Comparing Mediation Effect of Functional and Emotional Value in the Relationship between Pros of Applying Big Data Analytics and Consumers ’ Responses

Applying Big Data analytics application brings many benefits for e-vendors and customers. Exploring the effect of consumer perceived value to consumers’ responses under applying Big Data analytics is lacking. And, what kind of perceived values do customers have more concerns under Big Data era. Therefore, the aims of this study are to analyze relationship between pros of applying Big Data analytics and Consumers’ responses under multiple mediators of perceived values as functional value and emotional value. Data analysis was done in a sample of 349 respondents. The results show that applying Big Data analytics have significant positive effect on customers’ responses. Functional and emotional values act as important mediators on the relationship between applying Big Data analytics and consumers’ responses. There are no significant different between mediator effect of functional value and emotional value. The findings of this study will have implications for e-vendors to understand the important mediator of perceived value on customers’ responses under Big Data analytics era.


Introduction
The amount of data is increasing faster than before due to the continuous generation of the data from many organizations' sources.Therefore, applying the applications of Big Data analytics (BDA) become a trend in all others industries such as healthcare, government, insurance, manufacturing and natural resources and others.Specially, in the e-commerce context, BDA can enable to track customers' behavior and determine the most effective way to connect with new customers and keep the repeat customers (Akter & Wamba, 2016).Applying BDA contributes the higher performance business by providing for e-vendors with transformative benefits to their customers, like as information search, recommendation system, dynamic pricing and customer services (Le & Liaw, 2017).The e-commerce firms that apply BDA into their value chain 5-6 % higher efficiency comparing with their competitors (McAfee, Brynjolfsson, Davenport, Patil, & Barton, 2012).Because of the high benefits of applying BDA in e-commerce to business value and satisfying their customers, BDA has become the trend for recent academic research and industry exploration.Applying BDA in e-commerce can offer many benefits for customers via website such as information search, recommendation system, dynamics pricing and improved customer services.
However, the problem that customers think about the application of applying BDA in running online shopping of e-vendors is not evaluated.Besides, when customers take online shopping, they may want to find benefits for them, like functional value as ease-of-use and satisfactory outcome and emotional values which provide enjoyment of shopping (Bridges & Florsheim, 2008).Cowles, Kiecker, & Little (2002) stated that e-commerce research should consider which kind of perceived value behind customers as their motivation to online shopping.
With those motivations, this research aims to evaluate the mediation effects of functional and emotional value on relationship between positive factor of applying BDA and customers' responses.Another purpose of this study is to examine which mediating effect of functional and emotional value has stronger effect.This contribution of this study could answer the question that is it worth for e-vendors to apply the new tool (BDA) and what kind of perceived value that customers are more interested under Big Data era.

Customers' Responses
A positive consumers' response is a vital intangible asset for an organization and help to grow substantially business either in direct or indirect way.From literature review, there are many ways to measure the customers' responses.However, the AIDA construct (A-Attention, I-Interest, D-Desire, A-Action) is famous presented model for measuring the effective of advertising and marketing on customers responses (Gharibi, Danesh, & Shahrodi, 2012).Under applying application of Big Data analytics, e-vendors will be successful if they can lead their customers to through four stages of hierarchical model as AIDA.Stage one is attracting customers to their new application by applying BDA.Stage two is generating customers' interest and demonstrating features and benefits, consumers get interested in their products or services.Stage three is create customers' desire that make customers feel it is worth to get the products or use the services.After three stages leads to stage four, customers take action to want to know about purchasing and to take the final decision to end the process.The AIDA model was developed in the 1920s based on theory of attracting attention, getting interest, motivating desire, and precipitating action (Mackay, 2005).Moreover, the AIDA model was applied to measured customers' resonponse in others studies (Ehrenberg, 2000;Lee, Lin, Liao, & Yeh, 2013).

The Relationship between Positive Factor of Applying BDA and Customers' Responses
Big Data analytics is defined as a process that includes collection, analysis, and interpretation of Big Data to gain insight value, create business value and establish the competitive advantages (Akter & Wamba, 2016).Applying BDA bring advantages for e-vendors to use their data in effective way, improve their decision making and empower their customers.Specially, firms apply BDA to track their customers' behavior, determine the customers' updated trend to gain new customers and keep repeat customers.From customers' view, applying BDA can offer many positive factors for customers.Positive factors of applying BDA concludes providing information search, recommendation system, dynamic pricing and customer services (Le & Liaw, 2017).
By using BDA, e-vendors can record and filter from large information to information which customers need.This application enables to provide the right products to right person at right time.The information search is achived by applying BDA which are quicky responeses (Delone & McLean, 2003), suitable, realistic and real-time services.Recommendation system is the most important application of applying BDA to design the website.It is now offererd in Amazon, eBay, Taobao and other many famous websites.By using different algorithms in BDA as collabrorative filtering (Huang, Zeng, & Chen, 2007) to evaluate the products, customers' interest and recommend for customers alternate or complementary products.Recommendation system also refer the best-selling products or the hottest commodity information to recommend and push these information to customers.This recommendation action could enhance customers' interest on website, provide consumers more choice and satisfy customers' need.The purpose of dynamic pricing is to provide different prices for different customer, location, product ad time (Kotler & Armstrong, 2000).Based on Big Data of customers' information like as demographics, geographic distribution, customers behavior, firms enable to adjust price of product and offer for individual customers.Therefore, the dynamic pricing has been made more flexibility strategy to satisfy online customers (Haws & Bearden, 2006).Besides, the above applications, using BDA also enhance business process by offering the track customers' order, virtual product experiences, buyer community to review customer's feedback.These services can inspire customers with positive behavior with e-vendors' website.All these applications of BDA will help to catch customers' attention, gain customers' interest, enhance desire and lead them to take action to purchase.Therefore, the hypothesis is as following: Hypothesis (H 1 ): The positive factor has positive relation with customers' responses.

The Mediating Role of Functional Value and Emotional Value
Perceived value has been become the most important concept of marketing practice in recent years (Aulia, Sukati, & Sulaiman, 2016) and succesful key for all companies (Huber, Herrmann, & Morgan, 2001).Perceived value's dimensions and their effects to customers' responses were stated in previous studies (Aulia et al., 2016;Carlos Fandos Roig, Sanchez Garcia, Angel Moliner Tena, & Llorens Monzonis, 2006;Sanchez, Callarisa, Rodriguez, & Moliner, 2006).Perceived value should not only viewed from ultitarian value which based on products' performance or functions, but also it should be based on the feelings of customers after experiencing (Holbrook & Hirschman, 1982).Therefore, functional and emotional value are the most two important dimensions of perceived value.Perceived value was found to be a powerful predictor of purchase intention (Zeithaml, 1988)

Sample Selection
Data comes from survey after respondent interacted with Amazon website (www.amazon.com)which a famous website using application of Big Data analytics.The respondents need to take an action through until the ending the process of purchasing one kind of products on the website, but not actually purchase to that item.Students were invited to participate in this study because college students have many experiences in using the Internet.The using college students as sample have been stated in many previous studies (Gefen, 2002;Kuo, Wu, & Deng, 2009).In addition, students nowadays are the key convenient shopper and become potential customers of e-commerce market.
A sample size of 372 students from Thai Nguyen University, Vietnam participated in this study during in 2016 and 2017.About 23 questionnaires were not fully completed and were removed before analysis.The rest of 349 samples were used for analysis.The majority (62.2%) of respondents are female.The customers had interaction with one of two kinds of products are similar percentage: fashion item (50.4%), electronics item (49.6%).The largest (31.2%) of respondents have experiences each month 1-2 times on website and 18.9 % respondents have no experiences with online shopping.

Measurement
Measurement variables were shown in table 1 which is considered for each construct used in this research.The measurement variables were used in this research according to related literature.A total 4 constructs were used.First, positive factors of applying Big Data analytics was measured on four variables and adopted from previous study (Le & Liaw, 2017;Tang & Wu, 2015).Second, two validated items were to measured functional value taken from the studies (Carlos Fandos Roig et al., 2006;Sanchez et al., 2006).Third, emotional value was measured on two items based on previous studies (Carlos Fandos Roig et al., 2006;Sanchez et al., 2006).Fourth, customers' response was measure by AIDA model in four variables based on (Ehrenberg, 2000;Lee et al., 2013).The questionnaire includes two sections.The main section measures the respondents' perception of each construct in research model under using a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).In another section, several demographic characteristics were assessed: gender, experiences and which product was chosen to interact with website.The research construction and items included in the questionnaire are presented in Table 1.ators, take e and omers'

Conclusions
Under the urgency of applying BDA in e-commerce, the purposes of this study are to evaluate the mediating role of two dimensions of perceived values on the relationship between positive factor of applying BDA and customers' responses.The first result found that the applying Big Data analytics brings the positive influences on customers' responses.Applications of applying DBA are such as information search, recommendation system, dynamic pricing and customer services.A recent study by Columbus (2014) stated about business value that injecting BDA may contribute 10% and more of the growth for 56% firms.For customers' value, applying BDA enables customers gain more confidence, feeling pleasure and having high satisfaction.Big Data analytics is new method for e-commerce firms to understand more about their customers.Therefore, e-vendors should adapt this new method to attract more customers' intention toward the positive applications of BDA.
Two dimensions of perceived value act the mediating role on the relationship between positive factor of applying BDA and customers' responses.This mediating effect is divided into a functional value (referring to economic valuations) effect and emotional value (relating feelings or internal emotions) effect.In the view of the results obtained, it is highlight that the customer perceived value is important key factor that is mediator to gain more positive customers' responses.There are no significant different mediating effect between functional value and emotional value.This finding highlights the notification that under BDA era in e-commerce, customers concern both important dimensions of perceived value.It can be explained that customers nowadays not only find their products or services but also seek enjoyment when online shopping.Therefore, it raises a question for e-vendors that how to use positive application of BDA effectively to gain more functional value and emotional value at the same time.
Big Data analytics has become the trend for intelligent marketing analytics for e-commerce landscape.Although the benefits of BDA are real and significant to business value and customer value, there remain some hidden potential challenges for e-vendors and customers also.The biggest challenges of Big Data are not provide clear direction to reach business target (Akter & Wamba, 2016), find the right customers' information from massive data (Agarwal & Dhar, 2014).BDA is process which works with Big Data, techniques, skills and systems to create competitive advances.Leading famous e-commerce firms have already injected and gained growth from BDA such as Google, Amazon, eBay, Taobao and others (Le & Liaw, 2017).

Future Research
Future research of this study is mainly shown in two points.The first point is about the choice of sample, this study focused on potential customers as college students.They cannot represent the view of all online consumers such different occupational, age, experiences, so future research may include samples from diverse demographic population.The second point is beside positive factor of applying BDA to customers, it also bring negative factor and other risks.Therefore, the future research should deeply study about these factors to customers' responses.