Content area
Purpose
Owning to the influence small retailers have on the customer’s final choice, the purpose of this paper is to investigate the factors that dominate small retailer’s assortment planning decisions. Drivers of product adoption by small retailers are the focus of study. Earlier research works have primarily focused on the profit oriented factors of retailing. It is a multidimensional approach of understanding the decision making of small retailers.
Design/methodology/approachThe study is an exploratory in nature, using a mixed method approach that involves both qualitative and quantitative methodology. In the first stage of the study, grounded theory has been adopted that helps in building a conceptual model, which is further validated using SEM. Rural areas of Jammu and Punjab have been targeted to collect data.
FindingsThe study provides a conceptual model of product assortment planning for small retailers. The results indicate retail margin, which is the most important criterion toward product selection. Small retailers understand the customer profile and their catchment before selecting a product for their store. Store design is an important variable which impacts the number of categories kept in the store as the shelf space is limited. While determining the assortment planning for the store the retailers need to think in advance about buyer, supplier, environmental and the surplus oriented factors while determining the assortment planning for the store.
Research limitations/implicationsIn developing economies like India, major population (customers) lie in the rural areas of the country and prefer small retailers to shop their daily necessities. The study proposed that the manufacturers need to maintain good and healthy relationship with the associates of the channel and the retailers that are in connected with the end consumer. Marketing managers of firms with target audience as small retailers can draw many inferences from the present study. They may devise rural strategies keeping attributes like localization of supplier, doorstep delivery, supply frequency, etc., on the basis of product demand and attribute.
Originality/valueThis paper fulfills an identified need to explore the assortment planning criteria of BOP retailers in India. Also the mixed methodology is attractive and new in the retail domain.
Introduction
Unorganized retailers are the pinnacle of Indian retail sector. Prior research being conducted in rural context refers unorganized segment of retailers as “Small Retailers,” based on certain factors like the geography of the catchment, size of the catchment or the magnitude of their revenues (D’Andrea et al., 2006; Siddique and Siddique, 2012). Small retailers are stated as working with these four attributes, limited store operations, only-person handling the stores, undercapitalized and essential business goals are on survival (Davis et al., 1985). In a research conducted by Viswanathan et al. (2010), he talks about small retailers in a rural setup and refers them as subsistence retailers. The current research also studies the small retailers and defines them as retailers managing their retail stores individually, spread in a small area (<500 sq. feet) and carrying less product categories (Siddique and Siddique, 2012). Indian rural markets are a very well explored area of research; however, studies considering the retailer perspectives are limited.
According to Das Munshi (2005), small retailers behave differently in urban and rural environments,like the average stock keeping units in a small retail store in rural area is far lower as compared to an urban store. The number of product categories which were stocked by rural store was 19 whereas an urban store stocked 27 product categories (Das Munshi, 2005). This clearly demonstrates the need for different operations for small retailers in different geographies. According to Alur and Schoormans (2013), small retailers are Omni present and behave almost the same in rural and urban. With a vast presence in the retail environment, these retailers play a vital role in the product penetration. When companies launch a new product or want to enhance the catchment of the existing product, these small retailers act as a gateway to the final consumers. Seemingly, continuous support from the channel partners especially the retailer is very essential for the success of any product. A need to explore and study rural retailers in India has been expressed by the food and agricultural organization of the United Nations (Fao.org, 2015). Researchers have studied small retailers in various contexts and explored how these retailers influence consumer decisions. Retailer recommendations have a strong bearing on the final purchase decisions made by the customers (Dey et al., 2012; Sulekha, 2013). Multiple roles like advisor, creditor, friend and reviewer are played by the rural retailers (Preeti, 2011). Since the relationship of small retailers in very strong with its customers, they understand the needs, buying habits and seasonal income patterns, which is reflected in the decisions taken by retailers toward its store. Indian rural retailers have been found to impact around 35 percent of purchases of the customers (Kesari and Srivastava, 2012; Khaled, 2010).
India because of its vast consumer base has been a lucrative business opportunity, but of course with multiple challenges. With its diverse catchment network, last mile delivery for FMCG companies like HUL and P&G is a challenge. Reaching to the grassroots retailers is not an easy task and thus are approached through a third party or a middle man (local distributors and wholesalers) to tackle the demand in rural segments (Reinartz et al., 2011). Indian subsidiaries have been trying hard to strengthen their distribution chain to reach the millions of small retailers present in rural and urban India. To do so, multiple challenges like infrastructure, presence of regional players and changing customer demands come as a barrier. With technological advances, customer tastes and preferences are changing drastically, thus possessing a challenge for these small retailers to select from the large varieties of products (National and Regional) being offered in the market and then stock them accordingly (Kaufman et al., 2006). This is one of the most difficult task of the small retailers, to decide which products to keep and which not to, keeping the limited shelf space in mind. A qualitative study by Sinha et al. (2017), explores the brand adoption patterns by BOP retailers. They have developed a framework to understand this phenomenon through qualitative research. According to Gooderham et al. (2016), companies need to focus more on BOP markets and rework on their strategies and business models to create a satisfied market base. The current study creates a base for the companies targeting these small retailers, by understanding the product adoption phenomenon of rural retailers. Understanding the customers is not just enough, understanding the retailer decision making psyche is even more important. Prior researchers have tried to understand the retailer’s product adoption process; however the research is limited to organized retailing. The same might not be applicable to the small retailers due to difference in the operating styles (Ramkrishnan, 2010).
The earlier studies on rural consumers emphasize that these customers are unique in their own styles. These customers are price sensitive, brand loyal and do not switch very often. Thus, it induces many challenges for the small retailers like to maintain the preferred product in preferred quantities at the stores to avoid stock out situations, diverse merchandise in terms of price, keep customer preferred assortment etc. In a study by Sinha et al. (2017), it is seen that the value of adding these specific markets, particularly in the rural areas of India, is sky high. In the number of cases, there is a withdrawal of new products introductions by the manufacturers. The last mile stops for the suppliers as well as the customers are these village level retail stores. Hence, the role of a retailer in deciding which products to keep and which to delete is utmost. The current study is an attempt to understand how small retailers operating the rural markets undergo the product adoption process across multiple categories.
Literature review
Indian retail is dominated by unorganized retail which includes the small sized stores (Ramkrishnan, 2010). According to Kalhan (2007), unorganized retailing in India majorly contains small self-owned stores which are managed by the family members. The retail stores offer a small assortment but at very economic prices and at customer convenience (Halepete et al., 2008; Ramkrishnan, 2010; Sathish and Raju, 2010). The increasing organized market in the Indian retail scenario is posing threat to the survival of small retailers. So, the traditional retail store owners need to improve their retail services by understanding customer’s needs and expectations. The continuous improvement in the brand awareness among the customers is also posing a threat for small retailers for improvement in their assortments. Recent times have seen a change in the demographic profiles and in the income groups of the consumers (Sinha and Kar, 2007).
For every retailer the first showcase is the products they are carrying and is same is referred as the assortment carried by a retailer. When we talk about small retailers, this decision is even more strategic because of limited scape, cost involved and the price sensitive audience. Assortment planning is done by the retailers to maximize their sales or gross margin irrespective of various constraints like limited budget, limited shelf space and limited resources (Kök et al., 2009). The decision of assortment planning has several aspects. To broadly categorize them, these aspects can be how many different categories does the retailer have (called a retailer’s breadth), how many SKUs do they have in each category (called retailer’s depth) and how much stock they have of each SKU. There should be tradeoff between the breadth and the depth offered by the retailer. Retailers have to decide the categories to carry and the amount of space to allocate for each category. According to Jaiswal and Gupta (2015), when private brands try to sell their products which are luxury to the rural masses like, shampoos, deodorants, sunscreen lotions, etc., they unnecessarily occupy shelf space and thus waste the space resource. Retailer end up buying these discretionary products instead of buying products that satisfies the basic needs of the customer. Thus, a retailer needs to strategies their assortment prior in hand. Within each category, the retailer needs to decide the products to carry along with the inventory levels for each product. With restricted shelf area, rising variations means limited store space, which leads to more operational expense due to either lesser availability or higher refill amount. The study of literature proposes limited information on the small retailer’s evaluation and decision making of assortment planning. So, filling this gap, the current study wants to explore the decision making of these small retailers.
A very important variable of assortment planning involves stocking and placing of number of SKU’s within each category of product. Along with this, the most obvious store constraint is the physical dimension of a store. According to Mantrala et al. (2009), factors like average demand of the product, variations of demand and percentage of demand satisfied, dictate how much merchandise should be in a store depending upon the store size. These factors are easily maintained and monitored in the case of organized retailing (Mantrala and Rao, 2001). But these constraints are even more challenging for a small retailer where the store size is minimum and the categories offered cannot be compromised. Small retailers use a more heuristic approach. Irrespective of the location if the retailer, many internal and external factors influence the decision making of the small retailers. Understanding the above discussed factors, the current research explores that how do small retailers manage their product assortment? The current study investigates all these questions and tries to bring out a comprehensive model for small retailer’s decision making of assortment.
Research methodology
Design
A mixed method approach involving both qualitative and quantitative data methodologies is being used for the current study. According to Greene et al. (1989), mixed methodology is used when the outcome of one method serves as the input for the other stage. Initial data for the study were systematically collected and later analyzed to generate a theory grounded in the data. In the qualitative stage, grounded theory is used to develop a conceptual model and later the findings are integrated to build certain theoretical foundations. The qualitative research has helped to act as a guiding path to conceptualize the thoughts, literature and observations on the field. The items for the questionnaire have been extracted from the qualitative data and further filtered using EFA. The elaboration of the scale development is given in Table II. The hypothesis testing was done through statistical analysis using structural equation modeling through analysis of moment structures (AMOS) was used. First stage of the study comprised of building qualitative data to figure out the theoretical point of view of product acceptance of small retailers before proceeding for collection of data from the questionnaires (Corbin and Strauss, 2008; Maxwell, 2012).
Data collection
The first phase of data collection of the study is a qualitative approach constructed on grounded theory (Strauss and Corbin, 1990, p. 21). In-depth interviews were conducted with 37 retailers from four villages belonging to Jammu province. The villages chosen belong to the rural part of Jammu region. Using a categorical approach, the first stage generated a theoretical framework. Certain questions were asked on the basis on the store observations such as the current products the retailer carries, how he has placed them on shelves or the amount of goods he carries in the store and often does he refill the products on shelves. After conducting each of the interviews, it was transcribed and converted into text verbatim so as to interpret some meaningful insights from them. Average length of each interview was 30-35 min. Each of the interviews was transcribed before conduction of the next interview in order to analyze whether the data and the information were becoming redundant. First of all, the verbatim gathered directly from the text of interviews was considered as the first order codes based on the common themes emerging from the interviews. Common themes were then arrived at in the form of sentences, which constituted the second order codes. In the third step, the final themes were inferred for the behavioral constructs based on analysis of the second order codes. Further questionnaire was developed using the statements retrieved from the qualitative interviews. The final questionnaire had 7 themes including 46 items.
The second stage of the study involved a quantitative approach. Convenience sampling was used as a sampling method for the study. The sample of the study was drawn from the small retailers who own a retail store in the selected rural areas of Jammu and Punjab. The data were collected from 14 villages of four districts of Jammu Province and six districts of Punjab. The villages fall in the rural areas of Jammu and Punjab. The selection of the villages was based on stratified sampling technique. For data collection, a sample size of 400 retailers was targeted and responses from 354 was attained. According to Hinkin (1995), a sample size of 150 observations should be adequate to obtain precise result for an exploratory factor analysis and a minimum sample size of 200 is selected for confirmatory factor analysis. Hence, the sample size of 400 was sufficient for the quantitative analysis using SEM. The small retailers selected were mainly selling FMCG products. The offered product categories ranging from grocery to apparel to cosmetics.
Conceptual framework
Using in-depth qualitative interviews, certain themes were attained as the end result. Behavioral themes were generated from the process which involved data generation, data coding and data organization. Following the procedure, we arrived at seven constructs that contribute toward the small retailers’ product adoption decision (referred in Figure 1). With the help of the themes developed from the qualitative data collection and the post literature analysis, certain hypotheses were made, which helped to develop a conceptual model for the study. The scales developed from the qualitative study can be seen in Table II.
Hypothesis development
The conceptual model elaborates the various antecedents to the small retailer’s product adoption decision. The formulated hypotheses are as follows.
Retailer’s profitability
Price sensitivity is one of the prime consideration of a retailer catering to the rural consumers (Sinha et al., 2017). Thus, price acts as an important indicator for the rural consumers in making a choice among products. Value for money drives their product search and evaluation. Thus, small retailers need to stock products that serve the value for the customers, in a limited store space. Retailers stocking is strongly influenced by the margins they receive from the distributors. The retailer uses this plan of action for brand new product introduction (Shaikh and Gandhi, 2016). However, the competing cost and credit provisions the retailer provides to the people limits them to further use any promotional tool (Tellis, 1987). Further promotions are provided only when they are offered by the manufacturers. In rural areas, where the customer awareness is low, such benefits may even not be penetrated to the customers as the retailer gains all those profits. So, it can be hypothesized that:
Retailer’s profitability influences product adoption decision of a small retailer.
Customer demand
Customer demands is one of the most emphasizing factor that evolved from the interviews with the small retailers. Prior research has emphasized on how customers belonging to rural areas are brand conscious and do not want to switch. In case the retailer fails to stock these items, it creates a negative impact for the retailer thus reducing the store patronage (Lee et al., 2008).
Product assortment, convenience of transactions, price negotiations and shopping experience affects the consumer’s choice of small retail stores (Messinger and Narasimhan, 1997). Thus, a very important feature of small retailers is their capability to adjust the supply as per the demand of their local customers (Landry et al., 2005; Smith and Sparks, 2000). Economic constraints also impact customers focus toward specific choice of brands within a category. The strength of the small retailers is their capability of responding to customer’s demand (Griffith et al., 2006).Thus, retailers need to examine the demands of brands within each category and then decide upon which all products to keep in a store. Understanding the needs of the customers is one the most important factor. If a specific brand is not in demand for a continuous time, retailer consider to drop them. Thus, we can hypothesize:
Customer demand influences product adoption decision of a small retailer.
Customer brand awareness
Stocking established and popular brands was universal. Customers are now aware and are at an eager to use these brands. Webster (2000) indicated that brands provide retailers with many advantages containing enlarged consumer demand, a favorable approach toward branded products in their stores, and reliability. Every retailer stocks established brands (national and regional), as these brands are in demand and if customer will not find their preferred brand in one store they will easily switch the store. The awareness on the consumers shopping pattern in global scenario has also increased and also on the products introduced because of liberalization of the media (Rao, 2000). Multiple model have led to the increase in brand visibility like television, radio, newspapers and magazines. Indian customers have now begun trying different things with brands (Mukherjee and Patel, 2005). However, non-branded items keep on being sold through conventional retail outlets, in spite of the fact that items, for example, food items are sold through both traditional and present day outlets (Chattopadhyay et al., 2011). Indian customers are opening themselves toward brands and are accepting them. Indian consumers are aware of the fact that a brand adds value to a product (Rao, 1998). Both the rural and urban markets in India are quite a lot similar in their awareness about the brand and even about the quality associated with the brands, but in the developed areas customers have special preferences about foreign brands (Rao, 2000). Kumar and Bishnoi (2007) in a survey of 32 villages in India concluded that rural consumers are ready to buy a diverse products and brands if they are offered on discounts or lowered prices. Thus, it would be clear to hypothesize:
Customer brand awareness influences product adoption decision of a small retailer.
Relationship management
Relationship Management is one of the impelling cause for a small retailer. Marinating customer relations is not only what they indulge into, but supplier, distributor or wholesaler relations also play a strong role. The wholesaler or distributor plays an essential role in the product adoption process of the small retailers (Sinha et al., 2017). Almost all of the retailers were of the view that they were prepared to purchase the brands that were told to them by the wholesalers. The retailers have an informal relationship with the customers which live in the same catchment area. Retailers also stocked special products (specific brand) when a customer asks them to do. In a study, Home (2002) discovered that the customers who visit small retailers give preference to the friendly staff, convenience of the store location, purchase convenience and the chances of meeting relatives/friends at the store. The retailers’ conduct to treat their clients and the retailers’ learning about their regular buyers empowers them to serve them effectively and improves their capacity to deal with the complaints of the customers (Adjei et al., 2009; Lee et al., 2008). Research suggests that the relationship of the small retailers with their consumer play a major role in increasing the customer loyalty, repurchase intentions and minimizing the customer switching (Auh et al., 2007; Lee et al., 2008). So, we can hypothesize that:
Retailer relationship management influences product adoption decision of a small retailer.
Store attributes
The previous literature on retail has mostly concentrated on store image and significance of store attributes in understanding the purchase and store choice behavior of the customers (Carpenter and Moore, 2006; Sinha and Banerjee, 2004; Sinha et al., 2005; Sinha and Uniyal, 2005). Challenges of scare resources like capital and space, small retailers do not keep a wide variety of goods at the store. Catering to a limited catchment, small retailers do not feel the need to provide a better store in terms of attributes. They are not able to expand their store in terms of size, goods they carry, varieties they offer and the customers they cater. Due to space constraints, large inventories are not maintained by these retailers and thus leading to a stock out situation. According to Oppewal and Timmermans (1997), store attributes is one of the prime indicators of the store atmosphere, these attributes can stimulate cognitive responses among the customer’s needs and requirements. Small retailers design their stores based on the customers. Assortment of the store can act as a differentiating factor for a retailer when he is serving a limited catchment. The organization and placement of the products in the store with limited shelf space is a very important decision to be taken by the retailers. Such strategic decisions are important to a small retailer:
The store attributes are positively related to the Shelf space allocation of a product in the store.
Catchment area
Population of the trading area, buying characteristics of the customers in the catchment and the disposable income of the customers living there decides the store performance (Palmer-Jones and Sen, 2006). The rural markets have low population density as compared to other trading areas, thus the consumer shopping behavior is more consistent and the demographic features such as buyers’ income and age had very low variation. A more homogenous set of customers is relatively easier (Goswami and Mishra, 2009). But retailers do give emphasis to the trading area depending upon how far your distributors and suppliers are and thus make decisions of inventory management accordingly. Competition on the basis of location, assortment and prices being offered by various small stores located in a same catchment area can be a differentiator in customer attraction and retention.
So, we can hypothesize that:
Catchment area influences product adoption decision of a small retailer.
Customer profile
Indian demographic profile is a hub of multi-caste and multi-lingual people, so a retailer needs to select its assortment keeping all factors under consideration. Dholakaia et al. (2012) highlights the role of caste and family relationship within retail businesses and between wholesale and retail businesses, hinting at the deep ethno-social fabric, which plays a major role in business decisions relating to purchasing of stock and credit policies. The rural consumers’ income is less and lack stability. The choice of jobs is very less due to locational disadvantages. In small regions, income is either relying on farming or a comparatively very small level of non-farm activities. Farm employment also depends to a great extent on climatic conditions (Tiwari et al., 2008) so they economic flow is seasonal. This restricts the small consumer to have a trial with purchasing new products on a continuous basis within their confined income (Tellis, 1987). But as said by Viswanathan et al. (2010), the increase in the disposable income of rural customers has led to increase in the shopping. Their selection of products is no more just on the basis of cost. This has influenced the retailers to strategize their product selection:
Customer’s profile influences product adoption decision of a small retailer.
Data analysis
Quantitative data analysis was conducted using SPSS 22 and Structural Equation Modeling using AMOS 22 to analyze the measurement and structural models in the suggested framework. The approach of SEM is used in this research to empirically define and validate constructs, and study causal relationships among them. In specific, latest scales can be evaluated for reliability using coefficient α, with a value of 0.50 or greater as an accepted standard for brand new scales (Nunnally, 1978). The items showing a value less than 0.50 were deleted from the list. A total of 110 items were retained in the retailer questionnaire. A discriminant analysis was used to evaluate whether the location of the small retail store (urban area or rural area) will discriminate the behavior of product adoption by small retailers. With the help of discriminant analysis, a strong statistical evidence of no significant differences between urban located and rural located small retail store for all other constructs of the study was derived. The insignificant p-value (>0.005) for majority of the constructs results of the urban and rural location of the small retail stores does not discriminate the data set.
Assessment of measurement model
A two-step method highlighted by Anderson and Gerbing (1982) was used, where the measurement model is studied prior to the study of the structural model. First, items are tested for reliability and then the various levels of statistical validity analysis including convergent and discriminant validity analysis. Principal components analysis was conducted to set up that items load with each other appropriately, showing that the measures are described by an underlying construct. This analysis tends to make stronger claims of measuring validity. Reliability is the capability of the scale to continuously yield the similar results. Reliability was calculated using three different methods. First Cronbach’s α, an accepted measure of internal constancy was calculated. A minimum value of 0.50 was considered adequate (Nunnally, 1978). Chin (2010) mentioned that α is a lower bound guess for reliability since all indicators are fairly weighted in α, but adversely weighted in the measurement model. Two other determinants of reliability have been used composite reliability with a threshold limit of 0.70 and average variance extracted (AVE) which has a proposed cut off value equal to 0.50. Table I puts forward the details regarding reliability and validity. Each measured constructs display acceptable reliability build on the standard employed (refer Table I). AMOS 22 was used to estimate the exogenous constructs in the study.
Structural model
A model requirement requires determining every connection and variable in the model. The systematic model for the paper is described by allocating relation in the formulation of the study. The systematic model of this study is shown in the Figure 1. The details of the outcomes of CFA moved on the structural model are stated in Table II. The results indicate a good model fit and also confirm that the exogenous construct has a positive and significant correlation with the construct. The χ2 value is the traditional estimation to know overall model fit. The χ2 is the degree of freedom percentage for all over structural model for the present study was 3.915, showing a good model fit. The Goodness of Fit=0.858 and the Adjusted Goodness for Fit=0.827 are without limit fit indices and are required to instantly estimate how well the supposed theoretical model adjust the sample data (Figure 2).
“Root Mean Square Error of Approximation” (RMSEA) endeavors to correct for the sensitivity of χ2 to sample sizes greater than 200 (Byrne, 2010). RMSEA values less than 0.08 are believed to be acceptable (Hair et al., 2010), thus our study with an RMSEA value of 0.052 suggests a good fit. The incremental fit indices of “Normal Fit Index” and “Comparative Fit Index” were also studied for the model and the values of 0.748 and 0.859, respectively, depicted a good fit for the overall model.
The standardized estimates and the critical ratio values in Table II specify the importance for 16 out of 19 causal ways suggested in the framework. Therefore, we can see that the outcomes assist the theoretical model of the study. The hypotheses outcome from study of complete systematic model is summarized in the Table III. The suggested model shows a direct relationship of customer demand, retail profitability, relationship management, customer brand awareness, store attributes, catchment area and customer profile with retail assortment planning construct. Also the customer price perceptions and customer variety perceptions showed a direct and significant relationship with the retail assortment planning.
Discussion
The major objective of this study is to understand small retailer’s assortment decision making criteria. The study explores the factors that affect the product selection of small retailer in India. The results derived from the quantitative data indicate some interesting results. The study pinpointed theoretical connections between the emerged themes and through these linkages study presented a conceptual model of small retailer’s assortment planning model, grounded in data using inductive logic. Further, the conceptual model derived from the qualitative data is tested to authenticate the relationship between the identified factors and the dependent variable. The suggested model shows a direct relationship of Customer Demand, Retail Profitability, Relationship Management, Customer Brand Awareness, Store Attributes, Catchment Area and Customer Profile with retailer’s decision making.
Store attributes show a direct and strong relationship with the retailer’s assortment planning. This indicates that the small retailers utilize their store variables effectively to leverage the limited store resources. Limited store space however is a constraint for the retailers but he organizes the assortment in a way that the uses the space to the utmost point. The small retailers initially plan the space requirements for their stores by analyzing the number of categories (variety or breadth), then the space required by each and every category on the basis of number of SKU’s present inside the category (depth), and ultimately on the basis of number of units each SKU holds (desired service level). It was identified that the retailers organize the complimentary categories in the same shelf so that buyers shopping experience is more pleasant and easy.
It was also found that the margins given by the supplier or the distributors also influence the retailer’s decision of keeping the product in the store. Regional brands offer a high margin to the retailers over the national brands, so retailers prefer to add them in the assortment at the store. However, the customer demand is also a prime factor in retailer’s final decision making. The findings reflect that higher the customer demand, higher will the number of SKU’s in the store. Even though the retailers want to preferably sell regional brands due to high margins, customer demand and preferences also need to be kept in mind. Some studies have an opposite opinion in this reference. According to Rao and McLaughlin (1989) margins provided to the retailer have a negative impact on the product adoption by retailers, while Montgomery (1975) and White et al. (2000) in their study found no significant relationship between the two variables. The opposition in the behavior can be due the limited categories being offered in the small retail store. Since a small retailer carries limited assortment, in order to attain the maximum profits, he targets high margin products whereas to the contrary the categories offered are large in the organized stores. The small retailers and their suppliers mitigate the extra shelf life of stock requirements by abbreviating reorder and transferring times. The retailer prefers to order less units of an SKU more commonly, so that he can assign less area to that SKU without shortage of stock. This helps the small retailer manage assortment in low cost and low space requirements.
Customer brand awareness did not emerge to be a significant factor in assortment selection for small retailers. The Indian retail scenario has seen a tremendous shift and also the consumers have started experimenting with new brands. The insignificance of brand awareness in case of small retailers may be due to the reason that customers in the targeted region do not swap the brands much. Also because a small retailer gives margin and demand more emphasis rather than keeping new and advertised brands. However, retailers consider the new products only if customers demand them. New addition in the assortment is not made on the bases of advertisement or promotions of new brands but on customer’s willingness to buy it. The products with high awareness are kept in front display rather than the less known products. Relationship customers, distributors and the wholesaler also emerged to be an important factor of consideration. Customer relationship is something small retailers always strive for. When a loyal customer recommends certain goods to the retailer to keep in the store, the retailer keeps the product only for maintaining the relationship with the customer, and thus ends retaining the customer. Similarly, if the supplier offers a new product to be kept at the store the retailer keeps it only when the relationship between them is healthy. This can be linked to the village connectedness with the city area. If the villages are well connected to the city areas, customers are aware of brands and there is competition in form of other retailers, shopkeepers shall be compelled to listen to the customer and stock national brands. In remote villages where customers do not have any other option, retailers prefer local or regional brands with high margins. However, the villages surveyed in the study are quite affluent and thus retailers need to keep themselves updated. Similar results were given in the study by van Everdingen et al. (2011). The knowledge about the customers and the catchment area helps a small retailer to fulfill the needs of the customers. It is important to understand the shopping habits of customers and a market-centric approach act as a key strength of small retailers.
The theoretical foundations of the conceptual model not just limited to small retailers of Jammu and Punjab region. The identification of similar antecedents of assortment planning of retailers in geographically varied rural markets in India indicates a degree of psychological and behavioral similarity among retailers. Hence, the findings of the empirical data of the study conducted in Jammu and Punjab provinces of India may be relevant to other parts of the country and rural areas of other developing countries with similar scenario. A broader application of this current study may be inherent in the sampling method used since population-based stratified random sampling may guarantee that villages of each population strata symbolizes the final results (Agrawal, 2014; Zeller et al., 2002). Thus, we can generalize the results to the rural retailers as within each strata of the rural regions the small retailers may show similar descriptions. Recent findings have revealed that problems of category management are much more compound and exciting, highlighting the ongoing need for research that can help retail executive manage and assign assortments. The current study is an initiative to explore the factors that contribute in small retailers decisions on assortment planning. Prior research works have been organized retail dominated, and research in unorganized area have been scanty. However, the limited research that can be conducted focusses on profit oriented factors of retailing. This is a multidimensional approach to understand the concept of assortment planning by small retailers. A very important finding of the current study focuses that the small retailer’s assortment planning behavior does not get affected by the location of the store. The retailer of small stores located in the rural and urban areas behave similarly in terms of product selection and retail shelf management. So, the retailers need to understand the environment they are dealing into and the customer profile who visit their stores. Understanding customers profile and then selecting the products to be kept at the retail store will help the retailers attract more customers by satisfying the customers’ needs.
Managerial implications
The factors identified in the current study would help the marketing managers of firms targeting the small retailers, to explore the factors influencing small retailer’s assortment decision making. In developing economies like India, major population (customers) lie in the rural areas of the country and prefer small retailers to shop their daily necessities. These firms need to be acquaint with the factors being discussed here. Significance of each factor and its strength with the dependent variable is predicted using the regression weights in the model. Using this model, the products specially targeted for the rural India can be tested. Marketing managers of firms with target audience as small retailers can draw many inferences from the present study. They may devise rural strategies keeping attributes like door to door delivery, frequency of timely supply and localization of the supplier, etc., on the basis of product demand and attribute. Managerial application of the suggested mode for small retailers may build a future path for exploration of studies in the important and unexplored are of rural retailing. Small retailers understand their catchment and effectively utilize this information to build good relationships with its stakeholders. The most important feature of a small retailer is the retail facilities it provides to its customers as well as the suppliers. Retailers need to focus and retain the facilities like credit, buy back, replacement and home delivery in order to attract customers toward them.
The results indicate that higher margins from the distributors in comparison to the net margins from the manufacturer per product category, lead to higher chances of product acceptability by the small retailers. Manufacturers and suppliers should capitalize in improving the relationships with the distributors and the customers. The marketers should particularly need to take into consideration aspects of equality and motivate the sellers to build and encourage relationships with small retailers. The study clearly indicates that retailers need to develop their stores in such a manner that the maximum utilization of the space is done. The higher the number of shelves in the stores the more is the number of products being accepted by the retailer. Also the retailer displays more of the products in the stores which attracts more customer base. So, at the last remark the retailers should consider buyer, supplier, environmental together with the profit oriented determinants when deciding the assortment planning for the store.
Conceptual model
Structural model
Scales used and reliability analysis
| Construct | Cronbach’s α | Composite reliability | AVE |
|---|---|---|---|
| Customer profile (CP) | 0.795 | 0.712 | 0.880 |
| I have differentiated every customer based on the brands they carry (CP1) | |||
| I cater all local customers in my colony (CP2) | |||
| I am aware of my customers and their needs (CP3) | |||
| Customer demand (CD) | 0.782 | 0.984 | 0.898 |
| For me customer preference is important than margin (CD1) | |||
| Local brands are preferred because of its price (CD2) | |||
| For eatables customers prefer local products (CD3) | |||
| Customer brand awareness (CBA) | 0.831 | 0.903 | 0.754 |
| I have to update my products because my customers are up to date (CBA1) | |||
| Other retailers in my colony are updated so I have to be updated (CBA2) | |||
| Customers are aware of brands so I have to add new brands (CBA3) | |||
| Although customers prefer branded products but I have to keep local products (CBA4) | |||
| Retailer’ profitability (RP) | 0.840 | 0.977 | 0.934 |
| When the customer preferable product is not available I force them to buy my preferred product (RP1) | |||
| I prefer placing high margin products in front shelves (RP2) | |||
| I select supplier on the basis of margin he provides me (RP3) | |||
| Catchment area (CA) | 0.826 | 0.941 | 0.678 |
| I do not feel competition from other retailers as my customer are fix (CA1) | |||
| I add new products to my store when I see other retailers have added (CA2) | |||
| I update products based on retailers in city area (CA3) | |||
| As competition is tough so I need to differentiate products I carry (CA4) | |||
| I like to manage store like big retailers in city area (CA5) | |||
| I keep products for kids women and children (CA6) | |||
| My store is located in the city area (CA7) | |||
| I have to travel large distance to reach to my supplier (CA8) | |||
| My store is located by so many houses (CA9) | |||
| I keep products for kids women and children (CA10) | |||
| Relationship management (RM) | 0.719 | 0.956 | 0.816 |
| I add products to my store which are recommended by the supplier (RM1) | |||
| I have fixed supplier since I have opened my store (RM2) | |||
| My supplier delivers goods on time (RM3) | |||
| Whenever I visit my supplier he has goods available at store (RM4) | |||
| If customer demands products and it’s not available I get it afterwards (RM5) | |||
| My customers trust my recommended products (RM6) | |||
| Suppliers deliver products at my shop (RM7) | |||
| Store Attribute (SA) | 0.842 | 0.741 | 0.921 |
| I have increase my shop size (SA1) | |||
| I have increase no of shelves at my store (SA2) | |||
| I have fixed shelves for all items in the shop (SA3) | |||
| When all shelves are full customer get attracted (SA4) | |||
| I use hangers for product display (SA5) | |||
| I display goods near price counter (SA6) | |||
| I have refrigerator for display of cold drinks (SA7) | |||
| I place the refrigerator near counter for better display (SA8) | |||
| I have extra go down for stocking of goods (SA9) |
CFA results for structural model
| Estimate | SE | Critical ratio | |
|---|---|---|---|
| CD1←CD | 0.721 | 0.062 | 21.433* |
| CD2←CD | 0.646 | 0.054 | 18.826* |
| CD3←CD | 0.519 | 0.053 | 15.119* |
| CP1←CD | 0.732 | 0.060 | 19.442* |
| CP2←CD | 0.529 | 0.043 | 17.736* |
| CP3←CD | 0.613 | 0.052 | 17.680* |
| SA1←SA | 0.625 | 0.049 | 16.225* |
| SA2←SA | 0.754 | 0.053 | 16.792* |
| SA4←SA | 0.516 | 0.032 | 15.197* |
| SA9←SA | 0.818 | 0.063 | 17.138* |
| RP1←RP | 0.735 | 0.086 | 6.902* |
| RP2←RP | 0.712 | 0.078 | 9.510* |
| RP3←RP | 0.561 | 0.054 | 5.362* |
| CBA1←CBA | 0.645 | 0.063 | 10.321* |
| CBA2←CBA | 0.762 | 0.076 | 15.685* |
| CBA4←CBA | 0.596 | 0.071 | 13.539* |
| RM1←RM | 0.667 | 0.043 | 18.427* |
| RM2←RM | 0.479 | 0.066 | 17.223* |
| RM4←RM | 0.808 | 0.049 | 19.236* |
| RM5←RM | 0.818 | 0.065 | 17.856* |
| RM7←RM | 0.808 | 0.062 | 17.189* |
| CA1←CA | 0.724 | 0.054 | 13.351* |
| CA2←CA | 0.845 | 0.058 | 22.669* |
| CA3←CA | 0.849 | 0.055 | 23.438* |
| CA6←CA | 0.806 | 0.053 | 23.069* |
| CA7←CA | 0.815 | 0.062 | 22.428* |
Note: *Significant at 0.005
Standardized regression weights
| Hypothesis | Estimate | SE | Critical ratio | Result | |
|---|---|---|---|---|---|
| H1 | RAP←RP | 0.684 | 0.056 | 13.203* | Supported |
| H2 | RAP←CD | 0.708 | 0.062 | 12.054* | Supported |
| H3 | RAP←CBA | 0.583 | 0.056 | 13.211* | Supported |
| H4 | RAP←RM | 0.710 | 0.068 | 11.539* | Supported |
| H5 | RAP←RF | 0.440 | 0.035 | 10.041* | Supported |
| H6 | RAP←SA | 0.769 | 0.071 | 11.304* | Supported |
| H7 | RAP←CA | 0.870 | 0.063 | 13.158* | Supported |
| H8 | RAP←CP | 0.743 | 0.057 | 13.240* | Supported |
Note: *Significant at 0.005
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