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代寫Journal of Educational Psycholog

    *Donna L. Hoffman is Chancellor’s Chair and Professor of Marketing
    (e-mail: donna.hoffman@ucr.edu), and Thomas P. Novak is Albert O. Stef-
    fey Professor of Marketing (e-mail: tom.novak@ucr.edu), A. Gary Ander-
    son Graduate School of Management, University of California, Riverside.
    Praveen K. Kopalle is Associate Professor of Business Administration,
    Tuck School of Business, Dartmouth College (e-mail: praveen.kopalle@
    dartmouth.edu). This research was supported by grants from the University
    of California, Riverside’s Sloan Center for Internet Retailing, the Marketing
    Science Institute, the Tuck Associates Program, and the Lally School of
    Management at Rensselaer Polytechnic Institute. The authors thank the two
    anonymous JMR reviewers; seminar participants at the University of Cali-
    fornia, Riverside, Dartmouth College, Georgia Institute of Technology, the
    University of Illinois, Indian School of Business, Rensselaer Polytechnic
    Institute, and University of California/University of Southern California
    Seminar Series; and session participants at the 2008 Association for Con-
    sumer Research conference, 2008 Marketing Science conference, and 2008
    Utah Product and Service Innovation Conference for their many helpful
    and insightful comments. The authors also thank David Porter, inventor of
    SmartBox (U.S. Patent No. 5,774,053), for his gracious permission to use
    the SmartBox descriptions in this research. John Hauser served as associ-
    ate editor for this article.
    DONNA L. HOFFMAN, PRAVEEN K. KOPALLE, and THOMAS P. NOVAK*
    While much research has emphasized improving current new product
    concept techniques, little work has focused on trait-based approaches that
    specify which consumers are the “right” ones to use in the new product
    development process, particularly in the consumer goods industry. The
    authors propose that the right consumers to use possess what they call
    an “emergent nature,” defined as the unique capability to imagine or
    envision how concepts might be developed so that they will be successful
    in the mainstream marketplace. The authors draw on research on
    personality theory and information-processing styles to support their
    conceptualization and develop and validate a highly reliable scale to
    measure emergent nature (Study 1). In subsequent multipart studies,
    they show in both group (Studies 2a–2c) and individual (Studies 3a and
    3b) settings across two distinct product categories that consumers high
    in emergent nature are able to develop product concepts that
    mainstream consumers find significantly more appealing and useful than
    concepts developed by typical, lead user, or even innovative consumers.
    Keywords: concept development, new products, information processing,
    personality traits, lead users, dispositional innovativeness
    The “Right” Consumers for Better Concepts:
    Identifying Consumers High in Emergent
    Nature to Develop New Product Concepts
    © 2010,American MarketingAssociation
    ISSN: 0022-2437 (print), 1547-7193 (electronic) 854
    Journal of Marketing Research
    Vol. XLVII (October 2010), 854–865
    Consumer firms are interested in learning which con-
    sumers might be the “right” ones in developing new product
    concepts so that they can improve their chances of success
    in the marketplace. Determining the consumers who are the
    most appropriate to engage in the concept development
    process is important for new product success because new
    product development is a major activity of firms (Chandy
    and Tellis 1998) and failure rates are still high. In general,
    between 40% and 45% of new products fail (Griffin 1997),
    and the failure rate for consumer packaged goods is even
    higher at approximately 49% (Barczak, Griffin, and Kahn
    2009). Although much research has emphasized improving
    current new product concept techniques—for example,
    through mental analogies (Dahl and Moreau 2002), visual
    depiction and animation (Dahan and Srinivasan 2000),Web-
    based testing (Dahan and Hauser 2002), and conjoint analy-
    sis (Green, Krieger, and Vavra 1997)—little work has
    focused on trait-based approaches that specify which con-
    sumers may be most helpful in developing product con-
    cepts, particularly in the consumer goods industry.
    The lead user approach has received much attention in
    business-to-business settings. Lead users have a conscious
    awareness of their domain-specific needs, are motivated to
    innovate to satisfy those needs, and experience those needs
    earlier than others in the market (Lilien et al. 2002; Morri-
    son, Roberts, and Von Hippel 2000). Because of the limited
    number of lead user studies in consumer settings (e.g.,
    The “Right” Consumers for Better Concepts 855
    Schreier, Oberhauser, and Prügl 2007), it may be difficult to
    identify lead users in consumer markets, and lead user sta-
    tus may not be a trait-based characteristic but rather specific
    to domains of use.
    A notable consumer behavior trait-based approach that
    evaluates the potential success of an innovation uses con-
    sumer innovativeness, defined as an underlying predisposi-
    tion of consumers to buy new and different products (Midg-
    ley and Dowling 1978). The consumer innovativeness
    construct is distinct from innovation adopter categories
    (Rogers 2003), which are determined ex post product intro-
    duction (Steenkamp, Ter Hofstede, and Wedel 1999). Con-
    sumer innovativeness has been found to correlate positively
    with personality traits, such as extraversion, risk taking, and
    impulse buying (Steenkamp, Ter Hofstede, and Wedel
    1999).
    EMERGENT NATURE
    We propose that the right consumers to use when devel-
    oping new product concepts possess what we call an “emer-
    gent nature,” defined as the unique capability to imagine or
    envision how concepts might be further developed so that
    they will be successful in the mainstream marketplace. We
    theorize that this envisioning arises from a unique constella-
    tion of personality traits and processing abilities that
    enables such consumers to engage in a synergistic process
    of visualization and rationalization to improve product con-
    cepts. These unique personality traits and processing abili-
    ties for further developing successful product concepts
    include openness to new experiences and ideas; an intellec-
    tive self-focus, or “reflection”; the ability to synergistically
    apply both an experiential and a rational processing style;
    the ability to process information both verbally (rational
    style) and visually (experiential style); high levels of cre-
    ativity; and optimism. We briefly review the rationale
    underlying our predictions.
    Previous research has found that openness to experience
    is related to divergent thinking, an important component of
    creativity (McCrae 1987). People high on this trait are more
    imaginative and reflective and enjoy experiences with
    unique aesthetic, emotional, and intellectual components.
    We expect an open-minded thinking disposition (Stanovich
    and West 1997) to correlate strongly with emergent nature
    because people with such dispositional tendencies often
    exhibit openness to new experiences and ideas and apply
    logical reasoning.
    Reflection is a type of private introspection (Fenigstein,
    Scheier, and Buss 1975) stimulated by exploratory curiosity
    and represents an intellective self-consciousness or self-
    focus motivated by epistemic goals (Trapnell and Campbell
    1999). We hypothesize that consumers high in emergent
    nature exhibit greater amounts of internal reflection, thus
    contributing to an increase in network associations in mem-
    ory that could extend beyond the self to other associations.
    Such consumers are able to experientially explore and
    rationally investigate unique alternatives in product devel-
    opment contexts.
    Along these same lines of reasoning, we expect several
    types of information processing to be positively correlated
    with emergent nature. Extensive research in information
    processing supports people’s relative tendency to engage in
    a rational (analytical, logical, causal, and systematic) versus
    experiential (intuitive, affective, and holistic) processing or
    thinking style (e.g., Epstein et al. 1996; Sloman 1996; Smith
    and DeCoster 2000). Novak and Hoffman (2009) refer to
    “synergistic effects,” in which both experiential and rational
    task-specific thinking style might correlate positively with
    performance and function in a more complementary way.
    We expect consumers high in emergent nature to possess the
    ability to process information both experientially and ration-
    ally. We argue that the active, logical processing associated
    with a rational thinking style permits consumers to make
    optimal judgments about the utility of a particular product
    concept, while the experiential thinking style involves emo-
    tional and associative processing that we hypothesize yields
    a more intuitive understanding of the concept’s usefulness.
    This suggests that these information-processing styles oper-
    ate synergistically and will be positively correlated with
    emergent nature.
    We also expect consumers high in emergent nature to
    possess the ability to process information both verbally
    (rational style) and imaginally (experiential style). Verbal
    processing refers to a person’s ability to process words, and
    imaginal processing refers to a person’s ability to visually
    process imagery (Childers, Houston, and Heckler 1985).
    The ability to process words and images is highly relevant
    to a product concept–envisioning task that incorporates
    visualization and rationalization.
    We also predict that emergent nature will be positively
    correlated with creativity and optimism. Creativity can be
    conceptualized in a variety of ways, but it can be difficult to
    measure. Our conceptualization relies on self-reports that
    tap a person’s self-concept of creativity and “creative per-
    sonality” (Gough 1979). Optimism is related to the extent to
    which people view things to be better in the future than they
    are now (Kopalle and Lehmann 2001). Consumers who are
    able to envision how current new product concepts might be
    better developed for future success have an intrinsically
    optimistic outlook.
    Our conceptualization is related to the notion of so-called
    industrial technical visionaries (Vojak et al. 2006, p. 17)—
    people who can “effectively synthesize multiple technolo-
    gies and business strategy to identify new … products”—and
    to preliminary research from organizational neurospsychol-
    ogy that suggests that visionaries display higher levels of
    brain activity than nonvisionaries in areas of the brain asso-
    ciated with visual processing and information organization
    (Dvorak and Badal 2007; Peterson et al. 2008). We use our
    conceptualization to develop and validate a highly reliable
    scale that can be used to identify consumers high in emer-
    gent nature. After such consumers have been identified, we
    test the predictive validity of the idea that these consumers
    are better able to further develop product concepts than
    other consumers. We predict that emergent nature is uni-
    dimensional and distinct from both lead user status (also an
    original scale we develop from the work of Morrison,
    Roberts and Von Hippel [2000] and predict to be a uni-
    dimensional construct) and dispositional innovativeness
    (Steenkamp and Gielens 2003) and that it is positively cor-
    related with, but distinct from, openness to new experiences,
    reflection, verbal and visual processing styles, experiential
    and rational thinking styles, creativity, and optimism (Study
    1). We then use our highly reliable and valid instruments to
    measure emergent nature and lead user status, along with an
    existing scale to measure dispositional innovativeness, in
    several multipart studies in consumer settings to establish
    the predictive validity of the emergent nature construct. We
    predict that consumers high in emergent nature will be able
    to improve product concepts that mainstream consumers
    will find significantly more appealing and useful than con-
    cepts developed by typical, lead user, or even innovative
    consumers in both group (Studies 2a–2c) and individual
    (Studies 3a and 3b) settings across the two distinct product
    categories of home delivery and oral care.
    STUDY 1: SCALE DEVELOPMENT AND VALIDATION
    Calibration Method
    The total analysis sample comprised 1124 native English-
    speaking adult respondents randomly selected from a global
    online panel (for sampling details, see the Web Appendix,
    “Study 1 Sampling Details,” at http://www.marketingpower.
    com/jmroct10). Following Wickens (1989), we unevenly
    split the sample into a larger calibration sample of 754 ran-
    domly drawn respondents to develop the emergent nature
    scale; 370 respondents served as the validation sample.
    Respondents completed an online study that they were
    told had two separate and independent parts in the same
    experimental session. Respondents were told that the “first”
    study would assess their general attitudes toward products
    and services. All respondents answered a short series of
    questions regarding Internet usage. Following Churchill
    (1979), we used our theoretical definition of emergent
    nature to generate an extensive set of preliminary items as
    the first step in scale construction. Through item analysis in
    a pretest, we refined the set to 17 items. Respondents were
    presented with a battery of scales, including the 17 items
    constituting our original emergent nature scale, an existing
    eight-item scale measuring a consumer’s tendency toward
    dispositional innovativeness (Steenkamp and Gielens 2003),
    Rook and Fisher’s (1995) nine-item scale of impulse buy-
    ing, and eight items constituting our original lead user sta-
    tus scale. The context for all scales was the domain of con-
    sumer home delivery through an intelligent storage device
    outside people’s homes called “SmartBox” (for the descrip-
    tion used, see Appendix A). Respondents evaluated their
    general attitude toward the SmartBox; completed single-
    item measures regarding adoption, use, and ordering behav-
    ior; estimated the maximum price they would be willing to
    pay for installation of the SmartBox; evaluated how attrac-
    tive they believed the SmartBox currently is to average con-
    sumers; reported whether they could picture the SmartBox
    being developed in the future in such a way that average
    consumers would find it attractive; and provided up to 20
    ways they “can think of for changing the SmartBox so that
    it will be successful in the marketplace as a home delivery
    solution for average consumers.” Respondents also evaluated
    their interest and experience with the home delivery of
    goods and services using scales for product class involve-
    ment and knowledge (Beatty and Talpade 1994) and a
    single-item measure for actual use.
    In the “second” study, respondents completed a series of
    validation scales designed to measure the personality traits
    and information-processing styles hypothesized to corre-
    spond to our conceptualization of emergent nature, includ-
    ing openness to experience, reflection, verbal and visual
    processing, rational and experiential thinking style, opti-
    mism, creativity, and impulse buying behavior. We used the
    12-item “openness-to-experience” subscale from the Revised
    NEO (Neuroticism–Extroversion–Openness) Personality
    Inventory (Costa and McCrae 1992); Trapnell and Camp-
    bell’s (1999) 12-item reflection scale; two 11-item scales
    that tapped verbal and visual processing style (Childers,
    Houston, and Heckler 1985); the 24-item short form of the
    Rational Experiential Inventory (Norris and Epstein 2003)
    to measure rational and experiential processing; two reliable
    and valid self-report measures of creativity, one comprising
    three original items developed in pretests (“I consider
    myself to be a creative person,” “Creative endeavors are
    important to me in my life,” and “My best friends consider
    me to be a creative person”) and the other a widely used
    self-assessment checklist to assess “creative personality”
    using a person’s self-concept derived from the Adjective
    Check List (Gough 1979); and one three-item consumer
    optimism scale (Kopalle and Lehmann 2001).
    Scale Development Results
    We followed current practice in psychometrics (e.g.,
    Kline 2000) to construct the scales (see “Study 1 Scale
    Construction” in the Web Appendix at http://www.
    marketingpower.com/jmroct10).After we reduced the origi-
    nal 17 items, the final 8-item emergent nature scale (α =
    .929) accounted for 63% of the variation in the correlations
    and displayed one dominant factor, in support of the
    hypothesis that a consumer’s emergent nature is a unidimen-
    sional construct that can be reliably measured. An
    exploratory principal axis factor analysis and iterative item
    analysis of the domain-specific lead user status scale items
    produced a 5-item scale (α = .931) that accounted for 73%
    of the variation in the correlations and one dominant factor,
    in support of the hypothesis that the domain-specific lead
    user scale is unidimensional. We list the final sets of items
    for both scales in Table 1. We used Steenkamp and Gie-
    lens’s (2003) 8-item dispositional innovativeness scale with-
    out further modification (α = .830).
    Moderately low correlations among the observed
    summed scales support our theory that emergent nature is a
    construct distinct from dispositional innovativeness (r = .37)
    and lead user status (r = .39). Lead user status and disposi-
    tional innovativeness exhibited a weak correlation (r = .18)
    in the calibration sample, also consistent with theory. We
    used confirmatory factor analysis to formally test discrimi-
    nant validity of the three constructs. The fit of a single-factor
    structural model to the three scales was poor (comparative
    fit index [CFI] = .599, root mean square error of approxima-
    tion [RMSEA] = .171), but a three-factor structural model
    fit well (CFI = .941, RMSEA = .066), in support of our
    hypothesis that emergent nature, dispositional innovative-
    ness, and domain-specific lead user status are three distinct
    constructs. All factor loadings were above .60, except for
    three items on the dispositional innovativeness scale.
    Scale Validation
    In the validation sample, coefficient alphas were also
    high (emergent nature α = .937, dispositional innovative-
    ness α = .801, lead user α = .930), and correlations among
    the summed scales followed the same pattern as in the cali-
    bration sample: Emergent nature exhibited low to moderate
    correlations with dispositional innovativeness (r = .38) and
    856 JOURNAL OF MARKETING RESEARCH, OCTOBER 2010
    The “Right” Consumers for Better Concepts 857
    lead user status (r = .48), and lead user status and disposi-
    tional innovativeness were only weakly associated (r = .17).
    The fit of the confirmatory factor analysis three-factor struc-
    ture was also good (CFI = .938, RMSEA = .069), with all
    factor loadings above .60 except for three items on the dis-
    positional innovativeness scale, again in support of our
    theory that emergent nature, dispositional innovativeness,
    and domain-specific lead user status are three distinct
    constructs.
    Having established reliability and discriminant validity
    with the calibration and validation samples, we combined
    the samples to demonstrate construct validity. Means of the
    summed scales and measured variables, along with correla-
    tions with demographics, appear in the Web Appendix (see
    “Study 1: ConstructValidity” at http://www.marketingpower.
    com/jmroct10).
    Table 2 presents the correlations and regression coeffi-
    cients from fitting a series of simple regression models
    using emergent nature, lead user status, and dispositional
    innovativeness as predictors and the personality traits and
    information-processing scales as the dependent variables.
    Note that the regression coefficients in each model are
    attenuated compared with the correlation coefficients
    because they include the other constructs in the model.
    Thus, each regression model indicates whether emergent
    nature adds predictive value above and beyond lead user sta-
    tus and dispositional innovativeness and which construct is
    most important in accounting for variation in the dependent
    variable. Overall, the results show that emergent nature is a
    useful construct that adds predictive value above and
    beyond dispositional innovativeness and lead user status. It
    correlates with and is significant with more personality
    traits and information-processing scales than the other two
    predictors.As we predicted, it is significantly and positively
    associated with reflection, openness to experience, verbal
    and visual processing, experiential and rational thinking
    style, creativity, and optimism. The only regression model
    in which emergent nature does not add anything above and
    beyond the other constructs is impulse buying. This is rea-
    sonable considering that impulse buying behavior is an
    unplanned purchase defined by an immediate urge to buy a
    product, counter to behavior expected given the rational
    component posited in emergent nature. In contrast, disposi-
    tional innovativeness does not add additional predictive
    value above and beyond emergent nature, except for experi-
    ential thinking style and impulse buying. Compared with
    emergent nature, dispositional innovativeness has a higher
    association with experiential thinking style and impulse
    buying and a lower association with rational thinking style,
    reflection, openness, verbal and visual processing, creativ-
    ity, and optimism. Lead user status does not add predictive
    Table 1
    FINAL ITEMS FOR EMERGENT NATURE AND LEAD USER
    SCALES
    Emergent Nature
    1.When I hear about a new product or service idea, it is easy to
    imagine how it might be developed into an actual product or service.
    2. Even if I don’t see an immediate use for a new product or service, I
    like to think about how I might use it in the future.
    3. When I see a new product or service idea, it is easy to visualize how
    it might fit into the life of an average person in the future.
    4. If someone gave me a new product or service idea with no clear
    application, I could “fill in the blanks” so someone else would know
    what to do with it.
    5. Even if I don’t see an immediate use for a new product or service, I
    like to imagine how people in general might use it in the future.
    6. I like to experiment with new ideas for how to use products and
    services.
    7. I like to find patterns in complexity.
    8. I can picture how products and services of today could be improved
    to make them more appealing to the average person.
    Domain-Specific Lead User
    1. Other people consider me as “leading edge” with respect to home
    delivery of goods.
    2. I have pioneered some new and different ways for home delivery of
    goods.
    3. I have suggested to stores and delivery services some new and
    different ways to deliver goods at home.
    4. I have participated in offers by stores to deliver goods to my home
    in new and different ways.
    5. I have come up with some new and different solutions to meet my
    needs for the home delivery of goods.
    Table 2
    CORRELATIONS AND REGRESSION RESULTS FROM STUDY 1 VALIDATION MODELS WITH EMERGENT NATURE, DISPOSITIONAL
    INNOVATIVENESS, AND DOMAIN-SPECIFIC LEAD USER STATUS AS PREDICTORS AND PERSONALITY TRAITS AND INFORMATION-
    PROCESSING SCALES AS DEPENDENT VARIABLES
    Standardized Regression
    Coefficient (p-Value) for the
    Column Predictor Given the
    Correlations Row Dependent Variable
    E DI LU E DI LU Model R 2
    Experiential processing .166 .227 –.011 n.s. .140 (.000) .196 (.000)–.103 (.001) .069
    Rational processing .389 .148 .108 .412 (.000) .014 (.631)–.066 (.029) .155
    Reflection .397 .175 .230 .351 (.000) .038 (.196) .077 (.01) .164
    Openness .372 .281 .085 .348 (.000) .174 (.000)–.091 (.003) .170
    Verbal processing .309 .255 .160 .236 (.000) .166 (.000) .033 (.288) .121
    Visual processing .326 .168 .092 .327 (.000) .062 (.04) –.055 (.075) .112
    Creativity (self-perceived) .462 .204 .272 .406 (.000) .045 (.112) .095 (.001) .222
    Creative personality .360 .212 .189 .308 (.000) .095 (.001) .044 (.146) .139
    Optimism .270 .175 .146 .223 (.000) .090 (.003) .037 (.240) .081
    Impulse buying .145 .310 .162 –.005 (.890) .292 (.000) .113 (.000) .108
    Notes: E = emergent nature, DI = dispositional innovativeness, and LU = domain-specific lead user. All correlations, except as noted with n.s., are signifi-
    cant at the .01 level (two-tailed).All regression models are significant at the .000 level. Significant standardized regression coefficients appear as bold entries.
    value beyond emergent nature for any of the validation
    scales.
    In Table 3, we present a similar analysis using the Smart-
    Box scales as the dependent variables. In general, emergent
    nature and dispositional innovativeness tend to be more
    strongly associated with attitude and intention measures
    than lead user status, possibly because lead user status is
    domain specific, not SmartBox specific. However, lead user
    status adds predictive value above and beyond emergent
    nature and dispositional innovativeness for being attractive
    in its current form, category involvement, knowledge, and
    actual use. Note that emergent nature adds predictive value
    beyond dispositional innovativeness and lead user status for
    picturing how SmartBox can be developed in the future and
    the number of ways the SmartBox can be improved, in sup-
    port of our conceptualization.
    An additional main effects analysis (see Table W4 in
    “Study 1: ConstructValidity” in the WebAppendix at http://
    www.marketingpower.com/jmroct10) showed that con-
    sumers high in emergent nature exhibit significantly higher
    levels of openness to new experience, reflection, visual pro-
    cessing, experiential and rational processing, and creativity
    than consumers high on dispositional innovativeness or lead
    user status. However, consumers high on lead user status
    and dispositional innovativeness were significantly higher
    on impulse buying behavior than consumers high on emer-
    gent nature.
    Emergent nature is correlated with creativity (self-
    perceived r = .462, and creative personality r = .360), expe-
    riential thinking style (r = .166), and rational thinking style
    (r = .389). Formal tests using confirmatory factor analysis
    enable us to test the hypothesis that emergent nature,
    creativity, and experiential and rational thinking styles are
    distinct constructs. The fit of a single-factor model to
    the scales for emergent nature, creative personality, self-
    perceived creativity, and experiential and rational thinking
    styles was poor (CFI = .513, RMSEA = .10), but a five-
    factor confirmatory model fit well (CFI = .900, RMSEA =
    .044), with all factor loadings above .60 (except for the 30
    items on the creative personality checklist, which had 14
    items below .45). In addition, the fit of a single-factor
    confirmatory model to the scales for emergent nature, self-
    perceived creativity, and rational and experiential thinking
    styles was poor (CFI = .631, RMSEA = .206), but a four-
    factor confirmatory factor analysis model fit well (CFI =
    .965, RMSEA = .066), with all factor loadings above .60.
    This lends further support to the discriminant validity of
    emergent nature. Having established reliability and con-
    struct and discriminant validity, we examine predictive
    validity in several concept development domains to extend
    generalizability.
    STUDY 2: GROUP CONCEPT DEVELOPMENT AND
    MARKET TESTING
    Study 2a: Concept Development
    We created four mutually exclusive groups by classifying
    the Study 1 respondents according to their median scores on
    each of the three construct scales. The high emergent nature
    group contained respondents above the median on emergent
    nature and below the median on dispositional innovative-
    ness and lead user status. The high lead user and high inno-
    vativeness groups were similarly constructed so that each
    group had members above the median on that group’s con-
    struct and below the median on the others. The final group
    consisted of respondents who scored at the median on all
    three scales and served as the control group. 1 We randomly
    selected 50 respondents from each group and invited them
    by e-mail to participate in a follow-up five-day online bul-
    letin board group study.A total of 24 respondents completed
    the study (for selection and implementation details, see the
    WebAppendix, “Study 2a Sampling Details,” at http://www.
    marketingpower.com/jmroct10). Participants in each group
    were instructed to “further develop the SmartBox concept
    so that it will be successful in the marketplace as a home
    delivery solution for average consumers.” At the end of the
    three-day development period, each group had produced a
    single SmartBox concept (listed in Appendix B) that they
    believed would be the most appealing to the typical con-
    858 JOURNAL OF MARKETING RESEARCH, OCTOBER 2010
    Table 3
    CORRELATIONS AND REGRESSION RESULTS FROM STUDY 1 VALIDATION MODELS WITH EMERGENT NATURE, DISPOSITIONAL
    INNOVATIVENESS, AND DOMAIN-SPECIFIC LEAD USER STATUS AS PREDICTORS AND SMARTBOX SCALES AS DEPENDENT
    VARIABLES
    Standardized Regression
    Correlations Coefficient (p-Value)
    E DI LU E DI LU Model R 2
    Attitude toward SmartBox .220 .189 .119 .164 (.000) .126 (.000) .029 (.363) .063
    Adopt if given free .249 .230 .213 .141 (.000) .158 (.000) .127 (.000) .099
    Use if given free .289 .260 .186 .196 (.000) .178 (.000) .073 (.000) .116
    Order, if given SmartBox .273 .226 .228 .167 (.000) .144 (.000) .133 (.000) .109
    Max price willing to pay .165 .133 .122 .109 (.001) .084 (.008) .062 (.055) .037
    Attractive in current form .179 .130 .213 .085 (.012) .072 (.021) .165 (.000) .060
    Picture it developed in future .281 .220 .143 .221 (.000) .137 (.000) .027 (.396) .096
    Ways to improve Smartbox .212 .089 .094 .204 (.000) .016 (.611) .006 (.844) .045
    Category involvement .379 .267 .432 .193 (.000) .142 (.000) .327 (.000) .252
    Category knowledge .413 .259 .541 .188 (.000) .115 (.000) .443 (.000) .347
    Category actual use .311 .251 .376 .136 (.000) .152 (.000) .292 (.000) .190
    Notes: E = emergent nature, DI = dispositional innovativeness, and LU = domain-specific lead user. All correlations are significant at the .01 level (two-
    tailed).All regression models are significant at the .000 level. Significant standardized regression coefficients appear as bold entries.
    1 The remaining respondents were not relevant for the purposes of the
    study, and we did not use them further.
    The “Right” Consumers for Better Concepts 859
    sumer when introduced to the market. Participants then
    rated their trust of the other participants in the group (4-item
    scale adapted from Ramsey and Sohi 1997), satisfaction
    with the experience (11-item scale adapted from Mano and
    Oliver 1993), satisfaction with the final SmartBox concept
    (4-item scale adapted from Ganesan 1994), attitude toward
    the concept and new product novelty (7-item scale adapted
    from Moorman 1995), posttask mood (Allen and
    Janiszewski 1989), and involvement (Swinyard 1993), all
    measured on seven-point scales. Mean scores on the meas-
    ures for the four groups were not noticeably different, and it
    was clear that the online bulletin board concept develop-
    ment task was successful; the average (across group) scores
    for trust (M = 6.37), satisfaction with the experience (M =
    6.49), satisfaction with the concept (M = 6.15), attitude
    toward the concept (M = 6.19), new product novelty (M =
    1.89 [lower scores indicated more novel product concepts]),
    posttask mood (M = 6.46), and involvement with the task
    (M = 6.12) were uniformly high. Next, we used these final
    product concepts to test market reaction with a large group
    of real-world consumers.
    Study 2b: Testing Market Reaction
    We randomly selected 631 native English-speaking adult
    consumers from a global online panel to evaluate the four
    concepts from Study 2a. Sampling details appear in the Web
    Appendix (see “Study 2b Sampling Details”; http://www.
    marketingpower.com/jmroct10). Participants saw the dia-
    gram and basic description of the SmartBox (see Appendix
    A) and then reviewed the four different SmartBox concepts
    (see Appendix B), identified only by number (1–4), which
    we counterbalanced to control for order effects. Participants
    then indicated which concept was the most and least appeal-
    ing, rated their attitudes toward each concept on four stan-
    dard concept-testing scales (bad/good, dislike/like, dull/
    dynamic, and not useful/useful), indicated their involvement
    with and knowledge of home delivery (adapted from Beatty
    and Talpade 1994), and indicated their frequency of home
    delivery.
    On average, participants reported moderate levels of
    involvement with the general idea of home delivery (4.5 on a
    seven-point scale) and knowledge with the practice (3.94 on a
    seven-point scale). Only one-third of the respondents reported
    having goods delivered to their home once a week or more;
    12.5% reported having only rarely or never having goods
    delivered at home. As a group, the concept-testing sample
    was neither particularly knowledgeable/experienced nor
    inexperienced/not knowledgeable regarding home delivery.
    We standardized and summed the six items (most appeal-
    ing, least appealing, bad/good, dislike/like, dull/dynamic,
    not useful/useful) to create a composite score for each
    respondent, and we used those composite scores to con-
    struct scales for each of the four concepts. Coefficient
    alphas were uniformly high (control α = .853, high lead user
    α = .839, high innovativeness α = .80, and high emergent
    nature α = .848). A repeated measures analysis of variance
    (ANOVA) revealed a significant main effect (F = 92.73, p =
    .000) on the concept-testing scale, with the high emergent
    concept (M = 1.77) being a more highly rated concept than
    the high lead user (M = 1.19), high innovativeness (M =
    –.61), and control group (M = –1.27) concepts.
    Because we have multiple observations from each
    respondent, we accounted for respondent-specific effects by
    fitting a random-effects regression model (Raudenbush and
    Bryk 2002, p. 23), in which the composite score of each
    respondent on each concept served as the dependent
    variable and the independent variables were three dummy
    variables representing the four concepts. The dummy
    variable we left out was the concept the high emergent
    nature group developed (for model specification, see the
    Web Appendix, “Study 2b Model Details,” at http://www.
    marketingpower.com/jmroct10). We tested model signifi-
    cance by comparing the full model with a null model that
    includes the intercept and respondent-specific effects.
    The results reveal that the full model performs signifi-
    cantly better than the corresponding null model (N = 2524;
    –2 log-likelihood = 14,358.9;Akaike information criterion =
    14,362.9; χ 2 = 255.4, p < .001). The SmartBox concept the
    high emergent group developed was rated significantly
    higher than the lead user (by .58 units, p < .01), innovative-
    ness (by 2.37 units, p < .001), and control (by 3.04 units,
    p < .0001) concepts. Note that we can also account for
    respondent-level effects through ordinary least squares
    regressions with 3 dummy variables representing the four
    product concepts and either 630 dummies for the 631 partici-
    pants or the mean response for each respondent across the
    four concepts as another independent variable. In both analy-
    ses, we obtained results similar to those reported previously.
    Study 2c: Concept Evaluation
    To further understand consumer preference for the emer-
    gent nature and lead user concepts, two independent sam-
    ples of native English-speaking adult consumers randomly
    selected from a global online panel evaluated the high emer-
    gent nature concept (N = 97) and the lead user concept (N =
    95) (for sampling details, see the Web Appendix, “Study 2c
    Sampling Details,” at http://www.marketingpower.com/
    jmroct10). In each sample, consumers evaluated the concept
    on 15 attributes derived from a convenience sample of 25
    MBA students who read the basic SmartBox concept
    description and generated a list of potential product attrib-
    utes that would be relevant for such a product. Conceptu-
    ally, this approach is consistent with practice in large con-
    sumer goods companies when using a battery of questions
    in new product testing.
    Respondents rated the high emergent nature concept sig-
    nificantly higher than the high lead user concept on 11
    attributes (p < .01, p < .05, and p < .1 on 4, 9, and 11 attrib-
    utes, respectively). There were no significant differences on
    the remaining 4 attributes. A two-factor solution from a fac-
    tor analysis of the attribute ratings explained 73.4% of the
    variation. (We obtained similar factor structures when we
    factor-analyzed the ratings for each concept separately.) In
    general, the two dimensions can be interpreted as “utilitar-
    ian” (is easy to use, is secure, prevents breakage, keeps cold
    foods cold, can use anytime, is waterproof, is sturdy, is con-
    venient, has a unique design, is safe to use) and “hedonic”
    (is fun to use, looks good, saves money, saves time, is easy
    to install). A regression analysis of the factor scores showed
    that respondents rated the high emergent nature concept sig-
    nificantly higher than the high lead user concept (p < .05)
    on both factors, indicating that the high emergent nature
    concept provided more utilitarian and hedonic benefits than
    the high lead user concept. Figure 1 plots the attribute
    means for the two concepts.
    STUDY 3: INDIVIDUAL CONCEPT DEVELOPMENT
    AND MARKET TESTING
    Studies 2a–2c demonstrated in a group setting that peo-
    ple high in emergent nature together produced a home deliv-
    ery concept that was subsequently rated significantly higher
    than concepts produced by groups of people high in lead
    user status or innovativeness or average on all three con-
    structs. Because the groups’concepts were not standardized
    for length or style, we cannot rule out a confound with pres-
    entation. Our objective in Studies 3a and 3b is to simulate
    the concept development and market-testing process at the
    individual level in another category (a frequently purchased
    consumer packaged good) while controlling for concept
    presentation effects and individual differences in lead user
    status, emergent nature, innovativeness, involvement, and
    expertise.
    Study 3a: Individual Concept Development
    A large consumer packaged goods firm provided a basic
    description of a new product idea in the oral care category
    that could benefit from further concept development before
    market testing. One hundred eighty-five adult native
    English-speaking consumers purchased from a commercial
    research panel further developed a concept for “Orion” den-
    tal spray by completing a “fill-in-the-blanks” task using a
    concept development template. A professional concept
    development expert, blind to the study hypotheses, with sig-
    nificant experience working for large retail clients con-
    structed the template (see Appendix C) for the purposes of
    this study. Respondents were instructed to further develop
    the basic idea for the dental spray concept so that typical
    consumers would find it as appealing as possible and want
    to buy it. After the concept development task, we measured
    respondents’emergent nature, lead user status, and disposi-
    tional innovativeness, along with category involvement and
    expertise.
    We used a defined procedure to systematically combine
    and standardize the 185 individually developed dental spray
    concepts into four separate concept descriptions for the high
    emergent nature, high lead user status, high dispositional
    innovativeness, and control groups. We categorized each
    respondent into one of the four mutually exclusive groups
    according to their median scores on emergent nature, dispo-
    sitional innovativeness, and lead user scales. The high emer-
    gent nature group (N = 16) contained respondents above the
    median on emergent nature and below the median on dispo-
    sitional innovativeness and lead user status, the high lead
    user group (N = 13) contained respondents above the
    median on lead user status and below the median on high
    emergent nature and innovativeness, and the high innova-
    tiveness group (N = 21) contained respondents above the
    median on innovativeness and below the median on the
    other two. The control group (N = 54) consisted of respon-
    dents who scored at the median on all three scales. We did
    not include the remaining 81 respondents in subsequent
    analyses.
    We randomly selected the concept description templates
    for 12 respondents from each group for further analysis, and
    a research assistant, blind to the study’s hypotheses and
    group identification, independently evaluated them. 2 The
    researcher recorded the benefits identified in each respon-
    dent’s template, summarizing the unique benefits that each
    group mentioned as well as benefits that were commonly
    mentioned across all groups. Using the concept-writing
    template the professional expert developed, which specified
    how to integrate benefits to arrive at an overall concept
    description, the research assistant wrote dental spray con-
    cept descriptions for each group based on the unique bene-
    fits mentioned by that group. We used the common benefits
    mentioned across groups (quick, convenient, and on the go)
    to update the basic description of the dental spray. The pro-
    fessional expert and the research assistant, still blind to the
    study’s hypotheses and group identities, separately reviewed
    each group’s concept description against the list of benefits
    and templates to ensure that the descriptions accurately cap-
    tured the unique benefits each group identified. The basic
    description was similarly reviewed to ensure that it captured
    the common benefits mentioned across all groups. The pro-
    cedure produced four concept descriptions that were equiva-
    lent with respect to length and style but unique with respect
    to benefits identified. The final Orion dental spray concepts
    appear inAppendix D.
    Study 3b: Concept Testing
    An independent sample of 207 adult native English-
    speaking consumers purchased from a commercial research
    panel evaluated the four concepts in a within-group study.
    860 JOURNAL OF MARKETING RESEARCH, OCTOBER 2010
    2 Recent research (Dahl and Moreau 2007) finds that having 12 respon-
    dents produces “data saturation,” uncovering 97% of the themes and 92%
    of the total number of codes used in qualitative transcripts (Guest, Bunce,
    and Johnson 2006). Similarly, a widely applied model developed in usabil-
    ity engineering research (Nielsen and Landauer 1993) shows that 12 users
    are highly diagnostic for testing, uncovering 90% of the usability problems
    in a design.
    Figure 1
    MEAN RATINGS FOR THE STUDY 2C EMERGENT NATURE
    AND LEAD USER SMARTBOX CONCEPTS ON 15 PRODUCT-
    RELEVANT ATTRIBUTES
    8
    7.5
    7
    6.5
    6
    5.5
    5
    4.5
    4
    Unique
    Anytime
    Secure
    Conv
    Sturdy
    Safe
    Easy
    Wproof
    Time
    Cold
    Prevents
    Looks
    Fun
    Install
    Money
    Lead user, n = 95
    Emergent, n = 97
    Notes: Utilitarian attributes appear in bold.
    The “Right” Consumers for Better Concepts 861
    We counterbalanced the concepts to control for order
    effects. We instructed respondents to carefully review the
    four different concepts, identified only by number, and then
    indicate which concept was most and least appealing.
    Respondents rated their attitudes toward each concept on
    four standard concept-testing scales (bad/good, dislike/like,
    dull/dynamic and not useful/useful), along with their
    involvement with and knowledge of oral care and their fre-
    quency of oral care. For each concept, we also collected
    purchase intention and purchase frequency likelihood; three
    standard concept-testing items (different, believable, and
    solves a problem) adapted from Dolan (1993); and five
    items adapted from Rogers’s (2003) innovation dimensions
    of relative advantage, compatibility, complexity, observabil-
    ity, and trialability. We also measured respondents’ emer-
    gent nature, domain-specific lead user status, and disposi-
    tional innovativeness.
    Participants reported moderate levels of involvement with
    and knowledge of oral care (4.3 and 3.8, respectively, on a
    seven-point scale); almost all participants reported using
    toothpaste at least once a day. As in Study 2b, we standard-
    ized and summed the original six-item concept-testing scale
    to create a composite score for each respondent and used
    those to construct scales for each of the four concepts. Coef-
    ficient alphas were uniformly high (control α = .822, high
    lead user α = .878, high innovativeness α = .844, and high
    emergent nature α = .864). A repeated measures ANOVA
    revealed a significant main effect (F = 19.081, p = .000) on
    the concept-testing scale, with the high emergent concept
    (M = 1.80) being a more highly rated concept than the high
    lead user (M = .26), high innovativeness (M = –.43), and
    control group (M = –1.11) concepts. In addition, as Figure 2
    shows, the concept developed by high emergent nature
    respondents was consistently rated higher than the concepts
    developed by high lead users, those high in dispositional
    innovativeness, and those in the control group on all three
    concept-testing scales and all five innovation scales, particu-
    larly purchase likelihood.
    We fit a random-effects regression analysis to account for
    respondent-specific effects using the composite score of
    each respondent for each concept as the dependent variable.
    The independent variables were three dummy variables rep-
    resenting the four concepts. The dummy variable we left out
    was the concept developed by the respondents high in emer-
    gent nature. To control for observed heterogeneity (the
    random-effects regression model we fit accounts for unob-
    served heterogeneity), we also included covariates to con-
    trol for lead user status, emergent nature, dispositional inno-
    vativeness, involvement, knowledge of oral care, gender,
    and age (for model specification, see the Web Appendix,
    “Study 3b Model Details,” at http://www.marketingpower.
    com/jmroct10). The results show that the full model per-
    forms significantly better than the corresponding null model
    that includes the intercept and respondent-specific effects
    (N = 828; –2 log-likelihood = 4808;Akaike information cri-
    terion = 4812.0; χ 2 = 53.9, p < .001). As we predicted, the
    oral care concept developed by respondents high in emergent
    nature was rated significantly higher than the lead user (by
    2.06 units, p < .001), innovativeness (by 2.23 units, p < .001)
    and control (by 2.90 units, p < .001) concepts. Only the
    covariate for emergent nature was significant (p < .05); con-
    sumers high on emergent nature were more likely to rate the
    oral care concepts more highly than other consumers. We
    obtain similar model results when we treat all three concept-
    testing scales and all five innovation scales as dependent
    variables; that is, the emergent nature concept was signifi-
    cantly better than the other concepts on all measures.
    GENERAL DISCUSSION
    In this article, we argued that consumers with an emer-
    gent nature—the unique capability to envision how new
    product concepts might be developed—can be identified
    and used in business-to-consumer markets to further
    improve new product concepts so that they will be success-
    ful in the marketplace. To test our predictions, in Study 1,
    we developed a highly reliable and valid scale based on psy-
    chological theories of human information processing and
    trait-based personality to measure the emergent nature con-
    struct. This study distinguished the emergent nature con-
    struct from domain-specific lead user status and the disposi-
    tional innovativeness trait, as well as related personality
    traits and information-processing styles, such as openness
    to new experiences, reflection, verbal and visual processing
    Figure 2
    MEAN CONCEPT EVALUATION RATINGS FOR THE STUDY 3B
    ORAL CARE CONCEPTS DEVELOPED BY PARTICIPANTS HIGH
    IN EMERGENT NATURE, DISPOSITIONAL INNOVATIVENESS,
    AND LEAD USER STATUS ALONG WITH A CONTROL GROUP
    6.5
    6
    5.5
    5
    4.5
    How Different Is the New Product?
    New Product is Easy to Try
    New Product is Easy to Understand
    and Use
    New Product Would Solve a Problem
    Currently Not Being Addressed
    New Product’s Benefits Are Easy to
    Observe
    Purchase Likelihood
    New Product Is Improvement over
    Current Oral Care Product
    New Product Fits Current Oral Care
    Routine
    Purchase Frequency Likelihood
    How Believable Is the New Product?
    High emergent nature
    High disposational innovativeness
    High lead user status
    Control group
    styles, experiential and rational thinking styles, creativity,
    and optimism.
    In two multipart studies in group and individual concept
    development contexts in the distinct categories of home
    delivery (Study 2) and oral care (Study 3), we used the
    emergent nature scale to test the prediction that mainstream
    consumers would find product concepts that were further
    developed by the “right” consumers (i.e., those high on
    emergent nature) to be significantly more appealing (and
    have a higher purchase likelihood) than concepts developed
    by lead users, consumers high on dispositional innovative-
    ness, and average consumers. The results supported the pre-
    dictions and established the predictive validity of the emer-
    gent nature construct.
    Consumers high in emergent nature may have the ten-
    dency to emphasize utilitarian attributes in their improved
    product concepts compared with high lead users. Using data
    from Study 2c, Figure 1 shows the attributes ordered in
    terms of mean emergent nature concept ratings from highest
    (on the left) to lowest (on the right). The attributes clearly
    form two groups with utilitarian attributes (shown in bold)
    mainly on the left and hedonic attributes on the right. On
    average, the gap between the emergent nature and lead user
    mean ratings is larger for the utilitarian attributes. For the
    concepts in Appendix D, which is based on results from
    Study 3a, we note that the emergent nature concept men-
    tions “Approved by the American Dental Association” and
    the “patented fluoride mixture.” None of the respondents in
    the other conditions mentioned these utilitarian attributes. 3
    It might be fruitful to explore this observation in further
    research.
    Because we also developed a reliable and useful scale to
    measure lead user status in consumer-specific domains,
    researchers might also find value in further exploring the
    lead user construct in consumer contexts. The concepts
    developed by high lead users also fared well, though not as
    well as those developed by consumers high on emergent
    nature. This lends face validity to the results and reinforces
    research arguing that lead users represent a useful segment
    for developing new product concepts (Von Hippel 1986).
    How does emergent nature influence the ability to further
    develop product concepts? We believe that because of their
    openness to new experiences, reflection, verbal and visual
    processing styles, experiential and rational thinking styles,
    creativity, and optimism, consumers high in emergent
    nature are able to engage both in a process of successful
    idea generation to enhance original concepts and in logical
    analysis to refine and develop concepts further. We theorize
    an underlying process in which consumers with a high
    emergent nature develop an intuitive, almost “instinctual,”
    understanding of new concepts, for example, by visualizing
    latent uses through a sequence of affective and associative
    perceptions, and they also engage in logical and analytical
    efforts to evaluate and refine the concepts. These processes
    may work together in a complementary and iterative way
    such that a rational effort to analyze a product concept may
    activate further implicit experiential associations with that
    concept, followed by another round of rational analysis, and
    so on. The essence of our conceptualization of emergent
    nature is that consumers who have this skill are able to
    imagine or visualize new product concepts that may best fit
    typical consumers’needs and correspondingly inform their
    experiential impressions and associations with evaluative
    judgments, and vice versa. It may prove to be a particularly
    fruitful line of future inquiry to explore the synergistic
    action of these processes.
    Although the results, which are based on two product
    categories and individual and group settings, are promising,
    they are not without limitations. We tested the product
    concepts using written descriptions rather than physical pro-
    totypes, though descriptions are typically used for many
    concept-testing studies in which prototypes would be cost
    prohibitive. It would be important to show that actual prod-
    ucts based on concepts developed by consumers high in
    emergent nature are ultimately found to be more appealing
    and lead to greater sales than those developed by other types
    of consumers. This is a worthwhile area for further research,
    and this article provides the first step in identifying and
    using emergent consumers to develop new products. A
    related limitation is that we performed the studies in labora-
    tory settings. Because our primary goals were to demon-
    strate that emergent nature can be reliably and validly meas-
    ured and that concepts developed by consumers high in
    emergent nature would appeal most to typical consumers,
    laboratory settings are appropriate for this first demonstra-
    tion. Nonetheless, further research should attempt to repli-
    cate the results in multiple and diverse field settings.
    In addition, our focus was limited to consumers who were
    exclusively high in emergent nature, lead user status, or dis-
    positional innovativeness (along with control groups of
    average consumers). Although we believe that our results
    support the contention that consumers high in emergent
    nature are the “right” consumers to use in product concept
    development, we cannot make the claim that they are the
    “best.” Further research should examine which combina-
    tions of consumers with these unique capabilities are best
    for particular product concept development tasks and how
    these combinations (e.g., high only on emergent nature,
    high on both emergent nature and lead user status, high on
    both emergent nature and dispositional innovativeness, high
    on all three constructs) compare with one another.
    From a managerial perspective, this research comple-
    ments current concept-testing methods and could improve
    their effectiveness because the results suggest that concepts
    developed by consumers high in emergent nature may have
    a higher likelihood of ultimate success with mainstream
    customers. Identifying and employing such consumers in
    the concept development process may act as an “early warn-
    ing system” when products have the potential to be disrup-
    tive (Chandy and Tellis 1998). The results also provide
    direction to firms striving to adopt a positive orientation
    toward emergent customer segments (Govindarajan and
    Kopalle 2004), but they are less clear about how firms can
    identify such customers.Although much work remains to be
    done, the idea of identifying and using consumers high on
    emergent nature in the development of new products is
    viable and worthy of the effort required to understanding it
    more fully.
    862 JOURNAL OF MARKETING RESEARCH, OCTOBER 2010
    3 We thank two anonymous reviewers for suggesting we explore this
    insight.
    The “Right” Consumers for Better Concepts 863
    APPENDIX A: THE SMARTBOX PRODUCT CONCEPT
    Now we’d like you to evaluate a new product concept
    called the “SmartBox.” The SmartBox is depicted in the
    drawing below.
    Regardless of whether it’s laundry, dry cleaning, gro-
    ceries, or most anything else, the SmartBox should make
    home pickup and delivery secure and convenient even if no
    one is home.
    Presuming you had a choice of many styles, sizes, and
    installation locations, please imagine that a device similar
    to this is on, by, or close to your home—or, if you live in an
    apartment, that a cluster of them is by your building. Sup-
    pose that FedEx, UPS, and the Postal Service as well as gro-
    cers, dry cleaners, and anyone else you want to authorize
    could use it to make secure pickups and deliveries. Built-in
    intelligence enables authorized deliveries only and sends
    notification to both consumer and merchant whenever a
    delivery is made.
    Thinking about the SmartBox concept, please answer the
    questions below.
    APPENDIX B: SMARTBOX BASIC DESCRIPTION AND
    FINAL CONCEPTS PRODUCED BY THE FOUR
    GROUPS IN STUDY 2A
    Basic Description
    The SmartBox is a new device that enables secure and
    convenient delivery and home pickup of almost anything
    that can be delivered to the home (e.g., groceries and laun-
    dry and many other things). Many different styles are possi-
    ble and there are many different locations the SmartBox
    could be located in many different types of dwellings. The
    device is “smart” because it needs a code to be opened, so
    only people with authorization (like the person at home and
    the delivery person) can open it. It also tracks who delivered
    what and when and keeps a record of deliveries.
    Control Group Final Concept
    The SmartBox should be very easy to install and big
    enough to fit a few bags of groceries in it at least. It should
    be easy to get access to for the delivery person and the per-
    son at home by having a scanner for the delivery person and
    a code the person at home enters to open it. The main thing
    is convenience; if the SmartBox is not a convenience no one
    will use it. It must be easy to use so that most any age can
    do it, so there can’t be a lot of instructions one wants to get
    access or to install it.
    High Lead User Status Final Concept
    For new homes, the SmartBox can be built to blend with
    the appearance of the home. Shelves inside the unit collapse
    upward to have room inside for large items. The SmartBox
    can send an e-mail or text message to a mobile phone when
    a delivery has occurred. The SmartBox can also be built
    with a door opening from within the home so that it can be
    opened from inside. It has a freezer/refrigerator section for
    cold or frozen food deliveries and a built-in clothes hanger
    rack for laundry deliveries. It is easy for the owner to
    change the security code; the SmartBox has an alarm sys-
    tem that either sounds an audible alarm or sends a signal to
    the police in the event a thief tries to gain access.
    High Dispositional Innovativeness Final Concept
    The SmartBox can be insulated for perishables and is
    available in various designs. There is a SmartBox “profes-
    sional edition” that is customizable for businesses. The
    SmartBox is connected to e-mail or wireless communica-
    tion to the cell phone, sending an alert when packages have
    been delivered. A keypad allows all authorized “users” to
    easily access it. Authorized users would be given the code
    by the owner upon purchase of the item to be delivered. The
    SmartBox is sturdy, reliable, but not a permanent fixture.
    High Emergent Nature Final Concept
    The SmartBox is offered in various sizes and is accessi-
    ble from either the outside or the inside of the home or
    apartment for convenience in retrieving deliveries. Each
    delivery is uniquely computer coded with a randomly gen-
    erated computer code that expires soon after the delivery
    person accesses the SmartBox; retrieval of items by the
    owner is also via a unique code, with the option of using a
    key as well, again for convenience. The SmartBox is incon-
    spicuous, fire proof, vandalism proof, rust resistant, and is
    available with options such as multiple compartments,
    refrigeration and an alarm mechanism similar to car alarms.
    The SmartBox is affordable and has purchase incentives and
    installation incentives for first-time customers.
    APPENDIX C: “FILL-IN-THE-BLANKS” PRODUCT
    CONCEPT TEMPLATE FROM STUDY 3A
    Basic Idea for Project Orion
    Orion dental spray is a new way to clean your teeth with-
    out brushing. Instead of brushing, spray!Assume Orion will
    be available in a variety of sizes at reasonable prices at the
    stores people normally shop at.
    Fill-in-the-Blanks Concept Development for Project Orion:
    A New Oral Care Project
    (Project Sahara example is here if you need help)
    Now take your concept development ideas and put them
    together into a few sentences. If you need some help getting
    started, just click here to see the Project Sahara example.
    Your Project Orion Concept Description (limit 100 words)
    APPENDIX D: ORION DENTAL SPRAY BASIC
    DESCRIPTION AND FINAL CONCEPTS PRODUCED BY
    THE CONSUMERS IN STUDY 3A
    Basic Description
    Introducing Orion Dental Spray—the quick and conven-
    ient way to clean your teeth and have fresh breath without
    brushing. You can also carry the spray in your pocket or
    purse when you go out. Assume Orioin will be available at
    regular retail outlets in a variety of sizes at reasonable
    prices.
    Control Group
    Orion is easy for children to use and is more sanitary than
    using a toothbrush and toothpaste combination. It also
    works longer than regular brushing—you no longer have to
    worry about the toothpaste taste in your mouth and there is
    no need to use water with the spray. Orion is mess free.
    High Lead User Status
    Orion eliminates the issues associated with using a
    brush—bleeding gums and scraping away the enamel—
    plus, you can do away with the toothbrush, which can har-
    bor germs and bacteria. Use after any meal or snack
    throughout the day for a clean and fresh tasting mouth.
    Orion is a must for dentures.
    High Dispositional Innovativeness
    Orion is an easy way to “brush” your teeth and children
    can take better care of their teeth almost anywhere. Instead
    of brushing your teeth and risk not doing it long enough,
    you can simply spray your teeth clean. Orion is mess free
    and its minty flavor tastes great and eliminates the use of
    mouthwash.
    High Emergent Nature
    Orion simply sprays away plaque and tartar with the flexi-
    ble nozzle that directs the spray to places toothbrush can
    1.Why people will find Orion
    appealing. That is, what are its
    primary benefits? (up to 3)
    2.Why people will believe that
    Orion will deliver benefit 1.
    3.Why people will believe that
    Orion will deliver benefit 2.
    4.Why people will believe that
    Orion will deliver benefit 3.
    5.Additional features, if any
    (up to 3)
    miss—the longer lasting, fresher breath feels refreshing in
    two great flavors. Approved by American Dental Associa-
    tion (ADA), the patented fluoride mixture can also
    strengthen your tooth enamel with regular use.
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