The Effects of Departmental and Positional Power on Job Evaluation Outcomes: A Dual-Level Analysis of Power and Resource Allocation

We replicate research from two separate power and resource allocation research streams to test whether job evaluation outcomes at a university are simultaneously susceptible to effects of power held at both the group (i.e., academic department) and individual (i.e., a job\u27s hierarchical position) levels. In doing so, we illustrate limitations of the dominant rational model of research in job evaluation and, more generally, how dual levels of analysis can illuminate the relationship between power and resource allocation. We then investigate whether departmental and positional power interact in the allocation of resources at both levels. Results from six years of job evaluation data indicate that job evaluation outcomes are highly susceptible to both departmental and positional power. Moreover, our results suggest that positional power moderated the effect of departmental power on group level job evaluation successes. Drawing on our dual-level analysis, we propose a new model of power, resource allocation, and the perpetuation of power

Rational and Coalition Models of Job Evaluation: Do More Powerful University Departments Have an Advantage?

Job evaluation research has, to date, focused on the individual as the unit of analysis. After approximately 50 years of study, evidence on the basic assumptions supporting job evaluation is still inconclusive. This study expands the research by employing organizational theory to the topic and studying job evaluation at the group level. Prior work on rational and coalition models of resource allocation is used to develop hypotheses that are tested with six years of job evaluation data from a university. The results support the coalition model and the conclusion that departmental power can affect job evaluation outcomes

Challenges to the Integration of Renewable Resources at High System Penetration

Successfully integrating renewable resources into the electric grid at penetration levels to meet a 33 percent Renewables Portfolio Standard for California presents diverse technical and organizational challenges. This report characterizes these challenges by coordinating problems in time and space, balancing electric power on a range of scales from microseconds to decades and from individual homes to hundreds of miles. Crucial research needs were identified related to grid operation, standards and procedures, system design and analysis, and incentives, and public engagement in each scale of analysis. Performing this coordination on more refined scales of time and space independent of any particular technology, is defined as a “smart grid.” “Smart” coordination of the grid should mitigate technical difficulties associated with intermittent and distributed generation, support grid stability and reliability, and maximize benefits to California ratepayers by using the most economic technologies, design and operating approaches

Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

Restructuring of Human Resource Management In The U.S.: Strategic Diversity

Change is endemic in the U. S. economy and in worker-management relations. This change can be examined from the perspective of increasing centralization in which public policy dictates that corporations and the state act in concert, to a decentralized market system in which assets are constantly being reconfigured to more productive uses. This paper looks at the evolution of industrial relations and personnel administration to human resource management within this context of continual change through centralized versus decentralized perspectives. Major shifts in HR policies in American companies are described. Within these major shifts, a wide diversity of policy options for workermanagement relations exist. A strategic-contingency model may provide a unifying framework to assist decision makers in choosing among these policy options

Decision Support Tools for Cloud Migration in the Enterprise

This paper describes two tools that aim to support decision making during the migration of IT systems to the cloud. The first is a modeling tool that produces cost estimates of using public IaaS clouds. The tool enables IT architects to model their applications, data and infrastructure requirements in addition to their computational resource usage patterns. The tool can be used to compare the cost of different cloud providers, deployment options and usage scenarios. The second tool is a spreadsheet that outlines the benefits and risks of using IaaS clouds from an enterprise perspective; this tool provides a starting point for risk assessment. Two case studies were used to evaluate the tools. The tools were useful as they informed decision makers about the costs, benefits and risks of using the cloud.Comment: To appear in IEEE CLOUD 201

Models of everywhere revisited: a technological perspective

The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and nonlinearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment

Collaborative model development increases trust in and use of scientific information in environmental decision-making

While science matters for environmental management, creating science that is credible, salient to decision-makers, and deemed legitimate by stakeholders is challenging. Collaborative modeling is an increasingly-used approach to enable effective science-based decision-making. This work evaluates the modeling process conducted for two hydropower dam licensing negotiations, to explore how differences in the collaborative development of hydrological models affected differences in their use in subsequent decision-making. In one case, the model was developed iteratively through deliberation with stakeholders. Consequently, stakeholders understood the model and its limitations and trusted the model and modelers; the model itself was also better designed to evaluate resource managers’ questions. The collaboratively-developed model became the focal point for subsequent negotiations and enabled creative group problem-solving. Conversely, in the case with less engagement during model development, the model was not used subsequently by decision-makers. These differences are argued to result from trust built during the modeling process, applicability of the model to test real management scenarios, and the broader social context in which the models were used