Product Preference (Company)

Abstract

The Product Preference (Company) scale is a behavioral and psychometric measurement paradigm engineered to assess relative consumer choice between products originating from company-internal professional designers versus external peer users (user-designed products). Developed and validated by Song, Jung, and Zhang (2021), the instrument operationalizes consumer decision-making through rigorous paired-comparison, forced-choice behavioral protocols supplemented by continuous evaluative rating dimensions. The instrument specifically isolates the psychological mechanisms governing how consumers weigh source expertise against perceived authenticity and peer representation, focusing particularly on how cultural values—most notably power distance belief (PDB)—systematically moderate product selection across international markets.

Validated across cross-cultural cohorts comprising both Western (United States) and East Asian (China) consumers, the scale demonstrates robust psychometric properties across diverse consumer goods categories, including apparel, consumer electronics, and functional accessories. Statistical evaluation utilizing binary logistic regression, random utility discrete choice modeling, and multi-group confirmatory factor analysis confirms strong construct validity, exceptional discriminant validity from generalized brand affinity, and high internal consistency. By capturing consequential choice behavior rather than isolated abstract attitudes, the instrument provides an empirical bridge between psychometric attitudinal measurement and revealed consumer choice in open innovation, collaborative design, and international marketing contexts.

Keywords

Product preference, user-designed products, designer-designed products, power distance belief, cross-cultural psychometrics, discrete choice modeling, open innovation, source credibility, consumer decision-making, forced-choice paradigm

Authors

The primary architectural design, empirical validation, and psychometric calibration of the instrument were conducted by the following academic researchers:

• Xilin Song — School of Business, Renmin University of China, Beijing, China. Expertise: Consumer behavior, cultural psychology, crowdsourcing, and brand perception.
• Jichuan Jung — Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia, USA. Expertise: Marketing strategy, digital product development, and empirical choice modeling.
• Yexin Jessica Zhang — Rawls College of Business, Texas Tech University, Lubbock, Texas, USA. Expertise: Cross-cultural consumer behavior, social hierarchy, power distance, and consumer empowerment.

Purpose

The fundamental purpose of the Product Preference (Company) scale is to quantify and evaluate how consumers resolve trade-offs between professional institutional authority and decentralized consumer co-creation. Over the past two decades, commercial enterprises have increasingly integrated open innovation and crowdsourcing paradigms into their product development pipelines (e.g., Dell IdeaStorm, Lego Ideas, MUJI design competitions). However, marketing scholars and practitioners frequently observe divergent market responses to such initiatives: while some consumer segments enthusiastically celebrate crowdsourced goods as authentic and democratized, others reject them as unprofessional, amateurish, and inferior to expert-engineered alternatives.

Traditional Likert-type scales measuring general product attitudes often suffer from social desirability bias and acquiescence bias, particularly in cross-cultural settings where respondents hesitate to overtly criticize professional authority or egalitarian initiatives. The Product Preference (Company) measurement tool resolves this psychometric vulnerability by employing a standardized, comparative forced-choice methodology. Rather than asking respondents in an abstract vacuum whether they “like” crowdsourced goods, the scale places respondents in realistic, head-to-head evaluation scenarios where identical or functionally equivalent products are explicitly framed as either user-designed (originating from ordinary consumers via crowdsourcing contests) or designer-designed (originating from credentialed, in-house corporate design professionals).

In addition to basic consumer choice analysis, the scale serves critical theoretical and applied functions across psychological, organizational, and marketing disciplines:

• Cross-Cultural Psychometrics: It systematically diagnoses how internalized cultural orientations, specifically power distance belief (the extent to which individuals accept and expect hierarchical inequality and respect status-based authority), govern consumption choices across different sovereign nations and subcultural demographics.
• Psychological Mechanism Deconstruction: The scale enables researchers to parse the mediating tensions between perceived competence (attributed to corporate designers) versus perceived identity congruence and customer-centric benevolence (attributed to peer users).
• Strategic Marketing Allocation: For multinational organizations, the instrument provides quantitative decision metrics regarding whether promoting the “user-designed” origin of a product will enhance sales in egalitarian markets (such as North America or Northern Europe) or depress market share in hierarchically oriented markets (such as East Asia, Latin America, or the Middle East).

Psychological Construct

The psychological construct measured by the Product Preference (Company) paradigm is relative design-origin preference, embedded within an evaluative dual-source attribution framework. The construct does not treat product preference as an isolated sensory or functional evaluation; rather, it measures how the social categorization of the creator shifts the cognitive and affective valuation of an otherwise equivalent commercial artifact.

Core Dimensions and Psychological Facets

The construct encompasses three tightly coupled psychological dimensions that together drive consequential choice:

• 1. Source Competence vs. Benevolence Trade-Off: Rooted in the Stereotype Content Model and source credibility theory, consumers attribute contrasting latent qualities to designers versus peer users. The designer-designed dimension triggers cognitive associations of institutional competence, formal training, technological rigor, and standardized quality control. Conversely, the user-designed dimension evokes associations of warm user empathy, practical everyday insight, uncorrupted authenticity, and responsiveness to authentic consumer needs. The instrument measures the relative net valence resulting from this trade-off.
• 2. Status-Role Congruence: This dimension measures the psychological expectation that specific functional tasks belong strictly to specialized societal strata. For high-power-distance individuals, professional designers occupy a legitimate, superior echelon within the corporate-consumer hierarchy; user intervention in product design constitutes role transgression, violating cognitive legitimacy. For low-power-distance individuals, egalitarianism minimizes role boundaries, rendering peer contribution inherently legitimate and socially desirable.
• 3. Consequential Behavioral Allocation (Relative Choice Share): The behavioral crystallization of the construct, operationalized as the direct selection probability of Company A’s product (e.g., user-designed) versus Company B’s product (e.g., designer-designed). By requiring respondents to commit to an exclusive choice—frequently accompanied by incentive-compatible mechanisms such as actual product raffles or budget allocations—the construct captures revealed preference unencumbered by declarative measurement artifacts.

When evaluated comprehensively, the construct reflects the activation of latent cultural schemas. When a consumer encounters a product labeled as “designed by users,” their cognitive architecture processes the cue through their internalized cultural lens. If the individual subscribes to high power distance beliefs, the activation of authority norms suppresses the perceived value of peer input, generating an unfavorable evaluation. Conversely, when low power distance schemas are active, the peer origin is perceived as an empowering, democratic asset, elevating preference for the user-designed option over the corporate counterpart.

Theoretical Framework

The conceptual infrastructure of the Product Preference (Company) instrument integrates three major bodies of psychological and organizational theory: Hofstede’s Cultural Dimensions Theory, Source Credibility Theory, and Social Identity Theory.

1. Power Distance Belief (PDB) and Hierarchical Legitimacy

Originating from the comparative sociological work of Geert Hofstede and extensively adapted to individual-level consumer psychology by researchers such as Zhang, Winterich, and Mittal, Power Distance Belief represents the degree to which inequality and hierarchical order are accepted as legitimate aspects of social reality. In societies and individuals characterized by high PDB, people perceive social and professional hierarchies as natural, functional, and necessary for social stability. Expertise, decision-making authority, and production responsibilities are expected to reside strictly within designated elite authorities—such as professional corporate designers, engineers, and master artisans.

Within this theoretical paradigm, the introduction of user-designed products presents a direct violation of hierarchical structural expectations. High-PDB consumers perceive ordinary users as lacking the legitimate authority, technical status, and specialized credentials necessary to create commercial products. Consequently, they experience cognitive dissonance and skepticism when presented with crowdsourced offerings. In contrast, low-PDB consumers view all individuals as fundamentally equal in worth, creativity, and capability; to them, peer-designed products represent democratic participation, self-determination, and the dethroning of detached corporate gatekeepers.

2. Source Credibility and Attributional Processing

The second foundational pillar is Hovland and Weiss’s source credibility framework, bifurcated into perceived expertise and perceived trustworthiness/benevolence. The Product Preference (Company) scale builds on research demonstrating that design origin functions as an extrinsic quality cue. When functional performance is uncertain or difficult to verify pre-purchase, consumers rely on cognitive heuristics derived from creator identity:

• Designer Cue: Maximizes attribution of technical mastery, formal education, and institutional accountability.
• User Cue: Maximizes attribution of alignment with consumer self-interest, absence of corporate greed, and shared situational understanding.

The theoretical framework posits that cultural conditioning dictates which of these two credibility dimensions dominates information processing: high-PDB orientations systematically upweight expert competence heuristics, whereas low-PDB orientations upweight communal benevolence and authentic experiential relevance heuristics.

3. Compensatory Consumer Behavior and Identity Congruence

The framework also incorporates principles from social identity and empowerment theory. Consumers often use consumption to reinforce their internalized self-concepts and sociopolitical values. Supporting a user-designed product functions as an expressive act of solidarity with fellow consumers, asserting the collective agency of the public over corporate hegemony. The instrument relies on the theoretical proposition that this identity-expressive motivation operates robustly in egalitarian environments but is overridden by institutional deference in hierarchical social structures.

Validity

The empirical validity of the Product Preference (Company) measurement model has been rigorously established across multiple laboratory experiments, online cross-cultural panels, and field-simulated behavioral choice tasks documented by Song, Jung, and Zhang (2021).

Construct and Internal Validity

To verify construct validity, researchers established that manipulated design origins (user-designed vs. designer-designed) systematically and exclusively drove preference disparities while controlling for extraneous product attributes. Stimuli across comparative trials were standardized in visual presentation, physical specifications, functional descriptions, and brand framing. In manipulated conditions where the focal product was designated as “user-designed” by Company A and the competitor’s equivalent product was designated as “designer-designed” by Company B, preference shifts occurred strictly as a function of the design origin cue and the respondent’s measured or primed power distance belief.

Manipulation checks routinely confirmed that participants correctly encoded the creator origin ($F(1, 284) > 120.0, p < .001$), demonstrating that the scale accurately registers variance driven by the focal psychological construct rather than peripheral cognitive noise.

Predictive and Behavioral Validity

A notable strength of the scale’s validation is its predictive convergence with actual behavioral commitments. In incentive-compatible studies conducted by Song et al. (2021), participants were informed that their choices would directly determine which physical product they would receive in a real lottery draw. The forced-choice product preference metrics demonstrated powerful predictive validity regarding real behavior:

• In low-PDB cohorts (e.g., United States baseline), respondents exhibited a significant, consequential preference for the user-designed product over the designer-designed product (choice share: $60.8%$ vs. $39.2%$; $\chi^2(1) = 6.79, p = .009$).
• In high-PDB cohorts (e.g., China baseline), the behavioral pattern inverted completely, with respondents demonstrating a pronounced preference for the designer-designed option (choice share: $36.7%$ user-designed vs. $63.3%$ designer-designed; $\chi^2(1) = 10.12, p = .001$).
• Logistic regression models confirmed that measured individual PDB scores directly predicted the probability of selecting the user-designed company ($B = -.34, SE = .09, Wald = 13.82, p < .001, OR = .71$).

Convergent and Discriminant Validity

The instrument demonstrated strong convergent validity when cross-referenced against continuous multi-item measures of purchase intention, willingness to pay (WTP), and overall brand attitude. Bivariate correlations between the forced-choice metric and continuous purchase intention scales were consistently high and statistically significant ($r = .64$ to $.78, p < .001$). Discriminant validity was demonstrated through structural equation modeling: design-origin preference proved empirically distinct from generalized risk aversion, price sensitivity, and omnibus need-for-uniqueness, confirming that the scale captures a distinct cultural-cognitive choice dynamic rather than non-specific consumption conservatism.

Reliability

Because the primary outcome of the Product Preference (Company) instrument is operationalized through discrete paired-comparison and forced-choice tasks, classical internal consistency metrics (e.g., Cronbach’s alpha) are evaluated across multi-trial experimental blocks, paired multi-item evaluative extensions, and associated mediating scales.

Multi-Item Preference and Attitude Dimensions

When administered using multi-item continuous evaluative batteries assessing preference intensity (e.g., relative attractiveness, superiority, purchase likelihood, and perceived value), the scale exhibits high internal consistency across diverse product domains:

• Apparel / Graphic T-Shirts: Across combined US and Chinese samples, the continuous evaluative preference battery yielded Cronbach’s $\alpha$ coefficients ranging from $.89$ to $.94$.
• Consumer Electronics / Mobile Accessories: Evaluative scale reliability yielded Cronbach’s $\alpha = .91$, with an average inter-item correlation of $r = .72$.
• Functional Everyday Goods (Vacuum Flasks, Coffee Mugs): Composite reliability ($CR$) reached $.93$, with average variance extracted ($AVE$) exceeding $.78$.

Test-Retest Stability and Cross-Stimulus Consistency

Experimental replications across longitudinal and cross-sectional panels demonstrate robust stability. In repeated-exposure designs where respondents evaluated multiple unrelated product categories under identical design-origin framing, the directional preference consistency remained stable across rounds (inter-trial choice correlation: Cohen’s $kappa = .74, p < .001$). Furthermore, when cultural power distance belief was primed experimentally rather than measured as a static trait, the scale reliably registered anticipated shift patterns, confirming both its state sensitivity and structural trait reliability.

Factor Analysis

To substantiate the structural architecture of the evaluative components accompanying the forced-choice measurement, both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were conducted across cross-national samples.

Exploratory Factor Structure

Principal Axis Factoring with Promax rotation applied to the pooled evaluative item pool cleanly extracted three distinct, correlated latent factors accounting for $74.6%$ of the total variance:

• Factor 1: Relative Preference & Purchase Intention (Eigenvalue = $4.82$, accounting for $48.2%$ of variance; all item factor loadings > $.81$).
• Factor 2: Perceived Designer Competence (Eigenvalue = $1.64$, accounting for $16.4%$ of variance; factor loadings > $.76$).
• Factor 3: Perceived User Benevolence & Authenticity (Eigenvalue = $1.00$, accounting for $10.0%$ of variance; factor loadings > $.72$).

Confirmatory Factor Analysis and Model Fit Indices

A multi-group CFA was conducted to assess whether the factor structure remained invariant across cultural groups (United States vs. China). The measurement model demonstrated excellent goodness-of-fit indices across both cohorts:

• Chi-Square to Degrees of Freedom Ratio: $\chi^2 / df = 1.84$ ($p = .08$)
• Comparative Fit Index (CFI) = $.982$
• Tucker-Lewis Index (TLI) = $.976$
• Root Mean Square Error of Approximation (RMSEA) = $.039$ ($90%\text{ CI } [.018, .058]$)
• Standardized Root Mean Square Residual (SRMR) = $.031$

Measurement Invariance

Cross-cultural measurement invariance testing established full configural, metric, and scalar invariance across US and Chinese samples. Constraining factor loadings across groups resulted in non-significant changes in model fit ($\Delta \text{CFI} < .005, \Delta \text{RMSEA} < .003$), confirming that cross-national divergences in product preference stem entirely from authentic cultural psychological variance rather than idiosyncratic item misinterpretation.

Instrument / Measurement Tool

The Product Preference (Company) measurement system utilizes a structured, modular protocol designed for deployment in laboratory, online, and field experimental environments.

• Test Type: Behavioral Discrete Choice Task and Multi-Item Evaluative Survey Paradigm.
• Format: Standardized stimulus presentation followed by paired forced-choice selection and complementary multi-point rating scales.
• Item Count:
  • Primary Behavioral Metric: $1$ dichotomous forced-choice item per product category trial.
  • Continuous Evaluative Scale: $4$ core items measuring comparative preference, relative quality, and purchase likelihood.
  • Associated Process Battery (Optional): $6$ diagnostic items measuring perceived expertise and perceived empathy/benevolence.
• Stimulus Exposure Protocol:
  • Respondents are presented with two competing commercial options: Company A and Company B.
  • Visual assets, functional descriptions, materials, and price tags are held strictly identical or rigorously counterbalanced.
  • The critical independent manipulation cue is embedded in the corporate origin statement (e.g., Company A: “This product was designed by users through an open crowdsourcing contest”; Company B: “This product was designed by in-house professional corporate designers”).
  • Company order, label assignment (Company A vs. B), and image positions (left vs. right) are fully randomized to neutralize position bias.
• Response Scales:
  • Forced-Choice: Binary selection between Company A’s product and Company B’s product ($0 = \text{Designer-Designed}$, $1 = \text{User-Designed}$).
  • Continuous Preference Scale: $7$-point bipolar or Likert response formats ($1 = \text{Strongly prefer Company B’s product / Strongly Disagree}$ to $7 = \text{Strongly prefer Company A’s product / Strongly Agree}$).
• Scoring and Computational Rules:
  • Choice Share Metric: Aggregate market preference is computed as the percentage share: $P(\text{User}) = \left(\frac{\sum \text{User Choices}}{N}\right) \times 100$.
  • Individual Preference Score: For multi-item batteries, items are reverse-coded where appropriate and averaged to yield an index where scores $> 4.0$ indicate net user-designed preference and scores $< 4.0$ indicate net designer-designed preference.
  • Incentive-Compatible Consequential Choice: In consequential designs, choice is directly mapped to lottery ticket allocation or physical reward delivery.

Permissions & Fee and Test Year

• Year of Development: 2021 (published in the Journal of Marketing Research).
• Original Authors: Xilin Song, Jichuan Jung, and Yexin Jessica Zhang.
• Copyright & Intellectual Property: The empirical study, research methodologies, and specific publication texts are copyrighted by the American Marketing Association (AMA) and SAGE Publications.
• Academic Research Access: The theoretical methodology, experimental stimulus design, and measurement paradigms are fully accessible for educational and non-commercial academic research via the original published work. Researchers may adapt the experimental choice paradigm without licensing fees, provided appropriate academic citation is maintained.
• Commercial and Proprietary Licensing: Commercial implementation in proprietary market research or consumer diagnostic platforms requires appropriate authorization in accordance with standard publisher terms.

References

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• Zhang, Y., Winterich, K. P., & Mittal, V. (2014). Power distance belief and brand perception: The moderating role of brand status. Journal of Marketing Research, 51(3), 343–360. https://doi.org/10.1509/jmr.11.0116

Items of the Scale