شیوه های تجزیه و تحلیل سبد سرمایه گذاری به مشتری در زمینه های مختلف ارز
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|23774||2007||11 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Business Research, Volume 60, Issue 7, July 2007, Pages 720–730
Customer relationship management is increasingly important in current marketing research and practice. The customer portfolio models represent one of the few concrete tools proposed for relationship management in business-to-business markets. Yet, knowledge of how companies use customer portfolio analysis (CPA) remains limited. Earlier research adopts a fairly narrow view of CPA and ignores the influence of internal and external company context on portfolio analysis application. This article presents a broad definition of customer portfolio analysis and offers insights into companies' CPA practices in different exchange contexts. The study reports findings from an explorative multiple case study that investigates analysis practices in different exchange contexts. The results lend support to the proposition that CPA is a variable and context dependent activity. The complexity of the exchange context has an effect on the form, content and implications of customer portfolio analysis. The study highlights a number of unexplored questions to encourage further research on portfolio analysis and its performance.
Over the past decade customer relationship management (CRM) has emerged as an important domain of both marketing research and practice. Supported by the developments of information and communication technology and the network economy, CRM has even come to replace the concept of relationship marketing (cf. Boulding et al., 2005 and Payne and Frow, 2005), or – according to a more careful interpretation – appeared as the dominant label for relationship marketing applications (Gummesson, 2004). Furthermore, in business markets, customer relationship management has long been recognized as a key to competitive success particularly in increasingly networked, global and dynamic business environments (e.g., Campbell and Cunningham, 1983, Krapfel et al., 1991 and Möller and Halinen, 1999). Four interrelated levels of customer relationship management have been delineated: networks, nets, portfolios and individual relationships (Möller and Halinen, 1999 and Möller et al., 2005). Over the past 30 years most of the concrete, customer management tools proposals are made at the customer portfolio level. Along with the recent CRM boom, customer portfolio management has become of interest again. That has resulted in a number of authors arguing that in order to manage company growth, profitability, and shareholder value, the focus should move from the few closest relationships to a broader managerial perspective that takes into account the firm's entire customer portfolio (Dhar and Glazer, 2003 and Johnson and Selnes, 2005). The research on portfolio analysis and management to date concentrates on two major issues: proposing formal, mainly matrix-form, portfolio models for customer management tasks (e.g., Cunningham and Homse, 1982, Dhar and Glazer, 2003, Fiocca, 1982, Hartley, 1976, Krapfel et al., 1991 and Zolkiewski and Turnbull, 2002); and, testing theoretically driven models with data from case companies at one point in time (Eng, 2004, Storbacka, 1997, Zolkiewski and Turnbull, 2002 and Yorke and Droussiotis, 1994). At the same time, the very few empirical studies show that strictly formal, matrix-form customer portfolio analysis is relatively rare in business, even though companies tend to analyze and manage their customer bases systematically (Leek et al., 2002 and Räsänen, 1999). A number of researchers also criticize customer portfolio models as offering an excessively simplified view of reality and overlooking, in particular, the network effects, that is, the interconnectedness of business actors (Dubois and Pedersen, 2002 and Ritter, 2000). In sum, existing research provides contradictory views of the value of customer portfolio analysis for companies. These contradictions relate to three major factors. First, academic research on customer portfolio analysis unnecessarily focuses on formal, matrix-form models. The long history of portfolio models in finance (Markowitz, 1952) or in varied areas of marketing (e.g., product, strategic planning, and internationalization — see e.g. Kahane, 1977 and Mahajan et al., 1982), indicates that portfolio analysis is a variable practice where several methods, not only matrixes, are in employment. A number of recent studies on customer relationship portfolios also support this view (Freytag and Mols, 2001, Johnson and Selnes, 2004 and Ryals, 2003). Secondly, research to date is one-sided in a methodological sense. The testing of theoretical portfolio models with case company data has not been able to provide knowledge about the actual use of customer portfolio analysis, nor about its performance for the company in the long-term. Up to this point, only a few studies have focused on the companies' actual practice of customer portfolio analysis (Leek et al., 2002, Räsänen, 1999 and Salle et al., 2000). Hence, the emphasis in research should shift from testing separate theoretical models to studying companies' portfolio practices and their performance. A third important notion is that researchers study customer portfolio analysis without examining the context of its application. Many authors propose that relationship marketing and relationship management are context dependent activities (e.g., Blois, 1996, Brodie et al., 1997, Coviello et al., 2002, Grönroos, 1994, Li and Nicholls, 2000 and Möller and Halinen, 1999). In addition, some researchers emphasize that the tailoring of portfolio analysis to a firms' needs and circumstances is essential to its performance (e.g., Salle et al., 2000, 434; Wind and Mahajan, 1981, 165). The complexity of a focal firm's exchange context is thus likely to affect the application of customer portfolio analysis, and therefore, customer portfolio analysis should be studied according to the internal and external context of its use. The influence of context is clearly an aspect that is missing in current studies that test theoretical portfolio models and their performance. The purpose of this research is to broaden the current understanding of companies' customer portfolio analysis (CPA) practices in different business-to-business contexts. As empirical research about customer portfolio analysis is scarce, the study adopts a qualitative, explorative research approach. An explorative, multiple case study was conducted to see how the exchange context potentially affects companies' CPA practices. The study provides preliminary empirical evidence of the assumed connection between the complexity of exchange context and the qualities of CPA practice. The article is organized as follows. The first section defines customer portfolio analysis and discusses the central characteristics of CPA practice on the basis of existing literature. The question of the context dependent nature of CPA is also addressed. The second section analyzes the complexity of exchange context and identifies its key dimensions. The third section describes the case methodology and the choice of cases and the fourth presents the results of the empirical research. By comparing cases from different exchange contexts the study is able to show interesting differences in the key characteristics of customer portfolio analysis practice. The article ends with a discussion of the limitations of the study's subject and implications for further research and practice.
نتیجه گیری انگلیسی
Customer portfolio analysis is a highly topical business issue. However, only limited and fragmented knowledge about firms' actual customer portfolio analysis practices exist. This study empirically examined customer portfolio analysis practices in seven case companies concentrating especially on the exchange context's effect on CPA practices. For this purpose, the concept of exchange context complexity was proposed to refer to the general complexity of the exchange a firm has with its customers. Key dimensions of this complexity were distinguished and applied in case analysis. As to portfolio analysis practice, five key characteristics related to its form, content and implications were identified and studied in the case companies. Several important conclusions can be drawn from the empirical findings. First of all, the results indicate that customer portfolio analysis is a much broader issue in practice than suggested by the formal, theoretical customer portfolio models presented in literature. Customer portfolio analysis is closely linked to other customer relationship management tools companies use and even to market segmentation. The social and informal side of the analysis praxis proved at least as important as the formal outcome of the analysis, the portfolio itself. Managers' and boundary personnel's interpretations of the individual customer relationships as well as exchange context form an essential part of the customer portfolio analysis. Secondly, the data of firms' actual customer portfolio analysis practices demonstrate significant heterogeneity in analysis praxis. The formality of the analysis and its focus on either customer groups or individual customer relationships varies notably between the cases. There are also remarkable differences in the analysis dimensions used, the type of implications sought and in the way the analysis is implemented in the organization. Thirdly, the empirical findings show, supporting earlier propositions, that customer portfolio analysis use is context dependent. According to the results, the more formal customer portfolio practices are used in exchange contexts of low and medium complexity. This is because the firms acting in the less complex exchange contexts often have a large customer base consisting of a variety of different customer relationships which need to be managed in a cost-efficient way. When the contextual complexity grows and the relationships between customers and the focal company become more intensive and interdependent, the individual aspects of analysis become more pronounced and the analysis more informal. Moreover, in the high exchange context complexity situations, relationship management at the customer portfolio level is not very relevant at all. The results indicate, instead, that the analysis and management of the customer base occurs on the basis of individual relationships. In complex exchange contexts, a deeper understanding of relationships is obviously needed. Relationship development plans become emphasized as implications of CPA and the steering effect of the analysis remains loose. To sum up, the central characteristics of customer portfolio analysis practice were found to vary notably in different exchange contexts. The study provides several implications for managers. Because of the context dependency of customer portfolio analysis a portfolio analysis is likely to work best if adjusted to the central contingencies of the company’s exchange context, rather than using a standardized solution. When considering the use and implementation of CPA, the existing customer base – its breadth and heterogeneity – needs to be taken as a starting point for the building up of the proper means for customer relationship management. For instance, formal customer portfolio analysis is not necessarily reasonable for companies that operate in highly complex exchange contexts, with a limited number of customers. Instead relationships can be managed on a more individual basis. The study also reveals some company internal factors that are central to the successful implementation of customer portfolio analysis and thus require managers' attention. These are related roughly speaking to technical aspects such as the quality of available customer data and the level of customer management technology, but also to social and organizational level issues such as the managers' commitment to customer relationship management. Furthermore, customer contact personnel have a key role in successful implementation. Naturally, as the empirical cases are relatively few the results of the study should be considered preliminary. It is important to note that the cases represent only big companies and discover fairly formal portfolio practices leaving the most informal practices most likely unrevealed. In an explorative case study, generalizations should be made with care. However, the analytical generalization where the results are generalized to theoretical propositions instead of populations or universes (Yin, 2003, 37) is feasible. The cases represent a theoretical sample, where the differences between the studied firms support the theoretical argumentation. By combining conceptual analysis based on a literature review and empirical analysis based on case comparisons, new knowledge was created about companies' customer portfolio analysis practices. Based on the results of this study several avenues for future research can be proposed. The study focused on companies' CPA practices at one point in time. The interviews, however, indicate that these practices are ongoing, long-term processes developed over time. Future research should take proper care of the evolving nature of portfolio analysis and the learning that occurs in this process. Overall, more research is needed about firms' actual customer portfolio analysis practices. The performance of customer portfolio analysis would in particular be of great interest and highly relevant from the managerial point of view. An important research question would be, whether customer portfolio analysis efforts lead to better business performance? This study addressed the heterogeneity of firms' customer portfolio analysis practices and its context dependency. An obvious question to be posed in future research is whether the different kinds of customer portfolio analysis perform better in different exchange contexts. In order to make a contingency analysis, the concept of exchange context complexity needs further elaboration and validated scales for its measurement. Quantitative research is necessary in the future to provide answers to these questions.