Editorial Board

A Refereed Monthly International Journal of Management

OMNI-CHANNEL E-TAILING: DYNAMICS OF CONSUMER PURCHASE DECISION BEHAVIOUR

Author

Mugeshkannan Reguraman Research Scholar Department of Commerce Alagappa University Karaikudi, Tamilnadu, India E-mail:- mugesh.kannan1910@gmail.com

Ganapathy Subbiah Professor Department of Commerce Alagappa University Karaikudi, Tamilnadu, India

Abstract

Consider the dynamics of Omni-channel e-tailing in Chennai, in particular, present and contrast the purchase decision behaviour being pursued by the IT professionals. The purpose of this study is to understand the consumers’ purchase decision behaviour on Omni-channel e-tailing. Questionnaire method and non-probability Convenience sampling were used to collect data from 700 IT professionals and structural equation modelling was used to test the hypothesis. The results provided evidence that offers and operation quality, convenience, product quality and service quality significantly affect consumers’ purchase intention on Omni-channel e-tailing. The availability of 4G network and due to penetration of Smartphone, the form of new mobile technology is in great demand. This paper provides an exclusive view point concerning the consumers’ purchase decision behaviour on Omni-channel e-tailing.

Keywords: Omni-channel e-tailing, Purchase behaviour, Smartphone, Internet of Things, Social Media

Introduction

“Omni-channel e-tailing is a fully integrated approach to e-commerce that provides online shopper a unified seamless experience across online channels (i.e. Smartphone, Computer, e-store, Social Media, E-wallet, e-shipment etc.,)”

The global retail sector now widely recognized due to the penetration of Smartphone and internet, scope and interactivity provides an e-tailer with the potential to transform their customers’ seamless shopping experience, with a broad set of new technologies, influenced by Social Networking Sites and economic volatility etc., set to determine future (Mugeshkannan, 2018). The introduction of new e-tail channels has increased competition and price pressures, the greatest challenge being the rise of e-tailing, which is gaining ground as a faster and more convenient way to shop. Determinant factors like changing demographics, changing lifestyle, new technologies, informed customers, economic trends and the advent of Smartphone makes it imperative for e-tailers to use more effective channels to do business, than in the past.

At the “Internet of Things” era, every retailer is expected to have an online web store. In the early days, it was predicted that the e-commerce would soon dominate the whole online retail market due to the convenience of making a purchase within some clicks at Anywhere, Anytime and Anything. Omni-channel retailing is a fully-integrated approach to commerce that provides shoppers a unified seamless shopping experience across online channels (e.g. Touch points). The recent Omni-channel shopping extends to Smartphone, e-commerce marketplaces, e-store, Social Networking Sites, retargeting, and everything from brick-and-mortar locations. Omni-channel e-tail is a business model in which all existing channels become completely integrated to offer customers a seamless shopping experience, so the E-tailers have to take a strategic approach not only to understand the roles that stores and store networks can play best in today’s retail ecosystem, but also to keep stores at the center of the customer relationship, while maximizing value across channels. The retailers need to ensure that their business models and technology platforms are able to drive a consistent and constantly improving customer experience across multiple channels (i.e. Internet, mobile, retail outlets), while generating maximum business value from the wealth of data on purchasing behavior that these channel create. The stores need to be more flexible in terms of product ranges and pricing so as to cope with the changing customer needs. The present study, elaborating the Omni-channel e-tailing in Chennai, consist of purchase decision behavior with a similar approach, an attempt will made to determine the dynamics of the Omni-channel e-tailing in Chennai.

Purpose of the Study

Omni-channel e-tailing is about ensuring that organizations provide a seamless experience to customers across all channels through more interactive channels for engagement that enables a customer to design their own living room. An Omni-channel strategy helps to improve marketing effectiveness by enabling shop at 360 degree view and shelf activity. The Omni-channel paradigm develops system complexity by increasing through number of customer choices: more number of stock keeping units and wide product diversity. However, Omni-channel also helps to dealing with individual customer’s preference and expectation. This study shows that brand trust is one of the most important reasons people shop at their favorite Omni-channel e-tailers. Also, consumers like personalization, and more people visiting brand social media websites that offer personalized promotions, and most of the customers use coupons received on Smartphones to purchase at home, during transit or e-store. Omni-channel e-tailers can offer customized experiences to consumers only if they have access to information about consumers, but such information is difficult to come by as people are concerned about divulging personal information. E- shipping to customers & on-time delivery is one of the most significant steps in ensuring a good end-to-end customer experience. The age-old paradigm of buying a product at the store and taking it home is still important, but it’s starting to make way for newer fulfilment methods. This study discusses Omni-channel as applied to four e-tail processes for enhancing customer experience through Personalization, Payment, focused promotion and improving customer service.

Statement of Problem

The hyper-connected consumers and retail mechanism require immense persistence in order to provide a seamless and an unmatchable shopping experience across all those platforms where a customer is or can expected to be. With evolution in the retail from traditional brick-and-mortar retailing to Omni-channel e-tailing, consumers today have become more demanding be it in terms or shopping ease, product quality or touch-points. This has led to multidisciplinary research to address different factors involved in the system of e-commerce so as to get keen observations on the customers’ behavior and attitude towards technological innovations like Multi-channel and Cross-channel. But this multidisciplinary approach itself is a complex process. The penetration of internet and Smartphone has revolutionized the whole retail sector, enabling the consumers to research and shop at their convenience, Anytime, Anywhere and Anything. As customers embrace new technologies the shopping experience has become increasingly sophisticated, enabling new ways for leading e-tailers to reach their audience.

Omni-channel e-tailing is one of the major aspects of the vibrant and dynamic e-commerce that has grown leaps and bounds in India. From the outlook, the customers’ attitude and satisfaction appear to be positive for Omni-channel e-tailing, but studies on the technology and the customer behavior try to better the pertinent technology and customer overall experience. This would lead to a positive network of systems, helping each other. Hence a clear understanding of consumers’ shopping and buying decision is important for Omni-channel e-tailers. There are number of studies on Omni-channel retailing in countries like USA, UK, Europe, Korea, Malaysia and Singapore. Nevertheless, there is a big gap between the Omni-channel shopping technology and customers’ attitude and satisfaction. This gap needs to be filled by studying them from the customers’ perspective to make things better in future. Therefore, the present research study aims to analyze the purchase decision behavior of customers for the products purchased over the Omni-channel e-tailing.

Figure 1: Conceptual Model

Methodology

The proposed research model for this paper is shown in figure 1. The study is both descriptive and analytical in nature. In order to explore the variables in the proposed research model a well structured questionnaire survey was conducted, a convenient sampling method has been used to select sample respondents from various IT companies in Chennai. Samples of 700 respondents are covered for the study. The sample respondents are the professionals who use Omni-channel shopping in Chennai.

Scope of the Study

The conventional methods of marketing and selling have now been replaced by the advent of modern technologies like mobile apps, e-store, e-catalogue, etc. Today if a consumer wants to purchase any item placed anywhere in the globe they need not go or ask them for a sample. Consumer can trace out the needy products and could visualize in the online channels. Omni-channel eases the consumer to shop anywhere in the world by logging on to their personal electronic devices (Smartphone, Tablets and personal computers) with comfort even from their home. Omni-channel has some special characteristics compared with the other medium. Provision of information and others related to a product through all online channels is abundant when compared with the function performed by the single channel and multiple channel retailing. In this socio economic scenario as people are weary of work, they could spare time with their family, maintain physical and mental health, maintenance of elders in their family and others similarly in shopping too; Hence this study makes an attempt to augment Omni-channel e-tailing at this backdrop for satisfying the Omni-channel consumers. Through the Omni-channel, consumers can identify the products, compare price, quality, gain knowledge of products from friends and strangers and view the products from different angles without touch. Omni-channel testimonials and reviews provided by the users of products and services are the factors intriguing the users or consumers. The most exciting aspect of Omni-channel e-tailing is that it is a 24x7 affair in all channels. Easy and leisure shopping experience could be had rather than sensitive or emotional shopping through Omni-channel. The other dimension is that consumer directly purchases the items from an original merchant in Omni-channel e-tailing, no mediator comes between consumer and merchant. So it becomes cheaper than in other ways to purchase the products. Omni-channel e-tailers could sell with less resource (i.e., Capital) and expenses. Some e-stores do not have a physical showroom. They just display the products on Social media and service online and deliver the goods to customers’ doorstep on time.

Table 1; Indicators of the Measurement model

Each customer purchase decision behavior factor consisted of four indicators. Measurement model specified four factors: (Offer & Operation quality, Convenience, Product quality and Service quality). The degrees of agreement on the statements for above factors are used as theme indicators (Table 1). Every indicator was constrained for load only on the factors. There is no equality constraints on the factors loading were imposed and the factor co-variance to be estimated.

Table 2: Customer Purchase Decision Behaviour (Standardized Factor Loadings)

In order to establish convergent validity of the construct standardized factor loadings have been reviewed. According to Hair et al. (2010), for establishing convergent validity, standardized loadings should be 0.50 or higher, Average Variance Extracted (AVE) should be 0.50 or greater and Composite Reliability (CR) should be 0.70 or more. All of which are found to be greater than 0.50, factor loadings ranged from 0.810 to 0.989 (Table 2). Thus, all AVEs for each dimension of purchase decision behavior exceed the variance attributable to measurement error (AVE>0.50 and CR>AVE). Thus, Convergent validity of four dimensional purchase decision behavior scales have been tested and established.

In order to evaluate the adequacy fit of the proposed model (figure 1) to data, a combination of fit indices was investigated. Fit indices are as follows: Standardized RMR < 0.10; Non-Normalized and Comparative Fit Index (CFI) > 0.9; Root Mean Sqare Error of Approximation (RMSEA) < 0.10; Chi-square: When the sample size is large, it is normal to have p<0.05 (Ganapathy & Mugeshkannan, 2016). Among those indices the measurement model fits the data very well: Chi-square (n=700) 125.68, p<0.001, Comparative Fit Index is 0.903, Standardized RMR is 0.023 and RMSEA is 0.045. In reliability test, Cronbach’s coefficient α-values of four factor all surpassed 0.9, indicating excellent internal consistency.

Figure 2: Standardized Factor Loadings for Measurement Model

The value represents (Table 3) the simple correlation ‘ R= 0.971’, which indicates a high degree of correlation. The ‘R² = 0.942’ indicates how much of the total variation in the dependent variable can be explained by the independent variables. In this case, 94.2% can be explained, which means that the multiple regression analysis explains high variance in the data. The F value indicates the regression equation fits the data (i.e., predicts the dependent variable). The regression model predicts the dependent variable significantly well ( p <0.05).

Table 4: Regression Co-efficient

Source: Compiled from Collected data

Regression fitted: Y = 86.684 + 7.613 X₁ + 4.843 X₂ +3.202 X₃ +3.176 X₄

The analysis of variance of multiple regression models for customers’ purchase decision indicates that the overall significance of the model well fitted. The co-efficient of determination R² value shows that these variables put together explain the variations of purchase decision to the extent 94.2 %. Since the p-value 0.000 is less than the 0.05, the null hypothesis has been rejected at α =0.05 level of significance, there exists enough evidence to conclude that the purchase decision behaviour regression line is not zero. Hence, that offers & operation quality, convenience, product quality and service quality are useful as predictors of purchase decision behaviour on Omni-channel e-tailing.

Conclusion

Social Media in Omni-channel retailing offers to customer build and maintain social activities, create relationship with strangers, sharing information and thoughts, participate in social moments through the internet (Mugeshkannan & Flarans, 2018). Despite the remarkable growth in Internet users, there is evidence to suggest that Omni-channel consumers are a kind of critical customer segment for Omni-channel e-tailers. Omni-channel e-tailers should invest in technologies that provide a seamless consumer experience across all available channels, to facilitate the shopping process and enhance customer engagement and loyalty to the brand. Omni-channel retailer must focus on the technology that is relevant for e-fulfillment service quality which often influences their buying behaviour. In this regard, the Internet of Things opens a world of possibilities for Omni-channel e-tailers by integrating technology to improve their efficiency and make them more useful. This research shows that Omni-channel shopping would exhilarate more in future than at the present. Perception towards Omni-channel e-tailing is getting somewhat better compared with online retailing in South India. With the use of Smartphone and internet, a consumer can shop with seamless experience, Anywhere, Anytime and Anything with easy and secured payment options.

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