{"id":2923,"date":"2026-09-12T20:54:22","date_gmt":"2026-09-12T20:54:22","guid":{"rendered":"http:\/\/ashadocs.org\/scales\/attitude-toward-a-purchase-offer-apo\/"},"modified":"2026-09-12T20:54:22","modified_gmt":"2026-09-12T20:54:22","slug":"attitude-toward-a-purchase-offer-apo","status":"publish","type":"psych_scale","link":"https:\/\/ashadocs.org\/?psych_scale=attitude-toward-a-purchase-offer-apo","title":{"rendered":"Attitude Toward a Purchase Offer (APO)"},"content":{"rendered":"<h2>Abstract<\/h2>\n<p>The <strong>Attitude Toward a Purchase Offer (APO)<\/strong> scale is a concise, three-item self-report psychometric instrument designed to assess a consumer&#8217;s affective evaluation, personal liking, and subjective satisfaction regarding a specific promotional, pricing, or product offer. Originally operationalized and validated by <a href=\"https:\/\/doi.org\/10.1093\/jcr\/ucy074\" target=\"_blank\" rel=\"noopener noreferrer\">Fan, Li, and Jiang (2019)<\/a> across a multi-study investigation into consumer decision-making under conditions of resource scarcity, the instrument integrates theoretical insights from anchoring phenomena and negotiation dynamics (<a href=\"https:\/\/doi.org\/10.1037\/pspi0000016\" target=\"_blank\" rel=\"noopener noreferrer\">Ames &amp; Mason, 2015<\/a>). The instrument utilizes a unidimensional structure evaluated via a 7-point <a href=\"https:\/\/en.wikipedia.org\/wiki\/Likert_scale\" target=\"_blank\" rel=\"noopener noreferrer\">Likert scale<\/a> ranging from 1 (&#8220;strongly disagree&#8221;) to 7 (&#8220;strongly agree&#8221;). Psychometric analyses across multiple experimental datasets\u2014primarily drawn from adult consumer cohorts within the United States via Amazon Mechanical Turk\u2014demonstrate exemplary internal consistency reliability (with <a href=\"https:\/\/en.wikipedia.org\/wiki\/Cronbach%27s_alpha\" target=\"_blank\" rel=\"noopener noreferrer\">Cronbach&#8217;s alpha<\/a> coefficients consistently exceeding .90) and robust convergent, discriminant, and predictive validities. The scale demonstrates particular utility in marketing psychology, behavioral economics, and consumer judgment research, specifically in experiments measuring shifts in valuation driven by range promotional framing, price discounts, and transactional contexts.<\/p>\n<h2>Keywords<\/h2>\n<p>Attitude Toward a Purchase Offer, APO scale, consumer evaluation, promotional framing, resource scarcity, range offers, price perception, behavioral pricing, consumer decision-making, transaction utility, psychometrics<\/p>\n<h2>Authors<\/h2>\n<p>The Attitude Toward a Purchase Offer (APO) measure was formalized and implemented by:<\/p>\n<ul>\n<li><strong>Liyin Fan<\/strong> &mdash; Assistant Professor of Marketing, Department of Marketing, Chinese University of Hong Kong (Shenzhen) \/ University of Macau.<\/li>\n<li><strong>Xiuping Li<\/strong> &mdash; Associate Professor of Marketing, NUS Business School, National University of Singapore.<\/li>\n<li><strong>Ying Jiang<\/strong> &mdash; Associate Professor of Marketing, Faculty of Business Administration, University of Macau.<\/li>\n<\/ul>\n<p>The scale development also drew conceptual foundations from the prior work on tandem range offers and negotiation pricing conducted by <strong>Daniel R. Ames<\/strong> (Columbia Business School, Columbia University) and <strong>Malalane F. Mason<\/strong> (Columbia Business School, Columbia University).<\/p>\n<h2>Purpose<\/h2>\n<p>The primary purpose of the Attitude Toward a Purchase Offer (APO) scale is to deliver a swift, psychometrically sound, and theoretically sensitive measurement of a consumer&#8217;s overall evaluative response toward an explicit purchasing proposal. In contemporary consumer psychology and quantitative marketing research, experimental protocols frequently subject participants to varied framing configurations\u2014such as point-price promotions (e.g., &#8220;Save $10&#8221;) versus range-price promotions (e.g., &#8220;Save between $5 and $15&#8221;), discount packaging, bundling strategies, or tiered loyalty reward incentives. Researchers required a standardized, low-burden metric capable of detecting subtle experimental variance in offer favorability without inducing cognitive fatigue or hypothesis guessing.<\/p>\n<p>Beyond commercial marketing applications, the APO scale serves vital research functions in behavioral economics and judgment and decision-making (<a href=\"https:\/\/en.wikipedia.org\/wiki\/Judgment_and_decision-making\" target=\"_blank\" rel=\"noopener noreferrer\">JDM<\/a>). It quantifies the psychological appraisal of economic exchanges, isolating transactional attractiveness from broader brand equity or product utility. By focusing strictly on the &#8220;offer&#8221; itself, the scale captures consumers&#8217; immediate hedonic and evaluative impressions at the moment of prospective transaction appraisal.<\/p>\n<p>From an applied perspective, the tool is extensively employed in pre-testing sales promotions, measuring willingness-to-transact thresholds, and evaluating the psychological viability of novel pricing schemes across varied socioeconomic segments. Its brevity ensures seamless integration into complex experimental designs containing multiple factorial interventions, cognitive tasks, or longitudinal monitoring.<\/p>\n<h2>Psychological Construct<\/h2>\n<p>The construct captured by the APO scale is <em>offer-specific evaluative attitude<\/em>, defined as a consumer&#8217;s psychological tendency to evaluate a particular commercial proposal with some degree of favor or disfavor. Within classical social psychology, an attitude represents an enduring organization of motivational, emotional, perceptual, and cognitive processes with respect to some aspect of the individual&#8217;s world (<a href=\"https:\/\/en.wikipedia.org\/wiki\/Attitude_(psychology)\" target=\"_blank\" rel=\"noopener noreferrer\">Eagly &amp; Chaiken, 1993<\/a>). When applied to promotional consumer contexts, this construct must be carefully distinguished from adjacent constructs:<\/p>\n<ul>\n<li><strong>Attitude Toward the Brand (<span class=\"arabpsy-math-inline\" data-latex=\"A_{Br}\">$A_{Br}$<\/span>):<\/strong> Reflects global, enduring evaluations of a firm or trade name, driven by historical brand associations, reputation, and perceived corporate identity. In contrast, the APO construct is transient, contextual, and strictly anchored to the specific offer terms presented.<\/li>\n<li><strong>Attitude Toward the Ad (<span class=\"arabpsy-math-inline\" data-latex=\"A_{Ad}\">$A_{Ad}$<\/span>):<\/strong> Measures reactions to execution-related elements of marketing communications, such as aesthetic qualities, humor, or spokespersons. APO isolates the financial and propositional value proposition from communication vehicle aesthetics.<\/li>\n<li><strong>Perceived Product Quality:<\/strong> Denotes evaluations of physical functionality, longevity, and craftsmanship. A consumer may regard a product&#8217;s quality as exceptionally high while simultaneously expressing an unfavorable attitude toward an overpriced or poorly structured purchase offer.<\/li>\n<li><strong>Transaction Utility:<\/strong> Conceptualized by <a href=\"https:\/\/en.wikipedia.org\/wiki\/Richard_Thaler\" target=\"_blank\" rel=\"noopener noreferrer\">Richard Thaler (1985)<\/a> as the perceived merit or deal-value of a transaction, measured against an internal reference price. APO captures both this cognitive evaluation and the resultant positive affective reaction.<\/li>\n<\/ul>\n<p>The APO scale operationalizes this construct across three tightly interlocked dimensions of favorable appraisal: general affinity (liking), valence orientation (feeling positive), and hedonic fulfillment (feeling happy). These items converge into a unified cognitive-affective index indicating the overall attractiveness and subjective desirability of the transactional terms.<\/p>\n<h2>Theoretical Framework<\/h2>\n<p>The development and deployment of the APO scale are grounded in multiple converging theoretical streams within cognitive psychology and behavioral decision theory:<\/p>\n<h3>1. Resource Scarcity Theory<\/h3>\n<p>A central theoretical premise behind the scale&#8217;s empirical validation in <a href=\"https:\/\/doi.org\/10.1093\/jcr\/ucy074\" target=\"_blank\" rel=\"noopener noreferrer\">Fan et al. (2019)<\/a> is the psychology of scarcity (<a href=\"https:\/\/doi.org\/10.1126\/science.1222426\" target=\"_blank\" rel=\"noopener noreferrer\">Mullainathan &amp; Shafir, 2013<\/a>). When individuals experience a subjective sense of resource deprivation (e.g., financial constraint), their attentional mechanisms narrow, prioritizing immediate utility, efficiency, and room for economic opportunity. Fan and colleagues established that resource scarcity induces consumers to evaluate range marketing offers (e.g., &#8220;Get 10% to 30% off&#8221;) significantly more favorably than single-point offers, because ranges signal greater &#8220;room for opportunity.&#8221; The APO scale acts as the operational conduit measuring this psychological elevation in offer attractiveness.<\/p>\n<h3>2. Tandem Anchoring and Negotiation Framing<\/h3>\n<p>The conceptual genesis of the APO measure draws upon <a href=\"https:\/\/doi.org\/10.1037\/pspi0000016\" target=\"_blank\" rel=\"noopener noreferrer\">Ames and Mason&#8217;s (2015)<\/a> work on range offers. When presented with offer intervals rather than static values, human cognitive systems process multiple anchors simultaneously. An offer interval evokes distinct informational and polite inferences. The APO scale quantifies the net subjective balance resulting from these cognitive computations, determining whether the presented terms trigger satisfaction or cognitive resistance.<\/p>\n<h3>3. Mental Accounting and Framing Effects<\/h3>\n<p>Under <a href=\"https:\/\/en.wikipedia.org\/wiki\/Mental_accounting\" target=\"_blank\" rel=\"noopener noreferrer\">Mental Accounting Theory<\/a> (<a href=\"https:\/\/doi.org\/10.1287\/mksc.4.3.199\" target=\"_blank\" rel=\"noopener noreferrer\">Thaler, 1985<\/a>) and <a href=\"https:\/\/en.wikipedia.org\/wiki\/Prospect_theory\" target=\"_blank\" rel=\"noopener noreferrer\">Prospect Theory<\/a> (<a href=\"https:\/\/doi.org\/10.2307\/1914185\" target=\"_blank\" rel=\"noopener noreferrer\">Kahneman &amp; Tversky, 1979<\/a>), the psychological coding of financial outlays determines consumers&#8217; emotional equilibrium. Framing a price adjustment as a gain versus an avoided loss alters its cognitive coding. The APO scale directly captures the emotional dividend of this coding: when an offer aligns beneficially with a consumer&#8217;s internal reference points, it manifests as heightened scores on positive affect and liking.<\/p>\n<h2>Validity<\/h2>\n<p>The construct, convergent, discriminant, and predictive validities of the APO scale have been established across empirical marketing investigations totaling several thousand participants:<\/p>\n<h3>Construct and Convergent Validity<\/h3>\n<p>Construct validity is evidenced by high item-to-total correlations (typically exceeding <span class=\"arabpsy-math-inline\" data-latex=\"r = .82\">$r = .82$<\/span>) and substantial average variance extracted (<a href=\"https:\/\/en.wikipedia.org\/wiki\/Average_variance_extracted\" target=\"_blank\" rel=\"noopener noreferrer\">AVE<\/a>), consistently surpassing .75. The scale correlates strongly and positively with related evaluative metrics, including purchase intention (<span class=\"arabpsy-math-inline\" data-latex=\"r = .65\">$r = .65$<\/span> to <span class=\"arabpsy-math-inline\" data-latex=\".78\">$.78$<\/span>), perceived transaction value (<span class=\"arabpsy-math-inline\" data-latex=\"r = .70\">$r = .70$<\/span> to <span class=\"arabpsy-math-inline\" data-latex=\".82\">$.82$<\/span>), and willingness-to-recommend (<span class=\"arabpsy-math-inline\" data-latex=\"r = .58\">$r = .58$<\/span> to <span class=\"arabpsy-math-inline\" data-latex=\".71\">$.71$<\/span>). These significant associations confirm that the scale captures the intended motivational and evaluative core of consumer deal appreciation.<\/p>\n<h3>Discriminant Validity<\/h3>\n<p>Discriminant validity was established via confirmatory factor analyses against adjacent constructs. In multi-trait modeling, the correlation between the APO construct and general brand attitude (<span class=\"arabpsy-math-inline\" data-latex=\"A_{Br}\">$A_{Br}$<\/span>) remained moderate (<span class=\"arabpsy-math-inline\" data-latex=\"r \\approx .35\">$r \\approx .35$<\/span> to <span class=\"arabpsy-math-inline\" data-latex=\".45\">$.45$<\/span>), demonstrating that consumers clearly distinguish their evaluation of an immediate transaction proposal from their overarching feelings toward the issuing corporation. Similarly, the square root of the AVE for the APO scale consistently exceeds its shared variance with product category involvement and general price consciousness, satisfying the <a href=\"https:\/\/en.wikipedia.org\/wiki\/Fornell%E2%80%93Larcker_criterion\" target=\"_blank\" rel=\"noopener noreferrer\">Fornell-Larcker criterion<\/a>.<\/p>\n<h3>Predictive and Experimental Validity<\/h3>\n<p>In the primary empirical validation across five controlled experiments by Fan, Li, and Jiang (2019), the APO scale proved highly sensitive to subtle experimental manipulations. For example, in Study 1, participants exposed to a scarcity priming condition reported significantly higher attitudes toward range offers (<span class=\"arabpsy-math-inline\" data-latex=\"M = 5.62, SD = 1.08\">$M = 5.62, SD = 1.08$<\/span>) compared to point offers (<span class=\"arabpsy-math-inline\" data-latex=\"M = 4.95, SD = 1.34; F(1, 196) = 15.08, p &lt; .001\">$M = 4.95, SD = 1.34; F(1, 196) = 15.08, p &lt; .001$<\/span>), while baseline control participants showed no such differential preference. The instrument systematically predicted behavioral downstream consequences, such as actual coupon redemption and store visit selections.<\/p>\n<h2>Reliability<\/h2>\n<p>The Attitude Toward a Purchase Offer scale demonstrates high internal consistency across diverse empirical contexts, sample demographics, and promotional categories:<\/p>\n<ul>\n<li><strong>Internal Consistency:<\/strong> In the foundational series of studies conducted by <a href=\"https:\/\/doi.org\/10.1093\/jcr\/ucy074\" target=\"_blank\" rel=\"noopener noreferrer\">Fan et al. (2019)<\/a>, Cronbach&#8217;s alpha (<span class=\"arabpsy-math-inline\" data-latex=\"\u0007lpha\">$\u0007lpha$<\/span>) coefficients were computed independently across five distinct empirical studies:\n<ul>\n<li>Study 1: <span class=\"arabpsy-math-inline\" data-latex=\"\u0007lpha = .93\">$\u0007lpha = .93$<\/span> (<span class=\"arabpsy-math-inline\" data-latex=\"N = 200\">$N = 200$<\/span>, U.S. adult consumers)<\/li>\n<li>Study 2: <span class=\"arabpsy-math-inline\" data-latex=\"\u0007lpha = .91\">$\u0007lpha = .91$<\/span> (<span class=\"arabpsy-math-inline\" data-latex=\"N = 243\">$N = 243$<\/span>, evaluating range discounts in electronics)<\/li>\n<li>Study 3: <span class=\"arabpsy-math-inline\" data-latex=\"\u0007lpha = .95\">$\u0007lpha = .95$<\/span> (<span class=\"arabpsy-math-inline\" data-latex=\"N = 312\">$N = 312$<\/span>, testing scarcity moderation)<\/li>\n<li>Study 4: <span class=\"arabpsy-math-inline\" data-latex=\"\u0007lpha = .94\">$\u0007lpha = .94$<\/span> (<span class=\"arabpsy-math-inline\" data-latex=\"N = 288\">$N = 288$<\/span>, testing boundary effects of upper-endpoint feasibility)<\/li>\n<li>Study 5: <span class=\"arabpsy-math-inline\" data-latex=\"\u0007lpha = .92\">$\u0007lpha = .92$<\/span> (<span class=\"arabpsy-math-inline\" data-latex=\"N = 405\">$N = 405$<\/span>, field validation)<\/li>\n<\/ul>\n<\/li>\n<li><strong>Composite Reliability:<\/strong> In structural equation modeling frameworks, the composite reliability (Raykov&#8217;s $<br \/>\nho$ \/ McDonald&#8217;s <span class=\"arabpsy-math-inline\" data-latex=\"\\omega\">$\\omega$<\/span>) consistently ranges from <span class=\"arabpsy-math-inline\" data-latex=\".92\">$.92$<\/span> to <span class=\"arabpsy-math-inline\" data-latex=\".96\">$.96$<\/span>, far exceeding the conventional psychometric threshold of <span class=\"arabpsy-math-inline\" data-latex=\".70\">$.70$<\/span> or <span class=\"arabpsy-math-inline\" data-latex=\".80\">$.80$<\/span>.<\/li>\n<li><strong>Measurement Stability:<\/strong> Although primary use cases involve post-manipulation state evaluations, test-retest reliability across neutral control conditions over short intervals (e.g., 48 hours) yields temporal stability coefficients exceeding <span class=\"arabpsy-math-inline\" data-latex=\"r_{tt} = .80\">$r_{tt} = .80$<\/span>.<\/li>\n<\/ul>\n<h2>Factor Analysis<\/h2>\n<p>Psychometric evaluations confirm that the APO scale possesses an unambiguous unidimensional factor structure. Both exploratory (<a href=\"https:\/\/en.wikipedia.org\/wiki\/Exploratory_factor_analysis\" target=\"_blank\" rel=\"noopener noreferrer\">EFA<\/a>) and confirmatory factor analyses (<a href=\"https:\/\/en.wikipedia.org\/wiki\/Confirmatory_factor_analysis\" target=\"_blank\" rel=\"noopener noreferrer\">CFA<\/a>) support this single-construct specification:<\/p>\n<h3>Exploratory Factor Analysis<\/h3>\n<p>Principal axis factoring and principal component analyses consistently yield a single unrotated factor accounting for between 82% and 89% of the total variance across items. The scree test confirms a distinct drop-off after the first eigenvalue (initial eigenvalues: <span class=\"arabpsy-math-inline\" data-latex=\"\\lambda_1 \\approx 2.58\">$\\lambda_1 \\approx 2.58$<\/span>, <span class=\"arabpsy-math-inline\" data-latex=\"\\lambda_2 \\approx 0.24\">$\\lambda_2 \\approx 0.24$<\/span>, <span class=\"arabpsy-math-inline\" data-latex=\"\\lambda_3 \\approx 0.18\">$\\lambda_3 \\approx 0.18$<\/span>). Factor loadings for all three items are uniformly robust:<\/p>\n<ul>\n<li>Item 1 (&#8220;I like this offer&#8221;): Factor loading <span class=\"arabpsy-math-inline\" data-latex=\"lambda &gt; .88\">$lambda &gt; .88$<\/span><\/li>\n<li>Item 2 (&#8220;I feel positive about this offer&#8221;): Factor loading <span class=\"arabpsy-math-inline\" data-latex=\"lambda &gt; .91\">$lambda &gt; .91$<\/span><\/li>\n<li>Item 3 (&#8220;I feel happy about this offer&#8221;): Factor loading <span class=\"arabpsy-math-inline\" data-latex=\"lambda &gt; .87\">$lambda &gt; .87$<\/span><\/li>\n<\/ul>\n<h3>Confirmatory Factor Analysis<\/h3>\n<p>Given that a three-item single-factor measurement model is just-identified (<span class=\"arabpsy-math-inline\" data-latex=\"df = 0\">$df = 0$<\/span>), researchers examine model fit when the APO construct is modeled alongside collateral latent variables (e.g., purchase intention, brand perception). Across such multi-construct models, the single-factor specification of the APO yields exemplary global fit indices:<\/p>\n<ul>\n<li>Comparative Fit Index (<a href=\"https:\/\/en.wikipedia.org\/wiki\/Confirmatory_factor_analysis#Goodness-of-fit\" target=\"_blank\" rel=\"noopener noreferrer\">CFI<\/a>) <span class=\"arabpsy-math-inline\" data-latex=\"ge .985\">$ge .985$<\/span><\/li>\n<li>Tucker-Lewis Index (<a href=\"https:\/\/en.wikipedia.org\/wiki\/Confirmatory_factor_analysis#Goodness-of-fit\" target=\"_blank\" rel=\"noopener noreferrer\">TLI<\/a>) <span class=\"arabpsy-math-inline\" data-latex=\"ge .978\">$ge .978$<\/span><\/li>\n<li>Root Mean Square Error of Approximation (<a href=\"https:\/\/en.wikipedia.org\/wiki\/Confirmatory_factor_analysis#Goodness-of-fit\" target=\"_blank\" rel=\"noopener noreferrer\">RMSEA<\/a>) <span class=\"arabpsy-math-inline\" data-latex=\"le .048\">$le .048$<\/span> (<span class=\"arabpsy-math-inline\" data-latex=\"90% \\text{ CI } [.000, .072]\">$90% \\text{ CI } [.000, .072]$<\/span>)<\/li>\n<li>Standardized Root Mean Square Residual (<a href=\"https:\/\/en.wikipedia.org\/wiki\/Confirmatory_factor_analysis#Goodness-of-fit\" target=\"_blank\" rel=\"noopener noreferrer\">SRMR<\/a>) <span class=\"arabpsy-math-inline\" data-latex=\"le .021\">$le .021$<\/span><\/li>\n<\/ul>\n<p>These findings substantiate that the items measure a single, tightly knit latent construct without residual multidimensionality.<\/p>\n<h2>Instrument \/ Measurement Tool<\/h2>\n<p>The technical parameters and administration profile of the instrument are summarized below:<\/p>\n<ul>\n<li><strong>Test Type:<\/strong> Self-administered psychological rating scale; psychometric survey instrument.<\/li>\n<li><strong>Format:<\/strong> Available in paper-and-pencil, computer-assisted (e.g., Qualtrics, Gorilla Experiment Builder), or mobile administration formats.<\/li>\n<li><strong>Item Count:<\/strong> 3 items.<\/li>\n<li><strong>Subscales \/ Dimensions:<\/strong> None (Unidimensional structure).<\/li>\n<li><strong>Response Scale:<\/strong> 7-point Likert scale:\n<ul>\n<li><span class=\"arabpsy-eq\" dir=\"ltr\">1 = Strongly disagree<\/span><\/li>\n<li><span class=\"arabpsy-eq\" dir=\"ltr\">2 = Disagree<\/span><\/li>\n<li><span class=\"arabpsy-eq\" dir=\"ltr\">3 = Somewhat disagree<\/span><\/li>\n<li><span class=\"arabpsy-eq\" dir=\"ltr\">4 = Neither agree nor disagree<\/span><\/li>\n<li><span class=\"arabpsy-eq\" dir=\"ltr\">5 = Somewhat agree<\/span><\/li>\n<li><span class=\"arabpsy-eq\" dir=\"ltr\">6 = Agree<\/span><\/li>\n<li><span class=\"arabpsy-eq\" dir=\"ltr\">7 = Strongly agree<\/span><\/li>\n<\/ul>\n<\/li>\n<li><strong>Scoring Rules:<\/strong> All three items are scored directly (none are reverse-coded). A composite score is calculated by computing the unweighted arithmetic mean across the three items:<br \/>\n    <span class=\"arabpsy-math-display\" data-latex=\"\\text{APO Composite} = \\frac{\\text{Item } 1 + \\text{Item } 2 + \\text{Item } 3}{3}\">$$\\text{APO Composite} = \\frac{\\text{Item } 1 + \\text{Item } 2 + \\text{Item } 3}{3}$$<\/span><br \/>\n    Higher overall composite scores signify a more favorable, enthusiastic, and positive psychological attitude toward the presented purchase offer.<\/li>\n<li><strong>Administration Time:<\/strong> Under 30 seconds, making it ideal for experimental designs requiring minimal participant burden.<\/li>\n<\/ul>\n<h2>Permissions &amp; Fee and Test Year<\/h2>\n<p>The Attitude Toward a Purchase Offer scale was published in its standardized format in <strong>2019<\/strong> in the <em>Journal of Consumer Research<\/em> by Liyin Fan, Xiuping Li, and Ying Jiang, with foundational antecedents dating to Ames and Mason (2015). Under standard scholarly conventions and academic fair-use guidelines, the scale is made publicly accessible for non-commercial educational, scientific, and empirical research purposes without royalty fees. Researchers using the scale are expected to cite the foundational publication (<a href=\"https:\/\/doi.org\/10.1093\/jcr\/ucy074\" target=\"_blank\" rel=\"noopener noreferrer\">Fan, Li, &amp; Jiang, 2019<\/a>). Commercial applications, specialized marketing consulting platforms, or proprietary testing frameworks should contact the authors or the respective copyright holders for clearance.<\/p>\n<h2>References<\/h2>\n<ul>\n<li>Ames, D., &amp; Mason, M. (2015). Tandem anchoring: Informational and polite effects of range offers in negotiation. <em>Journal of Personality and Social Psychology<\/em>, 108(2), 254\u2013267. <a href=\"https:\/\/doi.org\/10.1037\/pspi0000016\" target=\"_blank\" rel=\"noopener noreferrer\">https:\/\/doi.org\/10.1037\/pspi0000016<\/a><\/li>\n<li>Eagly, A. H., &amp; Chaiken, S. (1993). <em>The psychology of attitudes<\/em>. Harcourt Brace Jovanovich College Publishers.<\/li>\n<li>Fan, L., Li, X., &amp; Jiang, Y. (2019). Room for opportunity: Resource scarcity increases attractiveness of range marketing offers. <em>Journal of Consumer Research<\/em>, 46(1), 82\u201398. <a href=\"https:\/\/doi.org\/10.1093\/jcr\/ucy074\" target=\"_blank\" rel=\"noopener noreferrer\">https:\/\/doi.org\/10.1093\/jcr\/ucy074<\/a><\/li>\n<li>Kahneman, D., &amp; Tversky, A. (1979). Prospect theory: An analysis of decision under risk. <em>Econometrica<\/em>, 47(2), 263\u2013291. <a href=\"https:\/\/doi.org\/10.2307\/1914185\" target=\"_blank\" rel=\"noopener noreferrer\">https:\/\/doi.org\/10.2307\/1914185<\/a><\/li>\n<li>Mullainathan, S., &amp; Shafir, E. (2013). <em>Scarcity: Why having too little means so much<\/em>. Times Books, Henry Holt and Company.<\/li>\n<li>Parducci, A. (1965). Category judgment: A range-frequency model. <em>Psychological Review<\/em>, 72(6), 407\u2013418. <a href=\"https:\/\/doi.org\/10.1037\/h0022602\" target=\"_blank\" rel=\"noopener noreferrer\">https:\/\/doi.org\/10.1037\/h0022602<\/a><\/li>\n<li>Thaler, R. (1985). Mental accounting and consumer choice. <em>Marketing Science<\/em>, 4(3), 199\u2013214. <a href=\"https:\/\/doi.org\/10.1287\/mksc.4.3.199\" target=\"_blank\" rel=\"noopener noreferrer\">https:\/\/doi.org\/10.1287\/mksc.4.3.199<\/a><\/li>\n<\/ul>\n<h2>Items of the Scale<\/h2>\n<div class=\"wpt-scale-notice\" style=\"direction:ltr; text-align:left; background:#f8fafc; border-bottom:1px solid #e2e8f0; padding:14px 20px; font-size:13.5px; color:#475569; font-weight:500;\">\n  Below are the authentic scale items in their original language as published in the standard psychometric validation studies, without modification or translation to preserve instrument validity and reliability:\n<\/div>\n<div class=\"wpt-scale-items-container\" style=\"direction:ltr; text-align:left; font-family:sans-serif;\">\n<p style=\"margin-top:16px; font-weight:600;\">Response Scale:<\/p>\n<p style=\"margin-left:10px;\"><span class=\"arabpsy-eq\" dir=\"ltr\">7-point Likert scale (1 = strongly disagree, 7 = strongly agree)<\/span><\/p>\n<p style=\"margin-top:16px; font-weight:600;\">Items:<\/p>\n<ol style=\"line-height:1.8; font-size:15px; margin-left:20px;\">\n<li>I like this offer.<\/li>\n<li>I feel positive about this offer.<\/li>\n<li>I feel happy about this offer.<\/li>\n<\/ol>\n<p style=\"margin-top:16px; font-style:italic; font-size:13.5px; color:#64748b;\">\n    Scoring: Items are averaged to create a single composite score reflecting attitude toward the offer, with higher scores indicating a more favorable attitude.\n  <\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>A comprehensive psychometric guide to the Attitude Toward a Purchase Offer (APO) scale, developed by Fan, Li, and Jiang (2019). Includes theoretical foundation, reliability, validity, factor structure, and authentic test items.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","categories":[1076,2499,30],"tags":[10924,10923,2275,10925,10926,6,7082],"class_list":["post-2923","psych_scale","type-psych_scale","status-publish","hentry","category-consumer-psychology","category-decision-making","category-psychological-scales","tag-apo","tag-attitude-toward-a-purchase-offer","tag-consumer-behavior","tag-marketing-psychology","tag-pricing-offers","tag-psychometrics","tag-resource-scarcity"],"_links":{"self":[{"href":"https:\/\/ashadocs.org\/index.php?rest_route=\/wp\/v2\/psych_scale\/2923","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ashadocs.org\/index.php?rest_route=\/wp\/v2\/psych_scale"}],"about":[{"href":"https:\/\/ashadocs.org\/index.php?rest_route=\/wp\/v2\/types\/psych_scale"}],"author":[{"embeddable":true,"href":"https:\/\/ashadocs.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ashadocs.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2923"}],"version-history":[{"count":0,"href":"https:\/\/ashadocs.org\/index.php?rest_route=\/wp\/v2\/psych_scale\/2923\/revisions"}],"wp:attachment":[{"href":"https:\/\/ashadocs.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2923"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ashadocs.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2923"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ashadocs.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2923"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}