ISSN 0798 1015

Vol. 40 (Number 13) Year 2019. Page 6

A model for determining the impact of channel factors on shoppers’ satisfaction

Un modelo para determinar el impacto de marketing multicanal en la satisfacción de compradores

AGARWAL Himanshi 1 & DIXIT Shailja 2

Received: 14/09/2018 • Approved: 30/03/2019 • Published 22/04/2019

Contents

1. Introduction

2. Literature review

3. Rationale

4. Research objectives

5. Data & methods

6. Analysis and results

7. Discussion

8. Implications

9. Conclusion

References

1. Introduction

Today, in the era of multi-channel marketing trend, shoppers find themselves in a real tough spot where they have a great deal of choices to think upon (Gajjar,2013) relating to all the 8 Ps of marketing- Product, Price, Place, Promotion, physical evidence, pace, people and process. Limiting the scope of study only to one product category- Apparels and confining the discussion only for the third P, that is ‘Place’, shoppers now have access not only to a number of store options but also to a variety of purchase channel choices, mainly, online and offline, or to be more specific, retailing and e-tailing channels.

The Apparel industry is the second largest and one of the fastest growing industry segments in India. The Indian apparel retail market has been estimated over USD 70bn in 2016 which is expected to reach USD 100bn by 2020, as per the Technopak report. Apparels, now-a-days, have become the fastest growing online sold item and there are a large number of e-tailing portals offering all kinds of apparels which has increased the competition among the online and offline retailers. A research by BCG and Facebook estimates that 5% of the apparel sales are being driven by digital channels which are expected to reach over USD 14bn by 2020.

Thus, as a consumer, the problem ‘where to buy’ becomes very complex when there are a number of channels to be considered along with a range of product and store options for the purchase of a particular product (Black et al., 2002)since there arises a need to think upon the channel factor too, along with the product and retailer factors.

Therefore, a primary survey was carried out to find which factors have the highest impact on the consumers’ decision regarding purchase channel for buying apparels. Since, there are a number of studies highlighting the factors affecting consumers’ purchase channel selection, hence, the questionnaire was formulated by choosing few relevant factors from the available literature and the degree of relevance of these factors with the consumer intention has been calculated in this empirical research paper.

2. Literature review

The ‘problem of choice’ is influenced by (i) product factors, (ii) retailer factors, (iii)channel factors, and obviously (iv) consumer factors (Black et al.,2002, Gerth and Yan, 2004, Nicholson et al., 2002). Consumers are expected to evaluate the channels before buying a product on the basis of their costs and benefits. Therefore, it could be argued that one could merely focus on the channel factors to choose the best channel with highest utility among the available options (Verhoef, Neslin and Vroomen, 2005). However the utility derived from a channel is influenced by the other three factors too, that is, product, retailer and consumer factors.

Channel factors are a part of decision making and they should be seen in the light of other factors. It is assumed that consumers’ decision to buy online or offline is generally based on what is delivered and how is it delivered (Heinonen,2004). Thus retailer factors like service quality, price and merchandise play a role in shaping influence what is delivered and channel factors influence how the product is delivered (Broekhuizen, 2006). However, consumer factors like age, gender, education and income level are likely to influence the channel use. Product factors also play a prominent role in shaping consumers’ intention. The products that consumers feel they need to touch and try are likely to be purchased offline (Chiang and Dholakia, 2003) whereas online channels are suitable for standardized products and repeat purchases.

Although, the process of decision making is very similar whether the consumer is purchasing online or offline (Katawetawaraks and Wang, 2003) but both the channels possess entirely distinct characteristics.

Product factors have a strong impact upon the consumers’ decision for channel selection (Black et al., 2002, Gerth and Yan, 2004, Nicholson et al., 2002, Keen et al., 2004). In other words, it can be said that there is strong product-channel interaction Black et al., 2002, Schoenbachler and Gordon, 2002, Inman et al., 2004). In this regard the classification of goods is often used (Gerth and Yan, 2004, Girard et al., 2017).

Table 1
Product category

Source: Author

Normally, Internet is suitable for selling standardized products and repeat purchases that basically have search aspects (Nicholson et al., 2002) opposite to this, products that possess high experiential aspects are sold offline (Alba et al.,1997). Moreover, expensive, risky, complex and high involvement products are usually purchased through offline channels as they often demand personal interaction (Black et al., 2002, Nicholson et al., 2002).

In this study, to limit the influence of product factors, we are considering just one factor, that is, apparels which are a high involvement experiential good having wide range of variety to choose from, thus the information available about the product is also limited and one needs to personally encounter the product to make purchase (Kevin, Eric and Bianca, 2003). Therefore, for these products consumers have the real opportunity to choose from online and offline channels. However textile and clothing have found the biggest acceptance in online retail and no other branch of the industry is as affected by internet as the apparel retail sales have (Heinemann and Schwarzl, 2010).

Retailer factors too greatly influence the consumer’s choice of channels. The more positive the consumers’ perception    are towards an offline/online retailers’ offerings and capabilities are, the more are the chances of that particular channel being selected for a certain purchase. Reliability, convenience, price competitiveness, informativeness & merchandise are the main influencers of retailer factor (Black et al., 2002, Gerth and Yan, 2004, Swamninathan et al.,1999).

Consumer factors like socio-demographic profile, lifestyle, and personality traits, shopping orientation and previous shopping experience, clearly impact the consumers’ decision about purchase channel (Inman et al., 2009, Dabholkar and Baggozi, 2002). For the success of any company it is very important to identify this element of decision making and study the changes occurring over the time to prepare adequate responses, in the form of product and services (Faria et al., 2013, Rousseau, 2007).

The aim of the current study is to identify those factors which have highest impact upon the consumers’ choice of purchase channel and the extent to which these factors (not) motivate an Indian consumer to choose a particular channel for buying a certain product. Few important factors that have been selected from the extensive literature survey are listed below. The reason behind selecting only these factors for further analysis is that previous researchers have repeatedly focused upon their relevance and they have been found in common in many consumer behavior studies. These factors have been taken as constructs for further analysis in the paper.

2.1. Shopping Convenience (SC)

Many authors (Chiang and Dholakia, 2003) believe that one of the key reasons behind the purchase channel selection is convenience which adds value by saving time and effort for the shopping activity (Lloyd et al., 2014). Shopping online offers not only convenience (Chiang and Dholakia, 2003) but some consumers favor online shopping due to price comparisons facility also (HuMonsuwe et al., 2004).

Ho1. Shopping Convenience has no significant effect on shopping satisfaction.

2.2. Shopping Ambiance (SA)

Few authors consider the retail shopping experience, a shopping motive in itself (Dawson et al., 1990, Bellenger and Korgaonkar, 1980, Benapudi and Berry, 1997). The recreational shopper enjoys shopping as a leisure-based activity, spends more time per shopping trip, considers store’s interior an important patronage decision, and tends to make unplanned purchases (Bellenger and Korgaonkar, 1980). Online retailers, on the other hand, find it difficult to replicate the sensory effects and product-trial experiences available to the consumer in a physical store setting and find it more challenging to attract recreational shoppers who may be less predisposed to shopping online (Rohm and Swaminathan, 2004).

Ho2. Shopping Ambiance has no significant effect on shopping satisfaction.

2.3. Shopping Risk (SR)

According to marketing literature, trust is positively and directly related to a consumer’s experience with the seller (Koufaris and Sosa, 2004). Online trust is obviously different from offline trust owing to the physical distance between consumer and retailer and the separation between buyers and products (Yoon, 2002). In internet shopping, there are risks involved in privacy, security, visual appearance of the product, delivery terms, payment conditions and product information (Parasuraman and Zinkhan, 2002, Burke, 2002).   Many studies, among them (Chang and Chen, 2008, Chen and Barnes, 2007, Dash and Sazi, 2007, Ganguly, 2012, Kim and Forsythe, 2010, Koufaris and Sosa, 2004, Ling, 2010, Yoon, 2002), found a significant positive relationship between trust and online purchase intention contrary to which, the risk of security and privacy issues adversely affect shopping satisfaction.

Ho3. Shopping Risk has no significant effect on shopping satisfaction.

2.4. Pricing Model (PM)

Price is the monetary cost that people pay for conducting any transaction. The presence of promotional offers increases the consumers intention to purchase in web-shopping (Wang and Sculli, 2005). It is foreseen that the price of a product differs in online and offline shopping channels. Dynamic pricing means the pricing strategy in which prices change over time, across consumers, or across product bundles can easily be executed in web shopping contrary to the conventional retail channels where price changes over the course of weeks or months (Katawetawaraks and Wang, 2003).

Ho4. Pricing Model has no significant effect on shopping satisfaction.  

2.5. Shopping Value Perception (VP)

Nowadays, shoppers are more leisure driven (Nicholls et al., 2002) for whom, shopping for apparels is an activity for fun, enjoyment, relaxation, pleasure and leisure. Consumers regard offline shopping more enjoyable than online shopping (Dennis and Harris, 2002). Few authors emphasized the need to increase the level of positive emotions in the shopping mall by creating an exciting and happy experience (Hunter, 2006). While in online shopping, consumers are expected to relate enjoyment with the experience perceived in the purchasing process and the excitement level arises during the time of product delivery (Broekhuizen, 2006).

Ho5. Shopping Value Perception has no significant effect on shopping satisfaction.

2.6. Tangibility (TB)

Regardless of shopping mode, tangibility is considered to be a factor that consumers definitely emphasize during the purchasing process. Products accessing ‘Tangibility’ factor like shoes and clothes, are needed to be felt and touched for making purchase decisions (Rajamma et al. ,2007). Consumers are very particular about the tangibility of a product because they need the security and assurance that the product purchased is in a good condition and assurance of purchasing the right thing. With the inability of consumers to feel and touch the product in an online context, it becomes difficult to market those products on the internet.

Ho6. Tangibility has no significant effect on shopping satisfaction.

2.7. Shopping Satisfaction (SS)

Satisfaction is defined as the perception of pleasure in the execution of consumers’ purchase experiences (Oliver, 1997). The customer satisfaction increases with an increase in the level of personal interactivity provided by an online portal and also with the number of product attributes mentioned (Ballantyne, 2006). Online shoppers' satisfaction and purchase intention is influenced by both objective and subjective interactivity (Zhao and Dholakia, 2009). Objective interactivity refers to the types of communication mediums available in an individual website while subjective interactivity relates to perceived interactivity.

3. Rationale

The paper attempts to fill a gap in the studies done in India regarding factors affecting purchase channel selection for apparels. Since apparels, is the second largest industry in India and the fastest growing online sold product, so this needs adequate attention to spot the factors which need considerable attention while formulating a suitable marketing strategy regarding channel selection to as to impart maximum shopping satisfaction to the customers. There are a number of researches focusing the factors affecting shoppers’ satisfaction but these studies have not particularly highlighted the extent to which any of those factors affect purchase channel selection for apparels.

4. Research objectives

Based on the relevant literature of the factors affecting shoppers’ satisfaction while selective a purchase channel for buying apparels, the research objectives are:

1. To highlight few important factors with affect consumers’ purchase channel selection for apparels from the available literature.

2. To calculate the extent to which these factors affect consumers’ choice of purchase channel for buying apparels.

3. To devise a model for factors influencing channel selection attractiveness for shoppers’ satisfaction.

5. Data & methods

In order to identify the items affecting purchase channel selection for Apparel Segment exhaustive literature survey was done. Focus group discussion and expert opinion were also taken from customers, stakeholders and academic experts. On the basis of literature survey and pre testing of the questionnaire, total 7 constructs/ factors were finally chosen which comprises a total of 38 items for the study. These items were made items / statements in the questionnaire. The respondents, who were the buyers of apparels, were asked their degree of acceptance on a 5 point Likert scale ranging from 1 to 5, 1 being strongly disagree and 5 strongly agree. The questionnaire was personally given to 600 respondents (selected on the basis of random sampling), of which 577 were received and have been processed. Table 5.1 enlists all the seven constructs/factors and 38 items that were made statements in the questionnaire and were used for analysis.

Table 5.1
Identification of constructs/ items
in the development of questionnaire

In terms of demographic findings, 53.9% of the shoppers were male and remaining 46.1% were female. An interesting fact, which has been repeatedly spotted by various studies, was seen here also, 77.8% shoppers are of age below 25, 15.4% fall into the age group 26-35 and remaining 6.7% are above 35 years of age. In terms of occupation or designation, majority of the buyers were students (80.4%), followed by the employees (11.6%), business personnel and others. A view of the customers’ familiarity with the online channels found that 89.6 % apparel buyers are familiar with the online portals and rest with not much tech savvy. Moreover, 77.3% respondents have at least once purchased the apparels online but rest has not. The summarized view of the demographic profile of the respondents is given in table 5.2.

Table 5.2
Summarised view of the demographic profile of the respondents

6. Analysis and results

Cronbach’s alpha was calculated to measure the internal consistency and reliability of the instrument. Initially we have checked internal consistency and reliability of all seven constructs/ factors by using SPSS-20 version. On putting the values, the value of Cronbach’s alpha for each construct came greater than 0.60 as shown in Table 6.1, thus the instrument was considered reliable for the study.

Table 6.1
Cronbach’s Alpha (Reliability Statistics)

6.1. Regression Analysis

Linear Regression estimates the coefficients of the linear equation, involving one or more independent variables that best predict the value of the dependent variable. Therefore our liner regression equation explains as unit change in any independent variable, what would be resultant change in dependent variable.

Table: 6.2
Beta Coefficient and Significance for Model

The b-values in the table 6.2 represent the relationship between shopping satisfaction and each predictor (i.e. identified constructs). If the value is positive we can tell that there is a positive relationship between the predictor and the outcome whereas negative coefficient represents a negative relationship. The b-value also tells us to what degree each independent variable affects the dependent variables if the effects of all other independent variables are held constant (Field, 2005).

The outcomes empirically verified the influence of the considered six factors on the shoppers’ satisfaction for purchase channel selection while buying apparels in India.

Shopping convenience has a positive and significant effect on the shopping satisfaction

The result of the multiple regression analysis supports the view of previous studies that a positive relationship exists between shopping convenience and shopping satisfaction. The b-value for shopping convenience derived above is 0.363 which means that more the convenience offered by a particular channel, more is the satisfaction derived by the shopper and more are the chances of choosing that particular channel for buying apparels.

Shopping ambiance has a positive and significant effect on the shopping satisfaction

Shopping ambiance is also considered as an important factor which selecting a particular channel for purchasing apparels. In offline context, ambiance refers to the interior and comfort offered by the store while in online context, ambiance means the website design and user friendliness. The value of shopping ambiance derived above is 0.565 which means more attractive the ambiance is, more is the shopping satisfaction.

Shopping risk has a negative and significant effect on the shopping satisfaction

Existing literature supports the view that trust positively affects channel selection while security and privacy threats adversely affect the channel image. The results of this study too, support this opinion. The b-value for shopping risk derived here is -0.452 which means that as the shopping risk increases the shopping satisfaction decreases and thus the chances of selecting a particular purchase channel also decreases.

Pricing Model has a negative and significant effect on the shopping satisfaction

The result of the multiple regression favors the law of demand theory as well as the opinion of previous researches that price is negatively related to demand. Here, the value of pricing model variable is -0.112 which means that if price of a product on a purchase channel increases, the intention to purchase from that particular channel decreases and vice versa. Alternatively, the availability of offers, deals and discounts increases the shoppers’ satisfaction.

Value Perception has a positive  effect on the shopping satisfaction

Many researchers have found a positive relationship between the leisure and entertainment delivered by a particular channel and the shopping satisfaction. The result of this empirical analysis too,  the b-value of value perception variable, which is, 0.039 supports that more the value perceived by the buyer from a particular channel more is the shopping satisfaction perceived by him/her. Though the impact is not very much significant yet, to some extent, it affects the shopping satisfaction.

Tangibility has a positive and significant effect on the shopping satisfaction

For the product like apparel, touch and feel factor holds great importance for a buyer. Here, the b-value of 0.084 also agrees with this that more the tangibility factor offered  by a particular channel, more are the customers accepting that particular channel since more will be the shopping satisfaction derived by it. Undoubtedly, offline channel is capable of providing greater touch and feel factor as compared to online channel.

In short, the beta value tells us the number of standard deviations that the outcome will change as a result of one standard deviation change in the predictor (Field, 2005). Higher beta value signifies stronger correlation with the dependent variable. In table 5 Shopping Ambiance (SA) have the highest beta (0.565), followed by shopping risk (-0.452), Shopping Convenience (0.363), Pricing models (-0.112), tangibility (0.084) and Shopping Value Perception (0.039), which means that shopping ambiance has the highest influence over the consumers’ choice of purchase channel selection for buying apparels followed by other variables.

Figure 6.1
Model for Determining the Impact of Channel Factors on Shoppers’ Satisfaction for Apparels

Source: Research Scholar’s own proposed model

7. Discussion

Table: 7.1
Model Summary of Regression

The summary table 7.1 provides the value of r, r2 and adjusted r2 for the model that has been derived.  “r” represents the value of the multiple correlation coefficients between the predictors and the outcome (Field, 2005). Here, r has a value 0.856; this value represents the simple correlation among Shopping Convenience (SC), Shopping Ambiance(SA), Shopping Risk (SR), Shopping Satisfaction (SS), Pricing Model (PM), Shopping Value Perception (VP), and Tangibility (TB). This means that a unit changes in any of these variables will bring around 85.6% changes in the overall shopping satisfaction perceived by the buyer.

The “r2” is a measure of how much of the variability in the outcome is accounted for by the predictors (Field, 2005). The value of r2 is 0.733 which tells us that these six shopping satisfaction variables can account for 73.3% of the variation in the shopping satisfaction that leads to E-tailing and retailing industry. This means that 26.7% of the variation shopping satisfaction cannot be explained by these six satisfaction variables. So, there must be other variables too that have an influence over the consumers’ choice for E-tailing and retailing industry.

The adjusted “r2” gives an idea of how well the model generalizes and ideally its value is likely to be the same or very close to, the value of r2 (Field, 2005). Here, the difference between r2 and adjusted r2 is 0.3% (0.733 – 0.730= 0.003). This means that if the model were derived from the population rather than a sample it would have accounted for approximately 0.3% less variance in its outcome.

Thus, for a marketer, it is of utmost importance to take the above mentioned six factors into consideration for the formulation of a suitable marketing strategy since only these six factors itself account for 73% variability in the shopping satisfaction for purchase of apparels which is gaining increased attention both on online as well as offline marketing platforms. A strong and suitable marketing mix policy can be devised by focusing on these factors along with a considerable attention on other factors too.

8. Implications

The hypothetical foundation of this research is based on literature about factors affecting purchase channel selection for buying apparels so as to impart maximum shopping satisfaction to the customers. It is obvious that the growth rate of ecommerce in India and the growing number of etailing websites has increased the competition for the offline retailers. Moreover, the competition becomes all the more intense when it comes to apparels which is one of the most sold online product category. Thus, there arises a need for the retailers to understand the wants and expectations of their customers to enhance their shopping satisfaction and maximize firms’ profits.

The empirical conclusion drawn from this research helps marketers to target their customers by giving considerable attention towards the factors which affect channel selection while formulating the marketing strategy for selling apparels. This helps them to retain their existing customers as well as attract new customers also.

9. Conclusion

This research is an original contribution to the existing stock of knowledge which has investigated the factors affecting channel selection on the basis of the importance and relevance that a factor holds towards shopping satisfaction. Few factors relating to channel selection, that are, shopping convenience, shopping ambiance, shopping risk, pricing model, value perception and tangibility were the spotlights of this research since they have a direct influence in the satisfaction perceived by the shoppers.

This study can be proved extremely helpful to the market researchers of fashion industry, who struggle with the number of variable factors affecting consumer behavior, while devising a marketing channel strategy for the sale promotion of the apparels. They can be quite sure that their marketing strategy would provide approximately 73% consumer satisfaction if formulated properly by focusing on these six factors only. Therefore, giving a reasonable attention towards other factors too, marketers can save their time and effort by giving major attention towards the above discussed factors while making an action plan for marketing their apparels through online or offline channels. 

Undoubtedly, this study is equally important for academician too. Since, it has paved a way for further exploration of new variables which affect the consumers’ intention to (not) purchase apparels from a particular channel. The similar kind of research can be extended to other products too. Moreover, the inter-relationship between the above used constructs as well as the impact of socio demographic profile can also be analyzed keeps this as a base study.

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1. Research scholar. Amity Business School. Amity University Uttar Pradesh. Lucknow, India. Email: neha.5890@gmail.com

2. Dr. Shailja Dixit Associate Professor Amity Business School Amity University Uttar Pradesh Lucknow . Email: shailjadixit1@gmail.com