https://nmrj.ui.ac.ir/ New Marketing Research Journal en daily 1 Sat, 21 Mar 2026 00:00:00 +0330 Sat, 21 Mar 2026 00:00:00 +0330 https://nmrj.ui.ac.ir/article_30192.html The advent of social media has revolutionized consumer interactions, giving rise to the phenomenon of the “online firestorm”. This phenomenon entails rapid and widespread public backlash against organizations driven by negative online feedback and exerts significant repercussions on brand reputation. This study aimed to review and classify primary literature regarding online firestorms and propose a framework for future research. Employing a systematic mapping method, this study analyzed 45  research articles published between 2014  and 2024. Findings indicated that the majority of studies had been conducted by utilizing a qualitative approach at the organizational level of analysis. Theories like Social Norm, Social Influence, Moral Panic, and Situational Crisis Communication Theory (SCCT) served as prevalent theoretical frameworks in explicating this phenomenon. Furthermore, social and communicational deficits had been identified as primary drivers underlying the formation of online firestorms. The scholarly focus on the organizational level had underscored the impact of this phenomenon on corporate reputation and financial performance; specifically, erroneous decisions, poor communication, and unethical behaviors had been identified as major triggers. Research had predominantly been conducted in European and American contexts attributed to the heightened consumer sensitivity toward social and communicational violations and the distinct cultural values inherent to these societies. Platforms like Twitter and Facebook had been considered the primary venues for these firestorms due to their technical affordances and the rapid propagation of critical reactions. The extensive application of social science and psychological theories had elucidated the roots of social interactions, collective emotional arousal, and cognitive biases in explaining online firestorms. Introduction Proliferation of digital platforms has fundamentally transformed stakeholder interactions during organizational crises (Zarepour Nasirabadi et al., 2023; Rahimnia et al., 2019). The networked nature of social media has given rise to the phenomenon of “online firestorms” defined by Pfeffer et al. (2014) as the sudden discharge of massive volumes of Negative electronic Word-of-Mouth (NeWOM) against a person, brand, or organization. Characterized by viral speed and high emotional intensity, this phenomenon poses a serious threat to organizational reputation (Rost & Stahel, 2022). It is estimated that approximately 50% of organizations have encountered this issue within the past two years (Delgado-Ballester et al., 2021). Researchers like Rauschnabel et al. (2016) and Chan et al. (2018) have examined the triggers and consequences of this phenomenon. Furthermore, studies by Kim et al. (2021) and Rost and Stahel (2022) have confirmed the role of psychological theories, including social norms and moral panic, in explaining this phenomenon. Despite the increase in research over the past decade, the existing literature remains fragmented and requires systematic consolidation (Li et al., 2019). This study aimed to provide a comprehensive overview of existing research by addressing 5 fundamental questions: the research approaches employed, levels of analysis, temporal changes in focus areas, reciprocal relationships between theoretical perspectives and focus areas, and the associations among firestorm audiences, geographical location, and triggers of firestorm emergence. Materials & MethodsThis study employed a systematic mapping methodology following the guidelines of Petersen et al. (2008) and Batory (2005). Unlike traditional systematic reviews, this approach focuses on mapping the landscape of a specific topic rather than answering a targeted research question (Heidari et al., 2018). As Sohrabi et al. (2021), citing Grant and Booth (2009), have noted, this type of review aims to categorize existing research to identify knowledge gaps. The Scopus citation database was selected as the data source due to its comprehensive coverage of credible sources (Caviggioli & Ughetto, 2019). The search was conducted by using keywords, such as “online firestorm”, “social media firestorm”, “collaborative brand attacks”, and “shitstorm” across title, abstract, and keyword fields within the timeframe of 2014 to 2024. From 70 identified articles, after removing duplicates and applying exclusion criteria, including non-English texts, dissertations, and editorial notes, 45 studies were selected.For quality assessment, the CASP checklist with 10 evaluation criteria was applied. This assessment focused on 3 dimensions: validity, methodology, and applicability of findings. Only articles scoring above 35 out of 50 were included in the analysis. Finally, the studies were classified based on research approach (quantitative, qualitative, mixed), level of analysis (individual, organizational, societal), focus area (what, why, how), theoretical perspectives, and geographical context. Research FindingsA systematic analysis of 45 selected studies within the 2014- 2024 timeframe revealed an unbalanced pattern in the geographical and platform distribution of the “online firestorm” phenomenon. The geographical focus of the research was predominantly centered on the United States and Germany, reflecting the mature digital activism ecosystem in these regions, whereas research in Asia and Africa accounted for a negligible share. From a technical platform perspective, “Twitter” hosting more than half of the studied cases served as the primary locus for the formation of these crises due to its instantaneous nature and rapid information dissemination capabilities with Facebook ranking second.An examination of methodological trends indicated a predominance of qualitative approaches (such as content analysis and text mining) over quantitative methods, suggesting the exploratory stage of knowledge in this field. The dominant level of analysis was the “organizational level” focusing on reputational consequences for firms, while social and individual levels had been less explored. The temporal evolution of the research also demonstrated a significant shift from describing the “what” of the phenomenon towards explaining the “why” and, more recently, the “how” of its management. In the theoretical dimension, pluralism was evident; to explain the “why”, theories of “social norm”, “moral panic”, and “social influence” exhibited the highest frequency, whereas in explaining crisis management mechanisms, “Situational Crisis Communication Theory (SCCT)” remained dominant. A key finding was the revelation of a correlation between “geographical context” and “trigger type”: in Western societies (Europe and the US), firestorms were mainly rooted in “social and communicational” violations (such as racism or insults), while in Asian societies, functional inefficiencies and “product/service failures” were the primary drivers of public outrage. Discussion of Results & ConclusionSynthesizing the findings of this study allowed for the delineation of a 3-stage “causal-processual model” (input-process-output) for the dynamics of online firestorms that transcended technological determinism. At the input stage, “cultural context” acted as a moderating variable; the high sensitivity of Western societies to normative values as opposed to the sensitivity of Eastern societies to functionalism dictated the type of crisis-inducing trigger. At the process stage, platform architecture (specifically Twitter) played the role of an “algorithmic amplifier”. Here, psychological mechanisms (grounded in social norm and moral panic theories) transformed fragmented individual complaints into “collective moral outrage” through emotional contagion. At the output stage, the literature focus on the organizational level and SCCT indicated that success in crisis containment was contingent upon the strategic alignment of the organizational response with the perceived origin of the crisis. This study argued that firestorms were inherently “sociological” phenomena, for which technology served merely as an acceleration medium. The scarcity of research in non-Western contexts (except for limited cases on China’s Weibo) represented a serious knowledge gap resulting from structural and cultural barriers to the disclosure of conflicts. Therefore, it is suggested that future research move beyond qualitative single-case studies towards “longitudinal quantitative” designs and “predictive modeling”. Furthermore, it is essential to expand the focus from text-centric platforms (Twitter) to image-centric and emerging platforms (such as TikTok) and develop indigenous crisis management models for emerging markets (like the Middle East) by considering specific cultural components. https://nmrj.ui.ac.ir/article_30216.html Objective: Greenwashing refers to the growing prevalence of misleading claims by companies regarding the environmental friendliness of their products or services. This study investigated the impact of greenwashing on the purchasing intentions of Generation Z. Methodology: The statistical population for this research comprised all customers of Iran Khodro in Tehran, constituting an unlimited population. A random sample of 384 customers was selected by using Cohen’s formula. Data were gathered through a questionnaire encompassing 8 dimensions and 30 items. The validity of the questionnaire was assessed through face-content validity and construct validity, while its reliability was confirmed by calculating Cronbach’s alpha coefficient and composite reliability. To test the research hypotheses, inferential statistics and the Partial Least Squares (PLS) technique were utilized. Findings: The results indicated that greenwashing negatively impacted brand image while positively influencing brand skepticism and cynicism. Additionally, brand skepticism correlated positively with brand hate and brand cynicism contributed to a negative attitude toward the brand. Furthermore, brand image significantly enhanced the purchasing intentions of Generation Z, while brand hate and a negative attitude detracted from this intention. Social influence moderated the relationship between brand hate and the purchasing intentions of Generation Z. Conclusion: Overall, the findings suggested that greenwashing significantly undermined purchasing intentions among Generation Z by damaging brand image and fostering negative emotions, such as skepticism, cynicism, and hate toward the brand. IntroductionIn recent decades, escalating environmental crises, climate change, and increasing social and regulatory pressures have prompted companies to prioritize sustainability and environmental responsibility within their marketing and communication strategies. In this context, green marketing has emerged in response to the rising consumer demand for environmentally responsible corporate behavior. However, with the proliferation of green claims, the issue of greenwashing has also escalated. Greenwashing refers to practices, through which companies portray themselves as environmentally responsible without demonstrating real, measurable, and substantiated environmental performance (de Freitas Netto et al., 2020).The significance of this phenomenon is particularly pronounced when green messages target Generation Z consumers. Growing up in a digital age, this generation has access to vast amounts of information and exhibits high levels of ethical sensitivity and environmental awareness. Generation Z critically assesses the credibility of brand claims and often reacts negatively when inconsistencies arise between corporate rhetoric and actual practices. Such reactions can lead to diminished trust, a tarnished brand image, and a subsequent decline in purchase intention (Balaskas et al., 2025).Within the automotive industry—often seen as one of the most environmentally detrimental sectors—greenwashing takes on strategic importance as environmental claims are frequently met with heightened skepticism. While there is a growing body of research on greenwashing, existing studies have not adequately explored how greenwashing influences the purchasing intentions of Generation Z through interconnected cognitive, emotional, and social mechanisms. Accordingly, this study aimed to develop an integrated framework that elucidated the effects of greenwashing on the purchasing intentions of Generation Z within the Iranian automotive industry, emphasizing the roles of brand image, brand skepticism, brand pessimism, negative attitudes toward the brand, brand aversion, and the moderating influence of social factors. Theoretical BackgroundGreenwashing is defined as a deceptive communication strategy characterized by a disconnection between marketing messages and actual corporate environmental performance. Systematic reviews reveal that greenwashing manifests in various forms, including vague environmental claims, misleading eco-labels, symbolic use of green imagery, and exaggeration of minor environmental initiatives (de Freitas Netto et al., 2020). While such practices may create favorable impressions in the short term, their eventual exposure can lead to severe and lasting negative repercussions for consumer perceptions.One of the most significant consequences of greenwashing is the erosion of brand image. Brand image encompasses consumers’ overall perceptions of a brand credibility, responsibility, and ethical orientation. When greenwashing is detected, the positive green brand image deteriorates, transforming into one characterized by distrust and perceived dishonesty. This shift can influence consumer behavior both directly and indirectly (Tu et al., 2024). For Generation Z consumers, who prioritize authenticity and transparency, the negative impact of greenwashing is particularly pronounced (Putra & Darma, 2024).At the cognitive level, greenwashing fosters brand skepticism. This skepticism arises when consumers question the sincerity and accuracy of brand claims. Empirical evidence indicates that skepticism is often the initial cognitive response to suspicious environmental messaging and can serve as a precursor to deeper, more enduring negative attitudes (Zioło et al., 2024). As skepticism escalates, it may evolve into brand pessimism, reflecting a generalized belief that brands deliberately deceive consumers and prioritize self-interest over genuine environmental and social responsibility (Balaskas et al., 2025).At the emotional level, cognitive distrust can escalate into intense negative emotions, such as brand aversion. Brand aversion represents one of the most damaging emotional responses consumers can develop, often resulting in purchase avoidance, negative word-of-mouth, and active resistance toward the brand. Recent studies indicate that brands accused of greenwashing are particularly susceptible to the swift emergence of brand aversion, especially among Generation Z consumers (Zioło et al., 2024).In addition to these cognitive and emotional mechanisms, social influence plays a crucial role in shaping the responses of Generation Z to greenwashing. This generation is significantly affected by peer opinions, social networks, and digital interactions. Negative perceptions of a brand can spread quickly through social media platforms, amplifying their effect on individual purchase intentions. Consequently, social influence serves as an important moderating factor in the relationship between brand aversion and purchase intention (Balaskas et al., 2025).Materials & MethodsThis study was applied in nature and utilized a descriptive survey design conducted cross-sectionally. The statistical population included all customers of Iran Khodro in Tehran. Due to the absence of an official customer database, the sample size was calculated by using Cochran’s formula for an unlimited population, resulting in a sample of 384 respondents selected through convenience sampling.Data were collected by using an adapted questionnaire comprising 8 latent constructs and 30 measurement items, which captured greenwashing, brand image, brand skepticism, brand pessimism, brand aversion, negative brand attitude, social influence, and purchase intention. The validity of the questionnaire was established through face validity, content validity, and construct validity, while reliability was assessed by using Cronbach’s alpha and composite reliability indices. Given the non-normal distribution of the data, hypothesis testing was conducted by using Partial Least Squares Structural Equation Modeling (PLS-SEM) with Smart PLS software. Research FindingsThe empirical results indicated that greenwashing significantly negatively impacted brand image while positively influencing brand skepticism and brand pessimism. Furthermore, brand skepticism greatly increased brand aversion and brand pessimism notably intensified negative attitudes toward the brand.The findings also revealed that brand image had a significant positive effect on the purchase intentions of Generation Z, whereas brand aversion and negative brand attitudes exerted significant negative effects on purchase intention. One of the key contributions of the study was the confirmation of the moderating role of social influence in the relationship between brand aversion and purchase intention. Specifically, higher levels of social influence amplified the adverse impact of brand aversion on the purchase intentions of Generation Z. Model fit indices indicated satisfactory goodness of fit for the proposed conceptual framework. Discussion of Results & ConclusionThe results demonstrated that greenwashing was not merely an ineffective short-term communication strategy but a detrimental practice that undermined the establishment of sustainable relationships between brands and Generation Z consumers. Greenwashing indirectly diminished purchase intention by damaging brand image and triggering a cascade of negative cognitive and emotional responses, including skepticism, pessimism, and brand aversion.In the Iranian automotive industry, which contended with inherent environmental challenges, these negative outcomes might pose long-term threats to brand credibility and organizational performance. Consequently, automotive companies must transcend tokenistic environmental claims and embrace genuine, transparent, and verifiable sustainability practices. Investments in green innovation, implementation of green information systems, and integration of environmental responsibility throughout the supply chain can help rebuild consumer trust (Mahmoudzadeh & Mahmoudzadeh, 2022). By offering an integrated framework that elucidates the psychological and social mechanisms, by which greenwashing affects consumer behavior, this study enhances the literature on green marketing and consumer behavior, providing valuable insights for managers and future research across various industries and cultural contexts. https://nmrj.ui.ac.ir/article_30276.html The widespread adoption of the Internet in the 21st century coupled with the increasing use of computers and mobile technologies has significantly heightened consumers' inclination and intention to make online purchases. This study aimed to identify, rank, and develop a conceptual model of the factors influencing customers' online purchase intentions. From a research perspective, the study adopted an applied approach and employed a mixed-methods design (qualitative and quantitative) with its primary innovation being the integration of these methodologies. In the qualitative phase, a meta-synthesis method was utilized. English and Persian articles related to online purchase intentions published from 2010 to May 2025 (Gregorian calendar) and 1390 to Ordibehesht 1404 (Iranian calendar) were systematically reviewed. After multiple screening stages—considering relevance based on article titles, abstracts, and content, publication language (English or Persian), study type, publication period, accessibility, and methodological quality assessed using the CASP checklist—55 articles were selected from an initial pool of 932 studies. In the quantitative phase, the Shannon entropy technique was employed to prioritize the identified factors. The analysis resulted in the extraction of 90 unique codes, 22 concepts, and 8 overarching categories, which were ranked based on their significance. The main categories identified included individual factors, technical and security factors, motivational factors, marketing-related factors, product-related factors, supportive and communicative factors, social factors, and AI-based factors. Notably, the Shannon entropy analysis revealed that "customer trust", "perceived risk", and "perceived ease of use" ranked as the top three factors, indicating their substantial influence on customers' online purchase intentions. Ultimately, a comprehensive model of the factors affecting online purchase intention was developed. The findings of this study offer valuable insights for scholars and practitioners in the field of electronic commerce. IntroductionRapid advancements in information technology coupled with the widespread adoption of the Internet and digital tools have fundamentally transformed consumer purchasing behavior. Online shopping has emerged as a prominent manifestation of this transformation, becoming an integral part of daily life and a primary channel for fulfilling consumer needs. This shift has not only altered traditional purchasing patterns, but has also introduced new forms of consumer behavior in digital environments. As a result, electronic commerce represents a tangible expression of the information and communication technology revolution within the economic sphere, reshaping both the structure and substance of commercial processes.In recent years, e-commerce firms have experienced remarkable growth, alongside a significant increase in the number of online consumers. While online shopping offers numerous advantages, consumers' purchase intentions in digital contexts are continually influenced by a diverse range of technological, informational, psychological, and contextual factors. Understanding these factors is crucial for managers and marketers as insights into online purchase intentions can inform strategic marketing decisions, demand forecasting, customer segmentation, user experience enhancement, and customer loyalty development. Conversely, a lack of knowledge about these determinants can lead to ineffective marketing strategies, lost competitive opportunities, and the failure of online services.Although a growing body of research has examined the factors influencing online purchase intentions, existing studies remain fragmented and, in some cases, yield inconsistent findings. Previous research has often concentrated on isolated dimensions, such as user-generated content, artificial intelligence technologies, or digital literacy, without providing a comprehensive and integrated analytical framework. Consequently, the literature lacks a systematic, multidimensional, and unified model capable of coherently explaining online purchase intentions. This fragmentation highlights a significant theoretical gap between the current state of scattered and unsystematic knowledge and the desired development of an integrated, evidence-based framework.Addressing this gap was the central focus of the present study. The primary objective was to systematically identify and prioritize the factors influencing consumers' online purchase intentions through a mixed-methods approach. Specifically, this study employed a meta-synthesis method to integrate and reinterpret findings from previous research, thereby extracting a comprehensive set of key determinants. Following this, the Shannon entropy technique was applied to quantitatively evaluate and rank the relative importance of the identified factors.The novelty of this research lay in the combination of meta-synthesis with Shannon entropy, leading to the development of a robust and evidence-based framework for understanding online purchase intentions. While the study was limited by its reliance on previously published research, this methodological integration facilitated a deeper and more systematic understanding of the phenomenon. Accordingly, this study aimed to address the following research questions: What factors influence consumers’ online purchase intentions? How can these factors be prioritized based on their relative significance? And can a comprehensive, systematic model of online purchase intention be developed to support strategic decision-making in e-commerce contexts? Materials & MethodsThe present study aimed to systematically identify and prioritize the factors influencing consumers' online purchase intentions through an evidence-based synthesis of prior research. This research was applied in nature and utilized a mixed-methods design concerning data and analytical logic. Specifically, a qualitative meta-synthesis approach was employed to integrate and reinterpret findings from existing studies followed by the application of the Shannon entropy method as a quantitative technique for determining the relative importance of the identified factors.Research Design and Data SourcesMeta-synthesis is an advanced qualitative research method that seeks to conceptually integrate findings from multiple studies addressing a common phenomenon. Unlike traditional systematic reviews, which primarily summarize results, meta-synthesis focuses on uncovering latent concepts, reinterpreting empirical evidence, and generating a comprehensive and coherent theoretical framework. This approach is particularly well-suited for research domains, such as e-commerce and consumer behavior, where existing studies are numerous, fragmented, and occasionally contradictory.The population of this study consisted of published scientific articles related to online purchase intention. To ensure methodological rigor and credibility of the included studies, the Critical Appraisal Skills Programme (CASP) checklist was utilized as a quality assessment tool. The meta-synthesis process adhered to the 7-step framework proposed by Sandelowski and Barroso (2006), which provided a structured and transparent procedure for qualitative synthesis.Step 1: Formulating the Research QuestionsThe 1st step involved defining clear and focused research questions to guide the entire synthesis process. This phase specified the research phenomenon, target population, temporal scope, and methodological approach. Accordingly, the central research question was formulated as follows: What factors influence consumers' online purchase intentions? This question was operationalized based on 4 parameters: the research focus (identifying and modeling influencing factors), the study population (published scholarly research), the time frame (from 2010 to May 2025), and the data collection method (documentary analysis of scientific literature).Step 2: Systematic Literature SearchIn the 2nd step, a comprehensive and systematic search of relevant literature was conducted. International databases, such as ScienceDirect, Wiley Online Library, Taylor & Francis, Sage Journals, Emerald, ProQuest, IEEE Xplore, PubMed, and ERIC were searched, alongside Iranian databases, including Magiran, NoorMags, SID, the Comprehensive Humanities Portal, Ganj, and Elmnet. A range of Persian and English keywords related to online purchase intention was employed. This initial search resulted in the identification of 932 potentially relevant articles.Step 3: Screening and Selecting StudiesThe 3rd step focused on screening and selecting eligible studies based on predefined inclusion and exclusion criteria. Articles were assessed in sequence based on title, abstract, full text, and methodological quality, utilizing the CASP checklist. Inclusion criteria comprised relevance to online purchase intention, publication within the specified time frame, availability of full text, publication in either Persian or English, and classification as peer-reviewed research articles. Studies that did not align with the research objectives or failed to meet quality standards were excluded. Ultimately, 55 articles were retained for final analysis.Step 4: Data ExtractionIn this 4th step, relevant information was systematically extracted from the selected articles. The extracted data included the authors' names, publication years, and all reported factors related to online purchase intentions. These data formed the foundation for subsequent coding and categorization. A comprehensive database of extracted concepts was developed to ensure transparency and traceability of findings.Step 5: Data Analysis and SynthesisThe 5th step involved qualitative content analysis and synthesis of the extracted data. Initially, open coding was used to identify unique factors across studies, resulting in 90 non-redundant codes. These codes were then grouped into 22 concepts based on semantic similarity, which were further integrated into 8 overarching categories: motivational factors, technical and security factors, social factors, marketing factors, supportive and relational factors, product-related factors, individual factors, and artificial intelligence–based factors. This stage highlighted that prior research primarily addressed isolated dimensions of online purchase intention, revealing the lack of a comprehensive and systematic framework in the literature.Step 6: Quality Control and Reliability AssessmentTo ensure the reliability of the coding and categorization process, inter-coder agreement was assessed by using Cohen’s Kappa coefficient. A subset of extracted codes was independently classified by an expert reviewer, who was unaware of the researcher’s categorizations. The resulting Kappa value of 0.89 calculated by using SPSS at a significance level of 0.001 indicated a high level of agreement and confirmed the robustness of the qualitative synthesis.Step 7: Presentation of Results and Quantitative PrioritizationIn the final step, the synthesized findings were quantitatively analyzed by using the Shannon entropy method to determine the relative importance of the identified factors. First, a decision matrix was constructed based on the frequency of each code across the selected studies. The matrix was then normalized and entropy values were calculated to measure the degree of uncertainty associated with each factor. Subsequently, entropy weights were computed with higher weights indicating greater importance. This procedure enabled the objective and data-driven prioritization of factors influencing online purchase intentions.By integrating qualitative meta-synthesis with Shannon entropy, this mixed-methods approach provided a comprehensive, reliable, and evidence-based framework for understanding and prioritizing the determinants of online purchase intention. The resulting model offers both theoretical advancements and practical guidance for researchers and practitioners in the field of electronic commerce. Research FindingsResults of the Meta-Synthesis ProcessStudy Selection: A total of 55 high-quality articles were analyzed to derive evidence related to consumers’ online purchase intention.Identification of Codes: Through content analysis, 90 non-redundant codes were identified, each representing distinct factors influencing online purchase intention.Categorization: Codes were clustered into broader concepts and integrated into overarching categories, resulting in a multi-level framework:Categories: Technological, psychological, social, marketing-related, and individual factors.Framework: Presented in Table 1, illustrating the comprehensive representation of influencing factors.Results of the Shannon Entropy AnalysisMethodology: The Shannon entropy method was applied to determine the relative importance of the identified factors based on their frequency and distribution.Findings: Customer Trust: Ranked highest indicating it significantly influenced online purchase intention. Perceived Risk: Second most influential reflecting concerns about uncertainty and security in online transactions. Perceived Ease of Use: Ranked third emphasizing the need for user-friendly interfaces. Product Price & Perceived Usefulness: Tied for fourth place highlighting the role of economic considerations and perceived functional benefits. User Privacy Protection, Perceived Enjoyment, & Perceived Value: Found equal importance suggesting experiential and value-based aspects influenced purchase intentions. Discussion of Results & ConclusionHierarchical Influence: The results indicated that customer trust was paramount in shaping online purchasing behavior.Risk and Usability Factors: Perceived risk and ease of use also played critical roles with implications for e-commerce strategies.Experiential Aspects: The inclusion of experiential factors pointed to a shift in understanding consumer behavior in online environments.Summary of Findings: The study highlighted the complexity of factors influencing online purchase intentions, establishing a clear hierarchy.Implications for Practice: Understanding these factors can help online retailers enhance their strategies to build consumer trust and address perceived risks.Future Research Directions: Further studies could explore the evolving factors influencing online purchasing as technology and consumer behaviors change over time. https://nmrj.ui.ac.ir/article_30245.html In today's market, luxury brands are adopting innovative strategies that blend high perceived prestige with more accessible pricing to attract middle-class consumers. This approach stands in clear contrast to the traditional methods employed by luxury brand owners and has given rise to an emerging field of research known as "masstige branding" and "masstige marketing", which is increasingly recognized as a distinct branch of luxury marketing. This study aimed to explore the determinants and outcomes of masstige branding. It was applied in nature, utilized a quantitative approach, and followed a descriptive-survey methodology. The research was classified as a cross-sectional study, focusing on the statistical population of Samsung mobile phone users. Data were collected through a field questionnaire administered to 308 users of this brand. To assess the questionnaire's validity, content validity, convergent validity, and discriminant validity were employed, while Composite Reliability (CR) and Cronbach’s alpha coefficient were used to evaluate reliability. Data analysis was performed using the Partial Least Squares (PLS) method through Smart PLS software. The findings indicated that determinants—such as brand love, value creation, and perceived uniqueness—had a positive and significant impact on masstige brand equity. Additionally, masstige brand equity was found to significantly influence brand happiness, overall brand equity, word-of-mouth communication, brand loyalty, and purchase intention. IntroductionIn recent decades, the notion of luxury has transformed from an exclusive symbol into a more democratized concept known as “masstige” or “mass luxury”. This shift arises from the increasing desire of the middle class to achieve a premium lifestyle while retaining price accessibility. Masstige brands strategically combine luxury prestige with affordable pricing, appealing not only to consumers' financial sensibilities, but also to their emotional connections. This approach has disrupted traditional luxury consumption patterns and introduced new consumer behaviors. Today's consumers opt for masstige products not solely to convey social status, but to attain “brand happiness”—a blend of pleasure, satisfaction, and personal distinction. This emotional experience creates a unique brand equity that surpasses functional product benefits, transforming consumers into loyal brand advocates. Furthermore, intrinsic motivations—such as the desire for uniqueness, brand love, and value co-creation—play a crucial role in driving masstige consumption. Despite the rapid growth of these brands, especially in emerging markets, our understanding of the mechanisms that shape masstige brand value remains limited. To address this gap, the present study proposed an integrated model that explored the interactive effects of consumer–brand relationships, key antecedents, and their consequences on masstige brand value. In doing so, we aimed to fill the existing research voids and provide a more nuanced understanding of this modern luxury phenomenon. Materials & MethodsThis study was applied in purpose and descriptive-analytical in nature, utilizing a quantitative survey design. The statistical population consisted of Samsung smartphone users chosen for the brand's prestige, diverse price offerings, and strong market presence. Given the uncertain population size, an initial sample of 384 was determined by using Cochran’s formula; however, through convenience sampling at mobile retail centers in Urmia, a total of 308 valid questionnaires were ultimately collected and analyzed. Data were gathered through a structured questionnaire containing 44 items on a 5-point Likert scale, assessing constructs, such as brand love, value co-creation, need for uniqueness, prestige brand value, brand satisfaction, brand loyalty, word-of-mouth, purchase intention, and brand equity. The validity of the questionnaire was established through content validity (expert review), convergent validity (using Average Variance Extracted—AVE), and discriminant validity (according to the Fornell–Larcker criterion). Reliability was evaluated by using Cronbach’s alpha and Composite Reliability (CR) with CR deemed superior as it accounted for actual factor loadings rather than assuming equal indicator weights. In data analysis, alongside these psychometric assessments, the study employed key Partial Least Squares Structural Equation Modeling (PLS-SEM) fit indices: R2R^2R2 to evaluate explanatory power, Q2Q^2Q2 to assess out-of-sample predictive relevance, and Goodness-of-Fit (GoF) to gauge overall model fit. These metrics collectively ensured a robust and comprehensive assessment of the structural model’s performance within the PLS framework, thereby enhancing the statistical validity and theoretical contributions of the research findings. Research FindingsThe analysis of the study revealed several critical results regarding the determinants and outcomes of masstige brand equity among Samsung smartphone users:Determinants of Masstige Brand Equity: Brand Love: Strong emotional connections with the brand significantly enhanced masstige brand equity. Value Co-Creation: Active participation in the brand's value creation process led to higher perceived brand value. Need for Uniqueness: Consumers seeking to express their unique identities through brand choice positively affected brand equity.Impact on Key Constructs: Masstige Brand Equity: This construct was positively influenced by the aforementioned determinants and had significant implications for several behavioral outcomes. Brand Happiness: Higher brand equity correlated with increased brand satisfaction and happiness. Brand Loyalty: Consumers exhibited stronger loyalty towards brands with high masstige value. Word-of-Mouth Communication: Enhanced brand equity led to more positive word-of-mouth behavior among users. Purchase Intention: The intention to repurchase was found to be notably influenced by masstige brand equity. Statistical Validation: The study's hypotheses were statistically supported as path coefficients aligned with expected directions and t-statistics the critical value of 1.96 at the 5% significance level. Reliability and validity checks, including Cronbach’s alpha and Average Variance Extracted (AVE), confirmed the robustness of the measurement instruments. Model Fit and Predictive Power: The model demonstrated strong explanatory power (R² values) for masstige brand value, brand happiness, brand loyalty, and brand equity, while indicating moderate predictive power for purchase intention and weak power for word-of-mouth. The overall model's goodness-of-fit (GoF) index of 0.429 indicated a strong fit. Contributions to Luxury Marketing: The findings emphasized that modern consumers were motivated by both functional benefits and emotional connections, requiring brands to enhance their identity and experiential elements to foster loyalty and advocacy.This comprehensive evaluation signified that masstige brands effectively blended luxury and accessibility, deeply integrating into consumers' lifestyles and fostering emotional and social ties. Discussion of Results & ConclusionThe factor analysis results indicated that all item loadings exceeded 0.4 with corresponding t-statistic value of greater than 1.96, thereby confirming the acceptability of the measurement indicators. Reliability coefficients, including Cronbach’s alpha and Composite Reliability (CR), for all constructs surpassed 0.7, demonstrating satisfactory internal consistency. Convergent validity was affirmed as the Average Variance Extracted (AVE) values were above 0.5. Additionally, discriminant validity was established by using the Fornell–Larcker criterion as the square root of each construct’s AVE was greater than its correlations with other constructs. The coefficient of determination (R2R^2R2) revealed strong explanatory power for key endogenous constructs—namely, masstige brand value, brand happiness, brand loyalty, and brand equity—while purchase intention exhibited moderate explanatory power and word-of-mouth communication showed weak power. The predictive relevance of the model was assessed by using the Q2Q^2Q2 statistic, which indicated strong predictive power for most endogenous constructs, moderate predictive power for purchase intention and brand equity, and weak power for word-of-mouth communication. Moreover, the overall model fit was evaluated by using the Goodness-of-Fit (GoF) index, resulting in a value of 0.429, which exceeded the threshold of 0.36 for a strong fit. The f2f^2f2 effect size was examined to evaluate the substantive impact of exogenous constructs on endogenous constructs with effects interpreted by using Cohen’s benchmarks (0.02=small, 0.15=medium, 0.25=large). Ultimately, all hypotheses were statistically supported as path coefficients were positive (aligning with the hypothesized directions) and their t-statistics exceeded the critical value of 1.96 at the 5% significance level.This study aimed to develop a comprehensive causal model that explored the antecedents and consequences of masstige brand value among Samsung smartphone users. The findings revealed that "brand love", "value co-creation", and "need for uniqueness" significantly enhanced masstige brand value. Specifically, when consumers established strong emotional connections with a brand, actively co-created value, or used the brand to express their unique identity, their perceived value of the brand increased substantially. Furthermore, masstige brand value led to a range of positive behavioral outcomes, including heightened brand satisfaction and "brand happiness", which in turn fostered brand loyalty, encouraged positive word-of-mouth, and elevated brand equity. Additionally, masstige brand value directly bolstered repurchase intention as consumers were drawn to such brands not only for their functional benefits, but also for their ability to provide social distinction and personal differentiation. Overall, masstige brands occupy a unique position in consumers’ minds by seamlessly blending luxury prestige with price accessibility, thereby becoming an integral part of their lifestyles. This emotional and social connection transforms the brand from a mere product into a symbolic extension of the self. Consequently, brands like Samsung can strengthen their competitive position by reinforcing emotional and identity-based elements, offering distinctive product designs and prioritizing customer experience. The results emphasized that modern masstige consumption is driven by both symbolic and experiential motives, necessitating that brands move beyond mere functionality to cultivate meaningful relationships that enrich consumers' identities. This integrated approach not only enhances perceived value, but also fosters long-term loyalty and advocacy in an increasingly competitive market. https://nmrj.ui.ac.ir/article_30203.html AI washing—defined as the misleading application of artificial intelligence terminology in marketing—has emerged as a significant challenge to consumer trust and market integrity. This study aimed to identify the conceptual dimensions, antecedents, consequences, and strategies for addressing AI washing within Iran’s competitive marketing landscape. Adopting an exploratory qualitative methodology, the research employed a thematic analysis approach. Data were gathered through semi-structured interviews with 18 marketing and management academics and experts from universities in Tehran, Mazandaran, Semnan, Qom, and Ilam. Snowball sampling was utilized until theoretical saturation was reached and the data were transcribed and analyzed according to ethical research principles. The findings yielded 144 basic codes, 24 organizing themes, and 6 global themes for antecedents—including lack of awareness and cognitive limitations, competitive market dynamics, legal and regulatory weaknesses, deceptive marketing strategies, psychological manipulation, and violation of ethical principles. Additionally, there were 86 basic codes, 30 organizing themes, and 6 global themes for consequences, which encompassed negative effects on consumer behavior, market dynamics, regulatory policymaking, cognitive and psychological impacts, economic and investment effects, and brand credibility and reputation. The strategies identified included 75 basic codes, 20 organizing themes, and 5 global themes: regulation and supervision, consumer education, ethics in marketing, interdisciplinary approaches, and collaboration and partnerships. The novelty of this study lay in the presentation of an integrated framework for analyzing the conceptual dimensions of AI washing, along with practical solutions anchored in ethical and interdisciplinary principles that had received limited attention in previous research. The results demonstrated that AI washing eroded consumer trust and fair competition, ultimately marginalizing genuine innovation. The proposed strategies—strengthening legal oversight, enhancing technological literacy, and adhering to ethical principles—can help foster a more transparent and ethically focused marketing environment.IntroductionThe increasing adoption of artificial intelligence in marketing has fundamentally transformed how firms communicate value, personalize offerings, and engage with consumers. Alongside these advancements, a concerning phenomenon known as AI-washing has emerged. This term refers to the exaggerated or misleading claims related to artificial intelligence that aim to enhance product appeal without accurately reflecting actual technological capabilities (Ozturkcan & Bozdağ, 2025; Nyilasy & Gangadharbatla, 2025). Such practices raise significant concerns regarding consumer trust, ethical marketing conduct, and integrity of competitive markets.AI-washing is exacerbated by a considerable knowledge gap between firms and consumers, many of whom lack a sufficient understanding of how artificial intelligence systems operate and what their realistic limitations entail (Tello & Espinoza, 2025). Under intense competitive pressure, firms may exploit this asymmetry by using technical jargon, symbolic imagery, and forward-looking narratives to create inflated perceptions of innovation (Hermann, 2023). This issue is compounded by weak regulatory frameworks and limited oversight of technology-related advertising, which enables misleading claims to proliferate without substantial consequences (Baqi et al., 2022).The ramifications of AI-washing extend beyond mere short-term consumer deception. Continuous exposure to misleading AI claims can erode consumer trust, cultivate skepticism towards genuine technological innovation, and distort competitive dynamics by granting unfair advantages to firms that engage in deceptive communication (Ottenheimer, 2024). In the Iranian context, where the actual adoption of advanced AI technologies remains relatively limited, the disparity between marketing claims and technological reality heightens the risk of AI-washing (Jami Pour et al., 2024; Marzdar, 2025).Despite increasing scholarly attention, existing research is fragmented and lacks an integrated framework for understanding AI-washing as a multidimensional phenomenon encompassing deception, emotional manipulation, and misrepresentation. Accordingly, this study aimed to address the following research question: What are the conceptual dimensions, antecedents, and consequences of AI-washing in competitive marketing claims and how can effective strategies be developed to mitigate misleading practices? Materials & MethodsThis study employed an exploratory qualitative research design rooted in an interpretive philosophical framework and an inductive methodological approach. The research strategy was guided by the research onion framework of Saunders et al., emphasizing a qualitative mono-method design and a cross-sectional time horizon. Data were gathered through semi-structured interviews with 18 academic experts in marketing and management from universities in Tehran, Mazandaran, Semnan, Qom, and Ilam. Participants were selected by using snowball sampling based on their academic expertise, research background, and professional experience related to marketing, artificial intelligence, or digital technologies.The interviews, which lasted between 45 and 60 minutes, were conducted either face-to-face or online and were audio-recorded with the participants' informed consent. The interview protocol consisted of open-ended questions addressing perceptions of AI-washing, its antecedents, consequences, and potential regulatory and ethical responses. All interviews were transcribed verbatim.Data analysis followed the 6-phase thematic analysis process outlined by Braun and Clarke (2006): familiarization with the data, generation of initial codes, searching for themes, reviewing themes, defining and naming themes, and producing the final report. To enhance credibility and reliability, several validation techniques were employed, including data triangulation, member checking, independent coding by multiple researchers, and systematic documentation of analytical procedures. Ethical considerations, such as confidentiality, voluntary participation, and the right to withdraw, were rigorously upheld throughout the research process.Research FindingsAnalysis of the interview data led to the identification of 144 initial codes related to the antecedents of AI-washing, which were organized into 24 themes and 6 overarching categories.Antecedents of AI-Washing Consumer Cognitive Limitations: Limited AI literacy, technical complexity, and inadequate access to transparent information rendered consumers vulnerable to misleading claims. Competitive Market Dynamics: Intense competition and pressure to appear technologically advanced encouraged firms to overstate their AI capabilities. Regulatory and Supervisory Weaknesses: The absence of clear legal frameworks and enforcement mechanisms facilitated deceptive marketing practices related to AI. Deceptive Marketing Strategies: The use of ambiguous terminology, exaggerated performance claims, and symbolic representations misled consumer perceptions. Psychological Manipulation: Emotional appeals, future-oriented imagery, and narratives of technological superiority affected consumer judgment. Ethical Violations: A short-term profit orientation and a lack of professional responsibility contributed to intentional misrepresentation.Consequences of AI-WashingThe consequences derived from 86 initial codes were categorized into 6 major themes:Erosion of consumer trust and increased skepticismDisruption of fair competition and marginalization of ethical firmsSuppression of genuine innovationNegative cognitive and psychological effects on consumersEconomic and investment distortionsDamage to brand credibility and long-term reputationStrategies to Mitigate AI-Washing5 overarching strategies emerged from the analysis: regulatory reinforcement, consumer education, commitment to ethical marketing, interdisciplinary collaboration, and institutional cooperation. Discussion of Results & ConclusionThe findings highlighted AI-washing as a complex, multidimensional phenomenon rooted in knowledge asymmetry, competitive pressure, and institutional gaps. While AI-related marketing claims might provide short-term visibility, they ultimately eroded consumer trust, distort market competition, and impede authentic technological advancement. Consistent with prior research, the results underscored the necessity of transparency, ethical accountability, and regulatory oversight in mitigating misleading AI claims (Nyilasy & Gangadharbatla, 2025; Ozturkcan & Bozdağ, 2025). Addressing AI-washing requires a comprehensive approach that integrates policy intervention, consumer education, and robust ethical marketing standards.Practical RecommendationsEstablishing clear regulatory standards for AI-related marketing claimsPromoting initiatives aimed at enhancing AI literacy and consumer educationEncouraging firms to adopt transparent and ethical marketing practicesFostering interdisciplinary collaboration among regulators, academics, and industry stakeholders.LimitationsThis study was subject to limitations inherent in qualitative research, including potential interpretive bias and reliance on expert perspectives. The cross-sectional design might not fully capture the evolving nature of AI-washing practices. Future research could employ quantitative or longitudinal approaches to expand upon these findings. https://nmrj.ui.ac.ir/article_30265.html By expanding and developing new business models, B2B startups provide new processes and ideal job opportunities, increase demand for goods and services, and improve investment in cross-business sectors. Given the importance of new business model development in B2B startups and their potential in using social media (SM) to achieve strategic goals, the purpose of this study is to investigate the strategic use of social media in new business model development in Iraqi B2B startups with the mediating role of absorptive capacity. This research is of an applied type in terms of purpose and of a descriptive-survey type in terms of nature and method. The statistical population of this study includes managers and employees of startup companies in Iraq and the statistical sample of the study is 384 people with the Cochran formula estimate. The sampling method is non-probability and available. The research data collection tool is a questionnaire. Data analysis was performed using structural equation modeling using SPSS and LISREL software. The findings of this study showed that the strategic use of social media in developing new business models in Iraqi B2B startups has a significant effect with the mediating role of absorptive capacity. The results of this study showed that the strategic use of social media and improving absorptive capacity in developing new business models in Iraqi B2B startups not only helps to strengthen the competitiveness of these startups, but also leads to the creation of an innovative and sustainable ecosystem. https://nmrj.ui.ac.ir/article_30274.html Purpose: The development of fourth-generation technologies has significantly transformed the tourism industry. Consequently, equipping marketing managers with the competencies required for this new generation of marketing has become essential. Accordingly, the present study aims to design a competency framework for fourth-generation marketing managers in the tourism sector. Methodology: This research is applied in nature and exploratory in terms of data collection, conducted through a qualitative approach. The participants included 15 experts in digital marketing within the tourism industry, selected using the snowball sampling method. Data were collected via semi-structured interviews, whose validity and reliability were confirmed. Grounded theory was employed for data analysis, using open, axial, and selective coding with the help of Maxqda software. Findings: Based on the findings, 154 open codes, 34 subcategories, and 14 main categories were extracted from the interviews. These were organized into six dimensions of the paradigm model as follows: Causal Conditions (Technological and Organizational Factors) Contextual Conditions (Infrastructure and Market Environment) Core Category (Ethical Competence, Tourism Marketing, Leadership, and Digital Skills) Intervening Conditions (Macro-Institutional and Macro-Environmental Factors) Strategies (Intra-Organizational and Networking Approaches) Consequences (Market and Performance Outcomes) Conclusion: The findings of this study offer strategic insights for managers and researchers into the development of marketing competencies in the tourism industry amid the emergence of fourth-generation marketing. https://nmrj.ui.ac.ir/article_30306.html approach have received much attention and study by researchers. effectuation approach is an approach based on tools and control, and entrepreneurs with this approach do not try to predict the future and seek to exercise control over the results. In contrast, the causation approach is based on goals and effects and focuses on specific programs to predict the future in a specific environment. Undoubtedly, the entrepreneurial behavioral approach in marketing affects its final performance. Therefore, the purpose of this research is to investigate the effect of causation on marketing performance by moderating dynamic marketing capabilities. Due to the growth of the mobile application industry, businesses based on this industry were selected as the research area. The current research is applied in terms of purpose and in terms of descriptive method and questionnaire data collection tool. The collected data were analyzed in the descriptive statistics section with SPSS software and in the inferential statistics section using the structural equation modeling technique and SMART PLS software. In this research, 102 questionnaires were collected from companies based on mobile applications. The results of the research showed that causal and effectuation behavioral approaches have a significant impact on marketing performance. Also, dynamic marketing capabilities moderate the behavioral approach of causation, but do not affect the behavioral approach of effectuation. In the following, research hypotheses are compared with previous studies, and at the end, suggestions for future studies are presented. https://nmrj.ui.ac.ir/article_30367.html The present study was conducted with the aim of identifying the opportunities, challenges, and requirements of marketing in the metaverse world, which is classified as a descriptive survey research in terms of its applied purpose and data collection. This study is considered a mixed research in terms of the type of data and the style of analysis. The qualitative data were collected using library studies and a review of the research background and analyzed based on the meta-synthesis method, as a result of which 86 open codes, 16 subcategories, and 3 main categories were extracted. In the quantitative part, in order to screen and confirm the indicators and categories extracted from the qualitative phase, the fuzzy Delphi method was used. Experts and specialists active in the field of digital marketing and metaverse formed the statistical population of the research in this stage, and 18 of them were selected using the purposeful non-probability sampling method based on the criteria of expertise in digital marketing, experience in the field of metaverse, and relevant work experience. Validity and reliability were examined and confirmed in this stage through content validity and test-retest, respectively. As a result of this research, immersion and providing an all-encompassing experience, customization, community building through value creation, extensive interaction, and keeping pace with the market, including opportunities and risks of product and service reputation, regulatory laws and complexities, intellectual property, and data security, were identified as marketing challenges in the metaverse world https://nmrj.ui.ac.ir/article_30379.html In recent years, halal products have emerged as a growing segment in the global market, drawing increasing attention in non-Muslim countries. Canada, with its cultural diversity and a growing Muslim population, is recognized as a potential market for these products. However, effective marketing of halal products to non-Muslim consumers remains theoretically and practically challenging. The aim of this study was to develop a comprehensive model for marketing halal food products in Canada, with a specific focus on non-Muslim consumers. The research employs a qualitative methodology based on grounded theory (Strauss & Corbin, 1998). Data were collected through semi-structured interviews with 11 managers of major retail chains in Canada. Participants were selected using purposive sampling and interviews continued until theoretical saturation was reached. In the process of data analysis, 113 open codes were extracted and, during the axial coding stage, were consolidated into 20 axial categories. Findings are presented in the form of a paradigm model encompassing causal conditions, contextual conditions, intervening conditions, central phenomenon, strategies, and consequences. The results indicated that factors such as brand trust, product quality and taste, consumer awareness, the role of halal certifications, and accessibility in mainstream stores are key elements influencing non-Muslim purchase intentions. The proposed model provides both a theoretical and practical framework to guide companies operating in the halal food industry. By employing effective marketing strategies, these businesses can increase their market share and enhance the trust and satisfaction of non-Muslim consumers in Canada.