Something Approaching Science?

2003 ◽  
Vol 45 (2) ◽  
pp. 1-19 ◽  
Author(s):  
Agnes Nairn ◽  
Paul Bottomley
Keyword(s):  
Cluster Analysis ◽  
Customer Relationship Management ◽  
Predictive Modelling ◽  
Customer Relationship ◽  
Future Research ◽  
Effective Management ◽  
Validity And Reliability ◽  
Data Set ◽  
Technical Advice ◽  
And Cluster Analysis

The customer relationship management (CRM) industry is set to be worth $76.3 billion by 2005 but over 50% of projects will fail to meet benefit objectives. While CRM nirvana is the attainment of profitable one-to-one relationships, current activity is concentrated on segmentation. As technology has moved segmentation from simple classification towards more complex predictive modelling, the use of CRM analytic suites comprising statistical techniques such as decision trees, neural networks and cluster analysis is increasing. It is suggested that the subjective nature of cluster analysis may be overlooked when the technique is integrated with other ‘tools’ into a data-mining package and, consequently, that inadequately tested cluster analysis solutions may be contributing to CRM dissatisfaction. This paper reports the findings of a study which subjected a data set designed for segmentation purposes to a series of rigorous validity and reliability tests and went as far as to randomise the data to ascertain whether current methods could detect ‘false’ data. The study shows, alarmingly, that under certain conditions random data can ‘pass’ standard tests and highlights just how meticulously and thoroughly cluster analysis solutions must be tested before they can be safely used in formulating marketing strategy. Practical, theoretical and technical advice is offered for managers working with CRM analytics suites and avenues suggested for future research into improved CRM performance through effective management of the IT/marketing interface.

scholarly journals Research status of human resource management in China based on scientific knowledge map

2021 ◽  
Vol 251 ◽  
pp. 03096
Author(s):  
Kun Qian ◽  
Yingxue Li ◽  
Yuenan Lv ◽  
Xiaonan Yang
Keyword(s):  
Cluster Analysis ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Scientific Knowledge ◽  
Visual Analysis ◽  
Future Research ◽  
Knowledge Map ◽  
Management Research ◽  
And Cluster Analysis

In order to accurately grasp the current research frontier of human resource management, according to certain retrieval conditions, 2724 literatures published from 2011 to 2021 were retrieved from CNKI database as data samples. CiteSpace software was used for visual analysis, CO citation analysis and cluster analysis were carried out on these literature data, and the corresponding knowledge map was drawn. The objective of this paper is to show the hot topics and cutting-edge trends of human resource management research in China and draw the current situation of human resource management research in China, in order to provide reference for future research.

scholarly journals Types of professionalization

2018 ◽  
Vol 8 (3) ◽  
pp. 298-316 ◽  
Author(s):  
Grazia Lang ◽  
Torsten Schlesinger ◽  
Markus Lamprecht ◽  
Kaisa Ruoranen ◽  
Christoffer Klenk ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Organizational Development ◽  
Online Survey ◽  
Hierarchical Cluster ◽  
Organizational Characteristics ◽  
Future Research ◽  
Content Type ◽  
Organizational Patterns ◽  
And Performance ◽  
And Cluster Analysis

Purpose The purpose of this paper is to identify types of professionalization in Swiss national sport federations (NSFs) and analyze organizational characteristics associated with specific types of professionalization. Such types reveal common patterns among the increasingly complex organizational designs of NSFs and thus contribute to the understanding of professionalization in NSFs. Design/methodology/approach An online survey of all Swiss NSFs was conducted to identify types of professionalization in these organizations using hierarchical cluster analysis, based on a multi-dimensional framework of professionalization. Findings The analysis revealed four types of professionalization: formalized NSFs managed by paid staff, NSFs managed by volunteers and a few paid staff off the field, NSFs with differing formalization and paid staff on the field, and moderately formalized NSFs managed by volunteers. The types differ in terms of the NSFs’ organizational characteristics, in particular, size, financial resources, Olympic status, and performance. Originality/value Applying factor and cluster analysis is a new approach to analyzing professionalization in NSFs that makes uncovering distinctive organizational patterns among a large number of NSFs possible. These results lay the foundation for understanding the professionalization of NSFs, counseling NSFs on their organizational development, and conducting future research on the design types of sport organizations.

A structured literature review on Big Data for customer relationship management (CRM): toward a future agenda in international marketing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pasquale Del Vecchio ◽  
Gioconda Mele ◽  
Evangelia Siachou ◽  
Gloria Schito
Keyword(s):  
Big Data ◽  
Customer Relationship Management ◽  
Research Agenda ◽  
International Marketing ◽  
Relationship Management ◽  
Customer Relationship ◽  
Future Research ◽  
Content Type ◽  
Future Research Agenda ◽  
Structured Literature Review

PurposeThis paper aims to advance the international marketing debate by presenting the results of a structured literature review (SLR) focusing on Big Data implementation in customer relationship management (CRM) strategizing. It outlines past and present literature and frames a future research agenda.Design/methodology/approachThe research analyzes papers published in journals from 2013 to 2020, deriving significant insights about Big Data applications in CRM. A sample of 48 articles indexed at Scopus was preliminarily submitted for bibliometric analysis. Finally, 46 papers were analyzed with content and a bibliometric analysis to identify areas of thematic specializations.FindingsThe paper presents a conceptual multilevel framework demonstrating areas of specialization emerging from the literature. The framework is built around four coordinated sequences of actions relevant to “why,” “what,” “who” and “how” Big Data is implemented in CRM strategies, thus supporting the conception and implementation of an internationalization marketing strategy.Research limitations/implicationsImplications for the development of the future research agenda on international marketing arise from the comprehension of Big Data in CRM strategy.Originality/valueThe paper provides a comprehensive SLR of the articles dealing with models and processes of Big Data for CRM from an international marketing perspective. Despite these issues' relevance and the increasing literature focused on them, research in this area is still fragmented and underexplored, requiring more systematic and holistic studies.

Applying Fuzzy Logic and Fuzzy Methods to Marketing

2012 ◽  
pp. 1056-1068
Author(s):  
Laurent Donzé ◽  
Andreas Meier
Keyword(s):  
Fuzzy Logic ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Future Research ◽  
Computing With Words ◽  
Linguistic Variables ◽  
Research Directions ◽  
Fuzzy Methods ◽  
Future Research Directions

Marketing deals with identifying and meeting the needs of customers. It is therefore both an art and a science. To bridge the gap between art and science, soft computing, or computing with words, could be an option. This chapter introduces fundamental concepts such as fuzzy sets, fuzzy logic, and computing with linguistic variables and terms. This set of fuzzy methods can be applied in marketing and customer relationship management. In the conclusion, future research directions are given for applying fuzzy logic to marketing and customer relationship management.

Nonuniqueness in traveltime tomography: Ensemble inference and cluster analysis

Geophysics ◽  
1996 ◽  
Vol 61 (4) ◽  
pp. 1209-1227 ◽  
Author(s):  
Don W. Vasco ◽  
John E. Peterson ◽  
Ernest L. Majer
Keyword(s):  
Cluster Analysis ◽  
Conjugate Gradient ◽  
Seismic Inversion ◽  
Low Velocity ◽  
Data Set ◽  
Traveltime Tomography ◽  
All Solutions ◽  
And Cluster Analysis ◽  
Starting Model ◽  
Norm Penalty

We examine the nonlinear aspects of seismic traveltime tomography. This is accomplished by completing an extensive set of conjugate gradient inversions on a parallel virtual machine, with each initiated by a different starting model. The goal is an exploratory analysis of a set of conjugate gradient solutions to the traveltime tomography problem. We find that distinct local minima are generated when prior constraints are imposed on traveltime tomographic inverse problems. Methods from cluster analysis determine the number and location of the isolated solutions to the traveltime tomography problem. We apply the cluster analysis techniques to a cross‐borehole traveltime data set gathered at the Gypsy Pilot Site in Pawnee County, Oklahoma. We find that the 1075 final models, satisfying the traveltime data and a model norm penalty, form up to 61 separate solutions. All solutions appear to contain a central low velocity zone bounded above and below by higher velocity layers. Such a structure agrees with well‐logs, hydrological well tests, and a previous seismic inversion.

Typisierung der Tarifvertragslandschaft / Identifying Types of Flexible Bargaining Agreements Using Cluster Analysis

2007 ◽  
Vol 227 (3) ◽  
Author(s):  
Wolf Dieter Heinbach ◽  
Stefanie Schröpfer
Keyword(s):  
Cluster Analysis ◽  
Collective Bargaining ◽  
Manufacturing Sector ◽  
Data Set ◽  
Different Types ◽  
And Cluster Analysis

SummaryThe introduction of opening clauses in collective wage agreements allowing firms to deviate from their collective bargaining agreements has become widely accepted for the last fifteen years. With respect to the flexibility agreed through collective bargaining, the distinctions between single collective bargaining areas of the same industry have increased. Hence, the economic idea of uniform industry-wide central collective bargaining agreements is no longer tenable. The data set of the IAW used in this article provides differentiated information about opening clauses in collective wage agreements. By means of correspondence and cluster analysis, seven groups of collective bargaining areas are identified, which differ in the type of opening clauses introduced. Over the period from 1991 until 2004, the examination of dynamic aspects of these seven groups exhibits typical paths of development towards an improved flexibility agreed through collective bargaining. Furthermore, the conjunction of the data set with the German Structure of Earnings Survey of the years 1995 and 2001 makes it possible to show the relevance of the different types of single collective bargaining areas for employment and industries of the German manufacturing sector.

The impact of customer knowledge and customer relationship management on service quality

2014 ◽  
Vol 6 (1) ◽  
pp. 77-96 ◽  
Author(s):  
Shu-Mei Tseng ◽  
Pin-Hong Wu
Keyword(s):  
Service Quality ◽  
Customer Relationship Management ◽  
Management Practices ◽  
Relationship Management ◽  
Customer Relationships ◽  
Customer Relationship ◽  
Future Research ◽  
Customer Knowledge ◽  
Content Type ◽  
The Impact

Purpose – Enterprises realize that customers are their most important asset and recognize that a high level of customer satisfaction can only be achieved by enhancing service quality. Thus, how enterprises acquire customer knowledge by which to initiate and maintain customer relationships, as well as to enhance service quality has become an important issue. The paper aims to discuss these issues. Design/methodology/approach – This study uses a questionnaire and statistical analytical techniques to explore the impact of customer knowledge and customer relationship management (CRM) on service quality. Findings – The results indicated that customer knowledge has a positive influence on service quality and CRM is the partial intervening variable between customer knowledge and service quality. That is, customer knowledge enhances the CRM, while CRM, in turn, increases service quality and provides competitive advantages. Research limitations/implications – This research explored the impact of customer knowledge and CRM on service quality based on the company's perception and there was no validation on the customers' perception of the company. Therefore, it is suggested that future research should involve company staff, current customers, and latent customers to strengthen the triangulation. Practical implications – The results found that customer knowledge is indeed an important source of competitive advantage. Hence, enterprises should acquire valuable customer knowledge in order to enhance the relationship with customers, as well as enhance their service quality. Originality/value – There is still little related literature investigating the relationships amongst customer knowledge, CRM, and service quality. Hence, this study applies questionnaire methods as the main research tools in order to conduct an in-depth investigation into the influence of customer knowledge and CRM on service quality. Furthermore, this research is expected to provide enterprises with valuable suggestions for management practices.

scholarly journals How to visualize high-dimensional data: a roadmap

2020 ◽  
Vol Special issue on... ◽  
Author(s):  
Hermann Moisl
Keyword(s):  
Cluster Analysis ◽  
High Dimensional Data ◽  
Latent Structure ◽  
High Dimensional ◽  
Graphical Methods ◽  
Data Set ◽  
The Third ◽  
Historical Text ◽  
International Audience ◽  
And Cluster Analysis

International audience Discovery of the chronological or geographical distribution of collections of historical text can be more reliable when based on multivariate rather than on univariate data because multivariate data provide a more complete description. Where the data are high-dimensional, however, their complexity can defy analysis using traditional philological methods. The first step in dealing with such data is to visualize it using graphical methods in order to identify any latent structure. If found, such structure facilitates formulation of hypotheses which can be tested using a range of mathematical and statistical methods. Where, however, the dimensionality is greater than 3, direct graphical investigation is impossible. The present discussion presents a roadmap of how this obstacle can be overcome, and is in three main parts: the first part presents some fundamental data concepts, the second describes an example corpus and a high-dimensional data set derived from it, and the third outlines two approaches to visualization of that data set: dimensionality reduction and cluster analysis.

The relationship between customer satisfaction and customer relationship management system; a case study of Ghavamin Bank

2014 ◽  
Vol 46 (4) ◽  
pp. 220-227 ◽  
Author(s):  
Alireza Rezghi Rostami ◽  
Changiz Valmohammadi ◽  
Jahan Yousefpoor
Keyword(s):  
Customer Satisfaction ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Capital City ◽  
Validity And Reliability ◽  
Statistical Population ◽  
Content Type ◽  
Crm System ◽  
The Relationship

Purpose – The purpose of this paper is to study the relationship between customer relationship management (CRM) system and customer satisfaction in branches of Ghavamin Bank in the capital city of Iran, Tehran. Design/methodology/approach – Based on the review of literature a questionnaire was designed. After the verification of its validity and reliability, the data were collected from statistical population, the customers of selected branches at Tehran city. The data were analyzed using inferential statistics and the SPSS software, and frequency distribution, distribution indexes, Pearson's correlation, and regression methods were also used. Findings – The results revealed that the four factors of CRM system, i.e. service quality, service characteristics, level of service access, and handling complaints have a positive effect on customer satisfaction in the surveyed branches of Ghavamin Bank. Research limitations/implications – The sample is restricted to only one city, so in generalizability of the obtained results caution should be taken. Originality/value – Given the ever growing importance of banking industry in Iran as a developing country, the results of this study could help policy makers of the surveyed bank to realize the importance of CRM's criteria and characteristics in increasing customer satisfaction.

Ranking e valutazione: il caso delle classifiche delle universitŕ

2009 ◽  
pp. 81-114
Author(s):  
Ferruccio Biolcati Rinaldi ◽  
Daniele Checchi ◽  
Chiara Guglielmetti ◽  
Silvia Salini ◽  
Matteo Turri
Keyword(s):  
Cluster Analysis ◽  
Key Words ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Partial Replication ◽  
Validity And Reliability ◽  
University Ranking ◽  
International Ranking ◽  
Components Analysis ◽  
And Cluster Analysis

- Abstract The paper consists of two parts. The first is more general: it introduces to university ranking, shows the leading international ranking, discusses the uses people make of rankings. The second focuses on Italian ranking Censis-la Repubblica developing two different kinds of analyses: after considering indicators validity and reliability, principal components analysis and cluster analysis are applied to a partial replication of Censis-la Repubblica data. A list of points to pay attention comes out of these analyses: it can be useful when defining rankings of complex institutions such as universities.Key words: ranking, university ranking, Censis-la Repubblica, validity and reliability, normalisation and combination of indicators.

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