Search results

The purpose of this paper is to examine empirically the relevance and impact of a number of factors on the role of local councils in local policy-making in Erbil province/Iraq.

This research theoretically based on literature review and adopted an analytical approach to clarify the related concepts through the policy cycle approach. On the empirical side, the research adopted a descriptive analysis for research questions and used statistical analysis to test the research hypotheses.

The results of the study reveal that variables of the local policy-making process, political factors, interaction patterns and the role of other actors have relevance in the role of local councils. In addition, the study concludes that technical feasibility, budgetary considerations, public opinion, coalition building, civil society, executive bodies, administrative organs and non-governmental organizations have a positive effect on the role of local councils in local policy-making in Erbil province, while interest groups have a negative effect on the role of local councils in local policy-making in Erbil province.

The findings and recommendations of this research can practically use by the local councils to achieve effective local policy, particularly in Erbil province/Iraq.

This research has interesting implications in theory and practice, as it provides several contributions to the literature, as well as the practical contribution for local councils in the local policy-making process.

The visualization of ranking information in global public policy is moving away from traditional “league table” formats and toward dashboards and interactive data displays. This paper explores the rhetoric underpinning the visualization of ranking information in such interactive formats, the purpose of which is to encourage country participation in reporting on the Sustainable Development Goals. The paper unpacks the strategies that the visualization experts adopt in the measurement of global poverty and wellbeing, focusing on a variety of interactive ranking visualizations produced by the OECD, the World Bank, the Gates Foundation and the ‘Our World in Data’ group at the University of Oxford. Building on visual and discourse analysis, the study details how the politically and ethically sensitive nature of global public policy, coupled with the pressures for “decolonizing” development, influence how rankings are visualized. The study makes two contributions to the literature on rankings. First, it details the move away from league table formats toward multivocal interactive layouts that seek to mitigate the competitive and potentially dysfunctional pressures of the display of “winners and losers.” Second, it theorizes ranking visualizations in global public policy as “alignment devices” that entice country buy-in and seek to align actors around common global agendas.

Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time. However, storing and processing large and varied datasets (known as big data) is challenging to do in real time. In machine learning, streaming feature selection has always been considered a superior technique for selecting the relevant subset features from highly dimensional data and thus reducing learning complexity. In the relevant literature, streaming feature selection refers to the features that arrive consecutively over time; despite a lack of exact figure on the number of features, numbers of instances are well-established. Many scholars in the field have proposed streaming-feature-selection algorithms in attempts to find the proper solution to this problem. This paper presents an exhaustive and methodological introduction of these techniques. This study provides a review of the traditional feature-selection algorithms and then scrutinizes the current algorithms that use streaming feature selection to determine their strengths and weaknesses. The survey also sheds light on the ongoing challenges in big-data research.

The aim of this research is to assess the influence of the underlying service quality variable, usually related to university students' perception of the educational experience. Another aspect analysed in this work is the development of a procedure to determine which variables are more significant to assess students' satisfaction.

In order to achieve both goals, a twofold methodology was approached. In the first phase of research, an assessment of the service quality was performed with data gathered from 580 students in a process involving the adaptation of the SERVQUAL scale through a multi-objective optimization methodology. In the second phase of research, results obtained from students were compared with those obtained from the teaching staff at the university.

Results from the analysis revealed the most significant service quality dimensions from the students' viewpoint according to the scores that they provided. Comparison of the results with the teaching staff showed noticeable differences when assessing academic quality.

Significant conclusions can be drawn from the theoretical review of the empirical evidences obtained through this study helping with the practical design and implementation of quality strategies in higher education especially in regard to university education.

Even with the recognized impact organizational leaders have on the outcome of digital transformation (DT), a comprehensive scholarly understanding of the competencies that leaders must possess to lead a DT to success is lacking.

To derive and list the competencies considered by experts as necessary for managing DT, the authors recruited 18 international senior managers with relevant experience and applied the Delphi method to survey the managers. Upon the completion of three survey rounds and the authors modifying the response list until consensus was reached, 39 items were shortlisted as constituting key competencies for managing DT. Furthermore, the authors engaged in inductive theorizing to derive propositional statements using these findings.

The practitioners agreed on visionary thinking, agility, understanding the value of data, data-driven decision-making, knowledge of strategy and accepting change as the most important requirements for managing DT. Through inductive theorizing, the authors further derived that the seven discovered clusters fell into two broader competencies – behavioral and strategic – and that each behavioral competency would have varying importance depending on the country and industry that the organization operates in.

As is typical for Delphi studies that involve multiple survey rounds, the study participant response rate was moderate. The implications of this study, in finding that a variety of leadership competencies are needed to ensure successful DT, validate prior research that people, not technology, drive DT.

This study helps mitigate assumptions that successful DT processes are only possible by hiring technological experts, as doing so highlights the importance of behavioral leadership competencies.

The study is one of the first to interlink digital leadership with DT by inductively theorizing behavioral and strategic competencies. The authors also establish that contexts are vital in determining which aspects of leadership competencies are deemed most important in driving DT.

This study aims to identify user perception of different qualities of optical character recognition (OCR) in texts. The purpose of this paper is to study the effect of different quality OCR on users' subjective perception through an interactive information retrieval task with a collection of one digitized historical Finnish newspaper.

This study is based on the simulated work task model used in interactive information retrieval. Thirty-two users made searches to an article collection of Finnish newspaper Uusi Suometar 1869–1918 which consists of ca. 1.45 million autosegmented articles. The article search database had two versions of each article with different quality OCR. Each user performed six pre-formulated and six self-formulated short queries and evaluated subjectively the top 10 results using a graded relevance scale of 0–3. Users were not informed about the OCR quality differences of the otherwise identical articles.

The main result of the study is that improved OCR quality affects subjective user perception of historical newspaper articles positively: higher relevance scores are given to better-quality texts.

To the best of the authors’ knowledge, this simulated interactive work task experiment is the first one showing empirically that users' subjective relevance assessments are affected by a change in the quality of an optically read text.

The study aims to analyze the previous literature on government initiatives to implement health information systems (HISs).

Proknow-C (Knowledge Development Process-Constructivist) was used in the selection of the literature and in the bibliometric and systematic analysis.

The research identified a portfolio composed of 33 articles aligned with the research theme and with scientific recognition, as well as periodicals, authors, papers and keywords that stood out the most. Amongst the government initiatives in the 24 identified countries, England has been the most studied nation, and there is a certain prominence of research arising from developed countries. Electronic health records (EHRs) have been the most explored technology. Efficiency and safety of health care delivery, integration of information and among health organizations, cost reduction and economicity are the most expected benefits from government programs. The difficulties found are related to the broader context in which the system is inserted, to the management of the program, to technology itself and to individuals. The most emphasized difficulties identified in most countries were previous context marked by a lack of standardization/interoperability, acceptance of providers and users and project financing. The findings of the present article provide a theoretical framework for future studies, in addition to yielding a replicable process for future use.

This research may be considered original as it analyzes – through a constructivism-structured process (Proknow-C) – the phenomenon under investigation by gathering bibliometric and systematic review data concomitantly. The countries and technologies reported emerge from the process itself.