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Introduction to NFC

Near field communication (NFC) is a short-range wireless technology that allows users to connect devices and access content and services by simply holding enabled devices near each other.

Once NFC chips are integrated into devices, a host of new applications can be built that can:

  • Pay for goods and services
  • Help people access such things as public transport, office buildings, or their cars
  • Download music, videos, and discount coupons from smart posters
  • Share content such as music, videos and photographs
  • exchange business cards

A few Android smartphones already support NFC and Microsoft and Apple are expected to integrate NFC in the phones to be launched in late 2012.

According to a recent study, one-third of iPhone users indicated that they were “likely” or “very likely” to use mobile payments. Analysis from Juniper Research states that the NFC mobile payments market will exceed $75 billion globally by 2013, when 20% of all phones shipped will possess NFC capability.

With these developments, a flurry of NFC enabled apps is expected to hit the market. Anokwa, Borriello, Pering and Want contend that since NFC can be used both for simple interactions like touching a secure door with a cell phone to gain access, and for more complex scenarios such as buying a movie ticket. Without a user model in place, NFC enabled applications may end up a mix of poorly thought out interfaces without a unifying interaction model.

User interaction models

To solve this problem, Anokwa et al. introduce a user interaction model for NFC enabled applications which relies on users’ existing mental model of the objects which they are interacting with. When a device scans an item it takes on the properties and context of that item. This transformation leverages the existing knowledge that users have about certain objects and thus can support a number of different applications tied together with simple, intuitive and repeatable interactions.

The manner in which the current interaction model works is that if you scan a smart movie poster, it gives you a URL that points to a movie site where you can purchase the ticket. After purchase, the device is authorized and allows access to the theater. Unfortunately, this model ignores the existing mental model of the user. If you buy a movie ticket in the real world, you get a physical object that you can interact with. You can verify and see if the ticket is correct, keep the stub as a souvenir, or you may also give the ticket to a friend.

The proposed interaction model simulates the real world. If the device scanned a smart movie poster, it could take on the properties of the ticket, containing all the information printed on a standard ticket. The user could transfer the ticket to a friend’s phone. After the ticket is used for accessing the theater, it could become a ticket stub.

Scenario to illustrate the user interaction model

Another study that is more focused on mobile phones is “Intimate Self-Disclosure via Mobile Messaging.” This study explores SRCT in the context of mobile phones. Following are the hypotheses tested through the study:

  1. Participants will self-disclose more via mobile messaging in response to intimate questions coupled with the flattery and social norms strategies than via direct requests.
  2. Participants will self-disclose more via mobile messaging in response to intimate questions ostensibly from a human than from a computer.
  3. Participants’ self-disclosure via mobile messaging in response to intimate questions will be differentially affected by a human or computer sender that flatters them as compared to one that does not flatter them.

The study was conducted with 71 university students. The students received course credit or a $20 Amazon.com gift certificate as incentive and were told that the study was testing a new questionnaire system. All participants used their own mobile phones and service plans. The experiment conducted was based on permutation of sender and strategy. Sender could be of two types, human and computer. Strategy could be of three types, “direct request,” “flattery” and “social norms.”

Participants were asked to choose two periods, each about 2 days long, to participate. The periods were spaced one week apart. In each day, participants were required to choose an hour-long time slot to receive six to seven questions via text message. The first two questions sent to the participants in each period were low intimacy, and the remaining ten each period were high intimacy. An example of a high intimacy question could be “What has been the biggest disappointment in your life?”

In some cases the sender was referred to as “research assistant” while in others as “research computer.”  This was highlighted to the participants across two reminder emails and four welcome messages. In reality, all messages were sent by a computer.

In the “direct request” strategy, participants were only sent the question. In the “flattery” strategy, each question was accompanied by a compliment (e.g. “Nice reply!” or “You are better at texting than most.”). In the “social norms” strategy, the question was accompanied by a sentence stating the percentage (85-100%) of participants who had fully answered the question.

Breadth, or quantity, of disclosure is measured by word count. Responses which contained “no comment” were counted as 0 words.

The results of the experiment are summarized in the table and figure below.

The study showed that participants showed significantly more disclosure when flattery was provided by the ‘human’ sender than by the ‘computer’.  Different strategies did not elicit significantly different disclosure when the participants thought they were interacting with a ‘computer.’

It could be concluded that though people reciprocate with computers in self-disclosure, flattery is a more effective as a strategy for humans than computers. These results can be seen as inconsistent with predictions of SRCT.

reason for using internet

Summary

Across the two contrasting studies talked about in this paper, it is evident people respond to computers/mobile phones as if they are social actors. This provides a tremendous opportunity to leverage mobile phones to persuade and induce behaviour change.

The point to keep in mind is that though there is a social response, it is not as much as human to human interaction. Technology/mobile phones have not arrived at the point where they could start to substitute human interaction. For now, they can be crude and rudimentary companions which humbly suggest and advise.

But the day is not far! As stated in Ray Kurzweil’s book The Spiritual Machine, the future of mankind would find a turning point when machines will start to surpass human intelligence and become a more than satisfactory substitute for human connection.


References

  • Computers are Social Actors
    Clifford Nass, Jonathan Steuer, and Ellen R. Tauber
    Department of Communication
    Stanford University

    Mobile Persuasion
    20 Perspectives on the future of behaviour change
    BJ Fogg & Dean Eckles

    The Spiritual Machine
    Ray Kurzweil

    Intimate Self-Disclosure via Mobile Messaging:
    Influence Strategies and Social Responses to Communication Technologies
    Dean Eckles, Doug Wightman, Claire Carlson, Attapol Thamrongrattanarit,
    Marcello Bastea-Forte, B.J. Fogg
    Persuasive Technology Lab, Stanford University
    Nokia Research Center, Palo Alto, CA

Message from the CEO, Dr. Eric Schaffer — The Pragmatic Ergonomist

Leave a comment here

Reader comments

Ilona Posner

Great idea as long as the discrete buzz of the movie ticket purchase is different than the notifications about your bank deposit, arriving text message from your mother, awaiting voice mail from your boss, and latest goal in your favorite team's game. Also, this buzz needs to be perceptible while the phone is inside my purse!

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