Making Tracks: Loyalty Cards As Consumer Surveillance

ABSTRACT - We investigate ethical and privacy issues concerning the use by retailers of loyalty card (club-card) transaction records. To investigate these issues we use one individual record for our case study (selected from a random sample of two-year purchase records of 254 cardholders from a major UK retail loyalty scheme). The individual selected has the greatest number of transactions, and therefore more data to interpret/reveal than others in the sample. This data record is interpreted to develop a 'picture’ of an individual. The direction and extent of our interpretation raises ethical and privacy issues. Such issues are becoming increasingly important given loyalty scheme, technology, competition and surveillance developments.



Citation:

Andrew Smith and Leigh Sparks (2003) ,"Making Tracks: Loyalty Cards As Consumer Surveillance", in E - European Advances in Consumer Research Volume 6, eds. Darach Turley and Stephen Brown, Provo, UT : Association for Consumer Research, Pages: 368-373.

European Advances in Consumer Research Volume 6, 2003      Pages 368-373

MAKING TRACKS: LOYALTY CARDS AS CONSUMER SURVEILLANCE

Andrew Smith, University of Nottingham, UK

Leigh Sparks, University of Stirling, UK

ABSTRACT -

We investigate ethical and privacy issues concerning the use by retailers of loyalty card (club-card) transaction records. To investigate these issues we use one individual record for our case study (selected from a random sample of two-year purchase records of 254 cardholders from a major UK retail loyalty scheme). The individual selected has the greatest number of transactions, and therefore more data to interpret/reveal than others in the sample. This data record is interpreted to develop a 'picture’ of an individual. The direction and extent of our interpretation raises ethical and privacy issues. Such issues are becoming increasingly important given loyalty scheme, technology, competition and surveillance developments.

INTRODUCTION

Foucault, Marx and Weber all predicted that surveillance would increasingly pervade society as technology developed (see Lyon 1993). The retail environment is no exception; shoppers are watched and studied in a number of ways and purchases are recorded and analysed. Loyalty cards provide unique opportunities to track an individual. On the basis of the information consumers provide and leave behind, retailers (and others) refine their understanding of shopping behavior. Products are developed to meet emerging needs. Retailers stock shops according to local demand patterns. Products are placed in known associations to encourage purchase. Switching patterns are encouraged and discouraged in the battle for market share. Reactions to layouts, fixtures, facilities and services result in re-designs and changes. Evans (1999) argues that this is a function of our increasing reliance on multiple retailers who are not 'grounded’ in local neighbourhoods i.e. we are more alienated or distant from retailers than we were in the past. Whilst general observation of consumers is helpful to retailers, the development of loyalty schemes and associated technology and software has transformed basic market research into an ongoing consumer surveillance system.

The aim of this paper is to investigate some of the ethical and privacy implications of this collection and potential use of individual-level loyalty card data. Previous papers on this issue have tended to focus at an aggregate level (e.g. Evans 1999), be theoretical or perceptual or be based on observations of and interactions with consumers (Sayre and Horne 2000). Here however we investigate these issues by examining and interpreting an individual’s behavior/record. We have a sample of 254 cardholders from one retailer’s loyalty card, providing a two-year record of purchase. From this we have selected one individual. Her record identifies her 1551 purchase transactions over this two year period and is the largest (i.e. most transactions) record in the data set. We introduce her here as 'Brenda’Baka 'The Big Spender’.

LOYALTY SCHEMES AND CONSUMER PRIVACY

Loyalty schemes always offer some kind of 'reward’ or incentive to the customer. They are in essence forms of operant conditioning (Sayre and Horne 2000). In most cases, the greater the degree of patronage, the greater the potential to reap the rewards offered. Beyond this common feature though, reward schemes differ greatly in terms of context, technology, delivery mechanisms and sector (Hart et al 1999). Previous research has suggested that the aims of a scheme may relate to data collection, sales promotion, more sophisticated strategic ends or any combination of these (Boussofiane 1996, Hart et al 1999). These aims might be additional to or even instead of the pursuit of customer loyalty, although there must be a large enough pool of repeat purchasers in order for the scheme to be viable. There is also a substantial debate about the effectiveness and impact of such schemes as well as the motivations and operational mechanisms by which repeat purchase and/or loyalty is engendered (eg Uncles 1994, O’Brien and Jones 1995, Conneran and Lawlor 1997, Dowling and Uncles 1997, O’Malley 1998, East et al 1998, Oliver 1999, Bolton et al 2000). However the crucial point about loyalty schemes in the context of this paper is that the consumer is, on the face of it, a willing participant, and as such may be complicit in the use of individual data and any compromise of privacy: they 'participate in their own surveillance’ (Lyon 2001:44). Indeed, consumers give up considerable data on application to join such schemes. This is very different for example to the privacy and ethical issues raised by video surveillance in shops (see Kirkup and Carrigan 2000), where acquiescence is implicit on entry to the store (normally through a small window sign indicating surveillance is operational for security reasons).

Privacy is a much debated construct and is subject to very different interpretations. As Nowak and Phelps (1995: 48) note: "To some "privacy" is a problematic, conceptually murky and constitutionally questionable concept". We all have some sense of what it is, but herein lies the problem. A sense of privacy is, paradoxically, a personal and singular thing. However, DeCew (1993) describes three primary types of privacy that provide a useful touchstone for this debate: i] Informational privacy ii] Expressive privacy and iii] Accessibility privacy. The first concerns our right not to have things divulged about us. The second concerns our right to be free from surveillance when making personal decisions. The third concerns physical surveillance of our public or private actions. Indeed loyalty cards and thus retailers and marketers are seen as potentially challenging all three privacy dimensions (Kirkup and Carrigan 2000).

In recent years, consumer privacy has become a greater concern due to the expansion of direct and database marketing, the Internet and surveillance and data capture techniques (eg Horne and Horne 1997, O’Malley et al 1999, Christy and Mitchell 1999). Phelps et al (2000) demonstrate how individual concerns vary, but can be ameliorated through disclosure and data management principles. Legal aspects of data protection remain vital (see http://www.dataprotection.gov.uk/ for example), but are variable amongst countries. Privacy issues might be expected to arise in loyalty schemes. The numbers of consumers signing up for loyalty schemes however would tend to suggest that privacy concerns are not a very powerful disincentive, compared with perceived benefits, or alternatively that consumers are in denial. Previous research has questioned the ethical basis of such data collection (Evans 1999) and provided evidence that consumers do have 'underlying’ privacy concerns (Long et al 1999, Sayre and Horne 2000). Recent work has suggested that consumers are often quite ignorant of how loyalty card data are used (Graeff and Harmon 2002), and this may help explain their willingness to sign up for such schemes.

In any retailer loyalty scheme there are at least three sources of data. First, consumers provide data on application to join the scheme. Secondly, retailers link these personal data with internal and external databases e.g. geodemographic and lifestyle data. Thirdly, transaction data from purchasing in store becomes available on a regular basis. Of these, only the first is obviously 'visible’ to consumers and it may be these data that they believe retailers’ hold and use. The more sophisticated components of loyalty scheme utilization may be less than apparent to most consumers. Even transaction data may be mis-understood with a view that the 'card’ is used to allocate points rather than to identify an individual (though this view may alter with Internet grocery shopping and dynamic shopping list development systems). O’Malley et al (1999) point to privacy problems in the fusion of these streams of data, whilst the potential to develop 'biographies of consumption’ through the combination of transactional and personal data has been raised by Evans (1998). This variation and potential integration amongst data types also questions the supposition that by signing up consumers are sanctioning all possible uses of the data.

METHODOLOGY

Here we adopt what is essentially a case study approach. To this end this paper focuses on an individual loyalty record to raise issues of ethics and privacy and to explore some of the points discussed above. We accept that it is only a fragment of the subject’s consumption life (and life in general), however it is a potentially revealing fragment. There are relatively few examples of single consumer case studies in the academic literature. Analyses of small cohorts are more common and are more often than not based within the interpretive tradition (e.g. Ritson et al, 1992, Mick et al, 1992). An important premise upon which our methodology is based is that the ethical and privacy issues of loyalty card data are best demonstrated, in the first instance, through the discussion of an individual case; 'Brenda’ is a device. [It is feasible that connectionist mathematical techniques could be used to attempt similar analysis of multiple records in order to establish generalizable >rules= of behavior, bases for segmentation (Boone and Roehm, 2002) or impacts of actions, but this is not the objective of this paper.]

Brenda was selected from a random sample of 254 loyalty card purchase records obtained from a national retail chain operating a loyalty card scheme in the UK. Women customers account for the vast majority of loyalty scheme members or this retailer. The retailer, to satisfy data regulations, anonymised this data set and removed personal identifiers or descriptors. The data set comprised the loyalty card records of 254 single women, aged 18-35, for a 104 week period (running from September 1998 to September 2000). In total there are 46797 product purchase transactions in the data set. The records were drawn from the corporate database using random sampling and are not restricted to one store or one region of the United Kingdom. The retailer is one of the UK’s leading retailers. The retail component of the group is engaged in the retailing of general merchandise with an emphasis on health and beauty and in the provision of services. The retailer trades particularly in cosmetics, snack food, medicines, toiletries and grooming products, household items and small gifts. It has over 1400 retail shops across the UK and achieves sales of c,4bn per annum. The stores are primarily high street locations, which attract a considerable proportion of the UK’s population each week. The loyalty scheme is long established, has almost 14 million cardholders and is used on over 50% of all sales (source: company annual report).

The data set consists of eight variables and details all purchases made with the retailer when the loyalty card was used. The loyalty card number and the date of transaction are identified on each case. A transaction number is also recorded which links products purchased at the same time (i.e. till visit). The volume of any individual item purchased is available (eg two bars of chocolate) as is the total spend on that item at that transaction. Each case also has an item descriptor and a product merchandise group allocated by the company. Finally, the points adjustment per transaction for the loyalty card scheme for each till visit is also available (including any redemptions). [In order to take out a loyalty card, an application form has to be completed. For this retailer it contains questions on standard personal details (name, address, postcode etc). It also requires data on the number of people in the family living at that address, occupation type, date of birth, dates of birth of any children and estimated completion date of any current pregnancy. In addition data are collected on the wearing of spectacles and contact lenses and the date of the last eye examination. We, unlike the retailer, do not have access to these data.]

There are many questions that could be explored via this data set as a whole (i.e. all 254 records). In examining basic descriptive statistics of the data however, variation was immediately noticeable. For example, the number of product purchase transactions made by any individual over the time period varied from a low of 2 to a high of 1551. Brenda was 'created’ both because she had the highest total number of product purchase transactions and because she accounted for the greatest percentage of spend in the categories of good (snack food) which itself accounted for the greatest percentage of transactions in the data set as a whole. Her transaction record is the most extensive in our sample. It is thus the most suitable for our case study approach to the data and privacy issues, as the more Brenda shops, the more the retailer knows about her.

A PICTURE OF 'BRENDA’

The data set allows us to track purchase when she uses her card; and from the sheer volume of recorded transactions it is reasonable to conclude that she uses the card the vast majority of the time. We therefore know when Brenda visits the retailer and purchases goods and can draw conclusions about her shopping behavior, her life in general and potentially aspects of her personality. We can try to develop a 'biography of consumption’ (Evans 1998). Over the two-year period, Brenda uses the card on 243 different days and spends ,2263.25. She undertakes 1551 product purchase transactions, resulting in 1667 items being purchased. Her mean spend per visit is ,9.31. This is subject to wide variation (standard deviation 9.6), with the minimum spend per visit being ,0.81 and the maximum ,54.03. The average price of an item purchased is ,1.36. Only eleven items are purchased at an item price of over ,10. Of these eleven, 7 are branded products and 4 are retailer brands. This is inverse to her overall product purchase pattern where 77% of products purchased are retailer brand, although they represent only 58.5% of sales value. Two of the top four most expensive products purchased are 'bought’ using loyalty points redemption.

Brenda’s days visited per week are highly variable, with on average a slight tendency to visit more often than once or twice a week. However for substantial numbers of weeks she uses the retailer either four or five times a week. On the surface these figures show she is retailer (and probably store) loyal. Figure 1 shows however that Brenda’s two year period contains at least two 'stages’ of behavior. This change in behavior appears to begin around week 43 (July 1999). Week 42 is the last 'four or more visit’ week for a long time and represents a change in the behavior pattern. Figure 1 also hints at a new pattern being established around week 94. Before week 43, Brenda has on average 3.7 visits a week and spends ,27.27 on average per week (average spend per visit of ,0.74). After week 42 the comparative figures are 1.4 visits and ,17.07 (with an average spend per visit of ,1.22). This is clearly a major shift in behavior in the visit (repeat purchase) pattern. Why does it happen? Does she move job/house, is she pregnant/a mother, or having to care for someone? Has the local competition changed?

FIGURE 1

VISITS PER WEEK

TABLE 1

A TYPICAL LUNCH?

The daily pattern of store visits in weeks 1-42 could indicate association with work (possibly lunchtime visits to the store). Many of the weeks contain Monday to Friday visits only and there is little evidence of weekend visiting (at least initially). The only examples of Sunday shopping in these first 42 weeks are associated with the run-up to Christmas. After Christmas 2000 however Sunday shopping becomes relatively more common, although still only seven times in nine months. Perhaps Brenda is/was religious or perhaps she has other commitments or better things to do on a Sunday? The change in pattern is again suggestive of a major shift in situation and/or lifestyle.

The data show what Brenda is buying at the merchandise group and individual product levels. It is clear from the number of products that her most common purchases are savoury and sandwich items together with soft drinks and chocolate (countlines). By value however, most money is spent on beauty aids and cosmetics, although the food items, through their regularity, again come high up. By item count, retailer brand products appear to dominate, whereas by value of spend, manufacturer (proprietary) branded products are more prevalent. An example of a typical week 1-42 shopping trip is given in Table I. A sandwich (or often flatbread) and a drink are the core purchases, but these are supplemented with various savoury snacks and chocolate bars. Retailer brand products dominate this visit. To some minds this may not be the most obviously healthy diet, despite the fact that many of these purchases are reduced calorie or low fat 'healthy’ items. The combination of this with the savoury items, chocolate and snacks is curious however. The sheer volume of these in the overall record is remarkable. Can we conclude that Brenda is a greedy and indulgent individual or could she be buying for others? Is Brenda happy with this consumption pattern? Perhaps, given the volume of healthy eating and diet products, she could be targeted for offers relating to weight management products. Would she welcome this or is this intrusive/unethical?

We would suspect that Brenda is retailer (and probably store) loyal, despite the shift in behaviour pattern. We can also consider brand and product loyalty. The prevalence of retailer brands has already been noted. They comprise 77% of the volume of purchases and 58.5% of the value. Proprietary products are bought in the more expensive categories generally. Does this make Brenda an astute value seeker or is it a function of her income? Or is she simply tight-fisted!

Brenda purchases a lot of broad health and beauty products and appears to take care of her appearance. She wears contact lenses not glasses, but does return to glasses for occasional use (glass cleaning cloths are purchased). She is a regular purchaser of lipstick (often shades of red) and a considerable user of lip salve, possibly in an effort to ward off cold sores (Blisteze). She purchases a lot of nail varnish and handwashes and spends a regular amount on hair care. She probably has long hair, as attested by hair grips, pony tail clasp etc. She could suffer from poor circulation if the hot water bottle purchased in April is symptomatic. From June 1999 onwards (week 42!) she has problems with her feet and there are regular purchases of insoles, foot deodorants, corn plasters and other Scholl products. She suffers from hay fever. When she gets a cough or cold (approximately once a year) she takes several weeks to shake it off. She occasionally buys vitamin pills. Brenda also resorts to instant tan products despite (or because of) taking holidays. As a loyal customer and big spender with this retailer, Brenda gains substantial reward points on her loyalty card. She redeems these points on 5 occasions, saving her ,105.72 (an approximate return of 4.5%). The first four points redemptions are effectively special purpose purchases. The first is aftershave, bought in December, presumably as a gift for Christmas. The fourth redemption is another pre-Christmas purchase on a beauty aid, again possibly as a gift. Holidays would seem to be the theme of redemptions two and five. Both occur at the same time of the year and involve suncare products. The third redemption is far more mundane. It is unclear why this redemption is so different to the others. Is it fair to conclude vanity is a trait and that appearance (of herself and others) is very important to Brenda? Brenda however appears to suffer from spots and/or bad complexion, as attested by a high spend on blemish concealer and the occasional purchase of Clearasil. This might be related to her purchase and presumed intake of chocolate and fizzy drinks. She is a large woman judging by the size of the tights purchased. This is consistent with the size of her typical lunch and other clues in the record (she does buy a set of weighing scales during the two-year period).

Brenda appears to have a boyfriend or partner/s and occasionally buys him aftershave and deodorant, as well as (men’s) razor blades. We can only speculate as to whether Brenda is trying to tidy him up or he has asked her to buy these things. Perhaps it is Brenda’s nature to be highly planned and organised and this includes for her partner (in October 1999 she buys an organiser but whether this is for her or is a gift we do not know). She clearly plans Christmas well in advance (cards for her parents/family in October) and the same is true of holidays. In the latter case she buys after-sun and sun lotion a few weeks in advance (we can tell when she is away because of the two week gap in the record). The purchase of a pack of nappies in May 2000 comes out of the blue and is an isolated occurrence. Is this for her own baby’s use or a favour or gift for a friend? Is this in any way related to the change in purchase behavior pattern almost a year before i.e. pregnancy? She does not purchase birth control or sanitary protection products during the two years. Some other subjects in the sample do provide records containing purchases of such products however as well as pregnancy testing kits and various medication.

This catalogue of fact and interpretation has been developed here to illustrate what a retailer interested in one of their most loyal customers could ascertain from their transaction data. Combine this with the other possible types of linked data and the potential to understand individuals in detail is clear. These transaction data represent the dynamic footprints of consumers over time and space. Tracking individual consumers is clearly possible and potentially profitable. Is it however ethical or acceptable?

DISCUSSION AND CONCLUSION

Clearly some of our more speculative interpretations of the data are somewhat mischievous. Some might feel that they are cruel or prurient. However, they have been developed to illustrate a point. Retailers can choose to draw conclusions from the raw data, which could be questionable, in factual and ethical terms. From a managerial perspective, individual level data raises important questions. As we have shown, various conclusions about Brenda’s lifestyle, health and priorities can be extrapolated from the data. The products she buys say a lot about her. Retailers are party to sensitive information. Some information is societally sensitive. Some is personally sensitive e.g. whether we have suffered from an embarrassing ailment inferred from medical purchases. Clearly the retailer can use such sensitive criteria to segment and target. However this raises various ethical considerations for retailers (and consumers, see below). This retailer could create and target a segment of apparently highly sexually active (very frequent condom buyers) or apparently vain individuals (i.e. high level consumers of particular cosmetics). The group targeting possibilities are, from a managerial point of view, endless and exciting (whatever the ethical implications might be).

However, with 14 million cardholders, whilst segments and groups are an obvious dimension of data use, individual level analysis is also possible. The management issue is whether or not it is rewarding to the retailer. The costs of systems development and the involvement needed to focus on the individual perhaps mitigate against analysis or interpretations such as we have developed here. Retailers might claim that individual level data is not of much use to them as ultimately group behavior is more valuable and actionable. Others may not be so sanguine or relaxed about personal data. Perhaps consumers are protected by the safety of numbers, although through technology the "anonymity of the masses" is no longer certain (Christy and Mitchell 1999). Understanding broad trends and placing consumers in relation to these is commercially important. However knowing what the 'best’ customers are doing and what individuals do buy must be at the heart of any true loyalty scheme, as the scheme links individuals to the retailer. With the recent interest in the expansion of ethnographic and individualized marketing research in consumer behavior, retailers may be further advantaged in terms of their existing data resources.

One could argue that loyalty schemes are ultimately in the consumers interests as they allow the retailer to target offers and inform the retailer about how best to satisfy the consumer. Indeed there is some evidence that some consumers appreciate this (Evans et al 2001). Whilst this might be the case, other more sinister actions can be conceived with these data (Christy and Mitchell 1999). For example, we could see a retailer seeking to exclude non-profitable customers from schemes, offers or stores and doing this on the basis of income, spend or simply postcode. Infrequent or low-spending customers might be charged higher prices. Other product purchases or associations might raise security issues or questions about parenthood and paternity. Addiction to non-prescription medication or high levels of alcohol consumption could be identified and used supposedly 'on behalf of’ or even against the consumer. The retailer could also sell on these data to other external businesses. Are such things flights of fancy or real dangers? Legal protection here is potentially murky.

Within the business, the retailer will merge transactional data sets with other internal and externally purchased data. In our case, the retailer has Brenda’s personal data from her application form and will have linked this to other external lifestyle, geodemographic and possibly personal data bases. They, unlike us, can link the ongoing transactional data with these other data sources. The emergence of super-loyalty schemes in the UK (e.g. Nectar), that collect transactional data across a number of competing but co-operating retailers, can only serve to exaggerate these concerns, and enhance the 'picture’ or 'life biographies’ that retailers have of their customers.

These are issues of just how right it is for retailers to act on some of the data that they are able to collect or infer. Fundamentally it remains obscure as to what the retailers’ responsibilities are towards the cardholder (beyond the basic legal obligations). Does the obtaining o initial consent absolve the data collector from further responsibility over data use or ongoing collection? If the business expands into new product categories eg alcohol, is consent still valid? For consumers as well however, ethical questions are apparent. Consumers in the UK appear to be highly unaware of the level and volume of data held on them and the potential interpretations of their lives that can be made. Consumers generally have a right to see the personal data that companies keep on them. The position with loyalty cards is unclear. The personal data that a retailer collects from an application form for a loyalty card have to be revealed. The consumer knowingly supplies these. However transaction data are not necessarily available, nor are data on the meaning of classifications or interpretations of individual patterns of behavior. Should consumers be more concerned about what is held and how is it used? We all live our lives under various gazes. If we wish to avoid all surveillance then we have to take extraordinary steps. However, consumers often seem willing to allow retailers to mark and follow their tracks, mainly for very little by way of return. Is this because they have nothing to fear or is it because of a lack of knowledge of what they should fear, or are they in denial, blinded by the perceived benefits of being in the scheme? If privacy is 'problematic, murky and questionable’ is this because we, as consumers, fail to care enough about the possible implications of this loss of privacy?

REFERENCES

Bolton R.N. Kannan P.K. and Bramlett M.D (2000). Implications of loyalty program membership and service experiences for customer retention and value. Journal of the Academy of Marketing Science; 28, 1: 95-108.

Boone D.S. and Roehm M. (2002). Retail segmentation using artificial neural networks. International Journal of Research in Marketing; 19: 287-301.

Boussofiane S. (1996). Exploiting data analysis in customer loyalty. Journal of Targeting, Measurement and Analysis for Marketing; 5, 1: 11-19.

Christy R. and Mitchell S. (1999). Direct Marketing and Privacy. Journal of Targeting, Measurement and Analysis for Marketing; 8,1: 8-20.

Conneran E. and Lawlor K. (1997). Consumer perceptions of the Superclub loyalty scheme and its influence on the store choice decision. Journal of Targeting, Measurement and Analysis for Marketing; 53: 210-220.

DeCew J. (1997). In Pursuit of Privacy: Law, Ethics and the Rise of Technology. Ithaca, NY: Cornell University Press.

Dowling G. R. and Uncles M. (1997) Do customer loyalty programs really work? Sloan Management Review; 38, 4: 71-82.

East R. Hogg A. and Lomax W. (1998). The Future of Retail Loyalty Schemes. Journal of Targeting, Measurement and Analysis for Marketing; 7,1: 11-21.

Evans M. (1998). From 1086 and 1984: direct marketing into the millennium. Marketing Intelligence and Planning; 16, 1: 56-67.

Evans M. (1999) Food retailing loyalty schemes and the Orwellian Millennium. British Food Journal; 101, 2:132-147.

Evans M. Paterson M and O’Malley L. (2001). The direct marketing-direct consumer gap: qualitative insights. Qualitative Market Research: an international journal; 4, 1: 17-24.

Graeff T. and Harmon S. (2002) Collecting and using personal data: consumers’ awareness and concerns. Journal of Consumer Marketing; 19, 4: 302-318.

Horne D.R. and Horne D.A. (1997). Privacy: a paranoid’s view. Advances in Consumer Research; 24: 351-354.

Hart S. Smith A. SparksL. and Tzokas N. (1999). Are loyalty schemes a manifestation of relationship marketing? Journal of Marketing Management; 15: 541-562.

Kirkup M. and Carrigan C. (2000). Video Surveillance Research in Retailing; ethical issues. International Journal of Retail and Distribution Management; 28, 11: 470-480.

Long G. Hogg M. Hartley M. and Angold S. (1999). Relationship marketing and privacy: exploring the thresholds. Journal of Marketing Practice: Applied Marketing Science; 5, 1: 4-20.

Lyon D. (1993). A Electronic Panopticon? A Sociological Critique of Surveillance Theory. Sociological Review; 41, 4: 653-679.

Lyon D. (2001). Surveillance Society: Monitoring everyday life. Open University Press. Buckingham.

Mick D.G. DeMoss M. and Faber R.J. (1992). A Projective Study of Motivations and Meanings of Self-Gifts: Implications for Retail Management. Journal of Retailing; 68: 122-145.

Nowak G.J. and Phelps J. (1995). Direct marketing and the use of individual-level consumer information: determining how and when "privacy" matters. Journal of Direct Marketing; 9, 3: 46-60.

O’Brien L. and Jones C. (1995). Do Rewards Really Create Loyalty? Harvard Business Review; 73, 3: 75-82.

O’Malley L. (1998) Can loyalty schemes really build loyalty? Marketing Intelligence and Planning; 16, 1: 47-55.

O’Malley L. Patterson M. and Evans M. (1999). Data Fusion and Data Control: privacy problemsBand solutions? Journal of Targeting, Measurement and Analysis for Marketing; 7, 3: 288-302.

Oliver R.L. (1999). Whence consumer loyalty. Journal of Marketing; 63: 33-44.

Phelps J. Nowak G.J. and Ferrell E. (2000). Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy and Marketing; 19, 1: 27-41.

Ritson M. Elliott R. and Eccles S. (1996). Reframing IKEA: Commodity-Signs, Consumer Creativity and the Social/Self Dialectic. Advances in Consumer Research; 23: 127-131.

Sayre S. and Horne D. (2000). Trading Secrets for Savings: how concerned are consumers abnout club cards as a privacy threat? Advances in Consumer Research; 27: 151-155.

Uncles M. (1994). Do you or your customers need a loyalty scheme? Journal of Targeting, Measurement and Analysis for Marketing; 2: 335-349.

----------------------------------------

Authors

Andrew Smith, University of Nottingham, UK
Leigh Sparks, University of Stirling, UK



Volume

E - European Advances in Consumer Research Volume 6 | 2003



Share Proceeding

Featured papers

See More

Featured

Divorcing the Market

Deniz Atik, University of Texas Rio Grande Valley, USA
A. Fuat Fırat, University of Texas Rio Grande Valley, USA
Ebru Uzunoğlu, Izmir University of Economics

Read More

Featured

Material Gifts as Relationship Mnemonics: Why More Material Gifts Are Given Than Wanted?

Adelle Xue Yang, National University of Singapore, Singapore
Minjung Koo, Sungkyunkwan University
JAEWON HWANG, Sejong University

Read More

Featured

Communicating Limited Financial Resources Increases Perceived Trustworthiness and Interpersonal Connection

Grant E. Donnelly, Harvard Business School, USA
Anne Wilson, Harvard Business School, USA
Ashley V. Whillans, Harvard Business School, USA
Michael Norton, Harvard Business School, USA

Read More

Engage with Us

Becoming an Association for Consumer Research member is simple. Membership in ACR is relatively inexpensive, but brings significant benefits to its members.