Analysis of Factors Affecting Purchase Intention on Smart Portable Garden in Indonesia: PLUS Study Case
Arya Putra Widianto1*, Arfenia Nita1
1 School of Business and Management, Institute Technology Bandung, Bandung, Indonesia
*Corresponding Author: [email protected] Accepted: 15 August 2022 | Published: 1 September 2022
DOI:https://doi.org/10.55057/ajrbm.2022.4.3.2
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Abstract: During mobility restrictions to prevent the COVID – 19, people tend to start new hobbies to eliminate boredom and one of the hobbies is urban farming. Refer to Amanda (2021), urban farming increase is represented by the increase of seed sales that reach five times during pandemic. According to the researcher’s preliminary survey, the newbie urban farmer hobbyists faced issues such as lack the time, knowledge, and proper space to do urban farming properly. Therefore, the researcher and team develop a portable smart garden that is supported by internet of things technology to solve the newbie urban farmer’s problem. Global market of the smart portable garden is growing but in Indonesia the similar products still not popular. Hence, research about purchase intentions toward smart portable gardens in Indonesia is conducted to grab the opportunity for related products in Indonesia. This research adapts the theories that project the customer purchase intention. Current research implements quantitative research methods through questionnaire distribution and analysis using PLS - SEM. Study result shows that purchase intention influenced by customer attitude, product pricing, perceived behavioural control, and environmentally conscious purchasing. Current research is expected to help entrepreneurs develop their businesses.
Keywords: Urban Farming, Purchase Intention, Environmentally Conscious Purchasing ___________________________________________________________________________
1. Introduction
COVID – 19 Pandemic generates problems and one of them is food security issues. Mobility restrictions to prevent the COVID – 19 spreads led to inhibition of domestic and global food supply chains. The Indonesian Government has already made several efforts to maintain food security through the food estate program. The Food Estate program is integrated food resources development by grouping the plantation and animal farms in one area. However, the proposed program still faces several issues (CNN Indonesia, 2021). Mobility restrictions policy led to the emergence of new hobbies in society such as urban farming. Locals do urban farming in the pandemic era to entertain themselves in their spare time. Besides making urban farming a hobby, urban farming also gives economic benefits to the society, provides healthier food source, and some urban farmers also utilize this hobby as a side income stream. (Nursantio et al., 2020) Urban farming industry is also on its growth stage especially in the pandemic and post - pandemic era. It could be seen if urban farming is in its positive trend by looking at seed sales that increased five times than before the pandemic came up (Amanda, 2021). Urban farming industry prospects also could be seen from MarkPlus survey in 2020 that conducted to random 110 respondents in Indonesia states that 43% of them already did urban farming and
92.7% of respondents that already did urban farming will continue it until the post - pandemic era.
The Indonesian Government also supports the urban farming activity and encourages the locals to do it by initiating several programs. Government Programs that push the people to start urban farming activity are Buruan SAE programs initiated by DISPANGTAN Bandung. Buruan SAE is an integrated urban farming program to increase local food security by utilizing available space at home as a growing area (Andriyawan, 2021).
According to preliminary study that conducted to random 37 urban farmer hobbyists through communities by researcher, they are facing issue in urban farming including lack of time, knowledge, and proper space to maintain their plants and smart portable garden is a solution to their problems. However, in Indonesia itself, there are only a few similar products with the PLUS planting kit that has been marketed throughout the country. Those similar competitor products also weren't as popular as hydroponic, aquaponic, and potted plants that are popular in Indonesia (Wigraha, 2020). In Europe, there are various choices of smart portable gardens with automatic watering systems like the PLUS planting kit such as Noocity portable garden.
There are also similar products but enhanced with grow light such as Aerogarden and Click&Grow that are marketed in the United States, Europe, South Africa, Singapore, and Hong Kong. According to Shi (2021), those products are popular because they could solve farming limitations in urban areas due to the population density and gain aesthetic value of the residence. Emergenresearch (2022) projected the market size for smart garden products is up to 110.2 million USD with a CAGR of 8.2 percent. Based on the circumstances, there is an opportunity for smart portable garden products to be popular in Indonesia and research analyzing factors that influence the purchase intention of smart portable garden in Indonesia is one action to grab and validate the opportunity.
2. Literature Review
Purchase Intention
Purchase intention refers to probability of a customer willing to purchase certain products (Doods et al., 1991). Determining the factors which are affecting the purchase intention is important to assess the customer’s expectation (Xiao et al., 2019). Assessing purchase intention is an important thing for businesses since it was a significant tool in forming competitive advantage of firm although it is difficult to determine (Kasornbua et al., 2019). One of the factors that has positive relationship toward purchase intention is attitude (Tamin et al., 2015).
It also proven that attitude has positive influence on purchase intention through study in organic products (Kozup et al., 2013). Purchase intention also influenced by price of a product, and it’s proven in study of economic and ecological benefits of hydroponic products (Balqiah et al., 2020).
Environmentally Conscious Purchasing
Maineiri et al. (1997) mentioned several terms in their study that have identical definitions with
“green consumption” and “environmental conscious purchasing” is the most similar term with green consumption. Monhemius (1993) concluded if the term can be understood as the knowledge of customers about environmental effects from individual buying decisions and consumption behavior, whereas “green consumption” could be given if predominantly environmentally friendly and sustainable products are purchased and the products that ignore the environmental and society negative consequences are avoided. Peattie (1992) discussed if a product could be categorized as a green product when a certain product could give significant
improvements in production, consumption, and disposal to give favor to the environment compared to non – green products. Referring to the studies mentioned above, PLUS Planting Kit is considered as an environmentally friendly product. Jaiswal and Kant (2018) confirmed a positive and significant impact of environmental concern on the attitude towards green products.
Theory of Planned Behavior
According to Bagher et al. (2018), Theory of Planned behavior explains if individuals’ actual behavior as a central factor is directly caused from the behavioral intention and perceived behavioral control (PBC). Perceived behavioral control could be defined how individuals could control their behavior such as ease or difficulties to perform certain action based on the experience and anticipates the consequences from the conducted action (Balqiah et al., 2020).
Retrieved from the research conducted by Balqiah et al. (2019), various name of researchers applies Theory of Planned Behavior to find out factors that influences the purchase intention for hydroponic product purchase intention, green products (Emekci et al., 2019), green restaurant (Tommassetti et al., 2018), organic food (Pandey et al., 2019), and energy-saving sense (Lin et al., 2020).
Conceptual Framework
H1: Consumer attitude has positive impact toward purchase intention on PLUS Planting Kit H2: Price has significant impact on PLUS Planting kit purchase intention
H3: Environmentally Conscious Purchasing has positive impact on PLUS Planting Kit Purchase Intention
H4: Perceived behavioral control has positive impact on the Purchase intention of PLUS Planting Kit
Figure 1: Conceptual Framework of the Research
3. Methodology
Research data is collected using quantitative method by distributing online questionnaires.
Quantitative research methods offer advantages which are not influenced by personal opinions at considering and representing research and fact, eases data processing for large amounts of
data, less difficult data comparison, and possibility for quantitative valuation indicators development (Yannis and Nikolaos, 2018). Online questionnaires offer advantages including cost efficiency, time saving, and wider range of survey participants (Sekaran and Bougie, 2016). Questions that will be distributed to the respondents will ask about the information of attitude, buying preference, and their considerations before purchasing portable garden products for urban farming activities. Survey will be conducted using Bahasa Indonesia through Google Form platform since the respondent targets are relevant with the PLUS target market which are lives in Indonesia. Questionnaires distributed through social media and instant messaging platforms. Current study utilizes 5 - point likert scale to which are score of 5 represents strongly agree perspective and score of 1 represent the opposite (strongly disagree) perspective to a circumstance (Albaum, 1997). Previous research that also analyzes attitude, perceived behavioral control, and purchase intention utilizes 5 - point likert scale measurement and validated as reliable measurement method (Talwar et al., 2020). Total 5 – point likert scale questions that distributed in current study is 17 questions.
Sampling method that used by the researcher is non – probability purposive sampling because it eases the generalization of the sample that involved in the study (Sharma, 2017). Target respondents that are relevant with PLUS target market which are male or female aged 17 – 65 that are interested in or have ever done urban farming that lives in Indonesia. Referring to the previous studies, the minimum sample size for marketing research will be 200 respondents (Malhotra, 2010).
Obtained research data will be analyzed using Partial Least Square - Structural Equation Modeling (PLS - SEM). Refer to Hair et al. (2011), Structural equation modeling massively applied in various scientific fields including management, marketing, and psychology.
However, Herman Wold (1982) developed a structural equation modeling with much greater flexibility namely Partial Least Square Structural Equation Modeling (PLS - SEM) and methodologists referred to measure model confirmation using PLS - SEM (Hair et al., 2020).
Before data analyzed, validity test required to check if indicators measure what is meant to be measured (Field, 2005), reliability test to examine consistency performance of the data (Said, 2018), and avoid collinearity issues (Hair et al., 2013). After conducting PLS – SEM calculations, the researcher assesses Path Coefficient R – Squared, F – Squared, Q – Squared, T – Value, and P – Value score of each construct.
4. Result and Discussion
Number of respondents that meet the criteria which are people who already did urban farming or have interest toward urban farming is 201 people that shortlisted through a filter question from total of 217 respondents.
Respondent Profile
From 201 respondents, 67% of total respondents or 134 of them are male and 67 respondents are female. Surprisingly, males are more likely to do urban farming than female. Respondents of the study consists of 76 respondents with 41 – 65 years old, followed by 69 respondents with 26 – 40 years old and the rest 56 are 17 – 25 years old. Gen X’s are more likely to interested with urban farming because most of them are near of retirement period and seeking activities to fill the time. Based on domicile, 84 respondents come from Surabaya Raya area that’s consist of Surabaya, Gresik, and Sidoarjo, 34 Respondents from Bandung, and 30 from Jabodetabek with the rest 53 of them come from various cities in Indonesia. From the result, Smart Portable Garden or similar products may offered to those three regions first.
Reliability and Validity Test
Reliability test is conducted to determine the consistency of measurement indicators. Current study conducted both indicator reliability and internal consistency reliability. Indicator reliability confirms the measurement indicators are consistent (Urbach and Ahleman, 2010).
Indicators should be considered reliable if the Outer Loadings value greater than 0.7 (Wong, 2013). Based on indicator reliability testing, PR1 which are an indicator to measure Price latent variable was removed because of the PR1 Outer Loadings value is 0.337 which means under 0.7. Removing unreliable indicator is necessary to keep the validity of indicators (Joe et al., 2011). After running the indicator reliability test, internal consistency reliability conducted by assessing the Cronbach’s Alpha and Composite Reliability value of the constructs. Cronbach’s Alpha of all variables greater than 0.6 and composite reliability score also higher than 0.7 which means the variables pass the reliability testing. Score of Cronbach’s Alpha should be higher than 0.6 to pass reliability test (Hair et al., 2018). Indicators considered as reliable if the composite reliability value higher than 0.7 (Wong, 2013).
Necessity of validity test is to ensure if the questions measure what is meant to be measured (Field, 2005). Data could be considered valid if they passed convergent validity test through ensuring if Average Variance Extracted score of the data is greater than 0.5 (Wong, 2013).
Discriminant validity test also conducted to ensure the validity test by finding out if the square root of the AVE coefficient in each variable greater than the correlations with the other latent variables (Wong, 2013). Collected data of current study already passed both convergent and discriminant validity
Collinearity Test
Collinearity could be defined as a situation when two or more predictor variables are linearly related (Alin, 2010). Collected data is determined has no collinearity issues if the VIF value of each indicator is less than 5 (Hair et al., 2013). All indicators in current study passed the collinearity testing with the highest VIF value score of 2.674 from PB3 indicator that measures Perceived Behavioral Control.
Descriptive Analysis
Descriptive analysis summarizes the overview of the study result. Environmentally Conscious Purchasing has the highest mean among all variables. This circumstance represents if the respondents purchase intention toward smart portable garden or similar products is highly influenced by their environmental awareness. Price has the lowest mean of 3.828 which represents if price has lowest effects toward respondents purchase intention toward smart portable garden products among other variables. Attitude has the highest standard deviation which means the respondents have various perspectives in attitude towards smart portable garden purchase intention.
Table 1: Descriptive Analysis Result of The Study
Variable N Mean Min Max Standard Deviation
Attitude 201 3.834 1.000 5.000 0.658
Price 201 3.828 1.000 5.000 0.642
Environmentally Conscious Purchasing 201 4.152 1.000 5.000 0.535 Perceived Behavioral Control 201 4.106 2.000 5.000 0.637
Purchase Intention 201 3.955 2.000 5.000 0.615
Structural Path Significance
In assessing the model quality of PLS - SEM data analysis, there are several coefficients that should be considered including Path Analysis coefficient, coefficient of determination (R2), predictive relevance (Q2), p - values, and t-values. Relationship in the model is considered significant if the t - value is greater than 1.96 and p - value is less than 0.05.
Figure 2: PLS – SEM Result
Table 2: Path Coefficient, Variance Explained, and Stone – Geisser
Structural Path Path
Coefficient
R - Squared
Q - Squared
Attitude → Purchase Intention 0.246 0.570 0.310
Price → Purchase Intention 0.191
Environmentally Conscious Purchasing → Purchase Intention
0.373
Perceived Behavioral Control → Purchase Intention 0.132
R2 coefficient ranges between 0 to 1 depending on how good the prediction accuracy of dependent variable (Hair et al., 2014). Current analysis shows the R2 value of Smart Portable Garden purchase intention is 0.570 and it means if the latent variables namely Attitude, Price, Environmentally Conscious Purchasing, and Perceived Behavioral Control explains 57% of the variance in Purchase Intention for Smart Portable Garden products. Based on the rule of thumb by Hair et al. (2013), coefficient of determination (R2) in current research is categorized as
moderate. Q2 value of the model is 0.310 which means the model has predictive relevance because Q2 value is higher than 0 (Hair et al. 2017). In SmartPLS software, Q - squared value could be obtained through running the blindfolding calculation.
F - Squared (Effect Size)
F - squared value used to measure the strength of the latent variables’ relationship (Wong, 2013). Besides evaluating the variables’ significance in the model, it is also necessary to measure the effect size between the variables’ (Chin, 1996). Refer to Cohen (1992), effect size or F - squared value is categorized into small with value of 0.02, 0.15 for medium, and big size effect if the value greater than 0.35. F - squared calculation result could be seen on Table 3
Table 3: Effect Size of Each Variable
Purchase Intention
Attitude 0.077
Price 0.050
Environmentally Conscious Purchasing 0.184
Perceived Behavioral Control 0.025
From Table 3, Attitude to Purchase Intention, Price to Purchase Intention, and Perceived Behavioral Control to Purchase Intention has weak effect size. Environmentally Conscious Purchasing to Purchase Intention has medium effect size.
Hypothesis Testing
Next step is testing the hypothesis through assessing the T - Values, P Values, and Path Coefficient that are shown on the table 4
Table 4: Hypothesis Testing Results
Hypothesis Structural Path Path
Coefficient T Values
P Values
Result
H1 Attitude → Purchase Intention 0.246 3.864 0.000 Accepted
H2 Price → Purchase Intention 0.191 3.164 0.000 Accepted
H3 Environmentally Conscious Purchasing → Purchase Intention
0.373 5.293 0.037 Accepted
H4 Perceived Behavioral Control → Purchase Intention
0.132 2.090 0.002 Accepted
The researcher runs a bootstrapping calculation method to obtain t - values and p - values to evaluate the significance of path coefficients.
H1. Attitude has a significant positive influence toward Purchase Intention
This hypothesis states that attitude has a significant positive effect on purchase intention of Smart Portable Garden product. Hypothesis 1 is accepted due to its t - value that reaches 3.864 which means that it is greater than 1.96. P value of Hypothesis 1 is 0.000 which means that
lower than 0.05 and it could be concluded that Attitude has significant positive influence toward Purchase Intention.
H2. Price has a significant positive influence toward Purchase Intention
Hypothesis 2 of current research is that price has a significant influence on purchase intention.
According to the bootstrap calculation, the t-value of this hypothesis is 3.164 which means that is greater than the critical value at 1.96 and p-value results also 0.000 which is also lower than 0.05. Path coefficient of the hypothesis is also positive with a value of 0.191. Therefore, hypothesis 2 is accepted
H3. Environmentally Conscious Purchasing has a significant positive influence toward Purchase Intention
Hypothesis 3 is Environmentally Conscious Purchasing has a significant positive influence on Purchase Intention. H3 is accepted since the t - value of this hypothesis is 5.293 which means that it is higher than 1.96 or passed the critical value and the p - value is 0.037 which means that it is lower than 0.05. Path coefficient of the current hypothesis is also positive with a value of 0.373.
H4. Perceived Behavioral Control has a significant positive influence toward Purchase Intention
Hypothesis 4 stated if Perceived Behavioral Control has a significant positive influence toward Purchase Intention. After running the bootstrapping calculation, the t - value of hypothesis 4 is 2.090 which means that is higher than the critical value of 1.96 and p - value is at 0.002 which means that is lower than the critical value of 0.05. Hypothesis 4 also has a positive coefficient path with a value of 0.132.
Discussion
Objective of the current study is to find out which factors that could affect the purchase intention of smart portable garden products in Indonesia. During the conduction of this research, the similar products with the smart portable garden are less popular than other urban farming methods namely hydroponic, aquaponic, vertical garden, and verticulture. Although smart portable gardens are less popular, the global market size is predicted to be emerging.
Hence, the author identifies an opportunity during the situation and finds out the factors that affect the purchase intention of smart portable gardens to Indonesian people that already do urban farming or interested in urban farming.
Current research findings show that purchase intention toward smart portable garden products is influenced by four variables. All the variables are attitude, price, environmentally conscious purchasing, and perceived behavioral control which all of those factors have a positive influence on smart portable garden purchase intention because according to PLS - SEM calculation those hypotheses passed the t - value, p - value, and path coefficient critical values.
Detail of hypothesis testing result is explained below:
Attitude has a positive influence toward Purchase Intention
Based on the effect size calculation, attitude is the second variable that has influence toward the Purchase Intention. Current research shows similar results with the Tamin et al. (2015) statement. Hartmann and Apaolaza-Ibáñez (2012) in their study of green energy brand purchase intention also shows a positive relationship between attitude and purchase intention. Attitude measures how strong is consumer knowledge and favorableness toward a product. From this result, it could be seen if people that have ever done urban farming or have interest toward
urban farming already have knowledge about smart portable gardens or its related products and liked the product.
Price has a positive influence toward Purchase Intention
According to the analysis, Price has the third contribution toward purchase intention of the smart portable garden product. Since the research shows if price didn’t become the factor that has the highest influence, Smart Portable Garden products could be offered with higher price than its substitutes. However, price also still has a significant impact toward customer purchase intention so that the quality and benefits still have to in line with the price increase. It is also supported by Eicchorn and Mexner (2020) statement if a product will be purchased only when its benefit is greater than the price that is paid.
Environmentally conscious purchasing has a positive influence toward Purchase Intention
Environmentally conscious purchasing has the highest influence on Smart Portable Garden purchase intention which is shown by its high effect size score. It could be concluded that PLUS target market which are people who have ever done urban farming or interested in urban farming care with the environment. Tamin et al. (2015) shows if environmentally care customers believe purchasing the environmentally friendly product could help protect the environment. This circumstance encourages the Smart Portable Garden makers to focus on gaining environmental benefit for their product and market them as an environmentally friendly product.
Perceived behavioral control has a positive influence toward Purchase Intention
Current research shows that perceived behavioral control has a positive influence on Purchase Intention. Although, this variable has the least significant influence on purchase intention compared to other three constructs. Refer to Balqiah et al. (2020), Perceived Behavioral Control could be defined as how individuals could easily control their behavior to perform certain actions. Research by Pandey et al. (2019) also shows significant positive influence of perceived behavioral control toward purchase intention. It could be concluded that respondents' intention toward smart portable garden products is significantly affected by their behavior but other factors such as price, attitude, and environmentally concerned purchase have higher influence. In the future, Smart Portable Garden products should be offered with easy and user- friendly purchasing methods.
5. Conclusion and Managerial Implications
Current study concludes if there are four factors that influence the smart portable garden products purchase intention. Four variables that influence the smart portable garden purchase intention are attitude, price, environmentally conscious purchasing, and perceived behavioral control. Based on the r – squared calculation, those four factors represent 57% of variables that influence the smart portable garden purchase intention while the remaining 43% projected by other variables that not tested in this study. Based on f – squared calculation result, factors or variables that tested in current research has low to moderate effects to the customers’ purchase intention. Environmentally conscious purchasing has the highest effect size that followed by attitude, price, and last is perceived behavioral control.
Managerial Implications
Environmentally conscious purchasing become the variable that has highest effect to the product purchase intention. PLUS should highlight the environmental benefits of its product
on their marketing activities. Besides on marketing, PLUS Planting Kit also should bring environmental benefits as well as water saving and contribute to reduce carbon footprint from vegetable distribution. Mentioned benefit could be achieved by increasing vegetable productivity from PLUS planting kit. Second factor is attitude influences smart portable garden purchase intention. Positive attitude toward the PLUS Planting Kit could be formed by delivering product knowledge to the target market. Engaging marketing activities as well as product demonstration in green communities and product review by key opinion leaders could be considered to build positive attitude toward the PLUS Planting Kit product. Price also significantly influenced the purchase intention. Hence, making the Planting Kit with greater benefits and feature than offered price is important to increase the purchase intention.
Entrepreneur should identify the price to benefits that offered by their competitors and bring product that has greater value for money than the competitors. Last is perceived behavioral control or ease of a customer to conduct certain activities. PLUS could make their product easy to use by the customer and bring the easy purchasing process for its customers.
Limitations and Future Research
Current research has limitations as well as involved respondents are dominated by samples from Surabaya Raya, Bandung, and Jabodetabek. It may lead to the result will not be representative to other cities especially less – developed cities. Market for smart portable garden in Indonesia also still limited that shown by only few companies that sell similar products. Future research may lead to different result due to market conditions change.
Further research is expected to adopt different sources of information compared to current study and reach larger geographical approaches. Different research approaches as well as qualitative research through interview with the experts also suggested for further study.
Another variables or factors that influences the purchase intention also expected to be discovered in the future similar research.
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