1. LAZY USER THEORY of Solution Selection Mikael Collan Franck Tétard

2. This presentation • Background to this research • The focus of the model • Lazy User Theory • Case mTicket • Learning issues • Relationship with some models explaining technology adoption • Conclusions IADIS CELDA 2007 Algarve, Portugal

3. Background • The model started from long discussions into why technology adoption models are mostly based on technology and not the user that adopts the technology • And another set of long discussions into what part does learning play in the selection of which solution to use • And a third discussion into why mobile services have not really taken off IADIS CELDA 2007 Algarve, Portugal

4. Focus areas of the theory • Focus on the user need and user characteristics, not only on the technology characteristics • Focus on the effort needed from the user (in €, £, $; time; activity) • Focus on putting many solutions on the same line (e.g., competing technologies) • Focus on effect of learning to the effort needed • The theory tries to explain selection of solutions ≈ technology adoption • Usable in understanding the chances of market penetration of new products & in the design of new products (solutions) • Now limited to solutions that fulfill one need 100% IADIS CELDA 2007 Algarve, Portugal

5. The Lazy User Theory of Solution Selection User need User selection of solution based on the lowest level of effort (cost) ”likelihood to select solution” defines Set of possible solutions to fulfill the need Solution 1 Solution 2 Solution 3 Solution 4 Solution 5 Solution 6 User state limits Explicitly specifiable want that can be (completely) fulfilled. The need can be tangible or intangible, e.g., information: type of information, depth of information, Quality of information, completeness of information, urgency of information delivery Circumstances: Location, available resources, available devices, available time, personal characteristics... USER FOCUS COMPETING SOLUTIONS (TECHNOLOGY) COST (UTILITY) IADIS CELDA 2007 Algarve, Portugal

6. Case: mTicket Need a ticket for the tram in Helsinki Set of possible solutions to fulfill the need User selection of solution based on the lowest level of effort (cost) User Need Buy from the tram Buy from a kiosk Buy from a ticket vending machine mTicket defines User state limits In hurry, with cash no hurry, with cash In hurry, no cash In Helsinki the ticket is 10% cheaper if bought with a mobile phone, or from a vending machine, than if bought from the tram mTicket selected because only solution mTicket likely selected if there is waiting time IADIS CELDA 2007 Algarve, Portugal

7. Solution selection The original solution COST LEVEL € £ $, Time, Effort User has selected a solution (technology) A newer less costly solution enters the market Learning takes place (user learns the system) It has a combination of cost level & likelihood that users choose the solution A new level reached through learning (becoming an expert user): What is a ”universal solution”? Because of the sunk cost in learning the user will not be more likely to adopt the new lower cost solution At least if it does not offer a lower level of cost than where the user is now It’s a solution that offers a cost level that is clearly the lowest universally => the likelihood to choose the universal solution is the highest Also: cost level of the universal solution is lower than any cost level of other solutions reachable through learning Cost (in effort/time) becomes lower due to expertise in use, this makes the likelihood to use the solution higher The cost of learning is a sunk cost and it has caused for this user a lasting change in the cost level of the solution AND a higher likelihood that this particular solution is chosen by this user in the future What about a new inexperienced user? Which solution will he/she be more likely to choose? The newer solution, because it offers a lower cost level Likelihood to choose solution IADIS CELDA 2007 Algarve, Portugal

8. Learning issues COST LEVEL € £ $, Time, Effort • - An investment in learning a solution makes the • cost of repeated use lower (economies of scale) • Learning is a sunk investment that is also a barrier of • entry; new competing solutions must be so much better • that they justify ex-ante a new investment in learning, i.e., • the faster the investment is ”paid back”, in the form of the • lower effort of use, the better • - The size of the learning investment comes from the learnability • of the solution (how easy is it to learn [to use]) and from the • portability of the knowledge needed (transferrability) • The barrier of entry is affected by memorability (how easy • is it to remember how to use), if low memorability => low barrier • of entry Gain of each repeated use Gain over old solution How many times must I use the new solution to justify the cost of learning? = Trade-off between cost of learning & the expected benefit Likelihood to choose solution Transferrability implication: Design new solutions so that users can use their previous knowledge Cost of learning (for example) IADIS CELDA 2007 Algarve, Portugal

9. Relationship with some models explaining IT adoption UTAUT: Unified Theory of Acceptance and use of Technology User need Set of possible solutions to fulfill the need User selection of solution based on the lowest level of effort (cost) TASK TECH FIT COGNITIVE MODELS defines TAM (Technology Acceptance Model) User state limits Source: Shaft & Vessey (2006) The Lazy User Theory of Solution Selection implication for IT adoption: The selection of the solution is dependent on the user need & characteristics that define the available (suitable) solutions, and that the user will select the least effort solution from the set of available solutions. Main differences with other models include the inclusion of competing solutions and the acknowledgement that effort (cost) is a main factor in solution selection that depends on the user characteristics (different cost for different individuals). Use is also strongly related to a need (of the user). UTAUT: Tries to explain what determines the acceptance and use of technology with four key constructs that are affected by four characteristics Focus on single technology at a time TAM: Characteristics of the technology determine use Focus on technology, not on the user COGNITIVE MODELS (AKA HCI): Fit between task and information presentation format leads to differences in Performance (better interfaces => better performance) TASK TECH FIT: Focus on fit of technology to task IADIS CELDA 2007 Algarve, Portugal

10. Conclusions • The Lazy User Theory takes into consideration user characteristics, competing solutions, and the cost of solutions • The theory has interesting implications for defining the effect of learning in selection of solutions through a change in the user characteristics, which cause an effect in the effort level (cost of use) • A number of theories explaining technology adoption have points of tangency with the model Future Research • Empirical research to test the theory • Further modelling of the different issues in learning vis-a-vis the cost (learnability, memorability, transferrability) • Implications of the theory to solution design • Taking into the model devices that integrate multiple solutions – including degree of fullfilling a need (now 100%) IADIS CELDA 2007 Algarve, Portugal

11. Thank You for your attention! Contact info: mcollan@abo.fi IADIS CELDA 2007 Algarve, Portugal