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An analysis of the factors influencing consumer viewpoints in online shopping

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12 July 2024

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17 July 2024

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Abstract
Most consumer purchases are influenced by their evaluation of a product's advantages, disadvantages, and emotional components. Research in psychology and marketing indicates that customer emotions play a role at different stages of the purchasing process. This study aims to identify the elements that may influence consumer feelings when purchasing high-end cosmetics. To explore the various aspects of customer emotions, a qualitative study was conducted using in-depth semi-structured interviews with 23 users of luxury cosmetics and health products in Telegram groups. This research uncovered multiple emotional dimensions and pinpointed factors that could elicit emotions in the target market. The next step, based on collective consensus, was to determine the variables impacting customer emotions. At this stage, the panel included 15 experts in marketing, psychology, luxury cosmetics import businesses active on digital platforms, and managers of luxury cosmetics and hygiene groups in online environments. Through a three-step consensus method, experts identified and assessed 36 factors affecting customer emotions based on their significance and perceived impact. These factors were then categorized into three groups: personal variables, group and product variables, and contextual variables.
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Subject: Business, Economics and Management  -   Marketing

1. Introduction

A worldwide trend, which is also growing swiftly in Iran, is the attraction to luxury items, including high-end cosmetics and personal care products. This trend is most prevalent among the younger demographic of society [1]. The promotion of international luxury brands in Iran, such as cosmetics from MAC, Clinique, Chanel, Kiehl’s, Lancôme, Dior, Morph, and Toofaced, exemplifies this phenomenon. Recently, with the rise in smartphone internet users and virtual networks like Telegram and Instagram, many manufacturers and sellers have turned to these platforms as distribution channels. The allure and elegance of the products can trigger internal motivation and the desire to purchase, with this passion being a spontaneous emotional response. Additionally, given that the youth comprises 45% of Iran’s population, according to the Iranian Statistics Center (35.7 million individuals aged 20 to 44 years) (Iran Statistics Center 2019), this trend becomes even more significant. Customer emotions play a critical role in the acquisition of luxury goods and significantly influence consumer experiences and reactions. Consumption emotions are the emotional responses experienced before and during the use of a product [2]. Modern consumers form an emotional bond with the product and brand, influencing their purchasing decisions [3,4,5]. Thus, understanding the impact of customer emotions is crucial for product marketing [6]. Furthermore, identifying all the factors that excite customers in a market, leading to the purchase process, is specific to that market. These factors may include product variety, prices, shopping environment, and other previously mentioned elements. Therefore, in each market, these and other yet-to-be-identified factors should be studied based on the environmental, cultural, technological, and other characteristics of that market. As noted in international studies, the factors affecting customer emotions, particularly in online shopping, are not fully measured, with most research conducted in physical stores, such as [7,8,9]. This study aims to explore the factors influencing emotions in an online setting from the perspectives of customers and experts using comprehensive views. Moreover, considering that previous international studies were conducted in a Western cultural context, their findings cannot be generalized to all markets, especially the cosmetics market in Iran. Thus, more generalizable results can be achieved by considering non-Western cultures. Conducting thorough research in the Iranian market, taking into account the different consumer values for choosing products, as well as the clear distinction between luxury cosmetic brands and those available in Iran, which have been examined in studies on creating excitement and the factors affecting it for customers, can fill existing gaps, and this study seeks to achieve such goals.

2. Background

2.1. The Theoretical Background of the Study

2.1.1. Customer Emotion

Emotion expression is another form of discourse that is universally recognized and understood. Emotions should be considered a unique element to enhance the product or service offered [10]. Emotions refer to the assessment of customer feelings about the experience of a company brand, product, or service [11]. Emotion is an attitude that can stimulate, organize, and guide people’s perceptions, thoughts, and behaviors. Emotions influence all aspects of consumption from pre-purchase decisions to post-consumption behaviors [10]. Researchers differentiate between general emotions and consumption-specific emotions. Unlike general emotions, consumption-specific emotions occur specifically during the use of a product or may be evoked as effective responses. Emotions are brief, intense feelings that occur without conscious effort and are usually accompanied by increased activation of the autonomic nervous system, and physiological changes in heart rate and breathing [12]. Many authors acknowledge that there are positive and negative effects in the experience of emotions, with everyone experiencing either positive or negative emotions. [13] suggested that people’s emotional indicators include 62 emotional states. [14] believes that a person can express emotions through facial expressions and may exhibit ten basic emotions including interest, pleasure, surprise, sadness, anger, disgust, contempt, fear, shame, and guilt. [13] identified eight primary emotions, including fear, anger, joy, sadness, acceptance, disgust, anticipation, and surprise. In his study, [15] considered negative emotions, which included fear, anger, shame, discomfort, and disappointment. [16] considered the dimensions of customer emotions including excitement, enthusiasm, fun, happiness, interest, excitement, and inspiration. [17] illustrated emotions with components such as anger, comfort, pleasure, fear, happiness, importance, confusion, pride, specialness, distinctiveness, sadness, shame, and complexity. [9] categorized emotions into two groups: positive and negative. In their view, positive emotions included pleasure, excitement, and relaxation, while negative emotions included anger, distress, hatred, and fear. [18] divided emotions into two categories: positive emotions (excitement and happiness) and negative emotions (anger, anxiety, and depression). In their study, [19] focused only on positive emotions, considering them to include comfort, happiness, satisfaction, and romanticism. [20] also divided customer emotions into two categories: positive (joy, pride, fun, entertainment, interest, and attachment) and negative (anger, hatred, humiliation, disgust, enmity, and fear). [21] in their model considered satisfaction, happiness, peace, optimism, pleasure, and excitement as dimensions of positive emotions, and anger, fear, discomfort, and embarrassment as dimensions of negative emotions. [22] took into account positive emotions such as excitement, surprise, peace, and pleasure, and negative emotions such as anger, disgust, hatred, shame, distress, and despair.

2.1.2. Influences on Customer Emotional Purchases

Numerous investigations have explored emotional buying, aiming to pinpoint factors that facilitate these purchases. The elements influencing emotional buying behavior can be categorized into four types: personal factors, product-related aspects, environmental and situational elements, and factors associated with the individual that influence the propensity for emotional purchases. The stronger a consumer’s inclination toward emotional buying, the higher the likelihood of such purchases [23]. Product-related aspects are pertinent to items purchased on an emotional basis. Emotional buying patterns differ according to the product and its category. Environmental elements include store layout, unique displays, shelf indicators, and attractive graphic advertisements or sales promotions. Additionally, media formats that deliver information in the online shopping environment can impact emotional shopping tendencies. Situational elements involve the financial resources and time available for purchasing and the accessibility of credit [24]. Various investigations have demonstrated the impact of diverse factors on the emotions involved in purchasing various products and services, aiming to offer a comprehensive overview of the influences on customer emotions and emotional buying behavior. These can be broadly categorized as outlined below.
  • Personal Factors
Demographic details (age, gender, income level, etc.) are used as independent variables. There are differing views on whether consumers’ income and age significantly impact online shopping positively [25]. Previous research generally shows that younger individuals are more inclined to make emotional purchases than older individuals [24]. The distinction between men and women also influences decision-making priorities. Some studies indicate that men engage in online shopping more than women [25]. Income is also strongly associated with emotional buying behavior. Individuals with lower household incomes often rely on shopping lists [24]. Personality traits encompass thoughts, attitudes, behaviors, perceptions, activities, and other various characteristics of an individual. Personality can be described as the features, appearance, and attributes of human beings. Emotional shopping is viewed as an emotional component of personality that allows a person to act swiftly without extensive deliberation or consideration of alternative costs. To comprehend the role of personality in motivating purchases, the five-factor personality model is utilized, which includes openness, extroversion, agreeableness, conscientiousness, and neuroticism, covering all characteristics of human personality [26].
Variety-seeking: Some scholars suggest that consumers seek variety and options, which may be a primary reason for brand switching and emotional purchases. Additionally, variety-seeking behaviors are linked to emotional buying [27].
Hedonism: The enjoyment of shopping refers to the pleasure derived from the buying process [28]. Individuals who take pleasure in shopping are termed recreational buyers, who spend more time shopping and shop more frequently [29].
  • Contextual variables
Available duration: Consumers with ample time for shopping often exceed their planned purchases. Therefore, a shopper who feels comfortable in a store may prolong their stay, thereby increasing the likelihood of unnecessary purchases [25]. Conversely, shopping habits and choices may alter when time is limited. However, shoppers with sufficient time experience less pressure in selecting items and consequently pay more visual attention to the store environment, fostering serene and positive emotions during shopping [29].
Available resources: This pertains to the monetary funds or additional finances individuals possess or spend daily. Furthermore, available resources significantly influence people’s purchasing decisions. It serves as a purchasing power. Greater financial resources enable customers to alter their planned purchasing patterns, thereby enhancing their purchasing power [25].
Financial well-being: This refers to an individual’s economic health, distinct from the "available resources" variable in their bank account. When assessing this variable, one considers a person’s overall financial situation from a long-term perspective. High scores on the financial well-being scale are thought to increase the likelihood of emotional purchases [25].
User familiarity: The experience of using websites or social media significantly impacts e-commerce. The online shopping experience, a common situational factor, relates to user-friendly interfaces and the enjoyment derived from online shopping [30].
  • Merchandise and ecological factors
Presence of companions and peers in the setting: Based on the premise that friends and relatives bolster a buyer’s decision-making, resulting in increased purchases, establishments catering to couples, friends, or groups generally perform better. Peer presence heightens purchasing desire, while family members’ presence diminishes it [25].
Store ambiance: This encompasses the arrangement of products, lighting, and color schemes. It significantly influences consumer emotions and buying behaviors, potentially fostering emotional and intensified shopping behaviors [25].
Exclusivity and modernity of products: Purchases of emotionally charged products result from engagement with the product and the buyer’s desire for emotional purchases. Emotional buying, driven by current fashion trends and new brand introductions, spurs consumers toward emotional purchases [29].
Promotional activities and marketing stimuli: Sales promotions aim to stimulate customer demand and encourage emotional purchases of specific brands. Well-planned advertisements can also induce consumer purchase intentions, particularly when products are discounted. Consumers are more inclined to make emotional purchases in such scenarios [25].
Supportive interactions with staff: A courteous salesperson’s presence in-store constitutes exceptional customer service. Positive interactions during shopping can heighten the likelihood of emotional purchases, while knowledgeable staff can mitigate buyer’s remorse by providing support throughout the purchasing process [25].
Product specifications: Certain products evoke more emotional responses than others based on category, price, and symbolic significance. Emotional purchases are more probable for products with lower prices or shorter production cycles [31].
Consumer interaction with the merchandiseCustomer interaction with the merchandise and brand is an incentive state of curiosity sparked by a specific stimulus or circumstance. In general, engagement is visualized as an exchange between an individual (consumer) and an entity (merchandise). Product interaction may vary between emotional purchasing and scheduled, customary purchasing [29]

2.2. Foundation of the Experiment

In this segment, various local and foreign investigations connected to exploration variables are surveyed. [32] executed an inquiry titled "Assessing the impact of online shop attributes on impulsive shopping caused by consumer emotions." The findings underscored that the environmental features of virtual stores (store content, design, and navigation) positively and significantly influence impulsive online shopping behavior. Moreover, the mediating role of consumer emotions in the relationship between virtual store environmental features and impulsive shopping behavior was validated. [33] performed a study titled "Exploring determinants influencing online purchasing intent in Iran: A study of the fashion and apparel markets." His results highlighted that innovation, perceived security, quality of information, and trust within the fashion industry positively and significantly affect online purchase intent. Additionally, cost-effectiveness and timeliness positively and significantly impact perceived value in online fashion shopping. Furthermore, perceived value positively influences online purchasing intent. [34] conducted another investigation titled "Identification of foundational components (value proposition to customers) and their influence on customer satisfaction utilizing sentiment analysis through text mining." The results indicated that analyzing customer sentiments and user-generated content to explore consumer attitudes toward products is a practical and effective method for businesses to present successful products endorsed by consumers. [35] carried out a study titled "Exploring the impact of emotion on customer purchase intent with the mediating role of customer involvement." The study aimed to explore how emotions affect customer purchase intent, with customer engagement and brand image serving as mediators. Data analysis confirmed that emotions influence customer engagement, emotions affect brand image, engagement impacts brand image, and brand image influences purchase intent. [36] conducted research titled "Investigating factors influencing online shopping and sales promotions on consumer emotional buying behavior." Data analysis revealed that online shopping and sales promotion tools influence consumer behavior, and gender exhibits a significant relationship with emotional shopping. [7] conducted research titled "Individual and in-store factors influencing emotional purchasing behavior among consumers in small towns." Findings indicated that personal factors, including available time and family influence, exert a positive and intriguing influence on emotional buying behavior. In-store factors similarly impact impulsive buying behavior. However, the influence of available funds on impulsive buying behavior remained inconclusive. [21] conducted a study titled "The effects of positive and negative emotions in online shopping on consumer satisfaction, repurchase intention, and recommendation intention." Results demonstrated that positive emotions have a more significant impact compared to negative emotions. [26] conducted research titled "Impact of personality on emotional shopping behavior in developed countries." Findings revealed that traits such as openness, extroversion, conscientiousness, and neuroticism have substantial effects, while agreeableness has a minimal impact on emotional purchasing behavior. [8] conducted research titled "Exploring factors influencing emotional buying behavior." Study results indicated that available funds directly influence emotional buying behavior, with this effect becoming significant indirectly through the mediating variable of purchase intent. [16] conducted research titled "The Moderating Role of Situational Factors (Available Money and Time) on Emotional Behavior." This study demonstrated the direct effects of environmental characteristics on customers’ positive emotional responses and the direct effects of customers’ positive emotional responses to retail environments on emotional purchasing behavior.

3. Research Approach

To fulfill the study’s objective of identifying the facets of customer emotions and examining, prioritizing, and categorizing the precursors influencing customer emotions during the purchase of luxury cosmetic items, a two-phase methodology (qualitative-quantitative) was employed, combining thematic analysis and the fuzzy Delphi technique. Thematic analysis aimed to pinpoint customer emotion facets through firsthand experiences of customers actively involved in purchasing numerous luxury cosmetics via online shopping groups. Conversely, the fuzzy Delphi technique, achieving consensus among experts, explored potential precursors influencing customer emotions. Identified precursors were subsequently prioritized and categorized based on their significance.

3.1. Thematic Examination

Initially, an extensive semi-structured interview approach was employed to gather essential primary qualitative data. To this end, a selection was made of active and seasoned customers who have participated extensively in online cosmetics sales Telegram groups (based on repeated IDs in group listings). Given the qualitative nature of the study, sampling was conducted through a purposive or judgmental method, with sample size determined based on theoretical saturation. Consequently, the initial sample comprised 23 participants, achieving saturation through these interviews. The interview protocols comprised two principal segments. The first segment elicited information on respondents’ demographic characteristics, their virtual network usage (in daily hours), and their time spent engaging in online cosmetics group purchases. The second segment aimed to capture respondents’ emotional dimensions and factors influencing these during their group engagement and purchasing process phases. Respondents were prompted to articulate emotions such as fury, apprehension, joy, and trepidation upon entering an online cosmetics sales Telegram group, viewing products, perusing comments, engaging in discussions, and comparing prices. Responses were meticulously recorded using audio recording equipment to ensure comprehensive capture of insights. Subsequently, data from interviews underwent data-driven inductive thematic analysis to identify, scrutinize, and delineate patterns or themes within qualitative data. This method facilitated exposition of explicit as well as implicit meanings, assumptions, and insights conveyed through words, phrases, and sentences [37]. Furthermore, interpretation of themes and data analysis outputs were grounded in established theoretical frameworks, supported by input from three academic experts in marketing. Reliability of interview data was evaluated using the ICR method and the "Holsti method". In this study, initial coding was performed by the researcher followed by validation by an expert, yielding a reliability coefficient of 87%, indicating robust research data.

3.2. Fuzzy Delphi Technique

Aligned with the study’s objective of identifying factors influencing customer emotions during purchasing, a collaborative decision-making approach [38,39,40,41,42,43,44,45] was adopted, aiming to achieve consensus through expert panel deliberations [46]. This method holds particular significance in qualitative inquiries [47,48,49,50,51,52,53,54]. Panelists for the Delphi method were selected based on predefined criteria, emphasizing expertise and practical experience [55]. For this study, a panel comprising 15 experts in psychological marketing from luxury cosmetics-importing firms active in virtual networks, along with managers of Telegram groups specializing in luxury cosmetic products, was assembled.

4. Findings

4.1. Content Analysis Outcomes

As delineated in Section 1,Section 2 and Section 33, initial interviews were conducted to capture authentic consumer perspectives. Insights garnered from these interviews yielded three primary categories of information: (1) Demographic details, daily virtual network usage hours, and time allocation to purchasing cosmetics and hygiene products in online groups; (2) Dimensions of consumer emotions; and (3) Potential precursors to consumer emotions. For content analysis, interview transcripts were meticulously reviewed and iteratively examined to identify overarching textual patterns. Initial codes were established to catalog content, resulting in 454 primary codes. Subsequently, these codes were categorized into 33 thematic groups, aligning coherent concepts and themes. Table 1 summarizes findings from this phase, focusing on concepts pertinent to the study’s objectives and their frequency in interview responses. Ultimately, this process yielded 11 secondary themes, underpinning two organizing themes: "positive emotions" and "negative emotions," within the overarching theme of consumer emotions.
In the subsequent phase, utilizing the findings from the prior stage, a conceptual map illustrating the dimensions of customer emotional states is constructed. This visual representation takes the form of a network diagram akin to a web structure, detailing various thematic levels and their interrelationships. Figure 1 depicts the conceptual map derived from this study.

4.2. Fuzzy Delphi Approach

Initial stage: As previously indicated, interviews with engaged consumers identified key factors influencing emotional responses during online shopping from the consumer perspective. These factors, combined with those identified in prior emotional studies, constituted the foundational framework for applying the Delphi approach. Table 2 presents the influential factors affecting consumer emotional states.
Second stage: Initially, a semi-structured interview, divided into three segments, was conducted: A. Questions pertaining to experts’ demographic characteristics to gain a comprehensive understanding of the panel; B. Thirty-six items assessing experts’ evaluations of each factor’s potential impact on the subject under study as per Table 2 (factors derived from literature reviews and qualitative interviews, rated on a five-point Likert scale ranging from "strongly influential" to "minimally influential"); C. Lastly, experts were posed a general question: "Besides the aforementioned factors, please identify any other factors you believe influence consumer emotions during the purchase of cosmetics and health products, and specify their effects." Subsequently, this semi-structured questionnaire was disseminated to the 15 selected panel members comprising psychological marketing specialists, active managers of luxury cosmetics Telegram groups, and executives from luxury cosmetics-importing firms in Bandar Abbas engaged in online sales, alongside managers of Telegram groups focusing on luxury cosmetic products via email or in face-to-face meetings.
Third stage: Data assessment a. The subsequent phase involved scrutinizing the responses from the panel members, utilizing the fuzzy Delphi technique to achieve consensus on the experts’ viewpoints. Consequently, to transform the qualitative analysis into fuzzy values, trapezoidal numbers were employed as a corresponding conversion standard.
Table 3. Trapezoidal fuzzy values corresponding to the qualitative assessments.
Table 3. Trapezoidal fuzzy values corresponding to the qualitative assessments.
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b. Post conversion of the qualitative assessments provided by the panel members into trapezoidal fuzzy values, the fuzzy geometric mean of each element was computed using Eqs. 1 and 2 [46].
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A j i ˆ represents the i t h expert’s opinion about the j t h factor.
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Where, A j ; a v e denotes the average expert assessment concerning the jth constituent.
c. Subsequently, the variance between expert opinions and component averages was determined using Equation (3) and conveyed to the committee via the ensuing survey. This method enabled integration [56,57,58,59,60,61,62] of feedback from all participants and discrepancies between each expert’s views and the collective opinions, prompting them to adjust and refine their perspectives to achieve group consensus.
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Following the questionnaire’s final segment requesting subjects to identify additional factors influencing customer emotions from their unique viewpoints, newly proposed elements were incorporated into existing factors (Table 4). These were returned to experts alongside the results of Equation (3).
d. As previously stated, a subsequent questionnaire was formulated based on initial findings, distributed to experts to potentially amend their views based on peer feedback. This survey also provided panel-raised factors for review and weighting by other members. Each factor’s weight was transformed using trapezoidal numbers per linguistic variables [63] according to Table 3.
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Where B j i represents the i t h expert’s perspective on the j t h component. The mean geometric values [64,65,66,67,68,69,70,71] and variances between each member’s assessment and the mean were calculated using Equations (2) and (3), mirroring initial steps. The third and fourth stages of the fuzzy Delphi method were iterated until consecutive mean values approached a logical consensus, signaling acceptance [46]. The critical threshold for consensus was set at 0.2 [72]. Additionally, the variance between mean opinions from the first and second rounds was computed using Equation 5 [72].
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Where A j a v e denotes the mean of first-round opinions, and B j a v e represents the mean of second-round opinions. The outcomes are detailed in Table 5. The table demonstrates that the geometric mean disparity between first and second rounds for 8 variables exceeds the acceptable threshold (0.2). Moreover, factors 37 to 48 introduced in the first round lacked evaluation, precluding calculation of their mean disparity. These factors necessitate a third round of assessment. d. To address this, a third round questionnaire was designed to reflect feedback from the previous round and implement expert adjustments toward consensus. Procedures mirrored those of the second round, and outcomes are presented in Table 5.
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Where C j i signifies the i t h expert’s perspective on the j t h component. Results from the third round, detailed in Table 5, show that variances between mean opinions of the second and third rounds fall within acceptable ranges across all criteria, indicating consensus on factors influencing customer emotions. e. Finally, the last step involved analyzing defuzzified mean values of each factor to identify influential factors. Criteria with 5 ≤ A j a v e were considered viable [73]. Defuzzified mean expert opinions for each factor were calculated using Equation 7 [46].
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According to Table 5, some defuzzified mean values for factors fall below the acceptable threshold (5) and should be excluded from the list of factors affecting customer emotions. These include internet usage, educational level, family influence, group size, cultural factors, religion, belief in the halo effect of luxury products, marital status, desire for attention, and visual appeal. Other variables were identified as influencing emotions in luxury cosmetic product purchases.
The Delphi method aims to pinpoint factors influencing customer emotions through collaborative consensus. Ultimately, 36 factors were identified as influential, prioritized based on their individual significance, and detailed in Table 6. Subsequently, these factors were categorized into personal, situational, product, and group variables, as outlined in Table 7.

5. Discussion

In previous research on customer emotions, this study extended the scope to Iranian consumers within the luxury cosmetics sector, considering Iran’s unique circumstances including sanctions. Moreover, the study aimed to advance understanding of factors influencing customer emotions, drawing on both theoretical foundations and empirical consumer behavior insights in marketing. To achieve this, a dual-phase research approach was employed to identify factors impacting emotions when purchasing luxury cosmetic products.
The initial phase involved qualitative research through customer interviews, which formed the basis for a thematic framework encompassing emotions, customer perspectives, dimensions, and influential factors. Insights from interviews with customers and actual buyers from Telegram groups, who experience a range of emotions during product engagement and purchase, coupled with existing literature, informed the development of semi-structured questionnaires. Thematic analysis was applied to interpret data, revealing various positive and negative emotions among Telegram group members, resonating with findings by [9,17,20,21], and [18]. Predominantly, interviewees expressed feelings of happiness and pleasure, followed by "enthusiasm and excitement", "positive surprise", "relaxation and confidence", and "love and emotional attachment", which collectively serve as stimuli for purchasing luxury cosmetics and health products.
Conversely, negative emotions, such as sadness, fear, regret, inferiority, anger, jealousy, and despair—particularly fear—play a role in consumer decision-making, driving efforts to minimize their impact [74,75,76,77,78,79,80,81,82,83]. These findings underscore the significant influence of emotional triggers in luxury cosmetic purchases.
In the second phase, a fuzzy Delphi method was employed to achieve consensus among experts, prioritizing factors influencing emotional responses during purchasing decisions. Following three rounds of evaluation and deliberation among panel members, 36 factors emerged as pivotal in shaping customer emotions and guiding product selection. These factors were categorized based on their perceived impact, revealing insights not previously discussed.
Among the key findings, the factor "economical pricing relative to physical and online stores" ranked highest, followed by "group credibility and quality" and "Iranian sanctions impacting luxury brand imports", novel aspects not extensively covered in prior literature. Additionally, advertising efforts, marketing initiatives, and income levels were identified as influential, aligning with [25] and Ciunova Shuleska [24]. This underscores the predominant influence of product group factors, followed by situational factors, on Iranian consumer emotions, with personal factors playing a secondary role. These insights shed light on the emerging market dynamics of luxury goods via online platforms like Telegram, offering valuable perspectives on Iranian consumer behavior.

6. Limitations of the Study

  • (1) This study focuses exclusively on customer emotions within the luxury cosmetics sector, limiting its generalizability to other industries and product categories. Future research should explore emotional dynamics across diverse contexts and products to enrich understanding in this domain.
  • (2) The study’s sample primarily comprises members of Telegram groups engaged in luxury cosmetics, predominantly female. Consequently, caution is advised when extrapolating findings to broader consumer demographics. Future studies should strive for more representative samples to enhance the applicability of findings across diverse consumer segments.

7. Future Studies

  • (1) Given the first limitation, researchers are encouraged to explore the broader dimensions of customer emotions in online shopping across various virtual platforms and product categories, contributing to enhanced consumer insights in Iran.
  • (2) Future studies could benefit from examining more diverse consumer demographics, including both male and female participants, or conducting nationwide studies to capture broader consumer sentiment.

Acknowledgments

Parts of this research were supported in part by the NSF grant CMMI-1953323.

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Figure 1. Conceptual map illustrating dimensions of customers’ emotional experiences during the purchase of luxury cosmetics and health products in Telegram groups
Figure 1. Conceptual map illustrating dimensions of customers’ emotional experiences during the purchase of luxury cosmetics and health products in Telegram groups
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Table 1. Seeking and identification of codes and themes.
Table 1. Seeking and identification of codes and themes.
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Table 2. Determinants influencing emotions in e-commerce based on interviews and accessible sources.
Table 2. Determinants influencing emotions in e-commerce based on interviews and accessible sources.
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Table 4. Factors influencing customer emotions from the panel’s perspective
Table 4. Factors influencing customer emotions from the panel’s perspective
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Table 5. Mean geometric variation of expert perspectives and defuzzified mean assessments.
Table 5. Mean geometric variation of expert perspectives and defuzzified mean assessments.
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Table 6. Precursors influencing customer emotions in purchasing luxury beauty and hygiene products.
Table 6. Precursors influencing customer emotions in purchasing luxury beauty and hygiene products.
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Table 7. Personal, situational, product, and group factors influencing emotional responses
Table 7. Personal, situational, product, and group factors influencing emotional responses
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