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Learning and Technology Adoption: A Structural and Behavioral Analysis

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Title: Learning and Technology Adoption: A Structural and Behavioral Analysis


1
Learning and Technology AdoptionA Structural
and Behavioral Analysis
  • Brent Zenobia Department of Engineering and
    Technology Management Portland State
    Universitybcapps_at_hevanet.comCharles Weber
  • Department of Engineering and Technology
    Management Portland State Universitywebercm_at_gmail
    .com

2
Abstract
  • What is the relationship between learning and
    technology adoption? A case study of alternative
    transit mode choice suggests that adoption is a
    family of three learning processes which includes
    technology selection, evaluation, and
    maintenance. Structural and behavioral analysis
    is applied to uncover the properties, dimensions,
    and dynamic behavior of these processes.
    Technology evaluation and selection are
    cognitively distinct mental processes with
    different information requirements.

3
Adoption as a Learning Process
  • Adoption is learning about tools
  • Tool use sets us apart from most other primates
  • Baboons live in social groups but they dont
    use tools,have language, or possess a theory of
    mind
  • Social life drove the evolution of the primate
    brain toa certain point, then tool use took over
    and spurredthe development of language. This
    rewired the humanbrain in important ways (Cheney
    Seyfarth, 2007)
  • Thus, learning about tools is even more
    fundamental to human cognition than language.
  • Adoption is also useful as a substantive domain
    to study learning
  • Theories of learning that are difficult to test
    in organizational settingsmay reveal themselves
    in high-involvement adoption situations
  • Such studies will have the character of basic
    research

4
The Current State of Adoption Theory
Theoretical progress has stagnated the growth
of appropriate theory is at an apparent
standstill. (Katz, 1999, pg. 145) a kind of
sameness...stereotyped approaches. (Rogers,
2003, pg. 40) A reified concept without
behavioral referents (Eveland, 1979, pg. 5)
5
The Rogers Adoption Model
OUTDATED
and yet, Rogers himself said this model is wrong.
The supporting evidence is thin, the model is 50
years old, and the stages it predicts often occur
out of order or else are skipped entirely. Rogers
pleaded for decades for someone to apply
qualitative process research methods (as opposed
to surveys) to construct a better model of
technology adoption. No causal, empirically
derived theory of adoption yet exists.
  • By far the most widely cited adoption model

Source Rogers (2003)
6
Research Objective
To construct a theory of thetechnology adoption
process that is suitable for implementation in
simulated consumer agents.
  • Why simulated consumer agents?
  • Because agent-based social simulation is the
    keyto reviving theoretical progress in adoption
    research
  • Forces parsimony and conceptual clarity
  • Permits controlled experimentation
  • Enables falsification of hypotheses elimination
    of weak theory

Source Goldspink (2002) Andrews, Baptista and
Patton (2005)
7
Research Setting
The structural and behavioral aspects of
individual adoption are more easily brought out
into the openin high-involvement decision
settings like commuting
8
Process has Structure and Behavior
  • Structure key concepts static relationships
  • Requires sampling a wide variety of outcomes
  • Therefore, outcomes must be known in advance
  • Retrospective data is needed
  • Behavior patterns in the sequence of events
  • Requires watching the process as it unfolds
  • Therefore, outcomes cannot be known in advance
  • Longitudinal data is needed

Two-stage complementary assistance design Case
1 STRUCTURE behavior Case 2 structure
BEHAVIOR
Sources Morse (1991) Morgan (1998) Van de Ven
and Huber (1990) Leonard-Barton (1990)
9
Two-Case Design
  • Passport Plus Transit Pass
  • Emphasis on structural analysis
  • (Strauss and Corbin, 1998)
  • Retrospective data collection
  • 14 interviews other evidence
  • Novice Winter Bike Commuters
  • Emphasis on behavioral analysis
  • (Miles and Huberman, 1994)
  • Longitudinal data collection
  • 28 interviews other evidence

Outputs Relationship diagrams decision
diagrams sequence diagrams UML model
10
Structural Findings
Beliefs,judgements about cause and effect
A map of how technologiesare linkedto
motivesvia beliefs
Momors,MOtive-to-MOtive Relations
Temors,TEchnology-to-MOtive Relations
influences
Motives,representations of inner mental states
Technologies,tools pertaining to motives
selection
Desires,pursued fortheir own sake
Needs,pursued for the sakeof something else
11
Structural Findings
A map of how technologiesare linkedto
motivesvia beliefs

but HOW?
influences
Technologies,tools pertaining to motives
selection
Behavioral analysis is needed!
12
Behavioral Findings I
  • Adoption is a set of three cognitive
    processeswith distinct information requirements.
  • Selection ? Which technology best suits my
    current needs?
  • ? Uses beliefs
  • ? Simple behavior runs until it terminates
  • Evaluation ? How well does this technology suit
    my needs?
  • ? Changes beliefs
  • ? Event-driven behavior stimulus/response
  • Maintenance ? Is this technology ready to use?
  • ? Factual
  • ? Event-driven behavior stimulus/response

13
Behavioral Findings IIThe Selection Process (n
75 episodes)
CantQuit
NoOptions
SensitiveMotive
Quit
ReframeSituationalNeeds
MultipleOptions
MakeTradeoff
Closure
OneOption
Committo Option
TakeAction
FrameSituationalNeeds
PromptingMotive
ActionRequired
Procrastinate
RecallTechnologyOption
AssessOptionalNeeds
ScreenOption
StatusQuo
  • Adoption criteria
  • Timing

Framing Stage
Screening Stage
Choice Stage
14
Behavioral Findings IIIThe Evaluation Process (n
151 episodes)
  • Adoption criteria
  • Relevance
  • Familiarity
  • Value

15
Behavioral Findings IVThe Maintenance Process (n
57 episodes)
  • Gain access buy, subscribe, renew, borrow.
  • Lose access sell, unsubscribe, expire, discard.
  • Gain operation repair, resupply.
  • Lose operation break, consume.
  • Adoption criteria
  • Opportunity
  • Accessibility
  • Operability

16
Behavioral Findings V
  • Operational linkage between selection
    evaluation occurs through the mirror mechanisms
    of
  • Consolidation of needs into an habitual set of
    options
  • and
  • Differentation of needs into a sensitized set of
    options

17
The Seven Criteria for Adoption
  • Timing Is my need immediate or in the future?
  • Relevance Is this technology relevant to my need?
  • Familiarity Have I used this technology before?
  • Value Is it positive, negative, mixed, or
    unknown?
  • Opportunity Can I get this technology?
  • Accessibility Do I already have this technology?
  • Operability Does this technology function?

During future research these criteria will
provide the basisfor a survey instrument to
measure the stage of adoption
18
Summary
  • Adoption is a set of three cognitive processes
    having distinct information requirements
  • Selection
  • Evaluation
  • Maintenance

19
Main Contributions
  • Empirical findings
  • Research has established an empirical link
    between technology adoption and basic cognitive
    processes.
  • Selection and evaluation are cognitively distinct
    mental processes with different information
    requirements.
  • The first empirically derived theory of adoption
  • An explanatory theory more than a model
  • In the Whitehead tradition
  • Explicitly decision-theoretic

Sources Whitehead (1929)
20
Questions?
21
Bibliography
  • Andrews, C. J., Baptista, A. I., Patton, S.
    (2005). Grounded theory and multi-agent
    simulation for a small firm. In T. Terano H.
    Kita T. Kaneda K. Arai H. Deguchi (Eds.),
    Agent-Based Simulation From Modeling
    Methodologies to Real-World Applications. Tokyo
    Springer-Verlag.
  • Cheney, D. L., Seyfarth, R., M. (2007). Baboon
    Metaphysics The Evolution of a Social Mind.
    Chicago University of Chicago Press.
  • Eveland, J. D. (1979). Issues in using the
    concept of 'adoption of innovations'. Journal of
    Technology Transfer, 4(1), 1-13.
  • Goldspink, C. (2002). Methodological implications
    of complex systems approaches to sociality
    Simulation as a foundation for knowledge. Journal
    of Artificial Societies and Social Simulation,
    5(1).
  • Katz, E. (1999). Theorizing diffusion Tarde and
    Sorokin revisited. Annals of the American Academy
    of Political and Social Science, 566, 144-155.
  • Miles, M. B., Huberman, A. M. (1994).
    Qualitative Data Analysis. Newbury Park, CA.
    Sage.
  • Rogers, E. M. (2003). Diffusion of Innovations
    (5th ed.). New York Free Press.
  • Strauss, A. L., Corbin, J. (1998). Basics of
    Qualitative Research Techniques and Procedures
    for Developing Grounded Theory (2nd ed.).
    Thousand Oaks, CA. Sage.
  • Whitehead, A. N. (1929/1969). Process and
    Reality An Essay in Cosmology (paperback ed.).
    New York Free Press.
  • Photo credits Bike Portland, Flexcar, Trimet,
    Toyota

22
Behavioral Modeling
23
Composite Sequence Analysis
  • A method for identifying typical process
    sequencesand families of sequences (Miles and
    Huberman, 1994)
  • Provided evidence for the agents activity
    diagrams and statecharts
  • What follows is a step-by-step illustration of
    behavioral analysis
  • Interview?Transcript
  • Transcript?Chronology
  • Chronology?Decision Diagram (Langley, 1999)
  • Decision Diagram?Sequence Coding
  • Sequence Coding?Dataset
  • Dataset?Sequence Diagram
  • Sequence Diagram?UML Model

24
Interview?Transcript (optional)
Transcript
Paragraph
032
  • B How long have you been using TriMet?
  • 1 Oh, wellI moved back to Oregon after a
    number of years away, a long time, almost 20
    years away, in 1998. Ive been using TriMet since
    that time. I grew up with itI think it was
    called Rose City Transit when I was small. My mom
    took me everywhere in Portland on Rose City
    Transit. I grew up with riding the bus. Shes
    from Germany, they always had decent mass
    transit. She didnt know how to drive, so we were
    always on the bus somewhere.
  • time mark 1100
  • B If I were to ask you about some of the
    feelings or meanings that you have personally
    constructed around the bus or mass transit, could
    you describe some of those to me?
  • 1 I think its often very convenient. Its
    often slower than if you park your car, but on
    the other end you dont have to pay, you dont
    have to look for a parking place or pay for it,
    so to me it comes out even - even though I can
    get downtown quicker from my house in my car than
    I can on TriMet. But then I might use my time
    hunting for a parking place. I usually enjoy it,
    its sort of like a little cultural experience.
    Sometimes Im too tired to have the cultural
    experience, because you just never know what
    youre going to get on the bus. Sometimes its
    like walking into a play.

033
034
035
036
25
Transcript?Chronology
(or voicerecording index)
Timeline Issue Category Paragraph
Childhood Rides Rose City Transit bus with mother Personal 33
1998 Moves back to Portland after long absence lives in area with limited walking options Functional-Social-Personal 33, 76, 91
1998 Becomes caregiver for elderly mother Social-Personal 76
1998 Unable to find acceptable bus options for visiting mother Functional-Social 78, 80
2001? Working full time downtown Functional 63
Sept 2001 Hired as adjunct faculty for PSU and PCC Functional 13
2001-2006 Busy schedule pressed for time Functional 82, 84, 89
2001-2006 Dissatisfied with cost of campus parking Functional 9, 17, 159
2001-2006 Parking hassles at PSU PCC Functional 9, 17, 29, 159, 165
2001-2003 Bus use increasing buys monthly pass Functional 21, 63, 65-66
2001-2006 Uses personal auto to drive to transit center (w/ trip chaining) Functional 21, 27
2001-2006 Combines Trimet with PCC shuttle bus Functional 31
2001-2006 General satisfaction with Trimet, except for cost, availability, and accessibility issues Functional 36, 221, 227-229, 231, 235
2001-2006 Enjoys using bus ride for teaching prep, rest periods/naps Functional-Personal 9, 13, 17, 217-219
2001-2006 Tired of driving, but thankful to have a car Functional 97, 249
26
Chronology?Decision Diagram
  • Commuting between home, campus, downtown, mother
  • Increasing bus use buys monthly pass
  • Utilizes shuttle bus to commute between campuses
  • Tries to reduce use of personal vehicle (trip
    chaining)
  • Occasional walking

Hired as adjunct
Working as adjunct faculty at PSU PCC
Parking hassles at PSU PCC
(--)
(--)
(--)
Settles in area with few walking options
Campus parking is expensive
Pressed for time
FUNCTIONAL
Uses bus time for teaching prep
Unable to find acceptable bus options for
visiting mother
Rides Rose City transit with mother
Becomes caregiver for elderly mother
SOCIAL
Caregiver for elderly mother
Moves back to Portland after long absence
Uses bus time to rest and nap
PERSONAL
(-)
(-)
()
()
Commute tradeoff
Childhood
Sept 2001
2003
1998
27
Decision Diagram?Sequence Coding
  • Commuting between home, campus, downtown, mother
  • Increasing bus use buys monthly pass
  • Utilizes shuttle bus to commute between campuses
  • Tries to reduce use of personal vehicle (trip
    chaining)
  • Occasional walking

Hired as adjunct
Sequence codesare derived fromuse case analysis
Working as adjunct faculty at PSU PCC
Parking hassles at PSU PCC
(--)
(--)
(--)
Settles in area with few walking options
Campus parking is expensive
Pressed for time
FUNCTIONAL
Uses bus time for teaching prep
Unable to find acceptable bus options for
visiting mother
EVTS FSN AR RCL (bus) AON SCO RCL (car) AON SCO
CLO MO MT CMT ACT (bus)
Rides Rose City transit with mother
Becomes caregiver for elderly mother
SOCIAL
Caregiver for elderly mother
Moves back to Portland after long absence
Uses bus time to rest and nap
PERSONAL
(-)
(-)
()
()
Commute tradeoff
Childhood
Sept 2001
2003
1998
28
Sequence Coding?Data Set
  • 32 interviews yielded 283 sequences
  • 75 Selection sequences
  • 151 Evaluation sequences
  • 57 Maintenance sequences

EVTS FSN AR RCL (bus) AON SCO RCL (car) AON SCO
CLO MO MT CMT ACT (bus)
29
Dataset?Sequence Diagram
CantQuit
NoOptions
SensitiveMotive
Quit
ClosureExceeded
MultipleOptions
MakeTradeoff
ReframeSituationalNeeds
OneOption
Committo Option
TakeAction
FrameSituationalNeeds
PromptingMotive
ActionRequired
Procrastinate
RecallTechnologyOption
AssessOptionalNeeds
ScreenOption
StatusQuo
Framing Stage
Screening Stage
Choice Stage
30
CantQuit
NoOptions
SensitiveMotive
Quit
ClosureExceeded
MultipleOptions
MakeTradeoff
ReframeSituationalNeeds
OneOption
Committo Option
TakeAction
FrameSituationalNeeds
PromptingMotive
ActionRequired
Procrastinate
RecallTechnologyOption
AssessOptionalNeeds
ScreenOption
StatusQuo
31
PromptingMotive
FrameSituationalNeeds
ActionRequired
AssessOptionalNeeds
RecallTechnologyOption
ClosureExceeded
ScreenOption
ReframeSituationalNeeds
NoOptions
MultipleOptions
OneOption
CantQuit
MakeTradeoff
SensitiveMotive
Committo Option
Quit
Procrastinate
TakeAction
StatusQuo
32
Sequence Diagram? Activity Diagram
Select Technology ltltpreconditiongtgt usage
situation Prompting Motive Motive ltltpostconditio
ngtgt technology chosen
Info
Help
PromptingMotive
AcquireHelp
AcquireInfo
RecallSituational Need
Situational Context
Check for Closure
else
closure achieved
Check ifAction Required
else
From interviewto UML diagraman unbrokentrail
of evidence
action required
status quo
Reject Technology
Recall Technology
Technology
Technology Set
RecallOptional Need
Optional Need
Check for Closure
else
Check forViolation
closure achieved
technology set lt 1
technology set gt 1
Optional Need Set
else
else
limit exceeded
SensitizeMotive
MakeTradeoff
Check for Closure
else
ReframeContext
closure achieved
ChooseTechnology
SituationalContext
Check toBegin Action
limit exceeded
else
use
procrastinate
Situational Need
Optional Need
Technology
33
Bibliography
  • Langley, A. (1999). Strategies for theorizing
    from process data. The Academy of Management
    Review, 24(4), 691-710.
  • Miles, M. B., Huberman, A. M. (1994).
    Qualitative Data Analysis. Newbury Park, CA.
    Sage.
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