CC BY
20
Digital economy: theory and practice
DOI: 10.18721/JE.14101 UDC 338.001.36
ONLINE SHOPPING: FACTORS AFFECTING CONSUMER'S CONTINUANCE INTENTION TO PURCHASE
W. Muljono1, S.P. Pertiwi2, D.P.S. Kusuma3
1 Ministry of Communications and Information, Jakarta, Indonesia; 2 Institut Teknologi Sepuluh Nopember,
Surabaya, Indonesia; 3 UMBRA - Strategic Legal Solutions, Jakarta, Indonesia
Research confirms that continued intentions play an important role in consumers' decisions in online shopping. In our study, we assume that the factors influencing sustainable intention from the startup's side are service quality, delivery, and from the consumer side — their attitude towards online continuity intentions. The research was carried out at the beginning of the COVID-19 pandemic, which is known to have greatly influenced the increase in online shopping. This condition occurs due to restrictions on the mobility of people, but the goods delivery is not affected. The purpose of this study is to investigate service quality and shipping that has been considered a critical factor affecting the continuance intention of consumers in online shopping. Moreover, we investigate whether attitude acts as a moderator between service quality and shipping with regard to continued intention in online shopping. Later these empirical findings can provide recommendations to startups in developing service quality in online stores and trustworthiness in the delivery of goods purchased online. Both are considered to have disrupted the way of shopping in the digital era. This study was conducted using a quantitative approach by distributing questionnaires to online shopping consumers. Utilizing SEM with AMOS 22, the current study recruited 400 respondents to provide primary data. The findings on online service quality of inquiry showed that assurance, reliability, and responsiveness contributed to perceived innovativeness of service quality. The construct of service quality observed is confirming prior research, which indicated that the perceived service quality is based on assurance, which includes security, data protection, and a guarantee of no abuse. Reliability is closely related to accuracy, full responsibility, and absence of access failure. Shipping constructs is consistent with a reliable, safe, and timely delivery that is essential for online consumers. Thus, the findings indicate that although consumers hold a positive attitude towards continued intentions in online shopping, service quality is shown at a sufficient level and shipping wasn't detected. This study also found that attitude does not act as a moderator of the relationship between service quality and shipping towards continuance intentions in online shopping. After the factors were taken into consideration, we could conclude that in terms of service quality, the characteristics of assurance, reliability, and responsiveness in online shopping are decisive factors affecting customer shopping decision. Meanwhile, the shipping factor has no direct relationship with online shopping intentions. This condition can be explained by the fact that most consumers who shop online reside exclusively in Jakarta. Consequently, goods are swiftly delivered and received by consumers. In this report, if companies want to maintain a long-term relationship with consumers, they should provide excellent service for them in their choices for using websites, and even moreso, in online shopping, where the service quality instruments are different from the conventional businesses. One implication of these findings for managers, of both startup and shipping companies, is to pay attention to the website platforms as part of assessing perceptions of service quality.
Keywords: service quality, shipping, attitude, continuance intention, startup, online shopping, e-commerce
Citation: W Muljono, S.P. Pertiwi, D.P.S. Kusuma, Online shopping: Factors affecting consumer's continuance intention to purchase, St. Petersburg State Polytechnical University Journal. Economics, 14 (1) (2021) 7-20. DOI: 1018721/JE.14101
This is an open access article under the CC BY-NC 4.0 license (https://creativecommons.org/li-censes/by-nc/4.0/)
Introduction
E-commerce in Indonesia has become increasingly important in all market segments. In 2020, Indonesia's retail segments have already accounted for $40 billion. This year, Indonesia's e-commerce was higher at $17 billion compared to 2019's $23 billion, which followed suit. This indicates overall sales value to surpass estimate, driven by a new cohort of e-commerce users amid the Covid-19 pandemic. This condition is due to the increasing number of smartphone users in Indonesia, reaching 81.87 million users in 2020 [1]. Most retail goods traded via e-commerce are produced by small and medium enterprises (SMEs). Furthermore, the majority of businesses in Indonesia are SMEs, which represent 99% of the operating businesses1. Business models, such as the sharing economy model have predicted considerable growth in e-commerce. For example, GoJek in partnership with SMEs contributed a transaction volume of $ 1.2 billion in 20 1 72, which means that e-commerce in the SME sector is expected to grow considerably.
The e-retail industry has been developing very rapidly and changing prior distribution systems. Hence, e-retail has higher opportunities to improve their performance if they have strong logistics capabilities [2], which has led to partnerships between startups that collect SME products to be marketed online and existing shipping services to deliver goods to consumers. As a consequence, service quality (SQ) and shipping are significantly influencing attitude and continuance intention of online shopping (CIOS) and have emerged as a competitive advantage.
The most favorite websites to visit by Indonesian internet users are apparently online shopping sites, which are Shopee, Tokopedia, and Bukalapak3. This means that the service quality of online shopping sites is more innovative. This is also offset by courier services for shipping goods purchased online. Shipping service is required to implement and improve the service offered to fulfill various consumer needs and implement innovative solutions.
It does not mean there are no gaps in online shopping. Previous research pointed out the shortcomings, that the lack of access to sales associates in e-commerce is considered another restriction [3]. Indeed, the critical aspect could have implications for declining consumer intentions of online shopping. Witnessing the strong growth of e-commerce, academics have directed increasing attention to e-commerce research because e-commerce provides diverse goods, methods of payment, and delivery for items purchased through delivery services, which has led to a number of challenges.
E-commerce websites and the presence of the website-based apps were initially thought to be the drivers of success, SQ issues to stand out. When consumers could not complete transactions, products were not delivered on time, the viability of e-commerce websites was jeopardized, with the chance to be abandoned by consumers [4]. If e-commerce websites are to be accepted by consumers, start-up companies must shift the focus to e-service quality rather than to the electronic transaction process. The phenomenon of e-service as a novelty of technology adoption is an interesting and challenging issue to be studied.
Inconsistencies are observed between attitude and CIOS models related to e-commerce because each study is based on different objects and settings [5]. This condition provides an opportunity to design alternative models that are able to describe the phenomenon to be observed. A model alternative is built based on four variables, namely, SQ, shipping, consumer attitudes, and CIOS, which can be explained by the previous factors.
This research contributes to understanding SQ, shipping, and its attributes either directly or through attitudes towards CIOS to provide a clearer picture of the relationships them.
1 Das K., Tamhane T. et al. The digital archipelago: How online commerce is driving Indonesia's economic development. McKinsey&Company: Indonesia's online commerce journey, 2018, no. 1-11.
2 Walandouw P., Primaldhi A. et al. GOJEK's Impact on the Indonesian Economy in 2018. Jakarta, LD FEB UI, 2019.
3 Top 50 E-Commerce Sites & Apps Indonesia in 2020. URL: https://iprice.co.id/insights/mapofecommerce/en/ (accessed March 28, 2020).
Literature Review
The relevant literature for this study is discussed in this section, based on literature reviews. There are two main areas of literature used in the paper. The first is related to attitude and CIOS. The other one is related to the SQ offered by e-commerce companies and the shipping options of goods purchased.
Service Quality
Previous research has shown that prediction models of individual behavior intention show service quality needs to be examined because this variable effectively influences consumer attitudes [3]. A study of consumer behavior and product quality services showed that consumer perceptions about product quality are relative and changeable. This inconsistency is explained via product quality concepts and dimensions and SERVQUAL is a tool for measuring SQ [4]. The SQ becomes the associate's adequate activity for promoting to seek out and analyze data regarding consumer's needs, wants, and perceptions relating to the product offered. SQ refers to providing service that meets or exceeds consumers' expectations. Indeed, this definition was most cited by the other researchers for outlining SQ. Today, consumers have high expectations for startup firms to offer them what they require, once they wish it. Obviously, digital remodel from conventional SQ to electronic SQ is more beneficial for consumers.
Service quality is known as SERVQUAL, which contains five dimensions used as measurements: reliability, responsiveness, assurance, empathy, and tangibles [4]. Despite the universality of the five dimensions of SERVQUAL, they do not constitute all of the dimensions appropriate for measuring all aspects of a website due to the various characteristics and features of SQ on the website displayed. The five dimensions are industry-specific and are not applicable to any service industries without modifications [6].
Previous research has shown that a behavioral intention prediction model shows that SQ effectively influences consumer attitudes [7]. However, these reported findings are not without conflicting results. A study on consumer behavior and service quality shows that consumers' perceptions of SQ change due to consumer psychological influences [8].
To apply the SQ framework to the current analysis, we have ensured that the choice of dimensions of the framework is compatible with the SQ on the website displayed. Previous studies investigated the relationship between consumer loyalty and the purchase of products in online shopping, while considering 5 indicators, such as website navigation, product information, product availability, timeliness of delivery, and simplicity of the return of products [9].
Then, we included 2 key dimensions, particularly perceived SQ and perceived information quality of knowledge, each influencing CIOS absolutely [10]. Perception of SQ and information quality are both closely related to reliability and responsiveness. Reliability is the ability to perform the services in a dependable, accurate, and totally accountable manner, without access failure [11]. Responsiveness is the willingness to respond quickly and in real-time to consumer requests [8]. Responsiveness involves a willingness to respond quickly, keeping consumers informed regarding the availability of goods, delivery services, payment options, and a set price.
Assurance involves the consumers' trust in the website. Trust in the start-up website depends on the consumers' notion of security of however the website manages their personal information [12]. Websites can increase the trust of the consumers by enhancing website system security [9]. Privacy is the most serious issue in attracting a lot of online potential consumers and retaining the current ones. Empathy is defined as creating a relationship between consumers and sellers via web platforms, smart communication, and understanding the wants of consumers.
Tangibles is defined as the appearance of a website or application, the Android software package, straightforward and various options, and attention-grabbing content [13]. For the needs of this study, SQ is measured by reliability, responsiveness, assurance, empathy, and tangibles. Accordingly, we have proposed the following hypothesis:
Hypothesis 1. SQ is positively correlated with CIOS.
Shipping
Shipping in online shopping is a service used by start-up companies that sell goods over the internet. Thus, start-up companies have to hold a proper shipping partner. Startup ought to employ faster and cheaper shipping resources in order to stay up and meet consumer expectations. That is where the shipping service companies play a role in partnering with start-up companies and goods suppliers.
Startup companies need to take an omnichannel approach to parcel and deliver goods. This often means consolidating consumer orders across all of the shipping channels. For instance, large-format goods (e.g., a laptop) being delivered by a two-person courier may be delivered with smaller delivery goods (e.g., clothes) purchased separately but shipped to the same address. Shipping may be a link within the supply chain that directly affects the consumer and triggers their satisfaction. The reliability of goods shipping service is a road to consumer's CIOS. It implies that the consumer can receive the ordered product, that is well packed, which quantity, quality, and specification are in accordance with the order to a set delivery time and place. A reliable, safe, and timely delivery is something essential for online consumer satisfaction [14].
Shipping service is evaluated by consumers once goods purchased online are shipped quickly, safely, and received on time in accordance with its promise. The major reason why consumers switched to startup companies is attributable to shipping, notably delayed goods received. Meanwhile, a study of shipping sensitivity had no impact on the consumer's purchase intention. Shipping services ought to be investigated as a result of our understanding of the interaction between shipping and CIOS [15]. However, the interaction between shipping and CIOS remains unclear. Accordingly, it is therefore hypothesized as follow:
Hypothesis 2. Shipping is positively correlated with CIOS.
Attitude
The nature of the selling context of consumer orientation and attitude is taken into account to influence consumer CIOS. Today, attitude plays the leading role in the theories and analyses concerning consumer behavior. From a business perspective, consumer attitude is responsible for an evaluation of a product or service. Concerning consumer attitude towards product and service, the previous study claimed that attitude is an important factor in influencing consumers' intention towards product and service [16].
We begin by considering the definition of attitudes, which is individually attributed to emotions, beliefs, and behavioral tendencies an individual has towards a specific object. We have concentrated on uncovering the factors that affect the attitude towards goods purchased online. Consumers' attitude on online shopping is an important factor that influences the CIOS [17]. Through internet shopping, consumers can purchase more alternatives for products and shipping services.
Attitude is defined as the degree of one's positive feelings about taking part in online shopping [18]. A purchase can happen solely if consumers exhibit a positive attitude towards online shopping. Consumers' attitude, be it positive or negative, is related to their behavior in terms of finishing the shopping via the website. Attitude plays a vital role in forming CIOS. It is believed that consumers with more positive attitudes can have a lot of tendencies to repeated purchasing online. It is often indicated by many studies that attitude has a positive impact on the intention to purchase online [19].
To analyze consumer's attitudes, we use multi-dimensional models, which regard attitude as a construct of 3 components: cognitive, affective, and conative. This research focuses on explaining model predictions of attitude and CIOS. Though most attitudes have all 3 components mentioned above, they are strongly rooted in either the cognitive or the affective component [20-22]. Multi-dimensional models are used to describe the attitude of individual willingness to determine the consumers' attitudes towards online shopping. Thus, an attitude reflected by indicators such as useful, entertaining, and interesting is used to identify consistencies in attitude as an indicator of consumers' goodwill. In this case, the researcher seeks to identify individual's needs through the attitude dimension as a moderating variable. Accordingly, we have proposed the following hypothesis:
Hypothesis 3. Attitude is positively correlated with CIOS.
Continuance intention of online shopping
The CIOS is adopted from several earlier studies that designated continuance intention as a dependent variable [23]. In a similar way, let us define intentions as the consumer's conscious motivation to make an effort to engage in a specific behavior [24]. In short, CIOS is how hard consumers are willing to try, of how much of an effort they are planning to exert, in order to perform the behavior [25].
Online shopping is defined as the process a consumer engages in to purchase goods over the internet. Online shopping is buying goods and related services (including delivery service) over the internet [26]. The consumers are interested in exploring shopping websites depending on the goods and services being sold, the quality of website services, reliability of promised shipments, the experience of using online shopping websites, and payment security and privacy [27]. These factors affect consumers' behavior when shopping online.
In this research, the concept of continuance intention is analyzed by using the Theory of Planned Behavior (TPB) [18]. We use TPB because it is suitable to explain any behavior which requires planning, such as consumers' CIOS. Various researchers used different approaches to the TPB model: TPB was integrated with the construct(s) derived from various models [28]. In another study, TPB was employed as a research of the attitude towards the transaction and subjective norm directly influencing the intention of online transactions [29].
The TPB is based on three factors, namely, attitude toward the behavior, subjective norms, and perceived behavioral control. As indicated in TPB, attitudes of consumers are affected by subjective norms to deal with CIOS. Furthermore, subjective norms are expressed by how the behavior is being affected by the perceived opinions of others.
Our study tried to reveal that attitude is positively related to consumers' CIOS. It can be argued that TPB is a useful theoretical framework to investigate the attitudes among consumers to engage in consumers' CIOS. TPB proposes that consumers' intentions can best be predicted by their attitudes, subjective norms, and perceived behavioral control. Under the TPB, especially due to the addition of the perceived behavioral control factor, a decision to act is the best predictor of consumer intentions.
This study examines consumer CIOS using the key constructs of the TPB which are attitude and subjective norms. Adopting an attitude-behavior approach, this study empirically tests relations of consumer personal values, attitude, social norm, perceived behavioral control (PBC), and willingness to buy goods online. A person has a positive attitude, adheres to subjective norms, a span of stimulation of perceived behavioral control and intention, that certain people will perform the behavior [21]. The previous study related to subjective norms focused on online shopping and the subjects of analysis focused on consumers [30]. Subjective norm has a direct significant influence on the CIOS. The main predictors of consumer CIOS are attitude and subjective norms [31].
Trust is a crucial factor in online purchasing intention. Perceived risk has also been a determining factor in internet shopping intention [32]. Hence, trust has a key role in online transactions that can change attitudes and online shopping intentions. In an online shopping setting, trust is the willingness of a party to be vulnerable to the actions of another party. Consumers are required to trust in an impersonal provider of goods for an online transaction to occur.
In summary, CIOS translates to the consumer's willingness to repurchase goods via the internet. Also, the CIOS is defined as a specific desire to continue an online shopping relationship with a goods provider. Accordingly, it is therefore hypothesized as follow:
Hypothesis 4. SQ and shipping are positively correlated with CIOS.
Hypothesis 5. Attitude acts as a moderator of the relationship between SQ and shipping and thus affects the CIOS.
Fig. 1. Research Model
Method
The approach we adopted for building the intention model follows the original exploratory method, which provides eligibility criteria to explain a phenomenon [33]. The research was conducted in the Jakarta metropolitan area using a survey technique.
The target population of this research was consumers who intended to purchase goods online. The probabilistic samples were collected using the following criteria: (1) the respondents have had online shopping experiences using e-commerce websites, and the website-based apps and mobile-based apps; and (2) the respondents have shopped online at least 5 times in the last 3 months. This criterion relates to the aim of this study, to examine the CIOS. This research was carried out for two months, from January to February 2020.
The survey method as a data collection tool uses a questionnaire distributed to members of a population. The survey method is used in this study to obtain information regarding the consumers' CIOS and identify the relationship between two or more variables in certain situations. The survey technique is used to identify and understand the following variables: (1) SQ; (2) shipping; (3) attitude; (4) CIOS.
Sampling is performed by allotting the same probability of selection to all units of analysis within the population. Based on the sampling, the following sampling measures were applied:
First, to accurately determine a target group, samples are selected to represent the target population. Secondly, we identified the elementary units of the population (N), namely, 10,344,018 smartphone users, and then assessed the population based on a confidence degree of 95% and standard error of ± 5%. This study applied a margin of error of 5% or 0.05.
The sample size used the Slovin formula4 as follows:
n = N / (1 + (N x e 2)) n = 10,344,018 / (1 + (10,344,018x 0.05 2)) n = 10,344,018 / (1 + (10,344,018x 0.0025)) n = 10,344,018 / (1 + 25,860.045) n = 10,344,018 / 25,861.045 n = 399.962
4 Almeda J.V., Capi^rano T.G., Sarte G.M.F. Elementary Sati^ics. Diliman, Quezon City, University of the Philippines Press, 2010. 698 p.
When rounded out, the sample size is 400. n = sample, N = population, e = margin error
The sample size of 400 respondents was suitable for the SEM criteria [34]5.
Table 1. Survey Items
Variables Indicators
SQ adapted from Parasuraman et al. (2005), Zhou et al (2019)
SQ1 tangibles
SQ2 reliability
SQ3 responsiveness
SQ4 assurance
SQ5 empathy
SHP adapted from Ziaullah et al. (2014)
SHP1 reliable
SHP2 safe
SHP3 affordable
SHP4 consolidated
SHP5 timely
SHP6 return of goods
ATT adapted from Ajzen (2005)
ATT1 useful
ATT2 entertaining
ATT3 interesting
CIOS adapted from Ajzen (2005)
CIOS1 intend
CIOS2 willingness
CIOS3 friendly
CIOS4 subjective norm
CIOS5 fruitful
CIOS6 beliefs
Notes: SQ — Service quality, SHP — Shipping, ATT — Attitude, CIOS — Continuance intention of online shopping.
Results
For the demographic section, the respondents are divided into 4 groups according to different characteristics which are gender, level of education, age as well as total annual income. In terms of gender, 42.4% of the respondents are male and 57.6% are female. In terms of age, the majority of respondents came from the millennial and Z generations (88.9%) with only a small portion of the baby boomer generation (6.9%). In terms of the education of the respondents, most of them had high school education (39.3%), followed by those with a diploma, undergraduate and postgraduate level, respectively 24.6%, 11.3%, and 21.6%. These results indicate that millennials tend to have a better education. In terms of the level of income, 35% of the respondents had low income, and 61.5% had middle income. Only 3.5% were characterized as high-income respondents.
The analysis in this section is conducted to provide information about the consumer profiles consisting of start-up choices and products purchased online. The choice of application/website for online shopping is as follows: Shopee (23.50%), Tokopedia (23.25%), Bukalapak (15.75%), Blibli (15%), Lazada (12%) and JD.id (10.50%). The results of a comparison between the research report by iPrice Indonesia for the fourth quarter of 2019 and the Indonesian E-commerce Map, which ranks the large e-commerce players based on the average website visitors in each quarter, are not much different in succession: Shopee, Tokopedia, Bukalapak, Lazada, Blibli, and JD.id.
5 Hair J.F., Black W.C., Babin B.J., Anderson R.E. Multivariate data analysis. 8th ed. Bo&on (MA), Cengage, 2018.
The categories of products purchased online are fashion, 32.75%; souvenirs, 14.25%; cosmetics, 13.50%; gadgets, 13.50%; electronics, 8%; and health products, 18%. Similar results indicated that fashion products are the most popular among consumers. The products most often purchased online are fashion (45.8%), accessories (10.9%), and shoes (6.7%)6. Only health products are different, which is due to the Covid-19 pandemic. The economic pressure caused by the Covid-19 pandemic at the time of the survey was not visible. The Covid-19 case in Jakarta has not yet been released by the Government of Indonesia.
The results of the confirmatory factor analysis via SEM are used to analyze each indicator variable. Construct measurements are presented in Table 2.
The various types of SQ organized by start-up were measured by the SQ, which requires SQ attributes, namely, reliability, responsiveness, assurance, empathy, and tangibles. The results showed that assurance (with a = .85), reliability (with a = .82) and responsiveness (with a = .61) were the main SQ values, which indicates that start-up companies are already running well if they are trusted and reliable. The construct of SQ observed is consistent with the research [8, 9, 11, 12], which indicated that the perceived SQ is based on assurance (i.e., security, protect data, and guarantee not to abuse) and reliability (i.e., accurate, fully responsible and without access failure).
Table 2. Summary of measurement scales
Variables Indicators Weight value factor a CR P
tangibles .65 .43 25.70 .00**
reliability .90 .82 62.59 .00**
SQ responsiveness .78 .61 37.41 .00**
assurance .92 .85 70.60 .00**
empathy .65 .43 25.70 .00**
reliable .75 .56 33.26 .00**
safe .70 .49 28.92 .00**
cnp affordable .78 .61 37.14 .00**
Snr consolidated .68 .46 27.62 .00**
timely .86 .75 50.77 .00**
return of goods .55 .30 19.43 .00**
useful .82 .67 42.08 .00**
ATT entertaining .85 .72 47.16 .00**
interesting .83 .69 43.80 .00**
intend .79 .62 37.81 .00**
willingness .79 .63 38.82 .00**
CIOS friendly .76 .57 34.33 .00**
subjective norm .83 .69 44.47 .00**
fruitful .83 .69 44.18 .00**
beliefs .85 .73 48.75 .00**
Notes: SQ — Service quality, SHP — Shipping, ATT — Attitude, CIOS — Continuance intention of online shopping.
Hereafter, the constructs of shipping include (1) reliable, (2) safe, (3) affordable, (4) consolidated, (5) timely and (6) return of goods. The results showed the following: timely, a = .75; affordable, a = .61; and reliable, a = .56. Thus, these three constructs are the main values of shipping, which indicates that timeliness does affect the CIOS consumer perception. This result is consistent with the notion that a reliable, safe and timely delivery is something essential for online consumers [14].
Several indicators are used to measure attitude, namely, useful as a cognitive element (a = 0.67), entertaining as an affective element (a = 0.72), and interesting as a conative element (a = 0.69). All three indicators are the primary values for attitude. In addition, the constructs of CIOS include intend (a = .62);
6 Top 50 E-Commerce Sites & Apps Indonesia in 2020. URL: https://iprice.co.id/insights/mapofecommerce/en/ (accessed March 28, 2020).
willingness (a = .63); friendly (a = .57); subjective norms (a = .69), fruitful (a = .69) and beliefs (a = .73), which are the primary values for the CIOS.
We used SEM to test and analyze the hypothesized relationships in the proposed research model. This method was chosen because SEM allows for the testing of independent variables against the dependent variables at the same time. Thus, the SEM technique is simultaneously applied to several dependent variables that are directly or indirectly related to consumers' CIOS. Hypothesis testing using the SEM is performed to determine the model suitability and parameters used in the research through an absolute test of goodness-of-fit. Six tests must be performed to determine whether a model has reached the stage of absolute goodness-of-fit, and four of these six tests indicate that the model has reached the stage of absolute goodness-of-fit7. The SEM analysis shows that the six absolute goodness-of-fit tests are appropriate and suitable: probability values of the chi-square ratio statistics 6.79 (df = 3, p = .08); GFI = .97; RMSEA = = .08; AGFI = .89; CFI = .98; and NFI = .97. Thus, this model is formed to confirm the theory based on observational data.
The effect of SQ, shipping, attitude and CIOS can be identified based on the path coefficients between the variables used. Attitude is influenced by SQ as indicated by the p-value = .00 < .05, while shipping (p-value = .09 > .05) does not affect attitude. CIOS is significantly affected by attitude (p-value = = .00 < .05) and SQ (p-value = .00 < .05). Meanwhile, shipping (p-value = .13 > .05) does not affect CIOS.
Table 3. Path Coefficients of the Variables
Variables Estimate S.E. C.R. P
SQ ATT .27 .08 3.43 .00**
SHP TT .07 .04 1.70 .09
ATT CIOS .74 .20 3.69 .00**
SQ CIOS .85 .18 4.74 .00**
SHP CIOS .08 -.05 -1.52 .13
Note: CR - Critical Ratio
**p < .05
The relationship the model used to test the hypotheses is presented in Fig. 2. Shipping is negatively associated with CIOS as indicated by the -.05 coefficient, whereas the coefficient between SQ and CIOS is .18, between attitude and CIOS is .20, between attitude and shipping is .04 and between attitude and SQ is .08.
In this research, the hypotheses are tested by comparing the p-value < .05 to determine the significance level. When the p-value is < .05, Ho is not supported, whereas if the p-value is > .05, Ho is supported. The research hypothesis test was performed for all analysis results.
As described, SQ is positively associated with CIOS, which is indicated by a positive regression coefficient of .85 with CR at 4.74 and p = .00 < .05 In other words, the results of this research show that higher SQ has a significant effect on CIOS. Thus, the hypothesis is supported.
Furthermore, shipping influences CIOS negatively, although the effect is not significant as indicated by the p-value of .13 > .05 and regression coefficient of .08, which indicate that increased shipping does not affect attitude (p = .08 > .05). The CR value is -1.52, which indicates that none of the relationship effects were detected. Thus, the hypothesis stating that shipping has a positive effect on CIOS is not supported.
Attitude also has a significant influence on CIOS (regression coefficient of .74 with CR at 3.69 and p-value = .00 < .05); thus, H3 is supported. As described in Table 4, SQ and shipping are positively associated with CIOS as indicated by the following results: p =.00 < .05 and F = 13.73. Thus, H4 is also supported. Furthermore, the R2 value was .03, which means that the CIOS is only 3% influenced by SQ and shipping.
7 Hair J.F., Black W.C., Babin B.J., Anderson R.E. Multivariate data analysis. 8th ed. Bo&on (MA), Cengage, 2018.
Fig. 2. Model analysis results
Table 4. Relationship between SQ and shipping with CIOSb
R R2 Change R2 S.P. F df1 df2 Sig. F
.17a .03 .03 8.70 13.71 2 881 .00**
Note: a Predictors: (Constant) SQ and shipping ** level value .00 < .05 b dependent variable: CIOS
Finally, the relationship between attitude and shipping is not significant, which is indicated by the p-value of .09 > .05 and regression coefficient of .04. This finding means that a person's attitude does not change because of shipping. Furthermore, the relationship between attitude and SQ is significant, which is indicated by the p-value of .00 < .05 and regression coefficient of .08. This finding indicates that there is a positive relationship between attitude and SQ. Attitude has a significant relationship with CIOS, which is indicated by the p-value of .00 < .05 and beta coefficient of .20. This finding shows that there is a positive relationship between attitude and CIOS. The results showed that the relationship between attitude and shipping is not significant, while the relationship between attitude and SQ is significant. Therefore, attitude does not act as a moderator of the relationship between SQ and shipping and CIOS. Thus, the empirical results do not support H5.
Discussion
The hypotheses tests have proven that SQ and consumers' attitude affect the CIOS. The study's findings also confirmed that if together, SQ and shipping have a positive effect on the CIOS, implying that if the companies can offer a better SQ on their websites, consumers will continue to purchase online [2, 8—11].
Consumers considered moving from traditional shopping to online shopping due to its efficiency. Information, ease of use, security, privacy, and reliability are the other main concerns for consumer members when using websites. Consumers expect to get access to websites with facilities that make it easy for them to navigate, to search for products and information, to keep all their personal information in advance, that offer various types of delivery services, and have good and attractive designs and layouts. Besides, this study highlights that attitude is key to CIOS [16, 17, 19, 20].
Finally, if companies want to maintain a long term relationship with consumers, they should provide excellent service for them in their choices for using websites, moreover, in e-commerce, where the SQ instruments are different from conventional businesses. One implication of these findings for managers of both startup and shipping companies is to assess website platform as part of assessing perceptions of SQ.
Conclusion
Startup companies have the potential to offer micro-, small and medium-sized enterprises almost instant access to the global market like never before. SMEs can trade with a higher number of consumers and partners. In turn, several important enablers play a role in moving the startup ecosystem forward. Looking to the future, technology should be harnessed to bridge the gap between conventional SQ and e-SQ. However, technological solutions are less applied by SMEs due to the high costs and involvement of companies.
For Indonesia, the e commerce market is expected to grow rapidly over the next five years. The country is home to some 272 million consumers, reaching 81.87 million smartphone users who are already online. Several major e commerce platforms have increased their interest in the country, although SMEs may not easily adapt to this trend due to the many obstacles in the way.
The above summary is consistent with the findings in this study. In general, startups selected by consumers for shopping online are well-established startups, which are considered unicorns. Most of the products, such as fashion, cosmetics, souvenirs, or gadgets, are purchased online. However, certain products purchased online, such as fashion or electronic goods, are usually not produced by SMEs.
We identified certain effects between variables in the SEM analysis. For example, shipping does not affect CIOS. The findings also indicate that SQ and attitude are positively correlated with CIOS. Besides SQ, attitude constructs are critical factors that promote the CIOS. The constructs of attitude, namely, the cognitive, affective, and conative elements, are able to explain individual desires and generate a positive attitude towards online shopping. Moreover, SQ and shipping are associated with CIOS because SQ and shipping had positive effects on CIOS. Such a relationship is reasonable because online shoppers are more concerned with their goods received.
Finally, this research found that attitude is not a moderator of the relationship between SQ and shipping and CIOS. Thus, attitude cannot modify the relationship between SQ and shipping with the CIOS. Moreover, attitude in the context of e-commerce cannot be used to measure the strength of the relationship between SQ and shipping and the customers' CIOS or to determine the most promising shipping service company with timely deliveries . This relationship distinguishes the attitudes of customers between offline shopping and online shopping.
The results on consumer perception show that shipping is not an issue in e-commerce, especially in Jakarta, which is a metropolitan area in Indonesia. However, the consumer is most concerned with the consistency of the implementation of the main model of SQ. Implementation of SQ constructs into online shopping that the employed service features produced a significant influence on the CIOS. Besides, a startup company must understand what can distinguish the products and services it offers for the consumers.
Based on this research, a number of challenges of the e-commerce industry in Indonesia are reflected within the next 5 years when the Covid-19 Pandemic ends, including the e-commerce industry competitiveness and the prediction that it will "burn money" when startups enter the market to draw in consumers; expensive and incompetent logistics or shipping services holding down the e-commerce industry; lack of relevant human resources, especially in the fields of science and engineering required for the development of e-commerce industry governance.
Limitation
This study also has certain limitations. First, this research analyzes the effect of attitude towards online shopping, SQ, shipping, and CIOS. This study suggests that future researchers may adopt the model of the present study. In addition, there are other variables that may affect CIOS. The authors also suggest that future researchers may use other variables for exploration and analysis to make it widely developed.
Secondly, this research has been conducted exclusively on startup companies that partner with shipping companies and SMEs, and also the results and conclusions of this research might not apply to other industries. This model may also be utilized by researchers to test it within the e-commerce industry, which has
its own shipping division on condition that the results of the findings on consumer perception show that shipping is not an issue in e-commerce.
Thirdly, due to a shortage of time, the researchers did not manage to select a greater number of subjects to meet the requirement of a large sample size. Those who were chosen were based in Jakarta, hence not able to represent the population of Indonesian online consumers. Therefore, future research should be done with an increased sample size with various characteristics.
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Статья поступила в редакцию 14.01.2021.
THE AUTHORS
MULJONO W.
E-mail: wiryantamuljono@gmail.com PERTIWI S.P.
E-mail: priyankapertiwisetiawati@gmail.com
KUSUMA D.P.S.
E-mail: pritasetyakusumadewi@gmail.com
© Санкт-Петербургский политехнический университет Петра Великого, 2021
