Keywords

Health Drinks Consumption, Behavioral Reasoning Theory, Health Drink Marketing, Consumer Behavior.

Introduction

Malt-based health drinks (MBHD) are nutritious drinks that encourage milk consumption by improving its taste. They command a market size of about Rs 11,000 crore in India. Malnourishment and lack of availability of good milk have motivated consumers to use malt-based health drinks in India. The increased consumption resulted in a growth in the market of MBHDs. As per reports, India is the largest market for malt-based drinks globally and constitutes about twenty-two percent of world retail volume sales¹. In India, brands like Amul Pro, Boost, Bournvita, Complan, Horlicks, and Milo dominate the MBHD market. Horlicks and Boost constitute 54% of the malt beverage market, Bournvita command 15% of the market, PediaSure and Ensure constitute 9%, Complan, 5% of the market, and other brands, constitute the remaining 17% of the market. New brands and new products entered the market, and consumer preferences also changed in the process. It was expected that the market would grow and reach $ 1.76 billion by 2023². However, the market growth declined to 5-7% from 10-12% growth rate. The poor performance made a few companies sell their malt-based brands; GlaxoSmithKline Plc (GSK) sold Horlicks, and Kraft Heinz sold Complan³. Although the category was going through a phase of reduced growth, the overall industry growth for 2016-18 was 6%, and new firms were entering the market.

The experts believed, while the increased consumerism, lifestyle changes, and amelioration of living standards were the reasons for growth, health-oriented marketing initiatives and a young population propelled the growth of MBHD in India⁴. On the other hand, the reasons for decline included changed consumer behavior, changing market scenarios, and the emergence of alternatives. A significant reason behind the decline in growth was the consumer's perception of the product's sugar content. People's concern for healthy food was growing in India. It triggered the increased preference for less sugar content in food. The increased demand for less sugar content altered consumers' preference for MBHD. In addition, the availability of good quality milk across the country transformed consumers' practice of using MBHD as a taste enhancer. Besides, consumers also started using other alternatives like syrups and flavored milk to enhance milk taste. Analysis of per capita retail volumes for MBHD explains the story. The per capita volume consumption of MBHDs in India was relatively low⁵. In 2015, the per capita retail volume sales of MBHDs in India was 0.2kg compared to 1.2kg of sales in Singapore, 1.1kg in Malaysia, and 0.5kg in Hong Kong. So, the Indian consumer has reasons for and reasons against the consumption of MBHD that has driven the sales performance of MBHD in India.

Against this backdrop, it is realized that the malt-based health drinks consumption phenomenon in India, although quite interesting, has attracted limited interest from scholars. The analysis of the extant literature suggests that a very small number of studies have focused on consumers' purchases of malt-based health drinks in India. These studies explored the factors influencing malt-based health drinks consumption in specific local contexts. Findings from these studies suggest people prefer to consume malt-based health drinks for their nutrient content (Parsad et al., 2019), taste, flavor, and digestive properties (Raj & Shiny, 2017); doctors' advice and friends/relative's suggestion (Ananthi, 2018); muscle building (Parsad et al., 2019); for refreshment and as an energy drink (Thomas & Rajendran, 2020). To summarize, these studies explain the reasons for consuming malt-based health drinks. However, to understand the cognitive process influencing the attitude towards the consumption and intention to consume MBHD, it is imperative to understand both reasons for and against consumption (Westaby, 2005). Considering the gap in these researches, we propose this study to explore the reasons for and against the consumption of malt-based health drinks.

Furthermore, the practitioners believe the performance of MBHD is influenced by both consumer reasons for and reasons against the consumption of MBHD. The reasons for decline included changed consumer behavior, changing market scenarios, and the emergence of alternatives. A significant reason behind the decline in growth was the consumer's perception of the product's sugar content. People's concern for healthy food was growing in India. It triggered the increased preference for less sugar content in food. The increased demand for less sugar content altered consumers' preference for MBHD. In addition, the availability of good quality milk across the country transformed consumers' practice of using MBHD as a taste enhancer. Malt-based health drinks have nutritional properties. Indian consumers have preferred malt-based health drinks for their nutritional properties over time. However, with the availability of good milk, there has been a shift in consumers' preferences. Besides, consumers had also started using other alternatives like syrups and flavored milk to enhance milk taste. Nevertheless, academic studies have not so far studied this phenomenon.

In response to this gap, our study attempts to explore the integrated effect of reasons for and reasons against consumption on the purchase and consumption of MBHD in India.

About Mbhd& Mbhd Industry in India

MBHDs are malt-based foods consisting of malt, cereals, and legume flour. They may also contain milk and cocoa powder. They are marketed as nutritious beverages, and marketers claim the MBHDs contain carbohydrates, protein, fats, vitamin A, vitamin B, vitamin C, vitamin E, and minerals like calcium, iron, phosphorus, and potassium. In India, the beverages are commonly called health drinks. They are marketed as nutritional supplements and are positioned as an alternative source of nutrition for kids and the elderly. However, consumers prefer malt-based health drinks not only for their nutritional values but also for their taste. These are added to milk to enhance milk taste and encourage growing children to consume milk. Thus, MBHDs are traditionally consumed as milk additives by sick, young, and old consumers in India. The milk additives provided flavor to milk, increased the palatability of milk, and consumers believed it to fulfill the nutritional requirements. In an emerging market like India, these values helped malt-based health drink brands occupy a market of Rs 11,000 crore. As per reports, India was the largest market for MBHDs globally and constituted about twenty-two percent of world retail volume sales. South India and East India constituted the largest markets for MBHDs. The Market research studies also estimated the total market for MBHD in India to grow to $ 1.76 billion by 2023.

There are two categories of Health Food Drinks available in India; white drinks and brown drinks. Category wise white drinks accounted for about 66% of the market; however, brown drinks continue to grow fast. White drinks include major brands like Horlicks, Complan, Boost, Maltova, and Bournvita, and Milo constitute the brown drinks. In India, brands like Boost, Bournvita, Complan, Horlicks, and Milo dominated the MBHD market. Horlicks and Boost constituted 54% of the malt beverage market, Bournvita commanded 15% of the market, PediaSure and Ensure constituted 9%, Complan, 5% of the market, and other brands, constituted the remaining 17% of the market. It was expected that the market would grow and reach $ 1.76 billion by 2023. However, the market growth declined to 5-7% from a 10-12% growth rate. Although the category was going through a phase of reduced growth, the overall industry growth for 2016-18 was 6%, and new firms were entering the market.

The above discussion indicates the scope for continued growth for MBHD in India. Also, from the discussion, it could be inferred that to achieve this growth, the firms need to address the significant factor influencing the demand for MBHD in India, i.e., the changing consumer behavior patterns. Therefore, the design of a future course of action for the MBHD segment in India would require a proper understanding of the reasons behind this transformation.

About the Study

In this study, we aim to understand the consumer reasons that influence on consumption of MBHDs in India. In order to understand the future of this food product in an emerging market like India, it is essential to explore the reasons influencing consumer choices. It is essential to acknowledge that consumers can have two choices, i.e., accepting MBHD or rejecting MBHD. If consumers decide to accept MBHD, they purchase and consume health drinks. On the other hand, they do not purchase and consume MBHD if they choose to reject it. Keeping these two aspects of consumer choice in mind, we investigate the reasons for acceptance and reasons against acceptance of MBHDs in India. Previous studies have also shown that considering both reasons for and reasons against a purchase can provide better insight into behavioral reasoning behind consumer choices (Ryan & Casidy, 2018; Tandon et al., 2020). Therefore, the study's primary objective is; (RO1) to explore the consumer reasons for and reasons against the consumption of malt-based health drinks. While several prior studies (Parsad et al., 2019; Raj & Shiny, 2017; Ananthi, 2018; Thomas & Rajendran, 2020; Agbaeze et al., 2017; Anetoh et al., 2020) on MBHD consumption behavior have examined the factors influencing purchase and consumption behavior, none of the earlier studies have examined the impact of consumer reasoning on attitude, intention to consume MBHD and consumption behavior. Consequently, our study attempts to address this gap by investigating the relationship between attitude, intention, and consumption behavior using the Behavioral Reasoning Theory (Westaby, 2005). So, the second research objective is; (RO2) to understand the impact of the behavioral reasons on the consumer's attitude, intention, and consumption. The study findings are expected to help marketers make decisions regarding the marketing of MBHD.

Conceptual Framework and Hypotheses

It is essential to understand two perspectives of malt-based health drink consumption, i.e., acceptance and resistance. Acceptance tells about the reasons for consumption, and resistance suggests the reasons against consumption. Considering both perspectives can provide better insights into consumer decision-making (Ryan & Casidy, 2018). Available studies on the consumption of MBHDs in India suggests people prefer to consume malt-based health drinks for their nutrient content (Parsad et al., 2019), taste, flavor, and digestive properties (Raj & Shiny, 2017); doctors' advice and friends/relative's suggestion (Ananthi, 2018); muscle building (Parsad et al., 2019); for refreshment and as an energy drink (Thomas & Rajendran, 2020). However, consumer resistance to malt-based health drinks is still poorly understood. Hence, this research aims to understand consumers' behavioral reasoning processes in the context of malt-based health drink consumption. The research will use the behavioral reasoning theory (BRT) to investigate the process. The perspective suggested by BRT had been used across multiple contexts such as organic food consumption (Ryan & Casidy, 2018; Tandon et al., 2020), alcohol consumption (Norman et al., 2012), and leadership decision-making (Westaby et al., 2010). No study previously used BRT to explain malt-based health drink consumption for all we know. The present study extends the extant research findings by exploring the impact of consumer reasons for and against malt-based health drink consumption behavior in the context of the emerging Indian economy.

The BRT suggests that reasons for and reasons against the practice of a specific behavior can explain the consumer's adoption of the behavior (Westaby, 2005). Besides, the reasons are context-specific. Conversely, there is a lack of an established stream of research exploring consumers' purchases of malt-based health drinks (Mohamed et al., 2015). Although some knowledge about possible reasons against malt-based health drinks consumption is available, it is not coherent and lacks contextual specificity. Against this backdrop, the present study attempts to determine significant reasons against malt-based health drinks consumption in the specific context of India.

The studies as mentioned earlier suggest nutritional value (Parsad et al., 2019), taste and flavor (Raj & Shiny, 2017); malt-based health drinks' impact on health (Raj & Shiny, 2017; Parsad et al., 2019); the influence of friends and doctors (Ananthi, 2018) and energy content of the MBHD (Thomas & Rajendran, 2020) as the significant reasons for consumption. While these studies explained the factors influencing MBHD consumption, they did not consider the reasons against the consumption. Considering reasons against to explain consumer behavior can help explain the cognitive process influencing the attitude and intention of the consumer (Westaby, 2005). Consequently, this study follows BRT to explain malt-based health drink consumption behavior. BRT incorporates both reasons for and reasons against consumption in the conceptual framework to explain consumption behavior.

Thus the study sets two primary research objectives. RO1: To explore the reasons (for and against) the consumption of malt-based health drinks. RO2: To explore the impact of reasons (for and against) on the attitude, intention to consume malt-based health drinks, and consumption of malt-based health drinks. To address these objectives, we collected data from 502 participants from India and analyzed it to find the reasons and their association with other variables.

Behavioral Reasoning Theory

Behavioral reasoning theory (BRT) (Westaby, 2005) elucidates the interrelationships among reasons, beliefs, global motives, and behavioral intentions. BRT postulates that "reasons for" and "reasons against" are subjective factors and influence consumers' attitudes, intentions, and behavior. These reasons are context-specific (Tudor et al., 2007; Westaby et al., 2010). The "reasons for" are opposites of "reasons against" adoption and are qualitatively distinct constructs from the reasons against constructs. Furthermore, the reasons (for and reasons against) influence consumption decisions differently (Claudy et al., 2015). In the field of marketing, BRT has been utilized to describe the innovation adoption behavior (Claudy et al., 2015), charitable donation (Arli & Lasmono, 2015; Chatzidakis et al., 2016), adoption of urban bicycling behavior (Claudy & Peterson, 2014), and mobile banking usage behavior (Gupta & Arora, 2017). Studies in food marketing have used BRT to explain organic food consumption behavior (Ryan & Casidy, 2018). Findings from all these prior studies ascertain that BRT can effectively predict consumer attitude, intention, and behavior.

Following BRT, this study proposes that consumer reasons influence consumer attitudes and intention to adopt malt-based health drinks. Consumer attitudes will influence consumption intentions, and intentions will influence consumer behavior. The following section presents the theoretical justification for the conceptual framework.

Behavioral Intention and Behavior

Consistent with the behavioral reasoning theory (Westaby, 2005 ), we propose that a stronger intention to consume malt-based health drinks will influence behavior. Past studies on consumer purchase behavior suggest intention is the predictor of behavior (Zeithaml & Parasuraman, 1996 ; Michaelidou & Hassan, 2014; Sultan et al., 2020 ). Sheeran (2002) also suggests that intention represents people's decision to act. These findings align with the theory of reasoned action ( Fishbein & Ajzen, 1975) and the theory of planned behavior (Ajzen, 1991). Following these previous studies, we suggest that malt-based health drink consumption behavior will be influenced by the decision to consume malt-based health drinks. Based on these arguments, we hypothesize that;

H1: Consumer intentions to consume malt-based health drinks will positively influence consumption of malt-based health drink.

Attitude and Behavioral Intentions

Attitude indicates consumers' opinion (favorable or unfavorable) toward a behavior (Smith & Paladino, 2010).

In contrast, behavioral intentions relate to the subjective probability of associating with an action (Fishbein & Ajzen 1975). Consumer attitude influences consumer intention (Casidy et al., 2017; Dilmperi et al., 2016). Consequently, we hypothesize that.

H2: Consumers' attitudes towards consuming malt-based health drinks will influence their intention to consume malt-based health drinks positively.

Reasoning and Attitudes

The notion of "reasons for" and "reasons against" can be compared to functional theorizing, sense-making, and psychological coherence (Claudy et al., 2013). Individuals use reasons (both for and against) to justify their actions (Smith & Paladino, 2010). Consumers' reasons also influence their attitude formation (Myyry et al., 2009). Studies in the context of malt-based health drink consumption have reported nutritional value (Parsad et al., 2019), health, doctor's advice/friend's suggestion (Ananthi, 2018), refreshment (Thomas & Rajendran, 2020), and taste (Raj & Shiny, 2017) as the main reasons for consumption of malt-based health drinks. Many kids and a few adults do not like the milk's taste and flavor. However, the parents believe milk is essential for their kids' health. So, they add malt-based health drinks to the milk to enhance the taste of the milk and improve its flavor. If the changed flavor of milk enhances the acceptability of milk among kids, mothers perceive MBHD to be beneficial. Adults also add MBHDs to milk to enhance its palatability. Immediately after recovering from some illness, many individuals think about consuming MBHDs. They are advised to do so by some doctor or a friend. Individuals also consume MBHDs when they perceive them to be nutritionally essential. Consequently, if consumers have positive reasons to consume the MBHDs, they may perceive the product as useful. On the other hand, if individuals like the flavor and taste of milk and believe milk is complete nutrition and need no additives, they may not perceive MBHDs of any use. Besides, if consumers believe MBHDs can lead to sugar-related problems, they may perceive MBHDs as not beneficial. Therefore, consumers' reasons against consuming malt-based health drinks may result in a negative attitude towards the product. Consistent with the BRT framework, we propose that consumers with solid reasons for (against) consuming malt-based health drinks will possess a positive (negative) attitude toward it.

H3a. Consumer reasons for consuming malt-based health drinks will influence their malt-based health drinks consumption attitude positively.

H3b. Consumer reasons against consuming malt-based health drinks will negatively influence their consumption attitudes.

Reasons and Behavioral Intention

Consumers' reasoning influences their behavioral intentions directly (Westaby, 2005). Reasons are strong drivers of intention, and consumers use reasons to justify their actions. Consumers prefer simple decision-making processes (Tversky & Kahneman, 1974) and use cognitive shortcuts. In the context of malt-based health drinks, consumers may like the taste of the malt-based health drink, but they decide against the purchase of the drink because of a critical reason like the regular availability of the product.

H4a: Consumers' reasons for consuming malt-based health drinks will positively influence their consumption intentions.

H4b: Consumers' reasons against the consumption of malt-based health drinks will negatively influence their consumption intentions.

Reasons and Behavior

According to BRT, reasons are essential antecedents of people's behaviors (Westaby, 2005). People use reasons to explain and justify their behavior, and reasons influence their behavior (Westaby et al., 2010). Furthermore, reasons are critical for people's judgment and attitude formation (Bagozzi et al., 2003; Bartle et al., 2013). People's evaluation of behavior is favorable (unfavorable) when they have solid reasons for (against) doing the behavior (Westaby, 2005). Adding MBHD to milk changes the flavor of the milk. If the kid likes the changed flavor, then he drinks the milk. Acceptance of MBHD added to milk by a kid is the strong reason for mothers to continue using MBHD (Figure 1). Similarly, if the kid dislikes the sweet taste of the MBHD added milk and denies drinking the milk, then it is a strong reason against the use of MBHD in the future for the mother. People also use reasons to avoid cognitive dissonance. When the behavioral choices and the attitude lack a match, people use reasons to justify their behavioral choices (Claudy & Peterson, 2014). Consumers also use the reasons to simplify decision-making (Tversky & Kahneman, 1974). Against this backdrop, we suggest that context-specific reasons explain the variation in malt-based health drink consumption behavior. Accordingly, we hypothesize;

Figure 1 Conceptual Mode

H5a: Consumer reasons for consuming malt-based health drinks influence the consumption of malt-based health drinks positively .

H5b: Consumer reasons against consuming malt-based health drinks influence the consumption of malt-based health drinks negatively .

Methodology

Participants and Procedures

We conducted an exploratory qualitative study followed by an online survey to collect data. The purpose of the exploratory study was to understand context-specific reasons for and against malt-based health drinks consumption. The exploratory study was conducted to elicit reasons for and against the consumption of MBHDs. Then the researchers evaluated the findings of the elicitation study and converted them into multi-item scales. The analysis found that people consumed malt-based health drinks because they tasted good, enhanced milk taste, improved health, increased height, provided energy, and doctors suggested drinking malt-based health drinks to improve bone health. Conversely, the reasons against the consumption of malt-based beverages included lack of availability of malt-based health drinks, the belief that the malt-based health drinks decrease the efficiency of milk, and the perception that these are not good for health. The qualitative exploration helped generate items for the final survey. These initial items were pilot tested twice (n=100). After the first pilot test (n=50), the authors revised the measures and then conducted the second pilot testing (n=50) to check the revised measures. Next, the authors conducted an online survey. This study's subjects were all those who could consume malt-based health drinks. Because of our interest in people's perceptions regarding malt-based health drink consumption, our sampling frame included both types of consumers, i.e., people who like to consume and people who do not like to consume malt-based health drinks. Participation in the survey was voluntary and no monetary or any other incentives were offered to the respondents. On average, the survey took 15 minutes to complete. An online survey link was sent to 2000 respondents. The response rate was 27.5%, and we received five hundred fifty completed responses. Forty-eight incomplete responses were excluded from the final analysis. The final sample size was 502. Table 1 below presents the demographic profile of the sample.

Measures

The measurement items used were following the previous research on behavioral reasoning theory (BRT) (Westaby, 2005) and health food marketing (Júnior et al., 2019; Armitage & Conner, 1999; De Toni et al., 2018). This study used established scales based on extant research to measure the focal constructs. The scales were adapted to suit the Indian context. Attitude toward consumption of malt-based health drink was assessed using a three-item scale ("Consuming malt-based health drink is very good/beneficial/helpful") adapted from Júnior et al. (2019). The reliability for the scale was very high (alpha=0.926). Consistent with previous theory (De Toni et al., 2018), a two-item scale ("I think about buying malt-based health drinks next month"; "I will suggest my friends consume malt-based health drinks") was used to measure the behavioral intention. The Cronbach alpha for the scale was 0.809. Consumption behavior (α=0.948) was measured using a three-item scale ("I have continually purchased malt-based health drinks"; "I bought malt-based health drinks last month"; "My behavior regarding the purchase of malt-based health drinks is: I am buying and I have been doing this for a long time") which was consistent with previous research (Júnior et al., 2019; Armitage & Conner, 1999). Reasons were elicited through the qualitative research. The reasons for was assessed with six items, by asking respondents if they agreed or disagreed that they like to consume malt-based health drinks because; "it tastes good," "it enhances the taste of milk," "it improves health," "it increases height," "it provides energy," "doctors suggest drinking malt-based health drinks to improve bone health." The reliability of the scale was achieved (0.886). Similarly, reasons against were measured using a three-item scale ("These are not available at my place," "I think the malt-based health drinks decrease the efficiency of milk," "These are not good for health"). The Cronbach alpha for the scale was 0.828. The constructs were measured using a five-point Likert scale, ranging from strongly disagree (1) to strongly agree (5).

Findings and Analysis

After preliminary data processing, Jamovi (Version 1.8.1) was used for descriptive statistics and factor analysis. The analysis was followed by partial least squares structural equation modeling (PLS-SEM) using WarpPLS vs. 6.0 (Kock, 2017).

Sample Profile

The sample consisted of 59% males and 41% females. The majority of respondents (84%) belonged to the 21-30 year group, and 13% of the respondents belonged to the age group 15-20 years. About 82% of respondents completed graduation, and 10% possessed post-graduate or higher degrees. Half of the respondents (50%) were students, and around 40% reported having either a government job (20%) or a private salaried job (20%). According to annual household income level, 62% of the respondents reported an annual income of (1-5) lakh, about 20% reported an annual income less than 1 lakh, 17% of the respondents reported an annual income of 5-10 lakh and only 1% of the respondents reported annual household income greater than 10 lakh. Of the 502 respondents, 489 respondents (97.4%) reported consuming malt-based health drinks in the past; however, only 373 respondents (74.3%) reported they currently consume malt-based health drinks.

Common Method Bias

Variance inflation factors (VIFs) scores were considered to assess common method bias (Kock & Lynn, 2012; Kock & Gaskins, 2014; Kock, 2015). All the VIFs were less than 3.3. Therefore, the model was devoid of common method bias. Table 2 below presents the VIFs obtained for all the latent variables.

The research model testing involved a two-step process; assessing measurement model quality and testing hypotheses (Anderson & Gerbing, 1988). To assess measurement model quality, we determined its overall fit and examined its convergent and discriminant validity (Gefen & Straub, 2005). Hypotheses testing involved the examination of path effects and significance levels in the hypothesized structural model Table 3.

Measurement Model

Model fit with the data was assessed by considering the p values of the average path coefficient (APC), p values of the average r-squared (ARS), and the average variance inflation factor (AVIF) (Kock, 2017). The fit indices of the model met all of the three criteria, i.e., the p values for both APC and ARS were lower than 0.05, and the AVIF was lower than 5. The model has a good fit Table 3.

Validity and Reliability of Scales

Convergent validity: The factor loadings were all above the recommended threshold of 0.5 and significance levels of p<0.001 (Hair et al., 2011). The cross-loadings were much lower. Both composite reliability (0.898 to 0.967) and Cronbach's alpha (0.809-0.948) of the constructs were above the recommended threshold of 0.7 (Fornell & Larcker, 1981). These results indicate that the items exhibit acceptable convergence toward the latent variable Table 4.

Discriminant validity: The correlations among constructs are less than the square root of the average variance extracted (AVE) values indicating that the measurements have good discriminant validity. Table 5 below presents the values.

Structural Model

Next the authors conducted hypothesis testing by examining the structural models. Based on the results, all the initial hypotheses are supported at p<0.01. The best predictor of consumers' intention to drink MBHD is represented by consumers' reason against the consumption of MBHD (β= -0.58), followed by reasons for the consumption of MBHD (β=0.42), and consumer attitude towards MBHD (β=0.12). Consumers' attitude towards MBHD is determined by consumers reasons for drinking MBHD (β=0.73) and consumers' reasons against the consumption of MBHD (β=-0.14). Consumer behavior (i.e., consumption of MBHD) is predicted by consumer reasons for drinking MBHD (β=0.37), consumers' intention to drink MBHD (β=0.30), and consumers' reasons against the consumption of MBHD (β= -0.31) Figure 2.

Figure 2 Structural Path Estimates for the Hypothesised Model

Next, we assessed the magnitude of the relationships between latent variables using Cohen's effect sizes. According to Cohen's f-squared effect size coefficients, 0.02 represents a small effect size, 0.15 medium, and a coefficient 0.35 represents large effect sizes. Results are presented in Table 6. From the results, it can be stated that: i. Reason against the consumption of malt-based health drinks and reasons for drinking malt health drinks have a medium effect on consumers' intention to drink malt-based health drinks, while attitude has a small effect; ii. Reasons for drinking malt health drinks have a strong effect on consumers' attitude towards consumption of malt-based health drinks, and reasons against drinking malt health drinks have a small effect on attitude towards consumption of malt-based health drinks. iii. Intention and reasons for drinking have medium effects on behavior (regular consumption of malt health drinks), and reason against drinking malt-based health drinks have a small effect on behavior Table 7.

Discussion

This study adds substantially to our understanding of malt based health drink marketing. Using the BRT framework, the study explains consumers' cognitive processing associated with health drink consumption. The results intimate that consumers have reasons for and reasons against MBHD consumption. In particular, the findings suggest that consumers consume malt-based health drinks because (1)it tastes good and it can increase the taste of milk, (2) it can improve health, (3) it can increase height, (4) it helps in gaining weight during illness (5) it provides energy and (6) doctor's suggest malt-based health drinks consumption improve bone health. Conversely, consumers' reasons against the consumption of malt-based health drinks include; (1) non-availability of the product, (2) adverse impact on the efficiency of milk, and (3) health deteriorating effect. The reasons against consumption explain the most variance in intention to consume MBHD. Next to reasons against, the reasons for consumption explain the variance in intention to consume MBHD. On the contrary, consumer reasons for consumption explain most variance in health drink consumption behavior, followed by reasons against consumption. As others have highlighted (Claudy & Peterson, 2014), reasons and beliefs are perceptual phenomena. Our study validates that the reasons constitute the justifications consumers cite to consume MBHD. Therefore, to promote health drink consumption behavior, food marketers and health drink manufacturing companies must address the subjective factors that discourage consumers from consuming malt-based health drinks. In addition, marketers need to strengthen the reasons for the MBHD consumption.

There are cases where the attitude of a consumer has an insignificant influence on consumption behavior. Sometimes people may have a positive attitude towards malt-based health drinks, but they do not consume the health drinks. Secondly, some people may hold negative attitudes toward malt-based health drinks, yet they consume the malt-based health drinks. The inclusion of reasons can explain these behavioral choices that are not appropriately aligned with their attitude (Westaby, 2005). In light of these findings, marketers need to design behavior change interventions based on the reasons for and reason against consumption. The following section explicates the implications of our findings for malt based health drink marketing.

Theoretical Implications

This study identifies the importance of consumer reasoning in the context of malt- based health drink consumption. The results have several implications for research into understanding behavioral patterns related to malt-based health drink consumption. These findings demonstrate how consumer reasons significantly affect consumer attitude, intention, and behavior. The study accordingly supports previous findings in the literature related to the BRT framework (Peterson & Simkins, 2019; Claudy & Peterson, 2014; Norman et al., 2012; Westaby, 2005; Westaby et al., 2010).

Nevertheless, only a few studies examined the linkage of behavioral reasons (reasons for and reasons against) and consumer behavior (Sahu et al., 2020). Our study is an addition to this line of research that suggests consumer "reasons for" and "reasons against" consuming malt-based health drinks explain the variance in consumption behavior. By exploring the behavioral reasons for health drink consumption, our study adds substantially to our understanding of health drink consumption practices. The next most striking result of this study is the significance of consumer reasons for explaining the health drink consumption behavior. Context-specific reasons account for the differences in the consumption of health drinks. In this manner, the study lends support to the BRT by using behavioral reasoning to explain the new context of health drink consumption. These findings are unique because there was a need to explore BRT in a fast-moving consumer goods context (Sahu et al., 2020).

From a business perspective, firms have a myriad of options on how to introduce experiences to customers. Knutson et al. (2007) argue that firms can create the marketing offering to express the experience or the offering can be seen as the experience itself. Instinctively, in creating such an experience, the aim should be that all resources and activities are aligned such that a total package of sort is envisaged. With the above, more value is created for all stakeholders in the form of experiences (Knutson et al., 2007). Despite this insight, the customers’ perspective of the concept of experience is also riving with several interpretations and as such research seems to be limited as to what customer experience entails (Palmer, 2010).

Implications for Marketing of Malt-Based Health Drinks

The findings have significant marketing implications. First, marketers need to do more than just awareness generation to encourage voluntary behavior change (Howard, 2000). Increasing public knowledge and fostering a positive attitude towards health drinks may not effectively invoke the desired response in malt-based health drink consumption. Findings from this study indicate that influence of attitude on behavior is less compared to the reasons. The empirical findings indicate that people use reasons (mainly reasons against) to account for their current health drink consumption behavior. The use of reasons helps consumers avoid cognitive dissonance. Hence marketers need to design interventions based on consumer reasons. Reasons are people's perceptions hence marketers need to design communication strategies to change the negative perceptions and bolster positive perceptions of the consumers. Secondly, reasons against consumption contribute to maximum variance in intention to consume. Thus, marketing interventions targeted at consumer intention must work towards eliminating the reasons against consumption. Similarly, marketing interventions targeted at behavior change should focus more on strengthening the reasons for consumption because reasons for consumption contribute the most to variance in consumption behavior.

Thirdly, potential losses have a more significant influence than the potential gains on consumers' behavioral decisions (Kahneman & Tversky, 1979). Individuals use reasons to defend their behavioral decisions. They are subjective factors that may not involve objective cost-benefit evaluations. Marketers can reduce people's reasons against the consumption of malt-based health drinks, and in doing so, they can motivate change in intention to consume health drinks, particularly in situations in which availability is a problem. Specifically, MBHD manufacturers need to address the non-availability of the product, perception regarding the adverse impact on the efficiency of milk, and beliefs regarding the health deteriorating effect of MBHD. While increasing the accessibility can solve the problem of non-availability, sharing evidence-based information on the health benefits and advantages of MBHD can boost the intention to purchase.

Finally, voluntary behavior change is unlikely to result from merely changing consumer beliefs. The empirical results from this study propose that consumers have reasons not to engage in malt-based health drink consumption behaviors. Unless marketers address these reasons successfully within their specific context, health drink consumption rates among consumers cannot be improved. Enrichment of the milk taste, improvement of health, and physician's advice are the most compelling reasons affecting the consumer's behavior. Therefore, MBHD marketers need to design products to cater to three segments of the consumers; taste-loving consumers, health-conscious consumers, and hybrid consumers who want both taste and health.

The objective of the study was to explore the reasons for and reasons against the consumption of malt-based health drinks among Indian consumers. In this process, the study used the BRT framework to test the impact of psychological constructs on health drink consumption behavior. Nonetheless, the study has certain limitations. First, the study did not test the impact of value orientations on the reasons. Values influence consumer reasons. So, future studies could incorporate consumer value orientation in the model. Second, this study evaluated a limited set of antecedents to malt-based health drink consumption behavior.

Future studies can assess the impact of demographic factors, social and economic factors, consumer habits on health drinks consumption. The third limitation relates to the population and sample. The reasons are context-specific, and this study considered consumer reasons from India. Therefore, future research may attempt to look into the reasons for and reasons against consuming malt-based health drinks in other parts of the world. Fourth the study adopted a PLS- structural equation modeling (PLS-SEM) approach to assess the theory in the context of malt-based health drinks. However, future research can explore the evolution of the reasons in response to marketing claims. Using qualitative techniques (e.g., narrative analysis), future research could explore the changes in the consumer reasons (both for and against) associated with the consumption of malt-based health drinks.

Conclusion

In essence, our study attempted to explain the malt-based health drink consumption behavior. Toward this end, the study drew on Behavioral Reasoning Theory to explore the impact of consumer reasons, attitudes, and intentions on malt-based health drinks consumption behavior. Specifically, the findings indicate that context-specific reasons for malt-based health drinks consumption and, more importantly, reasons against malt-based health drink consumption explain much of the variance in consumers' health drink consumption behavior. Briefly, to conclude, BRT can be used as an effective consumer behavior model in promoting malt-based health drink consumption.

Endnotes

¹https://consumeraffairs.nic.in/sites/default/files/file-uploads/ctocpas/HealthDrinks.pdf

²The "India Malted Food Drinks Market By Product Type (With Cocoa Powder & Without Cocoa Powder), By Distribution Channel (Convenience Stores, Independent Small Grocers, Pharmacies, Online Channel & Others), Competition Forecast & Opportunities, 2013-202

³https://blog.euromonitor.com/health-positioning-leads-to-strong-growth-of-malt-based-hot-drinks-in-india/.

⁴ConsumerVoice. Health drinks making milk richer. 2013. http:// consumeraffairs.nic.in/consumer/writereaddata/Health_Drink.pdf. Accessed 11 Dec 2014.

⁵https://www.techsciresearch.com/report/india-malted-food-drinks-market/1286.html.

References

Agbaeze, E.K., Nnabuko, J.O., Ifediora, C.U., & Ekoja, G.O. (2017). Comparative analysis of consumers’ patronage of beverage food drinks in Enugu state, Nigeria. International Journal of Scientific & Engineering Research, 8(6), 1744-1766.

Ananthi, N. (2018). A Study on Consumer Behaviour towards Malt-Based Health Drinks in Madurai City. Multidisciplinary Global Journal of Academic Research, 5(3),35-43.

Anderson, J.C., & Gerbing, D.W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.

Anetoh, J. C., Nnabuko, J.O., Okolo, V.O., & Anetoh, V.C. (2020). Sensory Attributes of Malt Drinks and Consumer Purchase Decisions. Journal of Food Products Marketing, 26(5), 317-343.

Arli, D., & Lasmono, H. (2015). Are religious people more caring? Exploring the impact of religiosity on charitable organizations in a developing country. International Journal of Nonprofit and Voluntary Sector Marketing, 20(1), 38–51.

Armitage, C.J., & Conner, M. (1999). Distinguishing Perceptions of Control From Self-Efficacy: Predicting Consumption of a Low-Fat Diet Using the Theory of Planned Behavior1. Journal of Applied Social Psychology, 29(1), 72–90.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

Bagozzi, R.P., Bergami, M., & Leone, L. (2003). Hierarchical representation of motives in goal setting. Journal of applied psychology, 88(5), 915.

Bartle, C., Avineri, E., & Chatterjee, K. (2013). Online information-sharing: A qualitative analysis of community, trust and social influence amongst commuter cyclists in the UK. Transportation Research Part F: Traffic Psychology and Behaviour, 16, 60–72.

Casidy, R., Lwin, M., & Phau, I. (2017). Investigating the role of religiosity as a deterrent against digital piracy. Marketing Intelligence & Planning, 35(1), 62–80.

Claudy, M.C., Garcia, R., & O'Driscoll, A. (2015). Consumer resistance to innovation—a behavioral reasoning perspective. Journal of the Academy of Marketing Science, 43(4), 528-544.

Claudy, M.C., & Peterson, M. (2014). Understanding the Underutilization of Urban Bicycle Commuting: A Behavioral Reasoning Perspective. Journal of Public Policy & Marketing, 33(2), 173–187.

Claudy, M. C., Peterson, M., & O'Driscoll, A. (2013). Understanding the attitude-behavior Gap for Renewable Energy Systems Using Behavioral Reasoning Theory. Journal of Macromarketing, 33(4), 273–287.

De Toni, D., Eberle, L., Larentis, F., & Milan, G.S. (2018). Antecedents of perceived value and repurchase intention of organic food. Journal of Food Products Marketing, 24(4), 456-475.

Dilmperi, A., King, T., & Dennis, C. (2017). Toward a Framework for Identifying Attitudes and Intentions to Music Acquisition from Legal and Illegal Channels. Psychology & Marketing, 34(4), 428–447.

Ajzen, I., & Fishbein, M. (1975). Belief, Attitude, Intention, and Behaviour: An Introduction to Theory and Research, Addison-Wesley. Reading.

Fornell, C., & Larcker, D.F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50.

Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-Graph: Tutorial and annotated example. Communications of the Association for Information systems, 16(1), 5.

Gigerenzer, G., & Goldstein, D.G. (1996). Reasoning the fast and frugal way: models of bounded rationality. Psychological review, 103(4), 650.

Gupta, A., & Arora, N. (2017). Consumer adoption of m-banking: a behavioral reasoning theory perspective. International Journal of Bank Marketing.

Hair, J.F., Sarstedt, M., Ringle, C.M., & Mena, J.A. (2012a). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433.

Howard, G.S. (2000). Adapting human lifestyles for the 21st century. American Psychologist, 55(5), 509–515.

Júnior, A.P.S., Zucoloto, C.R.F., André, O. de F., Mainardes, E.W., & Link to external site, this link will open in a new window. (2019). Healthy food purchasing behavior for children. International Review on Public and Non - Profit Marketing, 16(1), 103–124.

Kahneman, D., & Tversky, A. (1979). On the interpretation of intuitive probability: A reply to Jonathan Cohen, 7(4), 409–411.

Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1-10.

Kock, N. (2017). WarpPLS user manual: Version 6.0. ScriptWarp Systems: Laredo, TX, USA, 141.

Kock, N., & Gaskins, L. (2014). The Mediating Role of Voice and Accountability in the Relationship Between Internet Diffusion and Government Corruption in Latin America and Sub-Saharan Africa. Information Technology for Development, 20(1), 23–43.

Kock, N., & Lynn, G. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for information Systems, 13(7).

Michaelidou, N., & Hassan, L. (2014). New advances in attitude and behavioural decision-making models. Journal of Marketing Management, 30(5–6), 519–528.

Mohamed, H.J.J., Loy, S.L., Taib, M.N.M., Karim, N.A., Tan, S.Y., Appukutty, M., ... & Tee, E. S. (2015). Characteristics associated with the consumption of malted drinks among Malaysian primary school children: findings from the MyBreakfast study. BMC Public Health, 15(1), 1-11.

Myyry, L., Siponen, M., Pahnila, S., Vartiainen, T., & Vance, A. (2009). What levels of moral reasoning and values explain adherence to information security rules? An empirical study. European Journal of Information Systems, 18(2), 126–139.

Norman, P., Conner, M.T., & Stride, C.B. (2012). Reasons for binge drinking among undergraduate students: An application of behavioural reasoning theory. British journal of health psychology, 17(4), 682-698.

Claudy, M. C., Peterson, M., & O’driscoll, A. (2013). Understanding the attitude-behavior gap for renewable energy systems using behavioral reasoning theory. Journal of Macromarketing, 33(4), 273-287.

Parsad, C., Chandra, C. P., & Suman, S. (2019). A Product Feature Prioritization-Based Segmentation Model of Consumer Market for Health Drinks. International Journal of Strategic Decision Sciences (IDS), 10(2), 70–83.

Peterson, M., & Simkins, T. (2019). Consumers' processing of mindful commercial car sharing. Business Strategy and the Environment, 28(3), 457-465.

Raj, P.A., & Shiny, S. (2017). A study on consumers preference towards malted food in kanyakumari. International Journal of Research-GRANTHAALAYAH, 5(4 (SE)), 52-62.

Ryan, J., & Casidy, R. (2018). The role of brand reputation in organic food consumption: A behavioral reasoning perspective. Journal of Retailing and Consumer Services, 41, 239–247.

Sahu, A. K., Padhy, R. K., & Dhir, A. (2020). Envisioning the future of behavioral decision-making: A systematic literature review of behavioral reasoning theory. Australasian Marketing Journal (AMJ), 28(4), 145-159.

Sheeran, P. (2002). Intention-behavior relations: A conceptual and empirical review. European review of social psychology, 12(1), 1-36.

Smith, S., & Paladino, A. (2010). Eating Clean and Green? Investigating Consumer Motivations towards the Purchase of Organic Food. Australasian Marketing Journal, 18(2), 93–104.

Sultan, P., Tarafder, T., Pearson, D., & Henryks, J. (2020). Intention-behaviour gap and perceived behavioural control-behaviour gap in theory of planned behaviour: Moderating roles of communication, satisfaction and trust in organic food consumption. Food Quality and Preference, 81, 103838.

Tandon, A., Dhir, A., Kaur, P., Kushwah, S., & Salo, J. (2020). Behavioral reasoning perspectives on organic food purchase. Appetite, 154, 104786.

Thomas, S., & Rajendran, D.S. A Study on Consumer Preference Towards Health Drinks in Thanjavur Town. JournalNX, 6(11), 222-226.

Tudor, T.L., Barr, S.W., & Gilg, A.W. (2007). Linking intended behaviour and actions: A case study of healthcare waste management in the Cornwall NHS. Resources, Conservation and Recycling, 51(1), 1– 23.

Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124–1131.

Westaby, J.D. (2005). Behavioral reasoning theory: Identifying new linkages underlying intentions and behavior. Organizational Behavior and Human Decision Processes, 98(2), 97–120.

Westaby, J.D., Probst, T.M., & Lee, B.C. (2010). Leadership decision-making: A behavioral reasoning theory analysis. The Leadership Quarterly, 21(3), 481–495.

Zeithaml, V.A., Berry, L L., & Parasuraman, A. (1996). The Behavioral Consequences of Service Quality. Journal of Marketing, 60(2), 31–46.

Kock, N. (2017). WarpPLS user manual: Version 6.0. Script Warp Systems: Laredo, TX, USA.

Kock, N., & Gaskins, L. (2014). The Mediating Role of Voice and Accountability in the Relationship Between Internet Diffusion and Government Corruption in Latin America and Sub-Saharan Africa. Information Technology for Development, 20(1), 23–43.

Kock, N., & Lynn, G. (2012). Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations (SSRN Scholarly Paper ID 2152644). Social Science Research Network.

Michaelidou, N., & Hassan, L. (2014). New advances in attitude and behavioural decision-making models. Journal of Marketing Management, 30(5–6), 519–528.

Mohamed, H.J., Loy, S.L., Mohd Taib, M.N., A Karim, N., Tan, S.Y., Appukutty, M., Abdul Razak, N.,Thielecke, F., Hopkins, S., Ong, M.K., Ning, C., & Tee, E.S. (2015). Characteristics associated with the consumption of malted drinks among Malaysian primary school children: Findings from the MyBreakfast study. BMC Public Health, 15(1), 1322.

Myyry, L., Siponen, M., Pahnila, S., Vartiainen, T., & Vance, A. (2009). What levels of moral reasoning and values explain adherence to information security rules? An empirical study. European Journal of Information Systems, 18(2), 126–139.

Norman, P., Conner, M.T., & Stride, C.B. (2012). Reasons for binge drinking among undergraduate students: An application of behavioural reasoning theory. British journal of health psychology, 17(4), 682-698.

O'Driscoll, A., Claudy, M., & Peterson, M. (2013). Understanding the attitude-behavior gap for renewable energy systems using behavioral reasoning theory. Journal of Macromarketing, 33(4), 273–287.

Parsad, C., Chandra, C.P., & Suman, S. (2019). A Product Feature Prioritization-Based Segmentation Model of Consumer Market for Health Drinks. International Journal of Strategic Decision Sciences (IDS), 10(2), 70–83.

Peterson, M., & Simkins, T. (2019). Consumers' processing of mindful commercial car-sharing. Business Strategy and the Environment, 28.

Raj, P.A., & Shiny, S. (2017). A study on consumer's preference towards malted food in Kanyakumari. International Journal of Research -GRANTHAALAYAH, 5(4(SE)), 52–62.

Ryan, J., & Casidy, R. (2018). The role of brand reputation in organic food consumption: A behavioral reasoning perspective. Journal of Retailing and Consumer Services, 41, 239–247.

Sahu, A.K., Padhy, R.K., & Dhir, A. (2020). Envisioning the future of behavioral decision-making: A systematic literature review of behavioral reasoning theory. Australasian Marketing Journal (AMJ), 28(4), 145-159.

Sheeran, P. (2002). Intention-behavior relations: a conceptual and empirical review. European review of social psychology, 12(1), 1-36.

Smith, S., & Paladino, A. (2010). Eating Clean and Green? Investigating Consumer Motivations towards the Purchase of Organic Food. Australasian Marketing Journal, 18(2), 93–104.

Sultan, P., Tarafder, T., Pearson, D., & Henryks, J. (2020). Intention-behaviour gap and perceived behavioural control-behaviour gap in theory of planned behaviour: Moderating roles of communication, satisfaction and trust in organic food consumption. Food Quality and Preference, 81, 103838.

Tandon, A., Dhir, A., Kaur, P., Kushwah, S., & Salo, J. (2020). Behavioral reasoning perspectives on organic food purchase. Appetite, 154, 104786.

Thomas, S., & Rajendran, D. S.(2020). A Study on Consumer Preference Towards Health Drinks in Thanjavur Town. JournalNX, 6(11), 222-226.

Tudor, T.L., Barr, S.W., & Gilg, A.W. (2007). Linking intended behaviour and actions: A case study of healthcare waste management in the Cornwall NHS. Resources, Conservation and Recycling, 51(1), 1-23.

Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124–1131.

Westaby, J.D. (2005). Behavioral reasoning theory: Identifying new linkages underlying intentions and behavior. Organizational Behavior and Human Decision Processes, 98(2), 97-120.

Westaby, J.D., Probst, T.M., & Lee, B.C. (2010). Leadership decision-making: A behavioral reasoning theory analysis. The Leadership Quarterly, 21(3), 481–495.

Zeithaml, V.A., Berry, L.L., & Parasuraman, A. (1996). The Behavioral Consequences of Service Quality. Journal of Marketing, 60(2), 31–46.