نقش تعدیل ریسک و بازده بر رابطه بین عملکرد تدارکات(لجستیک) و وفاداری مشتری در تجارت الکترونیک
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|1389||2010||13 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 9571 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
- تولید محتوا با مقالات ISI برای سایت یا وبلاگ شما
- تولید محتوا با مقالات ISI برای کتاب شما
- تولید محتوا با مقالات ISI برای نشریه یا رسانه شما
پیشنهاد می کنیم کیفیت محتوای سایت خود را با استفاده از منابع علمی، افزایش دهید.
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Transportation Research Part E: Logistics and Transportation Review, Volume 46, Issue 6, November 2010, Pages 950–962
Using data from online customer ratings, we explore how the relationships between logistics performance and customer loyalty are affected by risk characteristics of products and efficiencies of the websites. Risk is defined in terms of price and ambiguity of products. Efficiency is interpreted as the ability of the websites to achieve good ratings in terms of operational factors (such as satisfaction of customers with product specifications, refunds/returns, prices, management accessibility, etc.) and also achieve good ratings in terms of customer loyalty. Our results show that efficiency, but not risk, is a significant moderator of the impact of logistics performance on customer loyalty.
Ability of an organization to attract and retain customers is vital to its success. Customer loyalty requires a strong desire by the customer for a product for which several product vendors are available (Dick and Basu, 1994 and Otim and Grover, 2006). It is often shaped by positive experience by a customer on his purchase. A number of factors contribute to the experience – convenience, availability of the product, delivery, returns policy, etc. Obviously, some of these factors are based on efficient logistics performance of the company. This paper focuses on the relationship between logistics performance and customer loyalty in the context of the business-to-consumer (B2C) segment of electronic commerce. E-commerce has shown impressive growth in the last few years but the rate of growth is slowing down. For example, US e-commerce retail sales have grown (13.6% over the first quarter of 2007) faster than total retail sales (2.8%) for the first quarter of 2008. However, this rate of growth is small compared to the fantastic 51% growth recorded in the first quarter of 2001. It is argued that, with the pricking of the internet bubble, many e-tailers are looking to develop sophisticated strategies to build customer loyalty and sales (Kwak, 2001). Customer loyalty has gained increasing attention in the context of e-commerce in the recent literature (Burt and Sparks, 2003). Several studies have stressed the importance of various operational factors in determining customer retention and loyalty and ultimately the success of firms (e.g., Collier and Bienstock, 2006 and Hsiao, 2009). Some of these studies have focused on the relationship between company performance and logistics performance. Logistics performance has been either studied as a single factor or as a part of a set of operational factors (Karpinski, 1999). E-commerce, especially the B2C segment, is typically characterized by large numbers of small order sizes demanding shipments with a different distribution system compared to the brick-and-mortar business and hence provides larger scope for the role of logistics (Rutner et al., 2003, Bailey and Rabinovich, 2005, Bailey and Rabinovich, 2006, Cho et al., 2008 and Hsiao, 2009). It is believed that e-commerce has provided new opportunities to third-party logistics (3PL) service providers (Kroll, 1999) and that with continued growth of e-commerce, the importance of logistics is set to increase. It has been recognized in the literature that risk characteristics of products could affect the relative importance of logistics and other operational factors (e.g., Finch, 2007). Further, using the resource-based-view of a firm as their theoretical background, a number of previous studies have found that efficiency could act as a moderator affecting the links between resource capabilities (including logistics capabilities) and performance (Nath et al., 2010, Lai, 2004 and Daugherty et al., 2005). Hence, we study the role of risk and efficiency as moderating variables on the relationships between logistics performance and customer loyalty in this paper. Perceived risk plays an important role in shaping consumer behaviour (Hofacker, 2000) and is especially important with online customers (Doolin et al., 2005). Risk is a product-specific variable and varies based on the price and ambiguity of the product (Finch, 2007). Efficiency is a website-specific variable. We define efficiency of websites in terms of their ability to achieve good ratings in terms of operational factors and also in terms of customer loyalty. The paper is organized as follows. A brief literature survey on concepts relevant to this paper is provided in the next section. The conceptual setting of the paper is provided in Section 3, where the moderating roles of risk and efficiency on consumer behaviour are examined. Section 4 discusses data and results of empirical analysis. Detailed discussions of the result of this study are provided in Section 5. Finally, Section 6 provides the conclusions of this study along with limitations and scope for future research.
نتیجه گیری انگلیسی
Our study contributes to the literature on logistics and e-commerce in several ways. While previous literature on the impact of logistics capabilities and firm performance focused mainly in the traditional (non e-commerce) context, our study has investigated the link in a purely e-commerce context. Further, papers that study the moderating role played by risk and efficiency on this link are not many. We have provided these risk and efficiency perspectives in this paper. We have used Finch (2007) to support our risk characterizations, and used the theoretical tenets of RBV logic to argue the moderating role of efficiency. We have categorized websites in terms of the risk characteristics (risk and non-risk) of the products sold through them and calculated efficiencies of websites using DEA. We have used data on ratings by customers of 490 websites. Using moderated regression analysis, we have found that the relationship between logistics performance and customer loyalty is moderated by efficiencies of websites but not moderated by risk characteristics of products sold through them. The results found in the analysis of this paper are similar to several previous studies, and have much managerial significance. Our study has implications for both the managers of websites and also for logistics service providers (LSP). Since efficient e-commerce websites are able to better convert their logistics performance into customer loyalty, managers of e-commerce websites should ensure that goods ordered via their website reaches customers by ensuring high levels of logistics performance. This would necessitate adequate arrangements of various logistics functions (warehousing, order-picking, transportation, etc.) either in-house or outsourced. For logistics service providers, our study provides good scope for their future. By providing efficient service, LSPs can partner in the supply-chain activities of e-commerce websites. Unlike the traditional form of commerce, where LSPs are visible to only companies, e-commerce will make them more visible to the ultimate consumer. We believe that the analysis presented in this paper contributed to the literature by providing risk and efficiency perspectives to existing studies that analysed the relationship between logistics performance and firm performance. However, we also believe that there is scope for further improvement. A limitation of our study is that it considered only on-time delivery as the indicator of logistics performance. While it is a reasonable indicator, more constituents of logistics performance can be considered, including warehousing, order-picking, outsourcing, inventory management, information technology support, reverse logistics, etc. This cannot be done using the secondary data used in this study, but a primary survey can help address these issues.