1. Introduction
E-commerce continues to grow, initially only affecting the way people advertise and selling goods, then changing the way people shop, and finally, it continues to change the way retailers do business in Indonesia. The extraordinary acceleration in technological developments has led to the emergence of a new tradition of retail business, which is known as Multi-Channel. Multi-channel retailing includes a set of activities whose purpose is to sell goods and services through more than one channel, where these channels live together and allow interactions between them that are triggered by the customer or deliberately controlled by the retailer (Martin & Palmatier, 2020).
The urgency of this research is that there is a significant decrease in the Retail Sales Index. The IPR growth rate from 2015 reached 13.5%, followed by 10.8% in 2016, to 2.9% in 2017. This was followed by IPR growth of only 3.7% in 2018 and 3.8% in 2019.
Savitry (2020) states that the conditions after the new normal have forced various companies to be able to carry out an Omni-channel strategy. This is because people are now shopping online more because of concerns about the transmission of the virus. If you have to leave the house for a short time only. This shows the readiness of consumers for this Omni-channel style retail. For this reason, retail industry business actors need to be prepared to be able to answer new ways of shopping from consumers.
Researchers such as (Payne et al., 2017; Huré et al., 2017) discuss the gaps that must be filled in multi- and Omni-channel theories. Payne et al. (2017) identified the need for Omni-channel studies across most consumer theories including behavioral intentions, comparisons of utilitarian and hedonic experiences. Consumer behavior has changed dramatically as a result of advances in mobile platforms and social networks, as well as the convergence of these emerging channels into online and offline retail. Consumers are increasingly using alternative channels to buy products or services, request information, and ask questions about use or availability (Xu & Jackson, 2019). When customers switch to different platforms, the multichannel approach where silo channels are planned and handled independently of each other is inconsistent and fraught with inconsistencies (Saghiri et al., 2017). In an Omni-channel setting, channels are used simultaneously throughout the search and purchase period, making it very difficult for retailers to maintain control (Mladenow et al., 2018).
Kazancoglu and Aydin (2018) found that the Omni-channel experience provides shoppers with speed, access, time, price incentives, ease of use, and other benefits. Zhang et al. (2018) argue that Omni-channel retail provides consumers with a rich shopping experience with positive purchase intentions that build satisfaction and trust, contrary to this Xua and Jackson (2019) discuss that Omni-channel settings require transparency, convenience, and uniformity to drive shopper purchase intentions.
Utilitarians are mostly transactional based, hedonists are emotional (Yrjola et al., 2018). Customer buying patterns involve both task-based and experience-based. In task-based buying, the customer perceives the purchase as a means to fulfill certain specific goals. Whereas in experience orientation, they do not want to just buy, they want to feel all purchasing activities including the products or services they buy.
In fact, not only purchasing channels must be connected, but also payment services, stock warehouses, delivery of goods, IT systems, and others (Kembro & Norrman, 2019). Representing this, many studies have used channel integration variables. This research will try to provide an appropriate frame of mind for business people in dealing with existing phenomena. Providing a picture that is not only scientifically justifiable, but also practically applicable, especially in terms of what consumers are actually looking for today.
2. Review of Literature and Hypotheses Development
2.1. The Effect of Utilitarian Value, Hedonic Valueon Shopper Satisfaction
There are many studies that examine the relationship and influence of utilitarian value and hedonic value on customer satisfaction (Djelassi et al., 2018). Research by Djelassi et al. (2018), which was conducted at shopping malls, proved that there was a positive and significant influence between utilitarian and hedonic values on customer satisfaction. Research by Vieira et al. (2018) conducted a study whose purpose was to determine whether there was a relationship between utilitarian and hedonic shopping value on satisfaction at the retailer. Research by Moharana and Pradhan (2019) conducted a study whose purpose was to determine whether there was a relationship between utilitarian and hedonic shopping value on satisfaction at the retailer. The first and second hypotheses are thus formalized that;
H1: Utilitarian value has a positive effect on shopper satisfaction.
H2: Hedonic value has a positive effect on shopper satisfaction.
2.2. The Effect of Channel Integration Quality has a Significant Effect on Omni-Channel Shopping Intention
Omni-channel is the integration of multiple channels for simultaneous use of online and offline channels, regardless of the stage of a consumer's shopping journey (Lee et al., 2019). More than half of consumers participate in three to five channels in their buying or shopping journey (Lee et al., 2019). For example, they seek information from one channel and buy from another. In this situation, consumers' expectations of being able to easily use consistent information regardless of channel type have increased (Lee et al., 2019). Therefore, channel integration can be a key factor in the success of omni-channels (Lee et al., 2019). As a result, without considering quality, coordinated integration has no synergy for both companies and consumers (Lee et al., 2019). The third hypothesis, thus, is formalized that
H3: Channel Integration Quality has a significant effect on Omni-channel shopping intention.
2.3. Utilitarian Value, and Hedonic Value, towardsOmni-Channel Shopping Intention
Akram et al. (2021) proves that there is a positive and significant direct influence of utilitarian value and hedonic value on purchase intention in the context of social commerce products. This study also found that utilitarian value is a more dominant factor in determining purchase intention. In a study by Susanto et al. (2018), various antecedents of purchase intention can be found in the context of Omni-Channel. Among them are performance expectancy variables (one of which is utilitarian value), and hedonic motivation. The results of the study found that performance expectancy had a significant effect, while hedonic motivation did not affect Omni-channel shopping intention. The research of Evelina et al. (2020) examined the role of utilitarian value, hedonic value, and perceived risk on customer repeat purchase intention. This research has a B2C e-commerce context. In this regard, the study of Sun and Gao (2020) tries to see whether there is an influence between extrinsic and intrinsic motivation on intention-to-use. The fourth and fifth hypotheses, therefore, are formalized that:
H4: Utilitarian Value has a significant effect on Omni-channel Shopping Intention.
H5: Hedonic Value has a significant effect on Omni-channel Shopping Intention.
2.4. Channel Integration Quality on Omni-Channel Shopping Intention
Like the study from Xin et al. (2022) with a multi-channel context, it was found in this study that there is an indirect effect between integration quality on online purchase intention, which is mediated by online perceived value. In this case, integration quality is represented in 4 (four) dimensions. Meanwhile, the journal from Wang and Zhang (2018), uses the concept of multi-channel service quality which includes aspects of physical service, virtual service, and integrated service. It can also be found in research linking service quality which according to Lee et al. (2019) is the beginning of the existence of integration quality. The research is from Suwannakul and Khetjenkarn, (2022) which links Interpersonal Service Quality and SST (Self-Service Technology) Service Quality with retail patronage intention, with technology anxiety as a mediating variable. The sixth hypothesis, thus, is formalized that:
H6: Channel Integration Quality has a positive and significant effect on Omni-channel Shopping Intention
2.5. Omni-channel Shopping Intention and Shopper Satisfaction
While behavior here can be described as a measure of the strength or drive in which a person intends to perform a certain behavior. Conceptually, many theories refer to the cognition-affect-behavior relationship (Zheng et al., 2022). This concept was also used in the study of Albayrak and Caber (2018) which examined the relationship between satisfaction and intention to purchase, and found a significant relationship between the two. In social commerce applications, Okada et al. (2019) proves that there is a positive and significant influence between satisfaction and purchase intention. Meanwhile, in the context of multi-channel retailing, research from Wang and Zhang (2018) developed one hypothesis, namely: the higher the satisfaction with the new multi-channel integrated store, the higher the purchase intention of consumers to shop at the store. The seventh hypothesis, thus, is formalized that:
H7: Omni-channel shopping Intention has a positive and significant effect on shopper satisfaction
Table 1: Inconsistency Research
3. Research Methods
This study uses quantitative research methods. Quantitative research is research by collecting data taken from a representative sample of a population. In the context of this research, we will use a representative sample of retail users who have implemented an Omni-channel strategy in selling their products. This is because Omni-channel is a perfect blend of online and offline shopping, researchers use data on internet users in Indonesia. Regarding the number of respondents or samples from the study, referring to the approach of Hair et al. (2019), which said that the number of samples was determined based on the number of indicators, and multiplied by 5 (five). So based on this approach the minimum sample size is 250. This study uses a purposive sampling technique. Data were collected from major cities in Indonesia to provide evidence that the hypothesized model is not culture or sample specific results. The hypothesis was tested using SEM-PLS because our data contain a large variance which is indicated by the large variance of the data distribution across sample locations and demographics. To identify any variance, the AVE (Average Variance Extracted) test was applied to all items. In addition, the reliability of the model was tested with composite reliability (CR) to identify convergent validity problems in the tested model. Finally, to test the hypothesis, Structural Equation Modeling (SEM) is used which is an analysis of the research model to determine the relationship between variables in the study by providing a quantitative test of the theoretical model hypothesized by the researcher again (Anderson et al., 2019).
4. Results
Respondents from the distribution of questionnaires obtained 250 respondents who meet the requirements in Jabotabek. A total of 250 respondents whose profiles are described in Table 2.
Table 2: Respondent Profile
The 250 respondents who participated in this survey, most of them were female (56.8%), aged between 25-34 years (38.8%), located in Jabotabek (100%), have a bachelor's degree (46.4%) which indicates that the respondents perceive as young and educated. The most dominant occupation is private employee (31.6%). And household contests per month Rp. 3,500,001 – Rp. 5.000.0000/month by 39.2%. This respondent profile is relevant to the purpose of this study to analyze the effect of utilitarian value, hedonic value, channel integration quality on Omni-channel shopping intention and shopper satisfaction.
Construct reliability (Cronbach's alpha and composite reliability), construct validity (Average Variance Extracted-AVE), and discriminant validity (Heterotrait-Monotrait Ratio). In the external model output test, 28 indicators meet the external loading requirements. The outer model test results in Table 3 show that all reliable indicators in the research model are in accordance with the required outer loading value.
Table 3: Construct Reliability and Validity
Table 3. shows that all indicators have outer loading > 0.70 as required, with Cronbach alpha and composite reliability greater than 0.7 which indicates that the internal consistency of the construct is reliable. The AVE measures convergent validity checks, where all values have an AVE of 0.50, indicating that all constructs explain at least 50 percent of item variance and therefore establish validity (Hair et al., 2019).
To test the discriminant validity, the Heterotrait-Monotrait Ratio (HT/MT) is used because this method is known to have a more precise value (Hair et al., 2019). Referring to (Hair et al., 2010) the value of the Heterotrait-Monotrait Ratio table 4. none is above 1 so it can be said that the research model formed from the four variables above is valid. Table 3 (HT/MT Ratio) shows that all HT/MT values are well below the threshold of 1 for all variables. Thus, it is concluded that all indicators used in this research model have adequate discrimination to measure their respective constructs.
Table 4: Discriminant Validity : HT/MT Ratio
It can be concluded that all indicators in this research model have been well discriminated against and can measure their respective constructs. Each indicator can accurately and specifically measure its construct. There are four parameters to test the reliability and validity of the outer model above, namely reliability indicators (outer loading), construct reliability (Cronbach's alpha and composite reliability), construct validity (average variance extract), and discriminant validity (Heterotrait-Monotrait ratio).
Because goodness of fit is not used in PLS-SEM as suggested by Hair et al. (2019) this study performs R2 to measure predictive accuracy and the value of Q2 cross redundancy to measure the relevance of the test model predictions. As a rule of thumb, R2 values of 0.75, 0.50, and 0.25 can be considered substantial, moderate, and weak (Henseler et al., 2009; Hair et al., 2011). Omni-channel shopping has R2 = 0,931 and Q2 = 0.273, and shopper satisfaction (R2 = 0,595; Q2 = 0.466). Both, Omni-channel shopping and shopper satisfaction have moderate predictive accuracy (Hair et al., 2019).
Hypothesis testing with the bootstrap procedure was carried out to determine the effect of the variables and determine whether the hypothesis proposed by this study was supported. A bootstrap approach was used to determine the significance of the data (Memon et al., 2021). T-statistic cut-off value > 1.96 (one-tailed) with an alpha of 0.05 was used as a criterion to determine whether the hypothesis was supported or not.
Table 5 : Significant and Coefficient
Hypothesis testing with the bootstrap procedure was carried out to determine the effect of the variables and determine whether the hypothesis proposed by this study was supported. A bootstrap approach was used to determine the significance of the data. T-statistic cut-off value > 1.96 (one-tailed) with an alpha of 0.05 was used as a criterion to determine whether the hypothesis was supported or not.
Figure 1: Conceptual Framework
4.1. Discussion
Based on the results of the calculation, the t-count value (4,131) >1.96, it can be concluded that accept H1 and reject H0, which means that there is an influence between Utilitarian value on Omni-channel shopping intention. This shows that utilitarian values and hedonic values have begun to be included in the context of economic digitization by several researchers. Such as research from Moharana and Pradhan (2019) which reviews utilitarian value and hedonic value in social commerce. Research from (Djelassi et al., 2018) prove that utilitarian value and hedonic value have an influence on Omni-channel shopping intention in the context of B2B e-commerce.
Based on the results of the calculation of the t-count value (0.648) < 1.96, it can be concluded that rejecting H1 and accepting H0, which means that there is no effect between hedonic values on Omni-channel shopping intentions. This is different from the research of Vieira et al. (2018) which examines consumer behavior towards mobile social networking sites (SNS). The results of the study prove that both hypotheses can be accepted. On the other hand, there are also studies that reflect the utilitarian through the usefulness dimension, and hedonic through the enjoyment dimension (Djelassi et al., 2018; Moharana & Pradhan, 2019). Research Chun and his two friends, using a sample of students in Korea. The results of the study prove that there is a positive and significant direct effect between utilitarian-usefulness and hedonic-enjoyment, on the intention to adopt smartphone product use.
Based on the results of the calculation, the value of t count (1.336) < 1.96, it can be concluded that we reject H1 and accept H0, which means that there is no influence between the Channel integration quality on Omni-channel shopping intention. This contrasts with several other studies that have attempted to link the relationship between multi-channel service quality and shopping intention (Lee et al., 2019; Z. W. Lee et al., 2019). This research was conducted in the retail industry which aims to analyze the relationship between the variables of service quality, attitude, satisfaction, and purchase intention.
Based on the results of the calculation of the t-count value (3.148) > 1.96, it can be concluded that accepting H1 and rejecting H0, which means that there is an influence between the utilitarian value on Shopper satisfaction. This is supported by research by Akram et al. (2021) which states that in the context of Omni-channel shopping; and the nature of physical spending develops in both its utilitarian and social dimensions. Sun and Gao (2020) can find various antecedents of purchase intention in the context of the Omni-Channel. Among them are performance expectancy variables (one of which is utilitarian value), and hedonic motivation. The results of the study found that performance expectancy had a significant effect, while hedonic motivation did not affect Omni-channel purchase intention.
Based on the calculation results, the t-count value (3,788) > 1.96, it can be concluded that reject H1 and accept H0, which means that there is no influence between hedonic value on shopper satisfaction. This is supported by research by Evelina et al., (2020) which refers to the ABC attitude model (affect, behavior, and cognition), using utilitarian and hedonic values as a cognitive response, and followed by attitude and satisfaction as an effective response. While the construct of intention to purchase is used as an element of behavior. The results of the study found that there was a significant influence between utilitarian and hedonic values on satisfaction. In the context of social commerce, Susanto et al. (2018) prove that there is a positive and significant direct influence between utilitarian value and hedonic value on satisfaction, where hedonic appears as a more dominant factor in this study.
Based on the calculation results, the t-count value (2.813) >1.96, it can be concluded that accept H1 and reject H0, which means that there is an influence between channel integration quality on shopper satisfaction. This is supported by research by Xin et al. (2022) succeeded in proving that perceived multi-channel quality is one of the antecedents that positively and significantly affects customer satisfaction in the banking industry. Meanwhile, the study of Lee et al. (2019) also found a relationship between service quality perception and satisfaction. This research was conducted in the retail industry which aims to analyze the relationship between the variables of service quality, attitude, satisfaction, and purchase intention.
Based on the results of the calculation, it is found that the value of t count (4,194) >1.96, it can be concluded that accept H1 and reject H0, which means that there is an influence between Omni-channel shopping intention on shopper satisfaction. This is in accordance with the research of Zhang et al. (2018) who tried to study the relationship between satisfaction and patronage intention, and apparently the results also stated that the hypothesis was acceptable. Zhang and his colleagues' research is in line with the results of research by Jones, Reynolds and Okada et al. (2019) who found that retailer satisfaction has a positive and significant effect on re-patronage intention. Meanwhile, in the context of online shopping, Wang and Zhang (2018) prove that there is a positive and significant direct influence of satisfaction on website quality, with the variable purchase intention.
5. Conclusion and Limitation
5.1. Conclusion
Based on the results of the analysis and discussion, it can be concluded that there is an influence between the Utilitarian value on the Omni-channel shopping intention, there is no effect between the hedonic value on the Omni-channel shopping intention, there is no influence between the quality of Channel integration on the Omni-channel shopping intention, there is an influence between the quality of Channel integration and the Omni-channel shopping intention between utilitarian values on shopper satisfaction, there is no effect between hedonic values on shopper satisfaction, there is an influence between channel integration quality on shopper satisfaction, and there is an influence between Omni-channel shopping intentions on shopper satisfaction. The findings of this study prove that Omni-channel is one of the most effective management and marketing techniques to enhance an important aspect of their company, namely an efficient and holistic consumer shopping experience.
These findings provide guidance for the integration of Omni-channel retailer channels and customer value propositions. Retailers must deliver more hedonic and social value in the entire customer shopping process through channel integration and consider customer purchasing plans when delivering utilitarian value.
5.2. Limitation
This research has been carried out optimally. However, there are limitations to the study, namely the selection of research objects and limited samples, thus limiting the generalization of research results. Future studies may consider adding other research objects for comparison, increasing the research sample size to a larger size, and for future research it is necessary to include the role of technology in examining perceptions of utilitarian value, hedonic value and channel integration quality on shopper satisfaction.
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