This study aims to investigate whether perceived brand globalness (PBG) and perceived brand localness (PBL) can favor brand consistency, brand clarity and perceived quality to finally influence consumer purchase intention.
Ten local-global brands across 5 fast-moving consumer goods (FMCG) product categories have been selected to test the hypotheses by conducting a survey with 404 consumers in the emerging economy of Iran.
The results show that both perceived brand globalness (PBG) and localness (PBL) contribute to brand consistency in FMCGs, with globalness being a stronger signal than localness. However, while localness positively influences brand clarity, globalness does not. Additionally, brand consistency improves perceived quality, whereas brand clarity has no impact on it.
By fostering a higher perception of brand globalness, managers can directly boost brand consistency, perceived quality and purchase intention. Conversely, increasing the perception of brand localness will enhance brand consistency and clarity but not perceived quality.
This study uniquely investigates the direct effects of PBG and PBL on the signaling theory elements of brand consistency and clarity. It distinctively introduces brand consistency as a mediator between perceived brand globalness, perceived brand localness and perceived quality, while expanding signaling theory into the underexplored Middle Eastern context.
1. Introduction
Globalization has changed how consumers interact with brands, offering a wider choice between local and global products. This shift affects consumer behavior, preferences and how cultural factors influence branding outcomes (Garrido-Castro et al., 2024). As noted by Dalmoro et al. (2015), consumers now make choices based on cultural identity, personal values and product quality. It is increasingly important to understand how brand management adapts to consumer behavior and market dynamics (Veloutsou and Delgado-Ballester, 2018). Recent reviews highlight the need for more research on balancing global and local brand positioning in a changing market (He and Ge, 2023; Liu et al., 2021). Consumers perceive global brands through symbols, foreign words, quality, availability and innovation, viewing them as globally recognized (Godey and Lai, 2011; Özsomer, 2012). Local brands, rooted in cultural heritage, appeal to those who value tradition and locality (Godey and Lai, 2011; Özsomer, 2012). Consumer attitudes toward global and local brands vary by market context (Rodrigues et al., 2024), creating a diverse market where companies must address global and local preferences.
Perceived brand globalness (PBG) and perceived brand localness (PBL) impact consumer preferences and purchase decisions. Han (2023) highlighted the role of consumer–brand identification in moderating the relationship between PBG/PBL and purchase intention, whereas Xie et al. (2015) found that PBG and PBL enhance brand identity, influencing behavioral intentions. Vuong and Khanh Giao (2020) analyzed PBG’s effect on purchase intentions and its mediating roles. However, gaps remain regarding PBG and PBL’s effects on consumer behavior (Akram et al., 2011; Mandler et al., 2021; Sichtmann et al., 2019; Liu et al., 2021; Steenkamp et al., 2003; Steenkamp, 2020). Further research is needed on how PBG and PBL influence brand consistency (BCO), brand clarity (BCL) and purchase intentions.
We will apply signaling theory to brands as our theoretical framework (Erdem and Swait, 1998). In markets where consumers cannot directly assess the quality of products or services, they rely on various signals provided by brands to make informed decisions and, based on information economics, aim to reduce information asymmetry between parties (Spence, 2002). Erdem and Swait (1998) explored brands as information signals for decision-making. While studies on signaling theory and its relation to PBG and PBL exist (Mandler et al., 2021; Özsomer and Altaras, 2008; Xie et al., 2015), none have specifically examined their impact on brand clarity (BCL) and brand consistency (BCO). Additionally, the direct effect of BCO on perceived quality (PQ) remains understudied (Erdem and Swait, 2004; Pecot et al., 2018). Understanding how PBG and PBL influence BCO and BCL is essential for brand managers to craft effective strategies and build strong brand relationships. This research helps companies refine brand positioning and messaging to better connect with consumers, which is vital for success in a globalized market and leveraging diverse consumer preferences.
Most research on global or local brands has focused on developed economies (Abrantes and Ali, 2023; Morren and Grinstein, 2016) or emerging markets such as China, Turkey and India (Das, 2014; Özsomer and Altaras, 2008; Safeer et al., 2022; Xie et al., 2015). Despite large populations (Alzubaidi et al., 2021; Haj-Salem et al., 2022) and significant economic influence from oil reserves, Middle Eastern countries have been largely overlooked. With its rich cultural diversity, the region offers unique factors influencing brand perceptions (WorldAtlas, 2023; Statista, 2022). A gap remains in understanding Middle Eastern consumer preferences (Wilson and Liu, 2011), leading to our investigation of Iran, a key emerging economy and the second most populous nation in the Middle East (Worldometer, 2022).
While previous studies by Erdem and Swait (2004) and Mandler et al. (2021) have explored related outcomes such as brand credibility and perceived quality, the novelty of our research focuses on empirically testing the direct effects of PBG and PBL on BCO and BCL. Furthermore, we introduce a novel examination of brand consistency as a mediator between PBG, PBL and perceived quality. This extends the application of signaling theory to brand consistency and clarity, particularly within the underrepresented context of an emerging Middle Eastern economy, which has been insufficiently explored in prior research. It provides a deeper understanding of how global and local brand perceptions influence long-term consumer behavior (Özsomer, 2012; Liu et al., 2021; Xie et al., 2015).
In summary, based on the information asymmetry between firms and consumers (Pecot et al., 2018) and the predictive role of PBG and PBL in signaling theory (Erdem and Swait, 1998), we developed a conceptual model to explain the impact of PBG and PBL on BCO and BCL, with the following main objectives:
To investigate the direct influence of perceived brand globalness (PBG) on brand consistency (BCO) and brand clarity (BCL).
To investigate the direct influence of perceived brand localness (PBL) on brand consistency (BCO) and brand clarity (BCL).
To investigate the direct influence of brand consistency (BCO) on perceived quality (PQ).
This study also examines whether results from Iran, an emerging economy, differ from previous studies conducted outside the Middle East. It further explores the mediating role of BCO within the proposed model. The research addresses the following questions: Does PBG affect BCO, BCL and PQ? Can BCO mediate between PBG/PBL and PQ or BCL? Are there differences between findings in the Middle East and previous studies? Answering these questions will demonstrate the impact of PBG and PBL on BCO, BCL and PQ (Xie et al., 2015) and their effectiveness as signals in improving customer decision-making.
The remainder of the paper includes a literature review on brand signaling and the effects of PBG and PBL on BCO, BCL and PQ; a methodology based on a survey of 404 participants; analysis using structural equation modeling (CB-SEM) to test hypotheses and BCO’s mediating role; and sections on results, discussion, theoretical contributions, managerial implications, limitations and future directions.
2. Theoretical background and hypotheses development
2.1 Signaling theory and role of brand consistency and clarity
Signaling theory, introduced by Erdem and Swait (1998), examines how consumers interpret brand signals in purchasing decisions. Brands use signals to convey quality, reliability, consistency and clarity. Brand clarity (BCL) and brand consistency (BCO) enhance consumers’ perceived utility by fostering a positive brand perception. BCL reduces information ambiguity, influencing consumer utility (Erdem and Swait, 1998; Erdem et al., 2006). According to Veloutsou and Delgado-Ballester (2018), brands are likely to decline and ultimately disappear unless they lose their clarity and relevant positioning; thus, BCL concerns how consumers can understand a brand’s message and value proposition. It is associated with the degree of vagueness in brand information (Erdem and Swait, 1998; Erdem et al., 2006). BCO relates to harmony among marketing mix elements, maintaining brand equity through temporal consistency (Erdem and Swait, 1998; Erdem et al., 2006). BCO is crucial for maintaining a positive and consistent brand image supported by a rich heritage (Netemeyer et al., 2004). It plays a key role in managing internal stakeholders at brand contact points in corporate branding (Burmann and Schallehn, 2008; Hatch and Schultz, 2001; Kärreman and Rylander, 2008) and is essential in brand equity management, serving as a basic element in the brand signaling process (Erdem and Swait, 1998; Park and Zaltman, 1987; Pecot et al., 2018). Consistent branding aligns all communications and actions across touchpoints, enhancing brand equity and awareness. It also fosters brand trust, increasing the likelihood of consumer purchases (Eggers et al., 2013).
When a brand maintains high consistency and clarity, it reduces consumer uncertainty, making it easier for them to perceive the brand as reliable and of high quality, which is essential for building trust and enhancing brand equity (Erdem and Swait, 2004; Netemeyer et al., 2004). BCO and BCL act as powerful signals influencing consumer perceptions, enriching loyalty and encouraging purchase intentions.
2.2 Perceived brand globalness and localness
The degree of consumer perception for global and local brands defines brand competitiveness by fostering consumer-brand relationships (Sichtmann et al., 2019). Rodrigues et al. (2024) found that consumer attitudes toward global and local brands differ depending on the market context. In developed markets, rising nationalism has led to a preference for local brands, allowing local managers to protect their market share while global brands may need to adjust their positioning for successful market entry.
Global brands are characterized by global awareness, availability, acceptance and consistent market positioning (Özsomer and Altaras, 2008). PBG occurs when consumers perceive a brand as globally available, standardized and popular (Akram et al., 2011; Batra et al., 2000; Llonch-Andreu et al., 2016; Steenkamp et al., 2003). Standardized marketing strategies enhance this global perception (Torelli and Stoner, 2015; Mandler, 2019). Consumers often prefer global brands due to their association with higher quality and prestige (Holt et al., 2004; Steenkamp et al., 2003). In contrast, local brands evoke national pride and stronger connections with local consumers (Kapferer, 2002; Roy and Chau, 2011). PBL arises when consumers see a brand as a symbol of their country and national values (Llonch-Andreu et al., 2016; Steenkamp et al., 2003). Local brands are favored for their regional availability and responsiveness to local needs, which can limit global brand dominance and support economic growth (Godey and Lai, 2011; Schuiling and Kapferer, 2004; Mandler, 2019).
Research indicates that PBG and PBL positively influence brand attitudes and purchase intentions, with a stronger preference for global brands (Davvetas et al., 2015). Steenkamp and De Jong (2010) found that consumer attitudes toward global and local brands are distinct but not entirely oppositional, as they vary based on individual perceptions. Liu et al. (2021) identified similarities and differences in how PBG and PBL are conceptualized and their effects on brand preference. Also, Safeer et al. (2022) explored how PBG and PBL affect consumer behavioral intentions, including purchase intentions and willingness to pay a higher price.
2.3 Perceived brand globalness and localness as drivers of brand consistency and brand clarity
Signaling theory is crucial for understanding how global and local brands communicate quality, trust and value to consumers. For instance, Mandler et al. (2021) delve into how global and local brands use signaling theory to establish credibility, trust and quality, with a strong emphasis on the importance of consistent brand messaging in shaping consumer behavior. Özsomer (2012) showed that PBG and local iconness affect consumer attitudes through signals of credibility and authenticity. Safeer et al. (2022) highlight how signaling theory helps understand the influence of PBG and PBL on brand authenticity, which further impacts consumer attitudes.
A strong global image is a valuable asset, often linked to high quality, reliability and customer satisfaction (Atilgan et al., 2009; Batra et al., 2000; Bhardwaj et al., 2011). Brands with global access are perceived as having superior quality and expertise in manufacturing and distribution (Özsomer, 2012; Steenkamp et al., 2003). Global signals enhance consumer self-concept and brand trust (Sichtmann et al., 2019; Strizhakova et al., 2011; Xie et al., 2015). Conversely, lower globalness may reduce brand consistency. PBG acts as a strong signal of quality, expertise and product distribution (Özsomer, 2012; Steenkamp et al., 2003), helping maintain consistent marketing mix elements with consumer perceptions (Erdem and Swait, 1998). Therefore, higher PBG is expected to enhance BCO by transmitting stable global signals across product, price, place and promotion strategies (Kotler, 1964). Thus, the first hypothesis will be:
Perceived brand globalness (PBG) is positively related to brand consistency (BCO).
This paper extends traditional research on BCL by examining PBG as a driver of BCL (Erdem and Swait, 1998). Global brands, known for their quality (Steenkamp et al., 2003; Özsomer, 2012; Xie et al., 2015; Sichtmann and Diamantopoulos, 2013), make it easier for consumers to perceive their signals as clear and precise. As PBG increases, the brand is likely to be more understandable and clearer in its global signals to consumers. Therefore, the second hypothesis is:
Perceived brand globalness (PBG) is positively related to brand clarity (BCL).
PBL signals are promoted by firms that adapt to local consumer needs through cultural elements, distribution channels and pricing strategies (Hultman et al., 2009; Loken et al., 2023; Özsomer, 2012; Steenkamp and de Jong, 2010). According to signaling theory (Erdem and Swait, 1998), consumers’ perception of these local signals may enhance brand consistency. Brands seen as strong local icons are more likely to be viewed as consistent due to their stable marketing mix signals (Godey and Lai, 2011; Schuiling and Kapferer, 2004; Mandler, 2019; Llonch-Andreu et al., 2016; Steenkamp et al., 2003). Therefore, PBL is expected to positively influence BCO by providing consistent local marketing signals. Therefore, the study proposes that:
Perceived brand localness (PBL) is positively related to brand consistency (BCO).
From a consumer perspective, higher localness signals enhance brand clarity because of familiarity, brand name, symbols or increased awareness of local icons (Özsomer, 2012; Vaziri et al., 2021). Based on signaling theory (Erdem and Swait, 1998), when consumers perceive a brand as more local, they are more likely to find it clear and straightforward. Therefore, this study expects PBL to relate positively to BCL by conveying clear local signals to consumers. Therefore, our fourth hypothesis is:
Perceived brand localness (PBL) is positively related to brand clarity (BCL).
2.4 Direct effect of brand consistency on perceived quality
Perceived Quality (PQ) refers to the consumer’s assessment of a product’s superiority or excellence (Zeithaml, 1988). Consistent brand signals enhance consumer trust and perceptions of quality (Erdem and Swait, 1998, 2004; Pecot et al., 2018). We hypothesize that BCO will positively impact PQ, though previous research has not thoroughly analyzed this direct relationship (Erdem and Swait, 2004; Pecot et al., 2018). Thus, maintaining a consistent marketing strategy across product, price, distribution and communication channels will likely improve perceived brand quality. Thus, the fifth hypothesis is:
Brand consistency (BCO) is positively related to perceived quality (PQ).
2.5 Prior effects of perceived brand globalness and localness on perceived quality
Many studies have established a positive relationship between PBG and PQ (Alden et al., 2006; Batra et al., 2000; Özsomer, 2012; Steenkamp et al., 2003; Xie et al., 2015). However, evidence on the PBL-PQ relationship remains mixed. Steenkamp et al. (2003) found no significant link, while Özsomer (2012) noted that PBL positively affects PQ in food categories but not in non-food categories. Swoboda et al. (2012) found a positive impact of PBL on retail brand quality in Asian markets, but Xie et al. (2015) showed no effect on electronic products in China. Thus, the relationship between PBL and PQ remains unclear, and this study aims to test the link between PBG/PBL and PQ.
2.6 Downstream effect on purchase intention
Research on Purchase Intention (PIN) significantly contributes to consumer behavior theories (Wang and Yu, 2017), with PIN resulting from satisfaction with the consumer experience (Chen and Yang, 2021; Maxham, 2001; Yang and He, 2011). Perceived Quality (PQ) is a key driver of consumer loyalty and satisfaction (Aaker, 1997; Woodside et al., 1989; Yoo and Donthu, 2001) and influences purchase intentions across cultural backgrounds and product categories (Baek et al., 2010; Erdem et al., 2002; Erdem and Swait, 2004). This study suggests that PBG and PBL influence PIN through BCO, BCL and PQ, enabling brands to transmit consistent and clear signals that communicate quality and drive purchase intention (Figure 1).
The conceptual model shows perceived brand globalness labelled P B G and perceived brand localness labelled P B L on the left, with solid and dashed arrows labelled H 1 to H 4 leading from P B G and P B L to brand consistency and brand clarity, brand consistency shown above brand clarity, a dashed vertical arrow linking brand consistency to brand clarity, a solid arrow labelled H 5 leading from brand consistency to perceived quality, a dashed arrow leading from brand clarity to perceived quality, and a dashed arrow leading from perceived quality to purchase intention, with a note stating solid arrows represent hypothesized paths, dashed arrows represent replicated paths, P B G equals perceived brand globalness, and P B L equals perceived brand localness.Conceptual model
The conceptual model shows perceived brand globalness labelled P B G and perceived brand localness labelled P B L on the left, with solid and dashed arrows labelled H 1 to H 4 leading from P B G and P B L to brand consistency and brand clarity, brand consistency shown above brand clarity, a dashed vertical arrow linking brand consistency to brand clarity, a solid arrow labelled H 5 leading from brand consistency to perceived quality, a dashed arrow leading from brand clarity to perceived quality, and a dashed arrow leading from perceived quality to purchase intention, with a note stating solid arrows represent hypothesized paths, dashed arrows represent replicated paths, P B G equals perceived brand globalness, and P B L equals perceived brand localness.Conceptual model
3. Methodology
3.1 Data collection
We surveyed 404 individuals in Iran, 40% conducted online and 60% through face-to-face interviews during January and February 2019. The sample size, determined with a 95% confidence level and a 5% margin of error, is appropriate for a population above 100,000 (Cochran, 1977). The study applied a semi-proportional quota sampling to the urban population distribution regarding age and gender. As shown in Table 1, the sample was well-balanced in terms of gender and diversified in terms of age in relation to the Iranian population (Neyman, 1992).
Sample distribution age and gender
| Age groups | Sample | Iran population | Total differences % | ||||
|---|---|---|---|---|---|---|---|
| Gender (frequency, %) | Gender (%) | ||||||
| Male | Female | Total | Male | Female | Total | ||
| 18–24 | 47 (11.6) | 48 (11.8) | 95 (23.4) | 10 | 11.1 | 21.1 | 2.3 |
| 25–34 | 57 (14) | 55 (13.5) | 112 (27.6) | 18.4 | 14.5 | 32.9 | −5.3 |
| 35–44 | 52 (12.8) | 63 (15.5) | 115 (28.3) | 11 | 13 | 24 | 4.3 |
| +45 | 43 (10.6) | 41 (10.1) | 84 (20.7) | 11 | 11 | 22 | −1.3 |
| Total | 199 (49) | 207 (51) | 406 (100) | 50.4 | 49.6 | 100 | |
Note(s):
Statistical Center of Iran, Yearbook (2016–2017). The gender distribution within Iran’s Total population is 50.67% male and 49.37% female
With 85 million inhabitants, Iran is the second most populous country in the Middle East after Egypt (Worldometer, 2022). The region’s unique cultural environment shapes consumer perceptions of global and local brands (WorldAtlas, 2023). As an emerging economy, Iran remains underexplored compared to other major Asian economies, and research on global and local brands in such markets is still limited. With prominent global and local brands present, our findings in Iran can be generalized to other emerging economies in the Middle East and beyond. Data were collected in Tehran, the largest and most populous city (Worldometer, 2022).
3.2 Brand selection
The study focused on five fast-moving consumer goods (FMCG) categories – food and personal care – chosen for their universal relevance and frequent purchase cycles, facilitating brand evaluation. Each category included one global and one local brand, totaling 10 brands (5 global and 5 local). Global brands were selected from the top 100 Interbrand and Ranking the Brands lists (2019) (Ranking the Brands, 2019) for their global presence, while local brands were chosen based on cultural resonance and market dominance in Iran, following Özsomer’s (2012) criteria. FMCGs were selected for their low purchase risk and high consumer involvement, reducing confounding variables such as price sensitivity and complexity (Vera and Trujillo, 2017; Laurent and Kapferer, 1985), ensuring the findings’ generalizability to emerging markets. To enhance generalizability and avoid category specificity, sets of product categories were rotated across questionnaires (Batra et al., 2000; Halkias et al., 2016) (Lopez-Lomelí et al., 2019). Each participant answered questions about one global and one local brand, with a minimum of 80 and a maximum of 82 completed responses per brand set (Table 2).
Selected brands collection
| Set of questionnaires | FMCG product category | Brands | Number of participants | |
|---|---|---|---|---|
| Global | Local | |||
| Set 1 | Tea | Twining | Golestan | 80 |
| Set 2 | Dairy products | Dannet | Kalleh | 81 |
| Set 3 | Shampoo | Loreal | Sehat | 81 |
| Set 4 | Hand wash liquid | Dove | Active | 80 |
| Set 5 | Toothpaste | Close up | Pooneh | 82 |
| Total number of questionnaires | 404 | |||
Before the final survey, a pretest was conducted with a small sample to ensure readability and clarity. The authors took additional care to avoid linguistic issues by performing a back-translation process to confirm consistency with the measurement items (KoTable and Helsen, 2000). A professional translator, unaware of the research’s purpose, compared the original English and back-translated versions. Minor adjustments were made to the Persian version based on the translator’s feedback for the main study.
4. Scales and measurements
The exogenous latent variables are PBG and PBL, while the endogenous latent variables are BCO, BCL, PQ and PIN. This study measures the perceived globality and locality of each brand. Table 3 provides the sources, properties and psychometrics for the scales, with all items measured on a seven-point Likert scale (1 = completely disagree, 7 = completely agree).
Constructs and measures
| Constructs | Measurement items | Sources |
|---|---|---|
| Brand consistency (BCO) | 1. [Brand] 's image in advertisements and commercials has been consistent for many years 2. The quality of [brand] has been consistent for many years 3. [Brand] 's prices, ads, specials, and products match its overall image 4. Everything is consistent about [brand]- fit, quality, prices, ads, variety, specials, etc | Erdem and swait (1998); (2004) |
| Brand clarity (BCL) | 1. I know what this Brand stands for 2. I have trouble figuring out what image this brand is trying to create (R) | Erdem and Swait (1998) |
| Perceived quality (PQ) | 1. The quality of this brand is very high 2. In terms of overall quality, I would rate this brand as … | Erdem et al. (2006) |
| Perceived brand globalness (PBG) | 1. I think this is a global brand 2. I believe that consumers from other countries buy this brand 3. This brand is only sold in [country] (R) | Batra et al. (2000); Steenkamp et al. (2003) |
| Perceived brand localness (PBL) | 1. I associate this brand with things that are from [country] 2. For me, this brand does not represent what [country] is (R) 3. For me, this is a good symbol of [country] | Steenkamp et al. (2003) |
| Purchase intention (PIN) | 1. It is very likely that I will buy this brand 2. I will purchase this brand the next time I need [such a product] 3. I will definitely try this brand | Putrevu and Lord (1994) |
Note(s): R = Reverse question
4.1 Construct reliability and validity
The measurement model’s quality was evaluated through unidimensionality, convergent validity, reliability and discriminant validity. The results showed Cronbach’s alpha coefficients and composite reliability (CR) values exceeding 0.70, indicating acceptable reliability. An exploratory factor analysis (EFA) was conducted using SPSS to assess construct validity. The decision to use EFA over CFA was deliberate, as EFA better suited the study’s context. Adapted from validated scales (e.g. Erdem and Swait, 1998; Özsomer, 2012), EFA assessed construct validity in the underexplored Iranian market, addressing potential dimensionality differences. Its suitability for new cultural contexts (Henson and Roberts, 2006; Worthington and Whittaker, 2006) ensured theoretical alignment while addressing cultural nuances.
Standardized factor loadings exceeded 0.7, and all t-test values were highly significant, supporting convergent validity. Factor loadings ranged from 0.771 to 0.961 for all primary constructs, and the average variance extracted (AVE) exceeded 0.50, reaching the recommended threshold of 0.70 (Nunnally and Bernstein, 1994), indicating strong reliability and validity (Table 4).
Construct reliability and validity
| Total observations (n = 404) | |||||
|---|---|---|---|---|---|
| Constructs | Indicator | Factor loadings | Cronbach’s alpha | CR | AVE |
| Brand clarity | BCL1 | 0.952 | 0.849 | 0.928 | 0.866 |
| BCL2 | 0.909 | ||||
| Brand consistency | BCO1 | 0.917 | 0.943 | 0.959 | 0.853 |
| BCO2 | 0.942 | ||||
| BCO3 | 0.927 | ||||
| BCO4 | 0.908 | ||||
| Perceived brand globalness | PBG1 | 0.946 | 0.878 | 0.923 | 0.802 |
| PBG2 | 0.956 | ||||
| PBG3 | 0.771 | ||||
| Perceived brand localness | PBL1 | 0.889 | 0.905 | 0.936 | 0.830 |
| PBL2 | 0.893 | ||||
| PBL3 | 0.949 | ||||
| Purchase intention | PIN1 | 0.957 | 0.957 | 0.972 | 0.921 |
| PIN2 | 0.960 | ||||
| PIN3 | 0.961 | ||||
| Perceived quality | PQ1 | 0.960 | 0.914 | 0.959 | 0.921 |
| PQ2 | 0.959 | ||||
Note(s): CR = composite reliability (CR); AVE = average variance extracted
Additionally, discriminant validity was assessed by comparing the correlations of latent variables with the square root of the average variance extracted (AVE). The diagonal values exceeded inter-construct correlations, confirming adequate discriminant validity (Fornell and Larcker, 1981). Thus, this measure is considered a reliable and valid instrument for the seven models based on all criteria (Table 5).
Means, standard deviations and discriminant validity (Fornell–Larcker criterion)
| Total observations (n = 404) | ||||||||
|---|---|---|---|---|---|---|---|---|
| Measures | MEAN | SD | BCL | BCO | PBG | PBL | PIN | PQ |
| BCL | 4.712 | 1.610 | 0.931 | |||||
| BCO | 4.801 | 1.613 | 0.588 | 0.924 | ||||
| PBG | 4.782 | 1.748 | 0.368 | 0.639 | 0.895 | |||
| PBL | 3.975 | 1.595 | 0.180 | 0.108 | −0.167 | 0.911 | ||
| PIN | 4.797 | 1.769 | 0.575 | 0.833 | 0.646 | 0.140 | 0.959 | |
| PQ | 4.758 | 1.572 | 0.571 | 0.867 | 0.716 | 0.038 | 0.857 | 0.960 |
Note(s): PBG = Perceived Brand Globalness. PBL = Perceived Brand Localness. BCO = Brand Consistency. BCL = Brand Clarity. PQ = Perceived Quality. Pin = Purchase Intention. Bold figures on the diagonal show the square root of the average variances extracted AVEs; numbers below the diagonal represent the squared inter-construct correlations
5. Results
5.1 Structural model evaluation
After confirming the psychometric properties of the measurement instrument, we estimated the structural model using SEM and bootstrapping with 2,000 samples and 95% confidence intervals (Preacher and Hayes, 2008; Strizhakova et al., 2011; Zhao et al., 2010). We used AMOS v24 to calculate the direct effects of each latent variable. The model fit the data well, with fit indices showing a good representation (χ2 = 544.509, d.f. = 108, χ2/d.f = 5.04, p = 0.00; CFI = 0.969; NFI = 0.962; RMSEA = 0.071; GFI = 0.930), exceeding recommended thresholds (Bagozzi and Yi, 1988; Hu and Bentler, 1999; Byrne, 2010). The covariance between PBG and PBL was significant at −0.232 (p < 0.001). PBG and PBL explained 54.5% of BCO’s variance, 42.6% of BCL’s variance (R2 = 0.426) and together with BCO and BCL, explained 91.6% of PQ’s variance. All predictors explained 85% of PIN’s variance. Overall, the model showed adequate fit (Table 6).
Structural parameter estimates and goodness-of-fit indexes
| Connections | SEM model | |||
|---|---|---|---|---|
| Hypothesized path | β (standardized estimates) | SE | C.R. | p-value |
| PBG → BCO | 0.75 | 0.049 | 17.47 | *** |
| PBG → BCL | 0.041 | 0.066 | 0.893 | n.s. |
| PBL → BCO | 0.231 | 0.027 | 8.029 | *** |
| PBL → BCL | 0.109 | 0.038 | 3.463 | *** |
| BCO → PQ | 0.717 | 0.036 | 21.6 | *** |
| Replicated paths | ||||
| PBG → PQ | 0.254 | 0.035 | 9.144 | *** |
| PBL → PQ | 0.018 | 0.018 | 1.029 | n.s. |
| BCO → BCL | 0.607 | 0.058 | 13.09 | *** |
| BCL → PQ | 0.066 | 0.018 | 3.124 | ** |
| Downstream effect | ||||
| PQ → PIN | 0.922 | 0.027 | 38.003 | *** |
| Goodness-of-fit measures | ||||
| 2 | 544.509 | |||
| d.f | 108 | |||
| χ²/ d.f | 5.042 | |||
| CFI | 0.969 | |||
| NFI | 0.962 | |||
| RMSEA | 0.071 | |||
| GFI | 0.930 | |||
| R² (BCO) | 0.545 | |||
| R² (BCL) | 0.426 | |||
| R² (PQ) | 0.916 | |||
| R² (PIN) | 0.85 | |||
| N | 404 | |||
Note(s):
*p < 0.05, **p < 0.01, ***p < 0.001, n.s. Not significant. PBG = Perceived Brand Globalness. PBL = Perceived Brand Localness. BCO = Brand Consistency. BCL = Brand Clarity. PQ = Perceived Quality. Pin = Purchase Intention. β = Standardized Estimates (Standardized Regression Weights). SE = Standard Error. C.R. = Critical Ratio. 2 = Chi-square. d.f. = Degree of freedom. χ2/d.f = adjusted Chi-square. CFI = Comparative Fit Index. NFI = Normed Fit Index. RMSEA = Root Mean Square Error of Approximation. GFI = Goodness of fit index. R2 = Squared Multiple Correlations. n = Sample size
5.2 Test of hypotheses (direct paths)
PBG positively affects BCO and this relationship is highly significant (β = 0.75, p < 0.001), therefore H1 is supported. However, and contrary to our expectations, PBG did not influence of BCL (β = 0.041, p > 0.05), so H2 is not supported. One potential explanation lies in cultural factors specific to Iran, where global brands, relying on standardized marketing strategies, may fail to adapt to local cultural nuances, reducing their perceived clarity in this culturally rich market (Özsomer, 2012). PBL positively influences BCO (β = 0.231, p < 0.001), thus, H3 holds. In addition, the results show a positive effect of PBL on BCL (β = 0.109, p < 0.001), so H4 is supported. Also, BCO positively influences PQ (β = 0.717, p < 0.001); therefore, the data supports H5 (Tables 6 and 7) (Figure 2).
Summary results for direct paths
| Hypotheses | β | Significant? | Conclusion |
|---|---|---|---|
| H1. PBG → Brand consistency | 0.75 | Yes | Supported |
| H2. PBG → Brand clarity | 0.041 | No | Not supported |
| H3. PBL → Brand consistency | 0.231 | Yes | Supported |
| H4. PBL → Brand clarity | 0.109 | Yes | Supported |
| H5. Brand consistency → Perceived quality | 0.717 | Yes | Supported |
Note(s):
PBG = Perceived Brand Globalness. PBL = Perceived Brand Localness. β = Standardized estimates
The final model shows perceived brand globalness labelled P B G and perceived brand localness labelled P B L on the left, with solid arrows labelled H 1 to H 4 leading to brand consistency and brand clarity, including beta values shown next to each path, a dashed vertical arrow connecting brand consistency to brand clarity, a solid arrow labelled H 5 leading from brand consistency to perceived quality, dashed arrows leading from P B G, P B L, and brand clarity to perceived quality, and a dashed arrow leading from perceived quality to purchase intention, with solid arrows indicating hypothesized paths and dashed arrows indicating replicated paths.Final model
The final model shows perceived brand globalness labelled P B G and perceived brand localness labelled P B L on the left, with solid arrows labelled H 1 to H 4 leading to brand consistency and brand clarity, including beta values shown next to each path, a dashed vertical arrow connecting brand consistency to brand clarity, a solid arrow labelled H 5 leading from brand consistency to perceived quality, dashed arrows leading from P B G, P B L, and brand clarity to perceived quality, and a dashed arrow leading from perceived quality to purchase intention, with solid arrows indicating hypothesized paths and dashed arrows indicating replicated paths.Final model
In the replicating paths, PBG was positively related to PQ (β = 0.254, p < 0.001), so this supported previous studies (Alden et al., 2006; Batra et al., 2000; Özsomer, 2012; Steenkamp et al., 2003; Xie et al., 2015) whereas our results show that the impact of PBL on PQ was non-significant (β = 0.018, p > 0.05). BCO is positively related to BCL (β = 0.607, p < 0.001), and there is a positive impact of BCL on PQ (β = 0.066, p < 0.01). Ultimately, in line with expectations, the downstream effect reaffirms that PQ is positively related to PIN (β = 0.922, p < 0.001).
5.3 Mediation role of brand consistency
Additionally, this study examines whether BCO mediates the relationships between PBG/PBL and PQ, as well as between PBG/PBL and BCL. To investigate BCO’s mediating role, we used advanced bootstrapping methods (Preacher and Hayes, 2008; Zhao et al., 2010) with bias-corrected confidence intervals, 2000 samples and 95% confidence intervals, as recommended by Hair et al. (2017).
We propose that BCO mediates the relationship between PBG and PQ. The standardized indirect effect of PBG on PQ through BCO is 0.537, which is statistically significant (p < 0.01). Additionally, the standardized direct effect of PBG on PQ is also significant (β = 0.254, p < 0.001), indicating a partial mediation effect of BCO between PBG and PQ. Since there is no direct effect between PBL and PQ (β = 0.018, p > 0.05), BCO does not mediate this relationship (Table 8).
Mediation tests
| Pathways of indirect effects | Standardized indirect effect | β (standardized direct effect) | Result |
|---|---|---|---|
| PBG → BCO → PQ | 0.537 (***) | 0.254 (***) | Partial mediation |
| PBL → BCO → PQ | 0.165 (***) | 0.018 (n.s.) | – |
| PBG → BCO → BCL | 0.455 (***) | 0.041 (n.s.) | – |
| PBL → BCO → BCL | 0.140 (***) | 0.109 (***) | Partial mediation |
Note(s):
PBG = Perceived Brand Globalness, PBL = Perceived Brand Localness, BCO = Brand Consistency, BCL = Brand Clarity, PQ = Perceived Quality, *p < 0.05, **p < 0.01, ***p < 0.001, n.s. Not significant
BCO increases BCL (Erdem and Swait, 1998), but there is limited empirical evidence supporting BCO’s mediating role between PBG/PBL and BCL. We analyzed this pathway and, according to H2, found no significant direct relationship between PBG and BCL (β = 0.041, p > 0.05). However, the indirect effects between PBG and BCO (H1) and between BCO and BCL are significant (β = 0.455, p < 0.001). Thus, BCO does not mediate the link between PBG and BCL.
On the other hand, given the positive relationships between PBL and BCO and between BCO and BCL, we tested H4. The standardized indirect effect of PBL on BCL through BCO is 0.140 and significant (p < 0.01). With a significant direct effect (β = 0.190, p < 0.01), BCO partially mediates the link between PBL and BCL (Table 8).
6. Theoretical contributions
Drawing upon the signaling theory (Erdem et al., 2008; Pecot et al., 2018), our findings suggest that perceived brand globalness (PBG) and perceived brand localness (PBL) serve as valuable signals that directly enhance brand consistency (BCO) in an emerging market. Higher perceived brand globalness (PBG) and localness (PBL) contribute to more robust marketing mix strategies, improving brand consistency. This may result from better marketing knowledge, resources or professionalism in managing global or local brands. PBG has a slightly stronger effect than PBL, as it signals greater trustworthiness and consistency, acting as a potent indicator of brand quality and expertise (Strizhakova et al., 2011; Xie et al., 2015; Özsomer, 2012; Steenkamp et al., 2003). Additionally, PBL positively influences BCL, marking a new finding in our study. This effect may arise because localness signals, through brand names and symbols, make local brands clearer and more relatable as national icons (Özsomer, 2012; Vaziri et al., 2021). As consumers already have a strong image of domestic brands, higher PBL enhances their perception of BCL.
Our study complements prior research that examined perceived brand globalness (PBG) and localness (PBL) as antecedents of brand credibility, prestige, perceived quality and purchase likelihood (Mandler et al., 2021; Das, 2014; Özsomer, 2012; Steenkamp et al., 2003; Xie et al., 2015). We found that PBG significantly affects perceived quality (PQ), consistent with findings from earlier studies (Özsomer, 2012; Swoboda et al., 2012; Sichtmann and Diamantopoulos, 2013; Steenkamp et al., 2003; Mandler et al., 2021; Xie et al., 2015). However, our results show that PBL does not significantly impact PQ, aligning with studies conducted in China (Xie et al., 2015) and Turkey (Özsomer, 2012). As expected, PQ is positively related to PIN, as found in other emerging markets like India (Baek et al., 2010; Erdem et al., 2002; Das, 2014).
Furthermore, as expected, the results show a positive direct effect of brand consistency on perceived quality (PQ). This occurs because consumers perceive signals of a coherent and well-structured marketing mix (Erdem and Swait, 1998), leading them to view consistent brands as higher quality. The findings also confirm that higher BCO leads to higher BCL, and BCL is positively related to PQ. Brands with consistent features are seen as clearer and of higher quality. However, standardized coefficients indicate that BCO is a stronger signal of PQ than BCL.
This study provides initial evidence that brand consistency is a key mediator for both PBG, PBL and perceived quality, a facet not previously explored in the literature. This suggests that when consumers receive brand signals with higher perceived globalness, consistent brands are more likely to be seen as higher quality. A consistent brand likely signals that a company is organized and professional, capable of delivering uniform quality across its offerings. Brand consistency enhances clarity (Erdem and Swait, 1998), and our results indicate that brand consistency mediates the relationship between perceived brand localness and brand clarity. Higher perceived localness of a brand is associated with increased clarity through consistency.
7. Conclusion and practical implications
This research offers practical applications for firms marketing their brands globally or domestically, particularly in the Middle Eastern context. Companies should focus on understanding consumer knowledge rather than perceptions. The study calls for further research on marketing strategies and investment approaches for local and global brands in developed and emerging markets. This insight can guide companies in selecting content for their marketing campaigns (Garrido-Castro et al., 2024). It highlights how FMCG brands should be re-positioned in Middle Eastern emerging markets. Brand managers must recognize that their brands are valued not only for quality (Xie et al., 2015) but also for creating consistent, clear signals that aid customer decision-making and purchase intent.
From a practical perspective, our study highlights that companies should deliver consistent brand signals of localness or globalness through their marketing strategies, including product quality, pricing, promotion and distribution, to increase clarity. Global companies need to promote PBG, which is critical in strengthening BCO. However, to improve BCL, they should implement marketing actions revealing how their global brands adapt to local characteristics, transforming them into “glocal” brands (Deliceırmak, 2022; Grigorescu and Zaif, 2017). This approach can redefine the interaction between global and local brand strategies, offering new opportunities in the evolving market landscape (Liu et al., 2021).
Furthermore, the study found no significant impact of PBG on brand clarity, and global brands in such cultural contexts may need to embrace supplementary strategies to guarantee that their messages are clear and understood. For example, Colgate, a global brand in many Asian markets, has perfectly balanced its global identity and local cultural preferences. It offers herbal variants of toothpaste infused with local ingredients such as neem and clove, which are widely known in traditional oral care practices (Pandey, 2017; Attri, 2017). This approach allows Colgate to keep its global identity as a reliable oral care brand while aligning with local cultural preferences. Similarly, Iranian consumers may not perceive greater brand clarity through higher globalness signals, indicating a need for better communication strategies that emphasize globalness while adapting to local cultural values (Dong and Yu, 2020; Grigorescu and Zaif, 2017).
For local brands, an increase in the perception of localness will positively impact both brand consistency and clarity. However, to enhance perceived quality, local brand managers should focus on strengthening brand consistency, as clarity does not have a positive effect on quality. Since PBG has a stronger link to brand consistency than PBL, local brand managers should prioritize marketing strategies that enhance globalness perception, helping transform local brands into “glocal” brands while improving perceived quality.
If brand managers consistently manage product quality, image, price, distribution and promotional activities – the entire marketing mix – consumers will perceive the brands as higher quality, leading to increased purchase intention. Rodrigues et al. (2024) note that rising nationalism in developed markets has increased the preference for local brands, enabling local managers to protect their market share. For instance, global brands such as Milo and Nescafé, often perceived as local, can leverage this perception or adjust their positioning for successful entry. Thus, further research is needed on local and global brands’ marketing strategies and investment approaches in developed and emerging markets (Rodrigues et al., 2024).
We found that for Middle Eastern consumers, perceived brand localness positively affects brand clarity through brand consistency. When a global brand is perceived as having local signals, consistency across all touchpoints enhances clarity and transparency, leading to a higher perceived quality. Marketers should consider this when appealing to consumers who value the localness of global brands. Local brand managers can enhance their appeal by aligning with local traditions and cultural values while maintaining high product quality (Davvetas and Diamantopoulos, 2016). This strategy not only strengthens brand consistency and clarifies the brand’s message but also plays a key role in gaining consumer preference. A well-integrated marketing strategy that combines local cultural features can enhance the brand’s appeal and consistency, especially in emerging markets (Steenkamp, 2020). The findings provide further information on PBG and PBL influence BCO, BCL and PQ. Brand managers must maintain a consistent image across all channels to build a cohesive brand identity. Our study reveals that Middle Eastern consumers rely on brand consistency to assess brand quality, which significantly impacts their perceptions.
8. Limitations and future directions
Our model needs replication in other economies to validate its findings. While current research focuses on environmental dynamics like technological advancements and globalization’s impact on brands, future studies should explore how stable elements evolve (Veloutsou and Delgado-Ballester, 2018). Although we used signaling theory to explain PBG and PBL, further exploration through lab experiments and quantitative and qualitative research is needed.
Our results show that PBG has a stronger impact on BCO than PBL. Future studies could examine the influence of “PBGlocalness” on BCO and BCL and compare these effects with those of PBG and PBL. It is also worth investigating why PBG is unrelated to BCL in this context.
As Steenkamp (2020) suggests, global brand strategies must be adaptable to local markets, making it necessary for future research to explore how these strategies perform in diverse cultural landscapes. Comparative analyses across different emerging economies or cultural settings are crucial to generalizing the findings beyond Iran. Additionally, as noted by Cavusgil et al. (2018) and Zhu et al. (2024), understanding identity clarification in marketing and how it interacts with local and global branding is critical for future research.
Future research should consider moderators such as market environment, consumer attitudes (ethnocentrism, cosmopolitanism, materialism) or a dummy variable (local/global) that may alter the impact of PBG and PBL on downstream factors. Studies could also explore durable goods and culture-irrelevant (e.g. electronics) vs culture-relevant (e.g. food) products (Xie et al., 2015).
Moreover, with the rapid growth of digitalization (Gürhan-Canli et al., 2018; Liao et al., 2020), it is crucial to understand how consumers perceive PBG and PBL online (Liu et al., 2021). Follow-up studies should validate the model in online shopping contexts, exploring shifts in consumer interactions with global and local brands through social media and e-commerce. Neuromarketing methods could further illuminate perceptions of globalness or localness via brand visuals and packaging.
Finally, although the data was collected in 2019, the study’s framework remains relevant, addressing core PBG and PBL dynamics. Post-2019 changes, such as accelerated digitalization and e-commerce growth during COVID-19, may have influenced these dynamics (Gürhan-Canli et al., 2018; Liu et al., 2021).
Funding: SUSTAINABLE CONSUMPTION AND THE FUTURE OF BRANDS: PID2021-124089NB-I00.
