Predictors of hybrid organizational identity: evidence from the Turkish theatre field, 1923-1999

Being an essential concept in organization research for a long time, organizational identity has received a renewed interest both theoretically and empirically since it has increasingly been interpreted as contingent, dynamic and multiple. Although the notion of hybrid identity constitutes an important part of this interest, existing research mostly considers it as a starting assumption without investigating why there are such identities in the first place. By borrowing ideas from institutional and imprinting frameworks in organization theory, this study is an attempt to extend research by examining how particular field and organization-level factors may predict hybridity of organizational identities. Focusing on the Turkish theatre field as the empirical setting, first the identity claim categories in the field were discovered via cluster analysis by using the dataset of plays performed by professional theatre companies in Istanbul and Ankara during the 1923- 1999 period. Next, analyses were conducted by using multilevel (mixed effect) models in order to test study hypotheses. Hybrid identity was measured by Simpson diversity index weighted by category contrasts. Findings reveal that the degree of identity hybridization is largely enhanced by the identity hybridity of the organization at its birth, the transition in institutional logics and the strength of the mimetic mechanisms within the field. The results emphasize that diverse identity claims are combined more under specific institutional and founding conditions

Socio-spatial analysis of small-area need and accessibility of Primary Healthcare Services in Nigeria: A sequential mixed methods study

Ph. D. Thesis.Accessibility of primary healthcare (PHC) services is crucial for maintaining the good health of a population. Not only is health(care) associated with quality of life and socioeconomic productivity, systematic variations in healthcare accessibility are matters of social justice. Consequently, the overall goal of this project is to comprehensively analyze and explain smallarea need and accessibility of PHC services in Nigeria through a case study of Kogi State, with a view to making policy-relevant recommendations. To this end, both quantitative and qualitative methods are synthesized in an ‘explanatory sequential mixed methods research design’, which also features innovative data exploitations. This entails a synergy of: Automated Zone Design method, Spatial Microsimulation Modelling, and Generalized TwoStep Floating Catchment Area method for quantitative analysis as well as qualitative framework thematic analysis, to obtain research findings that are more robust than existing studies. In this way, genuine small-area variations in PHC need and accessibility are revealed and explicated, including extreme Medically Underserved Areas (eMUAs). Urban areas are more accessible than rural areas, as expected. Of senatorial districts, Kogi Central has the best healthcare accessibility because of its topography. Furthermore, these variations are mediated by the extant sub-optimal zoning system in Nigeria, which is a product of problematic historical political processes. Not only are eMUAs both very remote and rural, they also lack basic social amenities. Hence, it is not surprising that research participants expressed a myriad of dire disincentives in meeting their PHC needs. These difficulties can be mitigated by improving the quality of road infrastructure and ensuring an optimal socio-spatial configuration of PHC services. Broad mechanisms of social exclusion are also implicated in causing access-related disutility of PHC. It is therefore crucial that holistic interventions to alleviate social exclusion are enacted, since previous efforts at addressing only proximal concerns of PHC accessibility have proven unsuccessful. Keywords: Primary Healthcare Needs, Spatial Accessibility, Mixed Methods Research, Automated Zone Design, Spatial Microsimulation, Small-Area Variations.Newcastle University Overseas Research Scholarship (NUORS), Research Excellence Academy of the Humanities and Social Science Faculty (HaSS RE

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

An evolutionary AI-based decision support system for urban regeneration planning

The renewal of derelict inner-city urban districts suffering from high levels of socio-economic deprivation and sustainability problems is one of the key research areas in urban planning and regeneration. Subject to a wide range of social, economical and environmental factors, decision support for an optimal allocation of residential and service lots within such districts is regarded as a complex task. Pre-assessment of various neighbourhood factors before the commencement of actual location allocation of various public services is considered paramount to the sutainable outcome of regeneration projects. Spatial assessment in such derelict built-up areas requires planning of lot assignment for residential buildings in a way to maximize accessibility to public services while minimizing the deprivation of built neighbourhood areas. However, the prediction of socio-economic deprivation impact on the regeneration districts in order to optimize the location-allocation of public service infrastructure is a complex task. This is generally due to the highly conflicting nature of various service structures with various socio-economic and environmental factors. In regards to the problem given above, this thesis presents the development of an evolutionary AI-based decision support systemto assist planners with the assessment and optimization of regeneration districts. The work develops an Adaptive Network Based Fuzzy Inference System (ANFIS) based module to assess neighbourhood districts for various deprivation factors. Additionally an evolutionary genetic algorithms based solution is implemented to optimize various urban regeneration layouts based upon the prior deprivation assessment model. The two-tiered framework initially assesses socio-cultural deprivation levels of employment, health, crime and transport accessibility in neighbourhood areas and produces a deprivation impact matrix overthe regeneration layout lots based upon a trained, network-based fuzzy inference system. Based upon this impact matrix a genetic algorithm is developed to optimize the placement of various public services (shopping malls, primary schools, GPs and post offices) in a way that maximize the accessibility of all services to regenerated residential units as well as contribute to minimize the measure of deprivation of surrounding neighbourhood areas. The outcome of this research is evaluated over two real-world case studies presenting highly coherent results. The work ultimately produces a smart urban regeneration toolkit which provides designer and planner decision support in the form of a simulation toolkit.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An Initial Framework Assessing the Safety of Complex Systems

Trabajo presentado en la Conference on Complex Systems, celebrada online del 7 al 11 de diciembre de 2020.Atmospheric blocking events, that is large-scale nearly stationary atmospheric pressure patterns, are often associated with extreme weather in the mid-latitudes, such as heat waves and cold spells which have significant consequences on ecosystems, human health and economy. The high impact of blocking events has motivated numerous studies. However, there is not yet a comprehensive theory explaining their onset, maintenance and decay and their numerical prediction remains a challenge. In recent years, a number of studies have successfully employed complex network descriptions of fluid transport to characterize dynamical patterns in geophysical flows. The aim of the current work is to investigate the potential of so called Lagrangian flow networks for the detection and perhaps forecasting of atmospheric blocking events. The network is constructed by associating nodes to regions of the atmosphere and establishing links based on the flux of material between these nodes during a given time interval. One can then use effective tools and metrics developed in the context of graph theory to explore the atmospheric flow properties. In particular, Ser-Giacomi et al. [1] showed how optimal paths in a Lagrangian flow network highlight distinctive circulation patterns associated with atmospheric blocking events. We extend these results by studying the behavior of selected network measures (such as degree, entropy and harmonic closeness centrality)at the onset of and during blocking situations, demonstrating their ability to trace the spatio-temporal characteristics of these events.This research was conducted as part of the CAFE (Climate Advanced Forecasting of sub-seasonal Extremes) Innovative Training Network which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 813844

CORPORATE SOCIAL RESPONSIBILITY IN ROMANIA

The purpose of this paper is to identify the main opportunities and limitations of corporate social responsibility (CSR). The survey was defined with the aim to involve the highest possible number of relevant CSR topics and give the issue a more wholesome perspective. It provides a basis for further comprehension and deeper analyses of specific CSR areas. The conditions determining the success of CSR in Romania have been defined in the paper on the basis of the previously cumulative knowledge as well as the results of various researches. This paper provides knowledge which may be useful in the programs promoting CSR.Corporate social responsibility, Supportive policies, Romania

On Experimentation in Software-Intensive Systems

Context: Delivering software that has value to customers is a primary concern of every software company. Prevalent in web-facing companies, controlled experiments are used to validate and deliver value in incremental deployments. At the same that web-facing companies are aiming to automate and reduce the cost of each experiment iteration, embedded systems companies are starting to adopt experimentation practices and leverage their activities on the automation developments made in the online domain. Objective: This thesis has two main objectives. The first objective is to analyze how software companies can run and optimize their systems through automated experiments. This objective is investigated from the perspectives of the software architecture, the algorithms for the experiment execution and the experimentation process. The second objective is to analyze how non web-facing companies can adopt experimentation as part of their development process to validate and deliver value to their customers continuously. This objective is investigated from the perspectives of the software development process and focuses on the experimentation aspects that are distinct from web-facing companies. Method: To achieve these objectives, we conducted research in close collaboration with industry and used a combination of different empirical research methods: case studies, literature reviews, simulations, and empirical evaluations. Results: This thesis provides six main results. First, it proposes an architecture framework for automated experimentation that can be used with different types of experimental designs in both embedded systems and web-facing systems. Second, it proposes a new experimentation process to capture the details of a trustworthy experimentation process that can be used as the basis for an automated experimentation process. Third, it identifies the restrictions and pitfalls of different multi-armed bandit algorithms for automating experiments in industry. This thesis also proposes a set of guidelines to help practitioners select a technique that minimizes the occurrence of these pitfalls. Fourth, it proposes statistical models to analyze optimization algorithms that can be used in automated experimentation. Fifth, it identifies the key challenges faced by embedded systems companies when adopting controlled experimentation, and we propose a set of strategies to address these challenges. Sixth, it identifies experimentation techniques and proposes a new continuous experimentation model for mission-critical and business-to-business. Conclusion: The results presented in this thesis indicate that the trustworthiness in the experimentation process and the selection of algorithms still need to be addressed before automated experimentation can be used at scale in industry. The embedded systems industry faces challenges in adopting experimentation as part of its development process. In part, this is due to the low number of users and devices that can be used in experiments and the diversity of the required experimental designs for each new situation. This limitation increases both the complexity of the experimentation process and the number of techniques used to address this constraint