Understanding Consumer Resistance to the Consumption of Environmentally-Friendly Agricultural Products: A Case of Bio-Concentrated Liquid Fertilizer Product

Methane fermentation digested sludge is a sustainable resource that is used as a liquid fertilizer. An innovative liquid fertilizer called Bio-Concentrated Liquid Fertilizer (Bio-CLF) was developed to solve the problems such as high transportation cost associated with current liquid fertilizer. As an innovation product, Bio-CLF inevitably creates remarkable resistance from consumers. Hence, we used the Innovation Resistance Theory (IRT) to determine the reasons for consumer resistance to Bio-CLF products. A total of 2,000 samples from three major cities, including Tokyo, were extracted via the Internet, and 703 samples were finally selected for analysis. Perceived risk, complexity, and attitude toward existing products were found to have a positive and direct impact on consumer resistance to Bio-CLF products, while motivation and purchase intention were found to have a negative and direct impact on consumer resistance to Bio-CLF products. Notably, Relative Advantage and Compatibility had a positive impact on motivation and indirectly influenced consumer resistance to Bio-CLF products, the results of which are inconsistent with IRT, as those characteristics could have a direct influence on resistance. Additionally, we opted to provide some advice that for market managers: (1) allocate a specialized corner for the Bio-CLF product and (2) place the Bio-CLF product alongside other green products. For producers: (1) disclosure of production information; (2) design of an attractive and clear label sheet; (3) proving the advantage of Bio-CLF and that the Bio-CLF product is a green product. system for Bio-CLF products. For Bio-CLF developer, advancing the Bio-CLF technology and acquiring JAS certification of Bio-CLF

Additionally, it is difficult to adjust the ingredients of the fertilizer. Liquid fertilizer has to be applied to paddy fields at 2-4 kg/m 2 , and the liquid fertilizer contains a total nitrogen content of only 0.2-0.4%. Hence, the fertilizer has to be repeatedly transported from a facility to paddy fields (Ohdoi et al., 2013). In Japan, the liquid fertilizer is transported by a vacuum truck, and each vacuum truck can carry 2,500 kg each time. Further, the efficiency of the liquid fertilizer spreader is approximately 5 kg/m 2 per hour. Consequently, when a suitable period for fertilizer spread is approaching, farmers have to wait for the spreader. Based on these problems, farmers do not actively use digested liquid fertilizer, and methane fermentation facilities maintained by local governments have to spend a remarkable amount of time dealing with digested liquid and its discharge into the river (Note 1).
To solve these problems, Yabe (2019) developed a new technology based on liquid fertilizer derived from methane fermentation digested liquid, which is called Bio-Concentrated Liquid Fertilizer (Bio-CLF), as shown in Figure 1. First, Yabe used flocculants derived from natural ingredients instead of the usual chemical flocculants, to separate methane fermentation digested liquid into solid and liquid parts. Second, Yabe used an ultrafiltration membrane to remove suspended substances from the liquid. Third, Yabe used ED to concentrate nitrogen and potassium from the liquid part. Accordingly, Yabe can adjust the fertilizer ingredients to fit the crops. At the laboratory level, Bio-CLF will help farmers save 2,000 yen/ton in spread cost, and allows its easy transportation as it is concentrated (Yabe, 2019). Additionally, compared with ordinary fertilizer, Bio-CLF can be spread in horticultural facilities and hydroponic soil cultivation (Note 2).
However, the Bio-CLF, as an innovation product, like other types of innovation products such as mobile phones, will inevitably create resistance from consumers. Determining the underlying reasons for consumer resistance to the use of Bio-CLF and modifying the product will help to improve the utilization rate of Bio-CLF and eventually contribute to the effective use of local biomass resources.

Literature Review
The Innovation Resistance Theory (IRT) was postulated by Ram (1987). According to Ram and Sheth (1989), "Innovation resistance is the resistance offered by consumers to an innovation, either because it poses potential changes from a satisfactory status quo or because it conflicts with their belief structure." Consumer resistance plays an important role in the success of innovation, as it can inhibit or delay consumer adoption (Hosseini, Delaviz, Derakhshide, & Delaviz, 2016). Resistance may also occur earlier than adoption after the innovation is launched, and ultimately, consumer resistance may lead to innovation failure in the market (Ma & Lee, 2019). Sheth (1981) argued that as most consumers have no a priori desire to change, we might learn more by understanding the reasons for innovation resistance rather than the reasons for adoption. Hence, it is meaningful to understand the underlying reasons for consumer resistance to innovation.
However, to the best of our knowledge, research on consumer resistance to "liquid fertilizer," is lacking. Our study sought to address this gap by clarifying the underlying reasons for consumer resistance to Bio-CLF products.

The Model of IRT
Based on Ram (1987), consumer resistance to innovation can be viewed to be dependent on three sets of factors: innovation characteristics, consumer characteristics, and characteristics of propagation mechanisms. Among the three sets of factors, innovation characteristics have the power of expected resistance (Hosseini et al., 2016). However, consumer-dependent characteristics would generate resistance depending on how each consumer perceives the innovation carried out on each of these attributes (Ram, 1987). Consequently, we chose these two factors. The characteristics used in this study, based on Ram (1987) are shown in Figure 2. Note. Based on Ram (1987) and assembled by the authors.
Relative advantage represents the degree to which an innovation is perceived to be superior to current offerings (Plouffe, Hulland, & Vandenbosch, 2001). It is considered to be the dominant predictor of consumer adoption of innovation (Agarwal & Prasad, 1997).
Compatibility is an important consideration for a firm that sets its product specifications (Farrell & Saloner, 1985). It appears to have a significant impact on the willingness to adopt and the awareness of technologies (Mannan, Nordin, & Rafik-Galea, 2017).
To provide a clear meaning for the term "Effect on Adoption of other Innovation," it was replaced by the term "Expectation for Better Products" in some studies (Hosseini et al., 2016). In this study, we also used the latter term.
Resistance to innovation is dependent on the psychological characteristics of the consumer (Ram, 1987). In this study, we selected motivation because it was considered to provide more insights into consumer response variance to innovation (Barczak, Ellen, & Pilling, 1997).
The previous innovative experience of consumers also affects innovation resistance, and past experience plays an important role in shaping consumer perception and attitude formation (Ram, 1987). Hence, the attitude toward existing products was also selected in this study.
A green product is a product that is produced with the physical environment, such as air, water, and land in mind (Shrum, McCarty, & Lowrey, 1995). Gleim, Smith, Andrews, and Cronin, (2013) found that green product purchasing expertise plays a significant role in green purchasing decisions. Willingness to pay for organic food is positively related to organic food consumption (B. Chekima, K. Chekima, & K. Chekima, 2019). Moreover, the actual purchasing behavior of green products is positively influenced by their intention to buy green products (Testa, Sarti, & Frey, 2019). Hence, purchasing expertise and intention to buy green products are considered to influence consumer adoption of (or resistance to) Bio-CLF products, which are types of green products.

Hypotheses
We propose our hypotheses based on the innovation resistance model of Ram (1987) and previous research findings. The hypotheses are as follows.

Perceived Risk
Perceived risk is the risk associated with adopting the innovation, and can be of several types: physical risk, functional risk (performance uncertainty), psychological risk and social risk (Ram, 1987). In this research, the Perceived risk is defined as the safety risk in the case of Bio-CLF products. Based on past research, perceived risk has a positive effect on resistance to smart home services (Hong, Nam, & Kim, 2020). Some studies confirmed that perceived risk has a negative influence on the intention to use or adopt an innovation product (Martins, Oliveira, & Popovič, 2014;Yang, Liu, Li, & Yu, 2015;Yiu, Grant, & Edgar, 2007). Based on these previous studies, we hypothesize the following: Hypothesis 1: The higher the perceived risk of Bio-CLF, the higher the consumer resistance.

Complexity
A greater perception of complexity can lead to an aware individual refusing to acquire further information on new technologies and adopt these technologies (Vecchio, Agnusdei, Miglietta, & Capitanio, 2020). However, complexity in this study is defined as the process of purchasing the Bio-CLF product and whether it is easy to distinguish Bio-CLF products from their counterparts. Some studies have shown that complexity negatively affects the adoption of innovation products (Kousar, Sabri, Zafar, & Akhtar, 2017; Tan & Teo, 2000), which positively affects consumer resistance (Chouk & Mani, 2019;Mani & Chouk, 2018).
Hypothesis 2: The higher the perceived complexity of Bio-CLF, the higher the consumer resistance.

Motivation
Motivation is defined as "goal-directed arousal" that drives consumers need (Hosseini et al., 2016). Motivation for this research is defined as consumer motivation to purchase a Bio-CLF product. Ude and Diala (2015) found that there is a 0.446 increase in employee motivation for each one-point increase in support for innovation. Consequently, we hypothesize that motivation has a negative relationship with consumer resistance.
Hypothesis 3: The higher the consumer motivation regarding bio-CLF, the lower the consumer resistance.

Attitude toward Existing Products
Consumer experience with the use of a product affects consumer resistance to product innovation. For example, if consumers are satisfied with food irrigated using chemical fertilizer, liquid fertilizer, or organic fertilizer, they may consider that there is no need to buy food that was irrigated using Bio-CLF. This relationship was confirmed by (Hosseini et al., 2016), who found that the more positive the consumer attitude toward normal mobile phones, the higher the consumer resistance to mobile phones.
Hypothesis 4: The more positive the consumer attitude toward current food, the higher the consumer resistance to Bio-CLF food.

Purchase Intention
Purchase intention is based on whether a consumer has an intention to buy green rice, which consists of organic rice and rice grown without using or limited use of chemical fertilizers and pesticides. As mentioned above, if consumers have green product purchasing expertise, they may adopt and purchase Bio-CLF products, as Bio-CLF rice is also a type of green rice (strictly speaking, it is not defined as organic rice, but eco-friendly).
Hypothesis 5: The higher the consumer purchase intention toward green products, the lower the consumer resistance to the Bio-CLF product.

Knowledge
We use consumers' knowledge of organic fertilizer raw materials (Note 3) to measure knowledge. Understanding the information and gaining knowledge about green products will influence consumption behavior, as mentioned above.
Hypothesis 6: Consumers with knowledge of organic fertilizer raw materials will reduce their resistance to Bio-CLF.

Indirect Influence of Characteristics on Consumer Resistance
Previous studies have confirmed the relationship between compatibility, relative advantage, expectation of better products, and motivation. Reimer, Weinkauf, and Prokopy (2012) showed that the motivations for using different conservation practices were positively associated with relative advantages, compatibility, and observability (observing the practice's advantage). Compatibility and perceived relative advantages were associated with healthcare professionals' motivation to implement and continue a multidisciplinary primary care-based lifestyle intervention (Helmink, Kremers, Van Boekel, Van Brussel-Visser, & De Vries, 2012). The correlation between expectation and motivation was confirmed in a previous study (Wong, Cheung, & Wan, 2013). Additionally, Luo and Ye (2020) showed that tourists' expectations have a positive influence on motivation.
Consequently, relative advantage, compatibility, and expectation for better products may have an indirect influence on consumer resistance, as shown below.

Relative Advantage
A high level of perceived relative advantage means that innovation is considered to be a better option than its alternative based on an overall assessment made by the consumer (Wang, Yuen, Wong, & Teo, 2018). In this study, the relative advantage of Bio-CLF is defined as the advantage of Bio-CLF over chemical fertilizer. Consequently, we developed a hypothesis, according to (Reimer et al., 2012), by considering indirect influence.
Hypothesis 7. The higher the relative advantage of Bio-CLF, the higher the consumer motivation, which indirectly reduces resistance.

Compatibility
Compatibility is the degree to which society trusts that the invention is well matched with the old-style knowledge regarding "existing values, past experiences, and needs of the potential adopters" (Al-Rahmi et al., 2019). Compatibility helps the individual give meaning to the new idea, enabling it to be regarded as more familiar (Rogers, 2003). Joachim, Spieth, and Heidenreich (2018) showed that if a consumer perceives an innovation to be incompatible with past or existing products, compatibility barriers arise, and the compatibility barrier decreases the intention to adopt innovation. This means that compatibility decreases consumer resistance. The compatibility of Bio-CLF in this study is defined as the possibility of purchasing the Bio-CLF products instead of the more familiar and regularly-purchased products. Following the previous study (Reimer et al., 2012) and considering the indirect influence, we developed a hypothesis.
Hypothesis 8: The higher the perceived compatibility of Bio-CLF, the higher the consumer motivation, which indirectly reduces resistance.

Expectation for Better Products
In this study, we defined the expectation for better products as consumer expectations of future Bio-CLF products, which means that consumers wish Bio-CLF food will be more delicious, safer, and fresher with the progress of the Bio-CLF technology. Based on studies in different research contexts, positive attitudes toward organic food will positively influence consumer purchase intentions (Asif, Xuhui, Nasiri, & Ayyub, 2018;Bryła, 2016;Nuttavuthisit & Thøgersen, 2017;Slamet, Nakayasu, & Bai, 2016;Yadav & Pathak, 2016). In this study, the higher the consumer expectation of future Bio-CLF products, the higher their support for future Bio-CLF, and hence, the lower consumer expectation of the current Bio-CLF product and the higher their resistance to the current Bio-CLF product. According to Ram (1987) and Luo and Ye (2020), we developed another hypothesis.
Hypothesis 9: The higher the consumer attitude toward future Bio-CLF products, the lower the consumer motivation for the current Bio-CLF product, which indirectly causes higher consumer resistance to Bio-CLF products.

Research Model of Consumer Resistance to the Bio-CLF Product
Based on the hypothesis above, we constructed the theoretical model shown in Figure 3.

Data Collection and Sample Characteristics
We collected data through an Internet survey administered in Japan by the market-research company, Cross Marketing Inc. Data were collected from January 4 to 6, 2021. The target respondents were 20 years or older. The sample was collected from an individual enrolled in Cross Marketing Inc. Using random sampling, 1,000 in Tokyo, 500 in Osaka prefecture, and 500 in Fukuoka prefecture were finally stratified and extracted according to the age ratio of each local government.
To help respondents obtain an image of Bio-CLF, before questions, we used pictures to show the difference between the appearance of Bio-CLF and ordinary liquid fertilizer, and reveal the merits and demerits of Bio-CLF, and the materials of Bio-CLF. Under the pictures, we asked respondents, "Do you feel resistance to agricultural products cultivated using Bio-CLF in the pictures?" The consumers who answered "I don't feel resistance." were employed for the analysis. Finally, 703 samples were used in our research. Males occupied 56.2% of the cohort, and mean age was 44 years old.

Questionnaire and Measures
To measure the latent variables, we designed a questionnaire by referring to Hosseini et al. (2016); this questionnaire contained 33 questions. A Likert scale from 1 to 5 was used to measure the constructed variables, where, 1 = strongly disagree and 5 = strongly agree. Item loading is usually considered high if the factor loading is above 0.7 (Hair, Black, Babin, & Anderson, 2010). Hence, 28 questions were finally selected, and the components of each construct are shown in Table 1. Have you ever purchased organic rice that is not cultivated with chemical fertilizers or cultivated with less chemical fertilizers? 1 = "I have bought it and I still buy it" or "I have never bought it before, but I want to buy it". 0 = else. Note. Cronbach's alpha was 0.96. "Purchase Intention" and "Knowledge" are dummy variables. The factor loading of risk3 is 0.68, and half adjusted to 0.7, which was considered to be acceptable.

Source: Authors
The objective of our study was to analyze the causal relationships between innovation characteristic variables, consumer characteristic variables, and consumer resistance toward Bio-CLF products. Structural Equation Modeling (SEM) is a statistical technique for testing and estimating causal relationships based on statistical data and qualitative causal assumptions that can be used for analysis. Although the partial least squares (PLS) approach also fits our purpose, (Urbach & Ahlemann, 2010) suggested that when PLS approaches and SEM approaches can be applied, SEM should be used owing to the higher degree of validity of its results. Consequently, we used the SEM approach. We analyzed the data in R 4.1.0, and packages (GPArotation, lavaan, psych, psy, semPlot, semTools, tidyverse) were used.

Validity and reliability analysis
The validity and reliability of the model are shown in Table 2, which proves that our measurement model returned a good model fit. Note. *Reference values adapted from CFI (Bentler & Bonett, 1980), RMSEA (Hair et al., 2010), and TLI (Hu & Bentler, 1999). Table 3 shows the internal reliability of the model. The average variance extracted (AVE) was above 0.5 and construct reliability (CR) was above 0.7, which confirmed convergent validity and construct reliability according to (Hair et al., 2010). Half of the inter-correlations among the study constructs were smaller than the square root of the AVE values, which revealed that the discriminant validity of the model is acceptable. The results also revealed a high correlation between ADVANT, COMPA, EXPECT, and MOTIV.  Note. The values in the diagonal (bold) represent the square root of AVE, and the off-diagonals represent the correlations.

Structural Model
The results of the structural model showed that most of the hypotheses were supported, except H6 and H9, which were not significant (see Table 4). We confirmed that ADVANT and COMPA significantly affected MOTIV and indirectly influenced RESIST. MOTIV had a significant negative effect on RESIST. The structural model explained 40.8% variance in consumer resistance to the Bio-CLF product. Note. n.s. = not significant.

Discussion
In this study, we investigated the factors affecting consumer resistance to Bio-CLF products in Japan using IRT. Some factors were found to have a direct effect on RESIST as hypothesized, while some factors showed results that differed from those of the model of (Ram, 1987), which has an indirect effect on RESIST. The details are presented below.

Direct Influence Factors
H1 was supported. If consumers feel there is a risk associated with the purchase of the Bio-CLF product, they will resist it. This result is consistent with previous findings (Cheng, Lee, & Lee, 2014;Mohtar & Abbas, 2020;Ram, 1987). Hence, to reduce the degree of consumer resistance, it is useful to reduce consumers' perceived risk. For example, Bio-CLF food producers are suggested to disclose production information. For political makers, it is effective to have a monitoring system and a certification system. Certification systems affect consumer purchase behavior (Lee, Fu, & Chen, 2019).
H2 was supported. When consumers feel that it is complex to distinguish the Bio-CLF product from other green products or feel it is not easy to purchase this product from supermarkets or via the Internet, they will resist it. This result aligns with most available studies in different research contexts (Freeze & Schmidt, 2015;Hosseini et al., 2016;Kim & Bae, 2020;Mani & Chouk, 2018;Matsuo, Minami, & Matsuyama, 2018;Ram, 1987).  Vol. 14, No. 6; Consequently, it is important to reduce the complexity of the Bio-CLF product to reduce consumer resistance.
To distinguish Bio-CLF products from other green products, setting a specialized corner for Bio-CLF products is a considerable notion. For producers, designing a label sheet that is attractive to consumers and enable consumers to easily recognize that the product is irrigated by Bio-CLF is reasonable.
These results support H3, which is consistent with previous studies (Hosseini et al., 2016;Ram, 1987). Hence, to reduce consumer resistance, it is useful to increase consumer motivation to purchase Bio-CLF products. Due to the relationship between relative advantage (ADVANT), compatibility (COMPA), and motivation (MOTIV), the suggestions for increasing consumer motivation are shown in the next chapter.
H4 was supported. The more consumers are satisfied with the current food, the higher the consumer resistance to Bio-CLF food. The relationship between ATTITUDE and RESIST has also been shown in a previous study, and the effect has been confirmed (Hosseini et al., 2016). In Japan, there were two levels of cultivation methods: "Conventional cultivation," which uses chemically synthesized pesticides and is the traditional cultivation method in Japan; and "Reduced pesticide cultivation," which uses less than half the amount of chemically synthesized pest (Nishimura, 2021). According to different cultivation methods, conventional food, pesticide-reduced food, organic food, etc. were defined and are now available in the market. Therefore, if consumers are satisfied with their current food, they may resist Bio-CLF food.
The results support H5. Consumers who have higher purchase intentions toward green products will be less resistant to Bio-CLF products. As mentioned above, green product purchasing expertise plays an important role in consumer purchase behavior (Gleim et al., 2013;Testa et al., 2019). Consequently, for supermarket managers, placing the Bio-CLF product alongside other green products, such as organic products, is a good approach to attract green consumers. Producers should ensure the Bio-CLF product appears appealing as a green product. For the Bio-CLF developer, advancing the Bio-CLF technology and acquiring JAS organic certification of Bio-CLF product are feasible.

Indirect Influence Factors
These results support H7 and H8, and are consistent with those of previous research (Helmink et al., 2012;Luo & Ye, 2020;Reimer et al., 2012;Wong et al., 2013). Based on the results, to reduce consumer resistance, it is important to improve consumer motivation to purchase Bio-CLF products. According to the definition of ADVANT and COMPA in this study, to improve consumer motivation to purchase Bio-CLF products, it is suggested that Bio-CLF product producers have the relative advantages of Bio-CLF over chemical fertilizer. For example, compared with chemical fertilizer, Bio-CLF contributes to the improvement of the environment due to the use of organic waste, such as waste milk, raw garbage, manure, etc. Compared with ordinary liquid fertilizer, it contains the adjusted ingredients that the crops need; hence, it may be more delicious. It is also necessary to show the compatibility of the Bio-CLF product with the current product. Taking Bio-CLF rice as an example, the producer should ensure that the quality matches the expectation of consumers. Hence, the creation of a certification system for Bio-CLF products to guarantee quality is suggested.

Conclusion
Although the fertilizer spread cost of farmers may be reduced and the use of Bio-CLF may expand with the development of Bio-CLF, this innovation suffers from consumer resistance. To date, IRT has been applied in many fields. However, research on "agricultural products," especially on "liquid fertilizer" is rare. The findings of this study fill this gap. In this study, we used IRT to determine the underlying reasons for consumer resistance to Bio-CLF products. A total of 2,000 samples were collected from three populous cities, such as Tokyo, and 703 samples were finally used for the analysis.
Perceived risk, complexity, and attitude toward existing products have a positive and direct impact on consumer resistance to Bio-CLF products, while motivation and purchase intention have negative and direct impacts on consumer resistance to Bio-CLF products. Notably, relative advantage and compatibility have a positive impact on motivation and indirectly influence consumer resistance to Bio-CLF products, which is inconsistent with the IRT model of (Ram, 1987).
To reduce consumer resistance to Bio-CLF products and expand the usage of Bio-CLF, we provide some advice for market managers, producers, political makers, and Bio-CLF developers. We suggest that market managers: (1) allocate a specialized corner for the Bio-CLF product and (2) place the Bio-CLF product alongside other green products. For producers, we suggest the: (1) disclosure of production information; (2) design of an attractive and clear label sheet; (3) proving the advantage of Bio-CLF and that the Bio-CLF product is a green product. For political makers, we suggest that it is effective to have a monitoring system and a certification system for Bio-CLF products. For Bio-CLF developer, advancing the Bio-CLF technology and acquiring JAS organic certification of Bio-CLF products are suggested for the future.

Limitations and Future Work
This study had certain limitations that should be addressed by future researchers. The first limitation was the lack of generalization of the study results. The study samples were obtained from three major cities; therefore, the representation of consumer resistance to Bio-CLF is limited. Future studies should use a wider research area. Second, the study used cross-sectional data, which failed to determine the dynamic nature of consumer behavior. Hence, future research should conduct a longitudinal study to overcome this limitation.