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OR and the management of electronic services
Abstract
This review paper is meant to provide some insight to the relation between operations research and the management of electronic services. We use the term electronic services, within the broader e-business context, to refer to any service that is delivered to the customer via electronic means, mainly the Internet as a new channel to communicate with customers, but also through mobile and other digital communications. During the last years we have experienced an explosion in the development of electronic services, which is creating abundant opportunities for operations research (OR) applications, required to empower several types of technology-mediated interactions, exploit the large-scale digital data sources, and automate the recurring operational decisions. In this paper we summarise the various aspects in which operations research may support the management of electronic services, taking into account the different characteristics of alternative electronic media, such as the Internet, mobile communications, interactive television etc.
... This is because the failure to serve demand leads not only to immediate loss of revenue, but also to a possible loss of a future revenue stream due to churn (desertion of customers to alternative sources of content). The phenomenon of churn is a major concern of industrial actors [15,53]. One of the reasons for this is that a small improvement in customer retention can lead to a significant increase in profit [12]. ...
... This theorem is proved by substitution of (16) into (15) and solving the problem (15). ...
... This theorem is proved by substitution of (16) into (15) and solving the problem (15). ...
We consider the relationship of Internet service providers (ISP) and content service providers (CP) in the Internet ecosystem. Currently, the position of ISPs is challenged by the emergence of powerful content service providers, especially with the spreading of bandwidth-demanding video services. The further investment in the network capacity may be hindered by prevailing business models that largely exclude the ISPs from sharing in the major cash flows resulting from content provision. We develop modeling tools for evaluation of business models of ISPs and present results of an analysis of two models with the potential for the generation of additional cash flows for ISP: paid content peering and service differentiation. Firstly, we show that under certain conditions on the cost structure and the level of demand elasticity and uncertainty, it can be profitable for a powerful content provider to resort to paid content peering, thus transferring to the ISP a part of his content provision revenue. The resulting business model may provide substantial benefits to all major participants in this ecosystem: network providers, content and service providers and end users. After this we consider competition in the Internet provision sector and show that - also in this case - the paid content peering can help ISPs to expand the network capacity and at the same time increase profits of content providers. The end users benefit from the lower prices for content services. Finally, we consider the situation when an ISP differentiates the service offer by engaging in content provision, thus entering in direct competition with content providers.
... An online auction is an auction that is held over the Internet. As a successful application of Internet commerce, an online auction is the combination of a traditional auction and e-commerce [1]. A bidder can take part in an online auction no matter her/his location. ...
This work studies an online auction process of selling a secondhand good, which cannot be repeated many times. The secondhand goods market is of great significance in optimizing resource allocation, reducing resource consumption and reducing environmental pollution. The development of e-commerce and online auction provides a favorable tool for the prosperity and standardization of the secondhand goods market. Online auctions are widely used since they break the barrier of space. A buyout option allows the bidder to obtain the auction item immediately by accepting the buyout price. Whether a participant wins the auction or not is determined by a specific bidding price rather than the average price of all the others. This bidding price is called a focus point in this paper. A new auction model based on the focus point is proposed to analyze the decision behaviors of the seller and the bidders. It is an application and expansion of one-shot decision theory. By the new model, we obtain the optimal strategy of the bidders , state the necessity of providing the buyout option and suggest the price interval for the seller to increase their revenues. It provides a solution of low adoption rate of buyout price in reality, and provides theoretical support for the secondhand goods auction platform.
... For instance, Breugelmans and Campo [5] discussed the cross-channel effects of price promotions in the multi-channel grocery retail sector. A consistent finding in the promotion studies is the increase in purchase conversion rate after the promotion [30][31][32], which implies a positive response from customers' purchasing in many realms such as airline tickets [33], automotive industry [34], internet marketing [35]. ...
The micro-level customer purchase intent in promotions is crucial for the overall purchase conversion rate of promotions. In the context of joint promotions on multiple online channels, customers can access and compare prices and services by navigating between channels to aid their purchase decision. The interactions between customer and promotion channels offer another angle to predict their purchase intent during promotions. In this paper, we propose a feature-combined deep learning framework, in which a full-connected long short-term networks (FC-LSTM) is used for modeling the interactions between customers and promotion channels, as well as the nonlinear sequence correlations and cumulative effects between customer’s browsing behavior. To improve the performance of the prediction, the framework incorporates other features of customer profile including purchase history and demographics, integrating them into an end-to-end framework. We apply our method in a real prediction task for online multichannel promotion for concert tickets. Extensive experiments show that the proposed approach exhibits overall good performance compared with state-of-the-art methods on standard metrics such as precision, recall, f-measure, area under curve (AUC), and lift.
... In addition to goods and multimedia recommendations, applications of this system have been noted in various business areas (i.e., egovernment, e-health, e-tourism, e-library, e-resource services, and e-learning) [24,25]. Moreover, the recommendations of e-services fulfill the customer's satisfaction, which leads to benefiting different digital companies in terms of enlarging their sales, revenue, and loyalty [26]. Recently, e-commerce [27][28][29] has become the largest online marketplace for a variety of products, where recommendation techniques are used significantly. ...
Recommender systems support consumers in decision-making for selecting desired products or services from an overloaded search space. However, this decision support system faces difficulties while dealing with sparse and noisy rating data. Therefore, this research re-classifies users and items of a system into three classes, namely strong, average and weak to identify and correct noise ratings. Later, the Bhattacharya coefficient, a well-performing similarity measure for a sparse dataset, is integrated with the proposed re-classification method to predict unrated items from the obtained noise-free sparse dataset and recommend preferred products to consumers. Furthermore, the effectiveness of the proposed model is validated on two sparse and noisy datasets and compared with various published methods in terms of the mean absolute error (MAE), root mean square error (RMSE), F1-measure, precision, and recall values. The obtained results confirm that the proposed model performs better than other published relevant methods.
... Matching the right pairs of competitive customers and providers for electronic services on double-sided markets is an important optimization problem in Operations Research [2]. On these markets, multiple service providers offer electronic services of a specified quality of service (QoS), while multiple customers demand these services at a specific QoS. ...
We consider pricing schemes for matching customers and providers on double-sided markets for electronic services. While existing second-best solutions are incentive compatible, the associated payment functions are difficult to implement in real-world settings. Based on the Vickrey-Clarke-Groves (VCG) and the k-pricing mechanism, we propose two straightforward payment schemes that offer a practical alternative to the second-best solution. Our experiments provide evidence that the VCG payments fail to implement incentive compatibility. This failure is due to the interdependency of the participants' utilities.
... There are plenty of papers on the e-commerce. In the recent review paper (Doukidis et al., 2008;Fink et al., 2008;Hernandez-Ortega et al., 2008), e-business is captured under operational research management. The e-commerce affecting the optimal point of the particular firm was recently characterized (Kotabe et al., 2008). ...
Many traditional monopoly industries are pervaded by the external e-commerce in recent years. It is therefore important to address the internet in these special industries. We establish a model under the monopoly with the external e-commerce and the corresponding properties are achieved. This paper shows that it is advantageous for the e-commerce if there are more consumers with internet prone. The effects of the change of the market size are also discussed and we find that this change has more effects on the offline sales. In essence, we characterize the e-commerce with the industrial organization theory in this work.
... Because of the continuing transformation of industrialized economies from a manufacturing base to a service orientation, the global supply chain, which is characterized by multilayered supplier-customer relationships, presents a number of opportunities and challenges (Demirkan et al., 2008; Smith, Karwan, & Markland, 2007;). Numerous studies have shown that high levels of quality and service are essential if suppliers wish to meet supply chain challenges and enhance their competitive position in today's global environment (Abdullah & Tarib, 2012; Bendoly, Donohue, & Schultz, 2006; Chua & Linb, 2011; Doukidis, Pramatari, & Lekakos, 2008; Lin et al., 2005; Roussinov & Chau, 2008; Singhal, Singhal, & Starr, 2007 ). However , some scholars argue that the importance of services has been underemphasized (Metters & Marucheck, 2007 ). ...
Great changes within the business environment in the last 2 decades have made supply chain management (SCM) an important topic for academics and practitioners. Globalization, larger reliance on layered suppliers for specialized capabilities and innovation, changing customer needs, reliance on supply networks to maintain a competitive advantage, and developments in technology have all contributed to a very different supply chain environment. Most current works view customers as being outside the supply chain design; however, we believe that customers are the missing link in the supply chain. Therefore, in this paper, we focus on the customer's role in the process. We present an original discussion of the emerging discipline of services science, management, and engineering (SSME) in SCM, identify and bridge the gaps between SSME and SCM, as well as discuss ways to align them. In addition, we consider the specific challenges as well as the opportunities for SSME in supply chain management.
... However, the technological advances used to facilitate the flow of information in production-inventory systems, e.g. automatic warehouse review (Giordano, 2008), or Internet ordering (Doukidis, 2008), call for new solutions, which will not only provide good steady-state performance, but will also guarantee time-efficient response to the market changes. ...
In this paper we consider an inventory system where the stock at a distribution center, used to fulfill the demand imposed by customers and retailers, is replenished with delay from a supplier. In contrast to the typical, stochastic approaches, which operate mainly on average or static quantities, the emphasis is placed on optimizing the dynamics of the goods flow process in the presence of the time-varying delay between placing of an order and shipment arrival at the center. The designed policy ensures that the demand is always entirely satisfied from the on-hand stock (yielding zero lost-sales cost) and the warehouse capacity is not exceeded (what eliminates the risk of high-cost emergency storage). It is shown how the linear-quadratic (LQ) optimal controller with saturation achieves robustness with respect to the time-varying lead-time delay and unknown demand fluctuations.
... The rationale behind the group-buying business model has attracted much interest (e.g., see Doukidis, Pramatari, & Lekakos, 2008, Dholakia, 2010, Edelman et al., 2012, Jing & Xie, 2011. One of the most distinctive features of the strategy is that group-buying customers receive products at a discount price only if the minimum number of the sales volume is reached. ...
This paper studies the group-buying mechanism from a dynamic perspective. We consider a seller that offers a product in the form of group buying (priced low but uncertain) and spot purchasing (priced high but guaranteed). In the case of group buying, the information associated with the number of participating customers is updated in the middle of the sale. Customers are assumed to be strategic with a time-dependent utility. In addition to choosing between spot purchasing and group buying, customers could choose to delay their decisions until the information update. We characterize the customer behavior within a rational expectations framework. We then consider the effect of information and demand dynamics. Our results show that whereas an improvement in information quality has a positive effect on customer surplus and the group-buying success rate, the effect of inter-temporal demand correlation is mixed. We also discuss the seller’s profit maximization problem and derive the condition to be satisfied at the optimal group size.
... Because of the continuing transformation of industrialized economies from a manufacturing base to a service orientation, the global supply chain, which is characterized by multi-layered supplier-customer relationships, presents a number of opportunities and challenges456. Numerous studies have shown that, for suppliers, quality and service are critical to meeting supply chain challenges, as well as enhancing their competitive position in today's global environment [2,78910. However, it has been argued that academics have underemphasized the importance of services by viewing them merely as secondary activities [11]. ...
Most current works in supply chain view customers as being outside the supply chain design; however, in this paper, we focus on the missing link of the customer’s role in the supply chain. We present an original discussion of the emerging discipline of services science, management, and engineering (SSME) in SCM, identify and bridge the gaps between the two disciplines, and discuss ways to align them. In addition, we consider the specific challenges as well as the opportunities for SSME in the supply chain field.
... Third, Doukidis et al. (2008) provides a review paper about the relation between operations research and the management of electronic services, including internet, mobile communications, interactive television and other digital communications. He asserts that the explosion in the development of electronic services is creating abundant opportunities for operations research applications. ...
Nowadays, manufacturers are increasingly adopting direct channels to increase financial performance and improve services. Location-sensitive mobile channel helps retailers attract nearby incumbent consumers. How such a channel influences supply chain performance is unknown. In this paper, we evaluate the performance of a decentralised supply chain that has three channels: an electronic channel, a mobile channel and a physical channel. We model the supply chain interaction in a Stackelberg game and derive conditions that mobile channel benefits the various supply chain participants.
... However, the technological advances used to facilitate the flow of information in production-inventory systems, e.g. Internet ordering [2], or automatic warehouse review [3], call for new solutions, which will not only provide good steady-state performance, but will also guarantee prompt response to the changing market conditions. Therefore, in order to answer the challenges of the highly competitive and rapidly varying environment, the traditional approaches to the design of inventory management schemes must be augmented by the solid analysis of their dynamical features. ...
The paper addresses the problem of inventory control in production-inventory systems stressing the dynamical aspects of stock replenishment process. In the considered systems, the stock used to satisfy the unknown, time-varying demand can be refilled from multiple supply sources. The orders issued in each review period are realized with delay, which differs among the suppliers and transport alternatives. For the considered discrete-time nth-order system, a new inventory policy is developed using strict control-theoretic methodology. In contrast to the classical, stochastic approaches, the proposed policy is obtained through dynamical optimization with quadratic performance index. The designed policy ensures that the demand is always entirely satisfied from the on-hand stock (yielding zero lost-sales cost) and the warehouse capacity is not exceeded (what eliminates the risk of high-cost emergency storage). The closed-form solution of the linear-quadratic (LQ) optimization problem allows for a straightforward implementation of the developed control strategy in real systems.
... However, the technological advances used to facilitate the flow of information in production-inventory systems (e.g. Internet ordering (Doukidis, Pramatari, & Lekakos, 2008;Teich, Wallenius, Wallenius, & Koopius, 2004), automatic warehouse review ✩ This work was financed by the Polish State budget in the years 2010-2012 as a research project N N514 108638 ''Application of regulation theory methods to the control of logistic processes''. P. Ignaciuk gratefully acknowledges financial support provided by the Foundation for Polish Science (FNP). ...
The paper addresses the problem of efficient inventory management in production–inventory systems focusing on the dynamical nature of goods flow process. In the considered systems, the stock used to satisfy an unknown, time-varying demand is replenished either from a single or from multiple supply sources. The replenishment orders issued in each review period are realized with a delay, which differs among the suppliers and transport alternatives. For the analyzed setting, modeled as a discrete-time nth-order deterministic system, a new inventory policy is developed using a strict control-theoretic methodology. In contrast to the classical, stochastic approaches, the proposed control law is obtained by minimizing a quadratic cost functional, which guarantees the optimal dynamical performance of production–inventory systems with (possibly) different lead-time delays in the supply path. The designed policy ensures that the demand is always entirely satisfied from the on-hand stock (yielding zero lost-sales cost) and the warehouse capacity is not exceeded (which eliminates the risk of high-cost emergency storage). The closed-form solution of the linear–quadratic (LQ) optimization problem allows for a straightforward implementation of the developed control strategy in real systems.
... However, the technological advances used to facilitate the flow of information in productioninventory systems, e.g. Internet ordering (Doukidis, Pramatari, and Lekakos 2008) and automatic warehouse reviewing (Giordano, Zhang, Naso, and Lewis 2008), call for new solutions that will not only provide good steady-state performance, but will also guarantee prompt response to the changing market conditions (Ortega and Lin 2004). The recognised need for analysing the dynamical properties of productioninventory systems has resulted in a number of research efforts exploiting the tools of control theory (White 1999;Samanta and Al-Araimi 2001;Rodrigues and Boukas 2006;Wang, Rivera, and Kempf 2007;Aggelogiannaki and Sarimveis 2008). ...
In this article, the theory of discrete sliding-mode control is used to design new supply strategies for periodic-review inventory systems. In the considered systems, the stock used to fulfil an unknown, time-varying demand can be replenished from a single supply source or from multiple suppliers procuring orders with different delays. The proposed strategies guarantee that demand is always entirely satisfied from the on-hand stock (yielding the maximum service level), and the warehouse capacity is not exceeded (which eliminates the cost of emergency storage). In contrast to the classical, stochastic approaches, in this article, we focus on optimising the inventory system dynamics. The parameters of the first control strategy are selected by minimising a quadratic cost functional. Next, it is shown how the system dynamical performance can be improved by applying the concept of a reaching law with the appropriately adjusted reaching phase. The stable, nonoscillatory behaviour of the closed-loop system is demonstrated and the properties of the designed controllers are discussed and strictly proved.
... Jonason (2002) and Jonason and Eliasson (2001) discuss the applicability of standard and unique pricing theories, using the i-mode portal as an example. Doukidis et al. (2008) points out that the literature contains only a few theoretical studies on the economics of mobile service portals, and most of them focus on centralized decision making, ignoring interactions with other parties on the portal. While several researchers have analyzed complex forms including nonlinear and bundled tariffs (Constantiou and Damsgaard, 2004;Yaipairoj and Harmantzis, 2006), they have not accounted for different cost structures of independent decision makers. ...
Early mobile phones only provided voice transmission, for a fee. They have now evolved into voice and online data portals for providing additional services through 3rd party vendors. These service providers (vendors) are given access to a customer base “owned” by the mobile phone companies, for a fee. Typically customers make two payments: to the mobile phone company for phone services and to the 3rd party vendors for specific services bought from them. Variations to the above business model may involve outsourcing the online portal and/or acquiring customers from other independent portals. For these scenarios, we study how the fees for phone service and customer access are established and how they may relate to the prices of vendor services, and which services should be located on the portal – all in a game-theoretic context. Our results prove that it is possible to reorganize revenue flows through an invoicing process that may benefit the mobile network operator more than the other parties. In addition, we establish optimality in terms of the number of vendors on the portal, and determine a rank-ordering of vendors for their inclusion into the portal.
To the best of our knowledge, few studies have focused on the inconsistency between user ratings and reviews as well as natural noise management in recommender systems (RSs). To address these issues, this study introduces a sentiment based multi-index integrated scoring method to provide a reliable information input that reflects comprehensive user preferences for recommendation algorithms and facilitate improved performance. Initially, Bing Liu’s lexicon is expanded using a semi-supervised learning technique to obtain additional sentiment words and calculate the sentiment scores of reviews; then a normalized sentiment score method based on sigmoid function that considers the emotional tendencies of different users in reviews is designed to convert the scores into values corresponding to the rating scale of RS. Subsequently, a degree classification criteria approach is adopted to assign users and items to more fine-grained classes Further, a natural noise detection method is exploited to identify and correct noise ratings according to classification conditions. To effectively integrate normalized review and denoised rating information, two factors, user consistency and review feedback, are considered to obtain the importance of reviews and ratings; then, a weighted average method is used to generate a set of comprehensive ratings. The experimental results on two benchmark datasets indicate that the superiority of memory-based or model-based collaborative filtering methods (CFs) using comprehensive ratings over their respective methods using original ratings is determined by various accuracy metrics, which demonstrates that our scheme can enhance the reliability and accuracy of user information. Thus, the proposed scheme provides new insights for improving the accuracy of RSs from the perspective of multiple information sources. Additionally, this method exhibits good generalizability and practicality.
An efficient and accurate recommender system provides online users with a variety of personalized recommendation services, thus effectively improving the satisfaction and experience of users. However, there is a trade-off between the accuracy and efficiency in recommender systems. Accordingly, this study introduces a recommendation strategy to address this limitation. The extended degree classification criteria are first proposed to assign items to more fine-grained classes. Later, item similarity measure is deployed to quickly evaluate similarities between items within the same class, which greatly reduces the runtime of similarity calculation. To obtain a better recommendation result, a Hellinger distance (HD) based item similarity is presented to calculate item similarity from the perspective of rating probability distribution. Additionally, a sigmoid function is considered in the HD similarity to emphasize the importance of the co-rated items and effectively distinguish differences between a pair of items. The experimental results on two benchmark datasets show that the proposed similarity method using the classification criteria has better performance in both accuracy and efficiency compared to other methods. Also, the results verify the effectiveness of the proposed classification criteria, especially the runtime of item-based CF method is reduced by at least 61% while maintaining a relatively stable or higher accuracy.
This study proposes a decision support framework to help e-commerce companies select the best collaborative filtering algorithms (CF) for generating recommendations on the basis of online binary purchase data. To create this framework, an experimental design applies several CF configurations, which are characterized by different data-reduction techniques, CF methods, and similarity measures, to binary purchase data sets with distinct input data characteristics, i.e., sparsity level, purchase distribution, and item-user ratio. The evaluations in terms of accuracy, diversity, computation time, and trade-offs among these metrics reveal that the best-performing algorithm in terms of accuracy remains consistent regardless of the input-data characteristics. However, for diversity and computation time, the best-performing model varies with the input characteristics. This framework allows e-commerce companies to decide on the optimal CF configuration as a function of their specific binary purchase data sets. They also gain insight into the impact of changes in the input data set on the preferred algorithm configuration.
End-to-End (E2E) differentiated services refer to information services, delivered over the modern Internet with a differentiated grade of Quality of Service (QoS) over heterogeneous networks. Such services represent a prospective way of satisfying the needs of demanding customers, which cannot be satisfied with QoS delivered by the usual best effort Internet connectivity. This paper focuses on the differentiation aspect and develops stochastic optimization models designed for the selection of a portfolio of services with varying degrees of QoS by a risk-averse service provider under uncertainty concerning demand, generated by a multi-segment market of heterogeneous users.
The model includes decisions concerning service offer, quality of services, pricing and network capacity expansion. The risk/profit trade-off is computed using an industry-specific risk measure, which is the fraction of demand not satisfied under the required QoS. We provide the evaluation of a plausible stepwise business strategy for the introduction of these services
The advancement of Internet technology has enabled new formats for selling products in the B2C online auctions. At present, on the major online auction sites, there exist three popular selling formats, namely, the posted price, pure auction and buy-price auction formats. It is an important decision problem for a firm to select the most profitable format to sell its products through the Internet. The customer behavior is of course a crucial element of the decision process. To the best of our knowledge, most models available today assume that customers are perfectly rational. To better understand the decision process, in this paper, we incorporate the concept of bounded rationality into consideration. We first present a “behavior choice function” to characterize the behavior of the customers with bounded rationality. Then corresponding to each selling format, we construct a revenue model based on the bounded rationality for analysis. Finally, we conduct some elaborate computational experiments to investigate the performance of each revenue model for developing new managerial insights. Our computational results clearly demonstrate how the bounded rationality of customer behavior affects the choice of a preferable selling format for a B2C firm in an online auction.
Many enterprises are leveraging e-service to meet the demanding needs of customers. E-business online demands a more complex business logics, and requires to support information exchange between business parties. Countless business processes require the participation and interactions of multiple parties. Nonetheless, the state-of-the-art e-services can only serve one or many individual clients at a time. A new kind of e-service is needed. In this paper, we provide a conceptualization of e-service-services by which client or interacting clients obtained via an electronic network. Party e-services are defined. A new architecture based on the service-oriented architecture is proposed to support these e-services.
Recent advances in mobile wireless networks allow handheld devices, such as smart phones, pocket PCs, to connect to the Internet and use the distributed applications conveniently. And the model of software as a service enables the handheld devices to use the applications which previously run on PCs or servers. However, the mobile wireless environment is dynamic and resource-limited. It needs an efficient service supporting mechanism to keep continuous services for those devices. In this paper, we presented a dynamic service management framework for web services in mobile wireless networks. It adopts the architecture style of Representation State Transfer (REST) and supports the dynamic service discovery and adaptive service invocation. It is suitable for dynamic services access through the handheld devices. The case study illustrated that our framework can support the service subscribers to get sustaining and dynamic services.
Sellers usually set a promotional time limit to ensure that products can be sold as soon as possible in Internet markets. This research attempts to build a decision support system that optimizes the time limit for maximum sales response or profit in Internet shopping promotions. We decompose the effect of time limits into two opposing forces, which are the awareness and urgency of a promotional offer that are depicted as hyperbolic S-shaped functions. Using the decision calculus approach, we can determine the optimal promotional time limit with different input parameters. We illustrate the use of the proposed system with real world examples and conduct some sensitivity analyses. We compare our numerical results from hyperbolic functions with those from simple exponential functions; we find that hyperbolic functions yield more appropriate promotional time limits on Internet. This research contributes to the field of decision support by providing a new approach to determining the optimal time limit for online sales promotions.
In this paper we study the impact of introducing a mobile channel into a supply chain. Thus, the supply chain owns an electronic channel, a mobile channel and a traditional channel. We model the context as a Stackelberg game. Through numerical experiments, we find that as mobile channel becomes more distinct from existing channels and becomes cheaper, consumers and manufacturer will be better off. We also find the manufacturer's inclination to mobile channel will not eliminate the traditional channel. However, the manufacturer's mobile channel has to keep a balance between attracting consumers for retailers and for itself.
Today we expect information and services to be online and available around the clock in our homes, schools and work places. We have been quick to adopt new ways of communicating both in business and in our personal life. Government is responding to these new demands. E-government is all about government agencies working together to use technology so that they can better provide individuals and businesses with government services and information. Much of it is about establishing common standards across government, delivering services more effectively, and providing ways for agencies to work together using technology. E-government will deliver enhanced services to us as individuals and provide a better environment to build a knowledge-based economy and sustained prosperity. E-government makes it easier to do business with government. This document presents the evaluation of the Hellenic E-Government applications. As follows, a model of the use of multi-criteria is applied which based on the methods of Linear Programming.
The prevailing definitions of mobile business do not effectively capture the observed phenomena. They are also restrictive in terms of the research questions and implications that can be drawn from them. This paper asks how mobile business should be defined if we are to develop scientific theories that transcend the rapidly changing practice. Next, it describes a research program that would be appropriate given the proposed definition, offering a scenario-planning project as an example. Finally, it introduces the papers in this special issue, illustrating the relevance of the proposed approach.
Customer habits, behavior, informational needs and expectations were a subject of change in electronic commerce and are changing further in the mobile commerce. In this spirit, the "mobile" sellers must understand that the ways to assure customer satisfaction are also changing. A new, coherent and fully developed customer strategy is indispensable in the assurance of … mobile satisfaction. This paper analyzes the changes in the mobile customer behavior, and also proposes some recommendations for a successful mobile marketing strategy.
At first glance, there seems to be a broad understanding regarding business models. However, a more thorough analysis of existing resources paints a different picture. The term 'business model' often remains undefined and a consensus on the elements of business models is lacking. An analysis of various sources, such as electronic databases, conference proceedings, and EM - Electronic Markets itself supports this statement. Nevertheless, business models are largely believed to determine the success of an electronic venture. To establish some structure and to identify the critical components of business models, the existing definitions and approaches were analysed and led to a model, which differentiates six business model elements. This model is also used to position the articles submitted to this special issue of EM - Electronic Markets.
The emerging capabilities of mobile telephony provide a promising alternative commerce channel, contributing to the configuration of the appropriate conditions for the forthcoming communication industry convergence. Elaborating on the rapid evolutions in the mobile commerce landscape, this paper investigates consumer attitudes towards mobile music services through an exploratory research approach conducted in Finland, UK and Greece. The objective of this study is to support content providers and mobile operators to capitalize on the unexplored marketing challenges existing in the virgin territory of mobile music. The findings indicate that content‐centric criteria (i.e., sound/image quality and content variety) are the most critical success factors for mobile music diffusion and consumer adoption, while content personalization capabilities, ubiquity, and easy‐to‐use interfaces constitute for the consumers the most desired features of a mobile music application. Significant differences were observed between consumers willing to adopt mobile music services and those that are not, in terms of the importance they assign to specific mobile music application selection criteria and features. Finally, significant differences were observed between the investigated countries in terms of consumers’ willingness to adopt mobile music services.
The digital economy is creating abundant opportunities for operations research (OR) applications. Several factions of the profession are beginning to respond aggressively, leading to notable successes in such areas as financial services, electronic markets, network infrastructure, packaged OR-software tools, supply-chain management, and travel-related services. Because OR is well matched to the needs of the digital economy in cer- tain ways and because certain enabling conditions are coming to pass, prospects are good for OR to team with related ana- lytic technologies and join information technology as a vital engine of further development for the digital economy. OR professionals should prepare for a future in which most busi- nesses will be e-businesses.
This article compares problems and strategies cited in the services marketing literature with those reported by actual service suppliers in a study conducted by the authors. Discussion centers on several broad themes that emerge from this comparison and on guidelines for future work in services marketing.
W e present a framework and empirical estimates that quantify the economic impact of increased product variety made available through electronic markets. While efficiency gains from increased competition significantly enhance consumer surplus, for instance, by leading to lower average selling prices, our present research shows that increased product variety made available through electronic markets can be a significantly larger source of consumer surplus gains.. One reason for increased product variety on the Internet is the ability of online retailers to catalog, recommend, and provide a large number of products for sale. For example, the number of book titles available at Amazon.com is more than 23 times larger than the number of books on the shelves of a typical Barnes & Noble superstore, and 57 times greater than the number of books stocked in a typical large independent bookstore. Our analysis indicates that the increased product variety of online bookstores enhanced consumer welfare by $731 million to $1.03 billion in the year 2000, which is between 7 and 10 times as large as the consumer welfare gain from increased competition and lower prices in this market. There may also be large welfare gains in other SKU-intensive consumer goods such as music, movies, consumer electronics, and computer software and hardware.
The Internet is creating opportunities to apply optimization. Firms can use operations research (OR) to improve their supply-chain performance within the enterprise whether their supply chains are being Internet-enabled or not. They can increase benefits by using OR to improve planning and execution in Internet-enabled supply chains with an expanded physical scope that includes vendors and customers and with an expanded functional scope that includes product design, marketing, and customer-relationship management.
Abstract Asthe,evolution of e-business,technology,has passed,from,the early phase,of hype,and innovation to the mature phase of adoption and use, the research interest of both the academic,and business,communities,is shifting to investigating opportunities,for market exploitation of e-business technologies. As a result, the debates around established ebusiness models, as well as the way to achieve business model innovation, are ever increasing. However, while many researchers and practitioners are contemplating business models, there is a distinct lack of appropriate theoretical tools in the literature to structure,and ,codify ,the ,extant ,knowledge ,in the ,area. The ,existing ,research contributions are featured by a great degree of diversity, which is due to the existence of Adamantia G. Pateli, George M. Giaglis a variety of reasons and motives for making research on business models. Thus, some researchers try to define business models, others to specify their primary elements, while others have proceeded further to introduce methodologies for developing, changing, or assessing business models. In this paper, we draw on a great number of research contributions,in the ,field of e-business ,models to propose ,a framework ,that further
E-business information systems are computer applications that leverage intra- and inter-firm process and systems integration. Considering the growth and strategic importance of e-business, while it is important for organizations to carefully plan for and architect e-business systems, none of the existing information systems planning models is adequate for the task. An e-business architecture planning model is developed by identifying 12 generic e-business models and three axes on which drivers of the information architecture needs of e-business firms fall. Sowa and Zachman’s information architecture is augmented to further facilitate e-business information systems architecture planning.
Vehicle routing (VR) is critical in successful logistics execution. The emergence of technologies and information systems allowing for seamless mobile and wireless connectivity between delivery vehicles and distribution facilities is paving the way for innovative approaches to real-time VR and distribution management. This paper investigates avenues for building upon recent trends in VR-related research towards an integrated approach to real-time distribution management. A review of the advances to-date in both fields, i.e. the relevant research in the VR problem and the advances in mobile technologies, forms the basis of this investigation. Further to setting requirements, we propose a system architecture for urban distribution and real-time event-driven vehicle management.
Interactive TV, also referred to as iTV, combines the appeal and mass audience of traditional TV with the interactive nature of the Web. As such, it offers viewers an active entertainment experience and industry players new business opportunities to learn better about and serve their audience and prospective customers. Interactivity, in particular, implies a two-way communication between the viewer and the medium, allowing for unprecedented personalization of programming and services. In this paper we deal with the topic of advertising over digital interactive TV and describe a specific approach to the delivery of personalized interactive advertisement content to viewers based on their individual profiles. The emphasis is placed on the transformation of industry business models that the new technological developments imply. The main implication of iTV advertising is a whole new set of information and information flows among industry players that are introduced to take advantage of interactivity and personalization. We suggest that a new value chain and new market intermediaries will be needed to harness the new information flows, proposing an integrated industry business model for a future technological platform.
The success of Internet based businesses in the Business to Customer segment in recent years is an indication of the events to unfold at the dawn of the new millennium. It is widely projected that the Business to Business segment is poised for a spectacular growth. However, a consistent definition and a framework for a business model for the Internet based business is still non-existent. This paper is an effort to fill in this gap. We propose a three dimensional framework for defining a business model and apply it to the emerging market structure. Furthermore, we also identify certain factors that would guide organizations in their choice of an appropriate business model. We also identify possibilities for further theory building in this area.
Over the past years, significant developments in mobile technologies and associated economies of scale via mature manufacturing processes have made the construction of ubiquitous computing applications possible in specific domains. This paper presents the business rationale and the architectural framework of an innovative ubiquitous computing application for the grocery sector (MyGROCER). MyGROCER exploits the opportunities provided by emerging wireless and mobile commerce technologies, coupled with automatic product identification technologies (RF-Id), in order to enable an efficient home replenishment schema, enhance the quality of service provided by retailers, and ultimately add value to the end-consumer. We present the architectural elements of the application by identifying the design challenges and the way they were dealt with. The paper concludes with a critical appraisal of ubiquitous computing applications in supermarket environments and identifies future research challenges.
This concludes a two-part commentary on management science and e-business, the theme of this two-part special issue. After reviewing the topical clusters that give organization to both parts, we sketch the papers appearing in this second part from the perspective of two key questions concerning the impact of the emerging digital economy on management science research: What fundamentally new research questions arise, and what kind of research enables progress on them. We then offer summary comments on the second question based on the papers in both parts. The principal conclusions are that, in meeting the challenges posed by the digital economy, management science researchers are (a) making greater use of parts of economics and computer science/information technology, and (b) exploiting the improving productivity advantages of empirical and methodological work in comparison with theoretical work.
This begins a two-part commentary on management science and e-business, the theme of this two-part special issue. After explaining the topical clusters that give organization to both parts, we pose two key questions concerning the impact of the emerging digital economy on management science research: What fundamentally new research questions arise, and what kind of research enables progress on them. We sketch the papers appearing in this part from the perspective of both these questions, and offer summary comments on the first question based on the papers in both parts. The principal conclusion is that the digital economy is giving birth to new research questions in three main ways (not all independent): by enabling and popularizing several types of technology-mediated interactions, by spawning large-scale digital data sources, and by creating recurring operational decisions that need to be automated.
The application of Internet--based virtual stock markets (VSMs) is an additional approach that can be used to predict short-- and medium--term market developments. The basic concept involves bringing a group of participants together via the Internet and allowing them to trade shares of virtual stocks. These stocks represent a bet on the outcome of future market situations, and their value depends on the realization of these market situations. In this process, a VSM elicits and aggregates the assessments of its participants concerning future market developments. The aim of this article is to evaluate the potential use and the different design possibilities as well as the forecast accuracy and performance of VSMs compared to expert predictions for their application to business forecasting. After introducing the basic idea of using VSMs for business forecasting, we discuss the different design possibilities for such VSMs. In three real--world applications, we analyze the feasibility and forecast accuracy of VSMs, compare the performance of VSMs to expert predictions, and propose a new validity test for VSM forecasts. Finally, we draw conclusions and provide suggestions for future research.
Evidence exists that service quality delivery through Web sites is an essential strategy to success, possibly more important
than low price and Web presence. To deliver superior service quality, managers of companies with Web presences must first
understand how customers perceive and evaluate online customer service. Information on this topic is beginning to emerge from
both academic and practitioner sources, but this information has not yet been examined as a whole. The goals of this article
are to review and synthesize the literature about service quality delivery through Web sites, describe what is known about
the topic, and develop an agenda for needed research.
We review the emerging field of multiple issue e-auctions and discuss their design features and performance criteria. We primarily consider B2B transactions in a reverse auction, that is, a procurement setting. In traditional auctions, the matching of buyers and sellers is typically based just on price. However, when there are quality and other differences in the merchandise and differences in the terms of the transaction, which are common in Request for Quotes, additional issues besides price should be considered. Such multiple issue, multiple unit e-auctions/negotiations, and their characteristics are the focus of our paper. We also discuss the role that OR has played and undoubtedly will play in the design and implementation of such e-auctions.
eb-basedgroup-buying mechanisms are being wid ely usedfor both business-to- business (B2B) andbusiness-to-consumer (B2C) transactions. We survey currently operational online group-buying markets, andthen stud y this phenomenon using analytical mod els. We buildon the literatures in information economics andoperations management in our analytical model of a monopolist offering Web-based group-buying under different kinds of demand uncertainty. We derive the monopolist's optimal group-buying schedule under varying conditions of heterogeneity in the demand regimes, and compare its profits with those that obtain under the more conventional posted-price mechanism. We further study the impact of production postponement by endogenizing the timing of the pricing and production decisions in a two-stage game between the monopolist and buyers. Our results have implications for firms' choice of price-discovery mechanisms in e-markets, and for the scheduling of production and pricing decisions in the presence (and absence) of scale economies of production. (Group Buying; Pricing; Demand Uncertainty; Quantity Discounts; Price Discovery; Demand Heterogeneity )
e studythe offers submitted byconsumers to a large Name-Your-Own-Price (NYOP) online retailer. A distinctive feature of this retailer is that it allows consumers to repeatedlysubmit offers on one and the same product. While consumers could identifythe threshold price (the minimum price for which the retailer is willing to sell) byincrementing their offer in small steps in each consecutive round, such a strategywould require them to go through manyadditional online transactions. We define frictional cost as the disutility that the consumer experiences when conducting an online transaction, such as submitting an offer. Thus, in our setting, consumers trade off a direct financial value (lower price) for frictional costs. Based on a consumer choice model capturing this trade-off, we use the observed consumer behavior to reconstruct the frictional cost parameters for the consumers in our sample. We show that, perhaps contraryto the general wisdom, frictional costs in electronic markets are substantial, with median values ranging from EUR 3.54 for a portable digital music player (MP3) to EUR 6.08 for a personal digital assistant (PDA). We find that consumers who have gathered experience with the NYOP channel in previous transactions exhibit lower frictional costs than consumers who use the channel for the first time. Surpris- ingly, sociodemographic variables do not help to explain the variation in frictional costs. (Electronic Markets; Frictional Costs; Name-Your-Own-Price Channel; Online Haggling; Price Dispersion)
Abstract The Internet’s computational power and flexibility have made auctions a widespread and integral part of both consumer,and business markets. Though online auctions are a multi-billion dollar annual activity, with a growing variety of sophisticatedtrading mechanisms, scientific research on them is at an early stage. This paper analyzes the current state of management science research on online auctions. It develops a broad research agenda for issues such as the behavior of online auction participants, the optimal design of online auctions, the integration of auctions into the ongoing operation of firms, and the use of the data generated by online auctions to inform future trading mechanisms. These research areas will draw from applied and theoretical work spanning management science, economics, and information systems. 3
The Internet is growing rapidly in terms of both use and infrastructure. Unfortunately, demand is outpacing the capacity of the infrastructure, as evidenced by unacceptably long response times. To support current load and further growth, we must address this problem. Several caching strategies have been proposed in the literature; many have been implemented to improve the quality of service on the Web. In this paper, we identify the main causes of delay on the Web, and provide a review of the various caching strategies employed to mitigate these delays. We also survey the application of Operations Research/Management Science (OR/MS) techniques to caching on the Web. Finally, we identify several open OR/MS research problems related to Web caching.
Internet-enabled markets are becoming viable venues for procurement of professional services. We investigate bidding behavior within the most active area of these early knowledge markets---the market for software development. These markets are important both because they provide an early view of the effectiveness of online service markets and because they have a potentially large impact on how software development services are procured and provided. Using auction theory, we develop a theoretical model that relates market characteristics to bidding and transaction behavior, taking into account costly bidding. We then test our model using data from an active online market for software development services, which yields contracts for 30%--40% of posted projects. In its current format, however, the studied market may induce excessive bidding by vendors. Consistent with our theoretical predictions and those of Carr (2003), higher-value projects attract significantly more bids, with lower average quality. Greater numbers of bids raise the cost to all participants, due to costly bidding and bid evaluation. Perhaps as a consequence, higher-value projects are also much less likely to be awarded.
We analyze a revenue management problem in which a seller facing a Poisson arrival stream of consumers operates an online multiunit auction. Consumers can get the product from an alternative list price channel. We consider two variants of this problem: In the first variant, the list price is an external channel run by another firm. In the second one, the seller manages both the auction and the list price channels.
Each consumer, trying to maximize his own surplus, must decide either to buy at the posted price and get the item at no risk, or to join the auction and wait until its end, when the winners are revealed and the auction price is disclosed.
Our approach consists of two parts. First, we study structural properties of the problem, and show that the equilibrium strategy for both versions of this game is of the threshold type, meaning that a consumer will join the auction only if his arrival time is above a function of his own valuation. This consumer’s strategy can be computed using an iterative algorithm in a function space, provably convergent under some conditions. Unfortunately, this procedure is computationally intensive.
Second, and to overcome this limitation, we formulate an asymptotic version of the problem, in which the demand rate and the initial number of units grow proportionally large. We obtain a simple closed-form expression for the equilibrium strategy in this regime, which is then used as an approximate solution to the original problem. Numerical computations show that this heuristic is very accurate. The asymptotic solution culminates in simple and precise recipes of how bidders should behave, as well as how the seller should structure the auction, and price the product in the dual-channel case.
The ever-widening reach of Internet has led to the proliferation of e-services. These e-services are sprouting in the form of portals and e-business web sites. Some of these e-services interact amongst themselves and undergo service composition to offer other complex services. Next generation e-services would undertake dynamic service composition because of the multiple benefits this model of operation provides. In addition, these e-services have varied implementations which makes managing these e-services a challenging task. These web based e-services also operate on line and would need continuous monitoring and control. This paper proposes and describes an e-service management solution itself as a web based e-service that enables remote management of e-services in a uniform platform independent manner.
A proper understanding of the general nature, potential and obligations of electronic services may be achieved by examining existing commercial services in detail. The everyday services that surround us, and the ways in which we engage with them, are the result of social and economic interaction that has taken place over a long period of time. If we attempt to provide electronic services, and do not take this history into account, then we will fail. Any attempt to provide automated electronic services that ignores this history will deny consumers the opportunity to negotiate and refine, over a large range of issues, the specific details of the actual service to be provided. To succeed, we require a rich and accurate means of representing services. An essential ingredient of service representation is capturing the non-functional properties of services. These include the methods of charging and payment, the channels by which the service is requested and provided, constraints on temporal and spatial availability, service quality, security, trust and the rights attached to a service. Not only are comprehensive descriptions essential for useful service discovery, they are also integral to service management, enabling service negotiation, composition, and substitution. This paper builds on an understanding of services and their interactions, to outline the non-functional properties of services and their uses.
The benefits of living in a fast changing information society become evident if effective ebusiness
practices are implemented, offering companies exposure and access to global
markets and consumer access to customized, high quality services. Such practices are
facilitated by innovative and effective e-business models. However, the business literature
defines business models from different viewpoints, each focusing on different components.
This leads to a fragmented and confusing picture regarding the shape and role of e-business
models and the factors that distinguish successful business models. This paper explains why a
more holistic approach to the study of e-business models is called for and proposes such an
approach enabled by the examination of five thematic areas in the development and adoption
of a business model: technical, individual, organizational, industrial, societal. A case study is
examined in order to prove the appropriateness and importance of the proposed approach in
the context of mobile business.
Quantitative models have proved valuable in predicting con- sumer behavior in the offline world. These same techniques can be adapted to predict online actions. The use of diffusion models provides a firm foundation to implement and forecast viral marketing strategies. Choice models can predict pur- chases at online stores and shopbots. Hierarchical Bayesian models provide a framework for implementing versioning and price-segmentation strategies. Bayesian updating is a natural tool for profiling users with clickstream data. A key challenge for practitioners of Internet marketing is to extract value from the huge volume of data that can be collected. These tech- niques illustrate how this information can be leveraged to cre- ate better decisions.
This paper describes a portable system to support a new way of visiting cultural and tourist sites. The perspective is that the visitor moves in a physical space like a museum, while seeking information and guidance through the use of a hand-held electronic guide. Techniques are presented to adapt the content of the presentations to the particular visitor, place, and moment of visit (that is, taking into account the user model, knowledge of the physical location and the physical space around it, and the history of previous interactions).
This chapter presents an ontology for e-Business models that is based on an extensive literature review. It aims to present the fusion of the ideas in the business model literature. These ideas of enterprise ontologies create an appropriate basis for the development of a range of new management tools in the e-Business domain. By merging the conceptually rich business model approach with the more rigorous ontological approach and by applying them to e-Business, an appropriate foundation for tools can be achieved that would allow the understanding, sharing and communication, change, measuring and simulation of e-Business models. The chapter proposes an e-Business model ontology that highlights the relevant e-Business issues and elements that firms have to think of to operate successfully in the Internet era.
This paper sets out to explain the vital role of an operations strategy in e-business. Suggests, through various research findings, that a firm can employ a number of operations strategies, and that they each possess certain core building blocks. Further, when properly combined, these strategies can be customised to a particular situation and offer substantial benefits for an organisation in driving e-business best practices. The paper gives definitions and descriptions of operations management, e-business, e-operations and an operations strategy for e-business. The work is also supported by empirical research data in the form of a small case study.
HIPS is a project recently funded by the European Commission within the I-Cube initiative whose main aim is to study new technologies and interaction modalities that allow people to navigate both a physical space and a related information space at the same time, with a minimal gap between the two. The project envisages a portable electronic tour guide (to exhibitions, museums, archaeological sites, expositions distributed over a city, and to cities themselves) which empowers visitors to determine themselves the structure of a tour, according to their own criteria, interests and needs and which allow different information delivery modalities.
Combinatorial auctions have two features that greatly affect their design: computational complexity of winner determination and opportunities for cooperation among competitors. Dealing with these forces trade-offs between desirable auction properties such as allocative efficiency, revenue maximization, low transaction costs, fairness, failure freeness, and scalability. Computational complexity can be dealt with algorithmically by relegating the computational burden to bidders, by maintaining fairness in the face of computational limitations, by limiting biddable combinations, and by limiting the use of combinatorial bids. Combinatorial auction designs include single-round, first-price sealed bidding, Vickrey-Clarke-Groves (VCG) mechanisms, uniform and market-clearing price auctions, and iterative combinatorial auctions. Combinatorial auction designs must deal with exposure problems, threshold problems, ways to keep the bidding moving at a reasonable pace, avoiding and resolving ties, and controlling complexity.
Message filtering is one of the techniques that can help achieve scalability of wireless communication and, eventually, mobile commerce. The core of message filtering is filtering decision-making: to make decisions as to whether a specific message should be filtered or not. The filtering decision is multicriteria decision making in nature, such as analytic hierarchy process (AHP) which ranks a set of alternatives and the choice of a preferred one. Under context-aware situations, however, we are concerned that the number of contextual states is too big, resulting in an AHP model that is too big to compute efficiently. Moreover, in such a situation, user preferences on filtering are dynamic or temporal, according to the change of contexts. Hence, an idea of context-aware message filtering is proposed in this paper. However, to handle a large set of AHP models, each of which fits a specific contextual state, is still difficult. Hence, in this paper, we propose a methodology for intelligent context-aware message filtering by applying a case-based reasoning that learns to adapt to the inexact matching and AHP. Moreover, a default AHP model is generated from the user's personal preference ontology. The default AHP model is refined according to the user's feedback to revise the case base.
Several telecommunication service providers are currently supplying data access services to mobile users who may connect and disconnect at any time. In order to ensure a high level of service, these firms must consider both load management issues as well as data access costs. We formulate several combinatorial optimization problems that arise in this context. In these problems, each user specifies a time interval during which data access is needed. The focus of our work is on two types of offline problems where each mobile user must be assigned a local base station. The first type considers this assignment problem under load constraints. The other seeks to minimize data access costs while satisfying the load constraints. When all the users connect at the same time, we show that the problems can be solved efficiently. However, if there are two or more distinct connect times, the problems become computationally intractable. For such problems, approximation algorithms with proven performance guarantees are presented. We also identify some special cases which can be solved efficiently.
Mobile advertising complements the Internet and interactive television advertising and makes it possible for advertisers to create tailor-made campaigns targeting users according to where they are, their needs of the moment and the devices they are using (i.e. contextualized mobile advertising). Therefore, it is necessary that a fully personalized mobile advertising infrastructure be made. In this paper, we present such a personalized contextualized mobile advertising infrastructure for the advertisement of commercial/non-commercial activities. We name this infrastructure MALCR, in which the primary ingredient is a recommendation mechanism that is supported by the following concepts: (1) minimize users' inputs (a typical interaction metaphor for mobile devices) for implicit browsing behaviors to be best utilized; (2) implicit browsing behaviors are then analyzed with a view to understanding the users' interests in the values of features of advertisements; (3) having understood the users' interests, Mobile Ads relevant to a designated location are subsequently scored and ranked; (4) Top-N scored advertisements are recommended. The recommendation mechanism is novel in its combination of two-level Neural Network learning, Neural Network sensitivity analysis, and attribute-based filtering. This recommendation mechanism is also justified (by thorough evaluations) to show its ability in furnishing effective personalized contextualized mobile advertising.
These days, Internet-based electronic marketplaces (EMs) are getting more and more popular. They emerge in different industries, supporting the exchange of goods and services of different kinds, with and for different types of actors, and are following different architectural principles. Most observers have assumed that EM would come to dominate the e-business landscape. Once you look beyond the publicity, however, you quickly see that most EMs are struggling. The supply chain dimension of an EM is largely neglected and poorly managed, while basic logistics operation is currently hampering turnover and revenues. The Paper at hand examines, based on a critical literature review, the actual EM discussion and calls for more supply chain management research within this field.
Advances in wireless network technology and the continuously increasing number of users of hand-held terminals make the latter a possible channel for offering personalized services to mobile users and give pace to the rapid development of mobile electronic commerce (MEC). MEC operates partially in a different environment than Internet e-commerce due to the special characteristics and constraints of mobile terminals and wireless networks and the context, situations and circumstances in which people use their hand-held terminals. In this paper, we discuss the business models in MEC and transaction modeling issues pertinent for the business models and the environment.
Electronic marketplaces represent a significant example for the evolution of the Internet from technical infrastructure to business enabler. Built on top of open standards like XML and value-added services like catalogue, negotiation, and transaction management, electronic marketplaces are the new hubs for business interaction. In first-generation electronic marketplaces service providers post information about their products, and service consumers post information about their needs. The matching is based on a market-dependent ontology, and standardised negotiation processes are supported by market mechanisms like auctions and exchanges. The final result is a one-to-one business relationship managed directly by the parties, outside the boundaries of the electronic marketplace. For second-generation electronic marketplaces the focus shifts to complete solutions. The capability to aggregate multiple services in order to match a specific service request should be provided as an internal service from electronic marketplaces. As an alternative, the electronic marketplaces should at least enable specific service providers to sustain effectively aggregation-oriented business models. After an overview of electronic marketplaces, we introduce the concept of e-services as electronic virtualisation of standard business services. We then present DySCo (Dynamic Service Composer), which includes a model and a reference infrastructure for e-service management and composition. Based on DySCo, a prototype has been developed for dynamic service aggregation through negotiation in multiple marketplaces. The prototype is presented, and the implications of the underlying business model are discussed.
We explore the generation of interactive computer graphics at digital set-top boxes in place of the fixed graphics that were embedded to the television video before the broadcast. This direction raises new requirements for user interface development, since the graphics are merged with video at each set-top box dynamically, without the traditional quality control from the television producers. Besides the technical issues, interactive computer graphics for television should be evaluated by television viewers. We employ an animated character in an interactive music television application that was evaluated by consumers, and was developed using the Virtual Channel Control Library, a custom high-level API, that was built using Microsoft Windows and TV technologies.
Present work introduces two network design algorithms for planning UMTS (Universal Mobile Telecommunication System) access networks. The task is to determine the cost-optimal number and location of the Radio Network Controller nodes and their connections to the Radio Base Stations (RBS) in a tree topology according to a number of planning constraints. First, a global algorithm to this general problem is proposed, which combines a metaheuristic technique with the solution of a specific b-matching problem. It is shown how a relatively complex algorithm can be performed within each step of a metaheuristic method still in reasonable time. Then, another method is introduced that is able to plan single RBS-trees. It can also be applied to make improvements on each tree created by the first algorithm. This approach applies iterative local improvements using branch-and-bound with Lagrangian lower bound. Eventually, it is demonstrated through a number of test cases that these algorithms are able to reduce the total cost of UMTS access networks, also compared to previous results.
This paper describes work carried out as part of the GUIDE project at Lancaster University. The overall aim of the project is to develop a context-sensitive tourist guide for visitors to the city of Lancaster. Visitors are equipped with portable GUIDE units which in turn provide interactive services and dynamically tailored web based information reflecting the visitor's preferences and environmental context. In contrast to existing tourist systems all information in GUIDE is obtained dynamically using a city-wide wireless network infrastructure. In this paper we focus on the design of the GUIDE information model. The model presented is novel by virtue of the fact that it enables both geographic and contextual information to be captured. The paper also describes our development of an efficient broadcast mechanism which enables visitors' requests for information to be serviced quickly despite the wireless communications infrastructure employed.
This paper describes a portable system lo support a new way of visiting cultural and tourist sites. The perspective is that the visitor moves in a physical space like a museum, while seeking information and guidance through the use of a hand-held electronic guide. Techniques are presented to adapt the content of the presentations to the particular visitor, place, and moment of visit (that is, taking into account the user model, knowledge of the physical location and the physical space around it, and the history of previous interactions).
revious work on the solution to analytical electronic customer relationship management (eCRM) problems has used either data-mining (DM) or optimization methods, but has not combined the two approaches. By leveraging the strengths of both approaches, the eCRM problems of customer analysis, customer interactions, and the optimization of performance metrics (such as the lifetime value of a customer on the Web) can be better analyzed. In par- ticular, many eCRM problems have been traditionally addressed using DM methods. There are opportunities for optimization to improve these methods, and this paper describes these opportunities. Further, an online appendix (mansci.pubs.informs.org/ecompanion.html) describes how DM methods can help optimization-based approaches. More generally, this paper argues that the reformulation of eCRM problems within this new framework of analysis can result in more powerful analytical approaches. (Data Mining; Optimization; eCRM Applications)