THE INFLUENCE OF TRUST, PRODUCT QUALITY AND PRICE PERCEPTION ON PURCHASE DECISIONS MEDIATED BY PURCHASE INTENTION

Sihat Aji Wardoyo

Pancasila University Jakarta, Indonesia

Abstract :

Indonesia has abundant natural resources, especially natural gas. However, using natural gas to meet household needs has yet to be utilized optimally, one of which is in Tarakan City. This research aims to determine the influence of trust, product quality and price perception through purchase intentions on purchasing decisions directly and indirectly. This research uses primary data with the data source distributing questionnaires via Google Forms. The data analysis technique uses Structural Equation Modeling (SEM) analysis, processed with SmartPLS version 3 software. The research results prove that the trust variable positively and significantly affects purchase intentions. The product quality variable has a positive and significant effect on purchase intentions. The price perception variable has a positive and significant effect on purchase intention. The purchase intention variable has a positive and significant effect on purchasing decisions. The trust variable does not affect purchasing decisions. The product quality variable does not affect purchasing decisions. The variable price perception through purchase intention does not affect purchasing decisions. From the results of the blindfolding analysis, results were obtained that showed good prediction accuracy with low criteria (0.02 ï¿½ 015). The results of the model suitability analysis show that the suitability level for this research model is 63%.

Keywords: Product Quality, Price Perception, Purchase Intention, Purchase Decision.

Appropriate: Healthy Aji Wardoyo

Email: [email protected]

INTRODUCTION

ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ Indonesia has abundant natural energy sources in the form of gas. However, these natural energy sources have yet to be utilized optimally (Sidik & Akbar, 2021). Natural gas has a critical position as the country's third most widely used primary energy after petroleum and coal, supporting people's lives and driving the Indonesian economy (Rahman, Dargusch, & Wadley, 2021 (Rahman, Dargusch, & Wadley, 2021). Unsurprisingly, it is a priority for the Government to develop infrastructure networks so that natural gas utilization can be maximized (Golara & Esmaeily, 2017).

One of the reasons for the low buying interest of potential natural gas network customers is that people need to be sure or believe in the continuity of gas supply or product quality if they use natural gas pipeline networks. People still perceive that prices are more expensive than using LPG. Another thing that is expected is to develop a company strategy to carry out more effective promotions. For example, to convince potential customers that natural gas is safe to use for daily needs and the price is low so that it can increase public trust, which can increase the attractiveness of potential customers.

The Government is building a natural gas infrastructure network for households because business entities are not interested in building it due to the lack of profit from managing it. (Sovacool & Del Rio, 2020). Therefore, it is hoped that local governments can participate and make their areas into gas cities in the future (Mahyuni & Syahrin, 2021). The implementation of the construction of the household gas network in Tarakan City, North Kalimantan Province, was carried out by the National Gas Company (PGN), which started in 2010 with a total of 3,366 customers until 2020 with a total of 34,145 household connections. Compared with the number of households in Tarakan City, which reached 64,135, they have not been utilized optimally, namely only 53%. On the other hand, natural gas resources are still very abundant, even enough to be used by all households in Tarakan City (Murtilaksono et al., 2023).

Trust is also a factor that can influence purchasing decisions (Kim, Xu, & Gupta, 2012). Trust is defined as a subjective possibility where consumers expect sellers to carry out certain transactions according to consumer trust expectations (Retnowati & Mardikaningsih, 2021).

Apart from the trust that influences purchasing decisions, other factors influence it, namely the quality of the product being marketed (Pop, Săplăcan, Dabija, & Alt, 2022). According to research, product quality is a potential strategic weapon to defeat competitors. The ability of product quality to demonstrate various functions, including durability, reliability, accuracy, and ease of use (Melati, Rachbini, & Rekarti, 2021).

Price perception is also another factor that can influence purchasing decisions. Price perception can be a consideration for consumers to influence the decision to purchase a product (Widyastuti & Said, 2017).

According to researchers, consumer trust is all the knowledge consumers have and the conclusions consumers make regarding objects, attributes and benefits (Agesti, Ridwan, & Budiarti, 2021). According to other researchers, consumer trust is a company's willingness to rely on its business partners (Pertiwi, Nurbaity, & Absah, 2021). There are several dimensions and indicators to determine consumer trust. According to Kotler and Keller (2016), there are four indicators of consumer trust: virtue, ability, integrity, and willingness to defend (Windiarti & Suwandi, 2022).

Product Quality

Product quality is one of the keys to competition between business actors offered to consumers. According to researchers, product quality is the ability of an item to provide results or performance that match or even exceed what customers want. ï¿½(Rachmawati & Santika, 2022)Based on the definition above, product quality is the ability of a product to fulfil consumer desires. Consumer desires include product durability, reliability, ease of use, and other valuable attributes free from defects and damage.

Price Perception

According to researchers, the perception of price fairness is defined as assessing a result and how a process will obtain an acceptable result and, of course, reasonable (Benetti Corrï¿½a da Silva, Matte, Bebber, Libardi, & Fachinelli, 2022). According to subsequent research, price perception is related to how price information is fully understood by consumers and provides deep meaning for them (Prakoso & Sugiharti, 2020). Meanwhile, according to other researchers, price perception is the sum of all the values customers give to obtain benefits from owning or using a product, both goods and services (Saragih, 2023).

Purchase Intention

Consumer purchase intention is when consumers determine their choice between several brands included in the choice set (Rodgers & Nguyen, 2022). Purchase intention is the tendency to buy a brand and, generally, is based on purchase motives by the attributes or characteristics of the brand being considered (Pangaribuan & Maulana, 2019). Meanwhile, according to researchers, purchase intention is consumer behaviour that occurs when external factors stimulate consumers to buy based on personal decision characteristics and decision-making processes (Hamzah & Tanwir, 2021)

Buying decision

The researchers revealed that the purchasing decision process consists of problem recognition, information search, alternative evaluation, and purchasing decisions (Al-Abdallah, Khair, & Elmarakby, 2021). Decision-making is critical to pay attention to because it is a process of actual purchasing after searching for information, identifying problems, and evaluating alternatives so consumers can decide whether to purchase. According to research, purchasing decisions are consumer decisions that are influenced by financial economics, technology, politics, culture, products, prices, locations, promotions, physical evidence, people, and processes.

Conceptual framework

This research has five variables consisting of three independent variables, one dependent variable, and one intervening variable. In this research, trust is determined to be the independent variable one (X1), Product Quality is the independent variable two (X2), and Price Perception is the independent variable three (X3). Purchase Decision is determined as the dependent variable (Z), and the Intervening variable (Y) is Purchase Intention.

Hypothesis Development

The Influence of Trust on Purchase Intention

Trust is defined as "The willingness of a party to be susceptible to the actions of another party" based on the expectation that the person entrusted with the mandate will perform specific actions that are important to trust, regardless of the ability to monitor or control the other (Ford, Piccolo, & Ford, 2017) Trust is the willingness to rely on an exchange partner (a person who is reliable and keeps promises) (R. Ladhari, 2017). This research shows that trust in a product dramatically influences potential consumers' purchasing intentions. Meanwhile, purchase intention will be low if a product does not gain trust.

The Influence of Product Quality on Purchase Intentions

Products have quality value not from the producer but from the consumer. Hence, the person who has the right to judge whether the product purchased and consumed meets initial expectations is the consumer himself. Based on previous research conducted by researchers, product quality has a positive and significant effect on purchase intention (Asshidin, Abidin, & Borhan, 2016). This is also in line with research conducted by other researchers, which shows that product quality variables significantly influence purchase intentions, especially among respondents in Manado City, and the influence is positive (Sondakh, Tumbuan, & Wangke, 2022).

The Influence of Price Perceptions on Purchase Intentions

Researchers define price as the amount consumers are willing to spend to purchase a product or service, including monetary and non-monetary goods. Thus, end consumers are more likely to purchase products whose prices are seen as cheap or reasonable. ï¿½(Yao, Oppewal, & Wang, 2020). However, consumers' perceptions of high and low prices are subjective and based on the value they receive from the product compared to the price they pay.

The Influence of Trust on Purchasing Decisions

In all buying and selling processes, trust is the primary key in all business forms, both online and offline. In this era of internet technology, which is full of openness, all prospective buyers can get detailed information about the goods/services they want to buy. However, on the other hand, this openness also requires business owners to always be vigilant. Because, with information disclosure, the slightest error can be immediately known by everyone, which can indirectly give a bad image or impression to a business.

The Influence of Product Quality on Purchasing Decisions

Product quality illustrates the extent to which a product can meet consumer needs. According to research, the results show that product quality positively and significantly influences purchasing decisions. Thus, the better the product quality, the better the consumer's purchasing decisions.

The Influence of Price Perceptions on Purchasing Decisions

Referring to the theory put forward by researchers, price is one factor that influences purchasing decisions apart from other factors such as financial economics, technology, politics, culture, products, location, promotions, physical evidence, people, and processes (Wirtz & Lovelock, 2021). So, people's price perception of a product is a determining factor for potential buyers to purchase.

The Influence of Purchase Intentions on Purchase Decisions

Referring to the theory put forward by researchers, purchase intention is a tendency and desire that encourages individuals to buy a product. Research shows that purchasing intentions positively and significantly influence purchasing decisions (Mauri & Minazzi, 2013)

RESEARCH METHODS

The design of this research is quantitative. This research was conducted in Tarakan City, North Kalimantan. This research period was carried out from April to July 2023. The population in this research is residents who still need to be customers of the gas network in Tarakan City, North Kalimantan, around 29,990 families. Based on data released by the Director General of Oil and Gas from 2010 to 2021, the number of customers is 34,145 household connections. It is estimated that there will still be additional additions until the data collection for this research. This research requires 395 respondents. The most dominant data of respondents are men (63%) and women (37%), with the dominant age category between 31 ï¿½ 50 years (65%), with D3/S1 education, which is very dominant. Level (57%), with the most dominant residence in East Tarakan District (33%).

RESULTS AND DISCUSSION

Results of respondents' descriptive answers It can be identified that most respondents were men (63%). In comparison, women accounted for 37% of the total respondents. Most respondents were in the 31-50 year age group, making up 65%, while the 20-30 year and over 50 year age groups accounted for 20% and 15%, respectively. Most respondents had a D3/S1 educational background, with 57% of the total respondents, while only 0.2% had a Masters/S3 education level. In terms of location, the most dominant place of residence is in East Tarakan District, with 33% of the total respondents, followed by West Tarakan District (24%), Central Tarakan District (23%), and North Tarakan District (20%).

Measurement Model Testing (Outer Model)

An indicator is categorized as good and has met convergent validity if it has an outer loading value > 0.70 ï¿½(Hair Jr, Howard, & Nitzl, 2020). The composite reliability (CR) and Cronbach's alpha (CA) tests aim to test the reliability of the data collection instruments. Suppose all latent variable values have CR and CA values of 0.70. In that case, the construct has good reliability or reliable and consistent data (Vij & Walker, 2016)

Based on the Model Measurement Results (Outer Model), it is known that the outer loading value obtained is the recommended one, namely 0.70 so that each indicator used in the questionnaire is valid by meeting the requirements for convergent validity, coupled with consideration of the average value of Extract variance for each variable that have a value > 0.5 meet the average value of the extracted variance for each variable because they meet the requirements for discriminant validity. Composite reliability Cronbach's alpha value above 0.7 is stated to have good reliability. An indicator is declared valid or meets the requirements for discriminant validity if the cross-loading indicator value on that variable is the greatest compared to other variables (Cheung, Cooper-Thomas, Lau, & Wang, 2023).

The discriminant validity test (cross-loading) results illustrate the level of correlation between the various variables in this research. Specifically, this matrix shows the relationships between constructs measured by several questions. Each number in the matrix is a correlation coefficient between each variable. The matrix shows a high correlation between the variables "Build," "Buy," and "Purchase Decision", with positive coefficients close to one. In contrast, significant negative correlations are seen in "Trust" against the other variables. The "Product quality" variable has a relatively low correlation with the other variables, indicating that this variable may uniquely contribute to the measured construct. Likewise, the "Price Perception" variable has lower correlations with the other variables, indicating that it may uniquely contribute to the measured construct. The calculation of the Fornell Larcker criteria states that the resulting variable value is greater than the value of the relationship with other variables (Dam & Dam, 2021). The discriminant validity value is based on cross-loading and the Fornell Larcker Criteria to categorize it as good.

Structural Module Testing (Deep Model)

The R-Square coefficient of determination (R2) determines how much influence the independent latent variable has on the dependent latent variable. An R-Square model with a value above 0.7 is categorized as vital. Anything below 0.67 is categorized as moderate.

Based on the analysis, the Adjusted R-square (Rï¿½) value for the Buying Interest variable is 0.790, which shows that changes in the Trust, Product Quality and Price Perception variables can explain 79% of the Buying Intention variable. In comparison, the other 21% is caused by other factors outside the model. The Adjusted R-Square value for the Purchasing Decision variable is 0.48, which means that changes in the Trust, Product Quality and Price Perception variables can explain 48% of the Purchasing Decision variable. Moreover, 52% is influenced by other factors outside the model.

The data processing results show that the Q2 (Q-Square) value for both variables is 0.04 for Purchase Intention and 0.06 for Purchase Decision, which means the model diagram has a small predictive ability (0.02 ï¿½ 0.15).

Hypothesis testing

Bootstrapping calculation procedures can obtain hypothesis testing. The significance or non-significance value using the t-table value at alpha 0.05 (5% level) is 1.96 with the t-table compared to the T-statistic (calculation).

Figure 2. Path Diagram Results with Bootstrapping

Source: SmartPLS Data Processing (2023)

Table 6. Summary of Hypotheses

Hypothesis	*Immediate effect*	*Path Coefficient*	*T statistics*	*P value*	Comment
Hypothesis 1	Trust -> Purchase Intent	0.133	2,579	0.01	Positive and significant influence
Hypothesis 2	Product Quality -> Purchase Intention	0.195	3,701	0,000	Positive and significant influence
Hypothesis 3	Price Perception -> Purchase Intention	0.115	2,247	0.025	Positive and significant influence
Hypothesis 4	Trust -> Purchase Decision	0.025	0.474	0.636	Positive and insignificant influence
Hypothesis 5	Product Quality -> Purchase Decision	0.024	0.375	0.708	Positive and insignificant influence
Hypothesis 6	Price Perception -> Purchase Decision	0.057	0.866	0.387	Positive and insignificant influence
Hypothesis 7	Purchase Intention -> Purchase Decision	0.209	3,948	0,000	Positive and significant influence
*Indirect Effects*
Hypothesis 8	Trust -> Purchase Intention -> Purchase Decision	0.028	2,123	0.034	Positive and significant influence
Hypothesis 9	Product Quality -> Purchase Intention -> Purchase Decision	0.041	2,467	0.014	Positive and significant influence
Hypothesis 10	Price Perception -> Purchase Intention -> Purchase Decision	0.024	1,877	0.061	Positive and insignificant influence

Source: SmartPLS Data Processing (2023)

CONCLUSION

The analysis results show that trust, product quality and price perception have a positive and significant impact on purchase intentions, so these variables become trigger factors that influence potential customers' decisions in buying Jargas/PGN products. On the other hand, trust, product quality, and price perceptions do not significantly influence purchasing decisions directly. However, through purchase intention, these variables positively and significantly impact purchase decisions. Thus, purchase intention becomes an essential link between these factors and the customer's final purchase decision.

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