Peter Bodorik

Supporting the e-business readiness of small and medium-sized enterprises: approaches and metrics

Government initiatives are continuously being designed to create stable and supportive environments for developing new industries. Presents a conceptual model for use by governments in creating and sustaining an appropriate climate that facilitates the national adoption of e‐business. It focuses specifically on the needs of small and medium‐sized enterprises (SMEs). Also suggests six categories of e‐business readiness metrics and measures to be used for assessing how a country is performing in terms of providing a positive e‐business readiness climate. Examples of innovative initiatives are provided from Canada, The Netherlands, Norway, and Singapore. Concludes that a balance among attention to infrastructure components has not yet been achieved in these countries.

Enabling and measuring electronic customer relationship management readiness

This work provides a comprehensive customer-focused evaluation framework that businesses can use to assess their electronic customer relationship management (e-CRM) readiness. The framework is intended to provide a big picture of the overall composition of e-CRM, to facilitate gap analysis, and to support a monitoring and feedback process. Knowledge management, trust, and technology are identified as key enablers of e-CRM. Finally, we propose weighting and rating scales to aid in assessing customer relationship management readiness, and provide examples of their use.

Developing Internet e-commerce benchmarks

Abstract A benchmark is a standard for measuring and comparing the performance of like systems. For new product makers, a benchmark can provide important statistical information so products can be fine-tuned before their deployment. For end users, on the other hand, a benchmark can be used to compare the strengths and weaknesses of different products so that an informed decision can be made about system adoption. Benchmarks aid in estimations of scalability in terms of the number of users and/or transactions that a system can support, and system response times under various loads and hardware/software deployment platforms. This paper focuses on the design issues in developing benchmarks for e-commerce. Because of the multidisciplinary aspects of e-commerce and the various emerging and distinct e-commerce business models, creating a single benchmark for the e-commerce application is not feasible. Add to this the diverse needs of small to medium enterprises (SMEs) and big business and we motivate the need for a benchmark suite for e-commerce. It is the thesis of this paper that the business model plays the primary role in the development of a e-commerce benchmark. It is the business that determines processes and transactions and thus also the database and navigational designs. For illustrative purposes, we step through the design of an e-commerce benchmark specification, WebEC, based on a e-broker (cybermediary) Internet business model. An example implementation of the benchmark specification, based on Microsofts COM technology, and sample benchmark results are also presented.

Making business sense of electronic commerce

Although its infrastructure is still very young, e-commerce continues to create new business models and innovative marketing and technology strategies. To avoid unraveling their core processes, organizations considering e-commerce applications must take time out to evaluate the many facets of adoption and integration. Arguments for not investing in e-commerce are rapidly dissolving. It is now widely accepted that a business cannot ignore e-commerce investment without incurring heavy penalties over the long run. We believe organizations that want to invest in e-commerce must have a significantly higher degree of technological fluency and a bolder approach to experimentation with unfamiliar business models than they would for investments in other areas. Successfully exploiting e-commerce requires creatively linking an organizations strategy and its supporting technology as well as managing pervasive IT applications that change very quickly and are becoming increasingly integrated and convergent. Only then can enterprises achieve the flexible and adaptive behavior that is central to effective e-commerce.

Deciding to correct distributed query processing

Most algorithms for determining query processing strategies in distributed databases are static in nature; that is, the strategy is completely determined on the basis of a priori estimates of the size of intermediate results, and it remains unchanged throughout its execution. The static approach may be far from optimal because it denies the opportunity to reschedule operations if size estimates are found to be inaccurate. Adaptive query execution may be used to alleviate this problem. A low overhead delay method is proposed to decide when to correct a strategy. Sampling is used to estimate the size of relations, and alternative heuristic strategies prepared in a background mode are used to decide when to correct. Evaluation using a model of a distributed database indicates that the heuristic strategies are near optimal. Moreover, it also suggests that it is usually correct to abort creation of an intermediate relation which is much larger than predicted. >

Government support for the e-readiness of small and medium sized enterprises

Government initiatives are continuously being designed to create stable and supportive environments for developing new industries, enhancing the global competitiveness of companies, promoting innovation and fostering fair competition. Because of its significant potential, electronic business (e-business) is now the focus of efforts in many countries, and governments are beginning to play a critical role in nurturing the e-readiness of various industry sectors. This paper presents a conceptual model for creating and sustaining an appropriate e-readiness climate that facilitates the national adoption of e-business. It focuses specifically on the needs of small and medium-sized enterprises (SMEs) and showcases various government e-readiness initiatives aimed at them. The paper also suggests six categories of e-readiness metrics/measures to be used for assessing how a country is performing in terms of providing a positive e-readiness climate for businesses/citizens.

PeCAN: An architecture for users' privacy-aware electronic commerce contexts on the semantic web

Supporting e-Commerce on the Semantic Web implies more sophisticated integration of Web services, agent interaction, domain ontologies, and data markup languages than is being done on todays Web. We explore user e-commerce, trust, and privacy scenarios and provide a vision for future e-commerce interactions with a more informed and in-control user. We present the Personal Context Agent Networking (PeCAN) knowledge architecture consisting of client-side and web-side architectural data components and services which inform the user of online privacy and trust within e-commerce tasks. A novel organization scheme and the composition of user contexts in this environment are proposed. Client-side ontologies and data structures for representing user contexts are introduced. For proof of concept, we describe a data belief ontology and illustrate PeCANs compliance to the P3P privacy data schema. We use OWL as an implementation basis for maintaining privacy-aware e-commerce contextual knowledge for effective agent action in the PeCAN environment. Categories and Subject Descriptors: Semantic Web Application Architecture, Web Information Systems Applications, Electronic Privacy, Decision Support System Application

Distributed query processing optimization objectives

The authors examine objectives, or measures of cost, which can be used in optimizing queries in a distributed database (DDB). They include the delay and dollar cost due to the network data transfer, CPU processing or a combination of both, and cost measures in terms of the size of partial results. These measures are used in distributed query processing modeling on a testbed of queries to examine the effect of choosing one measure of cost in optimizing strategies on their cost expressed in other measures and the cost of strategies generated by a two-phased approach. Results indicate that best strategies are generated when optimization considers cost measured in terms of both CPU processing and a network data transfer. They also confirm that the two-phased optimization yields close to optimal strategies.<<ETX>>

Heuristic algorithms for distributed query processing

This paper examines heuristic algorithms for processing distributed queries using generalized joins. As this optimization problem is NP-hard heuristic algorithms are deemed to be justified. A heuristic algorithm to form/formulate strategies to process queries is presented. It has a special property in that its overhead can be “controlled”: The higher its overhead the better the strategies it produces. Modeling on a test-bed of queries is used to demonstrate that there is a trade-off between the strategys execution and formulation delays. The modeling results also support the notion that simple greedy heuristic algorithms such as are proposed by many researchers are sufficient in that they are likely to lead to near-optimal strategies and that increasing the overhead in forming strategies is only marginally beneficial. Both the strategy formulation and execution delays are examined in relation to the number of operations specified by the strategy and the total size of partial results.

Consistent privacy preferences (CPP): model, semantics, and properties

The Platform for Privacy Preferences (P3P) is a W3C specification that can be used to build useful protocols and services for protecting user privacy on the semantic Web. An outstanding issue is the need for a simple and efficient representation and management of consistent sets of rules for user privacy preferences. Thus we describe a model for privacy preference representation and management that has a number of desirable properties which are lacking in privacy preference models proposed thus far. We detail semantics and properties of matching preference rules with requests. We specify the properties of a consistent set of privacy preferences, and propose maintenance operations. Finally, we describe an implementation of our proposal that uses OWL (Web Ontology Language) and the Jena reasoning engine to illustrate the practicality of managing consistent user preferences in privacy rule-sets. An important advantage of our approach is that the user is encouraged to clarify privacy preferences as he/she modifies them as part of a back-end management task, as opposed to mainly at website interaction times.