Executing marketing through a gender lens: a consumer purchase decision-making study in an emerging economy

Abstract

Purpose

With rapidly changing marketing landscape, nowadays, the formulation of various marketing strategies is increasingly focused on how consumers tend to make decisions. To meet the highly demanding consumer expectations, market segmentation can be used as an important marketing strategy. Due to gender marketing concept familiarity in the contemporary world, gender difference is one of the reference features in the process of market segmentation for marketers. This research is aimed to examine various determining factors that foster consumer purchase decision-making and the differences between consumers of different genders while making shopping and purchase decisions with special reference to an emerging economy, i.e. Pakistan.

Design/methodology/approach

Based on a cross-sectional sample of 367 consumers, the study adapted Sproles and Kendall's (1986) Consumer Style Inventory (CSI) to scrutinize the decision-making of both genders in Pakistan. For data analysis, the exploratory and confirmatory factor analysis in addition to the structural equation modeling has been used.

Findings

The study emphasized that, with the exception of quality awareness, brand consciousness, fashion consciousness, option overload and price consciousness greatly affect buying decisions. In addition, when it comes to consumer purchase decision-making, significant gender variations were discovered for both fashion consciousness and price consciousness.

Originality/value

Drawing upon the distinctive cultural characteristics of Pakistan and its people, in-depth research was conducted on purchasing behaviors of Pakistani consumers and the decision-making characteristics of customers of different genders were summarized. The outcomes are expected to make a significant contribution to the field of gender marketing by organizations.

Citation

Siraj, A., Zhu, Y., Taneja, S., Ali, E., Guo, J. and Chen, X. (2024), "Executing marketing through a gender lens: a consumer purchase decision-making study in an emerging economy", Arab Gulf Journal of Scientific Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/AGJSR-02-2023-0064

Introduction

The instigation of global markets has caused an overabundance of product choices as well as retail channels especially e-retail channels like the internet, television, online stores that offer discounts under promotional activities which makes decision-making by the consumers increasingly more complex. Consumers behave differently in the way they make purchase and consumption decisions (Tarnanidis, Owusu-Frimpong, Nwankwo, & Omar, 2015). There are several personal and non-personal factors that play an important part in shaping their consumption preferences, and these factors differ across various customer segments. Several attempts have been made in the extant marketing literature for understanding and measuring these differing styles and patterns (Abdel Wahab, Diaa, & Ahmed Nagaty, 2023; Herrando & Martín-De Hoyos, 2022; Lou & Yuan, 2019; Rašković, Ding, Hirose, Žabkar, & Fam, 2020).

In the existing literature on consumer behavior, most of the researchers have assumed several consumer approaches during shopping with certain decision-making behaviors which combine together to form the ultimate consumer’s decision-making (Rayi & Aras, 2021). Few of these traits including store/branch loyalty (Moschis, 1976), quality-consciousness (Darden & Ashton, 1974) and value-consciousness (McDonald, 1993), have already been observed and investigated by some of the previous researchers (Kim & Lee, 2016; Tjahjaningsih, Ningsih, & Utomo), and the most inclusive instrument measuring all these traits had been developed by Sproles and Kendall’s (1986) (CSI) Consumer Styles Inventory. The relevant literature mostly follows their seminal work (Sproles & Kendall, 1986) to scrutinize consumer decision-making styles in different contexts.

The process of consumer decision-making involves the determination of consumers’ needs, collection of relevant information, and evaluation of possible alternatives that help in making purchase decisions (Kim, Kireyeva, & Youn, 2014; Feng, 2016; Ngo, Nguyen, Long, Tran, & Hoang, 2019; Nguyen, 2019; Potluri & Johnson, 2020). From the consumers’ point of view, this kind of behavior is the result of a joint action of their psychological state and economic situation. They are influenced by different environmental factors, including cultural, group and social values (Yi & Su, 2014). From a company’s perspective, understanding consumer needs are important for them to choose their target market, position their products and develop appropriate marketing strategies (Han, Cho, & Yang, 2014; Han, 2020; Hooda & Ankur, 2018; Sung, 2021). Among the various market strategies, market segmentation is one of the important ways to cater to the rapidly changing customer needs.

The word Segmentation has been derived from the Latin word ‘segmentum’, which means ‘cut’. Market segmentation is a process of dividing a diverse market into different consumer groups to make them more recognizable. Market segmentation is a very important step in the marketing process. If the company does not take into account the needs of consumers and fails to recognize the difference between these needs, they cannot be able to accurately produce and sell their products (Wedel, Kamakura, & Böckenholt, 2000). Subdividing the market into homogeneous subsets of customers may be known as market segmentation and any subset of them can be identified as marketing targets and implemented through different marketing mixes (Kotler, 2012).

The benefits of market segmentation include (a) rapid detection of rapidly changing market trends (b) designing products that truly meet market needs (c) identifying the most effective advertising claims (d) directly promoting the right amount of media providing the greatest potential profits (Loudon & Della Bitta, 1984). In earlier related studies, the market segmentation was usually based on demographic aspects. Many of the everyday consumer products like clothing and personal care are designed, positioned and promoted based on the gender differences among the population. Therefore, the population-level classification is critical for the companies to segment their markets.

Another reason for market segmentation based on demographic characteristics is that the demographics are generally well explained and are easy to measure (Pol, 1991). Researchers often use the characteristics of income, age, gender, race, generation, and marital status to divide the consumer market among many demographic variables (Bashar, Ahmad, & Wasiq, 2013; Chaney, Touzani, & Ben Slimane, 2017; Do & Do, 2020; Kim & Yang, 2020; Pinna, 2020). Among these variables, gender is the most common form of business segmentation in the market for products as well as services (Yim, 2020). Similarly, marketing scholars such as Meyers-Levy and Sternthal (1991) considered that gender segmentation based on physiological gender itself can successfully segment the market because gender differences are easy to access, easily identifiable, and can be used for most of the consumer goods and services. Consumers are considered to be differing in making consumption choices (Tarnanidis et al., 2015) and gender is one of the most vital factors that influence consumer behavior.

Previous research has focused on the aspect of gender-based marketing, stating that there can be significant differences among males and females while making their shopping decisions in a variety of contexts (Cheung, Leung, Chang, & Shi, 2021; Yang, Isa, Ramayah, Blanes, & Kiumarsi, 2020). For instance, studies are there depicting that men see shopping as undesirable and unpleasant, and they tend to spend lesser time in making shopping decisions as compared to their women counterparts (Mehta, 2020). Also there are differences between both genders in assuming responsibility for different product categories (Kanwal, Burki, Ali, & Dahlstrom, 2022). The variations spotted in the literature direct us to expect and propose the differences in the decision-making styles and traits of different genders. Prior researchers have studied the association between consumer’s decision-making styles and consumer behavior based on different contexts, such as by finding varying patterns across various age groups, regions, and channels, among others (Abdel Wahab et al., 2023; Rašković et al., 2020). Little research exists on the differences in decision-making styles across genders, especially in developing countries. Among the developing nations, with a population of 235 million and $376 billion GDP having 6.2% growth each year (World Bank, 2023), Pakistan is the seventh-largest market of the Middle East, South Asia and African regions as measured by PPP (Purchasing Power Parity) (Wolf, 2020). Pakistan has numerous attributes which make it an attractive marketplace for global and multinational firms especially FMCGs. Previous studies have focused on noteworthy disparities in ownership and consumption of diverse product categories across genders in nations such as Pakistan (Amber & Chichaibelu, 2023). This highlights the significance of devising distinct marketing approaches for each gender within these regions. Acknowledging the significance of gender-based marketing and the limited amount of research conducted on this crucial aspect (Mehta, 2020), our endeavor involves an exploration of diverse determinants that influence the process of decision-making and the gender disparities pertinent to this sphere. Therefore, this research aims to direct towards answering the following research questions:

RQ1.

What are the various determining factors of consumer purchase decision-making?

RQ2.

How different genders differentiate with respect to these factors based on a sample gathered from an emerging economy, i.e. Pakistan.

To address the given questions, the study aims to achieve the objectives as follows:

1. To identify various determinants of consumer purchase decision-making.

2. To examine the moderating role of gender in the factors determining consumer purchase decision-making.

Literature review

Previous studies have generally focused on the question of what influences consumer choice and their decision-making styles. The consumer decision-making styles are closely related to the consumers’ cognition and the existing body of literature indicates that the perceptions of the consumers always dominate their choices (Karimi, Holland, & Papamichail, 2018). However, only a few scholars have studied the consequences of the styles of consumer decision-making. The seminal work of Sproles and Kendall (1986), i.e. CSI has been the most widely used for classifying the consumers by their decision-making styles. Over the time, this measurement instrument has fetched significant research attention, and there are several investigations based on this inventory in measuring context-specific and/or culture-specific differences (Helmi, Komaladewi, Sarasi, & Yolanda, 2023; Ma & Hahn, 2022). The instrument ranging back to several years is required to be tested for its validity in current contexts, and therefore recently, Eom, Youn, and Lee (2020) tested the inventory on two different groups of participants in the US, and reaffirmed its applicability and validity for studying decision-making styles of contemporary customers. Consequently, the significant studies in this direction (Islam & Chandrasekaran, 2020; Tarnanidis et al., 2015) establish CSI as a robust instrument to measure consumer decision-making styles in various contexts.

Initially, related research work was conducted by McDonald (1993) in which he attempted to study how the companies can further predict consumer loyalty by observing the shopper’s decision-making behaviors. Shim and Koh (1997) studied two aspects in this regard: social factors and social structure variables and explored how these two factors determine the decision-making styles of young customers. Salleh (2000) subdivided the decision-making style dimensions of the consumers concerning different products. On the same line, Wesley, Le Hew, and Woodside (2006) studied the relationship between consumer decision-making styles and shopping center behavior. Cowart and Goldsmith (2007) had explored different decision-making styles and behaviors of college students in the online apparels sales industry. With respect to the influence of lifestyle, Kwan, Yeung, and Au (2008) had argued that different lifestyles have an impact on the decision-making style of young Chinese consumers. Mokhlis (2010) had undertaken to compare the decision-making styles of consumers with different religious beliefs. Eun Park, Yu, and Xin Zhou (2010) explored whether the consumers' ability to innovate affects their shopping style significantly. Through a systematic study, Karimi, Holland, and Papamichail (2018) examined the intrinsic mechanism of consumer decision-making styles and the product knowledge affecting their decision-making process. In a recent study around the association of consumer decision styles, involvement, and intention, Klein and Sharma (2022) studied online group buying and found mediating role of involvement between different consumer decision-making styles and their intention to participate in group buying in online format.

In an attempt to view this aspect from a cultural lens, De Mooij and Hofstede (2010) found that most of the times the behavior of consumers is culturally constrained. The study reviewed the relationship between culture and self, personality, and attitude. These are considered to be the foundations of consumer’s behavioral patterns, brands and advertising strategies. Further, Mehta and Dixit (2016) studied the cross-cultural phenomenon of consumer decisions by investigating the consumption behavior of 185 German and 558 Indian students, comparing the socio-economic and cultural environments in which Indian and German consumers were found to have different decision-making styles. In similar direction, for understanding the regional differences in consumer decision-making styles using the cultural materialism perspective in China, Zhou et al. (2010) found that the consumers differ in hedonic shopping styles and not the utilitarian shopping styles. Further, some researchers studied specific variables of CSI across cultures to gain further insights. For example, to examine the differences between patterns of mobile shopping in Thai and Finnish consumers, Eriksson, Fagerstrøm, Khamtanet, and Jitkuekul (2021) established price consciousness as the basis for possible variations among different segments.

Concerning the classification of consumer decision-making styles, Bakewell and Mitchell (2003) divided them into five decision-making groups through a survey of adult female consumers in the United Kingdom: ‘People who pursue entertainment quality’ and ‘pursue entertainment discounts’ People, ‘people who are loyal to the trend’, ‘people who are not interested in shopping and fashion’ and ‘people who save time/money’. In a further study of British male consumer decision-making styles, Bakewell and Mitchell (2004) added four new features to the original classification: determining store loyalty/low price pursuit, time-energy Savings, chaotic time limits and promiscuity in stores. A few of the scholars have conducted research on the gender differences in decision-making styles of consumers (Lin, Featherman, Brooks, & Hajli, 2019; Mehta, 2020), such as Mitchell and Walsh (2004) selected the German males and females as the research subjects and analyzed their decision-making styles. Through the analysis, eight factors affecting female shoppers and four factors affecting male shoppers were identified, and the structural validity was tested in the article. The conclusions of the final research showed that the proportion of perfectionists is lower among male consumers than female consumers and male consumers have lower novelty and fashion sense, and will not get easily confused while shopping.

Bakewell, Mitchell, and Rothwell (2006) conducted similar research on college students in the UK They surveyed 480 students and found nine decision-making styles that were common among male and female college students. In addition, they identified different characteristics of boys and girls during the shopping process. The characteristics of boys were: store loyalty/low price seeking, confused time constraints and store confusion, and girls were characterized by bargaining, imperfections and shops loyalty. Another study by Hanzaee and Aghasibeig (2008) in Iran indicated that male and female consumers of Generation Y have significant differences in decision-making. Among 10 factors solution determined by males and 11 factors solution determined by females, 9 factors are shared by both the sexes. Researchers believed that this similarity was the result of changes in the gender role of Iran.

Research is increasingly focusing on profiling consumers based on their decision-making styles and the relationship of these cognitive styles with consumer behavior (Islam & Chandrasekaran, 2020; Javed, Rashidin, & Xiao, 2022; Klein & Sharma, 2022; Nayeem & Casidy, 2015). For example, Sofi and Nika (2017) compared impulsive buying behaviors of different gender groups and divided them into the relationship between impulsive buying behavior and various internal factors. The results of their study revealed that women are more likely to develop cognitive dissonance, poor publicity and a positive buying sensation than male consumers. Dennis et al. (2018) analyzed the shopping behavior of consumers in eleven countries. The analysis showed that males and females are having different shopping styles during the evolution process. The higher the gender equality in the country, the greater is the actual difference between the shopping styles of males and females. Among the variables, empathy was found to bear a greater impact on the women’s shopping style, while systemic was considered as more capable to adjusting the men’s shopping style.

Defining the gender difference in consumers' decision-making styles will help the companies to position their products and to identify the consumers in an effective manner (Tifferet & Herstein, 2012; Ye, Bose, & Pelton, 2018). Therefore, some prior researchers in the recent past have conducted research on this field of gender marketing (Ameen, Willis, & Shah, 2018; Javed et al., 2020; Lin et al., 2019). Machado, Vacas-de-Carvalho, Azar, André, and dos Santos (2019) considered gender to be a relevant source of consumers’ brand equity. However, brands having a strong gender identity tend to increase the consumer exposure and love for the brand, confirming the advantage of gender positioning. Borau and Bonnefon (2020) examined how men and women benefit from consumer products with gender characteristics and formalized people with typical gender-based products are considered to be sexier and more popular. Further, founded on gender as well as socio-cultural theories, Mehta (2020) conducted an empirical investigation of gender differences in the decision-making styles of the consumers in India with styles such as novelty consciousness, hedonism, brand loyalty orientation, and price value consciousness. She provided significant insights by highlighting the differences in the Indian males and females, more specifically, the millennial generation with respect to the decision-making styles.

From the review of extant literature, we identified interesting research gaps that need to be covered to add to the rich body of literature on consumer decision-making. Though there are several studies on the differences across various consumer segments with respect to their decision-making styles, not much emphasis has been made on understanding the influence of these styles on their purchase decisions. Also, there is a paucity of research on how different genders behave while making their purchase decisions based on different decision-making styles they carry. In addition, vast majority of relevant literature is focused on studies in developed countries (Eom et al., 2020; Nayeem & Casidy, 2015; Tarnanidis et al., 2015), where a little research has worked upon understanding the phenomena in emerging economies, despite the significant difference of population composition and consumer behavior in these nations (Rašković et al., 2020).

Sproles and Kendall (1986) has propounded eight consumer characteristics based on decision-making styles, i.e. brand conscious, price-value conscious, fashion-conscious, perfectionistic, recreational shopping conscious, impulsive, confused by over choice, and habitual or brand loyal. For the current research, we conceptualized a model signifying the various characteristics as the determining factors of consumer purchase decision-making. Five variables namely, brand consciousness, fashion consciousness, quality consciousness, price consciousness, and confused by over-choice (the state of being in confusion due to many options in hand) are considered as the constructs that can influence consumer purchase decision-making taking into consideration the unique consumer characteristics of Pakistani consumers and also based on the expert’s opinion at the stage of designing of the questionnaire for the current research. The use of this scale has been recommended by several scholars in the literature (Prakash, Singh, & Yadav, 2018), for instance, recent research conducted by Eom et al. (2020) has validated the use of the CSI scale to understand consumer decision-making behavior. They suggest CSI as a relevant tool to capture consumer decision-making behavior and to develop suitable marketing strategies. Based on Sproles and Kendall’s (1986) Consumer Style Inventory (CSI) and the discussion of the extant literature review, the following hypotheses are framed:

H1.

Quality consciousness significantly influences consumer purchase decision-making.

H2.

Fashion consciousness significantly influences consumer purchase decision-making.

H3.

Brand consciousness significantly influences consumer purchase decision-making.

H4.

Confused by over choice significantly influences consumer purchase decision-making.

H5.

Price consciousness significantly influences consumer purchase decision-making.

The relevant literature based on gender with respect to marketing suggests that there can be differences across the genders concerning consumer behavior. Consequently, we propose the following hypothesis:

H6.

There are significant gender differences concerning the factors influencing consumer purchase decision-making.

From the discussion of relevant literature, we found that consumers' decision-making style is closely related to gender, as well as their living environment and national culture. Therefore, based on the unique cultural characteristics of Pakistan, we conducted in-depth research on purchasing behaviors of Pakistani consumers using a survey instrument and summarized the decision-making characteristics of customers of different genders. This research expect to make significant contributions to the existing body of knowledge for future researchers as well as the marketers. The main objective of this research is to examine the decision-making styles of males and females in shopping, and to understand how they differ from each other and to identify the various factors that mark them different from each other. Further, the research aims to examine the factors that are common to these groups. Figure 1 depicts the research model conceptualized for the current research.

Methodology

This study focused on the decision making styles of consumers in Pakistan. The structured questionnaire was used to collect the required data from 367 Pakistani consumers who were selected from different regions of Pakistan. In order to achieve the aforementioned objectives, data from 271 male consumers and 96 female consumers were collected. The consumers' decision-making characteristics were measured with the variables in the original Consumer Style Inventory (CSI) by Sproles and Kendall (1986) and few items in CSI had been modified to suit the purpose of the research. The scale was designed following an extensive review of the literature and a focus group discussion with experts from academics and industry.

The questionnaire was developed following Sproles and Kendall (1986) CSI variables. Based on CSI, we developed earlier pool of items to represent a shopping situation, i.e. purchasing of apparels for self. Further, a focus group discussion was conducted with 4 experts from academia and 6 from industry to seek their opinion around the content validity of the scale as well as to finalize the scale. Based on the feedback received from the experts, five styles namely price consciousness, quality consciousness, brand consciousness, fashion consciousness, and confused by over choice were retained, in addition to consumer decision-making as the dependent variable for the study. The items for decision-making were adapted from generic scales for purchase decisions given by prior researchers, i.e., Ajzen (1991) and Prasad, Garg, and Prasad (2019). In the styles selected for the study also, some modifications were made to suit the context of current research. Therefore, a total of 25 items were generated for the questionnaire. Before going for final data collection, the questionnaire was pre-tested on a sample of 30 consumers to test the reliability and validity of the scale for proceeding with further study. The internal reliability of the scale was tested using Cronbach’s alpha (α) scores. For content validity, the feedback from pilot sample respondents was sought in terms of wording, understandability, completeness, unambiguity, and correctness of the scale questions. Based on the results of reliability and validity analysis, 4 items were deleted from the questionnaire, i.e. the items having α scores less than 0.5 (well below 0.7 benchmark by Nunnally, 1978) were omitted. The study constructs and their respective measurement items are depicted in Table 1.

The sample for the study was selected based on the convenient sampling technique. A total of 450 questionnaires were distributed among people living in different areas of the country. The data were primarily gathered from the students and the employed section of the population, and 395 (87.78%) of the questionnaires were retrieved, 6.22% of which were excluded for not meeting the requirements of validation, hence, a total of 367 (81.56%) valid questionnaires were attained for the purpose of further analysis. The current sample size is considered to be appropriate because according to Hoe (2008), any sample larger than 200 can provide adequate statistical power for analyzing the data. Further, for applying covariance-based SEM (CB-SEM), the minimum required sample size is 200 (Hoelter, 1983).

A self-administrated questionnaire was relied upon to gather data for the underlying study. The questionnaire consisted of (Sproles & Kendall, 1986) 21-items Likert-scale CSI. All scales were measured on 5-point Likert-type scales ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The reliability of CSI scale (according to Sproles & Kendall, 1986) was recorded at more than 0.7 for all the variables. These items were randomly ordered in self-administrated CSI instrument for consumer balance possible ordered effects. Moreover, the questions pertaining to demographic variables were also included in the questionnaire to understand the composition of current sample.

To examine the role of underlying variables in this study, the factor analysis tool by using statistical-based software, i.e. SPSS was employed. According to Vogt (1999), factor analysis is a tool that is often used in survey research questions and statement of evidence of research. It also provides a measure of construct validity (Huck, 2000). So for the purpose of current research, factor analysis was used to confirm whether the sample size was adequate for further analysis in this research. Factor Analysis tool was also used for confirmation of consumer decision-making style in the applied conversion of data into manageable factors about consumer decision-making style. Varimax rotation and KMO was used to summarize the items and measuring the sample adequacy respectively. Usually, KMO varies from values 0 to 1.00, however, according to Hair, Black, Babin, Anderson, and Tatham (2006), the acceptable value of KMO statistic should be higher or at least equal to 0.5 for satisfactory factor analysis to proceed. The KMO value for the current dataset was found to be satisfactory for employing factor analysis on it. To confirm the factor structure obtained through exploratory factor analysis, the confirmatory factor analysis was applied, following the two-step approach recommended by Anderson and Gerbing (1988). Structural equation modeling was employed to test the interrelationships among the variables and to identify the gender differences in consumer purchase decision-making.

Data analysis and results

For analyzing the data gathered from the sample of consumers, the exploratory and confirmatory factor analysis, followed by structural equation modeling technique (Anderson & Gerbing, 1988) was employed.

Table 2 shows that 74% of the respondents were males while the rest of 26% were females. A large percentage of respondents lie in the age range of 25 to 40, constituting 79% of the total respondents, while with respect to the income group, the two ranges are almost similar with a little margin of difference, i.e. less than 20,000 and 20,000 to 40,000.

The exploratory factor analysis was conducted using Principal Component Analysis with varimax rotation to explore the factor structure out of the dataset. A satisfactory factor pattern was attained with all the factor loadings exceeding 0.7 (Field, 2009). Next, the two-step approach to structural equation modeling was used. The confirmatory factor analysis was performed in order to confirm the factor pattern as well as to ensure the construct validity. The measurement model specified for the given dataset was found to be fit based on various indices (Hair, Black, Babin, Anderson, & Tatham, 2010; Bentler & Bonett, 1980; Carmines & McIver, 1981), i.e. χ² = 269.63, df = 314, p < 0.001; χ²/df = 1.55 (<3); GFI = 0.94 (>0.90); CFI = 0.97 (>0.90); TLI = 0.97 (>0.90); RMR = 0.05 (<0.08); RMSEA = 0.04 (<0.06). Table 3 represents the convergent and discriminant validity results.

To confirm the construct reliability and validity, the measures of internal consistency and composite reliability were calculated. The Cronbach’s alpha values as the measure for internal consistency for all the constructs were found to be more than 0.7 (Nunnally, 1978). The composite reliability scores were also recorded as above the threshold of 0.7 as recommended Carmines and Zeller (1979). In addition, the average variance explained (AVE) scores for all the constructs were found to be exceeding 0.5 (Fornell & Larcker, 1981) as well as greater than the maximum shared variance (MSV) values to hold the convergent validity to be true.

In order to ensure the discriminant validity, the diagonal and off-diagonal values in the correlation matrix were compared and the scale was found to be valid with the square roots of the AVE scores greater than the inter-construct correlation values. In addition, the data was diagnosed for the absence of common method bias (CMB). To avoid any potential issues of CMB, we informed the respondents about anonymity of responses before getting the questionnaires filled from them. It was done to avoid any potential biases, such as social desirability bias, at their end. Further, following Harman’s single-factor test (Harman, 1976), exploratory factor analysis was employed to find how much variance a single factor accounts for in the un-rotated solution. And the data was found to be free of the CMB with a single factor accounting for 21.55% of the total variance, i.e. far below 50% as per the recommendations of Podsakoff (2003).

Structural model

Concerning the model fitness of the structural model developed depicting the interrelationships among the constructs, it was found to be a fit with all the indices same as that of the measurement model. The results of the structural model containing the hypothesized relationships are given in Table 4.

The results of hypotheses testing (See Table 4 and Figure 2) revealed that all the exogenous variables, i.e. fashion consciousness, brand consciousness, confused by over choice, and price consciousness except quality consciousness were found to be significantly influencing consumer purchase decision-making. With respect to the differences based on gender (H6), the influence of two constructs namely, fashion consciousness (Critical Ratio = 3.20) and price consciousness (Critical Ratio = −4.09) on consumer purchase decision-making was found to be significantly different across different genders. It can be conferred that males and females consider fashion and price differently in the process of making purchase decisions.

Discussion

This research is an attempt to understand the gender differences in the process of consumer purchase decision-making. The findings of the study revealed that four variables, i.e. brand consciousness, price consciousness, fashion consciousness, confused by over-choice are found to be significantly influencing consumer purchase decision-making. These findings are consistent with the findings of various prior studies (Eom et al., 2020; Erikkson et al., 2021). In this regard, Rezaei (2015) have also established that consumer characteristics including brand consciousness, price consciousness, and fashion consciousness play major role in shaping consumer behavior across channels of advertising and retailing. Previous studies also support our finding that consumer’s purchase decision-making gets influenced when they are having decision-making style of being confused by over-choice, among other aforementioned styles (Tarnanidis et al., 2015). Therefore, it provides vital insights to the marketers to focus on these aspects while developing and selling their products. However, Gender differences were highlighted with respect to fashion consciousness and price consciousness which implies that different genders emphasize fashion consciousness and price consciousness in different ways while making shopping decisions. This finding is in conjunction with the outcomes of Mitchell and Walsh (2004). This finding can prove to be a great insight for businesses and practitioners while undertaking marketing strategies based on gender-based market segmentation.

Implications for theory and practice

The study offers significant implications for marketing research and practice. The results and findings of the study contribute to the existing body of knowledge on consumer behavior and marketing in general by focusing on consumer decision-making styles. The study extends the applicability of the scale adapted for this research, i.e. CSI scale, for understanding the purchase decision variances among different segments and targets. Also, the study adds to the scale validity by putting a gender lens to identify and study differences in consumer behavior. Moreover, by understanding the concept of gender-based marketing across different consumer decision-making styles in a developing country, the research adds a new perspective to the existing literature which is predominantly focused on developed parts of the world. Our research paves the way for further research to continue discovering gender differences in diverse shopping environments.

Based on the outcomes of the research undertaken, it can be stated that it is more likely that the consumers scoring exceedingly on the certain/specific decision-making characteristics will have clear needs associated with those characteristics that marketers could use to target in pursuing further marketing strategies, particularly the targeting strategies for the market segments based on gender. Therefore, the results are expected to contribute significantly to the field of gender-oriented marketing efforts by the companies. The marketers can formulate their target market policies by using the findings of the current research at an optimum level. Accordingly, the marketers and businesses can focus on different consumer styles as highlighted in our research for improving demand for their products in the market. Also, as fashion and price consciousness characteristics have been found to be different across genders, the marketers can stress on these dimensions while designing and marketing the products to different genders. The results could also provide insights and help the new market entrants to re-think the product positioning and target market of their specific product.

Conclusion and future research areas

This study has examined the various factors influencing consumer decision-making behavior while shopping and made a comparative analysis between the determinants of purchase decision-making of males and females in the context of Pakistan. These factors include brand consciousness, price consciousness, fashion consciousness, and confused by over choice. When viewed from the gender lens, fashion conscious and price conscious consumers were found to be behaving different in terms of their purchase decisions. The overall findings provide valuable insights to the marketers for framing appropriate strategies to shape demand and purchase behavior for their products, especially when they are catering to different genders in their market segments.

Though this study include sincere research efforts, there are certain limitations that are inherent in this research and can prove to be significant research directions for future investigations., Since the study considered different decision styles of consumers, further additional exploratory qualitative research can also be conducted to examine other aspects such as habit, cultural factors and other normative factors, and to explore the richness of the country’s consumer behavior. Country-specific factors precisely developed for the specific country to be considered would have to be taken into account and could be addressed in future cross-cultural applications of CSI. Future researchers can extend our research to the consumer’s purchase decision-making in the online retail environment to advance gender marketing research. Moreover, a comparative analysis of factors influencing consumer decision making in physical and online retailing can be a fruitful avenue for research in this field. Future research might focus on applying the CSI scale by including additional contextual variables to understand consumer decision-making styles for different contexts such as fashion marketing and organic consumption.

Figures

Figure 1

Research model

Figure 2

Structural model

Table 1

Study constructs and measurement items

Construct	Item code	Measurement items
Price consciousness	PC1	Price is an important factor while making a purchase decision
	PC2	I prefer to purchase lower price products
	PC3	I prefer to buy as much as possible on discounted sale price
Brand consciousness	BC1	Brand has a significant value for me while shopping
	BC2	I like to purchase one brand I like the most every time
	BC3	I like to select brand among my favorite brands according to their collection over and over
	BC4	The expensive brands are usually my choice
	BC5	I prefer buying the best-selling brands
Quality consciousness	QC1	Getting very good quality is important for me
	QC2	When it comes to deciding between good quality and price, I prefer quality
	QC3	I make special effort to get the best quality products
Fashion consciousness	FC1	I try to keep my wardrobe up-to-date with the changing trends
	FC2	Fashionable and attractive styling is very important for me
	FC3	I visit different brands and store to get variety
Confused by over choice	CBOC1	There are so many brands to choose from that often I feel confused
	CBOC2	Sometimes it’s hard to select which brand and store I should visit
	CBOC3	All the information about different products confuses me
	CBOC4	The more I learn about the product, the harder it seems to choose the best
Consumer decision-making	CDM1	I am interested in buying the particular brand/product
	CDM2	I will recommend this particular brand/product to others
	CDM3	I will be buying this brand/product over and over again in the future

Source(s): Scales adapted by authors

Table 2

Demographic profile of sample respondents

Demographic sample (% age of attained responses)
Gender	Male	74
	Female	26
Age	Below 25 years	7
	25–40 years	79
	41–55 years	13
	56 years & Above	1
Income	Less Than 20,000	36
	20,001–40,000	31
	40,001–60,000	15
	60,001 & Above	18

Source(s): Table by authors

Table 3

Convergent and discriminant validity

	CR	AVE	MSV	MaxR(H)	BC	CBOC	CDM	QC	FC	PC
BC	0.877	0.588	0.141	0.879	0.767
CBOC	0.819	0.531	0.076	0.824	0.058	0.729
CDM	0.892	0.734	0.141	0.896	0.375***	0.251***	0.857
QC	0.839	0.635	0.027	0.844	−0.036	−0.081	−0.08	0.797
FC	0.835	0.628	0.085	0.848	0.075	0.276***	0.292***	−0.053	0.793
PC	0.824	0.61	0.113	0.824	0.176**	−0.005	0.336***	0.164*	−0.001	0.781

Note(s): Significance of Correlations

†p < 0.100, *p < 0.050, **p < 0.010, ***p < 0.001

Source(s): Table by authors

Table 4

Structural model results

Label	Hypotheses	Estimate	S.E.	C.R.	P	Result
H1	QC → CDM	−0.099	0.057	−1.739	0.082	Not Supported
H2	FC → CDM	0.288	0.074	3.908	***	Supported
H3	BC → CDM	0.332	0.061	5.404	***	Supported
H4	CBOC → CDM	0.204	0.069	2.954	0.003	Supported
H5	PC → CDM	0.372	0.071	5.258	***	Supported

Note(s): †p < 0.100, *p < 0.050, **p < 0.010, ***p < 0.001

Source(s): Table by authors