A Study on the Influence of Omni Channel's Shopping Value on Users' Innovative Tendency and Service Attitudes

Abstract

Purpose: Due to COVID-19, the rapidly changing untact culture from offline to online has spread rapidly, increasing the utilization of omni-channel. However, among the studies on consumers in the online market, there are not many studies that analyze Shopping Values and attitudes toward omnichannel Acceptance. Research design, data, and methodology: This study investigated through empirical analysis how Shopping Values and innovation propensity of consumers using omni channels affect omni channel Acceptance attitudes. The analysis results based on a total of 268 questionnaires using SPSS v.23 and AMOS v.23 statistical programs are as follows. Results: First, it was found that the perceived Value of omnichannel use had a positive effect on the innovation tendency, and the pleasure Value had a greater effect than the actual Value. Second, it was found that the practical and hedonic Value of the omnichannel had a positive effect on the attitude of service Acceptance. Third, it was found that Omni Channel's consumer innovation tendency had a positive effect on service Acceptance attitude. Conclusion: This study proved that Shopping Value perception and individual innovation propensity for omnichannel services have a positive effect on Acceptance attitude, and it is of academic significance in that it expanded understanding of what factors are needed to increase Acceptance attitude of Omni Channel services.

1. Introduction

Omni Channel is a word describing the way that distribution Channels work using all the IT technology available. The word Omni means ‘all’ and it encompasses all technology available including online, offline, mobile or a desktop device. Omni Channel allows the consumer to search and make purchases using all the available distribution Channels. (Verhoef et al., 2015). Today, consumers can choose a single Channel, to multi-Channel, or cross Channel, but the consumers are transitioning into Omni Channel. (Berman & Thelen, 2004). Since the advent of Omni Channel, the distribution companies can connect and operate all processes from product planning, sales approval, and inventory control through integration of all the Channels, thereby increasing sales by providing lower price benefits to consumers. Consumers are also expected to be able to communicate more effectively with the distribution companies and establish a virtuous cycle with the companies (Pauwels & Neslin, 2015). Since the start of the pandemic in 2020, face to face interactions have been heavily reduced, the utilization of online from offline activities have increased even in the areas of logistics and distribution. The companies utilizing Omni Channels have placed themselves in the best position to capture the new phenomenon called ‘reverse showrooming,’ where the consumer does all the Shopping and comparison online and comes in the showroom to make the purchase offline (Emily et al., 2017). These signs are from the fact that consumers use more than one Channel to get their information. The consumers use many Channels to find the best information and use the more favorable Channels to finish their Shopping and have become ‘smart consumer.’ This course of conversion has been disproved (Herhausen et al., 2015). The companies are not only valuating the consumers on an economic level, but also an experiential level as well. And therefore, the companies must utilize the Omni Channel method to increase consumer satisfaction (Ailwadi & Farris, 2017). The studies being conducted about Omni Channel on a conceptual level and introduction was conducted by Verhoef et al. (2015), Another study by Flavian et al. (2016); Herhausen et al. (2019); Konus et al. (2008) looks at the acceptance and attitudes by consumers about Omni Channel. Zhang et al. (2009) studied about the usages and usability of Omni Channel. Chen et al. ( 2011); Beck et al. (2015) studied about the technological needs of Omni Channel. On the other hand, people tend to prefer things that they are familiar with, therefore, the usage of modern technology can vary depending on the savvy of the consumers. Recently simple payments and mobile payments have been quickly on the rise, but very few research has been performed empirically analyzing the spending habits of MZ generations. This research will be to determine the attitudes of consumers about the usage and usability of Omni Channels in a very empirical view.

2. Theoretical Background

2.1. Shopping Value

Shopping Value is a subjective evaluation of factors that consumers experience through price, product quality, and benefits of purchase. It also refers to the enduring belief that consumers have about the act of shopping (Tynan et al., 2010). Hirschman and Holbrook (1982) described the practical aspects of problem solving and acquiring Shopping Value and how it was divided into pleasure aspect that pursues itself. In other words, consumers follow their beliefs in what they Value and make purchases accordingly. Holbrook and Corfman (1985) define Shopping Value from a two-dimensional point of view: utilitarian Value that occurs in the process of acquiring an object with a clear purpose, and a hedonic Value, a joy that arises from the act of purchasing itself. Utilitarian Value refers to the Value obtained when consumer makes an active decision and intentionally purchase based on rational and practical judgement (Babin et al., 1994). Consumers who Value the utilitarian Value are task oriented, so they want to purchase something that meets the Value of specific needs and successfully resolved with thorough research and collecting sufficient data about the products and services (Baldauf et al., 2003). Following that, in the process of obtaining a product or service according to one’s plan, economic Value, Shopping efficiency, and excellence of products or services is prioritized (Mathwick et al., 2001). On the other hand, consumers who pursue hedonistic Values that pursue psychological and experiential Values satisfy their needs and recognize Values through emotional responses that they experience through the actual Shopping process rather than the product (Holbrook & Hirschman, 1982). Therefore, the Value is determined by not the product itself, but Value is recognized subjectively by emotional, symbolic, and experiential benefits recognized in the process of shopping itself (Babin et al., 1994). On the other hand, Prior research into predicting consumer behavior related to Shopping Value was done by Eroglu et al. (2005); Jones et al. (2006). Chiou and Ting (2011) claimed that internet consumers most important Value was the actual practical Value of the product, Prashad (2017) claimed that the cognitive and emotional stimulation of online shopping malls persuaded the online consumers to make the purchase and be satisfied with their purchase. On the other hand, many smart retail stores (Adapa et al., 2020), self-service (Lao et al., 2021), Omni Channel (Hure et al., 2017) appeared to make novel studies on Shopping Values (Wongkitrungrueng & Assarut, 2018).

2.2. Innovation Tendencies

According to the innovation attribute theory proposed by Rogers (1995), people’s efforts to pursue changes in the types of people and characteristics of communication Channels and social structure have a significant impact on process of accepting innovations (Yang et al., 2012). In this case the perceived attitude of an innovation is a relative advantage. It consists of compatibility, complexity, trainability, and observability (Mowen & Minor, 1995). Consumer innovativeness, which is based on the innovation diffusion theory refers to the tendency or degree to take risks predicted while adopting new products and technologies more quickly. In other words, innovation tendency is the tendency to actively adapt to the novelty created by the company to try new things. Understand the skills and advise more people and thus experience pleasure (Goldsmith & Hofacker, 1991; Solomon, 2012).

Consumers propensity to innovate are related to consumption related Value types: functional, sensory, cognitive, and social Value types (Sweeney & Soutar, 2001). However, when modern technologies are accepted by the early adapters, they spread the uses of the innovations. It also contributes to the formation of socially favorable attitude while increasing the number of technology adapters. In the event, there are levels of adapters depending on their savvy, at the top are the innovators, early adapter, early majority, late majority, and finally, laggard. In the theory of cognitive dissonance, it says that higher the innovativeness, higher the self confidence that leads to making decisions (Park & Chung, 2011). Therefore, consumers with high innovativeness are valuable to companies since they will be the first to use a new product, new lifestyle, and will affect the companies’ profits (Foxall, 1988). Therefore, prior studies have emphasized the relationship between new product acceptance, attitude, and consumer innovativeness (Im et al., 2007). In previous studies it was found that consumer innovativeness is related to new products or brand purchases. In addition, it was found that an individual’s involvement with a product affects innovative consumer behavior, and that intrinsic innovativeness has a positive effect on new product purchase attempts in the products’ acceptance (Manning et al., 1995). However, consumer innovativeness has no direct impact on new product acceptance. Studies show only an indirect effect (Im et al., 2007). From these and other research, it has been shown that higher the innovativeness of the individual, the more likely that individual would adapt to modern technology. Therefore, it is assumed that using the Omni Channel would be faster and more effective by the individuals with high innovativeness.

2.3. Omni Channel Service Acceptance Attitude

In Social Studies, an attitude is the evaluation of the likes and dislikes of a specific behavior.This can also refer to the consumer’s preference for a particular product or service (Fishbein & Ajzen, 1975; Ajzen, 1991). On the other hand, Acceptance Attitude refers to clearly expressing positive and negative beliefs based on the behavior of consumers who respond positively to the services provided by the company (Um et al., 2020). Therefore, the attitude towards accepting of services is based on the cognitive, political, and economic Values of the consumer. This also refers to the consumer’s likelihood of using Omni Channel for services and goods (Chopra, 2019; Gan & Li, 2018). Previous research on service demand attitudes doubling the theory of acceptance and innovation of modern technologies, and usage of such modern technology to evaluate. In previous studies, the attitude towards accepting new services looks at usefulness, enjoyment, and risk and innovation performance (Alexandra et al., 2020). Most of the research conducted in the past about Acceptance Attitude toward technologies such as the Omni Channel and the relationship between industrial innovation and work performance acceptance (Rogers, 2003). Chauhan (2019) confirmed the effect of consumer propensity on service acceptance and use of modern technologies and services. The relationship between the uses of modern technologies in the fashion industry showed a positive correlation (Lee & Rha, 2013). Using the results from previous research, it can be deduced that people with higher innovativeness tend to adapt to modern technologies faster and have a higher Acceptance Attitude towards new goods and services such as Omni Channel (Chandrasekaran & Telis, 2011). And therefore, it can be assumed that there is a positive correlation between consumer Acceptance Attitude and the innovativeness of the consumers.

3. Research Method

3.1. Research Model

In this study, Shopping Value and innovation propensity of consumers using Omni Channel services as shown in figure 1. A research model was proposed through an empirical analysis of how the Acceptance Attitude was affected.

Figure 1: Research Model

3.2. Research Hypothesis

3.2.1. Shopping Value and Innovation Tendency

For smart watch consumers, Hong et al. (2017) found that young consumers with innovative tendencies were more likely to use online shopping malls than younger consumers with non-innovative tendencies. A study done about the pop-up stores by Fiore et al. (2007) found that innovations in consumption and new forms of marketing related to positive attitudes by the consumers. Pop up retailers can satisfy the consumers with high innovativeness the pleasures of Shopping as well as the practical Values, driving up the need and Values of pop-up retailers (Venkatraman & Price, 1990). Based on the previous studies, the following hypothesis is established.

H1: Practical Shopping Values will have a positive effect on innovation tendencies

H2: The Value of hedonistic Shopping will have a positive effect on innovation tendencies

3.2.2. Innovation Tendency and Omni Channel Acceptance Attitude

The following hypothesis is established based on studies done by Kim et al. (2010), which confirms that individual characteristics, including innovativeness, of American consumers affect desirable benefits and attitudes toward pop up retail.

H3: Innovative tendencies will have a positive effect on service Acceptance Attitude.

3.2.3. Shopping Value and Omni Channel Acceptance Attitude

Kim et al. (2012), found that success of internet shopping malls closely relates to customer satisfaction and purchase intentions (Wolfinbarger & Gilly, 2001). In several studies done by Jones et al. (2006), it was found that there is an importantly relationship between business performance such as Shopping Value and satisfaction, word of mouth effect, repurchase intentions, and neutrality (Yang et al., 2018), show that hedonistic Value and practical Values all claim to have positive effect on purchase intentions. Following these studies, the following hypothesis is established

H4: Practical Shopping Value will have a positive effect on service Acceptance Attitude.

H5: hedonistic Shopping Value will have positive effect on service Acceptance Attitude.

3.3. Measuring Tool

The concept that constitutes this study is the practical Shopping branch of Omni Channel. Hedonistic Shopping Value molding the Channels Service Acceptance Attitude, and operational definition and measurement items for each component is summarized on table 1

Table 1: Construct Parameter, definitions, and Measure

3.4. Collection and Analysis of Data

An online survey was conducted from October 10 to December 9, 2021, of consumers who purchased products through the Omni Channel within the past three months. A total of 300 surveys were collected, but only 268 were used in the study, since the 32 respondents were insincere. For statistical programs SPSS v23 and AMOS v23 were used, and frequency analysis for identifying typical characteristics of respondents, validity and reliability analysis of measurement tools, and structural equation model analysis for hypothesis testing were performed.

4. Analysis

4.1. Typical Characteristics of Respondents

As the typical characteristics of 268 respondents’ gender, age, occupation, and monthly income were investigated as well as the usage of Omni Channel. The results are in Table 2. In the gender, male 49.6%, female 50.4%, a similar number. Age rages were 30’s 32.1%, 40’s 31.7%, 50’s 30.6%, and 20’s 5.6%. Employment ranges were company worker 65.3%, with a monthly pay of 300-399 k won had the largest range of 23.9%. And the usage of Omni Channel twice a month 43.7%, and once at 41.8%.

Table 2: Demographic Characteristics (n=268)

4.2. Feasibility and Trustworthiness Verified

In this study, factor analysis, (exploratory factor analysis, confirmatory factor analysis was conducted to confirm the validity of the measurement tool) for statistical analysis, Cronbach’s alpha was used to verify the results. The exploratory factor analysis was conducted by selecting the Berth analysis method. Serialized inquiry method was conducted.As it can be seen in Table 3, four factors corresponding to an Eigen Value of 1 or higher were derived. If two or more factors were loaded based on the loading amount of the loaded items for each factor, the corresponding items should be removed. But no items were removed since that phenomenon did not occur. Table 3. Next, the confirmatory factor analysis was performed to obtain conceptual reliability (C.R.) and mean variance extraction index, (AVE) for each construct. After calculations, the concentrated validity is judged to be secured when the CR coefficient and AVE coefficient are 0.7 or more and 0.5 or more, respectively. Discriminant validity can be judged to be secured when the AVE I squared root is larger than the correlation coefficient with other constructs (Formell & Larcker, 1981). As a result of comparison between the AVE squared root and correlation coefficient for each construct used in this study as shown in Table 5. The AVE squared root was larger than all correlation coefficients indicating that discriminant validity was secured. For reliability, Cronbach’s alpha coefficient, which can examine the internal consistency between items, was calculated to confirm whether the criterion was met. Cronbach’s alpha coefficient calculation results for each construct, practical Value 0.891, hedonistic Value 0.899, innovation propensity 0.885, Omni Channel Service Acceptance Attitude 0.889, all of which being higher than the standard Value of 0.7 (Nunnally, 1978). The validity of this study was confirmed.

Table 3: Results of Exploratory Factor Analysis: EFA

Table 4: Results of Confirmatory Factor Analysis: CFA

Table 5: Discriminant Validity Analysis Results

() is the square root of AVE.

** p<0.01

4.3. Hypothesis Testing

To statistically analyze the relationship between perceived Value innovation and formation of Omni Channel services, and service Acceptance Attitude, a structural equation adventure that estimates multiple paths at the same time was used x² /df=1.354, RMR=0.065, GFI=0.947, NFI=0.956, RFI= 0.945, CFI=0.980, RMSEA=0.036 became the average figures. After calculations, the results are posted on table 6, and all the 5 hypotheses were adapted as shown. Specifically, the effect of first hypothesis Omni Channels perceived Value on innovativeness was significant (beta 0.197, t=3389, p<0.001) and hedonistic Value (beta 0.590. T=9478, p<0.001). This was found to have an effect and was adopted. Second hypothesis the effect of perceived Value of Omni Channel service from service Acceptance Attitude is (beta=0.215, t=9.478, p<0.001). Hedonistic Value (beta=0.405, t=5.133, p<0.001), showing a significantly positive impact the third hypothesis of the effect of innovativeness on Omni Channels Service Acceptance Attitude is (Beta=0.22, t=2.782, p<0.001), also showing a positive impact.

Table 6: Result of Hypothesis Analysis

*** p<0.001, ** p<0.01, * p<0.05

5. Conclusion

In this study, the perceived Shopping Value and innovation propensity of consumers who use Omni Channel were investigated to determine how they affected their acceptance of Omni Channel services. First, a hypothesis was established through theoretical consideration, and data were collected through an online survey targeting consumers who had experience purchasing products through Omni Channel to perform a statistical analysis of the hypothesis. To summarize the results of the analysis based on collected data,

First, it was found that perceived Value of using Omni Channel service had positive effect on the innovation tendency, and the hedonistic Value had a greater effect than the practical Value. Second, it was found that the practical and the hedonistic Values of Omni Channel services have a positive effect on the service Acceptance Attitude. Third, the consumer’s tendencies to innovate in Omni Channel was found to also have a positive effect on the service Acceptance Attitude. Through the analysis results of this study, the following academic and practical implications can be presented. First, consumers on or offline purchases as well as mobile purchases being combined in the Omni Channel has a positive impact on the service Acceptance Attitude. This has an academic significance in that it proves that individual innovation disposition has a positive effect on Acceptance Attitude and broadens the understanding as a factor necessary to increase the Acceptance Attitude of users. Second, it is meaningful in that it empirically analyzed the perceived Shopping Value as a leading factor that can improve the innovative tendency, which is important in accepting new products or new services or determining the acceptance speed. In particular, the hedonistic Value has a greater effect on the innovation tendency than the practical Value, and it can be inferred that it is due to the interest inducing factor provided in the Omni Channel Shopping environment rather than the single Channel Shopping. Next, the practical implications are first, to maximize the innovativeness of Omni Channel user sand to form a positive Acceptance Attitude. It can raise the importance of developing a perceptual element of Value for Omni Channel services. This is because if the practical and hedonistic Values of Shopping are perceived through the Omni Channel services the advantage of Omni Channel service can be fully realized. This will bring a positive effect on attitude toward accepting and using the new services before others. Therefore, to develop and provide appropriate strategic elements. Second, it is necessary to understand the service levels and requirements provided for groups with high innovation propensity. Also, that user’s propensity to innovate will be more interested in Shopping through Omni Channel services rather than single Channel services. Therefore, it is necessary to separately select the users with high innovativeness, conduct interviews and surveys to derive positive experience factors, and consider applying them to Omni Channel environment. Despite the above implications, this study has the following limitations. First this study was conducted about Omni Channel after the consumer perceived it, so it became biased. Therefore, in future research, it will be necessary to present and verify an integrated model that leads to consumer behavior after use, starting with the antecedent factors affecting the perception of services of Omni Channel. Second, it has limitations in that the characteristics of Omni Channel service users are not considered. The attitude to accept Omni Channel services in the environment was determined by gender. Since the difference may occur depending on demographic characteristics such as age, it will be necessary to include this in the future studies.