Italian Consumers: Craft Beer or No Craft Beer, That Is the Question

Abstract

The aim of our study is to investigate the factors that drive craft beer consumption choices in Italy. To this end, we simultaneously analyze purchase intentions and actual craft beer consumption. The theoretical approach took into account the main doctrinal frameworks, particularly those most widely used in marketing studies. Through PLS-SEM analysis (partial least squares structural equation modeling), we examine how consumption habits, liking, appeal, territorial identities, and perceived quality shape intentions and also the actual behavior of Italian consumers towards craft beer. The results highlight how attractiveness and interest in the craft beer phenomenon, lifestyle, and curiosity for new flavors and aromas demonstrate an openness to craft beer and a new cultural identity among consumers. In many cases, respondents stated that they wanted to support local craft breweries and the local economy. Consumer trust in agri-food products is closely linked to their perception of authenticity and compliance with quality and safety standards. A better understanding of these aspects could help everyone involved in the entire supply chain implement more effective and targeted campaigns.

1. Introduction

Beer is one of the world’s oldest beverages. Its production has been a human activity since the dawn of urbanization and civilization in the Neolithic [1] and has evolved alongside the populations who consumed it, so much so that it itself constitutes the history of scientific and technological progress as well as the history of administration, economy, rituals, and daily life [2]. Beer was a staple of the ancient diet across a vast territory, stretching from the Middle East to Egypt and from the Aegean to Rome. The first traces of beer production appear to date back to the Sumerians [3] whose production process spread from Mesopotamia to Anatolia, Syria, and Israel, while industrial beer production continued in Egypt [4].

In the Middle Ages, beer production spread across Europe, probably thanks to monks who brewed beer and used it for both liturgical and commercial purposes [5]. The industrial revolution did not even spare beer production, which became mechanized and standardized. Thus, modern industrial beer was born [1]. Today, beer also represents differentiation, variety, and innovation. A new beverage, born from the creativity and passion of master brewers, is produced around the world with a vast array of styles and varieties. “Craft beer” which contrasts with the more well known and widely consumed “industrial beer” is increasingly widespread thanks to experimentation and is made with selected production methods and high-quality ingredients [6,7]. Having established itself in the United States at the end of the last century, it soon spread throughout Europe. The first entrepreneurial experiments were also noted in Italy [8,9]. However, it was only after the first decade of the new century that the production of craft beers acquired new interests and dimensions [10]. The same legislator will have to intervene with a specific regulatory provision on craft beers [11] in 2016, through the law on the hygienic regulation of beer production and trade (Law 1354 of 1962). It is the first regulatory instrument to introduce, in Italy, the definition of craft beer. The legislator establishes this: craft beer is beer produced by small independent breweries and not subjected to pasteurization and microfiltration processes (Law no. 154 of 2016). Today, craft beer in Italy is not only a beverage that claims a role and dignity independent of industrial beer, but it is also a movement that involves the entire country, with raw materials and production mostly carried out by small- and medium-sized manufacturing companies [12]. The beer industry has recently been experiencing a crisis due to declining consumption. Indeed, as reported by [13], the very perception of beer is changing radically, and new trends have emerged globally. For example, in Germany, unlike the conventional beer market, the craft beer market shows potential for development, as craft beer is well received by consumers who appreciate diversity and originality. Therefore, producers have begun to adapt their marketing strategies. And this despite the fact that Italians are “light beer drinkers”, almost as if to underline the choice to privilege diversity rather than quantity [14]. Whatabeer counted 693 unreleased beers from 211 Italian breweries in 2024. In 2023, the count included 653 beers from 184 breweries [15]. The 2024 data therefore demonstrate a significant increase in new beers. Several factors are behind this increase: certainly the refinement of survey techniques, but above all the confirmation of the “unreleased beers” phenomenon, which continues to characterize the activity of Italian breweries, and the increase in collaborative beers. The latter, of the total unreleased beers, reached a share of 18.84%, confirming a trend that has continued to grow since 2021. In 2024, therefore, almost one in five new beers was born from the collaboration between two or more breweries, demonstrating how much this practice is appreciated by Italian producers, to the point of becoming, in some cases, a clear marketing strategy. In 2022, beer-producing companies in Italy reached 1326 units, employing a total of 9612 direct employees [16]. Italy ranks sixth in Europe (after France, the United Kingdom, Germany, Switzerland, and the Netherlands) in terms of the number of breweries and ninth in terms of production volume. According to a 2024 study by AssoBirra, the craft beer sector saw substantial growth in production, exceeding 480,000 hl after a decline in 2023 [12].

Over the last fifteen years, research on the craft beer market has increased. Studies on craft beer production and consumption have focused primarily on quality, safety, innovation, and geographical origin [17]. Many have considered in their research the consumption and purchasing habits, the intrinsic and extrinsic attributes preferred by consumers and their main socio-demographic characteristics [14,18,19,20,21,22,23,24,25]. However, at present, although research on the factors that determine craft beer consumption preferences is further growing [17,26,27,28,29], studies on the propensity to purchase remain relatively scarce and only a few studies have investigated it empirically. Furthermore, among the studies on craft beer, PLS-SEM analysis (partial least squares structural equation modeling) is applied only in a few studies [30,31,32].

Our study follows this path and, using PLS-SEM analysis, aims to investigate the factors that influence this propensity, to help improve knowledge about consumption choices and the (emotional and cognitive) behaviors involved in purchasing craft beer in Italy.

The study identified seven multi-item latent constructs that examine the preferences and behaviors of 363 consumers. The first two, “Like” and “Consumption Habit,” were identified from six formative items, such as established habits; the remaining five latent constructs are assessed by thirteen reflective items: Appeal, Perceived quality, Territorial identity, Purchasing capability end Propensity purchase and consume. The seven constructs are made up of a total of 19 items that refer to the survey questions inspired and drawn from the literature [21,29,33,34,35]. Respondents are asked to indicate the extent to which they agree or disagree with each statement on a 5-point scale Likert (from 1 = strongly in disagreement at 5 = strongly in agreement). In order to determine which latent variables and hypothetical relationships to test with the PLS-SEM method, several reference theories most commonly used in marketing studies and used in research were a valuable guide. These were also identified in the literature. The theoretical framework guided the construction of the PLS-SEM model. The theories and hypotheses formulated in the theoretical framework represent the conceptual presuppositions for formulating the research hypotheses and indicate which latent variables and relationships to test with the PLS-SEM method. The theories served as the conceptual presuppositions for formulating the research hypotheses, developing, implementing, and ultimately interpreting the results.

In this context, we posed the following research questions:

QR1: What are the main attributes that guide and influence craft beer consumption choices in Italy? QR2: What is the propensity of Italians to purchase craft beer?

Based on these research questions, this study aims to advance research on the topic of craft beer in three ways: (a) by exploring the factors that drive and influence consumption choices and the propensity to purchase craft beer in Italy; (b) by formulating research hypotheses based on the literature review and the theoretical approach predominantly used in marketing studies; (c) by implementing, with the aid of PLS-SEM analysis, a model to examine the relationships between latent constructs and indicators (the measurable variables) and to evaluate the predictive performance of the model itself.

2. Theoretical Background and Research Model

2.1. Literature Review

Many researchers have studied craft beer, one of the most consumed beverages in the world, to examine the market, both from the supply and demand side and to investigate very broad aspects that in the field of food science have a multidisciplinary approach, which integrates principles of economics, marketing, microbiology, chemistry, nutrition, food technology and sensory sciences [36]. The emergence of craft beer consumption as a new market segment is a recent phenomenon [37] which has seen the growth and spread of craft breweries driven by new consumer demands, oriented towards innovation and consumer demand for quality and safety, new aromas and new complex flavors [18,19]. The craft beer segment brings together people seeking new, authentic, symbolic, and identity-building experiences. The choice of craft beer varies based on consumer preferences in relation to intrinsic attributes such as flavor, aroma, head, style, temperature, visual appearance, color, and alcohol content [17,20,38]. Meanwhile, extrinsic product attributes (brand, price, packaging, origin, label) concern information held by the consumer that can influence consumer expectations. In this context, several scholars have identified consumer typologies based on their characteristics and preferences using hierarchical cluster analysis [19,33].

With reference to studies conducted in Italy, several authors have investigated the main market segmentation factors, particularly sociodemographic characteristics (age, gender, income, household composition), consumption habits, and lifestyle. Among other factors, attitudes, motivations, and interest in ingredients and local provenance have been analyzed to group consumers based on behavioral and sociodemographic similarities [17,20,21,26,39].

In recent years, the literature review has been well addressed in many complete and exhaustive studies, in particular see Hernández-Mora et al., 2022 [38], Gobbi et al., 2024 [36], Ualema et al., 2024 [40] and Pilone et al., 2023 [17].

2.2. Theoretical Background

Regarding the theoretical framework, the current wide range of foods and beverages on the market can make consumer choice difficult. Consequently, this increases the complexity of studies and theoretical approaches within different fields of study, ranging from food economics to consumer sciences and marketing. Many scholars study the behaviors, intentions, and propensities to consume and purchase food and beverages by applying various theories that provide ideas and conceptual insights to develop a theoretical framework and formulate the most suitable research hypotheses to be tested empirically with the construction of the PLS-SEM model.

Consumer economic theories of food and beverages focus on how consumers make purchasing decisions and analyze the factors that influence preferences, choices, and quantities purchased, considering factors such as income, prices, individual preferences, expectations, and external influences. Consumer preferences are also influenced by psychological factors (such as personal tastes, habits, perceptions, lifestyle) and social factors (such as fashion, cultural influences, advertising).

Economic theories therefore offer tools for understanding how consumers make purchasing decisions, considering a wide range of factors that influence their choices and quantities purchased. These theories are useful for analyzing consumer behavior, forecasting market trends, and developing effective marketing strategies. To this end, in this study, we considered the eight theories listed below.

• The extended model of the Theory of Planned Behavior (TPB) [41,42]. Recently, many new constructs and theoretical approaches have been added to the TPB theory [43,44]. Among the studies on beverages, the articles by Sabina de Castillo et al. (2021) [45] and García-Barrón (2025) [46] stand out. The authors apply the extended model to the theory of planned behavior by adding other constructs to the original ones indicated by Ajzen, the first to predict the intention and behavior of local wine consumption [45], the second to determine the factors that influence the consumption of a traditional fermented beverage such as pulque to contribute to its promotion and to identify new marketing opportunities [46]. Ungureanu et al. in a very recent study on the agri-food sector in a north-eastern region of Romania, apply PLS-SEM to identify the elements that influence consumers’ purchasing decisions [47]. In their work, the authors consider sociocultural influences, product characteristics, brand trust, tradition, and lifestyle, examining the interrelationships between subjective norms, product attributes, price, consumer trust, and purchasing decisions. In this theoretical approach, in addition to the addition of new constructs, other theories were considered.
• The self-determination theory (SDT), which is widely used in marketing studies. SDT takes into account a person’s commitment to a certain behavior to explain and predict the intrinsic and extrinsic motivations of purchase decisions [48,49].
• Zhao et al. (2025), in their study on the beverage industry and sustainable marketing, use PLS-SEM, integrating the Big Five personality model (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism) with the experiential marketing theory, building a chain mediation model that links personality traits, experiential dimensions and green purchase intention [50]. In their work, they consider the “Experiential Marketing Theory” (sense, sensation, thought, action and relationship) [51], with the “Trait Theory” of Tett et al. (2021) according to the latter, specific situational cues activate consumers’ personality traits, eliciting emotional and behavioral responses [52]. This theoretical integration offers insights into how intrinsic personality traits interact with experiential stimuli to shape green consumption experiences.
• The protection motivation theory (PMT), Pang et al., 2021 [53] in their study on factors influencing intention to purchase organic food, propose Roger’s (1975) protection motivation theory (PMT) [54]. PLS-SEM has also recently been used to explore the role of health-related perceptions in influencing citizens’ engagement in forest conservation using the health belief model (HBM) [55].
• Also very interesting for foods and beverages is the cognitive response theory (CRT), which examines the factors that influence the persuasion to consume a product. In the work of Goel and Garg, A., 2025, such exhortation is addressed to people by influencers and/or through promotional messages and information [56]. Due to the limitations of human influencers, companies are allocating budgets to promote marketing strategies based on virtual influencers (VIs), whose popularity is pushing companies to redesign their marketing strategies [56].
• Other studies focus on consumer acceptance of novel foods and beverages (NFBs). In this regard, Syuzanna Mosikyan et al., 2024 [57] in their systematic literature review, examine the main key theories and theoretical frameworks identified on consumer acceptance of novel foods and beverages (NFBs). They emphasize the importance of individual beliefs, attitudes, and subjective norms that shape consumer acceptance. This highlighted the importance of understanding the cognitive and psychological mechanisms underlying consumer decision-making processes and which influence when new foods and beverages (NFBs) are introduced into a market.
• Anchored in Consumer Culture Theory (CCT), this field of study examines how consumption is influenced by broader cultural and social contexts [14,18]. CCT emphasizes that consumption is not an isolated individual activity, but is profoundly influenced by the social and cultural context in which it occurs and represents an expression of identity and belonging to a group [58]. It represents a cultural practice that contributes to creating and maintaining shared meanings and values within a territory. Within the theory of consumer culture, craft beer represents an expression of identity, a lifestyle, and plays a role in social construction, identity expression, and meaning-making. In this regard, Sakdiyakorn and Chirakranont’s contribution to a case study of community craft beer consumption in Thailand is interesting [59]. Ulver et al. (2021) [60] in their work on the social ethics of craft consumption, also examine the case of craft beer in a regulated market. The authors question how an alcoholic beverage can have ethical meanings despite strong health trends in global consumer culture and find that craft beer is integrated with a consumerist imaginary of social work and community ethics, which overcomes the potential stigma of alcohol. Weber et al. (2018) [61] also explored consumer culture and behavior to test Wisconsin residents’ loyalty to local craft beer versus imported beer. The research showed not only the study participants’ ethnocentric tendencies, but also their cultural behavior as part of the system for these products in Wisconsin, USA [62].
• Agnieszka Wiśniewska et al., 2025, incorporate the Value-Believes-Norms theory (VBN) into their study on consumer engagement for a green economy [63]. This theory argues that individual values influence beliefs, personal norms, and behavior. In the context of local connection, VBN suggests that an individual’s core values regarding the protection of the local economy and food and beverage producers foster specific beliefs and concerns about socioeconomic and environmental issues, contributing to behavioral attitudes and actions that favor the local economy and environment.

These theories, which address the influences of different factors on consumer purchasing behavior, offer a multidisciplinary perspective and a framework for understanding consumption preferences and propensity to purchase.

2.3. Hypothesis and Research Model

The various theories identified and their related methodological approaches served as a useful starting point for us to address and study the propensity to consume and purchase craft beer. The conceptual framework for this study is shown in Figure 1. The model shows the potential drivers that guide consumers’ choices and their propensity to consume and purchase craft beer. The study formulated eight research hypotheses defined by using the literature and the economic and marketing theories previously identified.

Craft beers have a fascinating and appealing appeal for consumers. They attract with their novelty and new flavors, and they align with their lifestyle and their desire for unique consumer products that enhance their well-being. Craft beers evoke a sense of identity and transform the drinking experience into a unique one [64]. Compared to industrial beer, craft beer is changing the way consumers perceive the beer category [65,66]. Carbone and Quici (2020) observed that the sense of “naturalness and authenticity” is one of the reasons why consumers demand craft beer [23]. In this sense, the TPB and the constructs added in many recent studies, represent a first step in our theoretical framework to examine behaviors, preferences and the interrelations between the propensity to purchase with the attributes of product, price, trust, subjective norms [41,47]. Craft beer represents a cultural and social phenomenon that determines and influences the propensity to purchase and consume it. Among the theories that take social and cultural engagement into account, we considered: SDT, experiential marketing theory, and trait theory. These elicit emotional and behavioral responses in consumers that shape perceptions, evaluations, and lifestyles [23,48,51,52,67,68].

The propensity to purchase is related to income and the potential or otherwise to purchase and consume it. As reported by Donadini et al., 2016 [20] Europeans in recent years have indulged in more and more expensive craft beers. Disposable income is increasing and therefore they are more inclined to experiment with new flavors, aromas, color, opalescence, brightness, bubbles, and foam [20]. In this scenario, the advantage of craft beers lies in innovation, creativity, uniqueness, and authenticity, thanks to the experimentation with innovative combinations of ingredients and flavors that consumers can find in craft beer [69]. They appreciate and follow the craft beer phenomenon, are passionate about it, and are open to tasting and purchasing craft beers with new flavors and aromas [21]. Theoretical frameworks on the acceptance of novel foods and beverages fall within the scope of NFB studies.

Consumer appeal and attractiveness for craft beer also depends on safety and perceived quality. Consumers care about label information, safety, product quality, and production technology. In this case, Roger and Deckner’s PMT and the health belief model (HBM) are important theoretical approaches for consumers who are increasingly concerned about food safety and the quality of food and beverages. In light of these observations, three research hypotheses have been postulated:

Hypothesis 1.

The appeal of craft beer has a positive impact on the propensity to purchase and consume craft beer.

Hypothesis 2.

The appeal of craft beer has a positive and significant impact on consumers’ purchasing power.

Hypothesis 3.

The appeal of craft beer has a positive impact on perceived quality and taste.

The theory of planned behavior (TPB) also helps us understand the purchasing behavior and the possible repurchase of craft beer, in fact, Income, WTB, and willingness to pay (WTP) are factors consumers consider when purchasing craft beer. Price and income are often considered (positively or negatively) in consumer choices. Craft beer, often sells for more than industrial beers [19,24,29,33,70]. This aspect has been observed by Carbone and Quinci (2020), who underline in particular the willingness to pay of the interested consumers [23], while, Cascone et al. (2025), highlight how craft beer consumers consider the price a relevant factor for their purchasing decisions [71]. In general, predictive purchase and consumption intention is influenced by several factors, including income, product price, and motivational factors such as habits, lifestyle, and availability. Therefore, the fourth research hypothesis is identified:

Hypothesis 4.

The ability to Purchase have a positive and significant influence on the propensity to consume and purchase craft beer.

An interesting aspect of the conceptual model hypothesized relates to consumer territorial identity, support for local breweries [72,73] and the production of local craft beers. Consumers place importance on brewery location and prize environmental sustainability, local sourcing, and local production. These aspects strengthen the sense of place and community. The local craft breweries, in turn, using historical and identifying names and images of the place in their labeling and marketing efforts. This approach supports local economies and strengthens the cultural identities of the communities in which these breweries are located [39,74,75,76]. In this case, reference can be made to consumer culture theory (CCT) [18,61] and value-belief-norms theory (VBN), which examine cultural and social influences on purchasing behavior [63]. This interdisciplinary perspective recognizes the influence of factors such as group and com-munity identity, ethical behavior, and attention to quality and food safety on purchasing choices. The research hypotheses (H5 and H6) sought to capture these growing aspects regarding the consumption and interest in local craft beers by the interviewees [21,74,77]:

Hypothesis 5.

Perceived Quality and taste has a positive and significant influence on consumers’ local identity.

Hypothesis 6.

Consumers’ local identity has a positive influence and stimulates the propensity to consume and purchase craft beer.

In the conceptual model, two research hypotheses (H7 and H8) concern formative constructs that influence the attractiveness and appeal of craft beer. Once the factors influencing the intention to drink craft beer were determined, a PLS-SEM model was developed to explore consumption trends and forecasts. In the external measurement model, the latent variables are exogenous (independent variables). The two constructs—Consumption Habits and Like for craft beer—both have positive and significant effects on the appeal of craft beer. Consumers drink craft beer because they like it, they consume it both at home and away, and they are discerning in their choice and selection of craft beer (lager, ale, etc.). When they like craft beer, they choose it and have a positive attitude toward both local craft beers and those from other areas and countries. Furthermore, they pay attention to the media, they keep themselves informed and follow influencers, they drink or buy craft beer taking into account information on the web relating to positive reviews on craft beers and the phenomenon of craft beers [21,74,77].

The TPB, with its three main components based on attitude, perceived behavioral control, and subjective norms, represents an important reference theory. Among the items of the Like construct, cognitive response theory (CRT) is of particular interest due to the role and influence of advertising, promotional messages, and influencers on consumer persuasion. However, the other theories we have considered in this paper also contribute to identifying research hypotheses 7 and 8:

Hypothesis 7.

Consumption habits have a positive and significant effect on the appeal of craft beer.

Hypothesis 8.

Craft beer appreciation has a positive and significant effect on craft beer appeal.

3. Materials and Methods

3.1. Methodological Approach

In order to identify the factors that influence the propensity to consume craft beer it was used the Partial least squares structural equation modeling (PLS-SEM) [78,79]. In recent years, this analytical methodology has received increased attention by scholars of different fields of research, such as marketing, consumer choice, social sciences, and others [80,81,82]. The rationale lies in the methodology’s ability to evaluate complex measurement models and structural pathways involving numerous variables [31,83].

The model allows for the explanation of multiple statistical relationships simultaneously [84] to understand the relationship between latent constructs, generally indicated by different dimensions, and adopts a confirmatory approach after examining the data with exploratory analyses. SEM provides a single complex model that includes various dependence and independence relationships between the constructs [85]. Using PLS-SEM analysis, it is possible to examine both the measurement model (also called the external model) and the structural model (also called the internal model) [86,87,88]. Scholars [67], thanks to the use of appropriate theories and the application of advanced PLS-SEM models [78,89] can estimate, enrich and examine [78,90] business practices and marketing actions [89,91] offering companies competitive advantages and new marketing tools [92].

The path model (see Figure 1), which represents the hypotheses and relationships between the constructs, was implemented with PLS-SEM analysis includes a structural and a measurement model. The first, also called the internal model, represents the theoretical component that is the first step to identify and represent the path model in terms of direct and indirect effects, as in the case where intermediate constructs are involved. The second is composed of two types of measurement: (i) formative measurement (called mode B, on the left of the model), i.e., the external model of exogenous latent variables, which act as independent variables. The items have unidirectional arrows pointing towards the construct and indicate a sequentially preceding and predictive relationship of the variables placed on the right; (ii) reflective measurement (called mode A, on the right of the model), i.e., the external model of endogenous latent variables, which act as dependent variables. In this case, the items and have unidirectional arrows pointing outwards. In this work both types of measurement were used [93,94].

According to Ringle et al., compared to other analysis models, PLS-SEM requires constant multivariate assumptions, has greater flexibility and is considered better at obtaining predictions [95]. The PLS-SEM analysis software used in this study is SmartPLS4 Version 4.1.1.4. A bootstrap procedure was performed to verify the significance of the paths in the structural model.

3.2. Data Collection and Survey Structure

To identify the factors that determine craft beer preferences and consumption habits in the study areas, the survey used a questionnaire that was administered anonymously online from December 28 to 30 March 2025. Before administration, the questionnaire was tested for validity and comprehensibility. The questionnaire was shared via email, WhatsApp, Instagram, and the Facebook portal. The questionnaire contained several sections and was administered using the snowball sampling method [96]. The choice of this sampling method was driven by the duration and cost of the survey. The questionnaire was pre-tested to ensure clarity and consistency in the wording of the questions [80,81]. Participants agreed to be interviewed and were informed of the guarantee of anonymity and that the data collected would be used for research purposes only and in an aggregate manner.

The research team ensured that, both in developing and administering the questionnaire, it complied with the provisions of the General Data Protection Regulation (GDPR 2016/679) as well as with full compliance with European legislation on personal data protection. Ethical review and approval were waived for this study due to the nature of this research.

The closed-ended questions were prepared based on research and studies in the literature which, as illustrated in

Table 1. Construct, survey question and reference literature.

Construct	Survey Question	Main Reference Literature
PPC	PPC_1 For me, craft beer tastes better than industrial beer PPC_2 For me, craft beer is very good. PPC_3 Buying craft beer is my preference.	[17,29,64]
PC	PC_1 The availability and possibility of purchasing craft beer influences my choices	[17,19,23,24,29,33,70,71]
A	A_1 I’m interested and attracted by the craft beer phenomenon. A_2 Buying and consuming craft beer is in line with my lifestyle. A_3 I buy and consume craft beer because I’m interested in new alternatives and new flavors.	[14,21,24,57,64,69,97]
PQ	PQ_1 When I buy and consume craft beer, I consider the label. PQ_2 When I buy and/or consume craft beer, I pay close attention to safety and quality. PQ_3 When I buy and consume craft beer, I pay close attention to safety and quality.	[19,24,27,29,33,53,70]
TI	TI_1 I like to buy and/or drink craft beer to pair with food. TI_2 I prefer to buy and drink craft beer from my local area. TI_3 I buy and drink craft beer because I want to support local breweries.	[21,45,75,76,77,79,98,99,100,101]
CH	CH_1 I usually drink craft beer when I’m away from home CH_2 I like to drink craft beer at home CH_3 When I drink craft beer, I choose the type CH_4 I drink craft beer because it satisfies me	[19,33,69,76]
L	L_1 I follow craft beer influencers L_2 I have a positive attitude toward local craft beers and/or beers from other areas and countries	[21,45,74,77]

Source: the authors.

, have been useful for measuring consumer tendencies and inclinations regarding the consumption and purchase of craft beer. The questionnaire was structured to collect binary (yes/no) responses, multiple-choice responses, and responses based on a five-point Likert scale (from 1 = strongly in disagreement at 5 = strongly in agreement). The breadth and complexity of the survey instrument used allowed for the collection of a large amount of data and information.

The database was created using SPSS v20 and SmartPLS 4 software, and data loading was carried out with the research objective in mind [43,82,88,102,103,104]. The database, which collects the socioeconomic information and the information related to consumption behavior and choices, comprehends a total of 49 variables. Craft beer consumption is part of a complex decision-making process that also involves curiosity about flavorings and increasingly consumer social media trends. Furthermore, ethical and health concerns also have an importance in the choice, as does the willingness to support local breweries and the local economy [19,29,37,105,106,107,108].

The first section of the questionnaire focused on gathering the respondents’ socioeconomic characteristics (age, gender, occupation, region of origin, income, etc.). The second section comprehended variables relating to the main characteristics of craft beer consumption, such as habits and frequency of consumption, and points of purchase. The third section aimed to gather information on the respondents’ motivations, personal beliefs and on their opinions regarding intrinsic and extrinsic attributes of craft beer. Preferences for certain sensory characteristics (flavor, aroma, color), alcohol content, style and type of beer, and preference for bottled, canned, or draft beer were investigated. Opinions were also asked about the importance attributed to the brand and the producer’s reputation, the potential influence of the provenience of the raw materials, and the consideration of price when purchasing. Specific attention was given to the perceptions, curiosity, interest, and motivations that guide the choice to purchase and consume craft beer. The variables included in the second and third sections of the questionnaire have been identified also thanks to the results of literature retrieval related to the consumption of craft beer.

4. Results

4.1. Descriptive Analysis of the Sample

A total of 366 questionnaires were collected. Three of these were excluded because the respondents did not provide authorization for the use of the data. The consumers who responded to the questionnaire have an average age of 42 years, ranging from 18 to 78 years (Standard Deviation 12.623). The distribution of respondents by age group shows a higher prevalence of those between 40 and 49 years of age, accounting for 31.1% of the total, followed by those between 30 and 39 years of age with 26.7%, and those over 50 years of age with 24.5% of the total (

Table 2. Demographic Profile of the Respondents (n = 363).

	Indication	Freq.	%
Age class	18–29	64	17.6
	30–39	97	26.7
	40–49	113	31.1
	50 or older	89	24.5
Gender	Male	234	64.5
	Female	129	35.5
Education	primary schools	11	3.0
	High School	146	40.2
	3 year university	59	16.3
	Master’s degree	102	28.1
	post degree	45	12.4
Income	not answer/no income	27	7.4
	Up to 15,000 €/year	66	18.2
	15,000–29,000 €/year	157	43.3
	30,000–50,000 €/year	86	23.7
	50,000 €/year or more	27	7.4
Working status	Employed	281	77.4
	Student	36	9.9
	Retired	22	6.1
	Other	24	6.7
No. of family members	I live alone	52	14.3
	2 members	107	29.5
	3 members	80	22.0
	4 members	102	28.1
	5 or more members	22	6.1

Source: the authors.

).

Women represent 35.5% of the total respondents. Regarding educational qualifications, 40.2% of respondents have a high school diploma, 28.1% have a master’s degree, 16.3% have a bachelor’s degree, 12.4% have a postgraduate education, and 3% have a primary school diploma. Regarding income, 43.3% declared an income between €15,000 and €29,000 per year, 23.7% declared an income between €30,000 and €50,000 per year, 18.2% declared an income of less than €15,000 per year, and 7.4% declared an income of more than €50,000 per year. 77.4% of respondents are employed, 9.9% are in education, 6.1% are retired, and 6.7% have other employment. 29.5% of respondents live in a two-person household, 28.1% live in a four-person household, 22% live in a three-person household, 14.3% live alone, and 6.1% live in households with five or more members.

81.5% of respondents stated that they personally purchase beer. The highest consumption is related to draft beer (41.6%), followed by canned beer (26.7%). Only 2.8% prefer bottled beer, while the remaining 28.9% of respondents declare themselves indifferent.

Table 3. Beer consumption habits of the sample interviewed (n. 363).

	n.	%		n.	%
- I drink craft beer more often	187	51.5	- I drink industrial beer more often	105	28.9
Craft beer consumption			Industrial beer consumption
- Never	22	6.1	- Never	83	22.9
- On some occasions	159	43.8	- On some occasions	177	48.8
- Once a week	50	13.8	- Once a week	58	16.0
- 2–3 times a week	66	18.2	- 2–3 times a week	28	7.7
- More than 2–3 times a week	66	18.2	- More than 2–3 times a week	17	4.7
Do you prefer blonde, red, dark, or white beers?			Preferred alcohol content of the beers consumed
- Golden ale	140	38.6	- Low alcohol content (less than 5°)	66	18.2
- Red ale	40	11.0	- 5°	73	20.1
- Stout	36	9.9	- 6–7°	53	14.6
- White	11	3.0	- Over 7°	16	4.4
- Indifferent	136	37.5	- I choose based on the type of beer	155	42.7
Where do you buy beer? (both industrial and craft)			Monthly expenditure declared for the purchase of beer (industrial and/or craft)
- Beer shop only or in combination with other outlets (supermarket and liquor store)	79	21.8	- Around 20 euros	128	35.3
- Online only or in combination with other outlets (beer shop, supermarket, and retailer)	81	22.3	- Between 20 and 40	101	27.8
- Supermarket only	144	39.7	- Between 41 and 60	49	13.5
- Retailer only or in combination with supermarket	30	8.3	- Between 61 and 80 euros	29	8.0
- Liquor store only or in combination with another unspecified outlet	29	8.0	- More than 80 euros	56	15.4

Source: the authors.

shows that 51.5% of survey respondents prefer craft beer; however, 28.9% drink industrial beer more often, while the remaining 20% drink both equally. The questionnaire included questions regarding the frequency of craft and industrial beer consumption. Survey participants are not heavy beer drinkers, only consuming on occasion: 43.8% drink craft beer and 48.8% industrial beer. However, 36.4% of those who consume craft beer drink it more frequently (2–3 times a week or even more).

Regarding one of the most obvious attributes of beer, namely color, the interviewees undoubtedly prefer lagers (38.6%), 37.5% have no preference, 11% prefer reds, 9.9% prefer dark beers, and just 2.8% of respondents prefer white beers. Preferences for alcohol content are more nuanced, less clear because 42.7% say they choose based on whether they consume beer outside the home or purchase it. A significant 38.3% prefer beers with a low alcohol content of around 5% (20.1%) or very low alcohol content, less than 5% (18.2%). Among the latter, according to current trends, many presumably drink non-alcoholic beer. Beers with a stronger alcohol content, 6–7° or more than 7°, are preferred by 19% of survey participants.

When they buy beer, they mainly go to the supermarket (39.7%), and it is interesting to note that 22.3% of the survey participants buy online, in some cases in combination with other points of sale. A segment of consumers (21.8%) prefer beer shops that offer a greater variety/range of choice; in this case too, consumers orient themselves by purchasing at multiple points of sale.

A total of 8.3% turn to the retailer who also buys at the supermarket and at other points of sale. 8% indicate a Liquor store or an “other point of sale” not indicated. As for the average declared expenditure for the purchase of beer, both industrial and craft, 35.3% declare that they spend around twenty euros per month, which reaches forty euros for 27.8%. The remaining 37% gradually increase their expenditure on the purchase of beer, until reaching 15.4% who are willing to spend more than 80 euros per month.

4.2. Path Modeling Results, Validation, and Evaluation of PLS-SEM Applied to Craft Beer in Italy

In this article, the variables associated with the motivations, choices, and opinions of the interviewed individuals were used to build a variance-based PLS-SEM model. Figure 2 below highlights the hypothesized path: the measurement model (also called the outer model) includes: (i) two exogenous latent variables, the constructs “Like” and “Consumption Habit,” modeled as formative measures, i.e., constructs that explain other constructs in the model; (ii) four endogenous latent variables, the constructs “Appeal,” “Perceived Quality,” “Territorial Identity,” and “Propensity to Purchase and Consume”.

These constructs are modeled as reflective measurements, i.e., those constructs that are explained in the model and in which the relationship goes from the construct to the item; (iii) the “Purchasing Capability” construct is a single item, and the relationship is directionless. The single item measures income, which serves as a control variable for its explanatory value. We included this despite being aware of the limitations of single-item measures [109].

As can be seen from

Table 4. Construct Measurement Type, constructs and items, standardized variable loadings, KMO Test, Mean, Std. deviation and Collinearity Statistics (VIF).

Measurement		Constructs and Items	Standardized Variable Loadings	Kaiser–Meyer-Olkin KMO	Mean	Std. Deviation	VIF
Reflective		Appeal (A)
	A_1	I drink craft beer because I’m interested and attracted by the craft beer phenomenon.	0.847	0.911	2.826	1.492	2.098
	A_2	Drinking craft beer is in line with my lifestyle.	0.906	0.930	2.972	1.431	2.483
	A_3	When I drink craft beer, I like to experiment with new flavors.	0.825	0.936	3.672	1.249	1.600
Reflective		Purchasing Capability (PC)
	PC	My income and the price of craft beer influence my choices.	1.000	0.785	3.063	1.009	1.000
Reflective		Propensity to Purchase and Consume (PPC)
	PPC_1	For me, craft beer tastes better than industrial beer.	0.874	0.942	3.152	1.413	2.081
	PPC_2	For me, craft beer is very good.	0.895	0.931	3.835	1.317	1.974
	PPC_3	Buying craft beer is a habit of mine.	0.822	0.938	3.934	1.111	1.779
Reflective		Perceived Quality and Taste (PQ)
	PQ_1	When I buy and consume craft beer, I consider the label.	0.800	0.856	3.179	1.400	1.618
	PQ_2	When I buy and consume craft beer, I pay close attention to quality and taste.	0.904	0.888	3.554	1.215	1.957
	PQ_3	I’m interested in learning about craft beer production technology.	0.809	0.881	3.132	1.283	1.599
Reflective		Territorial Identity (TI)
	TI_1	I enjoy purchasing and/or consuming craft beer to pair with food.	0.817	0.940	2.983	1.273	1.429
	TI_2	I prefer purchasing and consuming local craft beer.	0.741	0.871	3.011	1.251	1.462
	TI_3	I purchase and consume craft beer because I want to support local breweries.	0.873	0.926	3.146	1.321	1.694
Formative		Consumption Habits (CH)
	CH_1	I usually drink craft beer when I’m away from home.	0.736	0.926	2.559	1.103	1.940
	CH_2	I like to drink craft beer at home.	0.710	0.927	2.592	1.057	1.920
	CH_3	When I drink craft beer, I choose the type.	0.822	0.940	3.780	1.227	1.245
	CH_4	I drink craft beer because it satisfies me.	0.789	0.889	2.986	1.261	2.896
Formative		Like (L)
	L_1	I follow craft beer influencers	0.864	0.931	3.317	1.280	1.092
	L_2	I have a positive attitude toward craft beers, both local and from other areas and countries.	0.734	0.972	2.163	1.298	1.092

Source: the authors.

, in our case study the external saturations are between 0.710 (I like drinking craft beer at home) and 0.906 (I buy and consume craft beer because it is in line with my lifestyle). Furthermore, the standardized loadings of all items are valid (equal to or greater than 0.6) [69,88].

The table also shows the statistics relating to the principal components analysis (PCA) with the Kaiser-Meyer-Olkin KMO index, which records high and valid values for all indicators. The means, standard deviation, and VIF for all constructs are also highlighted.

Table 5. Testing Composite Reliability, Convergent Validity, and Discriminant Validity.

Indication	A	PQ	PPC	PC	TI
Construct reliability and validity
Cronbach’s Alpha	0.823	0.790	0.832		0.745
Composite Reliability (rho_a)	0.828	0.827	0.859		0.775
Composite Reliability (rho_c)	0.895	0.876	0.898		0.853
Average Variance Extracted (AVE)	0.739	0.703	0.747		0.660
Discriminant validity—Heterotrait—Monotrait HTMT
Appeal (A)
Perceived Quality_ (PQ)	0.600
Propensity of Purchase and Consume (PPC)	0.892	0.503
Purchasing Capability (PC)	0.156	0.037	0.229
Territorial Identity (TI)	0.868	0.619	0.711	0.139

Source: the authors.

collects the measurements related to the reliability and validity of the construct and to the discriminant validity of the model which is examined with the Hetero-trait-Monotrait (HTMT) correlation ratio as also recently suggested by Sarstedt [93]. For the Composite Reliability (rho_a and rho_c) the recommended value of 0.7 has been exceeded [110,111,112]. Regarding the AVE value, the indicated constructs are above the threshold considered acceptable (≥0.50).

As suggested by Franke and Sarstedt (2019) the HTMT correlation ratio was used to examine the discriminant validity: the authors recommend values equal to or lower than ≤0.90 [113,114]. Our work on craft beer shows, based on the interviewees’ answers, valid values that are significantly lower than 1 except in two cases which, although valid, are close to the limit value: PPC <-> A (0.892) and TI <-> A (0.868). “As for the coefficient of determination” R2, in the PLS-SEM approach it is calculated for each dependent variable in the model, providing a measure for each of them.

With reference to the R² values, they are considered as follows: “substantial ≥ 0.75”, “moderate 0.50–0.74” and “weak 0.25–0.49” [115]. In our case, the “Purchasing Capability” (PC) construct, which is made up of a single indicator, has a value considered weak; however, it does not affect the validation results of the model (

Table 6. Coefficients of determination.

	R2	Q2 Predict *
Appeal (A)	0.561	0.550
Perceived Quality (PQ)	0.245	0.198
Propensity Purchase and Consume (PPC)	0.587	0.588
Purchasing and Consumption (PC)	0.021	0.039
Territorial Identity (TI)	0.246	0.170

* Result Q² predict—procedure PLS predicting CVPAT (SmartPLS4 version 4.1.1.4.). Source: the authors.

). In the book by Hair et al., hey specifically emphasize that R2 is not indicative of the model’s predictive power [79]. We therefore examined the Q2 test for this purpose, obtained using the blindfolding procedure (PLSpredict CVPAT), which provides cross-validated predictive power. Q² predict values are valid when they are greater than zero (0.000). A Q² predict greater than zero indicates significant predictive relevance. As can be seen from Table 6, in this study, all Q2 predict values are valid.

Table 7. The f² value and the internal model collinearity statistics.

	f2	VIF
Appeal (A) -> Perceived Quality and Taste (PQ)	0.324	1.000
Appeal (A) -> Propensity to Purchase and Consume (PPC)	0.531	1.975
Appeal (A) -> Purchasing Capability (PC)	0.021	1.000
Consumption Habits (CH) -> Appeal (A)	0.196	1.807
Like (L) -> Appeal (A)	0.229	1.807
Perceived Quality and Taste (PQ) -> Territorial Identity (TI)	0.326	1.000
Purchasing Capability (PC) -> Propensity to Purchase and Consume (PPC)	0.024	1.023
Territorial Identity (TI) -> Propensity to Purchase and Consume (PPC)	0.017	1.969

Source: the authors.

highlights the collinearity statistics and f² values. To check for collinearity, we used the variance inflation factor (VIF indicator): the values are all valid and between 1.000 and 1.975, in fact, as indicated by Hair et al. (2017) [115] multicollinearity is considered valid when the value is lower than the threshold value of five and higher than the minimum tolerance level of 0.20. Also in this case, the statistics found with reference to collinearity are valid and range from 1000 to 2896. As for the f² values, according to Cohen (1998) [116], the following value are used to evaluate it: 0.02–0.14 is a small effect; 0.15–0.34 is a medium effect; > 0.35 is a large effect. As reported below, one path recorded a large effect, four paths recorded medium effects and three paths had small f² effects.

(i) The path “A -> PPC” has a large f² effect (0.531); (ii) the paths “PQ -> TI” (0.326), “A -> PQ” (0.324); “L -> A” (0.229) and “CH -> A” (0.196) have medium f² values; (iii). The remaining three paths record small values with f² equal to: “PC -> PPC” (0.024); A -> PC” (0.021) and “TI -> PPC” (0.017).

Table 8. Correlation of latent variables.

	A	CH	L	PQ	PPC	PC	TI
Appeal (A)	1.000
Consumption Habits (CH)	0.679	1.000
Like (L)	0.689	0.668	1.000
Perceived Quality (PQ)	0.495	0.439	0.402	1.000
Propensity to Purchase and Consume (PPC)	0.755	0.826	0.687	0.429	1.000
Purchasing Capability (PC)	0.144	0.260	0.192	0.037	0.211	1.000
Territorial Identity (TI)	0.701	0.501	0.527	0.496	0.592	0.134	1.000

Source: the authors.

provides information on the correlation of the latent variables. It shows the degree of association between the latent variables examined and the tendency of their values to vary together. As can be seen, the latent factor PC shows a weaker correlation with the other latent factors.

PLS-SEM is a randomized predictive method. Among the goodness-of-fit indices, Schuberth et al. (2023) [117] argue that the standardized root mean square residual (SRMR) should also be included to examine the method. SRMR values should not exceed 0.08 [94]. In our elaboration, the SRMR index calculated with PLS-SEM is valid (equal to 0.074) [117].

The North Fit Index (NFI) was evaluated, which estimates the proportion of variance contributed by the expected population covariance. This index ranges from 0 to 1, and the widely recommended threshold is usually 0.90. In our example, NFI has a valid value of 0.777. PLS-SEM is a random prediction method.

Schuberth et al. (2023) argued that the standardized root mean square residual (SRMR) should also be included to examine the method [117]. SRMR values must not exceed 0.08. In our analysis, the SRMR index (equal to 0.074) was also valid.

Furthermore. d__ULS index (i.e., the squared Euclidean distance) and d__G index (the geodesic distance) indicate a good fit of the model (equal to 1.040 and 0.451, respectively).

Structural equation modeling with partial least squares methods (PLS-SEM) uses sample bootstrapping to calculate the significance of model parameter estimates (e.g., path coefficients) [118]. From the perspective of explanatory statistical modeling, hypothesis testing is a fundamental element for developing relevant and rigorous theory [119].

The research hypothesis testing was based on bootstrapping. This procedure creates subsamples with observations randomly drawn from the original dataset (with replacement). As indicated by Ringle et al. (2022) [95] and Hair et al. (2022) [120] who illustrate bootstrapping in PLS-SEM in detail, the subsample is used to estimate the PLS path model.

This process is repeated until a large number of random subsamples are created. As suggested by Sarstedt et al., 2022 [94], the following specifications were used in our work: full bootstrapping, percentile bootstrapping, 10,000 samples, and two-tailed (p = 0.05). The parameter estimates obtained from the subsamples are used to derive 95% confidence intervals for significance tests [121]. Thus, through bootstrapping, the t-value is obtained to evaluate and highlight the path coefficients, and the p-value is used to assess the significance of each estimate. The t-value is used to test the null hypothesis. A high t-value suggests strong evidence against the null hypothesis, indicating a statistically significant relationship.

Specific guidelines [122] have also been considered for determining standardized path coefficients (β), including indirect and specific indirect effects (so-called mediation paths), applied using the bootstrapping technique. The pathways leading to the interest and propensity expressed by interviewed consumers for the purchase and consumption of craft beer in Italy were evaluated according to the following values: β between 0.01–0.08 indicates a small effect; between 0.09–0.24 the effect is considered medium; while a value greater than or equal to 0.25 is a large effect.

The path coefficients (β) presented in

Table 9. Summary of the results of the significance test of the model path coefficients.

Path Coefficients	Hypothesis	β	Stdev.	t-Values	p-Values	97.5% Confidence Intervals	Are the Hypotheses Supported?
A -> PPC	H1	0.658	0.050	13.284	0.000	[0.559; 0.753]	YES
A -> PC	H2	0.145	0.049	2.922	0.003	[0.045; 0.236]	YES
A -> PQ	H3	0.497	0.044	11.316	0.000	[0.403; 0.575]	YES
PC -> PPC	H4	0.101	0.033	3.061	0.002	[0.036; 0.166]	YES
PQ -> TI	H5	0.498	0.044	11.346	0.000	[0.399; 0.574]	YES
TI -> PPC	H6	0.118	0.052	2.275	0.023	[0.015; 0.216]	YES
CH -> A	H7	0.401	0.049	7.993	0.000	[0.290; 0.484]	YES
L -> A	H8	0.423	0.049	8.724	0.000	[0.332; 0.522]	YES

Source: the authors.

provide a summary of the path coefficient estimates, t-values, p-values, and confidence intervals, while

Table 10. Hypothesis testing results: final result and total effects.

Total Effects	Hypothesis	β	Stdev.	t-Values	p-Values *	97.5% Confidence Intervals	Are the Hypotheses Supported?
A -> PC	H2	0.145	0.049	2.922	0.003	[0.048; 0.239]	YES
A -> PPC	H1	0.702	0.038	18.573	0.000	[0.627; 0.776]	YES
A -> PQ	H3	0.497	0.044	11.316	0.000	[0.410; 0.580]	YES
A -> TI	H3 -> H5	0.249	0.040	6.152	0.000	[0.172; 0.329]	YES
CH -> A	H7	0.401	0.049	7.993	0.000	[0.304; 0.497]	YES
CH -> PC	H7 -> H2	0.058	0.021	2.647	0.008	[0.019; 0.101]	YES
CH -> PPC	H7 -> H1	0.282	0.042	6.560	0.000	[0.202; 0.366]	YES
CH -> PQ	H7 -> H3	0.200	0.032	6.182	0.000	[0.141; 0.263]	YES
CH -> TI	H7 -> H3 -> H5	0.100	0.021	4.531	0.000	[0.062; 0.145]	YES
L -> A	H8	0.423	0.049	8.724	0.000	[0.326; 0.517]	YES
L -> PC	H8 -> H2	0.061	0.022	2.739	0.006	[0.020; 0.107]	YES
L -> PPC	H8 -> H1	0.297	0.037	8.150	0.000	[0.227; 0.370]	YES
L -> PQ	H8 -> H3	0.210	0.031	6.895	0.000	[0.153; 0.272]	YES
L -> TI	H8 -> H3 -> H5	0.105	0.021	5.057	0.000	[0.068; 0.149]	YES
PC -> PPC	H4	0.101	0.033	3.061	0.002	[0.037; 0.167]	YES
PQ -> PPC	H5 -> H6	0.059	0.027	2.165	0.030	[0.008; 0.113]	YES
PQ -> TI	H5	0.498	0.044	11.346	0.000	[0.408; 0.581]	YES
TI -> PPC	H6	0.118	0.052	2.275	0.023	[0.016; 0.218]	YES

(*) For significance testing, we refer to bootstrap confidence intervals. Significance p-value < 0.05. Source: the authors.

provides an overview of the final results and allows for an examination of the total bootstrapping effects. As can be seen, the results of these total effects of the exogenous constructs Like (L) and Consumption Habits (CH) on the endogenous constructs Appeal (A), Perceived Quality (PQ), Territorial Identity (TI), Purchasing Capability (PC), and Propensity to Purchase and Consume (PPC) are all valid and significant, and the hypothesized paths are confirmed. The indirect effects and specific indirect effects have 97% confidence intervals that do not include zero, are all significant (

Table A1. Indirect total effect.

	Hypothesis	β	SD	t-Value	p-Value	Confidence Intervals
						2.5%	97.5%
A -> PPC	H1	0.044	0.016	2.666	0.008	0.014	0.077
A -> TI	H3 -> H5	0.249	0.040	6.152	0.000	0.172	0.329
CH -> PC	H7 -> H2	0.058	0.021	2.647	0.008	0.019	0.101
CH -> PPC	H7 -> H1	0.282	0.042	6.560	0.000	0.202	0.366
CH -> PQ	H7 -> H3	0.200	0.032	6.182	0.000	0.141	0.263
CH -> TI	H7 -> H3 -> H5	0.100	0.021	4.531	0.000	0.062	0.145
L -> PC	H8 -> H2	0.061	0.022	2.739	0.006	0.020	0.107
L -> PPC	H8 -> H1	0.297	0.037	8.150	0.000	0.227	0.370
L -> PQ	H8 -> H3	0.210	0.031	6.895	0.000	0.153	0.272
L -> TI	H8 -> H3 -> H5	0.105	0.021	5.057	0.000	0.068	0.149
PQ -> PPC	H5 -> H6	0.059	0.027	2.165	0.030	0.008	0.113

and

Table A2. Indirect specific effects.

	Hypothesis	β	SD	t-Value	p-Value	Confidence Intervals
						2.5%	97.5%
A -> PC -> PPC	H2 -> H4	0.015	0.007	2.104	0.035	0.003	0.030
A -> PQ -> TI	H3 -> H5	0.249	0.040	6.152	0.000	0.172	0.329
CH -> A -> PQ -> TI -> PPC	H7 -> H3 -> H5 -> H6	0.012	0.006	1.990	0.047	0.002	0.024
PQ -> TI -> PPC	H5 -> H6	0.059	0.027	2.165	0.030	0.008	0.113
CH -> A -> PC	H7 -> H2	0.058	0.021	2.647	0.008	0.019	0.101
CH -> A -> PPC	H7 -> H1	0.264	0.042	6.106	0.000	0.185	0.351
L -> A -> PC	H8 -> H2	0.061	0.022	2.739	0.006	0.020	0.107
CH -> A -> PQ	H7 -> H3	0.200	0.032	6.182	0.000	0.141	0.263
L -> A -> PPC	H8 -> H1	0.278	0.037	7.566	0.000	0.208	0.353
L -> A -> PQ	H8 -> H3	0.210	0.031	6.895	0.000	0.153	0.272
A -> PQ -> TI -> PPC	H3 -> H5 -> H6	0.029	0.014	2.060	0.039	0.004	0.059
CH -> A -> PC -> PPC	H7 -> H2 -> H4	0.006	0.003	1.962	0.050	0.001	0.012
CH -> A -> PQ -> TI	H7 -> H3 -> H5	0.100	0.021	4.531	0.000	0.062	0.145
L -> A -> PC -> PPC	H8 -> H2 -> H4	0.006	0.003	2.065	0.039	0.001	0.013
L -> A -> PQ -> TI	H8 -> H3 -> H5	0.105	0.021	5.057	0.000	0.068	0.149
L -> A -> PQ -> TI -> PPC	H8 -> H3 -> H5 -> H6	0.012	0.006	1.974	0.048	0.002	0.026

in the Appendix A), and represent complementary mediators of the various relationships.

In particular, the final results that highlight paths with a larger effect (β) and a higher t-value are the following (Table 10):

-

H1, where Appeal exerts a marked and significant effect on the propensity to purchase and consume craft beer. In the final results, the total effect of the β coefficient increases from 0.658 to 0.702, as does the t-value, which increases from 13.284 to 18.573.

-

H5, where Perceived Quality exerts a marked and significant effect on Territorial Identity, β = 0.498 and t-value = 11.346, with no mediation effects.

-

H3, where Appeal exerts a significant effect on Perceived Quality (β = 0.497 and t-value = 11.316).

-

Paths H8 (β = 0.423 and t-value = 8.724) and H7 (β = 0.401 and t-value = 7.993), i.e., Like and Consumption Habits, are followed by the Appeal of Craft Beer.

-

Consumption habits lead to two valid and significant paths: one path leading to the propensity to consume and purchase craft beer, mediated by the Appeal construct (CH -> A -> PPC) (β = 0.282, t-value = 6.560); and another path leading, again mediated by the Appeal construct, to Perceived Quality (CH -> A -> PQ), where β = 0.200 and t-value = 6.182.

-

Finally, two paths are highlighted: the first, A -> PQ -> TI (β = 0.249 t-value = 6.152), where the appeal of craft beer is mediated by consumers’ emphasis on perceived quality; the second, L -> A -> PQ -> TI (β = 0.105 t-value = 5.057), in this case mediated by the Like construct, through the mediation of Appeal and Perceived Quality, highlights consumers’ appreciation for the territorial identity and local products.

-

The remaining paths, while valid and significant, appear less impactful, with t-values ranging from 4.531 to 2.165.

Ultimately, the results highlight the role of craft beer appeal, which, in addition to exerting an important direct effect that underlies interest in craft beer, plays a complementary mediating role for both perceived quality and territorial identity.

Therefore, part of the effects of perceived quality and territorial identity on the propensity to consume and purchase craft beer is attributable on the appeal the product arouses in the consumer.

5. Discussion

Among the various actors involved in the craft beer supply chain and market, this article focuses on consumers. The study aims to understand their perspective on purchase and consumption intentions and analyzes the factors that influence this propensity [19,23,33,70]. Understanding consumer behavior is useful for identifying market trends and developments and for supporting producers in formulating effective and appropriate marketing strategies.

The model applied in the research aims to identify motivations and pathways that lead to the propensity to purchase and consume craft beer. The predictive analysis identifies the constructs and pathways that lead to varying degrees, to this propensity to purchase.

In particular, the research confirms and reinforces the results conducted in Italy and Europe by various authors; for example, Carbone and Qinci found that people interested in craft beer have a higher willingness to pay (WTP) and willingness to buy (WTB) compared to industrial beer [23].

According to Donadini et al., Italians appear to be less sensitive to a “price effect” and are less concerned about paying a premium for craft beers [34]. Gomez et al. in their studies in Mexico, point out that the craft beer experience can be a private or social occasion: price and availability tend to isolate consumers who do not share the experience, or at most, share it with a small circle of friends [33].

The theoretical and methodological choices adopted in this study are based on exploring the key factors that influence craft beer selection decisions in Italy. Specifically, an online survey of 363 consumers examined the propensity to purchase and consume, interest in craft beer and its production region, the importance attributed to quality, taste, and aroma, socio-cultural influences, and preferences expressed by the consumers interviewed.

The PLS-SEM methodology used, because it allows for the simultaneous explanation of multiple statistical relationships, allows us to explore and correlate multiple key factors that contribute to consumer orientation in their consumption choices. The analyses carried out with this methodology show that purchasing and consumption decisions are linked to a variety of factors, some strictly conjoined to beer, for example flavor, appearance, and quality, while others relate to the consumers’ personal sphere, such as socio-cultural influences, lifestyle, and attention to health aspects. This is perfectly in line with what emerged from the literature analysis [47,48,67]. For example, gender differences, as highlighted in the paper by Rivaroli et al., have a marginal impact on craft beer consumption behavior, both in Italy and Germany [18]. Gomez-Corona in Mexico also reached the same conclusion [22]. It should also be noted that the beer industry is going through a difficult period in Italy and other European markets, such as Germany, because industrial beer consumption has declined, partly due to increased consumer interest in non-alcoholic or low-alcohol beverages. Therefore, producers have begun to adapt their marketing strategies. This also applies to the craft beer sector, which, despite showing potential for growth due to its originality and consumer appreciation, is nevertheless affected by new trends resulting from the increase in non-alcoholic beer consumption. This phenomenon is developing within the context of a general reduction in alcohol consumption. These aspects have been examined in the work of Baiano 2021 [11] who also highlight a transversal preference in terms of consumer age: for the elderly, it is associated with health risk profiles and for young people to align with new fashions and consumer trends. Furthermore, consumers often pursue specific product attributes such as provenance and sustainability to satisfy broader lifestyle values. Therefore, understanding the evaluative criteria consumers use when making craft beer purchasing and consumption choices is crucial for a comprehensive understanding of market dynamics [83,89].

In particular, the results of the PLS-SEM structural equation analysis model highlighted the main drivers influencing attitudes and propensities toward craft beer. PLS-SEM analysis methodology has been widely used in recent studies on food and beverage consumption intentions and preferences. In this context, we believe our research represents an original study in the craft beer sector and contributes to research and to the analysis of indicators and constructs useful to predict consumption and current trends in Italy.

In our study, we drew on various consumer economic theories to ascertain and empirically try out the factors that affect preferences, choices, motivations, intentions, and propensity toward craft beer. Different attributes and motivations influence attitudes: craft beer is considered good and tasty, and superior to industrial beer [33]; it is enjoyed and enjoyed, both at home and away from home [19,33,34]. Consumers have a positive attitude towards craft beers both local and from other areas and countries [24,98]. Furthermore, craft beers have a fascinating and appealing effect on consumers, attracting them with their novelty and being in line with their lifestyle. The results suggest that consumers are informed and attentive to labels, expiration dates [53], and provenance, and are loyal to their preferred beer style. These findings are consistent with recent studies analyzing craft beer in Italy and other European and non-European countries, as also highlighted in the comprehensive and interesting review by Hernandez-Mora et al. [38].

The survey examined reflective and formative constructs that provide a useful background for studying respondents’ consumption experience. The former relate to appeal, perceived quality, connection to the local area, and the ability and propensity to purchase and consume craft beer. As for the formative constructs, they consider satisfaction with and appreciation for craft beer. Data processing through PLS-SEM modeling highlighted how hypothesis H1 (A -> PPC t-value 18.573 and f² 0.531) represents the main predictor of the propensity to consume and purchase craft beer. The Appeal construct is connected to the items on new flavors, interest in the craft beer phenomenon, and the importance of the consumer’s lifestyle. This result confirms the recent findings of Cela et al., which highlight how sensory characteristics such as taste, body, aromas, and color are important in shaping consumer preferences and acceptance [98]. The appeal of craft beer is tied to the product itself. Consumers find aromas, scents, and flavor nuances in the beverage, making one craft beer unique and unique, and changing from time to time. The presence of active yeasts allows the beer and its flavor to evolve over time, giving it an ever-changing flavor [123]. Craft beer is a surprise of taste that pushes the consumer to be attracted by a complexity of aspects.

From a theoretical perspective, the importance of the indicators that constitute the Appeal construct can be traced back to various theories, such as experiential marketing theory [30] and trait activation theory (TAT) [51,52]), which are oriented towards experience, emotional connection and personality. Among the items of the Appeal construct, the one on the “pleasure of experimenting with new flavours” draws on the theory of acceptance of new foods and beverages (NFB), which explores the dynamics between consumers and new food experiences [57], just as the items regarding “interest in craft beer” and “lifestyle” relate to the theory of consumer culture/Consumer Culture Theory (CCT), where the importance of cultural and social contexts is particularly highlighted [14,18].

Particularly interesting and in line with our results is the article by Wiśniewska et al., which underlines the importance of integrating different economic theories to discover the predictive role of the cognitive (awareness and knowledge) and affective (emotions and concern) components of the Value-Believes-Norms theory (VBN) [63].

Our study also highlights an interest in consumers’ perceived quality, which involves the paths of hypotheses H5 (PQ -> TI) and H3 (A -> PQ). In the first case, perceived quality has a positive and significant influence on territorial identity (t-value 11.346 and f² 0.326), and in the second hypothesis, for consumers, the appeal of craft beer also matters with reference to perceived quality (t-value 11.316 and f² 0.324). Indeed, consumers attribute greater authenticity and higher overall quality to craft beer, both of the product and of the production chain, as widely highlighted in the literature [21,24,108].

The indicators considered in the QP construct are: consumers’ attention to labels and expiration dates, their interest in learning about production technology, and the importance they attach to quality and taste. These items foster a connection with their local area and promote a specific preference for local craft beer. Consumers pay attention to quality, taste, specific information on the label, the type of craft beer, the brand, the producer, etc., while also demonstrating curiosity and interest in production technology.

Our findings on PQ information confirm previous and current studies that emphasize the importance of “perceived quality” in the predictive capacity of the model. These aspects emerge, for example, from the work of Grunert et al. and Staples, who report consumer interest in information on the ingredients and nutritional characteristics of alcoholic beverages, which, in the EU, are not currently available on alcoholic beverage labels [123,124,125]. As for the theoretical approach relating to the factors that influence perceived quality, they refer to theories that integrate that of planned behavior (TPB), as occurs, for example, in the work of Pang et al. who use the Protection Motivation Theory (PMT) when purchasing organic foods [53]. The health belief model (HBM) is applied in the original contribution by Maleknia who examines, in an urban forest context, the behaviors of citizens concerned about perceived health risks deriving from air pollution [55].

In our work, the H5 path (PQ -> TI) leads to territorial identity also involving the theoretical approach of “consumer culture”/Consumer Culture Theory (CCT) where consumption is deeply linked to the social and cultural context of the individual and contributes to creating and maintaining shared meanings and values within a territory. The results obtained are in line with what emerged from the literature analysis, in the specific case, with what was stated, for example, by Weber et al. (2018) when they note that food and drinks allow consumers to emphasize local culture instead of a homogeneous national culture [61]. In particular, craft breweries highlight local identities and peculiarities, clarify the sense of place to the consumer, constituting an ideal link between products and territories [61]. In the literature, the contribution of craft beers to the recognition of territorial identity is often highlighted, in the sense that the evolution of craft breweries has marked a clear trend toward strengthening the link between territory and beer. Furthermore, the choice of several microbreweries to link their product to the territory in which they operate leads to the recognition of beer within a context in which it is no longer just an “agricultural” product but also a “cultural” one [72,108].

The path relating to the formative construct of hypothesis H7 is valid and significant (CH -> A: β = 0.401; f² = 0.196). In it, consumption habits relate to the pleasure and satisfaction of drinking craft beer both at home and away from home. Furthermore, consumers declare that they choose the type and style of their favorite craft beer clearly and precisely. This relationship between consumption habits and Appeal is consistent with Self-Determination Theory (SDT). Widely used in marketing studies, this theory considers consistency in behavior to explain and predict purchasing choices and motivations. Moreover, this appears to be in line with a large number of articles in the literature that note the high appreciation of craft beers by consumers who are significantly attracted by their flavor, originality, consistency, aromas, and even foam and density [21].

In hypothesis H8 (L -> A where β = 0.423 and f² = 0.229), the formative construct Like is connected to the role of information and appreciation for craft beer, both local and from other areas or countries. Consumers appreciate craft beer, research it on specialized sites, follow influencers, reviews, etc. The path is valid and significant, and the relationship between likes and appeal can be linked to cognitive response theory (CRT) due to the role played by information via the internet, advertising, and human and virtual influencers who play an important role in persuading people to consume a product. An interesting cosmopolitan consumer also emerges who appreciates the cultural and traditional differences in craft beer production, is open to new experiences and flavors, and generally seeks out different cultural experiences, including foods and drinks from around the world.

However, another significant result concerns hypothesis H6, which, while valid, nevertheless records low significance. The TI -> PPC path is the one relating to the importance of territorial identity on the consumption and purchase of craft beer, which reveals limited purchase and consumption, despite the survey participants having expressed interest in craft beers from their area and declaring their intention to ensure support for local breweries. This result likely reflects the poor availability of local craft beers due to the limited production and insufficient marketing capacity of small local breweries.

The other paths, H2 and H4, are valid and significant, but are less powerful. This confirms that the appeal of craft beer still positively influence consumers’ purchasing power (H2), just as purchasing power has a weak but positive and considerable influence on the inclination to consume and purchase craft beer (H4).

6. Conclusions

This study explores consumer preferences for craft beer consumption in a sample of consumers distributed across the Italian peninsula, where the tradition of craft beer production and consumption, while rapidly expanding, is certainly less deeply rooted than in other areas of Northern Europe.

The study explored the main factors influencing craft beer consumer choices in Italy, highlighting how these choices are connected to multiple factors incorporated into the PSL-SEM model as endogenous and exogenous factors. The methodology used has advantages and disadvantages. Among the main advantages is its flexibility, which allows for the analysis of complex relationships between variables and, in particular, the ability to measure multidimensional phenomena that are not directly observable, as well as the relationships generated between them. The methodology can also be used to make accurate predictions about the outcomes of interest. Among the disadvantages is the complexity of the methodology, which requires the use of essential indicators for the validation and interpretation of the results obtained, which must be carefully carried out.

The results are consistent with several other studies conducted in other consumption regions, but they also highlight unique characteristics. Craft beer continues to be a highly attractive product for various types of consumers. The product, despite being alcoholic, increasingly reflects and incorporates elements of social ethics and connection to the territory and local development, overcoming concerns about alcohol. The results highlighted interesting consumption characteristics, albeit specific to the sample studied.

The study also highlighted different drinking styles among the consumers surveyed. An interesting study would be to compare the behavior of Italian consumers with that of consumers in other European regions, such as the Nordic countries, where craft beer has a stronger tradition. This could help determine whether the drinking styles highlighted in this study differ from those prevalent in other European regions. The study revealed a greater preference for lower-alcohol beers. A future study should also consider consumer demand for non-alcoholic beers, especially in high-income countries. This new trend adds to the trend of substituting safe and sustainable foods, which, in the case of alcoholic beverages, is largely driven by the desire for a healthier lifestyle.

Limits of our study suggest to move toward future research. First, the study data were collected online and used snowball sampling. The results in fact cannot be united beyond the characteristics of the sample which, although adequate for the size indicated by several authors, is not representative of the population as a whole. Furthermore, the issue of online participation should be observed, because interviewed subjects were free to answer to the survey, so mainly respondent that know the topic (both positively and negatively) participated. Therefore, future surveys with a larger number of respondents from different demographics and locations could help improve the understanding of craft beer consumption behavior and, consequently, enhance the results. A study with a larger sample size would be useful to assess whether the results achieved are also robust under this additional hypothesis. A future study should also take into account the current consumer demand for non-alcoholic beers, especially in high-income countries. This new trend adds to that of safe and sustainable foods, largely driven by the desire for a healthier lifestyle.

As for future studies, in addition to consumer research, it could be useful to better understand the industry by analyzing the production system, including those businesses that, born from a passion for beer and the processing of raw materials, have subsequently transformed into entrepreneurial ventures. This could highlight the unique characteristics of a constantly evolving industry, even in Italy.