سوابق و عواقب قصد ارتباط : مفاهیمی برای بازاریابی رابطه ای و معامله ای
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|2810||2003||10 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Industrial Marketing Management, Volume 32, Issue 8, November 2003, Pages 667–676
The terms relationship marketing (RM) and loyalty have been extensively promoted in marketing literature. Advocates of RM and loyalty have argued that RM leads to loyalty and loyalty leads to profitability. However, currently available evidence questions these arguments. We propose a term relationship intention. Relationship intention is willingness of a customer to develop a relationship with a firm while buying a product or a service attributed to a firm, a brand, and a channel. We build a multi-item scale for measuring relationship intention. We propose a framework, wherein we argue that the relationship intention is influenced by the customers' perceived firm equity, perceived brand equity, and perceived channel equity. We propose the consequences of relationship intention as being low cost to serve, price premium, word-of-mouth promotion, and company advertisement. We also argue that relationship intention moderates the association between lifetime duration and profitability. Finally, we discuss the managerial implications of relationship intention in terms of transaction and RM.
Social psychology literature states that a good predictor of what individuals will do is their stated intention (Fishbein & Ajzen, 1975). On the other hand, conventional wisdom suggests that the best predictor of future behavior is past behavior. Purchase intention-based research has dominated the marketing literature for more than two decades. However, in the mid-1990s, with the computational revolution and the availability of behavioral data, marketing researchers were able to increasingly depend on behavioral data. Armstrong, Morwitz, and Kumar (2000) stated that both intentions and past behavior are useful for forecasting future behavior. In this paper, we attempt to build a framework that combines a customer's actual behavior (duration of stay with a firm) and the customer's behavioral intention (intention to build a relationship). We then conceptualize the effects of both purchase intention and actual behavior on customer profitability. A buyer firm (hereafter referred to as Customer) may repeatedly buy from a supplier firm (hereafter referred to as Firm) because of one or more of many factors such as price advantage, inertia, convenience, trend, social influence, high switching costs, and their emotional attachment with the firm. Firms should therefore ask the question, “Do these customers really want to build a relationship with us?” If the answer is “No,” it means that these customers do not possess an adequate level of emotional attachment with the firm, which makes them want to build a relationship with the firm. If firms mistake these No customers as “loyal customers” based only on their observed behavior, the firm would end up investing incorrectly in building relationship with these reluctant customers. Thus, if a firm can find which of these customers really intend to build a relationship, it will be able to better target these candidates to invest in a relationship building. In this paper, we develop an argument that relationship intention, defined as the willingness of a customer to develop a relationship with a firm, is as important as the customer's actual behavior. We also propose that a customer with a high relationship intention is more profitable in the long run. A customer with no relationship intention may not be profitable to a firm, if the firm attempts to build a relationship with this customer. It may also seem straightforward that it is easier to build a relationship with customers with high relationship intention. But, one of the major objectives of this paper is to find how relationship intention develops. We contend that a firm can improve customers' relationship intention by acting upon the antecedents of relationship intention. We will understand, explore, and discuss the antecedents of relationship intention and its consequences. First, we define and develop the relationship intention construct. Second, we develop a conceptual framework to describe the antecedents and consequences of relationship intention. Third, we understand how the relationship intention moderates the association between lifetime duration and profitability. Finally, we suggest strategic recommendations based on relationship intention.
نتیجه گیری انگلیسی
We proposed that relationship intention is an important parameter that helps marketers, and discussed about which marketing approach is well suited for the customers. We also defined three antecedents driving relationship intention, viz., brand equity, firm equity, and channel equity. These antecedents are proposed to be positively affecting relationship intention, and relationship intention influences the association between lifetime duration and profitability. The relationship intention does not necessarily change over time if the firm equity, the brand equity, and the channel equity also do not change over time. Finally, there are marketing implications of this framework, which suggest us to follow the TM and RM approaches according to relationship intention. There are two limitations important to be noted here. First, only extremes of relationship intention continuum, their importance, and their implications are discussed. The intermediate levels on this continuum need to be explored. Second, we have implicitly assumed that there is no negative side to the relationship intention continuum, where a customer has an intention to build a negative relationship. This can also have major implication for managers. This conceptual model lays a foundation for further research. Operationalization and measurement of the constructs, development of methodology, determination of data collection, and finally, empirical testing need to be conducted for empirical evaluation of the model. Further, the model can be tested across various industries, markets, firms, brands, and channels.