Customer loyalty programs to sustain consumer fidelity in mobile telecommunication market

Companies realized the importance of well-managing their relationships with their customers. Customer Relationship Management (CRM) allows companies to manage their marketing strategies and deliver specific services to clients with different values. The mobile telecommunication market is a very competitive market where the customers are tended to move from one company to another easily. Mobile telecommunication companies should carry on specific programs and services to their customers in order to keep them satisfied and thus ensure their fidelity with the company. In this article our objective is to provide companies a model that facilitates to decide what kind of customer loyalty programs they should address to their clients from different segments. In order to do that we present a fuzzy based Hungarian method that allow assigning different loyalty programs to customers with different characteristics.     

Enhancing customer relationships by semantic consumer support systems

For enterprises to succeed in their business, customer relationships have been commonly recognized as a critical factor. Effective customer relationships help enterprises deliver services to customers based on their needs or preferences. In this context, many ideas have already been presented among which Consumer Support Systems (CSS) is the most recently introduced, and one that alleviates the shortcomings of other approaches by a 4-layer framework of collaborative mechanisms to support effective information/service provision between customers and enterprises. Since there are many integration issues to be addressed in CSS (e.g., sharing of information/requests among customers or comparison of services from enterprises), a comprehensive structure for easy sharing/comparison of this information/requests/services in the literature is therefore necessary. To meet this need, we present a specification method in this paper that takes advantage of the pristine structure for knowledge-sharing by ontology to specify these materials in respective ontologies. With such ontological semantics, CSS is particularly able to support dynamic service provision for customers where desired requests can be satisfied by suitable services in a dynamic manner through referencing any matches between request and service ontologies. The method is illustrated by a semantic CSS for travel arrangements and more discussions about the application of its constructed ontologies for enhancing customer relationships are also provided.     

数据挖掘技术在客户关系管理（CRM）中的应用及具体实现策略

人们普遍认识到,各种规模的企业需要学习效仿那些小型的、以服务为导向的商业模式,总是能做好建立一对一的客户关系。客户关系管理是广泛出现在很多书籍和会议上的议题。从铅跟踪软件到广告系列管理软件,再到呼叫中心软件。如今,在销售中一切都作为顾客关系管理工具。通过提高公司的能力和我们的顾客形成学习关系,数据挖掘可以在提升顾客关系管理。每一个行业中,高瞻远瞩的公司正在试图走向一对一的理解每一个客户,运用那种了解以方便客户做生意,而不是一个竞争者。同样,这些公司正在学习看终身价值的每一个客户,这样他们就能知道有哪些值得投资金钱和精力来坚持,哪些让下降。从大市场分割到个体消费者,这一关注的转变需要公司的改变,更重要的莫过于市场营销,销售和顾客的支持。     

Exploring consumer adoption of new services by analyzing the behavior of 3G subscribers: An empirical case study

As the profit margins of 3G mobile network operators gradually decline, and market competition becomes increasingly intensive, they must develop rich and diverse varieties of brand new application services to attract new subscribers and retain old ones. Understanding the customer’s purchasing behavior is a key issue in this process. The operator must accurately grasp movements in the market based on analysis of the behavior of 3G subscribers. This study proposes a comprehensive customer relationship management strategy framework to furnish a beneficial plan to overcome such challenges. First, we propose a new model to identify who are the high-value customers related to the characteristics of new telecommunication services. After segmenting the customers, we propose a procedure to provide different kinds of usage analysis, including inter-cluster analysis and intra-cluster analysis. The experimental results are determined based on rules extracted from a large number of call detail records generated by the mobile subscribers of leading 3G mobile system operators in Taiwan. The dependency network demonstrates the relationship between voice services, data communications, message services, micropayments and entertainment. Finally, we propose some marketing recommendations for 3G system operators based on these interesting rules.     

Perceived risks and customer needs of geographical accessibility in electronic commerce

Customer needs of geographical accessibility still plays an important role in electronic commerce, though the extent to which it does so varies according to the characteristics of products, services and the market strategies of firms. In this study, factors affecting customer needs of geographical accessibility and their structural relationships were investigated through a customer survey and statistical analysis using the methods of confirmatory factor analysis and structural equation modeling. The result shows that the three independent factors, unease of delivery, complexity of services, and trust and reliability affect significantly customer needs of geographical accessibility, with perceived risks of distant orders being a mediating factor in the relationship.     

Location-based services deployment and demand: a roadmap model

The advancements in mobile, wireless and positioning technologies have enabled applications and services such as route guiding and emergency call-out assistance. These and other similar services have become known as ‘location-based services’ (LBS). The literature on LBS development and deployment addresses technological issues (for example, usability and integration) and issues related to LBS implementation—including LBS business models, adoption and customer concerns and requirements. In the study presented here LBS development and deployment were investigated from a case study perspective and the LBS landscape is explored and analyzed. The study finds that while the regulatory environment has played a critical role as a success factor in the markets investigated some of innovative business approaches may have been equally important as customer demand generators. Economies on the road to deploying LBS should therefore focus on creating a supportive environment encouraging the development of services, which meet the identified needs and requirements of the target customer market.     

The Effects of Customer Value on Loyalty and Profits in a Dynamic Competitive Market

Providing high value products and services to customers normally leads to customer loyalty and profits. In practice, the relationship of customer value, loyalty, and profits can be observed in the market. However, the dynamic interactive relationships which lead to customer loyalty and profits still remain ambiguous. In this paper, the Agent-Based Computational Economics (ACE) model is introduced to explore the formation of customer loyalty in the Taiwanese imported lumber market. Using agents with reinforced learning algorithms in trading simulations, the effects of customer value on loyalty and profit are incorporated and examined in this interactive dynamic model. As results, the positive correlations among variables of customer value, loyalty, and profits are observed. A controlled experiment shows that changing customer value leads to changes in customer loyalty and profits, but price is not the determinant factor for improving customer loyalty. The R ² values of customer loyalty and profits elucidate that they are increasing as the time lapsed elongate. Providing high value of products and services is a better strategy for suppliers to attract potential loyal customers.      

Referenzprozessabläufe für Telekommunikationsunternehmen

The telecommunication market is experiencing substantial changes. New business models, innovative services, and technologies require reengineering, transformation, and process standardization. Enterprise Architecture Frameworks support the transformation by specifying methods, procedures, and reference models. With the Enhanced Telecom Operation Map (eTOM), the TM Forum offers an international de facto reference process framework, based on specific features and requirements of the telecommunication industry. However, this reference framework only offers a hierarchical collection of processes on different levels of abstraction; a control view in terms of a sequential ordering of tasks and hence a real process flow as well as an end-to-end view on the customer are missing. In this paper, we extend the eTOM reference model by reference process flows, in which we abstract and generalize the knowledge about processes in telecommunication companies. With reference process flows, we aim to assist companies in achieving a structured and transparent re-structuring and re-design of their processes. We demonstrate the applicability and usefulness of our reference process flows in two case studies, and evaluate them by means of criteria for reference model evaluation. Our reference process flows have been accepted as a standard by the TM Forum and published as part of eTOM version 9. We further elaborate on those components of our approach which can be applied outside the telecommunication industry.     

聚类算法在电信客户细分中的应用研究

结合聚类算法的分析，提出了一种解决电信客户细分的应用模型，该模型在实际中得到了较好的应用并为电信服务产品的策划设计提供了依据。同时，通过引入指标区分度的定义，给出了一种聚类方法应用效果评估的方法。该方法结合电信的案例应用与K-Means、SOM、BIRCH等聚类方法结果的分析，得出K-Means方法在电信客户市场细分中的应用优越性。     

Optimizing lead time and resource utilization for service enterprises

Lead time is generally defined as the period of time for which customers have to wait before receiving completed products or services from enterprises. In the key public utility markets, such as telecommunications market, that are tightly regulated by government watchdogs, service enterprises are obliged to provide equivalent services to all their customers. In the context of service lead time, this means that “standard lead times” should be universally applied to all customers. Existing industrial practice in deriving “standard lead time” is manual and erroneous. Regardless of the variances of demand and resource across geographical areas and across time horizon, service enterprises are generally confined to single fixed “standard lead times”. Ill-derived “standard lead times” lead to wrong promises made to customers, which not only forces service engineers to work overtime to deal with overflowing jobs but also incur huge compensation costs due to delayed or failed customer services. In this paper, we set out to tackle the “standard lead time” problem. In particular, we devised an automated approach to testing the existence of legal optimal allocation schemes based on actual customer demand, enterprise resource and assumed standard lead time. We first modelled this as a combinatorial optimisation problem; we then experimented a heuristic local search method, namely “single day shift”, inspired by previous work on virtual telescope scheduling; further on, we improved the first method by introducing a new heuristics, namely “multiple day spread”, which achieved a speed of search for optimal solutions, 1.29 times faster than the first method. A case study on comparisons between existing default “standard lead time” and the calculated one using our approach for a telecommunication service provider was conducted to demonstrate the necessity and effectiveness of this approach. Finally, we compared our approach with related work. We concluded that our approach is more suitable for the problem of optimizing lead time and resource utilisation, and the results from our work are widely applicable to various industry sectors that concern equivalent customer services, balanced work load and optimal lead times.     

The Rise of Neo-Intermediation: The Transformation of the Brokerage Industry

Developments in information technology and increased competition both within and outside the industry have led to the unbundling and desegregation of brokerage functions. Nimble on-line institutions like E*Trade and Microsoft Investor are usurping the roles traditionally played by full-service and discount brokerages, forcing some powerful firms to narrow their focus and others to broaden their product offerings. These changes raise the question: will full-service and discount brokerages continue to exist as we know them in the twenty-first century? To answer this question, the authors provide a new market transformation framework called Neo-Intermediation that helps explain how leading on-line firms are desegregating and reagregating functionality in order to create value in innovative ways. The pattern of change for brokerages is: Unbundling of traditional services—market players examine the elements of the buyer and seller relationship; Reallocation of authorities as the “customer” determines what they will do and what they will pay for in the market; Creation of strategic alliances with complementors—sites/products whose products complement yours. This means that if a customer has their product, they would also want yours; and Repackaging and emergence of both commodity and differentiated service providers that serve the needs of the “new” customer. The authors believe that these patterns are evident in all forms of financial services and form the basis of market interventions in most service industries. This paper addresses the transformation of the brokerage services marketplace. With new patterns of intermediation emerging, the winners of the future will be those who most successfully create new context bundles that meet customers' needs.     

服务创新顾问案中所采用的顾问方法整理与评估

Many consulting firms and research institutions have started providing consultancy services for service innovations. However, academic research has not kept pace with rapidly changing developments in consulting businesses. This study evaluated all known methods currently used in service innovation consulting, and analyzed the actual practices of service innovation consulting to clarify trends in service innovation. Methods are evaluated by their strategy orientation and divergence orientation, and then classified according to a proposed general service innovation consulting framework. The findings of this study indicate that the current focus of service innovation consulting is: customer needs discovery. However, an integrated service innovation methodology covering customer needs discovery, market discovery, idea generation, strategy formulation, service engineering, and simulation/pilot is urgently needed.     

Applying Bayesian Belief Network approach to customer churn analysis: A case study on the telecom industry of Turkey

In telecommunication industry, for many organizations, it is really important to take place in the market. As competition increases between companies, customer churn becomes a great issue to deal with by the telecommunication providers. For an effective churn management, companies try to retain their existing customers, instead of acquiring new ones. Previous researches focus on predicting the customers with a propensity to churn in telecommunication industry. In this study, a model is constructed by Bayesian Belief Network to identify the behaviors of customers with a propensity to churn. The data used are collected from one of the telecommunication providers in Turkey. First, as only discrete variables are used in Bayesian Belief Networks, CHAID (Chi-squared Automatic Interaction Detector) algorithm is applied to discretize continuous variables. Then, a causal map as a base of Bayesian Belief Network is brought out via the results of correlation analysis, multicollinearity test and experts’ opinions. According to the results of Bayesian Belief Network, average minutes of calls, average billing amount, the frequency of calls to people from different providers and tariff type are the most important variables that explain customer churn. At the end of the study, three different scenarios that examine the characteristics of the churners are analyzed and promotions are suggested to reduce the churn rate.     

Strategic reasoning about business models: a conceptual modeling approach

Strategic reasoning about business models is an integral part of service design. In fast moving markets, businesses must be able to recognize and respond strategically to disruptive change. They have to answer questions such as: what are the threats and opportunities in emerging technologies and innovations? How should they target customer groups? Who are their real competitors? How will competitive battles take shape? In this paper we define a strategic modeling framework to help understand and analyze the goals, intentions, roles, and the rationale behind the strategic actions in a business environment. This understanding is necessary in order to improve existing or design new services. The key component of the framework is a strategic business model ontology for representing and analyzing business models and strategies, using the i* agent and goal oriented methodology as a basis. The ontology introduces a strategy layer which reasons about alternative strategies that are realized in the operational layer. The framework is evaluated using a retroactive example of disruptive technology in the telecommunication services sector from the literature.     

Empirische Evaluation von Fair-Use-Flatrate-Strategien f��r das mobile Internet

The fair use flat rate is a promising tariff concept for the mobile telecommunication industry. Similar to classical flat rates it allows unlimited usage at a fixed monthly fee. Contrary to classical flat rates it limits the access speed once a certain usage threshold is exceeded. Due to the current global roll-out of the LTE (Long Term Evolution) technology and the related economic changes for telecommunication providers, the application of fair use flat rates needs a reassessment. We therefore propose a simulation model to evaluate different pricing strategies and their contribution margin impact. The key input element of the model is provided by so-called discrete choice experiments that allow the estimation of customer preferences. Based on this customer information and the simulation results, the article provides the following recommendations. Classical flat rates do not allow profitable provisioning of mobile internet access. Instead, operators should apply fair use flat rates with a lower usage threshold of 1 or 3 GB which leads to an improved contribution margin. Bandwidth and speed are secondary and do merely impact customer preferences. The main motivation for new mobile technologies such as LTE should therefore be to improve the cost structure of an operator rather than using it to skim an assumed higher willingness to pay of mobile subscribers.     

Exploring the Effect of Cognitive Biases on Customer Support Services

In order to meet the increasingly more complex needs of customers and respond to decreasing product margins, product‐oriented firms have developed a growing interest in extending their service business. Over the last couple of years, most product‐oriented companies have explored the numerous opportunities offered by traditional customer service and product‐related services. Currently, these opportunities have reached a certain level of maturity. A number of practitioners and theorists stress the growing importance of customer support services. However, the entry point to the theorizing is the observation that very few product‐oriented firms have already innovated customer support services successfully. In most firms, cognitive biases limit the motivation of managers to facilitate creative potential for new customer support services. In this paper, four cognitive biases are elaborated through 12 mini‐cases and 8 in‐depth cases. The results suggest that disbelief in the financial potential, risk aversion, tendency to set over‐ambitious objectives, and fundamental attribution error plays a critical role in creating customer support services. These four cognitive biases, and the key factors in overcoming them, provide guidance for managers who aim to facilitate creative potential for customer support services.     

Affective and cognitive design for mass personalization: status and prospect

The prevailing practice of design for mass customization manifests itself through a configure-to-order paradigm, which means to satisfy explicit customer needs (CNs) and built upon legacy design. With pervasive connectivity and interactivity of the Internet and sensor networks, personalization has been witnessed in a number of industry sectors as a promising strategy that makes the market of one a reality. Mass personalization entails a strategy of producing goods and services to satisfy individual customer’s latent needs with values outperforming costs for both customers and producers. This review paper envisions an affective and cognitive design perspective to mass personalization. By exploiting implicit market demand information and revealing latent CNs, mass personalization aspires to assist customers in making better informed decisions, and to the largest extent, to anticipate customer satisfaction and adapt to customer delight. The key dimensions of mass personalization are identified and discussed. By capitalizing on user experience, affective and cognitive design for mass personalization is expected to address individual customer’s latent CNs. The decisions of affective and cognitive design, involving affective and cognitive needs elicitation, affective and cognitive analysis, and affective and cognitive fulfillment, are reviewed with a wide range of interests, including engineering design, human factors and ergonomics, engineering psychology, marketing, and human-computer interaction. Recent trends and future research directions are also speculated to inspire more meaningful research in this area.     

Requirements for intelligent network service operations

A service operation architecture and operation system platform are proposed that separate commonly used information from operations functions, and that use access control functions. This enables new applications to be developed more easily and increases operating efficiency. The operation system platform is related to several surrounding platforms, and requires standardized reference points such as CMIS/P and managed objects. A managed object methodology is a suitable approach for accessing the operation system platform, and managed object classes and methods are proposed for intelligent network service operations. This architecture and platform will allow telecommunication to meet the demands created by intelligent networks for enhanced customer services, more reliable operation systems, and lower development costs. On the basis of proposed platform, service surveillance prototype systems for free-phone services have already been developed, and the next versions of the service operations systems for virtual private networks services are being developed.     

CCSOA在羊毛衫网络化生产管理系统中的应用研究

本文引入以消费者为中心的SOA（CCSOA）技术，以解决传统SOA架构中服务消费者被动地荻取服务的问题。文中阐述了CCSOA架构和工作原理，并应用于羊毛衫网络化生产管理系统中，为系统设计了整体架构，最后分析了一个客户定制实例，以体现CCSOA架构的优越性。在基于CCSOA架构的羊毛衫网络化生产管理系统中，企业服务以客户为中心，能够更敏捷地响应市场需求的变化。CCSOA的应用可为企业提高生产效率。     

Eliciting Customer Preferences for Products From Navigation Behavior on the Web: A Multicriteria Decision Approach With Implicit Feedback

The goal of raising customer loyalty in electronic commerce requires an emphasis on one-to-one marketing and personalized services. To this end, it is essential to understand individual customer preferences for products. In this paper, we present a method for identifying customer preferences and recommending the most appropriate product. The identification and recommendation of such products are all based on the use of customer's real-time web usage behavior, including activities such as viewing, basket placement, and purchasing of products. Therefore, in this approach, we do not force a customer to explicitly express his or her preference information for particular products but rather capture his or her preferences from data that result from such activities. Information on the web usage behavior for the products determines the ordinal relationships among the products, which express that certain product is preferred to other products across the multiple aspects. The ordinal relationships among the products and the multiple aspects of products lead to the consideration of a multiple-criteria decision-making approach. Thus, the problem eventually results in the identification of weights attached to the multiple criteria in the multidimensional preference space constructed by the ordinal relationships among the products. The derived weights are then used for the prioritization of products that are not included in the navigation behavior due to factors such as time pressure, cognitive burden, and the like.