2017 International Conference on Economics, Management Engineering and Marketing (EMEM 2017) ISBN:

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1 2017 International Conference on Economics, Management Engineering and Marketing (EMEM 2017) ISBN: A Study on Price Perception, Order Fulfillment, Online Relational Selling Behavior and Online Customer Xiang-Yu MENG a, Xin-Feng ZHU b*, Xian-Yong MENG c 1 Zhuhai College of Jilin University, Zhuhai, China a jilinuniv@163.com, b zhuxinfengwhu@163.com, c meng_xianyong@hotmail.com Keywords: Online Vendors Attributes, Online, Customer Citizenship Behavior. Abstract. The purpose of this study was to propose and test a conceptual model that links online vendors attributes, relationship quality, and customer citizenship behavior. The empirical results showed that relational selling behavior was the most important attribute to enhancing both trust, commitment and satisfaction, followed by security and order fulfillment. Introduction The emerging online market provides benefits for both retailers and consumers. In order to successfully service online consumers and avoid potential failures, online vendors should know exactly what the consumers expect from them and how to build the customer relationships and improve the online relationship quality. Accordingly, it is important to understand the issue of online relationship quality (customer satisfaction, trust and commitment) and the related antecedents. A complete conceptual framework is needed to define the online relationship quality and its antecedents in terms of the online retailing context. Price Perception Price is one of the elements in marketing mix, which it plays a very heavy role because marketers use price as communication medium with customers where the message is being clearly perceived by customer as what it meant to the marketers (Dickson and Sawyer, 1990; Monroe and Lee, 1999; Vanhuele and Dreze, 2002). A product price is one of the main decision methods for both customer and also retailers as now the market is very competitive, price has made its position and role in differentiate in designing marketing and business strategies. Price resulted to be the main point for customer to judge what is offered in the market (Monroe, 2003; Monroe and Lee, 1999; Oliver, 1997). Price is also a main factor in transaction relation-ship where it is one of the medium used by marketers to counter the market, either in attracting or in retaining customer or as a element in competing with competitors. Order Fulfillment In online retailing, the fulfillment process can be understood to consist of three stages: order acceptance, order selection, and order delivery (Stock & Boyer. 2009). Taken together, the single external indicator that can be considered to account most parsimoniously for smooth execution of all three 373

2 stages is or-der cycle time (Eroglu, Machleit & Davis, 2001; Boyer et al., 2009). Increasingly, it is believed that effective order fulfillment of promised delivery serves as a means of satisfaction and customer de-light (Boyer and Hult, 2005; Rao Goldsby, Griffis & Iyengar, 2011). Many point to examples of excellence in online order fulfillment driving business growth (Brady, 2010).With timely, accurate, and error-free order fulfillment, e-tailers can offer their customers benefits, such as saving time and convenience of shopping without being restricted by store hours or store location (Dholakia & Uusitalo, 2002).Order fulfillment refers to the delivery of a product or service relative to orders placed by consumers, and it is an essential aspect of Web sites with transactional ability (Yakov et al., 2005). Relational Selling Behavior Relational selling behavior is aimed at managing the quality of the interpersonal relationship between salespeople and customers and tends to build and maintain strong relationships (Boles et al., 2000; Crosby et al., 1990). Relational selling behavior has a positive influence on the buyer-seller relationship if the salesperson plays the role that fits the customer s expectations (Solomon et al., 1985). Crosby et al. (1990) defined Relational Selling Behavior as a behavioral tendency exhibited by some sales representatives to husband/cultivate the buyer-seller relationship and see to its maintenance and growth. Relational selling behavior has a positive influence on the buyer-seller relationship if the salesperson plays the role that fits the customer s expectations (Solomon et al., 1985). In other words, relational selling behavior is aimed at managing the quality of the interpersonal relationship between salespeople and customers and tends to build and maintain strong relationships (Boles et al., 2000; Crosby et al., 1990). Online Crosby et al. (1990) suggested that relationship quality comprises two parts, trust and satisfaction, which are each considered an emotional state that occurs in response to an evaluation of these interaction experiences (Westbrook, 1981) Relationship quality can be defined as a construct composed of several distinct but related facets such as trust, commitment, identification, intimacy, and reciprocity, which reflect overall assessment of strength and depth of relationships between organizations and consumers (De Wulf, Odekerken-Schröder, & Iacobucci, 2001; Fournier, 1998; Palmatier, Dant, Grewal, & Evans, 2006). Based on the literature, Key indicators of relation-ship quality, which is viewed as the most critical outcome of relationship building, are (1) relationship satisfaction, (2) trust, (3) relationship commitment. 374

3 Research Model and Hypotheses Figure 1. Research model and hypotheses. Hypothesis 1: Price Perception has a positive and direct influence on online relationship quality. Hypothesis 2: Order Fulfillment has a positive and direct influence on online relationship quality. Hypothesis 3: Relational Selling Behavior has a positive and direct influence on online relationship quality. Method In this research, the target population for this re-search consists of online vendors clients, who have online purchasing experience. They have more potential to need online purchasing in the future, and are willing to develop long-term relationship with their existing online vendors. To collect the data, a self-administrated questionnaire was developed for student samples. Paper questionnaires were distributed to the student sample in class with the aid of instructors, or in the library or other on-campus facilities by the researcher. Most surveys were collected in online questionnaires. Many researchers have employed online register lists or databases to get the sample for their online consumer surveys (e.g., Anderson & Srinivasan, 2003; Ba & Pavlou, 2002; Evanschitzky et al., 2004; Koufaris et al., 2002). The web questionnaire (the link to the questionnaire) was sent by s or QQ to students. The web questionnaire technology was developed by All the data collected from the web questionnaires were automatically recorded in the background database for further data transformation. The combination of data generated from Web questionnaires and handout questionnaires produced no extreme errors in the estimates, and provided reliable results for most of the variables. Model and Hypotheses Testing The data analysis procedures included seven major steps, from descriptive analysis, preliminary data analysis, to model and hypothesis testing. The main part of data analysis focused on hypothesis testing. A structural equation modeling (SEM) procedure was employed to test these hypotheses. Essentially, SEM may be viewed as a combination of exploratory factor analysis and multiple regression analyses (Ullman, 2001). In contrast to exploratory factor analysis, SEM demands that the (presumably causal) structure of inter variable relations, grounded in theory and/or empirical findings, be specified a priori. The analyses were conducted using AMOS 21, and followed guidelines suggested by Byrne (2001) and Ullman (2001). AMOS was chosen over other 375

4 model fitting programs such as LISREL and EQS, for its unique strength in preventing errors in model specification (Kline, 2005), and its extensive boot-strapping capabilities, which is an effective tool for dealing with non-normal data (Rundle-Thiele, 2005). Table 1. Structural Model Testing Results. Path Hypothesis Estimates T-value Supported Price Perception Online H N Fulfillment Online H * Y Online Relational Selling Behavior Online H *** Y *p <.05 **p <.01 ***p<.001 * Y = supported ;** N = not supported Based on the t-values of the standardized parameter estimates in above tables, a summary of the structural model testing results is shown in Table 1. According to Table 1, the results fully supported Hypothesis 2 and Hypothesis 3. While Hypothesis 1 is not supported. Conclusions Overall, the studies show specific associations between online relationship quality and each of its antecedents, so valuable insights and suggestions on how to improve online relationship quality and ultimately for increasing their customer citizenship behavior will be adopted by the online vendors. This study empirically supported that order fulfillment and online relational selling behavior may be important determinants of online customer relationship quality. As a consequence, in order to strengthen the perception of online relationship quality, online vendors have to give priority to the order fulfillment and online relational selling behavior improvement. In brief, relationship quality has various challenges. It is difficult to use one model to explain all the issues. But it is recommended more examinations of the relationships between customers and online vendors to be performed, better relationship strategies to be formulated and more values to customers to be provided. References [1] Dickson, P. R., & Sawyer, A. G. (1990). The price knowledge and search of supermarket shoppers. The Journal of Marketing, 15(6), [2] Oliver, C. D., & Stephens, E. P. (1977). Reconstruction of a mixed-species forest in central New England. Ecology, 27(7), [3] Stock, J. R., & Boyer, S. L. (2009). Developing a consensus definition of supply chain management: a qualitative study. International Journal of Physical Distribution & Logistics Management, 39(8), [4] Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2001). Atmospheric Qualities of Online Retailing: A Conceptual Online Order Fulfillment and Referrals 291 Model and Implications. Journal of Business Research 34(2),

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