and statistical analysis of, 301–303 Scale values, computing, 303–304 Scanner-based consumer panels, 250 Scanner data, 26–27, 28–29 Scantel Research, 14 Scarborough Research, 433 Schönbrunn Palace case study, 373–374 Schwinn bicycles, 141 Scientific decision processes, 155–156 Scientific method, 7–8, 45–47 Scientific Telephone Samples, 411 Scrolling layout, 357 Search engine, 32 Secondary data, 161–163, 171–179 Secondary-data research designs, 164–170 Secondary sampling units, 393 Security issues with Internet surveys, 230 Selection effect, 277 Selection of course of action, 9–10 Self-administered questionnaires electronic, 225–231 by mail, 219–225 Self-efficacy intervention and job attitude, 257–260 Self-selection bias, 191 Semantic differential scales, 320–321, 328, 341 Semi-structured interviews, 151–152 Send.com ad, 83 Sensitivity of measurement, 309 Sentence completion method, 152 Sequence of questions in questionnaires, 349–351 Sequential sampling, 434 Service monitoring, 97–98 Significance level, 510–512 Silent probe, 449 Simple (bivariate) linear regression, 564 Simple-dichotomy questions, 340 Single-source data, 26–27, 178 Site analysis techniques, 168–169 Situation analysis, 112–113 Skip questions, 354, 356, 466 Smart agent software, 33 SMART car, 116 Snowball sampling, 398 SOAP (Simple Object Access Protocol), 256 Social desirability bias, 193–194 Social networking, 152, 228, 497 Software See also SPSS Askia, 443 ATLAS.ti, 138 CHAID, 492 for data analysis, 499–501 GUI, 356 to make questionnaires interactive, 360–361 SAS, 499–500, 538, 595 smart agent, 33 Sorting task in attitude measurement, 316, 328 Sources of data, 171–178 Speed Internet surveys and, 227 telephone interviews and, 215 Split-ballot technique, 345 Split-half method, 306 Sponsorship of mail surveys, 224 SPSS (Statistical Package for the Social Sciences) correlation matrix, 565 cross-tabulation output, 500 data file stored in, 471 data storage terminology in, 470 factor analysis in, 595 MANOVA, conducting, 591 popularity of, 499 regression results, obtaining in, 587 reverse coding scales in, 305 Spyware, 92 Squishing error, 347–348 Standard deviation, 419–421, 434 Standard error, pooled estimate of, 535 Standard error of the mean, 425 Standardized distribution curve, 424 Standardized normal distribution, 421–422 Standardized normal tables, 422 Standardized regression coefficient (␤ ), 566 Standardized regression estimates, 567 Standardized research services, 87–88 Standardized value, computation of, 423 Stapel scales, 322–323, 341 Starbucks, 4, 5, 14 Static group design, 279–280 Statistical Abstract of the United States, 28 Statistical base, 490 Statistical databases, 28–29 Statistical software packages, 499–500 See also SAS; SPSS Statistical techniques determining when to use, 547 selection of, 516–518 Statistics, 413, 440 Status bar, 357 St Louis Community College, 213 Stratified sampling, 400, 438–439 String characters, 470 Structuration theory, 41 7/14/09 9:20:25 AM 674 Structured qualitative responses, coding, 469–470 Structured questions, 196 Students adjustment to college by, 406 as subjects, 277–278 weight gain by, 511 Subjective research, 135 Subjects See also Participants, rights and obligations of; Respondents children as, 92–93 description of, 258 matching, 265 students as, 277–278 Summary of research project, 614–615 Summated scales, 303–304, 318–319 Supervision of fieldworkers, 455–457 Suppliers and contractors client sponsors and, 100 limited research service companies, 88 standardized research services, 87–88 syndicated service, 86–87 top 25 global firms, 89 Surveys See also Questionnaires administrative error in, 194–195 advantages of, 187–188 categories of error in, 189 consumer panels, 198 cross-sectional studies, 196–197 description of, 66 ethical issues in, 233 longitudinal studies, 197–198 mobile, 207 participation in, pretesting and, 233 random sampling error in, 188 research designs for, 231–232 respondent error in, 189–194 rule-of-thumb estimates for error, 195 systematic error in, 189 total quality management, 200–203 uses of, 186–187 Survey Sampling International, 409 SurveySite, 407 Susceptibility to influence, 294, 297 SUV sales, 116, 182 Symptoms of business problem ambiguity of, 111 description of, 51–52 identifying, 114–115 identifying relevant issues from, 116, 117 as scattered or widespread, 111 Syndicated service, 86–87 Systematic error, 189, 195, 203, 264 Systematic sampling, 399 Systematic sampling error, 394 Syzygy research firm, 255 T TABH, Inc case study, 636–637 Table of contents, 613 Tables contingency, 488–489, 491 display of data in, 498–499, 618–619 dummy, 127–128 frequency, 488 standardized normal, 422 two-way contingency, 490 Tables, statistical area under normal curve, 640 chi-square distribution, 642 critical values of F for ␣ ϭ 01, 644 critical values of F for ␣ ϭ 05, 643 93754_31_Ind_668-674.indd 674 Index critical values of Pearson correlation coefficient, 645 critical values of T in Wilcoxon matched-pairs signed-rank test, 646 random digits, 639 t-distribution for given probability levels, 641 Tabulations, 362, 475–476, 488 See also Cross-tabulations Tachistoscope, 272 Tallying, 488 Target population, 69, 390, 408 T-distribution calculating confidence interval estimate using, 520–521 description of, 518–520 for given probability levels, 641 univariate hypothesis test using, 521–522 Technology and lifestyle, attitude survey regarding, 333–334 Telemarketing, 91–92 Telephone interviews automated surveys of teens, 218 central location, 217 characteristics of, 215–217 computer-assisted, 218 computerized voice-activated, 218–219 description of, 214 initial contact, 445 layout of page from, 353 mobile phone, 214–215 precoded format for, 473, 474 questions for, 341–342 with skip questions, 354 Telescoping error, 347–348 Television monitoring, 247–249 Temporal sequence, 58 Terminating interviews, 451 Tertiary sampling units, 393 Testing effect, 276 Test-market, 59–60, 271, 273 Test of differences, 530, 531 Test-retest method, 306–307 Test tabulation, 475–476 Test units, 264–266, 389 Test variables, 536 Texas Instruments, 255 Text-message surveys, 231 Thematic apperception test, 153–154 Themes, and case studies, 140 Theory building, 44–45 definition of, 39 goals of, 39 graphical presentation of, 43, 44 practical value of, 47 verifying, 43–44 Thomas and Dorothy Leavey Library, 459 Thurstone scales, 325 Time constraints mail surveys and, 221 need for research and, 11 sampling method and, 405–406 scientific decision process and, 155–156 Time for research, 82 Timeliness of data, 21 Time series designs, 282 Title page of report, 613 Titles of questionnaires, 352 Tobii Eye Tracker system, 461 Tooheys beer, 289 Totally exhaustive response alternative, 341 Total quality management, 198–203, 455 Total variability, 546 Toyota, 318 Tracking mechanisms case study, 105 Tracking studies, 198 Trade association sources of data, 176 Traffic cameras, 248 Training for interviewers, 445, 454 Transmittal letters, 613, 614 Travel questionnaire case study, 371–372 Trend analysis, 165 T-test for comparing two means, 534–540 description of, 518 independent samples, 534–538, 542 one- and two-tailed, 521 paired samples, 538–540 type of question and, 516 TV-Cable Week (magazine), 13 Twitter, 497 Two-tailed test, 521 Two-way ANOVA, partitioning sum of squares for, 556–557 Two-way contingency tables, 490 Type I and Type II error, 515–516 Type of research, and uncertainty, 60–61 U Umbria Communications, Buzz Report, 170 Unaided recall, 347 Unbalanced rating scales, 330 Uncertainty in decision making, 52–53 type of research and, 60–61 Undisguised questions, 196 Uniform resource locator (URL), 32 United Airlines survey, 10–11 Unit of analysis, determining, 119 Univariate statistical analysis, 509 Universal Product Code (UPC), 28–29, 176 Universe, 387 Unobtrusive methods of data gathering, 69, 92 Unrestricted samples, 407 Unstructured qualitative responses, coding, 468–469 Unstructured question, 196 Urbanized areas, geographic hierarchy in, 404 Usability assessment of Web site, 322 U.S Department of the Interior telephone survey, 481 Utah Jazz case study, 605–606 V Validity external, 277–278 internal, 274–277 of measurement, 307–309 Value labels, 471 Vangard AccuSpeech and Mobile Voice Platform, 477 Vans shoes, 132 Variable piping software, 360 Variables blocking, 258 categorical, 119, 261 concept values and, 296 decision situations, hypotheses and, 121 definition of, 42, 119 dependent, 120, 257, 263–264 dummy, 585 establishing control of, 269–270 experimental, 59 extraneous, 265, 266, 269–270, 275–277 grouping, 536 hypotheses and, 121, 296 independent, 120, 257, 260–263, 491 moderator, 492 nuisance, 264 operationalizing, 42–43 selection of statistical techniques and, 516–517 test, 536 types of, 119–120 Variance See also ANOVA covariance, 559, 561–562 dispersion and, 420 partitioning, 544–545 wording questions to generate, 348–349 Variate, definition of, 581 Vendors of data, 172 Verification by reinterviewing, 457 of sampling plan, 455–456 of theory, 43–44 Vidal Sassoon, Inc., 505 Videoconferencing, and focus groups, 148 Video databases, 29–30 Visible observation, 240 Visual aids, and personal interviews, 211 See also Graphical representations of data Visual estimation of simple regression model, 567–568 Voice-pitch analysis, 252 W Walker Information Group, 205 Wal-Mart, data warehouse of, 472 Wang Laboratories, 83 Water, bottled, trend for, 176 Web sites Business.gov, 616 description of, 32 FedWorld, 175 random sampling of visitors to, 407 statistical resources, 517 traffic to, monitoring, 249–250 usability assessment, 322 Welcome screen, 227 “Why” follow-up questions, 448 Wilcoxon matched-pairs signed-rank test, 646 Within-group error, 545 Within-subjects design, 273 Wording questions, 337–342, 375–384 Work-family conflict, 558 Working population, 391–393 World Wide Web (WWW), 32 Y Yankelovich Partners, 452 Yoplait Go-Gurt, 8–9 Z Z-distribution, 520 Zogby International, 430 Z-test, 520, 540–541 7/14/09 9:20:25 AM ... Chapter 1: The Role of Business Research 17 Key Terms and Concepts applied business research, basic business research, business research, cross-validate, 15 evaluation research, 10 marketing-oriented,... the value of the research information exceed the cost of conducting research? No Yes Yes No Yes No Yes Conduct Business Research No Do Not Conduct Business Research Business Research in the Twenty-First... PROPRIETARY BUSINESS RESEARCH Business research has already been defined as a broad set of procedures and methods To clarify the DSS concept, consider a narrower view of business research Proprietary business