Information systems in supply chain integration and management

Performance measures and metrics are essential for effectively managing logistics operations, particularly in a competitive global economy. The global economy is featured with global operations, outsourcing and supply chain and e-commerce. The real challenge for managers of this new enterprise environment is to develop suitable performance measures and metrics to make right decisions that would contribute to an improved organizational competitiveness. Now the question is whether traditional performance measures can be used and out of them which ones should be given priority for measuring the performance in a new enterprise environment. Some of the traditional measures and metrics may not be suitable for the new environment wherein many activities are not easily identifiable. Measuring intangibles and nonfinancial performance measures pose the greater challenge in the so-called knowledge economy. Nevertheless, measuring them is so critical for the successful operations of companies in this environment. Con...

Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995–2004) for research and applications

Nowadays, numerous journals and conferences have published articles related to context-aware systems, indicating many researchers' interest. Therefore, the goal of this paper is to review the works that were published in journals, suggest a new classification framework of context-aware systems, and explore each feature of classification framework. This paper is based on a literature review of context-aware systems from 2000 to 2007 using a keyword index and article title search. The classification framework is developed based on the architecture of context-aware systems, which consists of the following five layers: concept and research layer, network layer, middleware layer, application layer and user infrastructure layer. The articles are categorized based on the classification framework. This paper allows researchers to extract several lessons learned that are important for the implementation of context-aware systems.

Context-aware systems

Security lapses and the omission of information security measures: A threat control model and empirical test

Human resources are the most important among all the resources an organization owns. To retain efficient and experienced workforce in an organization is very crucial in overall performance of an organization. Motivated employees can help make an organization competitively more value added and profitable. The present study is an attempt to find out the major factors that motivate employees and it tells what is the relationship among reward, recognition and motivation while working within an organization. The data were collected from employees of diverse type of organizations to gain wide representation of sectoral composition. In all, 250 self administered questionnaires were distributed among the employees of different sectors and they returned 220 completed useable questionnaires for response rate of 88%. The participation in survey was voluntary and confidentiality of responses was ensured. The statistical analysis showed that different dimensions of work motivation and satisfaction are significantly correlated and reward and recognition have great impact on motivation of the employees. Implications of the study for managers and policy makers in the context of human resource practices have been discussed. Limitations and guidelines for future research are also provided.

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Impact of Reward and Recognition on Job Satisfaction and Motivation: An Empirical Study from Pakistan

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.

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

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.

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Enabling and measuring electronic customer relationship management readiness

Developing Internet e-commerce benchmarks

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 organization's 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.

Making business sense of electronic commerce

Distributed denial of service (DDoS) attacks are a major security threat against the availability of conventional or cloud computing resources. Numerous DDoS attacks, which have been launched against various organizations in the last decade, have had a direct impact on both vendors and users. Many researchers have attempted to tackle the security threat of DDoS attacks by combining classification algorithms with distributed computing. However, their solutions are static in terms of the classification algorithms used. In fact, current DDoS attacks have become so dynamic and sophisticated that they are able to pass the detection system thereby making it difficult for static solutions to detect. In this paper, we propose a dynamic DDoS attack detection system based on three main components: 1) classification algorithms; 2) a distributed system; and 3) a fuzzy logic system. Our framework uses fuzzy logic to dynamically select an algorithm from a set of prepared classification algorithms that detect different DDoS patterns. Out of the many candidate classification algorithms, we use Naive Bayes, Decision Tree (Entropy), Decision Tree (Gini), and Random Forest as candidate algorithms. We have evaluated the performance of classification algorithms and their delays and validated the fuzzy logic system. We have also evaluated the effectiveness of the distributed system and its impact on the classification algorithms delay. The results show that there is a trade-off between the utilized classification algorithms’ accuracies and their delays. We observe that the fuzzy logic system can effectively select the right classification algorithm based on the traffic status.

Peter Bodorik

Papers

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

Enabling and measuring electronic customer relationship management readiness

Developing Internet e-commerce benchmarks

Making business sense of electronic commerce

DDoS Detection System: Using a Set of Classification Algorithms Controlled by Fuzzy Logic System in Apache Spark