No Arabic abstract
There is no doubt that management practices are linked to the productivity and performance of a company. However, research findings are mixed. This paper provides a multi-disciplinary review of the current evidence of such a relationship and offers suggestions for further exploration. We provide an extensive review of the literature in terms of research findings from studies that have been trying to measure and understand the impact that individual management practices and clusters of management practices have on productivity at different levels of analysis. We focus our review on Operations Management (om) and Human Resource Management (hrm) practices as well as joint applications of these practices. In conclusion, we can say that taken as a whole, the research findings are equivocal. Some studies have found a positive relationship between the adoption of management practices and productivity, some negative and some no association whatsoever. We believe that the lack of universal consensus on the effect of the adoption of complementary management practices might be driven either by measurement issues or by the level of analysis. Consequently, there is a need for further research. In particular, for a multi-level approach from the lowest possible level of aggregation up to the firm-level of analysis in order to assess the impact of management practices upon the productivity of firms.
Information and Communication Technologies (ICT) has practically penetrated into all spheres of life. Therefore a closer look at the impact of ICT in public financial management and performance is highly justified. Public finance is defined as a field of economics concerned with paying for collective or governmental activities, and with the administration and design of those activities. Activities will be viewed as services or more precisely as public services. We believe that there is need to consider performance from the perspective of effective performance and the perceived performance. In fact the real or effective performance might not correspond to the perceived performance. A service can be considered from the perspective of the decision-maker, who in our case could be a government or a collectivity. ICT can be employed in the three phases that concern the decision-maker: design, implementation and evaluation. The beneficiaries of a service can employ ICT in any of the three phases - awareness, exploitation and assessment - for guarantying a high level of efficiency. Each phase in the environment of a service will be presented as well as illustrations of how ICT can be employed in order to improve the end-result of each one of them. We believe that a high efficiency of each phase will produce a high global efficiency. It should be noted however that the effectiveness of any system is highly dependent on the human engagement in the system. Therefore, the impact of ICT in public financial management will be felt only if the decision-makers and the end-users of the services engage themselves in the success of the system. Instead of giving a catalog of services, the focus has been on the model (or methodology) to adopt in designing services for which ICT could enhance the implementation.
Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents could offer potential for fostering sustainable organizational capabilities in the future. The project is still at an early stage. So far we have conducted a case study in a UK department store to collect data and capture impressions about operations and actors within departments. Furthermore, based on our case study we have built and tested our first version of a retail branch simulator which we will present in this paper.
AI researchers employ not only the scientific method, but also methodology from mathematics and engineering. However, the use of the scientific method - specifically hypothesis testing - in AI is typically conducted in service of engineering objectives. Growing interest in topics such as fairness and algorithmic bias show that engineering-focused questions only comprise a subset of the important questions about AI systems. This results in the AI Knowledge Gap: the number of unique AI systems grows faster than the number of studies that characterize these systems behavior. To close this gap, we argue that the study of AI could benefit from the greater inclusion of researchers who are well positioned to formulate and test hypotheses about the behavior of AI systems. We examine the barriers preventing social and behavioral scientists from conducting such studies. Our diagnosis suggests that accelerating the scientific study of AI systems requires new incentives for academia and industry, mediated by new tools and institutions. To address these needs, we propose a two-sided marketplace called TuringBox. On one side, AI contributors upload existing and novel algorithms to be studied scientifically by others. On the other side, AI examiners develop and post machine intelligence tasks designed to evaluate and characterize algorithmic behavior. We discuss this markets potential to democratize the scientific study of AI behavior, and thus narrow the AI Knowledge Gap.
For better reliability and prolonged battery life, it is important that users and vendors understand the quality of charging and the performance of smartphone batteries. Considering the diverse set of devices and user behavior it is a challenge. In this work, we analyze a large collection of battery analytics dataset collected from 30K devices of 1.5K unique smartphone models. We analyze their battery properties and state of charge while charging, and reveal the characteristics of different components of their power management systems: charging mechanisms, state of charge estimation techniques, and their battery properties. We explore diverse charging behavior of devices and their users.
Intelligent agents offer a new and exciting way of understanding the world of work. Agent-Based Simulation (ABS), one way of using intelligent agents, carries great potential for progressing our understanding of management practices and how they link to retail performance. We have developed simulation models based on research by a multi-disciplinary team of economists, work psychologists and computer scientists. We will discuss our experiences of implementing these concepts working with a well-known retail department store. There is no doubt that management practices are linked to the performance of an organisation (Reynolds et al., 2005; Wall & Wood, 2005). Best practices have been developed, but when it comes down to the actual application of these guidelines considerable ambiguity remains regarding their effectiveness within particular contexts (Siebers et al., forthcoming a). Most Operational Research (OR) methods can only be used as analysis tools once management practices have been implemented. Often they are not very useful for giving answers to speculative what-if questions, particularly when one is interested in the development of the system over time rather than just the state of the system at a certain point in time. Simulation can be used to analyse the operation of dynamic and stochastic systems. ABS is particularly useful when complex interactions between system entities exist, such as autonomous decision making or negotiation. In an ABS model the researcher explicitly describes the decision process of simulated actors at the micro level. Structures emerge at the macro level as a result of the actions of the agents and their interactions with other agents and the environment. 3 We will show how ABS experiments can deal with testing and optimising management practices such as training, empowerment or teamwork. Hence, questions such as will staff setting their own break times improve performance? can be investigated.