Volume 23, Number 2 (2023): 249-258 E-ISSN: 2252-6757
CITATION: Irawan, C. F., Hartono, R., Maulidah, S., Isaskar, R., (2023) THE INFLUENCE OF PRICE PERCEPTION AND ELECTRONIC WORD OF MOUTH ON CONSUMER PURCHASE DECISION THROUGH E-COMMERCE IN MALANG (STUDY AT SHOPEEFOOD SERVICES IN SHOPEE E-COMMERCE), Agricultural Socio-Economics
THE INFLUENCE OF PRICE PERCEPTION AND ELECTRONIC WORD OF MOUTH ON CONSUMER PURCHASE DECISION THROUGH E-COMMERCE IN
MALANG (STUDY AT SHOPEEFOOD SERVICES IN SHOPEE E-COMMERCE)
Cholista Ferry Irawan, Rachman Hartono, Silvana Maulidah, Riyanti Isaskar*
Agriculture/Socio-Economic Department, Agriculture Faculty, Brawijaya University, Indonesia
*corresponding author: [email protected]
Abstract Technological developments in the era of globalization have provided changes for society both in social, economic, and cultural aspects. This massive technological development has created unprecedented new job and business opportunities. One of the business potentials created by the massive development of information technology is the emergence of a business opportunity through e-commerce. This study focuses on the Shopeefood service. This study's objective was to investigate the influence of price perception "and electronic word of mouth” on consumer purchase decisions. This study employs a quantitative methodology and data collection strategies using online surveys through questionnaires. The data in this study were analyzed using SEM-PLS. This research was conducted in Malang City from April to May 2022. This study used three variables, namely price perception (X1) and Electronic Word of Mouth (X2) as exogenous variables and purchase decision (Y1) as endogenous variables. This research proves that/price perception and e-WOM/have a significant effect on purchase decisions. With a "path coefficient” value of 53% and a P- Value of 0.01, the price perception variable strongly significantly influences the decision to buy. With a path/coefficient value of 17% and a P-Value of 0.03, the e-WOM variable significantly affects consumer decision-making.
Keywords: price perception, e-WOM, Purchase Decision, e-commerce
http://dx.doi.org/10.21776/ub.agrise.2023.023.2.14 Received 8 March 2023 Accepted 20 March 2023 Available online 30 April 2023
INTRODUCTION
Technological information developments in the era of globalization have provided changes to society both in social, economic, and cultural aspects. The development of this technical information makes people accustomed to using the internet to find information and communicate.
People from different countries can connect with
each other because of the internet. So that the use of the internet can facilitate all human activities. The internet also creates time efficiency and effectiveness in community activities. When technological advancements take place, there is a tremendous rise in internet users. Based on data from Internet World Stats (2021), In Indonesia, there were 212.35 million internet users in 2021. In
2016, there were 132 million internet users in Indonesia. This shows a growth in internet users of 37.83% over the previous five years. This massive development of technology has created job opportunities and new businesses that have never existed before. One of the business potentials created by the development of massive information technology is the "emergence” of a business opportunity through /e-commerce.
E-commerce/is a form of business that is carried out online through various platforms and media that are integrated directly with the internet.
Based on research by Snapcart (2020), 88.1% of internet users in Indonesia utilize e-commerce to make their desired purchases. E-commerce in Indonesia is experiencing very rapid development due to the era of globalization. The increase in internet users in Indonesia and the rapid growth in consumption levels of the Indonesian people make e-commerce a transaction activity usually carried out by the people in Indonesia. By 2030, the value of e-commerce transactions in Indonesia is expected to expand up to eleven times, to Rp. 4.500 trillion, from its current value of Rp. 395 trillion in 2021 (Bank Indonesia, 2021). This data is proof that e-commerce in Indonesia has the potential for very rapid development. This data also can be a motivation for other business people to enter the world of e-commerce in doing business development.
Business-to-business (B2B), business-to- consumer (B2C), consumer-to-consumer (C2C), social commerce, local commerce, and mobile commerce (M-Commerce) are the six categories or six forms of e-commerce (Laudon & Traver, 2019).
According to Kotler & Keller (2016), the most widely used e-commerce business model in Indonesia is Business to Consumer (B2C). B2C e- commerce is a type of business where products and services are sold directly to consumers or in groups.
One of the e-commerce that implements the form of Business to Consumer is Shopee.
One of Southeast Asia's biggest internet marketplaces is Shopee. Shopee provides a safe, fast, and easy online shopping experience for customers with strong logistics support and an easy payment system. The SEA Group introduced Shopee for the first time in Singapore in 2015, and it has since extended to Thailand, Malaysia, Taiwan, Indonesia, Vietnam, and the Philippines.
SEA Group then created a subsidiary under the name Shopee International Indonesia Ltd., which focuses on expanding its business in Indonesia. The transaction value at Shopee Indonesia in 2020
reached $14.3 billion or Rp. 203.4 T, making Shopee the most popular e-commerce in Indonesia (Katadata, 2021).
Shopee International Indonesia Ltd. used the C2C (Consumer to Consumer) business concept when it was first established. As the number of users increases, Shopee has started using a hybrid concept that includes B2C and C2C by inviting brand-owning companies as Shopee's business partners. Shopee International Indonesia Ltd. has grown by providing a variety of services to meet consumer needs. One of these services is the Shopeefood service. Shopeefood was founded in 2021 and continues to expand its service range in all regions of Indonesia. Shopeefood is a food delivery service with a B2C (Business to Customer) business model that connects food business owners with consumers who need food online (Shopee, 2021).
Shopeefood has various strategies in order to influence buyers to buy food through Shopeefood, namely by providing competitive prices and making it easier for consumers to provide product reviews online.
One of the factors that can influence a person's purchase decision is price perception. Based on the statement from Setiadi (2019), perception can be defined as meaning that is interpreted based on past experience and stimuli or stimuli received through the five senses, such as sight, hearing, taste, and so on. The customer's opinion or perception of an item's pricing is known as the price perception by looking at a certain price (high, low, reasonable) which can have a strong influence on the desire to buy and purchase satisfaction. (Harjati & Venesia, 2015). Consumers will evaluate the value based on the comparison of price and product quality in purchase decisions. Pricing by sellers also has an influence on consumer buying behavior, and this is because prices that can be reached by consumers can make consumers make purchases of these products.
A form of promotion that can be applied by companies with e-commerce businesses to increase the company's market share is to build a good brand image in the market. Brand image can be formed through consumer experience when viewing, buying, or using certain products. Brand image can be formed through community interactions who buy the same product. In this society, knowledge is
“shared” orally or through a mechanism known as word of mouth. In the e-commerce business, Word of Mouth activities are carried out online through reviews in certain forums, so the exchange of
information is called Electronic “Word of Mouth”
(e-WOM).
“Electronic Word of Mouth” (e-WOM) is a type of intensive marketing that emphasizes getting people to interact with one another/through the media (Akbar & Sunarti, 2018). E-WOM is-a marketing technique that relies on social relations between individuals in a market environment.
Individuals usually seek first information about a product before deciding to make an online purchase. The process of exchanging e-WOM information can be done through several online platforms such as Facebook, Instagram, Twitter, and Whatsapp, and also through reviews on e- commerce.
The existence of attractive prices and e-WOM can influence consumer decisions to buy products through e-commerce. The Consumer buying decision is a process in which an individual chooses and evaluates a product before buying based on needs and wants. Easy internet access and easy-to- reach e-commerce applications also make it easier for individuals to buy products through e- commerce.
Therefore, this research- seeks to ascertain the impact of price perception and e-WOM on consumer purchase decisions through Shopee e-commerce on Shopeefood services.
RESEARCH METHODS
This “research” was conducted in Malang City in April-May 2022. The research location was chosen with the consideration that Malang City is the second most populous city in East Java.
Therefore, Malang City residents prefer to shop online to make time efficient. The “research approach” used in the research is a quantitative approach. The total sample of this “research” is 108 respondents. A non-probability sampling design with a “purposive sampling technique” was used to determine the sample in this study. Data was collected through online survey questionnaires. The data in this research were analyzed using the
“Structural Equation Modeling – Partial Least Square (SEM-PLS)” analysis tool with WarpPLS 7.0 application. This research used three variables.
The independent variables consist of “Price Perception” (X1) and “Electronic Word of Mouth”
(X2). Another variable is a dependent variable that consists of Purchase Decisions (Y1).
RESULTS AND DISCUSSION Respondents Characteristics
The following are the details of each respondent's characteristics:
Table 1. Respondent Characteristics
Characteristics Description Total Percentage
Gender Male
Female
42 66
39%
61%
Age 17 – 25 Years Old
26 – 34 Years Old 35 – 43 Years Old 44 – 52 Years Old
99 4 3 2
91.6%
3.7%
2,8%
1.9%
Educational Level Senior High School Diploma Bachelor Master or Doctor
15 6 81
6
13.8%
5.6%
75%
5.6%
Income “Rp. 1,000,000”
“Rp. 1.000.000 – Rp. 3,000,000“
“Rp. 3.000.000 – Rp. 5,000,000“
“Rp. 5.000.000 – Rp. 7,000,000“
“Rp. 7.000.000 – Rp. 10,000,000“
“> Rp. 10,000,000“
33 47 12 4 2 10
30.5%
43.5%
11.1%
3.8%
1.9%
8.3%
Occupation Government Employees
Private Employees Entrepreneur Students / College Students
Freelancer
4 8 9 86
1
3.7%
7.4%
8.3%
79.6%
0.9%
Respondents in this research were consumers who bought food and beverages through Shopeefood services on Shopee e-commerce. 108 people were included in that poll as respondents. Based on data, it is known As many as 66 respondents or 61% of the total, indicate that respondents are overwhelmingly female. Those who responded on behalf of the masculine sex totaled 42 people, or 39% of the total number of respondents.
Characteristics of Respondent based on age show that respondents aged 17-25 years with a total amount 99 respondents or with percentage consist of 91.6% of the total respondents. Based on the findings, it is known that respondents in this study were predominately those with a bachelor's degree, accounting for 75% of all respondents. - Respondents with Bachelor's education level were 81 people. Based on income, respondents in this research were dominated by respondents with an income of Rp. 1.000.000 - up to Rp. 3,000,000.
According to their income, the majority of respondents in this study had incomes between Rp.
1.000.000 and Rp. 3,000,000. 47 respondents, or 43.5% of the total respondents in this study, are respondents with incomes of “Rp. 1,000.000” or more up to Rp. 3,000,000. Respondent's characteristics based on occupation show that respondents are dominated by respondents with Students / College Students, with a total of 86 respondents.
Outer Model Analysis
This analysis uses by understanding the correlation model, evaluation of the “measurement model” (outer model) was done in order to determine the model's validity and reliability. With reflexive and formative indicators, a construct can be created for the evaluation of the outer model.
According to Sholihin & Ratmono (2021), the indicator values of reliability, “internal” consistency reliability, convergent validity, and “discriminant validity” should be examined first when evaluating the outer model with a reflective construct. The
“formative” construct evaluation begins by looking at indicators of reliability and collinearity.
1. Formative Measurement Model
In the “formative measurement” model, it can be done by looking at the Significant Weight and VIF parameters that can be obtained through the resampling procedure. The conditions used in the VIF parameters, according to Solimun et al. (2017), are less than equal to 3.3. This research shows that the VIF value for each indicator of the exogenous
variable has a VIF value of less than equal to 3.3.
Hence, it can be said that there are no issues or collinearities between the exogenous variable X1 (price perception) and the exogenous variable X2's indicators (e-WOM).
2. Reflective Measurement Model”
Starting with the reliability indicator value, internal consistency” reliability, convergent validity, and discriminant validity, the reflective model is measured. The first step is to look at the Reliability Indicator on the Loading Factor parameter. According to Solimun et al. (2017), a loading factor with a value > 0.5 can meet convergent validity. This study provides an explanation for why each indicator's loading factor value is more than 0.5. The p-value for each indicator also gives information about the value is less than 0.05 thus, the indicator that is used meet the requirements and rules of the predetermined criteria. The second step is to measure “internal consistency reliability” using “composite reliability” and Cronbach alpha parameters.
According to Solimun et al. (2017), the minimum value required for composite reliability is > 0.7, while the minimum value required for Cronbach alpha is > 0.6. It is comprehensible why the composite reliability value displays a number greater than > 0.7, indicating that it satisfies the criteria for composite reliability. The third step is to see the "Convergent Validity through the Average Variance Extracted (AVE)” parameter. The requirements for a good AVE value are that it must show a score of more than 0.5 (Solimun et al. 2017).
The outcome reveals that the Average Variance Extracted value is more than 0.5, indicating that AVE is good and convergent validity is met. The cross-loading and loading indicators are compared in the first phase of the fourth stage, discriminant validity. The following is a table of Correlation
“Among Latent Variables” and Square Roots of AVEs:
Table 2. Correlation Among Latent Variable and Square Roots of AVEs
X1 X2 Y
X1 (0.763) 0.348 0.579
X2 0.348 (0.746) 0.347
Y 0.579 0.347 (0.756)
Source: Primary Data Processed (2022)
Based on the AVEs data, this explained that the score marked with brackets is an indicator value of the variable, while the value that is not marked with brackets is the correlation value of other indicators.
Table 2 demonstrates that the cross-loading value is
greater than the loading indicator value, supporting the validity of the indicator. The second stage is to look at Discriminant Validity through the “AVE square root parameter” and the correlation between latent constructs with the condition that the AVE square root must be greater than the correlation between latent constructs. Also, the variables “X1 and X2” display an “AVE square root” value that is higher than the correlation between the variables.
Inner Model Analysis
Following are the outcomes of many component elements that serve as criteria in the evaluation of the inner model:
1. R-squared
The R-squared value obtained in this research is 0.383. This means that the Price Perception and e- WOM can explain the purchase decisions variable of 38.3%, while 61.7% of the remaining data are affected by additional factors not considered in the model. According to Solimun et al. (2017), R-square was classified as < 0.70, < 0.45, and < 0.25 for endogenous latent variables that should be used as a general reference. Each R-square value is described at a high, medium, or weak level. It can be concluded that the R2 value in this study belongs to the medium or moderate category with an R2 value of 0.383.
2. Q-squared
The relevance of a collection of predictor latent variables to the variable criterion is evaluated using the Q-square value. Q-square value has a value of more than 0 indicating a good predictive. According to Solimun et al. (2017), a model with predictive validity must have a Q-squared value greater than zero. The q-squared value for the Purchase Decisions variable (Y) is 0.387, so it can be interpreted that the research model has good predictive relevance.
3. Full Collinearity VIF
In the evaluation of the inner model, the measure of collinearity is the variance inflation factor (VIF), which is defined as the inverse of tolerance. Solimun et al. (2017) mentioned that the requirements are the same as the full collinearity test, which requires a value of 3.3. It should be noted that "the VIF" value is supplied for each criterion variable indicating the level of collinearity or redundancy between the predictor variables. The following table is the "VIF” value of this research:
Table 3. VIF Value Price
Perception (X1) e-WOM (X2)
Purchase Decision
(Y)
1.562 1.181 1.561
Source: Primary Data Processed (2022)
Based on the score above, it can be concluded that all VIF values < 3.3, namely the price perception variable (X1) is 1.562 and the e-WOM variable (X2) is 1.181. The value of VIF on the dependent variable of purchase decision (Y) is 1,561. Therefore, it can be concluded that this study does not have a collinearity problem.
4. Effect Size
Based on the statement from Hair et al. (2014), The influence size f2 enables the evaluation of the exogenous construct's contribution to the endogenous latent variable's R2 value, which is utilized as a comparative indicator of predictive relevance. Three criteria—> 0.02 (little influence), >
0.15 (mid influence), and > 0.35 (big impact)—are used to determine whether an influence size value is appropriate (large influence). The price perception variable (X1) has a value of 0.32. This value is greater than 0.15, which means that the price perception variable (X1) has a moderate impact on purchase decisions (Y). The “e-WOM” variable (X2) has a value of 0.063. This value belongs to the category of small exogenous constructs, so the influence size value of the e-WOM variable (X2) has a small impact on purchase decisions (Y).
5. Goodness of Fit
The goodness of fit test is used to ascertain the index and magnitude of the association between latent variables. The Fit & Quality Indices Model's requirements were fully met by the model used in this research. According to Solimun et al. (2017), the P-value for APC and ARS must be less than 0.05 so that it becomes significant, besides that, AVIF as an indicator of multicollinearity must be smaller than 5.
Based on the results shown in the table above, it can be seen that the P-value of APC and ARS has a p- value <0.001, which is smaller than 0.05, and the AVIF value is 1.435. This AVIF value is less than 5, so it can be declared that it has met the criteria and is feasible. The “Goodness of fit (GoF)” value generated in this study shows a value of 0.453, which says that the fit model is included in the large category and is feasible because it has a GoF value of more than 0.36.
Hypothesis Test
The criteria in hypothesis testing are divided into three criteria, including a p-value of 0.10 belonging to the weakly significant category, a p- value of 0 belonging to the significant category, and a p-value of 0.01 belonging to the highly significant category (Solimun et al., 2017). Figure 1 shows the path coefficient and p-value outcomes of this study.
Figure 1. Path Coefficient Diagram and Significance As seen in the aforementioned image, the path coefficient value has a favorable impact on each construct. The path coefficient value of 0.53 and the high significance p-value of 0.01 indicate a significant and positive effect of the price perception variable (X1) on purchase decisions (Y). With a path coefficient of 0.17 and a p-value of 0.03, the e- WOM variable (X2) has a significant and “positive impact” on purchase decisions (Y).
In the research that has been done, the results obtained data that demonstrate the impact of e- WOM and price perception on consumer decisions to shop for Shopeefood services. In the Shopee application. The constructs used in this study are exogenous variables of price perception and e- WOM, and the endogenous variable is the purchase decision. By examining the path coefficient and p- value on each external variable to the endogenous variable, the results of hypothesis testing are displayed. The following are the findings of the hypothesis test:
Table 4. “Path Coefficient Value and p-value”
Source: Primary Data Processed (2022)
The decision rule for hypothesis testing, according to Solimun et al. (2017), is broken down into three categories, with a p-value of 0.10 falling into the weakly significant category, a p-value of 0.05 falling into the significant category, and “p- value” 0.01 falling into the extremely significant category. Consequently, it is evident from the data in the table that the variables Price Perception (X1)
and“e-WOM” (X2) have a “highly significant and significant” impact on Purchase Decision (Y).
The Influence of Price Perception on Purchase Decisions on Shopeefood services
The findings of the research investigation describe how price perception variables influence consumer purchasing decisions in Malang City, which is in line with the original goal of this study, which was to analyze the influence of price perception on purchase decisions through Shopeefood services on Shopee e-commerce. This variable is reflected in 4 indicators, namely the affordability of price with purchasing power, conformity of price with quality, price competitiveness, and suitability of price with benefits. Perception of price is a perception related to the relative costs that must be incurred by consumers in obtaining products or services (Rangkuti, 2013). The other definition is according to Rahmanita & Gunawan (2017), Price perception is defined as the tendency of consumers to employ price to make judgments regarding product quality.
Price perception refers to how people interpret pricing information and convey its significance to potential customers.
Price perception has an influence and a positive effect classed as highly significant to purchase choice, according to the analysis of path coefficients and p-value of the price perception variable on purchasing decisions in this study. The path coefficient score obtained is 0.53, and the p-value is
<0.001. The outcome of this study is in line with the study from Kuswanto & Vikaliana (2020), who found a positive influence and a high significance between price perceptions and purchasing decisions.
This can be seen through the condition of the people in Malang City, who mostly pay attention, consider and compare prices before making a purchase.
According to Yuliana & Maskur (2022), while buying something, people always pay close attention to how they perceive the price. Consumers will contrast the price being provided with the price range they have in mind for the product as they process price information cognitively.
Research done by others has also shown the impact of price perception on purchasing decisions.
Tecoalu et al. (2021) research, it is explained how someone considers several aspects in making a decision while purchasing a product based on consideration of the price of a product. This study explains that the suitability of price with purchasing power, suitability of price with quality, price competitiveness, and suitability of benefits is part of Path
Correlation
Path Coefficient
p-
value Information Price
Perception (X1) → Purchase Decision (Y)
0.53 <0.01 highly significant
e-WOM (X2)
→ Purchase Decision (Y)
0.17 0.03 significant
price considerations in consumer purchasing decisions. The theory put forth by Kotler &
Armstrong (2016), explains the dimensions of the price perception indicator. Based on the outcome of the research conducted, price perception “has a significant and positive” influence on consumer purchasing decisions. This study is also still relevant with another research, there is research from Anwar et al. (2022), which demonstrates that price perception has a favorable and large impact on customer purchase decisions, is in line with this study as well.
The Influence of e-WOM on Purchase Decisions on Shopeefood services
The findings of this study demonstrate how Electronic “Word of Mouth” influences consumer purchase decisions in Malang City based on the original goal of the study, which was to investigate the influence of e-WOM on purchasing decisions through Shopeefood services on Shopee e- commerce. This variable is reflected in 3 indicators, namely “intensity, the valence of opinion, and content. Electronic word of mouth” (e-WOM) is an interchange of knowledge in the form of digital communication with feedback made by consumers on products and services by communicating through cyberspace. (King et al., 2014). Another definition of e-WOM from Ahmad & Febrina (2017), is e- WOM is a declaration or expression made by actual, potential, and recent consumers regarding a product or service. E-WOM offers various ways to exchange information freely and confidentially, many of which consumers conduct “product” reviews anonymously so as to protect consumer privacy and security.
Through the analysis of path coefficients and p-value of the e-WOM variable on purchasing decisions in this study, it is known that e-WOM has a “positive and significant effect” on purchasing decisions. The path coefficient value obtained is 0.13, and the p-value is 0.003. The “results” of the study have similarities with the research by Setianingsih (2022), which states that e-WOM has a positive and “significant effect” on consumer purchasing decisions. This can be seen through the condition of the people in Malang City, which some see and compare the ratings or reviews of previous consumers, which is reflected in the results of the descriptive analysis of this study. The existence of e-WOM will help previous consumers share experiences about food or beverage products that have been obtained in Shopeefood services. In addition, consumers can also view and compare
assessments or reviews from previous consumers regarding the delivery process by drivers who are Shopeefood service partners on Shopee e- commerce. According to Yuliani & Suarmanayasa (2021), Consumers in e-commerce tend to consider positive reviews, negative reviews, and recommendations submitted by previous consumers so that this can influence the purchasing decisions of potential consumers.
The influence of e-WOM on purchasing decisions can also be seen through research conducted (Sari et al., 2017). In the research from Sari et al. (2017), it is explained how someone considers several aspects of e-WOM in making a decision to purchase a product. This study explains that e-WOM has a “significant effect” on purchasing decisions. This study includes the theory proposed by Goyette et al. (2012), which explains the dimensions of e-WOM indicators, namely intensity, valence of opinion and content. This study is also in accordance with previous research, namely research from Sindunata & Wahyudi (2018), which explains that e-WOM has a “positive and significant” effect on consumer purchasing decisions.
CONCLUSION
Based on the initial objectives of the study and also the results of the research that has been carried out, it can be concluded that:
1. Price perception has a “positive” influence on purchasing decisions. In this study, price perception has a significant value that is classified as highly significant. It can be concluded that the higher the level of price perception, the higher the level of purchasing decisions.
2. e-WOM has a “positive” influence on purchasing decisions. The significance value of e-WOM is quite significant. t. It can be concluded that the increase in e-WOM will be followed by an increase in purchasing decisions.
SUGGESTION
Based on the results of the discussion and research conclusions that have been obtained, the following are some suggestions that can be given:
1. Shopee International Indonesia Ltd.
Shopee International Indonesia Ltd. needs to maintain the value of a product and company.
Therefore, Shopee International Indonesia Ltd. must be able to build branding so that consumers judge
that the products sold have benefits that are comparable to the prices offered so that the products are still in demand by customers. In addition, Shopee International Indonesia Ltd. also needs to consider the e-WOM aspect well. Shopee International Indonesia Ltd. can improve the service quality of the Shopeefood platform and the services of restaurants, cafes and shops that are partners so that consumer ratings or reviews are better. This can prevent customers from switching to other e-commerce platforms that offer food delivery services similar to Shopeefood services.
2. For further research
For further research, it is hoped that this research can be used as a reference. Researchers can develop research by adding other variables or adding other indicators with similar topics of discussion.
Researchers can also develop research by comparing the Shopeefood platform with other e-commerce platforms.
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Appendix 1. Model Fit and Quality Indices
No. Model Fit and Quality Indices Criteria Score p-value Information 1 Average path coefficient (APC) p < 0.05 0.352 p<0.001 fulfilled 2 Average R-squared (ARS) p < 0.05 0.383 p<0.001 fulfilled 3 Average adjusted R-squared
(AARS) p < 0.05 0.371 p<0.001 fulfilled
4 Average block VIF (AVIF)
Accepted if ≤ 5,
ideal ≤ 3.3 1.164 Ideal
5 Average full collinearity VIF (AFVIF)
Accepted if
≤ 5, ideal
≤ 3.3 1.435 Ideal
6 Tenenhaus GoF (GoF)
Small
≥0.1;
Medium ≥ 0.25;
Big ≥ 0.36
0.453 Big
7 Sympson's paradox ratio (SPR)
Accepted if
>0.7, ideal =1
1 fulfilled
8 R-squared contribution ratio (RSCR)
Accepted if
>0.9, ideal =1
1 fulfilled
9 Statistical suppression ratio (SSR)
Accepted if
>0.7,
ideal =1 1 fulfilled
10
Nonlinear bivariate causality direction ratio
(NLBCDR)
Accepted if >0.7, ideal =1
1 fulfilled
