A multidimensional model of client success when engaging external consultants

Too often the relationship between client and external consultants is perceived as one of protagonist versus antogonist. Stories on dramatic, failed consultancies abound, as do related anecdotal quips. A contributing factor to many "apparently" failed consultancies is a poor appreciation by both the client and consultant of the client's true goals for the project and how to assess progress toward these goals. This paper presents and analyses a measurement model for assessing client success when engaging an external consultant. Three main areas of assessment are identified: (1) the consultant;s recommendations, (2) client learning, and (3) consultant performance. Engagement success is emperically measured along these dimensions through a series of case studies and a subsequent survey of clients and consultants involved in 85 computer-based information system selection projects. Validation fo the model constructs suggests the existence of six distinct and individually important dimensions of engagement success. both clients and consultants are encouraged to attend to these dimensions in pre-engagement proposal and selection processes, and post-engagement evaluation of outcomes.

A resource management scenario for traditional and scientific management of pink shrimp (Farfantepenaeus paulensis) in the Patos Lagoon estuary (RS), Brazil

Abstract Background This article aims to discuss the incorporation of traditional time in the construction of a management scenario for pink shrimp in the Patos Lagoon estuary (RS), Brazil. To meet this objective, two procedures have been adopted; one at a conceptual level and another at a methodological level. At the conceptual level, the concept of traditional time as a form of traditional ecological knowledge (TEK) was adopted. Method At the methodological level, we conduct a wide literature review of the scientific knowledge (SK) that guides recommendations for pink shrimp management by restricting the fishing season in the Patos Lagoon estuary; in addition, we review the ethno-scientific literature which describes traditional calendars as a management base for artisanal fishers in the Patos Lagoon estuary. Results Results demonstrate that TEK and SK describe similar estuarine biological processes, but are incommensurable at a resource management level. On the other hand, the construction of a “management scenario” for pink shrimp is possible through the development of “criteria for hierarchies of validity” which arise from a productive dialog between SK and TEK. Conclusions The commensurable and the incommensurable levels reveal different basis of time-space perceptions between traditional ecological knowledge and scientific knowledge. Despite incommensurability at the management level, it is possible to establish guidelines for the construction of “management scenarios” and to support a co-management process.

The productivity of people : grant projects in human resource management : Intergovernmental personnel act.

Mode of access: Internet.

Introduction : Islam and human resource management

Purpose – The purpose of this paper is to introduce this special issue on Islam and human resource management (HRM). Design/methodology/approach – The paper introduces the papers in this special issue, which further current understanding of the association between Islam and HRM, and HRM practices in Islamic countries. The papers debate whether it makes sense to talk about an Islamic HRM, and try to identify the key features of an Islamic HRM model that is substantially distinctive from existing normative models of HRM. Findings – The papers examine the impact of Islamic values on HRM practices and organisational outcomes, but more research is needed to gain a deeper understanding of the role Islam plays at the work place, and specifically how Islamic ideals, culture, values and norms are used in practice and implications thereof on workplace environment and overall organisational performance. Originality/value – The paper introduces the concept of Islam and human resource management.

Human resource management and innovation: what are knowledge-intensive firms doing?

An undeniable shift in focus from traditional production companies to Knowledge-Intensive Firms (KIFs) poses challenges for academics and practioners alike. In particular, effective management of an organization's human resources has become a critical issue for ensuring sustained innovation capacity. The relationship between Human Resource Management (HRM) in KIFs is however still a largely unexplored arena. The objective of this paper is to explore this relationship in an effort to identify HRM practices that support innovation. To this end, the paper includes reviews of the literature relevant to HRM and innovation in KIFs and four case studies from companies in Denmark and Australia that have been recognized for excellence in innovation. On the basis of content analyses conducted on the case data, some preliminary conclusions are posited regarding the role of HRM in KIFs. More specifically, the findings from this study suggest that while there are commonalities between HRM practices in traditional manufacturing companies and KIFs, there are also important differences, especially in terms of staffing practices. The paper contributes by offering recommendations for management of HRM in innovative KIFs and potential avenues for research to further develop our understanding of how HRM can support innovation in KIFs.

Examining the role of human resource management in continuous improvement

The objective of this paper is to take a first step in developing a theoretical framework describing the role of HRM in successful CI, based on the current literature from both fields. To this end, elements from the CI Maturity Model and a framework depicting the role of HRM in innovation serve as a foundation for examining how specific bundles of HRM practices utilised during different phases of the CI implementation process may contribute to sustained organisational and enhanced operational performance. The primary contribution of this paper is theoretical; however, the framework has practical value in that it suggests important relationships between HRM practices and behaviours necessary for successful CI. A preliminary test of the framework in an empirical setting is summarised at the conclusion of this paper, where a number of possible research avenues are also suggested.

Modelling issues on the railway resource management process using multi-agent system

Many infrastructure and necessity systems such as electricity and telecommunication in Europe and the Northern America were used to be operated as monopolies, if not state-owned. However, they have now been disintegrated into a group of smaller companies managed by different stakeholders. Railways are no exceptions. Since the early 1980s, there have been reforms in the shape of restructuring of the national railways in different parts of the world. Continuous refinements are still conducted to allow better utilisation of railway resources and quality of service. There has been a growing interest for the industry to understand the impacts of these reforms on the operation efficiency and constraints. A number of post-evaluations have been conducted by analysing the performance of the stakeholders on their profits (Crompton and Jupe 2003), quality of train service (Shaw 2001) and engineering operations (Watson 2001). Results from these studies are valuable for future improvement in the system, followed by a new cycle of post-evaluations. However, direct implementation of these changes is often costly and the consequences take a long period of time (e.g. years) to surface. With the advance of fast computing technologies, computer simulation is a cost-effective means to evaluate a hypothetical change in a system prior to actual implementation. For example, simulation suites have been developed to study a variety of traffic control strategies according to sophisticated models of train dynamics, traction and power systems (Goodman, Siu and Ho 1998, Ho and Yeung 2001). Unfortunately, under the restructured railway environment, it is by no means easy to model the complex behaviour of the stakeholders and the interactions between them. Multi-agent system (MAS) is a recently developed modelling technique which may be useful in assisting the railway industry to conduct simulations on the restructured railway system. In MAS, a real-world entity is modelled as a software agent that is autonomous, reactive to changes, able to initiate proactive actions and social communicative acts. It has been applied in the areas of supply-chain management processes (García-Flores, Wang and Goltz 2000, Jennings et al. 2000a, b) and e-commerce activities (Au, Ngai and Parameswaran 2003, Liu and You 2003), in which the objectives and behaviour of the buyers and sellers are captured by software agents. It is therefore beneficial to investigate the suitability or feasibility of applying agent modelling in railways and the extent to which it might help in developing better resource management strategies. This paper sets out to examine the benefits of using MAS to model the resource management process in railways. Section 2 first describes the business environment after the railway 2 Modelling issues on the railway resource management process using MAS reforms. Then the problems emerge from the restructuring process are identified in section 3. Section 4 describes the realisation of a MAS for railway resource management under the restructured scheme and the feasible studies expected from the model.

Strategizing public sector human resource management : the implications of working network

Networks have come to the fore as a means by which government can achieve its strategic objectives, particularly when addressing complex or “wicked” issues. Such joined-up arrangements differ in their operations from other forms of organizing as they require collaborative effort to deliver the collaborative advantage. Strategic Human Resource Management is concerned with the matching of human resource practices to the strategic direction of organizations. It is argued that the strategic direction of government has been towards network involvement and that, as a result, a reconfiguration of Human Resource Management practices is needed to support this new direction. Drawing on eight network case studies findings are presented in relation to the roles government is expected to play in networks and conclusions are drawn about what types of human resource management practices would best support those roles. Implications for Strategic Human Resource Management are posited.

Career paths in the third sector : implications for human resource management

My interest in career paths in the third sector came from three early observations. First, the majority of workers appear to be women, in fact 77% of community sector community services in NSW (O'Donnell, 1985). Second, when asked about their career, most workers express the opinion that they have none. Third, when I examined the individual career paths of community sector workers I was struck by the stop and start nature of their paid work. Even, or perhaps especially, well qualified workers would move out of a position after about two years often to a more difficult position in a new area, with little or no salary increase and little prospect of future promotion. Indeed, there appears to be little career path available. These observations raise a number of important questions, some of which will be explored in this paper. What is the structure of the third sector labour market? What is the staff structure of third sector organisations? Is it true that career paths are unavailable, either within organisations or within the sector? If none exists, why do workers stay in the field? What motivates them? If there is a high turnover of staff, is this the reason? What are the implications of all this? If some sort of career path does exist, why do workers deny having a career? What do we mean by `career' anyway?

Modeling resource management in the building design process by information constraint Petri nets

The effect of resource management on the building design process directly influences the development cycle time and success of construction projects. This paper presents the information constraint net (ICN) to represent the complex information constraint relations among design activities involved in the building design process. An algorithm is developed to transform the information constraints throughout the ICN into a Petri net model. A resource management model is developed using the ICN to simulate and optimize resource allocation in the design process. An example is provided to justify the proposed model through a simulation analysis of the CPN Tools platform in the detailed structural design. The result demonstrates that the proposed approach can obtain the resource management and optimization needed for shortening the development cycle and optimal allocation of resources.

Waste and resource management practices, legislation and policy encouraging and influencing ‘regeneration reuse’ of property assets

Carbon taxation governance is becoming increasingly popular, further evolving the polluter pays concept already well established in the built environment as a mechanism to controlling and licensing waste generation. This paper presents an explanation of property asset ‘regeneration reuse’ principles following deconstruction, which reduce waste generation associated with the process of demolition, construction and operation. An analysis is made of strategies in Australia and the United Kingdom, comparing jurisdiction targets pertaining to construction and demolition waste that encourage ‘regeneration reuse’. From examination of applicable Australian and United Kingdom legislation, strategic, fiscal and policy that influence on the 'regeneration reuse' of property assets, an evaluation to the variety of issues relevant to waste and resource management practices is reached. The paper concludes that a systematic evaluation framework to selecting building components and structures suitable for reuse after deconstruction must be considered in legislation.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.