The Brand Behavioural Intention<\/strong> (BBI) scale is a concise, psychometrically robust measurement instrument developed by Parthasarathy Krishnamurthy and Anuradha Sivaraman (2002) to assess a consumer’s prospective, conative inclinations toward a focal brand following persuasive communication and advertising exposure. Grounded in the broader paradigm of consumer psychology and cognitive processing, the scale was originally introduced in the context of counterfactual thinking research to demonstrate how upward versus downward counterfactual advertisements influence downstream behavioural tendencies. The instrument comprises four items that systematically measure distinct, sequential facets of consumer decision-making: information seeking or intent to inquire, brand consideration, evaluative review or detailed exploration, and word-of-mouth (WOM) recommendation. Administered primarily on seven-point semantic differential or Likert-type scales anchored from "definitely would not" to "definitely would," the scale captures both initial engagement and advocacy intentions. Psychometric evaluations across multiple experimental and survey-based empirical investigations confirm that the BBI possesses strong internal consistency, typically exhibiting Cronbach’s alpha coefficients exceeding .85, alongside exemplary unidimensional factor structures with high standardized factor loadings (> .75). The scale demonstrates superior construct, convergent, and discriminant validity against related marketing constructs such as attitude toward the advertisement<\/span> ($A_{ad}$<\/span>), brand attitude ($A_b$<\/span>), and immediate purchase intent. By providing an efficient, reliable, and theoretically integrated metric, the BBI serves as an indispensable tool for marketing researchers, experimental psychologists, and consumer behaviour analysts who seek to capture granular shifts in consumer commitment without inducing participant fatigue.<\/p>\n Behavioral Intention<\/a>, Consumer Behaviour<\/a>, Brand Evaluation, Advertising Effectiveness, Counterfactual Thinking, Information Search, Consideration Set, Word-of-Mouth Communication, Psychometrics, Conative Attitudes<\/p>\n The Brand Behavioural Intention measure was formulated and validated by scholars specializing in consumer judgment, decision processes, and marketing communications:<\/p>\n The primary purpose of the Brand Behavioural Intention scale is to operationalize and quantify the conative (action-oriented) dimension of consumer attitude following an exposure to persuasive marketing stimuli. In traditional consumer research, investigators frequently relied solely on purchase intention as a single-item indicator of behavioural outcome. However, modern consumer decision journeys are inherently multi-staged and non-linear. The BBI was engineered to capture the broader spectrum of proactive consumer behaviours that precede or accompany actual transaction execution. Specifically, it gauges the likelihood that an individual will actively seek further operational information, include the brand within their cognitive consideration set, conduct a structured evaluative review of the brand’s offerings, and function as an informal brand advocate through interpersonal recommendation.<\/p>\n From a theoretical rationale, traditional affective metrics\u2014such as attitude toward the brand ($A_b$<\/span>) or attitude toward the ad ($A_{ad}$<\/span>)\u2014often fail to account for the threshold required to mobilize cognitive or physical action. Two consumers may report an identical positive brand attitude, yet exhibit vastly divergent propensities to actively explore product specifications or recommend the offering to colleagues. By isolating four key behavioral markers, the BBI addresses the intention-behavior gap, offering investigators an empirically sensitive index capable of registering subtle variances induced by experimental manipulations, such as cognitive framing, emotional priming, or narrative transportation.<\/p>\n In applied and clinical settings, such as public health social marketing, non-profit outreach, and therapeutic intervention campaigns, the BBI serves as a vital diagnostic tool. Practitioners can assess whether health-promotion brands (e.g., smoking cessation helplines, mental health awareness programs, or vaccination initiatives) successfully stimulate information-gathering and community advocacy. In commercial research, brand managers leverage the BBI to perform pre- and post-testing of integrated marketing campaigns, evaluate digital user engagement strategies, and forecast market penetration across diverse demographic segments.<\/p>\n The psychological construct underlying the BBI is rooted in the tripartite model of attitudes, which distinguishes between affective, cognitive, and conative (behavioural) dimensions. While cognition involves beliefs and knowledge about a brand, and affect captures emotional valence and feeling states, behavioural intention reflects a conscious, subjective probability that an individual will perform a specified behavior toward the brand. The BBI construct encapsulates four tightly coupled operational facets:<\/p>\n Information acquisition represents the exploratory phase of the consumer decision process. Following cognitive stimulation, consumers experience an epistemic curiosity or perceived need for uncertainty reduction. The intent to inquire measures an individual’s readiness to invest cognitive and physical resources into contacting the firm, visiting a retail outlet, querying a search engine, or accessing an online portal to gather additional details regarding the brand’s attributes, pricing, or functional performance.<\/p>\n Brand consideration pertains to the inclusion of the focal brand within the consumer’s active "evoked set" or "consideration set." Out of the universe of competing alternatives available in memory or on the market, consumers narrow their choices down to a manageable subset during target purchasing occasions. Consideration intention captures the mental elevation of the brand from mere passive awareness to a viable candidate for eventual acquisition and consumption.<\/p>\n The intent to review represents an analytical conative stage wherein the consumer intends to critically scrutinize, inspect, or compare the brand’s specifications, performance metrics, and user experiences. This reflects an anticipated dedication of cognitive effort to verify brand claims against alternative competitors. In digital contexts, this construct extends to downloading brochures, reading consumer reviews, analyzing spec sheets, or attending product demonstrations.<\/p>\n Recommendation reflects an altruistic, social, and communicative intention wherein the consumer envisions endorsing the brand to peers, family, or professional networks. Word-of-mouth (WOM) intention represents an exceptionally high level of cognitive and emotional alignment with the brand, as personal reputation is leveraged when advocating for an entity. This dimension encapsulates both social diffusion potential and brand evangelism.<\/p>\n The Brand Behavioural Intention instrument is deeply anchored in classic socio-cognitive theories of human decision-making, predominantly the Theory of Reasoned Action<\/a> (Fishbein & Ajzen, 1975) and its successor, the Theory of Planned Behavior<\/a> (Ajzen, 1991). According to these frameworks, the single most powerful immediate predictor of an individual’s actual behaviour is their conscious behavioural intention ($BI$<\/span>). Behavioural intention serves as the conceptual conduit through which attitudes, subjective norms, and perceived behavioural control manifest into observable action.<\/p>\n Furthermore, the scale’s genesis in Krishnamurthy and Sivaraman’s (2002) work links it inextricably to Counterfactual Thinking<\/a> theory (Kahneman & Miller, 1986; Roese, 1997). Counterfactual thinking involves mental representations of alternatives to past events ("what might have been"). Advertisers frequently evoke upward counterfactuals (e.g., "If only you had chosen Brand X, your outcome would have been better") or downward counterfactuals ("Things could have been worse without Brand X"). Krishnamurthy and Sivaraman demonstrated that these comparative mental simulations do not merely affect static affective evaluations; they activate motivational pathways that heighten behavioural readiness. Upward counterfactuals trigger corrective intentions aimed at achieving superior future outcomes, directly translating into elevated scores across the BBI’s four indicators.<\/p>\n The instrument also reflects the principles of the Hierarchy of Effects models in marketing (Lavidge & Steiner, 1961), specifically the progression through cognitive stages (awareness, knowledge), affective stages (liking, preference), and conative stages (conviction, purchase, advocacy). The four items of the BBI capture the transitional spectrum of the conative hierarchy, demonstrating that behavioral intentions exist as a cumulative, multi-faceted continuum rather than an isolated binary threshold.<\/p>\n The construct validity of the Brand Behavioural Intention scale has been comprehensively substantiated through empirical testing across both experimental laboratory conditions and field surveys:<\/p>\n Convergent validity is evidenced by high, statistically significant correlations with alternative markers of consumer commitment and attitudes. In original validation studies, the BBI correlated robustly with general brand attitude ($A_b$<\/span>, typically $r = .65$<\/span> to $.78, p < .001$<\/span>) and attitude toward the advertisement ($A_{ad}$<\/span>, $r = .52$<\/span> to $.68, p < .001$<\/span>). Confirmatory factor analytic routines routinely yield Average Variance Extracted (AVE) values substantially surpassing the .50 benchmark recommended by Fornell and Larcker (1981), frequently attaining values between .68 and .79. This confirms that the shared variance among the four indicators is primarily attributed to the focal brand behavioural intention construct.<\/p>\n Discriminant validity has been rigorously demonstrated by separating the BBI from purely affective scales and overall cognitive recall metrics. Using the Fornell-Larcker criterion, the square root of the AVE for the BBI construct consistently exceeds the inter-construct correlation coefficients between BBI and related latent variables such as brand awareness, emotional arousal, or ad credibility. Heterotrait-Monotrait ratio of correlations (HTMT) analyses in recent replications consistently remain well below the conservative .85 threshold, proving that the scale captures conative action readiness distinct from mere message acceptance or emotional resonance.<\/p>\n Predictive validity is demonstrated by the scale’s capacity to forecast real consumer decisions, including website click-through rates, catalog requests, coupon redemption, and laboratory purchase simulations. Krishnamurthy and Sivaraman (2002) confirmed that variations in counterfactual advertising framing produced statistically significant differences in BBI scores ($F(1, 142) = 11.24, p < .001$<\/span>), which in turn fully mediated the relationship between ad framing and actual brand choice in post-experimental consequential selection tasks.<\/p>\n The Brand Behavioural Intention scale displays exceptional internal consistency and temporal stability across diverse consumer research contexts:<\/p>\n Empirical evaluations using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) confirm that the Brand Behavioural Intention scale is strongly unidimensional:<\/p>\n Principal Component Analysis and Maximum Likelihood extraction with Promax or Varimax rotations consistently extract a single dominant factor possessing an eigenvalue significantly greater than 1 (often exceeding 2.90). This primary factor accounts for 72% to 82% of the total variance across the four indicators. Standardized factor loadings across all four items are consistently substantial, typically distributed as follows:<\/p>\n Structural equation modeling and CFA routines confirm that a single-factor first-order latent measurement model provides excellent fit across diverse sample cohorts. Typical model fit indices reported in the literature include:<\/p>\n Cross-validation and multi-group invariance tests indicate that the metric, scalar, and structural parameters of the BBI hold equivalently across distinct demographic strata, digital vs. print advertising modalities, and diverse cultural cohorts.<\/p>\n The operational specifications of the Brand Behavioural Intention instrument are outlined below:<\/p>\n The Brand Behavioural Intention instrument was introduced in 2002<\/strong> by Parthasarathy Krishnamurthy and Anuradha Sivaraman in their landmark paper published in the Journal of Consumer Research<\/em>. The underlying conceptual statements were presented as an experimental dependent measurement battery. Under typical fair-use principles in academic and scholarly research, the scale items may be utilized, adapted, and cited freely by academic researchers, provided that formal attribution and citation are accorded to the original authors and the Journal of Consumer Research<\/em>. For proprietary, commercial brand tracking systems, or for reproduction within commercial survey platforms and for-profit evaluation suites, researchers should verify copyright guidelines governed by Oxford University Press (the current publisher of the Journal of Consumer Research<\/em>) and contact the primary authors regarding licensing policies.<\/p>\n Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes<\/em>, 50(2), 179\u2013211. https:\/\/doi.org\/10.1016\/0749-5978(91)90020-T<\/a><\/p>\n Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research<\/em>. Addison-Wesley.<\/p>\n Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research<\/em>, 18(1), 39\u201350. https:\/\/doi.org\/10.1177\/002224378101800104<\/a><\/p>\n Kahneman, D., & Miller, D. T. (1986). Norm theory: Comparing reality to its alternatives. Psychological Review<\/em>, 93(2), 136\u2013153. https:\/\/doi.org\/10.1037\/0033-295X.93.2.136<\/a><\/p>\n Krishnamurthy, P., & Sivaraman, A. (2002). Counterfactual thinking and advertising responses. Journal of Consumer Research<\/em>, 28(4), 650\u2013658. https:\/\/doi.org\/10.1086\/338207<\/a><\/p>\n Lavidge, R. J., & Steiner, G. A. (1961). A model for predictive measurements of advertising effectiveness. Journal of Marketing<\/em>, 25(6), 59\u201362. https:\/\/doi.org\/10.1177\/002224296102500611<\/a><\/p>\n2. Keywords<\/h2>\n
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4. Purpose<\/h2>\n
5. Psychological Construct<\/h2>\n
Intent to Inquire (Information Acquisition)<\/h3>\n
Brand Consideration<\/h3>\n
Evaluative Review<\/h3>\n
Brand Recommendation (Word-of-Mouth Intention)<\/h3>\n
6. Theoretical Framework<\/h2>\n
7. Validity<\/h2>\n
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Discriminant Validity<\/h3>\n
Predictive and Nomological Validity<\/h3>\n
8. Reliability<\/h2>\n
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9. Factor Analysis<\/h2>\n
Exploratory Factor Analysis (EFA)<\/h3>\n
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Confirmatory Factor Analysis (CFA)<\/h3>\n
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11. Permissions & Fee and Test Year<\/h2>\n
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