An agent‐based approach for managing e‐commerce activities

In this article, we propose an agent‐based approach for managing e‐commerce activities. In our approach, an agent is present in each e‐commerce site, managing the information stored there. In addition, another agent is associated with each customer, handling his/her profile. The proposed approach is based on the use of a particular conceptual model called the Behaviour‐Semantic Distance and Relevance (B‐SDR) network, which is capable of uniformly representing and handling information stored in e‐commerce sites and customer profiles. The capabilities of the B‐SDR network model are exploited to let customer and site agents cooperate in such a way in order to support a customer in identifying, whenever he/she accesses an e‐commerce site, those products and services present in the site itself and for better matching his/her interests. The approach has been implemented in a prototype in which its functionalities are discussed here also. © 2004 Wiley Periodicals, Inc.     

Specification and testing of autonomous agents in e‐commerce systems

This paper presents a generic formal framework to specify and test autonomous e‐commerce agents. First, the formalism to represent the behaviour of agents is introduced. The corresponding machinery to define how implementations can be tested follows. Two testing approaches are considered. The first of them, which can be called active, is based on stimulating the implementation under test (IUT) with a test. The peculiarity is that tests will be defined as a special case of autonomous e‐commerce agent. The second approach, which can be called passive, consists of observing the behaviour of the tested agent in an environment containing other agents. As a case study the framework is applied to the e‐commerce system Kasbah. Copyright © 2005 John Wiley & Sons, Ltd.     

Assessing e‐commerce systems success: a respecification and validation of the DeLone and McLean model of IS success

Abstract. DeLone & McLean (2003) propose an updated information systems (IS) success model and suggest that it can be extended to investigating e‐commerce systems success. However, the updated IS success model has not been empirically validated in the context of e‐commerce. Further, the existing IS/e‐commerce success models have been subject to considerable debate on the ‘IS Use’ and ‘Perceived Usefulness’ constructs, and the nomological structure of the updated DeLone and McLean model is somewhat inconsistent with the IS acceptance and marketing literature. Based on the IS and marketing literature, this paper respecifies and validates a multidimensional model for assessing e‐commerce systems success. The validated model consists of six dimensions: Information Quality, System Quality, Service Quality, Perceived Value, User Satisfaction and Intention to Reuse. Structural equation modelling techniques were applied to data collected by questionnaire from 240 users of e‐commerce systems in Taiwan. The empirical evidence suggests that Intention to Reuse is affected by Perceived Value and User Satisfaction, which, in turn, are influenced by Information Quality, System Quality and Service Quality. The nomological structure of the respecified e‐commerce systems success model is concurred with that of the technology acceptance model (TAM) in the IS field and the consumer behaviour models in the traditional business‐to‐business and retail contexts. The findings of this study provide several important implications for research and practice. This paper concludes by discussing the contributions of this study and the limitations that could be addressed in future studies.     

Developing community capability for e‐commerce development in rural China: A resource orchestration perspective

Community capability enables a large number of rural citizens to cooperatively engage in e‐commerce as an e‐commerce cluster, and it thus plays a critical role in e‐commerce development in the rural regions of developing countries. Taking the resource orchestration perspective as the theoretical lens, this study investigates the process for developing community capability. Two cases of community capability development in rural Chinese villages are studied. The findings reveal two settings for community capability development—government supported and self‐orchestrated—and show that community capability is developed through the individual capabilities of lead users and the resource orchestration interactions of stakeholders. This study has theoretical implications because it reveals the importance of developing community capability by orchestrating resources beyond merely providing training and education to rural community members and because it identifies the processes for developing community capability in the two respective settings. It also extends the resource orchestration perspective from a single‐firm context to a community context by revealing the resource orchestration interactions.     

e‐Learning recommender system for a group of learners based on the unified learner profile approach

In the age of information explosion, e‐learning recommender systems (eL_RSs) have emerged as effective information filtering techniques that attempt to provide the most appropriate learning resources for learners while using e‐learning systems. These learners are differentiated on the basis of their learning styles, goals, knowledge levels and others. Several attempts have been made in the past to design eL_RSs to recommend resources to individuals; however, an investigation of recommendations to a group of learners in e‐learning is still in its infancy. In this paper, we focus on the problem of recommending resources to a group of learners rather than to an individual. The major challenge in group recommendation is how to merge the individual preferences of different learners that form a group and extract a pseudo unified learner profile (ULP) that closely reflects the preferences of all learners. Firstly, we propose a profile merging scheme for the ULP by utilizing learning styles, knowledge levels and ratings of learners in a group. Thereafter, a collaborative approach is proposed based on the ULP for effective group recommendations. Experimental results are presented to demonstrate the effectiveness of the proposed group recommendation strategy for e‐learning.     

Belief‐rule‐based expert systems for evaluation of e‐government: a case study

Little knowledge exists on the impact and results associated with e‐government projects in many specific‐use domains. Therefore, it is necessary to evaluate the efficiency and effectiveness of e‐government systems. Because the development of e‐government is a continuous process of improvement, it requires continuous evaluation of the overall e‐government system as well as evaluation of its various dimensions such as determinants, characteristics and results. E‐government development is often complex, with multiple stakeholders, large user bases and complex goals. Consequently, even experts have difficulties in evaluating these systems, especially in an integrated and comprehensive way, as well as on an aggregate level. Expert systems are a candidate solution to evaluate such complex e‐government systems. However, it is difficult for expert systems to cope with uncertain evaluation data that are vague, inconsistent, highly subjective or in other ways, challenging to formalize. This paper presents an approach that can handle uncertainty in e‐government evaluation: the combination of Belief Rule Base knowledge representation and Evidential Reasoning. This approach is illustrated with a concrete prototype, known as the Belief Rule Based Expert System (BRBES) and implemented in the local e‐government of Bangladesh. The results have been compared with a recently developed method of evaluating e‐government, and it is demonstrated that the results of the BRBES are more accurate and reliable. The BRBES can be used to identify the factors that need to be improved to achieve the overall aim of an e‐government project. In addition, various ‘what if’ scenarios can be generated, and developers and managers can obtain a foretaste of the outcomes. Thus, the system can be used to facilitate decision‐making processes under uncertainty.     

A logical foundation for the case‐based reasoning cycle

Case‐based reasoning (CBR) has drawn considerable attention in artificial intelligence (AI) fields with many successful applications in systems such as e‐commerce and multiagent systems. For the moment, research and development of CBR basically follows the traditional process model of CBR, i.e., the R⁴ model and problem space model introduced in 1994 and 1996, respectively. However, there has been no logical analysis for this popular CBR model. This article will fill this gap by providing a unified logical foundation for the CBR cycle. The proposed approach is based on an integration of traditional mathematical logic, fuzzy logic, and similarity‐based reasoning. At the same time, we examine the CBR cycle from the knowledge‐based (KB) viewpoint. The proposed logical approach can facilitate research and development of CBR. © 2003 Wiley Periodicals, Inc.     

Resolving uncertainty and creating value from the exercise of e‐commerce investment options

This study examines the effect of the resolution of uncertainty on real options exercise decisions with respect to three e‐commerce investment options: scale‐up, stage and joint investment, and the relationship between exercise of these options and firm performance. The results of a study of 172 public e‐commerce investment announcements show that resolution of external (exogenous) and internal (endogenous) uncertainty has a significant effect on option exercise decisions. However, the results also imply that simply waiting without investment in active learning does not create significant value from real options. The key differentiator is how a firm resolves endogenous uncertainty as this endows it with the ability to successfully undertake the information technology investment and exploit the economic opportunity implied by the resolution of exogenous uncertainty. Furthermore, our results imply that different options should be used to manage situations involving certainty of loss on one hand and severity of loss on the other hand. Thus, it is important for firms to make the right choices when using options‐based investing to manage risk. We suggest that, perhaps, managers need to maintain a portfolio of options to manage the two dimensions of risk simultaneously.     

A mood‐ and situation‐based model for developing intuitive Pop music recommendation systems

Traditionally, a per‐song‐purchased base recommendation system is used on most music websites, but this method produces unsatisfactory results under various situational practices. This study proposes a hybrid procedure that includes both an expert‐attributes selection capability and a mood/situation‐attributes categorization functionality. This procedure fosters the development of a so‐called MoMusic model as an unlimited online streaming service to replace current systems and artfully provide music to interested parties. This study employs a dataset consisting of 821 songs from the 2005–2010 annual music rankings as well as songs from the top artists from 2009 to 2010 from Taiwan's popular KKBOX music streaming service. The experimental dataset was assessed and coded by domain experts, and the expert‐attributes selections and mood/situation‐attributes categorizations were used to produce recommendation lists. These recommendation lists were then paired with questionnaire‐derived music preferences from experienced users. The experimental results conclusively show that the MoMusic model is approximately twice as accurate as the random selection‐based lists and the KKBOX‐like recommendation lists and performs better than the two listed recommendation systems. The MoMusic model scores 0.889 on the usefulness evaluation, whereas the system satisfaction is 0.96. The MoMusic model has the advantages of intuitive use and high performance.     

Poverty alleviation through government‐led e‐commerce development in rural China: An activity theory perspective

This paper uses activity theoretic analyses to investigate the role of governments in developing rural e‐commerce ecosystems and the effects of such ecosystems on poverty alleviation. On the basis of a case study of Longnan, one of the poorest regions in China, this paper reports and analyses the various actions taken by local governments in nurturing, supporting, and regulating the development of a local rural e‐commerce ecosystem and using this ecosystem to transform poverty alleviation. Our study articulates a model of poverty alleviation through e‐commerce. By documenting and theorizing the mechanisms underlying rural e‐commerce development and poverty alleviation through e‐commerce as well as governments' role in developing and sustaining them, this paper contributes to establishing a “theory of the solution” to the grand challenge of poverty alleviation both in China and globally.     

Whether a retailer should enter an e‐commerce platform taking into account consumer returns

Considering consumers are increasingly shopping online nowadays and the online sales market is dominated by e‐commerce giants, traditional retailers need to choose whether to enter e‐commerce platforms. Moreover, traditional retailers need to determine whether to offer offline return services considering online return services are very popular. To address these challenges, we explore a retailer's optimal offline return strategy and channel choice of whether or not to enter a platform in the contexts of symmetric information and asymmetric information, respectively. We present conditions for the retailer to share information. Interestingly, we find that the retailer in some conditions has no motivation to improve customer satisfaction rate of offline store. Most important, we find that the retailer's channel choice depends on the magnitude of the annual service fee that is affected by offline return strategy and asymmetric information, and the offline return strategy depends on the magnitude of the average residual value of returned products.     

Documenting electronic commerce systems and software using the unified modeling language

Electronic commerce (EC) systems are complex systems consisting of cooperating heterogeneous software, hardware and database subsystems that are distributed among processing nodes [1]. They are reactive, real-time and concurrent distributed systems. They are financially critical systems since they perform distributed business functions, the success of which is very critical for the business operation. The use of well-defined specification and documentation techniques is very essential for the effective development and maintenance of these systems. In this paper, we propose the use of the unified modeling language (UML) [2] as a technique for documenting and specifying EC systems at various levels of abstractions and from different views. We believe that the use of UML ensures a better reliability and reusability of these systems.     

The effect of e‐commerce on the integration of IT structure and brand architecture

Abstract. A company's information technology (IT) structure and its brand architecture are intended to minimize transaction costs both within the organization and between the organization and its customers. Business‐to‐Consumer (B2C) e‐commerce fundamentally alters the structure of those transaction costs relevant to the IT structure and the brand architecture. We conducted a survey among 102 chief information officers and chief marketing officers in 67 of the 100 most important B2C enterprises in Austria. The results show that companies typically implement a certain set of changes in the IT structure and the brand architecture if B2C e‐commerce is highly important to them and that these changes result in a stronger integration within and between the IT structure and the brand architecture. B2C e‐commerce projects thus require closely aligned conceptual, organizational and financial measures in both areas.     

Using multimedia for e‐learning

This paper reviews 12 research‐based principles for how to design computer‐based multimedia instructional materials to promote academic learning, starting with the multimedia principle (yielding a median effect size of d = 1.67 based on five experimental comparisons), which holds that people learn better from computer‐based instruction containing words and graphics rather than words alone. Principles aimed at reducing extraneous processing (i.e., cognitive processing that is unrelated to the instructional objective) include coherence (d = 0.70), signalling (d = 0.46), redundancy (d = 0.87), spatial contiguity (d = 0.79) and temporal contiguity (d = 1.30). Principles for managing essential processing (i.e., mentally representing the essential material) include segmenting (d = 0.70), pre‐training (d = 0.46) and modality (d = 0.72). Principles for fostering generative processing (i.e., cognitive processing aimed at making sense of the material) include personalization (d = 0.79), voice (d = 0.74) and embodiment (d = 0.36). Some principles have boundary conditions, such as being stronger for low‐ rather than high‐knowledge learners.     

A Neural Network Model Based on Logical Operations

On the basis of analyzing some neural network storage capacity problems a network model comprising a new encoding and recalling scheme is presented.By using some logical operations which operate on the binary pattern strings during information processing procedure the model can reach a high storage capacity for a certain size of network framework.     

A study of e‐mail patterns

Although electronic mail is an increasingly important service, there are few empirical studies of e‐mail traffic. We have observed over 2.85 million messages passing through our departmental servers over the course of seven months, and derived distributions that approximate several important e‐mail parameters including message sizes, message senders and receivers and the burstiness of message deliveries. Our work is unique in that we also analyse message payloads: attachment content types, e‐mail redundancy, and the use of e‐mail as a sharing mechanism. These data can be used in developing e‐mail workloads for mail system engineering or benchmarking. To this end, we provide an improved version of Postmark, a small‐file Internet benchmark, that better approximates mail server characteristics. Copyright © 2007 John Wiley & Sons, Ltd.     

Comparing model checking and logical reasoning for real-time systems

We apply both model checking and logical reasoning to a real-time protocol for mutual exclusion. To this end we employ PLC-Automata, an abstract notion of programs for real-time systems. A logic-based semantics in terms of Duration Calculus is used to verify the correctness of the protocol by logical reasoning. An alternative but consistent operational semantics in terms of Timed Automata is used to verify the correctness by model checkers. Since model checking of the full model does not terminate in all cases within an acceptable time we examine abstractions and their influence on model-checking performance. We present two abstraction methods that can be applied successfully for the protocol presented.Received June 1999Accepted in revised form September 2003 by M.R. Hansen and C. B. Jones     

A scalable manufacturing process for flexible active‐matrix e‐paper displays

Abstract— A scalable manufacturing process for fabricating active‐matrix backplanes on low‐cost flexible substrates, a key enabler for electronic‐paper displays, is presented. This process is based on solution processing, ink‐jet printing, and laser patterning. A multilayer architecture is employed to enable high aperture ratio and array performance. These backplanes were combined with E Ink electrophoretic media to create high‐performance displays that have high contrast, are bistable, and can be flexed repeatedly to a radius of curvature of 5 mm.     

A logical duality for underspecified probabilistic systems

This paper establishes a Stone-type duality between specifications and infLMPs. An infLMP is a probabilistic process whose transitions satisfy super-additivity instead of additivity. Interestingly, its simple structure can encode a mix of probabilistic and non-deterministic behavior, which, as we show, is strongly related to another well-known such model: probabilistic automata. Our duality puts in relation the category of infLMPs and a category of abstract representations of them based on properties only. We exhibit a Galois connection between these categories and show that we have an adjunct pair of functors when restricted to LMPs only. Our duality also shows that an infLMP can be considered as a demonic representative of a system’s information. Moreover, it carries forward a view where states are less important, and events, or properties, become the main characters, as it should be in probability theory. Along the way, we show that bisimulation and simulation are naturally interpreted in this setting, and we exhibit the interesting relationship between infLMPs and the usual probabilistic modal logics. This paper is an extended version of a Concur ’09 paper [13]; in particular, the comparison of infLMPs with probabilistic automata and the Galois connection are new.