D7.7: RFID, Profiling, and AmI

Title: SOCIAL ACCEPTANCE OF RFID IN RETAIL

Martin Meints (ICPP) 

Introduction

Since the 1980s (for example Davis 1989) intensive research was carried out to understand the factors that influence the acceptance of new technologies by the user. Originally dealing with Information Technologies (IT) in general, in the 1990s the research focused on mobile technologies and services. Target of this research was the ability to optimise products and services and to lower barriers for their acceptance from the perspective of the users. As a result the following relevant technical and social factors for technology acceptance were identified (cf. among others Spiekermann 2005): 

• Perceived usefulness influenced among others by

  • Social status of the user and his openness for new technologies 

  • Perceived fun 

  • Communicational element (interaction) 

  • Perceived personal freedom 

• Ease of use influenced among others by

  • Usability 

  • Interoperability (technical, formal and informal) 

  • The need for attention 

• Trust in the service provider influenced among others by

  • Availability and quality of the service 

  • Reputation of the service provider 

  • Perceived fairness of the price 

  • Non-intrusiveness of the service, privacy preservation and data security 

  • Perceived control over devices, services and personal data (all steps of the processing of personal data) 

Perceived Control

Günther and Spiekermann (2005) carried out a survey about RFID and its acceptance with 129 representatively chosen customers of the Metro Future Store. A film in two versions was used to show benefits and drawbacks of RFID including possibilities to handle drawbacks such as PETs*. Before and after the film was shown, the participants answered a number of questions.  

The majority of the participants in the survey understood and accepted the benefits of RFID in consumer products, such as easier operation of returns and guarantee services without the need of a receipt of purchase. They felt well informed about possible (and in this case hypothetic) PETs* for RFID systems* such as password protection or agent technology and felt that these PETs* are easy to use. Nevertheless, 73% of the users supported permanent physical disabling of RFID tags* after the purchase. This indicates that perceived control within ambient intelligent environments is more than a sub-factor of the trust in the service provider – for these types of systems it is a relevant main factor. 

Spiekermann (2005) also summarised the elements of perceived control and the link of perceived control with privacy in ubiquitous computing* environments, though in this area further research seems to be necessary. In fact, since the 1970s privacy has been defined by many authors as control, for example to access the self, the group one belongs to or personal data. Based on this understanding in their proposed technology acceptance model, Spiekermann and Rothensee (2005) understand privacy protection as an aspect of perceived control.  

Psychologists discriminate three types of control (Averill 1973): 

• Information control; information and knowledge about a system and related processes makes user feel a certain kind of control to use the known processes and the system

• Behavioural control; the knowledge that a system behaves different (and possibly reproducible different) when a user does so; the user has influence on the behaviour of the system

• Decision control (choice); the user has different options and is able to choose among them

A forth type of control developed in social science (self efficacy theory, Bandura 1989) is the ability of users to deal with new technologies. Users tend to transfer past experiences with at that time new technologies to a give situation. If they were for example successful in adopting new technologies in the past, they will likely be open for other new technologies and motivated to deal with them. 

Another factor influencing perceived control is the possession of relevant parts of complex systems. For example possession (or the lack of possession) of a communicational device can potentially influence the strength of the user’s reaction in either direction.  

The different factors of influence may result in either of two different tendencies:  

• Positive reaction, i.e. technology acceptance 

• Negative reaction, i.e. technology avoidance or stronger: opposition 

In the end these tendencies are balanced out to a resulting decision with respect to technology acceptance or avoidance/opposition by the user. 

The modified Technology Acceptance Model

Based on the results of this research, Spiekermann and Rothensee (2005) suggested a modified technology acceptance model for ambient intelligent environments. In this model the reaction of the user with respect to ambient intelligent technologies is understood as a balancing process of different tendencies. The different factors and their influences on tendencies and the resulting decision are summarised in the following figure: 

Figure : Factors for acceptance of ambient intelligent systems

Currently further research is being carried out by Spiekermann et al. ,which is focused on:  

• The relevancy of the described factors 

• The role of protection of privacy in perceived control 

Conclusion

In this chapter factors for the acceptance of ambient intelligent technologies are summarised and investigated. In comparison with established technologies such as Information Technology (IT) including mobile technologies and services, for AmI-systems the perceived control seems to be of higher importance. Perceived control in the technology acceptance model suggested by Spiekermann and Rothensee includes informational self determination and privacy.  

The proposed model describes that especially in cases where technology allows for a different design (for example in solutions based on RFID), ambient intelligent systems should foresee a sufficient control by the user to be able to enter the market successfully. System designs that do not take this into account will likely face opposition by the potential users or will be avoided.  

Currently, there seems to be not much research with respect to technology acceptance for AmI technologies, apart from the presented approach. Research carried out so far seems to deal with specific aspects of user acceptance so far, such as acceptance of profiling in AmI environments (Bohn et al., 2004) or potential social drawbacks (Friedewald, Da Costa, 2003). From this perspective the presented research proposes a technology acceptance model that connects well to established technology acceptance models for example developed by Davis (1989).

The proposed technology acceptance model still has potential for further development. Some of the introduced factors for example “Good Will of the User” or “General Trust of the User” currently seems to be explained quite generally. In addition the relevancy of the introduced factors is not fully assessed yet.  

Currently further research based on a survey together with the newspaper “Die Zeit” and the German Federal Ministry for Economics and Labour is being carried out by Spiekermann et al, with the target to describe the relevancy of the described factors more precise and to optimise the proposed model.