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The Relationship between Loyalty Schemes and Purchase Behaviour in the British Retail Industry: A Moderating Effect of Consumer Intention on the Provision of Personal Data

Chapter 1: Introduction

1.1. Problem Statement and Literature Gaps

The recent developments in the area of online marketing have provided companies with considerable opportunities for targeting the most attractive consumer groups in a highly effective way (Jai & King, 2016, 296). The Internet of Things (IoT) has created a network of connected devices and personal computers, allowing consumers to get fast access to the required goods and services. However, this coin has two sides as consumers have to provide business entities with their personal data, which is usually sensitive and should be securely stored (Mantelero, 2016, 238). Loyalty schemes, which offer consumers who frequently make purchases certain incentives, are among the marketing instruments that take advantage of the recent technological progress (Meyer-Waarden, 2015, 22).

Loyalty schemes allow marketers to easily assess their customers’ purchase behaviour and offer them the goods and services that are tailored to their current needs (Bruneau, Swaen & Zidda, 2018, 144). Thus, having access to personal information is crucial to establish and maintain effective customer relationships. However, the recent changes in the legislative framework in the European Union (EU) and the growing public concern over personal data privacy pose a certain challenge to organisations’ ability to extensively use their customers’ and clients’ personal data for marketing purposes (Gupta, Gupta & Shainesh, 2018, 196). Nonetheless, the existing literature, which explains how personal data concerns influence consumers’ purchase behaviour and their attitudes towards loyalty schemes, is still fragmented and insufficient (Giampietri, Verneau, Del Giudice, Carfora & Finco, 2018, 160). This project attempts to bridge this gap by exploring the moderating role of consumers’ intention to provide personal data in the relationship between loyalty schemes and purchase behaviour.

1.2. Topic Background

Loyalty programmes stimulate consumers’ purchase behaviour and contribute to their decision to buy (Sangroya & Nayak, 2017, 393). There is ample empirical evidence suggesting that consumers tend to perceive loyalty schemes to add value to the quality of customer service (Stathopoulou & Balabanis, 2016, 5801). This value usually translates into higher levels of brand loyalty and repeat purchases as consumers benefit from such incentives as discounted prices, gifts, and free offerings (Mantelero, 2016, 238). Nevertheless, loyalty programmes do not necessarily build attitudinal loyalty towards the company brand, which poses a certain challenge to marketers as the lack of brand loyalty can make consumers to switch to competitors (Jai & King, 2016, 296). The significance of this problem is especially deep in the context of the retail industry where switching costs are extremely low and organisations have to compete on other bases rather than price (Bruneau et al., 2018, 144).

The problem of poor brand loyalty is further exacerbated by the recent changes in privacy regulations in the EU (Miglicco, 2018, 9). The implementation of the EU General Data Protection Regulation (GDPR) aims to completely reshape the way in which organisations handle and process consumers’ personal data (Romanou, 2018, 99). Given the growing public concern over personal data privacy and the most recent trends towards less public disclosure of personal data, the retail market landscape is about to undergo a serious change (Yeh, 2018, 282). While cookies and other social marketing tools allow consumers to control what data to provide and how it could be treated by the company, loyalty schemes keep this information in the background (Romanou, 2018, 99). Data breaches, sale of personal data to third parties, and the lack of security measures can discourage consumers from sharing their personal data with retailers via loyalty cards and schemes (Li, 2018, 171; Mikhed & Vogan, 2018, 192).

1.3. Reasons to Undertake the Study

Drawing on the provided background, the current body of knowledge about the relationship between loyalty programmes and schemes and consumer purchase behaviour should be further developed in the light of recent changes in the European legislative framework and shifting public attitudes towards the issue of personal data privacy (Jai & King, 2016, 296). The retail industry can potentially bear significant financial losses because of these changes, which partly explains the selection of this topic for this doctoral thesis. Given the intensity of the retail industry, its competitiveness, and saturation degree, retailers put a heavy emphasis on their loyalty programmes as a means of targeting and generating profits (Dolsak, Hrovatin & Zoric, 2019, 246). However, the unwillingness to share personal data can become a barrier to retailers’ competitiveness and financial sustainability (Gupta et al., 2018, 196). This project contributes to the understanding of how shifting consumer attitudes and perceptions can reshape the retail landscape and force retailers modify their current marketing strategy to remain competitive.

1.4. Aims and Objectives

Using the planned behaviour theory and the social contract theory, this study examines how consumers’ intention to provide personal data moderates the impact of loyalty schemes on their purchase behaviour in the British retail industry. This aim requires the achievement of the following objectives:

  1. To examine the factors affecting consumer purchase behaviour in the online environment.
  2. To explore the main reasons behind consumers’ decision to engage in online information exchange.
  3. To assess the impact of loyalty programmes on consumer purchase behaviour in the context of the British retail industry.
  4. To identify the moderating role of consumers’ intention to provide personal data in the relationship between loyalty schemes and purchase behaviour.
  5. To recommend how British retailers could modify their customers’ purchase behaviour in the light of the recent changes in the legislative framework in the EU.

1.5. Applied Research Methods

This project involves primary data collection as it is the best way to assess consumer attitudes, preferences, and perceptions of personal data privacy issues. In addition, primary data allows for measuring the extent to which consumers are loyal to a certain store or brand (Creswell & Creswell, 2017, 163; Saunders, Lewis & Thornhill, 2015, 144). To obtain the required amount of personal data in a cost-effective manner, the researcher employed self-administered questionnaires distributed among British consumers via social media. In total, 224 customers of the largest UK-based grocery and general merchandise retailers such as Sainsbury’s and Tesco participated in the questionnaire survey. All statistical and graphical analyses were performed in SPSS and Excel (Chawla & Sodhi, 2011, 142).


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Chawla, D. & Sodhi, N. (2011). Research Methodology: Concepts and Cases. New Delhi: Vicas Publishing House.

Creswell, J. & Creswell, D. (2017). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 5th ed., London: SAGE.

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Meyer-Waarden, L. (2015). “Effects of loyalty program rewards on store loyalty”. Journal of Retailing and Consumer Services, 24(1), 22-32.

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Mikhed, V. & Vogan, M. (2018). “How data breaches affect consumer credit”. Journal of Banking & Finance, 88(1), 192-207.

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Sangroya, D. & Nayak, J. (2017). “Factors influencing buying behaviour of green energy consumer”. Journal of Cleaner Production, 151(1), 393-405.

Saunders, M., Lewis, P. & Thornhill, A. (2015). Research methods for business students. 7th ed., London: Prentice Hall.

Stathopoulou, A. & Balabanis, G. (2016). “The effects of loyalty programs on customer satisfaction, trust, and loyalty toward high-and low-end fashion retailers”. Journal of Business Research, 69(12), 5801-5808.

Yeh, C. (2018). “Pursuing consumer empowerment in the age of big data: A comprehensive regulatory framework for data brokers”. Telecommunications Policy, 42(4), 282-292.

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