Empirical Research On The Drivers Of Cross-buying Intention

The concept of retail is generally divided into the narrow and the generalized, the generalized retail refers to the direct sale of commodities or service to the final buyers to satisfy the individuals’or their families’consumer demands, the narrow retail refers to the direct sale of commodities to the final buyers to satisfy the individuals’ or their families’ demand, this paper studies the narrow retail. The retail is the most ancient and most active industry, is also our country’ the quickest developing one in recent years, is one kind of service that takes the medium commodities exchange as the goal function, is closely linked with people’s life. Because of the reform and open policy, following the economic development as well as the change of expense way, the retail is also experiencing the unceasing transformation. Under the condition of market economy, the retail trade is very important in a national economic system. For example, the total volume of retail sales of social consumption occupies38.83percent of GDP in2010in China.In the last decade, marketers have primarily focused on keeping customers. Only recently have they become aware that creating value by cross-selling additional services or products is also an important aspect of customer relationship management. In this article we investigate how store reputation, merchandise image, convenience image, perceived time pressure and customers’ switching cost affect customers’cross-buying intention at a supermarket. We don’t only consider the retailers’factors but also consider the customers’ factors who patronage the supermarket. Recently, managers have acknowledged that retaining customers is not sufficient to be successful. Many companies are seeking to enhance the value of their customers by expanding the range of products and services they buy from the firm. This goal has sparked a growing interest in how this goal may be achieved. In order to retain customers, managers have focused primarily on satisfaction. However, does satisfaction also create more value by leading consumers to cross-buy more products or services? The role of price discounts has also come under fire. For example, while customers for one product line may be initially attracted by low prices, can such buyers be profitably attracted to purchase other goods and services offered by the firm? These questions are especially relevant for multiservice or goods providers. The value of a customer of a merchandise provider depends on:the duration of the provider-customer relationship (length of relationship), the usage level of the consumed services (depth of the relationship), and the number of different services bought from the same provider (breadth of the relationship). For these companies, customer retention by itself is not fully responsive to the goal of value creation.Such evaluations are typically based on their currently purchased services or goods. Whether this intelligence will aid in the determination of cross-buying opportunities is not clear as other services may have demand determinants such as price elasticties and favored product attributes. A positive evaluation of a currently purchased service and goods does not imply a comparable interest in others. Depending on the consistency among the services or merchandises provided by the firm, the impact of merchandise image, convenience image, and perceived time pressure on cross-buying might be different from their effect on the length and depth of a relationship. This may be of major importance for cross-buying. As more alternatives are considered, the effect of competition may become more important. As additional goods are added to the decision, cross-buying is likely to become a more elaborate decision process relative to retention and usage decisions.Consumers’ cross-buying enables retailers to cross-sell their products and increase revenue contribution from existing customers. The effectiveness of cross-selling can be greatly improved by identifying the drivers of cross-buy and using them to target the right customers.In this study we identify factors of the retailers such as store reputation, merchandise image, and convenience image, and factors of supermarket customers such as perceived time pressure, and switching cost, as important drivers of cross-buying. The results of the study have important implications for academicians in understanding what drives cross-buying as well as practitioners to help design more effective cross-selling strategies. The firms can sell additional products and services and thereby expand the relationship with their existing customers. Cross-selling gives companies an opportunity to increase the revenue contribution from their existing customers. In many cases (especially services) cross-selling is an easier option for companies to grow compared to acquisition of new customers. Academic research has identified the importance of cross-selling in different facets of customer relationship and customer value. Effective cross-selling of multiple products or services enhances customer retention because customer switching costs increases with increased cross-buying. The return on cross-selling(or add-on-selling) as one of the three components of customer equity. Customers who buy multiple product categories from a firm tend to have longer profitable lifetime duration. Cross-buying is also an important driver of customer lifetime value, which in turn, leads to higher revenues, higher share of wallet, and higher customer value.Despite the importance of cross-selling for customer retention and customer value, limited research has been done to identify the drivers of cross-buying. With the limited resources available with firms to allocate for different marketing activities such as retention and cross-selling, it is not possible to target all existing customers for cross-selling. Neither is it wise to spend marketing resources on all the customers because, not all customers are likely to cross-buy. This makes it imperative for firms to identify customers who have higher propensity to cross-buy so as to maximize their return on investments in various marketing activities especially cross-selling. Identifying the customers who are most likely to cross-buy is the first and most important step in developing cross-selling strategies. A limited number of studies in the past addressed the question of identifying customers who are likely to cross-buy. Other relevant studies include a next-product-to-buy (NPTB) model and a model to predict the best way to sell the right product to the right customer at the right time. These studies give us insights on the drivers of cross-buy identified in the context of a service industry. In the case of services, the relationship is often contractual with higher switching costs. The customer often acquires the products/services in a natural sequence, for example, in financial services a checking account will often precede a mortgage or a loan. On the contrary, in a non-contractual setting such as retailing, the switching cost is often very insignificant and the natural sequence of product acquisition is less apparent. Because of these differences, we expect the drivers of cross-buy for retailing to be different from that of a contractual servicebased relationship. Moreover, some of the drivers identified in earlier studies such as satisfaction, payment equity, and perception of quality were evolved from surveybased studies. The need to collect primary data to measure these drivers often limits their use for identifying customers for cross-selling opportunities. The main advantage of studying perceived time pressure variable as drivers of cross-buy behavior is that the firms can then identify the customers’buying intention to pinpoint the customers who are likely to cross-buy. Furthermore, there is a need to quantify the benefits of cross-buy in terms of improvement in customer-based metrics. We address these issues in this study. Specifically, the objectives of our study are (1) to understand the motivation of supermarket customers to cross-buy,(2) to identify the drivers of cross-buy in non-contractual settings such as supermarket retailing, and (3) to observe whether cross-buy helps to improve revenue and other customer-based outcome metrics. We start with a discussion of the conceptual background of cross-buying. In the next section, we identify the factors that may facilitate cross-buy and formulate research hypotheses relating to the drivers of cross-buy in retailing. We then propose a framework for analyzing the antecedents of cross-buying intention in retailing. In the subsequent section, we provide a discussion of the data and the models used to test these hypotheses. In the final section, we point out some of the limitations of this study and offer suggestions for future research. In a contractual setting, cross-buying refers to buying additional products and services from the existing service provider in addition to the ones he/she currently has. By this definition, when a customer terminates a service, the level of cross-buy reduces compared to the previous period because cross-buying is measured as the difference in the number of services that a customer has in two consecutive periods. However, in non-contractual settings such as retail transactions, there is no equivalent to service termination and it does not seem meaningful to measure cross-buy as the difference between the number of different products purchased in two successive time periods. One of the earliest studies on cross-buy identifies prospects for cross-selling of financial services based on the current ownership of product or services and factors such as demographic characteristics and investment objectives of the household. Recent studies have identified some of the drivers of cross-buy or cross-buying intention in financial services. The drivers identified in these studies can be broadly classified into three: customers’ attitude towards a firm and its products, socio-demographic characteristics, and marketing effort by the firm. They do not find support for satisfaction or the difference in satisfaction between the focal firm and the competitors affecting cross-buy. A customer’s willingness to continue the relationship and favorable evaluations of the firm’s ability to provide different types of services also influence cross-buying intentions. Besides these attitudinal measures, cross-buying is also impacted by the channel of acquisition of customers, the type of service, total number of services held in the previous period, household level switching cost, demographic characteristics such as education, gender, income, and age. Marketing instruments such as loyalty programs and the number of direct mail in the previous period are also important determinants of cross-buying.Recently, managers have acknowledged that retaining customers is not sufficient to be successful. Many retail formats are seeking to enhance the value of their customers by expanding the range of products and services they buy from the firm. This paper tries to examine the impacts of store reputation, on the customer’s perceived value and cross-buying intention. By analyzing the customer samples from the supermarkets of retail formats taken as the research object, the key findings are:(a) merchandise image, convenience image, and perceived time pressure have significant influences on the customer’s cross-buying intention;(b) store reputation has a significantly positive impact on merchandise image;(c) merchandise image, convenience image, and perceived time pressure have significantly positive effects on customer’s switch cost but the effects of store reputation on customer’s switching cost is not significant;(d) customer’s switching cost doesn’t have significant influences on the customer’s cross-buying intention.In this research we seek to extend the literature by addressing the drivers of cross-buying intention in retailing. This paper tries to explore the drivers of cross-buying intention. We take the supermarket for an example in retailing to analyze the factors that drive the customers’ cross-buying intention who patronage the supermarket. The results indicate that store reputation has a statistically and significantly positive effect on merchandise image; merchandise image, convenience image, and perceived time pressure have a statistically and significantly positive effect on cross-buying intention, while store reputation and switching cost don’t have a statistically significant positive effect on cross-buying intention. Merchandise image, convenience image, and perceived time pressure have a statistically significant positive effect on switching cost, while store reputation doesn’t have a statistically significant positive effect on switching cost.This research totally sent25questionnaires in the primary investigating period, and recycled22valid questionnaires. The valid percent of recycling is88percent. The primary questionnaire was necessarily modified according to the information from the primary investigating, and then the formal questionnaire that it was applied in this research came into being.300questionnaires were sent in formal investigating period, and recycled219valid questionnaires. The valid percent of recycling is73percent.The mostly conclusions of this research are that store reputation has a statistically and significantly positive effect on merchandise image, store reputation, merchandise image, convenience image, and perceived time pressure have a statistically and significantly positive effect on cross-buying intention, while switching cost doesn’t have a statistically significant positive effect on cross-buying intention. Merchandise image, convenience image, and perceived time pressure have a statistically significant positive effect on switching cost, while store reputation doesn’t have a statistically significant positive effect on switching cost. Switching cost doesn’t have mesomeric effects on the relationships between store reputation, merchandise image, convenience image, perceived time pressure, and cross-buying intention. The conclusions of this research have important values and implication on enriching the literatures of cross-buying and guiding the future research on cross-buying behaviors.The important findings of this study are that customers’switching cost doesn’t have a statistically significant positive effect on customers’cross-buying intention, and store reputation doesn’t have a statistically significant positive effect on customers’switching cost. Switching cost doesn’t have mesomeric effects on the relationships between store reputation, merchandise image, convenience image, perceived time pressure, and cross-buying intention. It proved to some extent that because the relationship between the company and the customer is contractual in financial industry but the relationship between the retailer and customer is non- contractual in retailing, so the drivers of customers’cross-buying intention between the retailing and financial industry are different.The mostly academic contribution of this article is that this study both considered the factors from both the retailer image (Store Reputation, Merchandise Image, and Convenience Image) and the customer perceiving (Switching Cost, Perceived Time Pressure). It made a empirical study on the drivers of cross-buying intention in retail on the bases of market data surveyed from supermarket customers. The conclusions of this research enriched the literatures on cross-buying behavior. The drivers of cross-buying intention in retail that this paper explored have important reference values in the future research on cross-buying. The practical values of this study consist in that even if the research took the customers from supermarket for an example, but the research conclusions have valuable guidance functions and reference implications on studying other customer groups and retailing formats. It can help the supermarket managers do well in the practical marketing management. It offered theoretical foundations which are valuable and referable when supermarket marketing managers make cross-selling strategies and improve the validity of cross-selling strategies.This research made some significant conclusions basing on the questionnaires investigating on the supermarket customers, taking the customers for an example from supermarket that is the common retail format in our daily life, and by integrated using lots of statistical methods and structural equation modeling (SEM). At last this paper pointed out the limitations of this research and the future research directions.