Performance comparison based on customer relationship management using analytic network process

Customer relationship management (CRM) is a multi-perspective business paradigm which aims maximizing the benefits gained from relationships with customers. The aim of this paper is to compare the CRM performances of e-commerce firms using a multiple criteria decision making (MCDM) approach. Analytical network process (ANP) is a MCDM methodology which can take the inner and outer dependencies among multiple criteria into consideration. As there are dependencies among CRM performance evaluation criteria, ANP is used for comparing the CRM performances of the e-commerce firms under consideration. A sensitivity analysis also provided in order to monitor the robustness of the proposed ANP framework to changes in the weights of evaluation criteria. To the authors’ knowledge, this will be the first study which evaluates CRM performance using ANP.     

一个基于SLA的NGN定价KSS实现机制研究

提出了一个下一代网络（NGN）定价知识支撑系统（KSS）构架,通过采集和分析SLA决策、SLA检测和评估过程数据,确定ISP运营环境中的网络、市场和政策关键性能指标（KPI）,通过对KPI的分析,定义网络、市场和政策关键定量指标（KQI）,基于KQI的评估,定义利润和进行价格影响预测。开发了一个KSS的基于XML的SOA实现构架,在基于SLA的NGOSS原型系统平台上进行了仿真实验,并和获得IST奖的ITDSS/TelPrice进行了比较,实验结果很好验证了它的优点。     

Intelligent customer complaint handling utilising principal component and data envelopment analysis (PDA)

In this study, we consider customer to be a company's crucial asset. In order to have a fast, efficient decision-making process, it is vital that a customer relationship management (CRM) decision-maker condenses and abstracts the existing information. A questionnaire survey was conducted among respondents in order to obtain the required data. The questionnaire contains nine categories of satisfaction variables. To perform the analysis, we used principal component analysis (PCA) and data envelopment analysis (DEA). PDA has been utilised as an abbreviation for the integration of these two methods. To effectively analyse the procedure, PCA was utilised to assign a number to each category of questions related to each satisfaction variable. To achieve optimal precision, DEA was applied to the three categories of customers (‘most important’, ‘important’ and ‘ordinary’ customers) in order to determine the strengths and weaknesses of customer services from these customers’ perspectives. Customers were clustered and then DEA was used to determine their viewpoints. Using DEA, we have optimised our recognition of customers’ complaints and then provided recommendations and remedial actions to resolve the current issues in logistics and transport industry in general, and at Fremantle port in particular.SignificanceThe current study integrates soft computing and optimisation technique in order to build the CRM recommender system. It demonstrates the hybrid soft computing strengthens in area of CRM as the relevance solution. The significance of the proposed algorithm is three fold. First, it integrates soft computing and optimisation technique in order to build the CRM recommender system. Second, it utilises the most standard CRM variables in its decision making process. Third, it is an optimising algorithm because it integrates DEA with PCA technique.     

Determination of the effectiveness of the realization of enterprise business objectives and improvement strategies in an uncertain environment

This study determines the effectiveness of business objectives and key performance indicators (KPIs) of the identified business objectives for different types of enterprise. The evaluations of the relative importance of KPIs are called a fuzzy group‐decision‐making problem. The KPI weights are determined using the fuzzy analytic hierarchical process. The effectiveness of business objectives and KPIs is determined using the adopted Balanced Scorecard Designer Pro. Determination of the KPI rank with respect to each enterprise type is on the basis of Pareto analysis. The priority of management initiatives of the improvement strategy corresponds to the calculated rank, and it has a critical effect on the competitive advantage of any enterprise. The results discuss manufacturing, public and service enterprises, which exist in central Serbia. The proposed approach can also be adapted to different businesses.     

Ranking manufacturing processes from the quality management perspective in the automotive industry

The aim of this study is to propose a fuzzy decision‐making model to rank manufacturing processes from the quality management perspective in the automotive industry. This paper proposes a model for improving quality management through the assessment and ranking of manufacturing subprocesses with respect to key performance indicators (KPIs). The developed model, supported with the fuzzy extended ELECTRE III, allows for the determination of subprocesses' rank. An illustrative example indicates that the proposed model could be very useful in everyday business operations as total quality management asset. The model can handle all uncertain and vague input data by applying the theory of fuzzy sets. The research also suggests different managerial implications because it provides an adequate tool for overall quality improvement. The number of treated KPIs is relatively high, so ELECTRE III method gives an advantage over other multicriteria analysis methods because it embraces less subjective thinking and demands slightly less experts' knowledge during the process of decision making and assessment.     

MIKADO: a smart city KPIs assessment modeling framework

Smart decision making plays a central role for smart city governance. It exploits data analytics approaches applied to collected data, for supporting smart cities stakeholders in understanding and effectively managing a smart city. Smart governance is performed through the management of key performance indicators (KPIs), reflecting the degree of smartness and sustainability of smart cities. Even though KPIs are gaining relevance, e.g., at European level, the existing tools for their calculation are still limited. They mainly consist in dashboards and online spreadsheets that are rigid, thus making the KPIs evolution and customization a tedious and error-prone process. In this paper, we exploit model-driven engineering (MDE) techniques, through metamodel-based domain-specific languages (DSLs), to build a framework called MIKADO for the automatic assessment of KPIs over smart cities. In particular, the approach provides support for both: (i) domain experts, by the definition of a textual DSL for an intuitive KPIs modeling process and (ii) smart cities stakeholders, by the definition of graphical editors for smart cities modeling. Moreover, dynamic dashboards are generated to support an intuitive visualization and interpretation of the KPIs assessed by our KPIs evaluation engine. We provide evaluation results by showing a demonstration case as well as studying the scalability of the KPIs evaluation engine and the general usability of the approach with encouraging results. Moreover, the approach is open and extensible to further manage comparison among smart cities, simulations, and KPIs interrelations.

     

Integrating simulation modelling and multi criteria decision making for customer focused scheduling in job shops

Today, customer centricity is an important strategy in business-to-business markets and manufacturing companies need decision support systems that provide adequate information for customer centric applications. This study proposes an integrated decision support system that combines simulation modelling and multi-criteria decision making. More specifically, job shop lot streaming problem is dealt with, and it is aimed to determine the best dispatching rules to schedule batches on machines. To this aim, three renowned performance-oriented criteria; (i) mean flow time, (ii) percentage of tardy orders, (iii) makespan and one customer-oriented criterion; (iv) mean percentage deviation from the customer expectations are considered. Effect of different classical and customer-oriented dispatching rules on these performance criteria are investigated. The performance criteria are weighted using analytical hierarchy process by considering the level of bottleneck resource utilization and customer importance weights. The results reveal that customer-oriented dispatching rules provide better outcomes in case of high level of bottleneck resource utilization and high fluctuation amongst the customer importance weights.     

Examining business value of customer relationship management systems: IT usage and two-stage model perspectives

Empirical evidence for the business value of customer relationship management (CRM) systems remains unsolid in IS studies. This study proposes a new model for CRM value according to IT/IS usage theory and “two-stage model.” Empirical tests show that operational benefits of CRM are reflected in firms’ high revenue per employee, which leads to high profitability; strategic benefits of CRM are reflected in firms’ high customer satisfaction, which leads to high profitability and market valuation. Firm size positively moderates the operational and strategic benefits of CRM, while the industry’s product differentiation level negatively moderates operational and strategic benefits of CRM.     

Computer selection and criteria for computer performance evaluation

Computer evaluation, comparison, and selection is essentially a decision process. The decision making is based on a number of worth indicators, including various computer performance indicators. The performance indicators are obtained through the computer performance measurement procedure. Consequently, in this environment the measurement procedure should be completely conditioned by the decision process. This paper investigates various aspects of the computer performance measurement and evaluation procedure within the context of the computer evaluation, comparison, and selection process based on the Logic Scoring of Preference method. A set of elementary criteria for performance evaluation is proposed and the corresponding set of performance indicators is defined. The necessary performance measurements are based on a standardized set of synthetic benchmark programs and include three separate measurements: monoprogramming performance measurement, multiprogramming performance measurement, and multiprogramming efficiency measurement. Using the proposed elementary criteria, the measured performance indicators can be transformed into elementary preferences and then aggregated with other nonperformance elementary preferences obtained through the evaluation process. The applicability of presented elementary criteria is illustrated by numerical examples.     

酒店客户关系管理系统中客户获取的研究

客户获取是酒店行业决策支持的一个重要方面,也是客户关系管理的核心任务之一。本文分析传统酒店行业计算机管理系统的弊端,针对其客户获取的局限性,提出对现有客户和潜在客户同时建模并进行分析的客户获取解决方案,研究建立酒店数据仓库、现有客户模型、潜在客户模型等关键技术,实现客户获取,为酒店行业提供更为准确的决策支持。     

基于关系图提取算法的烟草销售客户关系管理的应用研究

展望客户关系管理,数据挖掘技术在其中起到了至关重要的作用,它可以挖掘出千万数据中的有用信息,企业才能对客户进行各类价值分类,然后预测客户的行为,从而做出正确有效的决策。在CRM应用中,基于数据挖掘技术的基础上,结合CRM系统的不足,为避免或减少客户管理系统因管理不到位而导致客户的流失,造成企业的损失,提出了客户关系图的提取算法,很好地分析了数据挖掘技术在CRM中的应用。     

A group decision making support system in logistics and supply chain management

PurposeThe paper proposes a decision support system for selecting logistics providers based on the quality function deployment (QFD) and the technique for order preference by the similarity to ideal solution (TOPSIS) for agricultural supply chain in France. The research provides a platform for group decision making to facilitate decision process and check the consistency of the outcomes.MethodologyThe proposed model looks at the decision problem from two points of view considering both technical and customer perspectives. The main customer criteria are confidence in a safe and durable product, emission of pollutants and hazardous materials, social responsibility, etc. The main technical factors are financial stability, quality, delivery condition, services, etc. based on the literature review. The second stage in the adopted methodology is the combination of quality function deployment and the technique for order preference by similarity to ideal solution to effectively analyze the decision problem. In final section we structure a group decision system called GRoUp System (GRUS) which has been developed by Institut de Recherche en Informatique de Toulouse (IRIT) in the Toulouse University.ResultsThis paper designs a group decision making system to interface decision makers and customer values in order to aid agricultural partners and investors in the selection of third party logistic providers. Moreover, we have figured out a decision support system under fuzzy linguistic variables is able to assist agricultural parties in uncertain situations. This integrated and efficient decision support system enhances quality and reliability of the decision making.Novelty/OriginalityThe novelty of this paper is reflected by several items. The integration of group multi-criteria decision tools enables decision makers to obtain a comprehensive understanding of customer needs and technical requirements of the logistic process. In addition, this investigation is carried out under a European commission project called Risk and Uncertain Conditions for Agriculture Production Systems (RUC-APS) which models risk reduction and elimination from the agricultural supply chain. Ultimately, we have implemented the decision support tool to select the best logistic provider among France logistics and transportation companies.     

A large group linguistic Z-DEMATEL approach for identifying key performance indicators in hospital performance management

In hospital management, performance measurement is of vital importance for improving healthcare service quality. The performance of a healthcare organization is often influenced by numerous indicators, and it is unrealistic to manage them all due to the restriction of resources. In addition, the performance measurement for improvement relates to the benefits of many departments, and it is necessary for large number of experts with different backgrounds to participate in the evaluation process of healthcare indicators. In response, this study develops a large group evaluation approach using linguistic Z-numbers and decision-making trial and evaluation laboratory (DEMATEL) to determine key performance indicators (KPIs) for hospital management. For this approach, the complex and uncertain interrelation evaluations among indicators are given by experts using linguistic Z-numbers. An extended DEMATEL method is proposed to determine KPIs based on the cause and effect relationships of performance indicators. Finally, a case study in a rehabilitation hospital is presented to illustrate the effectiveness and usefulness of the proposed large group linguistic Z-DEMATEL approach. The results indicate that incidents/errors, accidents/adverse events, nosocomial infection, nursing technology pass rate, and length of stay are KPIs for the given application.     

Identifying IT sustainability performance drivers: Instrument development and validation

IT firms vary in their performance to improve the environmental sustainability of their own operations and in their ability to provide products and solutions that enable and transform the environmental sustainability of other industries. In the parlance of the balanced scorecard, performance has two dimensions, that is, “drivers” and “outcomes”. The drivers, also known as leading performance indicators, refer to learning and innovation, processes, and customer value propositions. The outcomes, also known as lagging performance indicators, refer to financial results. This study has developed and validated an instrument to measure the environmentally sustainable IT performance (eSITP) drivers. We established the nomological network of the eSITP by drawing from several theoretical domains in the areas of innovation antecedents and values, balanced performance measurement and IT and eco-sustainability. Based on a survey of 133 IT firms, we developed and validated a four-dimension, 17 items eSITP instrument covering eco-learning, eco-process, eco-brand and eco-value governance. The instrument is validated by following a seven step rigorous process. The paper breaks new ground from both research and practice perspectives. The instrument makes it easier for other researchers who wish to explain the leading (drivers) and lagging (outcomes) of IT firms’ environmental sustainability and for IT business managers who want to improve their environmental sustainability performance.     

An Integrated Model for Customer Relationship Management: An Analysis and Empirical Study

Ensuring customer satisfaction and maintaining long‐term relationships with customers have become essential for survival among competitive service industries. The present study addresses this need by proposing a conceptually integrated four‐phase model that incorporates elements of customer relationship management (CRM) and customer satisfaction (represented by the extended American Customer Satisfaction Index model). Then, this study formulates structural equation modeling to test various research hypotheses related to the effect of the CRM initiative. An empirical study of 143 leading Taiwanese service firms distributed among seven service industries was conducted. The implementation levels of various constructs, input (customer knowledge), service provision (customer interactions), output quality, perceived quality, perceived value, perception of customer satisfaction, customer loyalty, purchasing intention, and profits of CRM are assessed in a range of service industries by means of a questionnaire survey and in‐depth interviews. The results of the empirical study reveal statistically significant influences among various constructs of the CRM integrated model. These results also represent a useful reference for managers of service organizations that could be used to improve the profitability and implementation level of CRM. The present study represents an important investigation in the development of an integrated CRM implementation system for service industries. © 2012 Wiley Periodicals, Inc.     

Fostering Creativity in New Product Development through Entrepreneurial Decision Making

Research has emphasized the importance of employees' individual entrepreneurial decision making for innovation. In this context, practised creativity as the ability to perceive and exploit creative opportunities, can be regarded as a crucial requirement for employees in new product development. We discuss the application of decision making logic as an important antecedent of practised creativity in new product development. We survey 219 employees from new product development departments of German product and service firms. Results indicate that the use of entrepreneurial decision making logic positively impacts practised creativity; comparably we find indicators that the use of causal decision making logic negatively influences creativity. The effects significantly depend on the moderating role of uncertainty. The results contribute to the literature of creativity, entrepreneurship and new product development by theoretically and empirically revealing effectuation as antecedent to practised creativity. The results open promising avenues for future research and allow the derivation of valuable guidelines for practitioners. Aligning the new product development process to support employees' entrepreneurial decision making may help generating practised creativity.     

The priority factor model for customer relationship management system success

As the market competition becomes keen, constructing a customer relationship management system is coming to the front for winning over new customers, developing service and products for customer satisfaction and retaining existing customers. However, decisions for CRM implementation have been hampered by inconsistency between information technology and marketing strategies, and the lack of conceptual bases necessary to develop the success measures. Using a structural equation analysis, this study explores the CRM system success model that consists of CRM initiatives: process fit, customer information quality, and system support; intrinsic success: efficiency and customer satisfaction; and extrinsic success: profitability. These constructs underlie much of the existing literature on information system success and customer satisfaction perspectives. We found the empirical support for CRM implementation decision-making from 253 respondents of 14 companies which have implemented the CRM system. These findings should be of great interest to both researchers and practitioners.     

基于数据挖掘的CRM分析

进行客户关系管理系统建设,是企业争取竞争优势的重要手段,数据挖掘技术在CRM的实施中起着关键的作用。文章介绍了数据挖掘技术和CRM技术,具体介绍了在酒店CRM建设中用到的决策树和模糊聚类这两种数据挖掘的实现方法,并做出了实验分析。     

数据挖掘技术在民航CRM中的应用

进行客户关系管理系统建设,是当今各大航空公司争取竞争优势的重要手段。数据挖掘技术在CRM的实施中起着关键的作用。文章分别介绍了数据挖掘技术和CRM技术,具体介绍了在民航CRM建设中用到的决策树方法和模糊聚类方法这两种数据挖掘方法,并作了实验分析。最后对数据挖掘技术在民航中的应用作了展望。