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Nowadays, informed decision-making is catching up. Technological advancements and computing ability further fuel and facilitate this tilt toward informed decision-making. In such a scenario, data is cynosure. Therefore, the ability to gather data by a nation (incredibly accurate public data) becomes equally important and relevant, as measured by statistical performance indicators (SPI). This study aims to explore the association of financial inclusion (FI); environmental, social and governance (ESG); poverty; and SPI.

The panel data of 140 nations for nine years are gathered to explore the association of FI, ESG and poverty with the SPI. Panel data estimation is conducted to arrive at the results.

The findings of this study highlight mixed outcomes for FI. ESG is positively associated with SPI, but poverty is not associated with SPI. These findings imply that an increase in FI may reduce the statistical capacity of the nations. An increase in ESG increases the capacity. However, change in poverty does not influence the SPI. The recommendation based on this study’s outcome suggests auditing the FI and poverty vis-à-vis SPI to ensure SPI’s veracity and robustness in the long run.

The way in which the individual social, economic and environmental indicators influence the SPI needs to be tested to establish the veracity and robustness of the SPI, which is barely researched as observed in the literature.

The purpose of this paper is to examine changes in accountability as the provision and control of education moved from private nonprofit organisations to a public sector provider.

Analysis of nineteenth century archival documents from significant primary educational providers in a major early New Zealand settlement.

The nonprofit education provider utilised public meetings including public examinations, whose effect was to develop trust based on the education values it shared with its community of stakeholders. It also published financial reports which, along with inspections and statistical returns, were preferred once the government became the education provider. Such publications and inspections indicated bureaucracy and control. Nevertheless, government funding, rather than the nonprofit organisation’s dependence on its community, made education provision sustainable.

It has been suggested that the differences between public sector and private sector accounting and accountability are not always sharply defined (Carnegie and Napier, 2012). However, this case study shows that a change of education provider did lead to a marked difference in accountability. While theory suggests that public sector accountability should enhance democracy, the party best meeting this brief was the nonprofit provider, with the public sector provider preferring hierarchical accountability. It could be argued that funding dependence drove these different approaches as community accountability was traded for financial security.

Distinctive study of accountability practices to external stakeholders, in a mid-nineteenth century education context.

The purpose of this research is to support responsible decision-making in Higher Education (HE) settings by understanding what type of learning journey satisfies students most in their HE experience and what they want from the learning.

This paper analyses the key tool used to assess satisfaction factors for UK students, the National Student Survey (NSS). It adopts peculiar regression statistical tests to identify the NSS items that influence “overall student satisfaction” by reviewing responses over 9 years from accountancy students at business schools located in England.

The findings of the study provide evidence that students are most satisfied with a learning journey where they are part of a course that is “well organised and running smoothly”, which provides “intellectual stimulation” that helps in developing their ability to “present themselves with confidence” and provides “academic advice and support”. The findings of the paper show that students are not satisfied so much by utilitarian aspects of learning but rather those that relate to who they are and where they are in their learning journey, the level of intellectual stimulation they have experienced, the self-confidence they have developed and the supportive relationship they have developed with academics. A factor that did not relate highly was “assessment and feedback” which has been the focus of much university resource. Results show the factors that impacted overall satisfaction are most related to students wanting to develop personal responsibility. These findings shape the key principles of responsible design and management of HE programmes and influence strategic decision-making.

Focussing on helping students experience, the type of learning journey that develops the virtue of responsibility emergent from the analysis will not only satisfy the student but will also have a knock-on effect of improving NSS scores, university league table ranking and accreditation under the Teaching Excellence Framework. The improved reputation aspects would then feed back into increased student satisfaction (Dean and Gibbs, 2015). The findings will also help HE managers and leaders to evaluate their decisions through three lenses: responsibility, students’ experience and students overall learning journey.

Much of the information published on the NSS have been predominantly descriptive and has resulted in decisions being made for students based on uninformed analysis of the survey’s results. This study uses advanced statistical modelling to evidence the relationship between factors of the NSS and overall student satisfaction providing key information regarding students’ importance to the type of learning journey they value and that this relates to a desire in wanting to develop responsibility. This study shows the link between factors of the NSS to provide useful lenses for HE managers and leaders to use to support responsible decision-making processes.

In line with business goals of customer satisfaction, higher education institutions of learning consider excellent student experience a priority. Teaching and learning are important aspects of satisfaction that are monitored annually by universities using tools such as the National Student Survey (NSS). The NSS results are useful for educational planning and informing consumer choices. This research measured undergraduate student experiences on an interdisciplinary project using the NSS framework. Hinged on diversity, the purpose was to investigate whether full-time (FT), part-time (PT) and degree apprenticeship students with varied work experience enhance their learning studying together on an interdisciplinary project.

This research has measured, using the NSS criteria, student experiences on an interdisciplinary project on a civil engineering programme. It benchmarks the quality of learning and student understanding and perceptions of learning. The method is based upon a literature review and questionnaire survey of students.

Results indicate good amounts of peer influence on learning in a simulated interdisciplinary team setting supported by a mix of diverse work experience in students’ background.

Sections of the NSS are extended with additional questions to capture the impact that FT, PT and degree apprenticeship study modes, closely associated with students’ background of job experience, have on teaching and learning.

This chapter critically examines how recent government papers and policies have informed and contextualised the new Higher Education and Research Bill (HERB) passed in April 2017. In particular, it concerns itself with the issue of ‘teaching excellence’, through what has been termed the Teaching Excellence Framework (TEF) that has emerged as a key plank of the current government’s policy for future funding of higher education (HE). It will consider the other spurs for reform in HERB, such as the desire to create a culture in HE where teaching has equal status with research, the need to ensure that universities provide better information about their courses and the experiences that they can offer students and the predictable governmental requirement for institutions to give value for money and to be clearly held accountable for any failure to provide a quality service to students. Lastly, there is also a strong emphasis on widening student participation across the sector and ‘levelling the playing field’ so that new providers can set up with the minimum of red tape. It is interesting to note how each of these additional areas for reform is clearly linked to TEF, which, this chapter will argue, will be the key vehicle used to drive them forward.

This chapter starts by interrogating the notion of teaching excellence. It then moves on to discussing some of the data sources currently used in Higher Education Institutions (HEIs) to monitor and measure the quality of teaching. What do these sources actually reveal about teaching excellence and how might we make better use of them? From large-scale national censuses like the National Student Survey (NSS) to institutional data sets such as teaching observations, the contribution that each source makes to our understanding of the quality of HE teaching is underexplored and contested. It is argued that there is a need for more transparent debate across HEIs and the sector as a whole about the benefits and limitations of such data as well as greater acknowledgement of the role of collaboration over competition. The chapter concludes that teaching excellence is a marketised misconception of the complex reality of the reciprocal relationship between teaching and learning. Contrary to policy rhetoric and far from encouraging an environment of collegial improvement, it introduces an unhelpful ethos of contrived competition into what is essentially an interdependent relationship underpinned by collective collaboration. It is by focusing attention on the latter where the real gains and insights are likely to be made.

The historical evolution of the economy of Ireland's South East region is traced, highlighting Waterford's key role as the region's leading urban centre and port. What had been a rather traditional regional economic structure underwent considerable modernisation in the last two decades, but lacks the sectoral specialisation which provides a strong economic base in other Irish regions. The National Spatial Strategy, launched in 2002, sought to promote regional specialisation in exporting sectors, but lacked the governance structures required to drive the process. The current National Planning Framework is more focused on building up the main regional centres, but is likely to leave Waterford City well short of the scale required to be competitive in global markets. An alternative strategy is proposed, whereby Waterford would work in collaboration with the South East's unique set of strong county towns to create a distinctive and coherent, region-wide and sectorally focused, urban system. The success of such a project, however, would be dependent on the creation of a strong regional government tier and the devolution to the regions of a wide range of powers and functions currently concentrated at national level.

The purpose of this paper is to solve the shortage of the existing methods for the prediction of network security situations (NSS). Because the conventional methods for the prediction of NSS, such as support vector machine, particle swarm optimization, etc., lack accuracy, robustness and efficiency, in this study, the authors propose a new method for the prediction of NSS based on recurrent neural network (RNN) with gated recurrent unit.

This method extracts internal and external information features from the original time-series network data for the first time. Then, the extracted features are applied to the deep RNN model for training and validation. After iteration and optimization, the accuracy of predictions of NSS will be obtained by the well-trained model, and the model is robust for the unstable network data.

Experiments on bench marked data set show that the proposed method obtains more accurate and robust prediction results than conventional models. Although the deep RNN models need more time consumption for training, they guarantee the accuracy and robustness of prediction in return for validation.

In the prediction of NSS time-series data, the proposed internal and external information features are well described the original data, and the employment of deep RNN model will outperform the state-of-the-arts models.

The purpose of this paper is to evaluate India's five year plan strategies for including the deprived in the development process since Independence.

This is a policy review paper based on past studies.

The paper argues that effective policy formulation for inclusion and its evaluation is conditioned by the available institutional capacity to generate and effectively utilize a sound information base. Using empirical illustrations based on past studies, this paper shows that India's pursuit of inclusion has been hampered because of the limited appreciation of design as well as limitations in available information. This has led to a mechanical pursuit of sophistication in policy formulation, which has rendered both the implementation and an honest evaluation of the policy process difficult.

This paper has relevance for inclusive policy reforms and will open up a debate, as well as future research, on the issues raised.

The paper aims to assess two sustainability metric methodologies, material flow analysis (MFA) and integrated sustainable cities assessment method (ISCAM), as applied practically to an Irish settlement, in order to compare utility and transparency for stakeholders and policy makers.

Both methods were applied to an Irish settlement, namely Tipperary Town, with MFA measuring efficiency of resource usage, as measured by urban metabolic efficiency, and the ISCAM method simulating alternative scenarios as well as calculating the divergence or otherwise of current or business as usual (BAU) trends from more sustainable scenarios.

It was found that both methods have high data requirements, presenting a need for proxy analysis and disaggregation, with the ISCAM method requiring data functionally matched to a time series and over a long time framework. The ISCAM method may also require more advanced extrapolation methods than the simple linear extrapolation employed in the analysis for statistical robustness to reflect behaviour modes more complex than the deterministic behaviour assumed for the selected indicators. A material flow analysis (MFA) was undertaken for household food and waste and it was found that there was a high metabolic efficiency.

This paper was restricted to an application of two methodologies by time constraints and thus was unable to appraise a more comprehensive range of sustainability appraisal options, for example, ecological footprints.

It applies novel methodologies in an Irish context, further highlights the need for more sustainable policy development in an urban setting and was aimed at policy makers at national and local levels.