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. Refer to part

Which β coefficient measures the effect of flexibility(x1)on relationship quality (y), independently of the other

b) independent variables in the model?

c) Repeat part b for reputation(x2), 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 eachx, x1,x2, orx3on 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?

Short Answer

Expert verified

a) The equation is y=y=β0+β1x1+β2x2+β3x3+β4x4+ε.

b) The βcoefficient that measures changes in y for a given 1-unit increase in flexibility is measured by.

c) According to the equation the β coefficients associated with reputation (x2), empathy (x3) , and task alignment (x4) areβ1,β2, and β3 respectively.

d) Ey=β0+β1x1+β2x2+β3x3+β4x4+β5x1x4+β6x2x4+β7x3x4+ε

e) The null hypothesis would be H0:β5=0against the alternate hypothesis Ha:β50;

f) To test whether the effect of reputation (x2) and task alignment (x4) interact, the value of β6is tested. Mathematically, the null hypothesis would belocalid="1651190898603" H0:β6=0; against the alternate hypothesislocalid="1651190913791" Ha:β60

g) To test whether the effect of empathy (x3) and task alignment (x4) interact, the value of β7is tested. Mathematically, the null hypothesis would be localid="1651190931488" H0:β7=0; against the alternate hypothesislocalid="1651190948413" Ha:β70

Step by step solution

01

First-order model equation

The first-order model equation here isEy=β0+β1x1+β2x2+β3x3+β4x4+ε

Where,x1= flexibility in dealing with customers

x2= service worker reputation

x3= empathy for the customer

x4= service worker’s task alignment

02

Interpretation of  β coefficient

The βcoefficient that measures changes in y for a given 1-unit increase in flexibility is measured byβ1 .

03

Clarification of β coefficient

The βcoefficients associated with different variables represent the changes in y due to a 1-unit change in the respective variable.

Therefore, according to the equation the β coefficients associated with reputation (x2) , empathy (X3), and task alignment (x4) are β2,β3 , and β4 respectively.

04

Interaction model

The interaction model where task alignment (x4) impacts the relationship of each (x1, X2, and X3) can be written as,

Ey=β0+β1x1+β2x2+β3x3+β4x4+β5x1x4+β6x2x4+β7x3x4+ε

Here the added variables x1x4,a, x2x4and x3x4represent the interaction between x1and x4, x2and x4, x3 and x4respectively.

05

Significance of β5

To test whether the effect of flexibility x1 and x4 task alignmentinteract, the value is tested

Mathematically,

The null hypothesis would be H0:β5=0against the alternate hypothesis;

06

Importance of β6

To test whether the effect of reputation (x2) and task alignment (x4) interact, the value is tested

Mathematically,

The null hypothesis would be H0:β6=0; against the alternate hypothesis Ha:β60

To test whether the effect of empathy (x3) and task alignment (x4) interact, the value is tested

Mathematically,

The null hypothesis would be H0:β7=0; against the alternate hypothesis Ha:β70

07

 Conclusion about the interaction model

When it is concluded from the t-test that none of the tests are statistically significant for interaction then it can be said that the researcher’s theory that there are some interactions in the model is not true.

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Most popular questions from this chapter

Question: The Excel printout below resulted from fitting the following model to n = 15 data points: y=β0+β1x1+β2x2+ε

Where,

x1=(1iflevel20ifnot)x2=(1iflevel30ifnot)

Suppose you fit the second-order model y=β0+β1x+β2x2+εto n = 25 data points. Your estimate ofβ2isβ^2= 0.47, and the estimated standard error of the estimate is 0.15.

  1. TestH0:β2=0againstHa:β20. Useα=0.05.
  2. Suppose you want to determine only whether the quadratic curve opens upward; that is, as x increases, the slope of the curve increases. Give the test statistic and the rejection region for the test forα=0.05. Do the data support the theory that the slope of the curve increases as x increases? Explain.

Question: Chemical plant contamination. Refer to Exercise 12.18 (p. 725) and the U.S. Army Corps of Engineers study. You fit the first-order model,E(Y)=β0+β1x1+β2x2+β3x3 , to the data, where y = DDT level (parts per million),X1= number of miles upstream,X2= length (centimeters), andX3= weight (grams). Use the Excel/XLSTAT printout below to predict, with 90% confidence, the DDT level of a fish caught 300 miles upstream with a length of 40 centimeters and a weight of 1,000 grams. Interpret the result.

Question:Suppose you fit the first-order model y=β0+β1x1+β2x2+β3x3+β4x4+β5x5+εto n=30 data points and obtain SSE = 0.33 and R2=0.92

(A) Do the values of SSE and R2suggest that the model provides a good fit to the data? Explain.

(B) Is the model of any use in predicting Y ? Test the null hypothesis H0:β1=β2=β3=β4=β5=0 against the alternative hypothesis {H}at least one of the parameters β1,β2,...,β5 is non zero.Useα=0.05 .

Can money spent on gifts buy love? Refer to the Journal of Experimental Social Psychology (Vol. 45, 2009) study of whether buying gifts truly buys love, Exercise 9.9 (p. 529). Recall those study participants were randomly assigned to play the role of gift-giver or gift-receiver. Gift-receivers were asked to provide the level of appreciation (measured on a 7-point scale where 1 = “not at all” and 7 = “to a great extent”) they had for the last birthday gift they received from a loved one. Gift-givers were asked to recall the last birthday gift they gave to a loved one and to provide the level of appreciation the loved one had for the gift.

  1. Write a dummy variable regression model that will allow the researchers to compare the average level of appreciation for birthday gift-giverswith the average for birthday gift-receivers.
  2. Express each of the model’s β parameters in terms ofand.
  3. The researchers hypothesize that the average level of appreciation is higher for birthday gift-givers than for birthday gift-receivers. Explain how to test this hypothesis using the regression model.
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