Concept explainers
Service workers and customer relations. A study in Industrial Marketing Management (February 2016) investigated the impact of service workers’ (e.g., waiters and waitresses) personal resources on the quality of the firm’s relationship with customers. The study focused on four types of personal resources: flexibility in dealing with customers (x1), service worker reputation (x2), empathy for the customer (x3), and service worker’s task alignment (x4). A multiple regression model was employed used to relate these four independent variables to relationship quality (y). Data were collected for n = 220 customers who had recent dealings with a service worker. (All variables were measured on a quantitative scale, based on responses to a questionnaire.)
- a. Write a first-order model for E(y) as a
function of the four independent variables. - b. Refer to part a. Which β coefficient measures the effect of flexibility (x1) on relationship quality (y), independently of the other independent variables in the model?
- c. Repeat part b for reputation (x1), empathy (x3), and task alignment (x4).
- d. The researchers theorize that task alignment (x4) “moderates” the effect of each of the other x’s on relationship quality (y) — that is, the impact of each x (x1, x2, or x3) on y depends on x4. Write an interaction model for E(y) that matches the researchers’ theory.
- e. Refer to part d. What null hypothesis would you test to determine if the effect of flexibility (x1) on relationship quality (y) depends on task alignment (x4)?
- f. Repeat part e for the effect of reputation (x2) and the effect of empathy (x3).
- g. None of the t-tests for interaction were found to be “statistically significant”. Given these results, the researchers concluded that their theory was not supported. Do you agree?
Want to see the full answer?
Check out a sample textbook solutionChapter 12 Solutions
Statistics for Business and Economics (13th Edition)
- Rebecca Chory, Ph.D., now an associate professor of communication at West Virginia University, began studying the effect of such portrayals on patients' attitudes toward physicians. Using a survey of 300 undergraduate students, she compared perceptions of physicians in 1992—the end of the era when physicians were shown as all-knowing, wise father figures—with those in 1999, when shows such as ER and Chicago Hope (1994–2000) were continuing the transformation to showing the private side and lives of physicians, including vivid demonstrations of their weaknesses and insecurities. Dr. Chory found that, regardless of the respondents' personal experience with physicians, those who watched certain kinds of television had declining perceptions of physicians' composure and regard for others. Her results indicated that the more prime time physician shows that people watched in which physicians were the main characters, the more uncaring, cold, and unfriendly the respondents thought physicians…arrow_forwardRebecca Chory, Ph.D., now an associate professor of communication at West Virginia University, began studying the effect of such portrayals on patients' attitudes toward physicians. Using a survey of 300 undergraduate students, she compared perceptions of physicians in 1992—the end of the era when physicians were shown as all-knowing, wise father figures—with those in 1999, when shows such as ER and Chicago Hope (1994–2000) were continuing the transformation to showing the private side and lives of physicians, including vivid demonstrations of their weaknesses and insecurities. Dr. Chory found that, regardless of the respondents' personal experience with physicians, those who watched certain kinds of television had declining perceptions of physicians' composure and regard for others. Her results indicated that the more prime time physician shows that people watched in which physicians were the main characters, the more uncaring, cold, and unfriendly the respondents thought physicians…arrow_forwardA researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. Is there significance for either gender or income?arrow_forward
- A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What is one research hypothesis (there are three possible hypotheses here – name them all if you can.arrow_forwardA researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. what is the significance of the interaction of gender and income?arrow_forwardA researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What is one research hypothesis (there are three possible hypotheses here name them all if you can but naming at least one is required)?arrow_forward
- 1 2 3 4 5 6 7 8 9 _0 1 2 3 _4 5 6 _7 8 9 20 21 22 23 24 25 26 27 28 29 30 31 52 53 4 35 36 37 38 39 10 11 12 13 14 15 16 47 18 19 50 51 52 53 54 A Income ($1000s) 54 30 32 50 31 55 37 40 66 51 25 48 27 33 65 63 42 21 44 37 62 21 55 42 41 54 30 48 34 67 50 67 55 52 62 64 22 29 39 35 39 54 23 27 26 61 30 22 46 66 B Household Size 3 2 4 5 2 2 1 2 4 3 3 4 1 2 3 4 6 2 1 5 6 3 7 2 7 6 1 2 5 4 2 5 6 2 3 2 3 4 2 1 4 3 6 2 7 2 AUANN 2 4 5 4 с Amount Charged ($) 4,016 3,159 5,100 4,742 1,864 4,070 2,731 3,348 4,764 4,110 4,208 4,219 2,477 2,514 4,214 4,965 4,412 2,448 2,995 4,171 5,678 3,623 5,301 3,020 4,828 5,573 2,583 3,866 3,586 5,037 3,605 5,345 5,370 3,890 4,705 4,157 3,579 3,890 2,972 3,121 4,183 3,730 4,127 2,921 4,603 4,273 3,067 3,074 4,820 5,149 D E F G H I J Karrow_forward“The rapid growth of video game popularity has generated concern among practitioners, parents, scholars, and politicians,” wrote researchers Hope M. Cummings and Elizabeth A. Vandewater. In their study, Cummings and Vandewater measured the time adolescents spent playing video games as well as time spent doing other activities, such as interacting with family and friends, reading or doing homework, or playing sports. [Source: Cummings, H., & Vandewater, E. (2007). Relation of adolescent video game play to time spent in other activities. Archives of Pediatrics & Adolescent Medicine, 161(7), 684–689.] After reading about the study conducted by Cummings and Vandewater, you decide to conduct a similar study among a sample of 10 teenage girls. You ask the girls to keep a log of their activities for a day. You want to test whether the amount of time girls spend playing video games is correlated with the amount of time they read for pleasure. You realize that because some of the…arrow_forward“The rapid growth of video game popularity has generated concern among practitioners, parents, scholars, and politicians,” wrote researchers Hope M. Cummings and Elizabeth A. Vandewater. In their study, Cummings and Vandewater measured the time adolescents spent playing video games as well as time spent doing other activities, such as interacting with family and friends, reading or doing homework, or playing sports. [Source: Cummings, H., & Vandewater, E. (2007). Relation of adolescent video game play to time spent in other activities. Archives of Pediatrics & Adolescent Medicine, 161(7), 684–689.] After reading about the study conducted by Cummings and Vandewater, you decide to conduct a similar study among a sample of 10 teenage girls. You ask the girls to keep a log of their activities for a day. You want to test whether the amount of time girls spend playing video games is correlated with the amount of time they read for pleasure. You realize that because some of the…arrow_forward
- The rapid growth of video game popularity has generated concern among practitioners, parents, scholars and politicians,” wrote researchers Hope M. Cummings and Elizabeth A. Vandewater. “Particularly during adolescence, when social interactions and academic success lay the groundwork for health in adulthood, there is concern that video games will interfere with the development of skills needed to make a successful transition to adulthood.” [Source: Cummings, H., & Vandewater, E. (2007). Relation of adolescent video game play to time spent in other activities. Archives of Pediatrics & Adolescent Medicine, 161(7), 684–689.] Cummings and Vandewater measured the time adolescents spent playing video games and the time they spent doing other activities, such as interacting with family and friends, reading or doing homework, or playing sports. Suppose you decide to conduct a similar study among a random sample of 62 teenage girls who play video games. You want to determine whether…arrow_forwardSuppose you have been hired as a management consultant by a major oil company to help it optimally price gasoline at its service stations. Your client would like your team to perform a study on customers' gasoline purchasing habits when they notice an increase in the price of gas. You have access to the following groups of people: Group Description Number in Group People who have not noticed a gas-price increase 30 People who drive electric cars 35 People who have recently noticed a gas-price increase 80 People who ride their bikes to work 20 People who ride the bus 100 To set up your experiment on how price-increase awareness impacts customer behavior, you would have ______ people in your treatment group and ______ people in your control group.arrow_forwardThe manager Concerned about her current customer base, manager Andersen started to think of factors that might affect the attractiveness of an auditing firm. Of course, the service quality provided and the fees charged by the auditor seem two important factors. Next, she decides that the reputation of the auditing firm also needs to be included in the framework as an independent variable. As illustrated by the dramatic effects of recent auditing scandals, reputation seems especially important for large auditors (i.e., auditing firms that are large in size). Finally, manager Andersen also thinks that the proximity of the auditing firm to the customer is another variable to be included as an independent variable. Proximity very likely affects the possibility for the client to personally meet with the auditors on a regular basis and she knows from her own contact with customers that they perceive personal interactions as quite important. Consider the above scenario shown; answer the…arrow_forward
- Big Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin Harcourt