Deliverable 2 CCSU scholars investigated whether the attributes of customer service quality and mobile app design quality predict mobile shoppers’ Trust, Repurchase Intention, or Recommendation...

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Deliverable 2 CCSU scholars investigated whether the attributes of customer service quality and mobile app design quality predict mobile shoppers’ Trust, Repurchase Intention, or Recommendation Intention. From 286 mobile consumers they recorded demographic characteristics that were described in Deliverable 1. They also measured the mobile shopping quality dimensions and customer attitudes as reported by the mobile shoppers: (1) Reliability: Items Q18, Q19, Q20 (2) Responsiveness: Items Q21, Q22, Q23 (3) Assurance: Items Q24, Q25, Q26 (4) Personalization: Items Q27, Q28, Q29 (5) Content quality: Items Q30, Q31, Q32 (6) Ease of use: Items Q33, Q34, Q35 (7) Aesthetics: Items Q36, Q37, Q38 (8) Risks: Items Q39, Q40, Q41, Q42, Q43, Q44 (9) Trust: Items Q45, Q46, Q47, Q48, Q49 (10) Repurchase intention: Items Q62, Q63, Q64, Q65 (11) Recommendation intention: Items Q66, Q67, Q68 The items were measured by the 5-point Likert Scale: 1=strongly disagree, 3=neutral, 5=strongly agree. Past research indicated that the quality dimensions (1)-(8) were good predictors for mobile shoppers’ attitudes (9)-(11). Analyze the data with a multiple regression model. You are needed to: 1. Pick one dependent variable from (9)-(11) (i.e., Trust, Repurchase intention, Recommendation intention). 2. Pick four independent variables from (1)-(8) (i.e., Reliability, Responsiveness, Assurance, Personalization, Content quality, Ease of use, Aesthetics, Risks). 3. Form four hypotheses between the independent variables and the dependent variable. 4. Test each hypothesis using simple linear regression. Is there a significant relationship between the independent variable and the dependent variable for each hypothesis? Explain. 5. Conduct a hierarchical linear regression analysis. Copy and paste your results below. For example, if you choose Trust (9) as the dependent variable and Reliability (1), Responsiveness (2), Assurance (3), and Personalization (4) as the four predictors. You can conduct the hierarchical linear model in three steps: I. Enter Trust (9) and Reliability (1); II. Add variable Responsiveness (2); III. Add variable Assurance (3); IV. Add variable Personalization (4). 6. Which of the four models (I, II, III, and IV) best explains the dependent variable? Explain. Uliana Batih Central Connecticut State University BUS-538-81 Summer 2022 Prof. Richard Zhang PROJECT FILE General/Demographic characteristics Overall group Male group Female group Other group   (n=286) (n=140) (n=134) (n=12)   n percentage n percentage n percentage n percentage Age (years)                 20-24 33 11.5 12 8.6 20 14.9 1 8.3 25-34 112 39.2 64 45.7 40 29.9 8 66.7 35-44 78 27.3 42 30.0 34 25.4 2 16.7 45-54 37 12.9 14 10.0 23 17.2 0 0 55-64 23 8.0 5 3.6 17 12.7 1 8.3 65 or over 3 1.0 3 2.1 0 0 0 0 Educational attainment Less than high school 1 0.3 0 0.0 1 0.7 0 0.0 High school 57 19.9 31 22.1 23 17.2 3 25.0 Some college 33 11.5 19 13.6 14 10.4 0 0.0 Trade/technical school 157 54.9 77 55.0 71 53.0 9 75.0 College graduate 10 3.5 3 2.1 7 5.2 0 0.0 Graduate school 28 9.8 10 7.1 18 13.4 0 0.0 Number of times per week using mobile apps for shopping or information search 1-2 times 27 9.4 13 9.3 13 9.7 1 8.3 3-4 times 24 8.4 9 6.4 15 11.2 0 0.0 5-6 times 88 30.8 43 30.7 37 27.6 8 66.7 7-8 times 30 10.5 20 14.3 10 7.5 0 0.0 9-10 times 97 33.9 49 35.0 45 33.6 3 25.0 Over 12 times 20 7.0 6 4.3 14 10.4 0 0.0 Number of hours per week using mobile apps for shopping or information search 1-3 hours 44 15.4 24 17.1 19 14.2 1 8.3 4-6 hours 43 15.0 20 14.3 20 14.9 3 25.0 7-9 hours 32 11.2 15 10.7 17 12.7 0 0.0 10-12 hours 44 15.4 22 15.7 20 14.9 2 16.7 13-15 hours 12 4.2 8 5.7 4 3.0 0 0.0 16-18 hours 30 10.5 14 10.0 12 9.0 4 33.3 Over 18 hours 81 28.3 37 26.4 42 31.3 2 16.7 Number of mobile purchases in the past 12 months 1-2 times 5 1.7 4 2.9 1 0.7 0 0.0 3-4 times 201 70.3 98 70.0 94 70.1 9 75.0 5-6 times 6 2.1 3 2.1 3 2.2 0 0.0 7-8 times 55 19.2 26 18.6 27 20.1 2 16.7 9-10 times 5 1.7 4 2.9 1 0.7 0 0.0 11-12 times 10 3.5 5 3.6 5 3.7 0 0.0 13-14 times 4 1.4 0 0.0 3 2.2 1 8.3 Mobile shopping experience/years Less than 1 year 23 8 14 10.0 8 6.0 1 8.3 1-2 years 53 18.5 30 21.4 21 15.7 2 16.7 3-4 years 76 26.6 27 19.3 45 33.6 4 33.3 5-6 years 16 5.6 9 6.4 7 5.2 0 0.0 7-8 years 94 32.9 46 32.9 44 32.8 4 33.3 Over 8 years 24 8.4 14 10.0 9 6.7 1 8.3 Most frequently purchased items Clothing/Shoes 210 73.4 94 67.1 106 79.1 10 83.3 Bags/Accessories 79 27.6 24 17.1 50 37.3 5 41.7 Appliance/Furniture 38 13.3 17 12.1 20 14.9 1 8.3 Electronics/Computers 196 68.5 111 79.3 78 58.2 7 58.3 Food/Groceries 142 49.7 58 41.4 80 59.7 4 33.3 Travel/Hotel/Ticket 107 37.4 53 37.9 52 38.8 2 16.7 Books/Movies/Music 188 65.7 95 67.9 85 63.4 8 66.7 Cosmetics/Body Care/Pharmacy 112 39.2 41 29.3 66 49.3 5 41.7 Others 37 12.9 15 10.7 20 14.9 2 16.7 According to the table, majority of the total respondents as well as males and females belongs to the age group 25-34 and very less respondents are from elderly age group. More than half (about 56 percent) of them are qualified with trade or technical school in each category where males pursued trade or technical school are 55 percent, female as 53 percent and others as 75 percent. The table shows that both males and females spend the most 9-10 number of times per week using mobile apps for shopping or information search, but the respondents belong to others gender used 5-6 times per week for this. More than 18 hours per week spend by males (about 26 percent) and females (about 31 percent) for shopping or information search using mobile apps whereas the hours spend are 16-18 for others gender. The number of mobile purchases is 3-4 times in past 12 month in each subgroup categories but the experience of mobile shopping in terms of years is more in males for 7-8 years whereas only 3-4 years for females. The most frequently purchased items for males are electronics/ computers (79.3 percent) followed by books/music/movies (67.9 percent) whereas females mostly bought clothing/shoes (79.1 percent). In the same manner, respondents who are of other genders mostly purchased clothing/shoes followed by books/music/movies and electronics/ computers.
Answered 1 days AfterJul 23, 2022

Answer To: Deliverable 2 CCSU scholars investigated whether the attributes of customer service quality and...

Shakeel answered on Jul 24 2022
78 Votes
Ans 1
Dependent variable:    
Trust:            Q49 (I feel that mobile retailer is trustworthy)
Ans 2
Independent variables:
Reliability:         Q 18 (The mobile retailer delivers exactly the same product as I order)
Responsiveness:    Q21 (The mobile retailer provides prompt cust
omer service)
Assurance:        Q24 (The mobile retailer can properly handle any problems that arise)
Ease of use:        Q 33 (The mobile retailer's app is easy to use)
Ans 3
Hypotheses are as follows:
Hypothesis 1    H0:    There is no significant relationship between Trust and Reliability
Hypothesis 2    H0:    There is no significant relationship between Trust and Responsiveness
Hypothesis 3    H0:    There is no significant relationship between Trust and Assurance
Hypothesis 4    H0:    There is no significant relationship between Trust and Ease of use
Ans 4
Hypothesis 1    H0:    There is no significant relationship between Trust and Reliability
Regression output: Trust Vs Reliability
    Parameter Estimates
    
    Estimate
    Std. Error
    Wald
    df
    Sig.
    95% Confidence Interval
    
    
    
    
    
    
    Lower Bound
    Upper Bound
    Threshold
    [Q49 = 1]
    -7.159
    1.031
    48.234
    1
    .000
    -9.179
    -5.139
    
    [Q49 = 3]
    -3.760
    .311
    145.972
    1
    .000
    -4.370
    -3.150
    
    [Q49 = 4]
    -.153
    .186
    .669
    1
    .413
    -.518
    .213
    Location
    [Q18=3]
    -2.871
    .740
    15.059
    1
    .000
    -4.321
    -1.421
    
    [Q18=4]
    -1.833
    .274
    44.682
    1
    .000
    -2.370
    -1.295
    
    [Q18=5]
    0a
    .
    .
    0
    .
    .
    .
    Link function: Logit.
    a. This parameter is set to zero because it is redundant.
The p-values of the responses 3 and 4 of the dependent variable – “The mobile retailer delivers exactly the same product as I order (Q18)” are 0.000 < 0.05, and hence, we reject the null hypothesis and conclude that there is significant relationship between Trust and Reliability.
Hypothesis 2    H0:    There is no significant relationship between Trust and Responsiveness
Regression output: Trust Vs Responsiveness
    Parameter Estimates
    
    Estimate
    Std. Error
    Wald
    df
    Sig.
    95% Confidence Interval
    
    
    
    
    
    
    Lower Bound
    Upper Bound
    Threshold
    [Q49 = 1]
    -7.221
    1.034
    48.780
    1
    .000
    -9.247
    -5.195
    
    [Q49 = 3]
    -3.852
    .328
    137.637
    1
    .000
    -4.495
    -3.208
    
    [Q49 = 4]
    -.377
    .228
    2.739
    1
    .098
    -.823
    .069
    Location
    [Q21=3]
    -2.187
    .382
    32.723
    1
    .000
    -2.936
    -1.438
    
    [Q21=4]
    -1.657
    .294
    31.737
    1
    .000
    -2.233
    -1.080
    
    [Q21=5]
    0a
    .
    .
    0
    .
    .
    .
    Link function: Logit.
    a. This parameter is set to zero because it is redundant.
The p-values of the responses 3 and 4 of the dependent variable – “The mobile retailer...
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