Influences of background factors on consumers’ purchase intention in China’s organic food market: Assessing moderating role of word-of-mouth (WOM)

Abstract

The present study aims to clarify how background factors influence consumers’ intention of purchasing organic food from individual, social, and information perspectives (i.e., health consciousness, self-perceived vegetarian, as well as labeling). Another aim is to explore the moderating role of word-of-mouth (WOM) in relationship between purchase intention and purchase decision to fill in the intention-behavior gap in the field of behavior of purchasing organic food. The data were acquired through purposive sampling method by distributing questionnaires among organic food consumers. 280 out of 306 questionnaires were valid to proceed to statistical analysis. All proposed hypotheses were verified through structural equation modeling (SEM) and SPSS PROCESS regression analysis. As suggested from the study results, except for hedonistic motivation factor, the other background factors (i.e., individual, social, and information) significantly impacted consumers’ purchase intention. Moreover, the relationship between purchase intention and purchase decision was significantly moderated by word-of-mouth (WOM). The present study sheds light on how to motivate consumers’ purchase intention by stressing vital background factors from individual (i.e., purchase attitude and health consciousness), social (i.e., self-perceived vegetarian and environmental concern), and information perspectives (i.e., labeling and social media information). Besides, a novel insight is presented for marketers on how to deepen the relationship between consumers’ purchase intention and purchase decision via the moderating effect of word-of-mouth (WOM).

Keywords:

• organic food
• background factors
• purchase intention
• purchase decision
• word-of-mouth (WOM)
• consumers in China

PUBLIC INTEREST STATEMENT

In recent 5 years, organic food market expanded so fast in developed cities of China, it is noticed that organic food are available not only in organic specialty stores but almost in each supermarket. Consequently, more and more Chinese consumers started being enthusiastic about purchasing organic food, especially for people who have strong awareness of health and food safety concerns. However, very limited study explores influencing factors that drive consumers purchase intention towards organic food by a systematic way in study background of China. Thus, this study each influencing factor is categorized into different background factors from perspectives of individual, social, and information, which can give a relatively clear and systematic study regarding to consumers organic food purchase behavior. Moreover, this study also provides insights into how to motivate consumers purchase decision towards organic food by incorporating moderating effect of WOM.

1. Introduction

As people’s living standards are being elevated, considerable consumers start to be enthusiastic about purchasing organic food for themselves, as well as for their families’ long-term health (Rana & Paul, 2017). Given the development of organic food market worldwide in 2017, China has been listed as the first leading nation by organic agriculture area (3 million hectares) (Sahota, 2018). Moreover, in 3-million-hectare organic agriculture area, FiBL and IFOAM—Organics International (2019) reported that China was ranked the leading nation of organic cereal (96.3 million hectares) and temperate fruit productions (22,400 hectares). In addition, China has a considerable Asian organic food market. To be specific, China’s overall organic packaged food and beverages market in 2017 introduced nearly USD 2.84 billion in sales, and organic standard milk dominated overall value sales, taking up over 71% of all market value (FiBL and IFOAM—Organics International, 2019). Accordingly, it is projected that China has a considerable organic food market in years ahead (Daxueconsulting.com, 2020). Besides, food scandals and health scares are considered major drivers of Chinese consumers in China to purchase organic food among (Pei et al., 2011). Nonetheless, how specific background factors motivate consumers to purchase organic food as a long-term diet habit in China has been rarely studied.

In the area of consumers’ behavior of food purchase, theory of planned behavior (Ajzen, 1991) is suggested as the most widely used theory to determine the relationships between purchase factors (i.e., purchase attitude, subjective norms, and perceived behavioral control) and purchase intention (Alam & Sayuti, 2011; Dowd & Burke, 2013; Qi & Ploeger, 2019). Except for applying original variables in TPB as a necessary theoretical support in studying consumers’ purchase intention and purchase decision, more scholars introduced new factors based on the theoretical framework of TPB to broaden TPB from multi-perspectives. Nardi et al. (2019) conducted a meta-analysis regarding consumers’ food choice based on TPB, indicating that consumers’ intention of purchasing food is effectively motivated by food origin, life cycle, involving technology, healthcare, ethical concern, and convenience matter. The result of the present study is reflected in numerous studies. For instance, Haro (2016) asserted that availability and information are identified as another two motives in driving consumers’ intention of purchasing Halal food. In support, Ali et al. (2018) indicated that perceived availability in line with personal conviction are closely related to Chinese Muslim’s intention of purchasing Halal food. Moreover, technology awareness is emphasized in studies on consumers’ intention of purchasing genetically modified food (Zhang et al., 2018). Country of origin (COO) is another frequently discussed factor in studying consumers’ intention of purchasing fresh food, foreign food, Halal food, and imported functional food (Holdershaw & Konopka, 2018; Muhamad et al., 2017; Sagheb et al., 2020; Xin & Seo, 2019).

Moreover, extended TPB is also widely applied in studying consumers’ intention of purchasing organic food. Yadav and Pathak (2016) added moral attitude as another critical factor by complying with the concept of purchase attitude to deeply study the type of attitude most significantly impacting young consumers’ intention of purchasing organic food. Except for discussing the roles of attitude, subjective norms, and perceived behavioral control (PBC) in consumers’ intention of purchasing organic food, Dangi et al. (2020) considered health motives, past purchase behavior, knowledge, affordability, and trust in organic food certificate as main facilitators in organic food purchase. Given this study, environmental concern and health consciousness are considered the most frequently discussed factors of consumers’ intention of purchasing organic food, then followed by price, knowledge, labeling, and certificate issue (Asif et al., 2018; Essoussi & Zahaf, 2008; Grimmer et al., 2016). However, factors of organic food purchase intention are found to require a clear category criteria, as considered a hindrance of studying behavior of purchasing organic food systematically. Therefore, the present study aims to investigate impacts of background factors on consumers’ intention of purchasing organic food from individual, social, and information perspectives in organic food market of China by applying extended TPB and reasoned action model (Fishbein & Ajzen, 2011) to comparatively conduct a clearer and systematic study, which is of high importance but rarely studied in existing literature.

As aforementioned, factors of consumers’ purchase intention have been extensively discussed in various contexts. However, existing literature ignored the gap existing in the relationship between intention and behavior (decision). Futerra (2005) claimed that consumers’ purchase behavior (decision) is not always directly predicted by purchase intention, i.e., purchase intention might not transit to purchase behavior (decision) straightforward. Accordingly, the present study intends to fill in intention-decision gap regarding organic food purchase by introducing a moderating effect in it. According to existing studies, word-of-mouth (WOM) has been considered more reliable and trustworthy information than messages generated from advertising and marketers (Bansal & Voyer, 2000; Carl, 2006; Filieri, 2015; Li et al., 2013). Consequently, consumers are inclined to exploit such information as an essential reference when making final purchase decision (Park, Lee, & Han, 2007; Sen & Lerman, 2007; T. Sun et al., 2006). Given the significance of direct effect of WOM on purchase decision, WOM is studied as a moderating role to investigate whether it can deepen the relationship between purchase intention and purchase decision on organic food.

2. Theoretical framework

2.1. Theory of planned behavior

TPB was originally proposed by Icek Ajzen in 1985, an extension by complying with the theory of reasoned action (Fishbein & Ajzen, 1975). It refers to a theoretically structured framework assessing and clarifying human’s behavior in terms of beliefs and attitudes (Ajzen, 1991). Specific to TPB, human’s behavioral intention is significantly driven by attitude, subjective norms, and perceived behavioral control (PBC), where human’s behavior is significantly impacted by behavioral intention (Fishbein & Ajzen, 2011). Moreover, attitude refers to individual’s opinion on whether a specific behavior is good or bad, positive or negative, favorable or adverse; subjective norms represent perceived social impacts or pressures, which refer to opinions and, to some extent, the approval of family, friends, co-workers, and any other person whom trusts; PBC can be defined as the ability to control specific behavior, i.e., the perceived “difficulty of declining the invitation” (Ajzen, 1985, p. 26).

In the area of food marketing, it was extensively found that the impact of purchase attitude significantly reaches over those of subjective norms and PBC in consumers’ purchase intention (Bashir et al., 2019; Jaafar et al., 2012; Singh & Verma, 2017). Furthermore, it is found that factors of consumers’ purchase intention aroused huge attention from most studies, whilst purchase intention is less likely to link purchase decision by applying extended TPB (Maichum et al., 2016; Othman & Rahman, 2014; H. Y. Kim & Chung, 2011). Given the significance of attitude, behavioral intention, and actual behavior in TPB as theoretical support, purchase attitude is studied as one of the individual factors of consumers’ intention of purchasing organic food; furthermore, the relationship between purchase intention and purchase decision is also further explored in line with moderator to give a holistic study based on TPB (Ajzen, 1991).

2.2. Reasoned action model

In the premise of TPB, reasoned action model was developed by Fishbein and Ajzen in 2010 (Fishbein & Ajzen, 2011). Compared with original TPB, RAM introduces background factors imposed on human beliefs; moreover, practical control is implemented in the relationships between perceived behavioral control and behavior. According to Fishbein and Ajzen (2011), background factors fall to three aspects, including individual factors (i.e., personality, mood, emotion, values, general attitude, perceived risk, and past behavior), social factors (i.e., education, age, gender, religion, ethnicity, and culture) as well as information factors (i.e., knowledge, media, and intervention). Jaccard (2012) asserted that RAM has a quite high influential power in social and health sciences. More importantly, RAM encourages researchers to delve into each individual background factor based on different perspectives, rather than through traditional modeling (Jaccard, 2012). Given this, the present study seeks to investigate how selected background factors impact consumers’ intention of purchasing organic food from individual, social, and information perspectives by applying RAM, whereas extant studies are less stressed.

3. Literature review and hypotheses development

3.1. Influences of individual factors on purchase intention

• Purchase attitude and purchase intention

Based on TPB, “attitude” refers to an individual’s attitude or opinion, i.e., whether a specific behavior is good or bad, positive or negative, or favorable or adverse (Ajzen, 1991). In marketing studies, attitude complying with TPB is tightly associated with purchase intention, and numerous studies proved that in various shopping situations, consumer purchase attitude either positively or adversely affects intention of purchasing specific products (Hartmann & Apaolaza-Ibáñez, 2012; Lee Bonn, & Cho, 2015; Phua & Kim, 2018; Pisitsankkhakarn & Vassanadumrongdee, 2020).

Recent studies determined the role of attitude in TPB to gain insights into its predictive power on organic food purchase intention. A wide range of studies proved that consumer purchase attitude is capable of impacting consumers’ purchase intention, either directly, or indirectly through alternative variables (e.g., health consciousness, environmental concern, food safety, as well as taste) (C.L. Hsu et al., 2017; K.H. Lee et al., 2015; Nguyen et al., 2019; Q. Pham et al., 2018). Given the important ways in which consumer purchase attitude impacts consumers’ purchase intention, and other studies regarding green/organic food purchase intention, Lin and Huang (2012) claimed that gaining a full insight into consumer purchase attitude can help policy makers, producers, and marketers boost green purchase habits and stimulate the consumption of green/organic products. Thus, purchase attitude is studied as one of the vital individual factors to probe into its predictive power on purchase intention in the field of China’s organic food market. For this reason, the following hypothesis is proposed:

Hypothesis 1: Purchase attitude significantly influences organic food purchase intention.

• Health consciousness and purchase intention

Health consciousness can measure the readiness to undertake health actions (Becker et al., 1977). Accordingly, health consciousness is highly considered a critical dimension involved in perceived food quality, frequently discussed with consumers’ purchase intention in relation to food products (Findling et al., 2018; Kang et al., 2015; Abdul Latiff et al. 2016). Under attributes contained in organic food (i.e., no artificial ingredients, no preservatives, no harmful chemicals, and no GMO), consumers with strong health consciousness are inclined to pursue healthier food (e.g., organic food in their daily life), so health consciousness is a critical driving factor effectively motivating consumers to purchase organic food (Nasir & Karakaya, 2014; Rao et al., 2020; Shaharudin et al., 2010; Wang et al., 2019).

Besides, existing studies found that the reason for purchasing organic food displays a tight association with its nutrition value perceived by consumers, numerous consumers hold that organic food contains more overall nutrition, more fiber, roughage, and more vitamin as opposed to conventional-produced food, and even it is not basically evidenced that organic food outperforms conventional food in terms of nutrition value (Curvelo et al., 2019; Nguyena et al., 2020; Shahriari et al., 2019; Smith-Spangler et al., 2012). Thus, perceived nutrition value is another critical cognition included in health consciousness, capable of driving consumers’ intention of purchasing organic food. In the context of China, food scandals definitely threaten Chinese consumers’ mind when considering food choice (Wu & Zhu, 2014). Thus, whether from the perspectives of attributes of organic food or perceived nutrition value of organic food, health consciousness should be taken as another individual factor to study its effect on consumers’ intention of purchasing organic food. Therefore, the following hypothesis is proposed:

Hypothesis 2: Health consciousness significantly influences organic food purchase intention.

• Hedonism and purchase intention

The term—hedonism is associated with the concept of hedonistic consumption, indicating consumers’ consumption behavior from the perspectives of multisensory, appealing, pleasure, and fantasy from relevant products (Hirschman & Holbrook, 1982). As a result, hedonism is considered a type of pleasure and sensuous satisfaction for individuals (Grunert & Juhl, 1995). According to Pohjanheimo et al. (2010), personal values are significantly stable individual factors rooted in people’s lives, usually guiding people’s behavior through attitude or other motives. For instance, it can be seen that hedonistic reason has been proven to drive consumers’ attitude and purchase intention regarding food choice (Audebert et al., 2006; Feil et al., 2020; H. J. Lee & Yun, 2015; Vermeir & Verbeke, 2006).

For organic food marketing, taste and appealing appearance are considered the most critical elements regarding hedonistic consumption (Anisimova, 2016; Huang & Lu, 2016; Kemp et al., 2010; Nasir & Karakaya, 2014; Sandhya & Nair, 2019). For instance, Paul & Rana (2012) stated that organic food taste displays a close relationship to consumers’ overall satisfaction and purchase intention. In China, one of the significant reasons for purchasing organic food is considered “better taste”, which implies organic food is perceived to have better taste than conventional food (Yin et al., 2010). In line with the present study, J. Chen et al. (2014) also indicated that taste as a critical attribute in sensory appeal shows a great impact on consumers’ intention of purchasing organic food. Moreover, appealing appearance is extensively discussed with consumers’ hedonistic consumption when purchasing organic food. According to M. Massey et al. (2018), when searching for organic food, consumers place stress on appearance. Also, in studies of online shopping behavior for organic food, the result demonstrated that age, income, and willingness to pay for organic food importantly attach to appearance of it (Bryła, 2018). Thus, it is necessary to further determine the relationship between hedonism and intention of purchasing organic food in the context of China’s organic food market, which is rarely mentioned in existing literatures. Thus, the hypothesis is proposed as follows:

Hypothesis 3: Hedonistic motivation significantly influences organic food purchase intention.

3.2. Influences of social factors on purchase intention

• Self-perceived vegetarian and purchase intention

Vegetarian displays a tight association with the term of vegetarianism, vegetarianism is defined as a type of cognition and emotional response in relation to food choice, interpreted as an indicator of identity (Twigg, 1979). Therefore, vegetarian refers to individual’s diet practice based on vegetarianism (merriamwebster.com). Given relevant definition, vegetarian diet excludes various meat, fish, poultry, and any productions of slaughter, so grains, vegetables, fruits, and nuts turn out to be the main food choices for vegetarians (vegsoc.org). Recently, vegetarianism arouses extensive concerns from increasing people in society for various reasons. According to the study by Beardsworth and Keil (1991), vegetarians’ principal motives are identified as aspects of spiritual, health, gustatory, ecological, and moral. Among the mentioned motives, heath and ecological aspects are extensively discussed with food choice. In relevant studies, considerable consumers hold that being a vegetarian would significantly benefit their health in a long term, greatly driving them to purchase healthy food (Hoek et al., 2004; Hartmann et al., 2018; J. Park et al., 2020). The significance of relationship between ecological concern and vegetarian is also found in existing studies by asserting that consumers with a strong ecological awareness are inclined to purchase meat-free products and be vegans (Fan et al., 2019; Iris et al., 2018; Mullee et al., 2017; Raggiotto et al., 2018).

Concerned with attributes of organic food (e.g., healthier, ecological-oriented, and environmental-friendly), vegetarian consumers’ intention of purchasing organic food is also driven based on the attributes. According to Hoek et al. (2004), compared with non-vegetarian consumers, vegetarian consumers are more willing to purchase healthy and organic food as their diet choices than non-vegetarian consumers. The present study result is supported by Onyango et al. (2007), claiming that vegetarian-vegan is considered a critical consumption group in enhancing consumers’ regular intention of purchasing organic food. Moreover, for socio-demographic information, latest studies also explicated that vegetarian group takes up a big proportion of organic food consumers (Baudry et al., 2016; Raghavendra, 2016; Saraiva et al., 2020; Simões-Wüst et al., 2017). Nonetheless, self-perceived vegetarian remains less studied as a vital social factor in relation to organic food purchase intention with quantitative research, so researchers seek to probe into the direct effect of self-perceived vegetarian on organic food purchase intention in China’s market. For this reason, the following hypothesis is proposed:

Hypothesis 4: Self-perceived vegetarian significantly influences organic food purchase intention.

• Environmentalism and purchase intention

Based on Merriam–Webster Dictionary, environmentalism is defined as “advocacy of the preservation, restoration, or improvement of the natural environment, especially the movement to control pollution” (merriamwebster.com). On that basis, in the field of food marketing, environmental concern, derived from definition of environmentalism, is highly considered the critical driving factor towards local/green/ecological/organic food purchase intention as environmentalists are reluctant to purchase chemicals and pesticides used products in market (Albayrak et al., 2013; Hughner et al., 2007; Jolly, 1990; Lee, 2010). Specific to green purchase behavior, existing study results suggested that consumers with a strong environmental awareness are more willing to purchase green products on a day-to-day basis, as compared with consumers without such an awareness (Arttachariya, 2012; Gilg et al., 2005; Mostafa, 2007). Likewise, the important role of environmental consciousness in motivating consumers to purchase local and organic food is supported. In a relevant study by Nie and Zepeda (2011), environmental concern, knowledge, and practices are identified as the key determinant elements in driving consumers’ intention of purchasing local-produced and organic food.

In line with the present study, Hjelmar (2011) conducted an in-depth interview regarding motives of organic food choice, the study result revealed that animal welfare and environmentalism embedded in ethical concerns are two typical motives of choosing organic food. In addition, the important role of environmental concern in shaping consumers’ attitude and intention of purchasing organic food was supported by other recent studies (Kushwah et al., 2019; Le‐Anh & Nguyen‐To, 2020; Nasir & Karakaya, 2014). For the important status of environmental consciousness in studies of behavior of purchasing organic food, the following hypothesis is proposed:

Hypothesis 5: Environmental concern significantly influences organic food purchase intention.

3.3. Influences of information factors on purchase intention

• Labeling and purchase intention

According to Alvensleben (1998), organic labeling interprets a type of quality information among consumers, which would encourage consumers to develop positive attitude towards organic foods. Makatouni (2002) also found that organic food labeling is considered a typical symbol in assessing process-related quality of organic food in the food market. Based on the informative function of labeling, O’Fallon et al. (2007) demonstrated that the significance of organic labeling helps consumers to make rational and informed purchase decisions on organic foods. In support, Żakowska-Biemans (2011) stated that particular logos and labeling can lift market visibility and expose more information regarding organic foods, by which consumers’ trust and purchase willingness to organic foods are progressively motivated. In line with this study, Liang (2016) revealed that organic food labeling positively impacts consumers’ trust and confidence in organic food.

Existing studies found that the role of organic food labeling is frequently explored with purchase attitude, trust and purchase intention. C. C. Teng and Wang (2015) suggested that organic labeling information perceived by consumers critically impacts consumers’ trust towards organic food, which in turn significantly impacts their attitude and intention of purchasing organic food. In organic food market, labeling certificate acting as a reliable signal informs attributes of organic food (i.e., natural, healthy, and safe) (Almli et al., 2019; Drexler et al., 2018; T. H. Pham et al., 2019; McEachern et al., 2005), thereby significantly forging consumers’ intention of purchasing organic food in a positive manner (Atkinson & Rosenthal, 2014; Tung et al., 2012). Thus, the hypothesis is proposed as follows:

Hypothesis 6: Labeling significantly influences organic food purchase intention.

• Social media information and purchase intention

Social media is defined as an online application program, platform, or mass media tool capable of facilitating communication, collaboration, or sharing information among users (Bilgin, 2018). Currently, a wide range of social media tools have been used increasingly for their benefits of perceived convenience, effectiveness, and perceived credibility (Yogesh & Yesha, 2014). Consequently, a growing number of consumers are highly engaged with social media platforms (e.g., Facebook, Youtube, Twitter, Instagram, Sina Weibo, and Tiktok) to acquire sufficient information regarding products (Alalwan et al., 2017; Haenlein et al., 2020; N. Kim & Kim, 2018; Latiff & Safiee, 2015). More importantly, in China, internet economy has boomed with the great support by 5 G internet service, and considerable Chinese consumers are enthusiastic about activities of “live streaming shopping” and “sec-killing interaction” (snapping up products in a limited time) enabled by various social media platforms when purchasing target products (Lv et al., 2018; Y. R. R. Chen, 2017; Y. Sun et al., 2019). Thus, social media information disclosed by various social media platforms intensively is suggested to drive consumers’ intention of purchasing particular products.

The significant impact of social media information on consumers’ purchase intention is reflected by numerous values. For online purchase, Sin et al. (2012) showed that perceived usefulness of social media information is considered the critical factor affecting consumers’ purchase intention towards online shopping, with the result also supported by relevant studies conducted by Lin & Kim (2016). Moreover, values of entertainment, customization, and interaction embedded in social media information are closely associated with consumers’ purchase intention regarding luxury fashion brands (Gautam & Sharma, 2017). Besides, attributes of informativeness, advertising value, emotional appeal, and creativity value arose from social media information have been extensively discussed with consumers’ purchase intention and behavior in different contexts (Alalwan, 2018; Dix et al., 2012; J. Lee & Hong, 2016; Shareef et al., 2017). Meanwhile, in the field of behavior of purchasing organic food, the function of social media information in motivating consumers’ purchase intention regarding organic food has been identified in relevant literatures (Brumă, 2020; David et al., 2017; Hilverda et al., 2018). Given the vital role of social media information working in marketing campaign with support of 5 G internet service, this study aims to delve into whether consumers’ intention of purchasing organic food is significantly motivated by information presented in social media in the context of China. This leads to following hypothesis:

Hypothesis 7: Social media information significantly influences organic food purchase intention.

3.4. Moderating role of word-of-mouth (WOM) in the relationship between purchase intention and purchase decision

Word-of-mouth (WOM) is explained as individuals’ evaluation of brands, products, services, or organizations that is conducted without commercial intention and diffused through face to face or other communications throughout social networks (Silverman, 1997). Relevant studies stressed that the function of WOM effectively encourages more consumers to share their comments regarding products and services, which information is considered more objective and reliable as opposed to propagandas offered by marketers (Sallam, 2014; Tenreng et al., 2019; Verkijika & De Wet, 2019). Consumers, therefore, are inclined to exploit such information as an essential reference when making final purchase decision (T. Sun et al., 2006; Park et al., 2007; Sen & Lerman, 2007). Thus far, WOM has been considered more reliable and trustworthy information than messages generated from advertising and marketers (Bansal & Voyer, 2000; Carl, 2006; Filieri, 2015; Li et al., 2013). As indicated from the literature review, the significant role of WOM that acts as an independent variable, mediation as well as moderation has been identified in relation to green/environmental-friendly/local/organic purchase intention and purchase behavior.

For instance, Al-Gasawneh and Al-Adamat (2020) conducted a study on content marketing and consumers’ green purchase intention in Jordan. According to the result, the relationship between content marketing and green purchase intention is subject to a significant mediation by electronic word-of-mouth (eWOM). Besides discussing the mediation role of WOM, the moderation role of WOM has been explored regarding green purchase intention by Mansoor and Noor (2019), the study claimed that positive WOM is capable of significantly moderating the relationship between environmental concern, green awareness, and green purchase intention. Specific to local culinary business, eWOM has indicated its direct effect on consumers’ intention of purchasing local food (Hamdani et al., 2018). Moreover, the significant impact of WOM effects on consumers’ purchase decision on organic food was also identified in the study by Chang and Chang (2017). According to the study result, WOM effects (i.e., tie strength, sender’s green expertise, and receiver’s green expertise) are significantly associated with consumers’ purchase behavior towards organic food in the context of Taiwan.

Futerra (2005) asserted that consumers’ purchase decision is not constantly directly predicted by purchase intention, i.e., purchase intention might not transit into purchase behavior straightforward. Given this study, intention-behavior gap can be revealed from other studies on consumers’ purchase intention and decision-making process as well (De Cannière et al., 2010; Carrington et al., 2010; Hassan et al., 2016). Though the critical role of WOM in purchase intention and purchase behavior has been extensively investigated in various marketing contexts, the study focusing on the gap between purchase intention and purchase decision has been rarely conducted by incorporating the moderating role of WOM in terms of organic food purchase. Next, this leads hypotheses below:

Hypothesis 8: Purchase intention significantly influences purchase decision on organic food.

Hypothesis 9: Word-of-mouth (WOM) significantly moderates the relationship between purchase intention and purchase decision on organic food.

4. The conceptual framework

Under a wide range of reviewed literatures and proposed hypotheses, a study conceptual framework is illustrated in Figure 1, helping readers gain insights into the relationships between background factors and purchase intention, as well as the moderating role of WOM in the relationship between purchase intention and purchase decision visually.

Figure 1. Study conceptual framework

5. Research methodology

5.1. Sampling design

Given the study purposes, quantitative research method was adopted by complying with the questionnaire survey strategy to collect primary data. The target population here covers all consumers with the experience in purchasing organic food at least once in organic food stores of Chaoyang district, Beijing, China. Under unknown sampling frame and characteristic of target population, non-probability and purposive (judgement) sampling method was selected as the most proper method for data collection.

As reported by duty managers working in organic food stores, the target population size in Chaoyang district was estimated as nearly 1000 per day. According to Saunders et al. (2015), the minimum sample size can be determined under a desired accuracy with non-probability sampling. Thus, in the present study, the minimum sample size was determined as 278 by considering estimated target population size (1000), the level of precision (5%) and the confidential level (95%) (Krejcie & Morgan, 1970). Besides, response rate refers to another crucial factor that should be considered when determining a representative sample size, since occurrence of ineligible response would practically increase bias and risk among minimum sample size. Based on this issue, Israel (1992) suggested that 10–0% of samples should increase over the minimum sample size to reduce risk of ineligible response and to ensure a desired sample maximally. By complying with the principle of time-saving and high-efficiency in terms of data collection, researcher decided to introduce extra 10% (278 × 10% = 28) samples to existing minimum samples. Thus, the desired sample size should be 306 (278 + 28 = 306).

Moreover, structural equation modeling (SEM) adopted as data analysis technique here has also been concerned by researchers to determine relatively representative sample size. Boomsma and Hoogland (2001) suggested that 200 is minimum sample size to yield a suitable statistical result in SEM. Also, Wolf et al. (2013) stated that required sample size for conducting SEM ranged from 30 to 460 cases. Therefore, the desired sample size (306) here also satisfied the requirement of conducting SEM analysis.

5.2. Measurement

All proposed constructs were measured with 5-point Likert scale questionnaire, and each item was adapted from origin studies conducted previously to better comply with study objectives. The questionnaire was originally designed in English. Since the target participants are Chinese, the questionnaire was translated into Mandarin by an expert. The following Table 1 lists the original source of items and number of items.

Table 1. Sources of measured items

Constructs	Source of adoption	Numbers of item
Purchase attitude	M.F. Chen (2007)	5
Health consciousness	Michaelidou and Hassan (2008)	5
Hedonistic motivation	Anisimova (2016)	5
Self-perceived vegetarian	Yang (2017)	5
Environmental concern	Wee et al. (2014)	4
Labeling	Minbashrazgah et al. (2017)	5
Social media information	Pop et al. (2020)	4
Word-of-mouth (WOM)	Reza Jalilvand and Samiei (2012); N. T. Kuo et al. (2012)	6
Purchase intention	Liang (2016)	4
Purchase decision	Tariq et al. (2019)	4

5.3. Data collection and response rate

In the present study, primary data collection was conducted with self-administrative questionnaire to collect 306 respondents on the whole. The data collection period lasted for nearly 2 months starting from 4^th July to 16^th September in 2020 at organic food stores in Chaoyang district, Beijing, China. First, before collecting data, general explanations related to study purposes, aims and requirements were conveyed to duty managers working in organic food stores to get the approval to approach to target respondents in shops. Second, a brief communication was made with target respondents, ensuring that respondents were willing to take part in this research. Third, researcher negotiated with staff, as an attempt to get the permission to guide respondents to complete and submit questionnaires in a designated place.

All collected questionnaires were rigorously scrutinized to avoid data input errors. As a result, 280 out of 306 samples were valid for proceeding in-depth data analysis, taking up 91.5% response rate. Furthermore, it was noticed that the 26 invalid questionnaires were not completely filled or filled with errors.

5.4. Socio-demographic profiles of respondents

Table 2 lists socio-demographic profiles of all respondents here. Among 280 respondents, more than half of respondents (58.6%) were females, and the other (41.4%) were males. However, only a slight proportion difference (11.6%) was found between female organic food consumers and male organic food consumers. For age group distribution, majority of organic food consumers distributed in age range between 35 and 44 years old (48.2%), then followed by 25–34-years old (37.9%), 45–54 years old (8.6%) and 18–24 years old (3.2%); the least organic food consumers were distributed in age range of 55-years old and above (2.1%). Specific to marital status, it was found that married respondents (55.7%) were inclined to purchase organic food than non-married respondents (44.3%). For the education level, the majority of respondents were master degree holder (55.7%), and undergraduate degree holders took up a second large proportion (43.6%), followed by doctoral degree holders (0.7%). Besides income level, 22.5% respondents earned monthly income ranging between RMB 5001 and RMB 8000, 31% respondents earned monthly income RMB 10,000 and above, and only 5% respondents earned monthly income of RMB 5000 and below. It was therefore revealed that majority of organic food consumers remained in the range of medium-high income level.

Table 2. Socio-demographic profiles of respondents (n = 280)

Items	Frequency	Percentage (%)
Gender
Female	164	58.6%
Male	116	41.4%
Age group (years)
18–24	9	3.2%
25–34	106	37.9%
35–44	135	48.2%
45–54	24	8.6%
55 and above	6	2.1%
Marital status
Single	156	55.7%
Married	124	44.3%
Education level
Undergraduate and below	162	57.9%
Master degree	116	41.4%
Doctoral degree	2	0.7%
Income (CNY/month)
5000 and below	14	5%
5001–8000	63	22.5%
8001–10,000	172	61.4%
10,000 and above	31	11%

6. Structural equation modeling result

6.1. Convergent validity and reliability

Validity test refers to a crucial step before conducting path analysis since measurement errors should be identified. Convergent validity can be assessed by examining index of Average Variance Extracted (AVE); the value of AVE greater than or equals to 0.5 interprets an acceptable convergent validity (Fornell & Larcker, 1981). Moreover, according to Hair et al. (2006), convergent validity should be assessed by coefficient of factor loading, which should exceed 0.4, indicating a good convergent validity. Thus, in the present study, convergent validity of all constructs was assessed by conducting CFA by checking indices of factor loading and AVE. According to Table 3 below, all constructs exceeded the indices benchmark of convergent validity (standardized factor loading ≥ 0.4 and AVE ≥ 0.5), interpreting a quite good convergent validity of constructs.

Table 3. Convergent validity and reliability of constructs

Constructs	Items	Standardized Factor Loading ≥ 0.4	AVE ≥ 0.5	CR ≥ 0.7	Cronbach α
Purchase attitude (PA)
	PA 1	0.783	0.525	0.834	0.822
	PA 2	0.484
	PA 3	0.853
	PA 4	0.758
	PA 5	0.628
Health consciousness (HC)
	HC 1	0.85	0.582	0.886	0.892
	HC 2	0.751
	HC 3	0.731
	HC 4	0.837
	HC 5	0.775
Hedonistic motivation (HED)
	HED 1	0.669	0.555	0.866	0.864
	HED 2	0.781
	HED 3	0.779
	HED 4	0.799
	HED 5	0.724
Self-perceived vegetarian (SPV)
	SPV 1	0.716	0.533	0.87	0.872
	SPV 2	0.697
	SPV 3	0.774
	SPV 4	0.8
	SPV 5	0.793
Environmental concern (ENV)
	ENV 1	0.797	0.625	0.877	0.877
	ENV 2	0.816
	ENV 3	0.758
	ENV 4	0.83
Labeling (LAB)
	LAB 1	0.828	0.585	0.887	0.834
	LAB 2	0.797
	LAB 3	0.803
	LAB 4	0.826
	LAB 5	0.917
Social media information (SMI)
	SMI 1	0.864	0.655	0.92	0.901
	SMI 2	0.826
	SMI 3	0.775
	SMI 4	0.872
Word-of-mouth (WOM)
	WOM 1	0.787	0.585	0.889	0.889
	WOM 2	0.767
	WOM 3	0.741
	WOM 4	0.732
	WOM 5	0.778
	WOM 6	0.736
Constructs	Items	Standardized Factor Loading ≥ 0.4	AVE ≥ 0.5	CR ≥ 0.7	Cronbach α
Purchase intention (PI)
	PI 1	0.796	0.661	0.881	0.88
	PI 2	0.836
	PI 3	0.807
	PI 4	0.782
Purchase decision (PD)
	PD 1	0.816	0.647	0.88	0.87
	PD 2	0.827
	PD 3	0.769
	PD 4	0.806

Notes: AVE = average variance extracted, CR = construct reliability.

For reliability test, Mitchell (1996) suggested that construct reliability can be assessed through internal consistency, the most common method of measuring internal consistency is to assess index of Cronbach’s alpha, values of Cronbach’s alpha 0.7 or above indicate a good internal consistency (Field, 2013). Besides test reliability through assessing internal consistency, construct reliability (CR) is required in SEM analysis (Perry, 1996). Accordingly, the indices of Cronbach’s alpha and CR were referred here to assess reliability of constructs. According to Table 3, Cronbach’s alpha of all constructs reached an acceptable internal consistency level from minimum of 0.822 to maximum of 0.901, indicating a quite good internal consistency. Also, construct reliability was verified by calculating CR based on standardized factor loading coefficients, the result indicated that all constructs reached a quite considerable construct reliability level from the minimum of 0.834 to the maximum of 0.920.

6.2. Measurement model

Measurement model refers to one of the critical parts in SEM, associating measured variables with latent variables (Shek & Yu, 2014). Moreover, assessing measurement model is another prior step for moving to path analysis in structure model under the significance of data fit (Brown & Moore, 2012). Based on CFA analysis result, the key goodness-of-fit indices are listed in Table 4. For absolute fit, RMSEA = 0.047 (less than 0.08), showing a good absolute fit. Specific to incremental fit, GFI = 0.837 (nearly 0.9), CFI = 0.937 (greater than 0.9), TLI = 0.930 (greater than 0.9) and NFI = 0.851 (greater than 0.8), indicating an incremental fit. Besides parsimonious fit, Relative χ² = 1.607 (less than 5), which also indicates a good fit.

Table 4. Measurement model fit indices

Fit Index	χ^2/df	RMSEA	CFI	NFI	GFI	TLI
Value	1.607	0.047	0.937	0.851	0.837	0.930
Benchmark	< 5.0	< 0.08	> 0.90	> 0.80	> 0.80	> 0.90

Sources: Browne and Cudeck (1993), Joreskog and Sorbom (1984), Bentler and Bonett (1980), and Bollen (1989).

6.3. Structural model

Based on proposed hypotheses 1–7, the structural equation model was applied to determine the relationships between exogenous and endogenous latent variables by using AMOS 24.0. The structural model is shown in Figure 2. Consequently, the Goodness-of-fit indices of structural model are listed in Table 5 as well: Chi-Square χ² = 1060.244, df = 621, Relative χ² = 1.707, p = 0.000, GFI = 0.824, CFI = 0.924; NFI = 0.836; IFI = 0.925, TLI = 0.919, RMSEA = 0.050. According to Hair et al. (2006), structural model meets the overall fitness if any three or four fit indices reached benchmark, thus, proposed structure model of the present study fitted the data well.

Figure 2. Structural equation model depicting the influences of background factors on purchase intention

Table 5. Structural model fit indices

Fit Index	χ^2/df	RMSEA	CFI	NFI	GFI	TLI
Value	1.707	0.050	0.924	0.836	0.824	0.919
Benchmark	< 5.0	< 0.08	> 0.90	> 0.80	> 0.80	> 0.90

Sources: Browne and Cudeck (1993), Joreskog and Sorbom (1984), Bentler and Bonett (1980), and Bollen (1989).

Table 6 illustrates the test outcomes of proposed hypotheses 1–7. In terms of individual factors, purchase intention was significantly predicted by purchase attitude (β = 0.174, p < 0.05) and health consciousness (β = 0.172, p < 0.05), while it was not predicted by hedonistic motivation (β = 0.020, p > 0.05). Therefore, H1and H2 were supported, H3 was not supported. For social factors, purchase intention was significantly predicted by self-perceived vegetarian (β = 0.184, p < 0.05) and environmental concern (β = 0.198, p < 0.05). Thus, H4 and H5 were supported. Besides social factors, purchase intention was significantly predicted by labeling (β = 0.295, p < 0.01) and social media information (β = 0.146, p < 0.05). Thus, H6 and H7 were supported. Meanwhile, by comparing the standardized path coefficients, it was found that purchase attitude (β = 0.174), environmental concern (β = 0.198), and labeling (β = 0.295) exerted more significant impacts on purchase intention than the other background factors.

Table 6. Path coefficients and hypotheses outcomes (H1—H7)

Hypothesized Path				Standardized Regression Weights Beta	S.E.	C.R.	p	Result
H1:	PA	→	PI	0.174*	0.057	2.545	0.011	Supported
H2:	HC	→	PI	0.172*	0.049	2.559	0.010	Supported
H3:	HED	→	PI	0.020	0.053	0.303	0.762	Not supported
H4:	SPV	→	PI	0.184*	0.052	2.757	0.006	Supported
H5:	ENV	→	PI	0.198*	0.053	2.941	0.003	Supported
H6:	LAB	→	PI	0.259*	0.054	4.049	0.000	Supported
H7:	SMI	→	PI	0.146*	0.038	2.258	0.024	Supported

Notes: *Significant at the level 0.05, S.E. = standardized error, C.R. = t-value, PA = Purchase Attitude, HC = Health Consciousness, HED = Hedonic Motivation, SPV = Self-Perceived Vegetarian, ENV = Environmental Concern, LAB = Labeling, SMI = Social Media Information, PI = Purchase Intention.

6.4. Moderation analysis

In the present study, SPSS PROCESS Macro was employed to determine the effect of WOM moderating the relationship between purchase intention and purchase decision. Prior to examining the moderating effect of WOM, regression analysis was conducted to confirm the relationship between purchase intention and purchase decision via SPSS. Table 7 indicates the significant association of purchase decision with purchase intention (t = 7.556, p = 0.000, 95% CI = [1.026, 2.118]). Hence, H8 was supported. Table 7 also indicates that WOM significantly moderated the relationship between purchase intention and purchase decision (t = 0.346, p = 0.001, 95% CI = [0.140, 0.551]). Therefore, H8 was supported at the level of p < 0.05. Notably, the mentioned finding revealed that purchase intention was greater or elevated as impacted by the interaction of WOM, i.e., WOM as a moderator deepened the relationship between purchase intention and purchase decision.

Table 7. Moderation effect of WOM outcome (H8—H9)

Hypothesized Relationship		Std Beta	Std Error	t-value	p	LLCI	ULCI	Result
H8:	PI → PD	0.550	0.056	7.556	0.000*	1.026	2.118	Supp orted
H9:	PI * WOM → PD	0.346	0.105	3.308	0.001*	0.140	0.551	Supported

Notes: *Significant at the level 0.05, PI = Purchase Intention, WOM = Word-of-mouth, PD = Purchase Decision.

Furthermore, to determine the significant interaction effect of WOM moderating the relationship between purchase intention and purchase decision, interaction scatterplot was drawn based on statistic result. According to Figure 3, the relationship between purchase intention and purchase decision was stronger under the high effect of WOM than under the low effect of WOM.

Figure 3. Moderation effect of WOM interaction scatterplot

7. Discussion

As study findings disclosed in above section, the proposed hypotheses were successfully supported by theory of planned behavior (TPB) and reasoned action model (RAM) (Ajzen, 1991; Fishbein & Ajzen, 2011). Overall, with the theoretical support of TPB and application of RAM, consumers’ intention of purchasing organic food was significantly motivated by majority of background factors from individual, social, and information perspectives. More importantly, the study result also found that purchase intention—purchase decision gap was successfully filled by the moderating role of WOM.

To be specific, in terms of individual factors, it can be seen that consumers’ intention of purchasing organic food was greatly driven by purchase attitude and health consciousness, while it was not associated with hedonistic motivation factor proposed in the present study. By looking to existing studies, the significant relationship between attitude and purchase intention complied with the existing study by Kitcharoen (2018), indicating consumers’ attitude towards organic food as a critical predictor of purchase intention during the online and offline purchase of organic food. Besides, the effect of health consciousness, i.e., one of indispensable personal values on organic food purchase intention, was noticeably supported by scholars previously (Michaelidou & Hassan, 2008; Wang et al., 2019; S. Y. Hsu et al., 2016). However, this finding revealed no significant relationship between hedonistic motivation and organic food purchase intention, inconsistent with existing studies by Anisimova (2016), Katt and Meixner (2020) and Olsen et al. (2012). This might be explained as Chinese consumers are less likely to focus on attributes given by organic food (e.g., taste, smell and appealing appearance), i.e., Chinese consumers perceived hedonic aspects as slight factors compared with other driving factors when considering to purchase organic food. In support, a consistent study by Y. M. Teng and Wu (2019) in Taipei city, Taiwan indicated that consumers perceived utilitarian value as the determinant factor, rather than hedonic value regarding green restaurant consumption intention.

Specific to social factors, the study findings supported that self-perceived vegetarian and environmental concern could significantly drive consumers’ intention of purchasing organic food. In existing studies, self-perceived vegetarian used to be studied as socio-demographic information to identify diet habit or lifestyle of organic food consumers (Gracia Royo & de-Magistris, 2007; Stobbelaar et al., 2007; Tung et al., 2015). In the present study, however, self-perceived vegetarian was explored as a vital independent variable with purchase intention by quantitative research method, helping confirm that proposed relationship between self-perceived vegetarian and intention of purchasing organic food exactly existed. Furthermore, the significant relationship between environmental concern and purchase intention was also identified in majority of studies on organic/green/local/ecological purchase behavior (Albayrak et al., 2013; Asif et al., 2018; Hughner et al., 2007).

Besides information factors, the study findings supported the proposed hypotheses, i.e., organic food purchase intention is significantly impacted by labeling and social media information. In line with existing studies, Ayyub et al. (2018) suggested that organic labeling was considered an indicator of organic food quality, which greatly elevated consumers trust towards purchasing organic food. Furthermore, previous scholars such as Ellison et al. (2016) and Sörqvist et al. (2015) also claimed that consumers perceived organic products with organic labels are healthier than that without organic labels, consequently consumers’ intention of purchasing organic food was driven by products with organic labels. In the context of China, the impact of social media information (marketing) on consumers’ intention of purchasing particular products was increasingly witnessed with the support of 5 G mobile internet (Lv et al., 2018; Y. R. R. Chen, 2017). Accordingly, the similar finding went to the present study, consumers’ intention of purchasing organic food was also largely motivated through massive information spread in varieties of social media platforms as more and more consumers relied on gathering sufficient information from social media Apps. This opinion was supported by Kumar et al. (2020), asserting that higher accessibility of information provided by social media apps had a big impact on consumers’ purchase intention in food and beverage industry in Malaysia.

Based upon the findings, existing studies related to the role of WOM and electronic word-of-mouth (eWOM) in influencing consumers’ purchase intention and purchase decision can be seen from different scholars (Erkan & Evans, 2016; Y. F. Kuo et al., 2013; M. K. Lee et al., 2011; Levy & Gvili, 2019; Munir et al., 2018). For instance, Y. F. Kuo et al. (2013) showed that positive WOM adversely moderated the relationship between consumer inertia and repurchase intention, but positively moderated that between satisfaction and repurchase intention. Nonetheless, very little study further explored the intention—behavior (decision) gap by adding WOM as moderation in studying consumers’ behavior of purchasing organic food. In the present study, the study result indicated that WOM significantly displayed the moderating effect on relationship between organic food purchase intention and purchase decision, which revealed that the relationship between consumers’ purchase intention and purchase decision on organic food was able to be enhanced by moderating effect of WOM.

8. Conclusion

In the present study, the empirical findings supported that consumers’ intention of purchasing organic food was significantly impacted by majority of proposed background factors from perspectives of individual (i.e., purchase attitude and health consciousness), social (i.e., self-perceived vegetarian and environmentalism), and information (i.e., labeling and social media information) by combined use of theory of planned behavior (TPB) and reasoned action model (RAM). Lastly, the purchase intention—purchase decision gap regarding behavior of purchasing organic food was filled by incorporating moderating role of WOM, which supported that the relationship between purchase intention and purchase decision on organic food was enhanced by WOM.

9. Study implications

9.1. Theoretical implications

The present study makes contributions on exploring consumers’ purchase intention and purchase decision on organic food by categorizing factors into different types of background factors (i.e., individual, social, and information) based on combined use of theory of planned behavior (TPB) and reasoned action model (RAM), by which, it was able to study consumers’ purchase intention by more holistic and systematic ways. Furthermore, the present study primarily incorporates moderating role of WOM in proposed relationship between purchase intention and purchase decision to investigate intention—behavior (decision) gap existing in TPB. As the result, WOM showed its moderating role in relationship between purchase intention and purchase decision on organic food, which fills in research blank in the field of consumers’ purchase behavior towards organic food.

9.2. Practical implications

In the context of China, the present study makes practical implications in several ways. In terms of individual background factors, purchase attitude and health consciousness are considered key factors that drive consumers to purchase organic food. Therefore, marketers and policy makers could pay more attention on conducting kinds of propagandas to emphasize the health concept brought by organic food, which can shape consumers’ purchase attitude towards organic food by a positive way. As study finding showed, Chinese consumers are not sensitive to hedonic aspect in organic food, thus, marketers might reduce the costs in making exquisite packaging. Instead, it might be possible for marketers to convey utilitarian values (i.e., non-pesticide, non-contaminated, and non-chemical fertilizer used) of organic food to drive Chinese consumers’ intention of purchasing organic food.

Specific to social factors, consumers’ intention of purchasing organic food displays a tight association with self-perceived vegetarian and environmental concern, which implies vegetarians and environmentalists advocate the healthy and environmental-friendly concepts rooted in organic food. For stimulating organic food purchase intention among vegetarian consumers, marketing activities should stress vegetarians’ daily diet needs and special diet preferences (e.g., healthier materials, ecological-oriented productive process, and environmental-friendly consumerist). Likewise, for environmentalist consumers, organic food consumption community can be created by marketers to share kinds of environmental-friendly production processes related to organic food to attract more consumers who hold the similar consumption values to join, by which, consumers’ purchase intention is intensively motivated.

With regards to information factors, both labeling and social media information play significant impacts on consumers’ intention of purchasing organic food. As aforementioned, labeling somehow indicates products quality and trust in consumers mind, due to this, organic food association should disclose as much credible information as possible in organic food label about how organic food materials are grown, processed, and inspected by specialized institution, as an attempt to increase consumers’ trust and confidence in purchasing organic food. Since social media information posted in social media Apps are progressively browsed by consumers, this provides an opportunity for marketers to exploit it to launch social media marketing activities from various perspectives (i.e., entertainment, informativeness, customization, and interaction). As a result, as supported by social media marketing, the relationship between organic food providers and customers gets closer, by which consumers’ purchase preferences is able to be captured more accurately by marketers.

As indicated from the study result, WOM critically deepens the relationship between purchase intention and purchase decision. Given this finding, notably comments and reviews related to organic food given by consumers who had consumption experience successfully impact others purchase decision on organic food. Accordingly, organic food marketers should take marketing effort on attracting more potential consumers by building channels either by online or offline to encourage organic food consumers to share comments, suggestions and feedbacks regarding organic food after purchasing. It is noteworthy that marketers should manage WOM reviews by topping the list with positive WOM reviews and coping with negative WOM reviews with a good attitude, thereby helping strengthen trust and purchase confidence of consumers intended to purchase organic food.

10. Limitations and future study directions

Though the present study makes several contributions on extant study fields from theoretical and practical perspectives, few study limitations remain to be concerned subsequently. First, the present study only selected background factors been frequently discussed in existing literatures, the other background factors (e.g., personality, mood, religion, education, and intervention) require further exploration to study consumers’ purchase behavior towards organic food more precisely. In addition, intention–behavior gap was somehow ignored when studying consumers’ purchase behavior towards particular products, while WOM was just identified as one of moderating roles in the relationship between purchase intention and purchase decision in organic food purchase. For this reason, subsequent studies could explore more alternative moderations capable of filling in the gap as aforesaid. Second, as impacted by unknown sampling frame, sample size was determined by non-probability sampling method. Furthermore, it was noticed that unbalanced sample happened based on age group, i.e., very limited respondents distributed in the age group 18–24, 45–54, and over 55. Hence, subsequent studies might focus on larger sample size to make study be more representative to alleviate sample bias problem. Third, concerned with time restriction, questionnaires were distributed in organic food stores where only located in Chaoyang district, Beijing. Therefore, subsequent studies are suggested to broaden questionnaire distribution areas and other cities from China to approach more different respondents, which is conducive to increasing the study accuracy.

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Shimiao Li

Shimiao Li is a PhD candidate in department of management and marketing at the University Putra Malaysia. Her research interests are focused on consumer purchase behavior, O2O business and social media marketing. Her works are available in the journals of International Services, Economics and Management and Frontiers of Business Research in China. She can be reached via [email protected]

Dr. Nor Siah Jaharuddin is a senior lecturer in department of management and marketing at the University Putra Malaysia. She is specialized in areas of operation management and strategic management. She has published numerous journals in international platforms, such as Advance Science Letters, The Social Science, and International Journal of Accounting, Business and Management. Besides, many of her papers have been presented at conferences such as ICMEF, GCBER, and ICSSR. She can be reached via [email protected].