Public service motivation and performance: a critical perspective

Purpose – A growing body of literature points to the importance of public service motivation (PSM) for the performance of public organizations. The purpose of this paper is to assess the method predominantly used for studying this linkage by comparing the findings it yields without and with a correction suggested by Brewer (2006), which removes the common-method bias arising from employee-specific response tendencies. Design/methodology/approach – First, the authors conduct a systematic review of published empirical research on the effects of PSM on performance and show that all studies found have been conducted at the individual level. Performance indicators in all but three studies were obtained by surveying the same employees who were also asked about their PSM. Second, the authors conduct an empirical analysis. Using survey data from 240 organizational units within the Swiss federal government, the paper compares results from an individual-level analysis (comparable to existing research) to two analyses where the data are aggregated to the organizational level, one without and one with the correction for common-method bias suggested by Brewer (2006). Findings – Looking at the Attraction to Policy-Making dimension of PSM, there is an interesting contrast: While this variable is positively correlated with performance in both the individual-level analysis and the aggregated data analysis without the correction for common-method bias, it is not statistically associated with performance in the aggregated data analysis with the correction. Originality/value – The analysis is the first to assess the robustness of the performance-PSM linkage to a correction for common-method bias. The findings place the validity of at least one part of the individual-level linkage between PSM and performance into question.

Thematic thinking and individual performance in research and development

Individuals differ in their preference for processing information on the basis of taxonomic, feature-based similarity, or thematic, relation-based similarity. These differences, which have been investigated in a recently emerging research stream in cognitive psychology, affect innovative behavior and thus constitute an important antecedent of individual performance in research and development (R&D) that has been overlooked so far in the literature on innovation management. To fill this research gap, survey and test data from the employees of a multinational information technology services firm are used to examine the relationship between thematic thinking and R&D professionals' individual performance. A moderated mediation model is applied to investigate the proposed relationships of thematic thinking and individual-level performance indicators. Results show a positive relationship between thematic thinking and innovativeness, as well as individual job performance. While the results do not support the postulated moderation of the innovativeness–job performance relationship by employees' political skill, they show that the relationship between thematic thinking and job performance is fully mediated by R&D professionals' innovativeness. The present study is thus the first to reveal a positive relationship between thematic thinking and innovative performance.

Improving Management of Distributed Services Using Correlations and Predictions in SLA-Driven Cloud Computing Systems

Recent advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing environmental conditions and number of users, application performance might suffer, leading to Service Level Agreement (SLA) violations and inefficient use of hardware resources. We introduce a system for controlling the complexity of scaling applications composed of multiple services using mechanisms based on fulfillment of SLAs. We present how service monitoring information can be used in conjunction with service level objectives, predictions, and correlations between performance indicators for optimizing the allocation of services belonging to distributed applications. We validate our models using experiments and simulations involving a distributed enterprise information system. We show how discovering correlations between application performance indicators can be used as a basis for creating refined service level objectives, which can then be used for scaling the application and improving the overall application's performance under similar conditions.

SLA-Driven Simulation of Multi-Tenant Scalable Cloud-Distributed Enterprise Information Systems

Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators.

Service Level Agreements-Driven Management of Distributed Applications in Cloud Computing Environments

Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

Evaluation of coughing and nasal discharge as early indicators for an increased risk to develop equine recurrent airway obstruction (RAO).

BACKGROUND It is often assumed that horses with mild respiratory clinical signs, such as mucous nasal discharge and occasional coughing, have an increased risk of developing recurrent airway obstruction (RAO). HYPOTHESIS Compared to horses without any clinical signs of respiratory disease, those with occasional coughing, mucous nasal discharge, or both have an increased risk of developing signs of RAO (frequent coughing, increased breathing effort, exercise intolerance, or a combination of these) as characterized by the Horse Owner Assessed Respiratory Signs Index (HOARSI 1-4). ANIMALS Two half-sibling families descending from 2 RAO-affected stallions (n = 65 and n = 47) and an independent replication population of unrelated horses (n = 88). METHODS In a retrospective cohort study, standardized information on occurrence and frequency of coughing, mucous nasal discharge, poor performance, and abnormal breathing effort-and these factors combined in the HOARSI-as well as management factors were collected at intervals of 1.3-5 years. RESULTS Compared to horses without clinical signs of respiratory disease (half-siblings 7%; unrelated horses 3%), those with mild respiratory signs developed clinical signs of RAO more frequently: half-siblings with mucous nasal discharge 35% (P < .001, OR: 7.0, sensitivity: 62%, specificity: 81%), with mucous nasal discharge and occasional coughing 43% (P < .001, OR: 9.9, sensitivity: 55%, specificity: 89%); unrelated horses with occasional coughing: 25% (P = .006, OR = 9.7, sensitivity: 75%, specificity: 76%). CONCLUSIONS AND CLINICAL IMPORTANCE Occasional coughing and mucous nasal discharge might represent an increased risk of developing RAO.

Predictive modelling of mineral scaling, corrosion and the performance of solute geothermometers in a granitoid-hosted, enhanced geothermal system

Experience is lacking with mineral scaling and corrosion in enhanced geothermal systems (EGS) in which surface water is circulated through hydraulically stimulated crystalline rocks. As an aid in designing EGS projects we have conducted multicomponent reactive-transport simulations to predict the likely characteristics of scales and corrosion that may form when exploiting heat from granitoid reservoir rocks at ∼200 °C and 5 km depth. The specifications of an EGS project at Basel, Switzerland, are used to constrain the model. The main water–rock reactions in the reservoir during hydraulic stimulation and the subsequent doublet operation were identified in a separate paper (Alt-Epping et al., 2013b). Here we use the computed composition of the reservoir fluid to (1) predict mineral scaling in the injection and production wells, (2) evaluate methods of chemical geothermometry and (3) identify geochemical indicators of incipient corrosion. The envisaged heat extraction scheme ensures that even if the reservoir fluid is in equilibrium with quartz, cooling of the fluid will not induce saturation with respect to amorphous silica, thus eliminating the risk of silica scaling. However, the ascending fluid attains saturation with respect to crystalline aluminosilicates such as albite, microcline and chlorite, and possibly with respect to amorphous aluminosilicates. If no silica-bearing minerals precipitate upon ascent, reservoir temperatures can be predicted by classical formulations of silica geothermometry. In contrast, Na/K concentration ratios in the production fluid reflect steady-state conditions in the reservoir rather than albite–microcline equilibrium. Thus, even though igneous orthoclase is abundant in the reservoir and albite precipitates as a secondary phase, Na/K geothermometers fail to yield accurate temperatures. Anhydrite, which is present in fractures in the Basel reservoir, is predicted to dissolve during operation. This may lead to precipitation of pyrite and, at high exposure of anhydrite to the circulating fluid, of hematite scaling in the geothermal installation. In general, incipient corrosion of the casing can be detected at the production wellhead through an increase in H2(aq) and the enhanced precipitation of Fe-bearing aluminosilicates. The appearance of magnetite in scales indicates high corrosion rates.