An Evaluative Analysis of Retail Chains in the 21st

Century

Leon Grove

University of Phoenix

Committee Membership

Dr. Santosh Sambare, Ph.D. – Mentor

Dr. Kevin Banning, Ph.D. – Committee Member

Dr. Craig Martin, Ph.D. – Committee Member

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Problem Statement In the retail chain of consumer goods,

there appears to be relatively limited information on the relationship between allocation of resources by these chains for marketing, technology and inventory initiatives and customer satisfaction and customer loyalty.

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Support for the Problem Statement

• “Firms that are unable to satisfy customers can expect to lose market share to rivals offering better products and service at lower prices” (Simon et al., 2009).

• “Satisfaction is also not always enough to ensure customer loyalty, even though satisfaction leads to loyalty in many instances” (Pleshko & Baqer, 2008).

Literature supports the hypothesis that customer satisfaction may not lead to customer loyalty in several situations:

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Purpose Statement The purpose of this study was to

determine if there is empirical data to support the hypothesis that retail store chains can increase customer satisfaction and customer loyalty through allocation of resources to marketing, technology, and inventory management systems.

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Significance of Study/Leadership

• The significance for the study is that retailing is an important component of consumers’ buying and consumer spending impacts the overall economy. Improvements gained through technology and inventory efficiency will allow retail store chains to provide the highest quality products at exceptionally low prices.

• Marketing initiatives lead to customer satisfaction and loyalty and helps consumers in particular and the economy in general.

• This research will help decision makers in implementing programs which will benefit their customers through improvements in satisfaction and loyalty.

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Research Questions Do retail store chains effectively use tools

such as marketing, technology, and inventory management systems to improve customer satisfaction?

How technology can be an effective management tool to improve customer’s loyalty?

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Research Questions

How may the inventory management systems improve customer loyalty?

How may the implementation or maintenance cost affect customer satisfaction and customer loyalty as it relates to marketing, technology, and inventory management systems?

How will management transform the technological processes to optimize the level of customer satisfaction?

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Hypotheses

• H1: There is no positive/negative relationship between technology processes and customer satisfaction.

• H01: There is a positive/negative relationship between technology processes and customer satisfaction.

• H1a: There is no positive/negative relationship between technology processes and customer loyalty.

• H01a: There is a positive/negative relationship between technology processes and customer loyalty.

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Hypotheses

• H2: There is no positive/negative relationship between marketing spend on customer satisfaction.

• H02: There is a positive/negative relationship between marketing spend on customer satisfaction.

• H2a: There is no positive/negative relationship between marketing spend on customer loyalty.

• H02a: There is a positive/negative relationship between marketing spend on customer loyalty.

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Hypotheses

• H3: The efficiency of inventory management systems do not reduce retailer’s cost to improve customer satisfaction.

• H03: The efficiency of inventory management system reduces retailer’s cost to improve customer satisfaction.

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Relevant/Important Research

Betancourt et al., (2007) research results imply that “distribution services are the main mechanism through which retailers can influence customer satisfaction with a transaction at the supermarket level” (p. 311).

Bowden (2009) conceptualized that “companies have a continued reliance on marketing to assess customer responses to their products and services in the belief that high levels of satisfaction will lead to increased customer loyalty, intention to purchase, word-of-mouth recommendations, profit, market share, and return on investments” (p. 63).

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Methodology

The methodology consisted of two parts:

In the first part, financial data of several retail store chains was captured.

In the second part, an online survey was used to collect data from customers and analytical approaches were applied to determine the relationship between the dependent and independent variables namely marketing, technology initiatives and inventory control systems.

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Target Population

The population for this research study are several leading retail chain for consumer goods in the US.

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Sample

The research study surveyed a sample of consumers to gain a better understanding of their overall level of satisfaction and loyalty as well as their satisfaction with specific variables related to their shopping experience at these stores.

The total sample for this study were 126 respondents who shopped at Wal-Mart, Target, and Kroger Stores.

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Analyses The data will be analyzed using

Analysis of Variance (ANOVA), to understand the relationship between marketing, inventory control and technological initiatives and customer satisfaction as well as customer loyalty.

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ResultsAnalysis of Variance: Comparison of Overall Satisfaction

SUMMARY

Groups Count Sum AverageVariance

Overall, I am satisfied with this store. – Wal-Mart 105 366 3.48 1.14

Overall, I am satisfied with this store. – Target 103 399 3.87 1.03

Overall, I am satisfied with this store. – Kroger 36 140 3.88 0.84

ANOVA

Source of Variation SS df MS F P-valueBetween Groups 9.19 2 4.59 4.38 0.01Within Groups 253.14 241 1.05

Total 262.34 243 

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ResultsAnalysis of Variance: Comparison of Overall Loyalty

SUMMARY

Groups Count Sum AverageVariance

I consider myself loyal to the store. – Wal-Mart 105 290 2.76 1.95

I consider myself loyal to the store. – Target 103 324 3.14 1.40

I consider myself loyal to the store. – Kroger 37 119 3.21 1.61

ANOVA

Source of Variation SS df MS F P-valueBetween Groups 9.85 2 4.925 2.94 0.054Within Groups 404.133 242 1.66

Total 413.98 244

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ResultsAnalysis of Variance Commitment to remaining a customer

SUMMARY

Groups Count Sum Average VarianceI am committed to the store - Wal-Mart 105 294 2.8 1.68

I am committed to the store – Target 105 339 3.22 1.46

I am committed to the store – Kroger 36 113 3.13 1.55

ANOVA

Source of Variation SS df MS F P-valueBetween Groups 10.11 2 5.05 3.22 0.041Within Groups 381.61 243 1.57

Total 391.73 245 

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Results

• From the above results we can infer that customer satisfaction, customer loyalty, and commitment to the store are different for these stores.

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Results• Evaluation of hypothesis H1

This hypothesis is related to the use of technology• Retailers employ technology to facilitate their functions as well as to make

shopping easier and efficient for customers. • Some of the benefits of utilizing technology are:

» reduction in waiting time» making it easier to locate items in the store» reducing processing time when items are returned » ability to process manufacturer’s and competitors coupons

The null and alternate hypotheses are noted below:

• H1: There is no positive/negative relationship between technology processes and customer satisfaction.

• H01: There is a positive/negative relationship between technology processes and customer satisfaction.

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ResultsTable 4-8Analysis of Variance Test Variable: Overall satisfaction with the storeReasonable Waiting time

Wal-MartGroups Count Average Std. Dev. Std. ErrorWaiting time is reasonable 13 4.15 .555 .154Waiting Time is not reasonable 92 3.39 1.09 .114

T-test df P-valueEqual Variances Assumed 2.47 103 .015

It can be inferred that for Wal-Mart store at 95% Confidence Level Customer Satisfaction is associated with waiting time.

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ResultsTable 4-8Analysis of Variance Test Variable: Overall satisfaction with the storeReasonable Waiting time

TargetGroups Count Average Std. Dev. Std. ErrorWaiting time is reasonable 49 4.06 .966 .138Waiting Time is not reasonable 54 3.70 1.04 .141

T-test df P-valueEqual Variances Assumed 1.81 101 .07

It can be inferred that for Target store at 93% Confidence Level Customer Satisfaction is associated with waiting time.

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ResultsTable 4-8Analysis of Variance Test Variable: Overall satisfaction with the storeReasonable Waiting time

KrogerGroups Count Average Std. Dev. Std. ErrorWaiting time is reasonable 16 4.25 .775 .194Waiting Time is not reasonable 20 3.60 .94 .210

T-test df P-valueEqual Variances Assumed 2.27 34 .03

It can be inferred that for Kroger store at 95% Confidence Level Customer Satisfaction is associated with waiting time.

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Accepted Hypotheses

Wal-Mart Target Kroger

H1: Reject Reject Reject

H01: Accept Accept Accept

H1: There is no positive/negative relationship between technology processes and customer satisfaction.

H01: There is a positive/negative relationship between technology processes and customer satisfaction.

Based on this analysis the null hypothesis can be accepted that there is a positive/negative relationship between technology processes and customer satisfaction

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Results• Evaluation of hypothesis H1a

This hypothesis is related to the use of technology• Retailers employ technology to facilitate their functions to improve customers

loyalty. • Some of the benefits of utilizing technology are:

» reduction in waiting time» making it easier to locate items in the store» reducing processing time when items are returned » ability to process manufacturer’s and competitors coupons» having advertised items in stock.

• The null and alternate hypotheses are noted below:

• H1a: There is no positive/negative relationship between technology processes and customer loyalty.

• H01a: There is a positive/negative relationship between technology processes and customer loyalty.

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ResultsTable 4-13Analysis of Variance Test Variable: I consider myself loyal to the storeReasonable Waiting time

Wal-MartGroups Count Average Std. Dev. Std. ErrorWaiting time is reasonable 12 3.25 1.22 .351Waiting Time is not reasonable 93 2.70 1.41 .146

T-test df P-valueEqual Variances Assumed 1.29 103 .200

It can be inferred that for Wal-Mart that the relationship customer loyalty and waiting time is not significant.

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ResultsTable 4-13Analysis of Variance Test Variable: I consider myself loyal to the storeReasonable Waiting time

TargetGroups Count Average Std. Dev. Std. ErrorWaiting time is reasonable 49 3.18 1.185 .169Waiting Time is not reasonable 54 3.11 1.192 .162

T-test df P-valueEqual Variances Assumed .310 100 .758

It can be inferred that for Target that the relationship customer loyalty and waiting time is not significant.

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ResultsTable 4-13Analysis of Variance Test Variable: I consider myself loyal to the storeReasonable Waiting time

KrogerGroups Count Average Std. Dev. Std. ErrorWaiting time is reasonable 17 3.47 1.18 .286Waiting Time is not reasonable 20 3.00 1.34 .299

T-test df P-valueEqual Variances Assumed 1.14 35 .263

It can be inferred that for Kroger that the relationship customer loyalty and waiting time is not significant.

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Accepted Hypotheses

Wal-Mart Target Kroger

H1a: Accept Accept Accept

H01a: Reject Reject Reject

H1a: There is no positive/negative relationship between technology and customer loyalty.

H01a: There is a positive/negative relationship between technology and customer loyalty.

Based on this analysis the alternate hypothesis can be accepted that there is no positive/negative relationship between technology and customer loyalty

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Results• Evaluation of hypothesis H2

This hypothesis is related to marketing spend• Retailers spend marketing dollars to employ processes to improve customer

satisfaction. • Some of the benefits of marketing spends are:

» Prices from most brands lower than other stores» Good customer service» Receive circulars with specials in the mail » Has good interior décor

• The null and alternate hypotheses are noted below:

• H2: There is no positive/negative relationship between marketing spend and customer satisfaction.

• H02: There is a positive/negative relationship between marketing spend and customer satisfaction.

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ResultsTable 4-18Analysis of Variance Test Variable: Overall satisfaction with this storePrices from most brands lower than other stores

Wal-MartGroups Count Average Std. Dev. Std. ErrorPrices from most brands lower 63 3.67 .950 .120than other storesPrices from most brands not 42 3.21 1.180 .182lower than other stores

T-test df P-valueEqual Variances Assumed 2.167 103 .033

It can be inferred that for Wal-Mart store at 95% Confidence Level Customer Satisfaction is associated with prices from most brands lower than other stores.

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ResultsTable 4-18Analysis of Variance Test Variable: Overall satisfaction with this storePrices from most brands lower than other stores

TargetGroups Count Average Std. Dev. Std. ErrorPrices from most brands lower 29 4.14 .743 .138than other storesPrices from most brands not 74 3.77 1.092 .127lower than other stores

T-test df P-valueEqual Variances Assumed 1.961 75 .054

It can be inferred that for Target store at 95% Confidence Level Customer Satisfaction is associated with prices from most brands lower than other stores.

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ResultsTable 4-18Analysis of Variance Test Variable: Overall satisfaction with this storePrices from most brands lower than other stores

KrogerGroups Count Average Std. Dev. Std. ErrorPrices from most brands lower 12 4.33 .651 .188than other storesPrices from most brands not 24 3.67 .963 .197lower than other stores

T-test df P-valueEqual Variances Assumed 2.41 31 .020

It can be inferred that for Kroger store at 95% Confidence Level Customer Satisfaction is associated with prices from most brands lower than other stores.

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Accepted Hypotheses

Wal-Mart Target Kroger

H2: Reject Reject Reject

H02: Accept Accept Accept

H2: There is no positive/negative relationship between marketing spend and customer satisfaction.

.

H02: There is a positive/negative relationship between marketing spend and customer satisfaction.

Based on this analysis the null hypotheses can be accepted that there is a positive/negative relationship between marketing spend and customer satisfaction

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Results• Evaluation of hypothesis H2a

This hypothesis is related to marketing spend• Retailers spend marketing dollars to employ processes to improve customer

loyalty. • Some of the benefits of marketing spends are:

» Prices from most brands lower than other stores» Good customer service» Receive circulars with specials in the mail » Has good interior décor

• The null and alternate hypotheses are noted below:

• H2a: There is no positive/negative relationship between marketing spend and customer loyalty.

• H02a: There is a positive/negative relationship between marketing spend and customer loyalty.

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ResultsTable 4-22Analysis of Variance Test Variable: I consider myself loyal to the storePrices from most brands lower than other stores

Wal-MartGroups Count Average Std. Dev. Std. ErrorPrices from most brands lower 85 2.75 1.362 .148than other storesPrices from most brands not 20 2.80 1.576 .352lower than other stores

T-test df P-valueEqual Variances Assumed -.135 103 .893

The results show that for Wal-Mart that the relationship customer loyalty and prices from most brands lower than other stores has no significant relationship.

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ResultsTable 4-22Analysis of Variance Test Variable: I consider myself loyal to the storePrices from most brands lower than other stores

TargetGroups Count Average Std. Dev. Std. ErrorPrices from most brands lower 29 3.48 1.214 .225than other storesPrices from most brands not 74 3.01 1.153 .134lower than other stores

T-test df P-valueEqual Variances Assumed 1.790 49 .080

The results show that for Target that the relationship customer loyalty and prices from most brands lower than other stores has no significant relationship.

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ResultsTable 4-22Analysis of Variance Test Variable: I consider myself loyal to the storePrices from most brands lower than other stores

KrogerGroups Count Average Std. Dev. Std. ErrorPrices from most brands lower 12 3.58 1.311 .379than other storesPrices from most brands not 25 3.04 1.241 .248lower than other stores

T-test df P-valueEqual Variances Assumed 1.20 21 .244

The results show that for Kroger that the relationship customer loyalty and prices from most brands lower than other stores has no significant relationship.

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Accepted Hypotheses

Wal-Mart Target Kroger

H2a: Accept Reject Accept

H02a: Reject Accept Reject

H2a: There is no positive/negative relationship between marketing spend and customer loyalty.

.

H02a: There is a positive/negative relationship between marketing spend and customer loyalty.

Based on this analysis the null hypotheses can be accepted that Wal-Mart and Kroger that there are no positive/negative relationship between marketing spend and customer loyalty. Target we accept the alternative hypothesis.

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Results• Evaluation of hypothesis H3• This hypothesis is related to efficiency of inventory

management systems• Retailers reduces the cost of inventory to improve customer satisfaction. • Some of the benefits of marketing spends are:

» Extensive variety products/services in the store» Various brands of each product available in store» Good selection of products always present» Products sold are of the highest quality

• The null and alternate hypotheses are noted below:

• H3: The efficiency of inventory management systems does not reduce retailer’s cost to improve customer satisfaction.

• H3: The efficiency of inventory management systems reduces retailer’s cost to improve customer satisfaction.

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ResultsTable 4-26Analysis of Variance Test Variable: Overall satisfaction with this storeExtensive variety products/services in the store

Wal-MartGroups Count Average Std. Dev. Std. ErrorExtensive variety products/services 63 3.67 .950 .120in the store Extensive variety products/services 42 3.21 1.180 .182in the store not reasonable

T-test df P-valueEqual Variances Assumed 2.167 103 .033

It can be inferred that for Wal-Mart store at 95% Confidence Level Customer Satisfaction is associated with extensive variety products/services in the store.

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ResultsTable 4-26Analysis of Variance Test Variable: Overall satisfaction with this storeExtensive variety products/services in the store

TargetGroups Count Average Std. Dev. Std. ErrorExtensive variety products/services 51 4.10 .944 .132in the store Extensive variety products/services 52 3.65 1.046 .145in the store not reasonable

T-test df P-valueEqual Variances Assumed 2.264 100 .026

It can be inferred that for Target store at 95% Confidence Level Customer Satisfaction is associated with extensive variety products/services in the store.

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ResultsTable 4-26Analysis of Variance Test Variable: Overall satisfaction with this storeExtensive variety products/services in the store

KrogerGroups Count Average Std. Dev. Std. ErrorExtensive variety products/services 14 4.29 .914 .244in the store Extensive variety products/services 22 3.64 .848 .181in the store

T-test df P-valueEqual Variances Assumed 2.137 26 .042

It can be inferred that for Kroger store at 95% Confidence Level Customer Satisfaction is associated with extensive variety products/services in the store.

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Accepted Hypotheses

Wal-Mart Target Kroger

H3: Reject Reject Reject

H03: Accept Accept Accept

H3: The efficiency of inventory management systems does not reduce retailer’s cost to improve customer satisfaction.

H03: The efficiency of inventory management systems reduce retailer’s cost to improve customer satisfaction.

Based on this analysis the null hypotheses can be accepted that the efficiency of inventory management systems reduces retailer’s cost which may improve customer satisfaction

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Accepted Hypotheses

• The results are summarized here

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Accepted Hypotheses

Wal-Mart Target Kroger

H1: Reject Reject Reject

H01: Accept Accept Accept

H1: There is no positive/negative relationship between technology processes and customer satisfaction.

H01: There is a positive/negative relationship between technology processes and customer satisfaction.

Based on this analysis the null hypothesis can be accepted that there is a positive/negative relationship between technology processes and customer satisfaction

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Accepted Hypotheses

Wal-Mart Target Kroger

H1a: Accept Accept Accept

H01a: Reject Reject Reject

H1a: There is no positive/negative relationship between technology and customer loyalty.

H01a: There is a positive/negative relationship between technology and customer loyalty.

Based on this analysis the alternate hypothesis can be accepted that there is no positive/negative relationship between technology and customer loyalty

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Accepted Hypotheses

Wal-Mart Target Kroger

H2: Reject Reject Reject

H02: Accept Accept Accept

H2: There is no positive/negative relationship between marketing spend and customer satisfaction.

.

H02: There is a positive/negative relationship between marketing spend and customer satisfaction.

Based on this analysis the null hypotheses can be accepted that there is a positive/negative relationship between marketing spend and customer satisfaction

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Accepted Hypotheses

Wal-Mart Target Kroger

H2a: Accept Reject Accept

H02a: Reject Accept Reject

H2a: There is no positive/negative relationship between marketing spend and customer loyalty.

.

H02a: There is a positive/negative relationship between marketing spend and customer loyalty.

Based on this analysis the null hypotheses can be accepted that Wal-Mart and Kroger that there are no positive/negative relationship between marketing spend and customer loyalty. Target we accept the alternative hypothesis.

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Accepted Hypotheses

Wal-Mart Target Kroger

H3: Reject Reject Reject

H03: Accept Accept Accept

H3: The efficiency of inventory management systems does not reduce retailer’s cost to improve customer satisfaction.

H03: The efficiency of inventory management systems reduce retailer’s cost to improve customer satisfaction.

Based on this analysis the null hypotheses can be accepted that the efficiency of inventory management systems reduces retailer’s cost which may improve customer satisfaction

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ConclusionsThe results shows that marketing, technology, & inventory

management systems affects customer satisfaction and customer loyalty. It affects customer satisfaction more so than customer loyalty.

The findings of this study indicates that retail stores can increase customer satisfaction and customer loyalty by allocating resources to marketing, technology, and inventory initiatives.

It is recommended to spend more on marketing and effectively deploying technology and reducing inventory cost.

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Limitations/Delimitations

• Limitation in this study is related to the online method of data collection versus personal interviews or surveys by mail. This methodology does not allow for probing as compared to personal interview method and may deter some respondents who are not familiar with online surveys.

• The delimitation also limits the research study to the marketing, technology, and inventory management systems as they relates to customer satisfaction and customer loyalty as opposed to employee involvement, brand identify, checkout times, customer service, and store neatness. The delimitation only focuses on how these independent variables relate to the dependent variable.

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RecommendationsRetail store chains should evaluate cost

effective initiatives that will help improve customer satisfaction and customer loyalty.

Retail store chains should evaluate how marketing, technology, and inventory management systems improves relationship with consumers.

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Future Study

• Researchers may consider obtaining the actual marketing spend to relate to customer satisfaction and customer loyalty.

• Researchers may consider tracking inventory movement: brand versus non-brand products and how they relate to customer satisfaction and customer loyalty.

• Research may consider regional understanding of the relationship between these variables.

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Questions

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ReferencesBetancourt, R. R., Cortinas, M., Elorz, M., & Mugica, J. M. (2007). The

demand for and the supply of distribution services: A basis for the analysis of customer satisfaction in retailing. Quant Market Econ, 5, 293-312. Retrieved January 14, 2010, from EBSCOhost database.

Bowden, J. L. (2009). The process of customer engagement: A conceptual framework. Journal of Marketing Theory and Practice, 17(1), 63-74. Retrieved February 2, 2010, from EBSCOhost database.

Simon, D. H., Gomez, M. I., McLaughlin, E. W., & Wittink, D. R. (2009). Employee attitudes, customer satisfaction, and sales performance: Assessing the linkages in US grocery stores. 30, 27-41. Retrieved December 3, 2009, from EBSCOhost database.

Pleshko, L. P. & Baqer, S. M. (2008). A path analysis study of the relationships among consumer satisfaction, loyalty, and market share in retail services. Academy of Marketing Studies Journal, 12(2), 111-127. Retrieved October 4, 2009, from EBSCOhost database.

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