新形势下中国外汇储备管理新思维初探

中国外汇储备持续快速的增长带来了许多新问题和新挑战,我国外汇储备管理体制必须作出相应调整。改革的关键是要建立外汇储备管理的新思维,要从观念上纠正五个重要的认识误区,并在储备功能分层管理、相关法制建设、运用市场化手段进行资产配置等三个方面推进中国外汇储备综合管理水平的全面提升。     

Euroconsumers?

This study developes a simple, inexpensive technique for segmenting nations on a psychological variable, perceived product value. It successfully applies the mechanism to three European countries, Austria, France and Switzerland. Respondents' perceptions on the value of several base products and their proposed modifications are compared within nation pairs as well as across all three nations. The magnitude in common value perceptions, particularly among product owners, supports the feasibility of this variable as an effective segmentation tool. The results also encourage the development of more uniform marketing strategies when introducing new consumer products cross-nationally.     

Gender Differences in Service Quality Expectations in the Fast Food Industry

Abstract

Services marketers can influence the evaluation of service quality by “managing” customer expectations. Expectations can also provide insights into market segmentation strategies. Gender is often used as a segmentation variable since it is easily identifiable, accessible, and profitable. The purpose of this study was to examine if there are any gender-based differences in the expectations of service quality in the fast food industry. Hypotheses on gender differences in expectations were tested by an ANOVA, where the composite scores of each of the five dimensions of fast food service were used as dependent variables. The expectations of women were significantly higher than men in four of the five dimensions of fast food service quality.     

Assessment of potential retail segmentation variables An approach based on a subjective MCI resource allocation model

The application of a multiplicative competitive interaction (MCI) resource allocation model to assess potential segmentation variables in terms of their capacity to homogenise consumers’ patronage preferences is proposed. The method consists of grouping the potential customers by the variable in question, determining the shopping profile of each resulting segment, and comparing the results to identify insightful relationships between the variable and the shoppers’ retail selection criteria. An empirical test of the procedure in the context of the grocery retail market is subsequently presented and confirms the importance of evaluating easy-measurable demographic and socioeconomic variables as orientative indicators of shopping behaviour.     

Market segmentation strategies for complex automotive products

ABSTRACT

With the advent of ‘big data’, the purpose of this empirical study was to take the opportunity to rethink conventional market segmentation strategies. This is particularly relevant for the automotive industry which is going through a period of rapid change with advanced technologies such as electric powered and autonomous vehicles, creating increased concerns as to how this complexity is communicated effectively.

A mixed methods approach was utilised to collect data from multiple sources, incorporating in-depth discussion groups, semi-structured interviews, an online survey, and data collection of communication processes through the attendance of new car product launches.

The results suggest that marketing departments should rethink their data capture methods to collect more relevant consumer information, not the contemporary trend of needs, attitude, and motivation variables that are difficult to identify and collect, but basic information on their level of familiarity with products through previous experience and exposure. The basic dimensions identified are characterised by a consumer’s expertise, involvement, and familiarity with a product. The findings are synthesised into a theoretical framework to define differing levels of product complexity, which would enable manufacturers to provide more closely defined market segmentation strategies when communicating new product information.     

先进装备制造基地建设中市场战略与技术战略的整合

市场是产业发展的空间,技术是产业发展的基础,离开市场或技术,产业都将无法生存。结合信息时代企业的市场战略特征和技术战略特征,先进装备制造基地的建设应该对市场战略和技术战略进行战略整合,实行一体化创新。     

Income and occupation as explanatory variables: Their power combined vs. separate

This study put a new explanatory variable, relative occupational class income (Y/O), through multivariate analysis in order to test the variable's predictive and marketing segmentation powers. Y/O was tested against income and occupation used separately as explanatory variables. The mid-1960s new-car market was used for the analysis.With respect to the power to predict individual buyer behavior, the new variable did not prove itself to be superior to income and occupation used separately. With respect to market segmentation, however, Y/O often identified more meaningful market segments, where the probability of buyers choosing the new car class involved was obviously much higher (or lower) than was true for the entire market. Whether it would be worthwhile to use the combination variable, Y/O, instead of occupation and income separately as segmentation variables is, nevertheless, a matter of marketing judgment and not of statistical power. It obviously takes time, money, and effort to build a combination variable such as Y/O, and it is often a complex procedure to use and interpret the results from such a variable. In a statistical sense, the difference in power in using Y/O as compared to using occupation and income separately in a multiple regression procedure is trivial. Y/O now needs to be tested as a market segmentation variable on other types of products. Yet, on the basis of the results from this study (and the previous studies involving income versus social class), one wonders if it is not better to use such demographic variables separately as explanatory variables.     

A data mining approach for segmentation-based importance-performance analysis (SOM–BPNN–IPA): a new framework for developing customer retention strategies

Importance-performance analysis (IPA) is a simple but effective means of assisting practitioners in prioritizing service attributes when attempting to enhance service quality and customer satisfaction. The purpose of this study was to demonstrate how IPA can be used with market segmentation to develop customer retention strategies for different market segments. For this purpose, a new framework have been proposed that uses self-organizing maps for customers’ segmentation and back-propagation neural network (BPNN) for implicity drive the importance of service attributes based on their effect on customers’ loyalty in each segment. Then, individual IPA matrixes are developed for each market segment. Also, an example case is presented to demonstrate the implementation and application of the proposed framework. The results of the proposed framework compared with a conventional BPNN-IPA approach indicated that it can increase reliability and applicability of IPA results.     

PERCEIVED RISK AND CONSUMER DECISION MAKING

The home economist has long been interested in effective family and consumer decision making and has tended to take a holistic or macro approach to decision theory. Recently, some applications of normative decision theory to consumer decision making—including the creation of rules for dealing with risk and uncertainty—have been advanced in home management textbooks. Since the early 1960s, consumer behaviour researchers in other disciplines have been developing a behavioural, micro-decision perspective centring upon the presence of perceived risk in the purchase decision of any customer. The empirical literature in home economics does not appear to have dealt with either of these perspectives. This paper identifies perceived risk as a useful analytical variable in the study of consumer product and store decisions and presents empirical data depicting the dual components of perceived risk and its four dimensions. The relationship of the normative and behavioural approaches to decision risk is discussed and implications for future research and application in home economics are identified.     

Segmentation of both reviewers and businesses on social media

Employing online consumer reviews, this research develops a market segmentation procedure that is feasible to businesses present on social media. Because online reviews typically encompass large numbers of both reviewers and businesses, this data structure allows for both reviewer segmentation and business segmentation. This two-side segmentation approach segments not only reviewers in the preferences expressed in their reviews, but also businesses in their business practices specified in the reviews. Whereas common existing segmentation approaches predominantly use survey and transaction data, the proposed procedure uses publicly available and detailed consumption information in such reviews. A large number of product features elicited from such reviews lead to rich and detailed profiling of both reviewer segments and business segments. Using restaurant reviews on Yelp, this research demonstrates how the proposed procedure can help businesses develop segmentation strategies on social media.     

Applications of the behavioural homogeneity evaluation framework: The predictive ability of consumer involvement for international food market segmentation

Abstract

This article proposes a framework of alternative international marketing strategies, based on the evaluation of intra- and inter-cultural behavioural homogeneity for market segmentation. The framework developed in this study provides a generic structure to behavioural homogeneity, proposing consumer involvement as a construct with unique predictive ability for international marketing strategy decisions. A model-based segmentation process, using structural equation models, is implemented to illustrate the application of the framework.     

Segmenting the Urban Economic Development Market:

Local government economic development strategies have been widely criticized for being ineffective and for lacking coherent, logical form. Of particular concern is the tendency of government to use a mass market, undifferentiated approach to potential business growth. Here, implications of creating and applying a market segmentation strategy to economic development is explored. Based on standard industrial classification schema and business growth orientation, a sample of businesses from a middle size mid-western city was segmented and responses to an economic development- oriented questionnaire were examined using stepwise discriminant analysis. Results showed that this market segmentation strategy differentiated significant variations in needs for assistance by both industrial type and growth orientation within type. Results are discussed in regard to the significance of market segmentation to effective public economic development policy.     

A Preliminary Study of Fintech Industry: A Two-Stage Clustering Analysis for Customer Segmentation in the B2B Setting

ABSTRACT

This practitioner note proposes a new approach considering two-stage clustering and LRFMP model (Length, Recency, Frequency, Monetary and Periodicity) simultaneously for customer segmentation and behavior analysis and applies it among the Iranian Fintech companies. In this practitioner note, the K-means clustering algorithm and LRFMP model are combined in the customer segmentation process. After initial clustering, for a better understanding of valuable customers, additional clustering is implemented in segments that needed further investigation. This approach contributes to a better interpretation of different customer segments. Customer segments, consisting of 23524 business customers are analysed based on their characteristics and appropriate strategies are recommended accordingly. The first stage clustering result shows that customers are best segmented into four groups. The first and fourth segments are clustered again and the final 11 groups of customers are determined. This note provides a systematic and practical approach for researchers and practitioners for segmentation, interpretation, and targeting of customers especially in the B2B setting and the Fintech industry and helps managers to make effective marketing strategies and enhance customer relationship and marketing intelligence.     

International Market Segmentation and Cross-Export Strategies Development Case Study: Iranian Furniture Industry

ABSTRACT

By developing an international market and significant differences between countries in this regard, segmentation becomes an increasingly important concept in marketing. In this article, the international market of Iranian furniture industry is segmented and cross-exporting strategies are developed to increase the market share of Iranian furniture in each segment. To achieve this, two distance functions are introduced based on correlation between export groups to cluster countries with k-means algorithm. After market segmentation for increasing sales in each segment, cross-exporting strategies are predicted by extracting association rules in each segment based on Apriori algorithm to set export baskets.     

Service Quality in Public Services as a Segmentation Variable

The application of perceived service quality to marketing segmentation makes a significant contribution to customer quality expectations by enabling more efficient segmentation. By means of an empirical analysis, the present work firstly contrasts the validity of perceived service quality measurements in public services. It goes on to analyse the usefulness of this concept as a segmentation criterion. Finally, customer segments are identified as a function of perceived quality and profiles are established for each segment. This study proves that service quality is a useful tool for segmentation in public services.     

Geodemographic and socioeconomic characterization of the retail attraction of leading hypermarket chains in Spain

This paper aims at examining the impact on demand of the competitive positioning strategies developed by the leading hypermarket chains in Spain. Specifically, the purpose is to carry out a geodemographic and socieconomic characterization of the potential consumers of each chain. As retail attraction has traditionally been divided into three components, distance, mass and image, a gravitational model is proposed which distinguishes them and facilitates the evaluation of existing differences across any a priori segmentation base. The empirical test identifies significant geodemographic differences in the retail attraction of hypermarket chains. Chains seem to target the whole market by developing an image balanced against the advantages and disadvantages derived from the spatial coverage strategy. Social class is not as good an indicator of hypermarket choice as expected, although some interesting patterns have been detected.