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The purpose of this paper is to take a cybernetic perspective on the impact of the earthquakes on the Convergence gathering. Convergence is an organisation formed by a network of alternative life-stylers almost 30 years ago in Canterbury, New Zealand. It holds an annual six-day gathering of 300-500 people over the New Year. Convergence evolved an acephalous structure in that there is no ongoing structured leadership. Leadership occurs in distributed, low key, transient and self-selected ways. Convergence has had its challenges and generally proved itself to be resilient.

This paper discusses the concepts of circularity, resilience, system archetypes, requisite variety, appreciative systems, network theory, antifragility, autopoiesis, structural coupling and learning organisations in relation to the Convergence gathering.

The Christchurch earthquakes of late 2010 and 2011 had an enormous impact on the people of Christchurch. While the earthquakes have not had any significant direct effects on Convergence, a significant number of people involved in Convergence suffered major chronic trauma or changes to life circumstances, which has impacted on the organisation. Nearly five years later many participants are still traumatised, while others are energised to develop Convergence as an organisation pioneering an innovative way of operating.

This research is a part of an ongoing PhD research project so results to date are provisional.

It may assist Convergence to understand the dynamics of perturbations.

There is little written on acephalous operation especially in the medium scale range. It is also hoped this research will help other organisations considering an acephalous structure.

This study aims to empirically investigate the effect of International Financial Reporting Standards (IFRS) convergence on corporate risk disclosure, with a particular emphasis on the quantity and coverage of risk information. The research also conducts economic benefit and cost analysis to investigate the economic implications that may arise from the transition to IFRS reporting.

A content analysis approach is used to measure two broader dimensions of risk disclosure, namely, risk disclosure quantity and risk topic coverage. Furthermore, using firm-fixed effect regression on a sample of 143 Indian-listed companies, this study investigates the variations in these risk disclosure dimensions before (2012–2016) and subsequent to (2017–2021) the convergence with IFRS.

The empirical results of this research demonstrate that IFRS convergence has led to a significant improvement in firms’ risk disclosure across several dimensions. Particularly, during the post-IFRS period, firms’ usage of risk-related words and sentences has considerably surged in MD&A, Notes and whole annual reports. In addition, upon IFRS convergence, firms’ risk descriptions have become more extensive and evenly distributed across risk topic categories. Moreover, the in-depth benefit and cost analysis revealed that firms reporting under IFRS benefit from decreased cost of equity capital, but they also incur a higher cost of audit fees.

This study contributes to the literature in two ways. First, this is the only study, to the best of the authors’ knowledge, to conduct a broader examination of the impact of mandatory IFRS convergence on corporate risk disclosure, with a major focus on quantity and coverage of risk information. Second, by conducting economic benefit and cost analysis, this study provides novel insights into the critical role of IFRS risk disclosures toward multiple economic outcomes.

The purpose of this paper is to explore the current practices in security convergence among and between corporate security and cybersecurity processes in commercial enterprises.

This paper is the first phase in a planned multiphase project to better understand current practices in security optimization efforts being implemented by commercial organizations exploring means and methods to operate securely while reducing operating costs. The research questions being examined are: What are the general levels of interest in cybersecurity and corporate security convergence? How well do the perspectives on convergence align between organizations? To what extent are organizations pursuing convergence? and How are organizations achieving the anticipated outcomes from convergence?

In organizations, the evolution to a more optimized security structure, either merged or partnered, was traditionally due to unplanned or unforeseen events; e.g. a spin-off/acquisition, new security leadership or a negative security incident was the initiator. This is in contrast to a proactive management decision or formal plan to change or enhance the security structure for reasons that include reducing costs of operations and/or improving outcomes to reduce operational risks. The dominant exception was in response to regulatory requirements. Preliminary findings suggest that outcomes from converged organizations are not necessarily more optimized in situations that are organizationally merged under a single leader. Optimization may ultimately depend on the strength of relationships and openness to collaboration between management, cybersecurity and corporate security personnel.

This report and the number of respondents to its survey do not support generalizable findings. There are too few in each category to make reliable predictions and in analysis, there was an insufficient quantity of responses in most categories to allow supportable conclusions to be drawn.

Practitioners may find useful contextual clues to their needs for convergence or in response to directives for convergence from this report on what is found in some other organizations.

Improved effectiveness and/or reduced costs for organizational cybersecurity would be a useful social outcome as organizations become more efficient in the face of increasing levels of cyber security threats.

Convergence as a concept has been around for some time now in both the practice and research communities. It was initially promoted formally by ASIS International and ISACA in 2005. Yet there is no universally agreed-upon definition for the term or the practices undertaken to achieve it. In addition, the business drivers and practices undertaken to achieve it are still not fully understood. If convergence or optimization of converged operations offers a superior operational construct compared to other structures, it is incumbent to discover if there are measurable benefits. This research hopes to define the concept of security collaboration optimization more fully. The eventual goal is to develop and promote a tool useful for organizations to measure where they are on such a continuum.

The main purpose of this paper is to examine the convergence hypothesis of House Price Index (HPI) in the case of 18 major Indian cities for the period 2014–2019.

To attain the authors main goal, this study applies a clustering algorithm advanced by Phillips and Sul. This test creates a club of convergence based on the growth of the cities in terms of HPI.

The study findings show the existence of two convergence clubs and one non-convergent group. Club 1 includes the cities with high HPI growth, whereas club 2 comprises of cities with least HPI growth. Cities belonging to the non-convergent group are neither converging nor diverging.

This study findings will benefit home buyers, sellers, investors, regulators and policymakers interested in the dynamic interlinkages of house price (HP) among Indian cities.

The majority of the studies are conducted in the case of China at the province or city levels. Furthermore, in the case of India, none of the studies has investigated the HP club convergence across Indian cities. Therefore, the present study fills this research gap by examining the HP club convergence across Indian cities.

This paper aims to explore the existence of convergence in non-monetary working conditions in Europe resorting to widely used definitions of this phenomenon and composite indexes of job quality.

The analysis relies on composite indexes, widely used in previous literature, for 207 regions in six different areas of job quality drawing on the microdata of the European Working Conditions Survey from 1995 to 2015. This study assesses the occurrence of convergence both in terms of dispersion of job quality outcomes (sigma-convergence) and, especially, regarding the existence of a catch-up process (beta-convergence).

This study finds evidence of both types of convergences in all the domains, with the exception of skills and discretion and prospects dimensions according to the sigma-convergence approach. The results do not suggest substantial differences between the 15 European Union countries before the 2004 enlargement and the new Member States and are robust to a wide range of changes in the sample and different econometric specifications.

Tot he best of the authors’ knowledge, this paper represents the first rigorous and systematic attempt of addressing the existence of convergence in non-monetary working conditions, applying formal and widely accepted definitions of this phenomenon. It contributes to our knowledge on this topic providing strong evidence of convergence in job quality. Those results can be of interest for scholars in Economics and other Social Sciences.

The objective of this study is to examine how the heterogeneity of the institutional environments within a single country influences International Financial Reporting Standards (IFRS) convergence and earnings quality based on a meso- and multi-level approach.

Using hierarchical linear modeling (HLM) to capture the between-group heteroskedasticity and within-cluster interdependence, this study investigates the simultaneous effect by incorporating institutional factors residing at different hierarchical levels and the interaction effects of factors within the same level on IFRS convergence and earnings quality in the largest IFRS adopter, China.

The results show that after IFRS convergence (i.e. 2007–2015), earnings quality decreases in terms of conservatism. However, the further analysis indicates that the strong institutional environment could mitigate the negative impact of IFRS on conservatism.

Consistent with the emphasis of heterogeneity within a country by Terracciano et al. (Science, 2005, 310 (5745)), this study indicates that the heterogeneity in the institutional environments and the simultaneous effect of the multilevel institutional environments within a single country cannot be ignored. This study also indicates that, equally important, research methodology plays a substantial role in investigating the outcomes of IFRS convergence. Finally, this study, based on an integrated theory, adopts a meso-paradigm linking macro- and micro-level institutions to provide comprehensive insights into IFRS convergence and conservatism.

There is vast disparity in public expenditure on science, technology and environment (STE) across various Indian states. Public expenditure on STE is crucial in maintaining symmetric growth, social cohesion and sustainable development. Literature on this topic is scarce, which prompted the investigation of club convergence of STE public expenditure. In particular, the purpose of this paper to study the club convergence of STE public expenditure in the case of 20 Indian states during the period from 1987–1988 to 2019–2020.

This study applies the clustering algorithm to identify club convergence, advanced by the Phillips and Sul test, which enables identification of multiple steady states or club convergence, unlike beta and sigma convergences.

The findings of this paper show that all Indian states do not converge towards single steady states. This suggests a disparity in STE public expenditure across Indian states. Moreover, the findings favour three clubs that have their own unique transition paths. The results of this study are supported by the robustness check.

The findings suggest that the allocation of public expenditure on STE can be made based on club convergence to achieve social cohesion, sustainable development and millennium development goals across states.

Although several previous studies have investigated the convergence of public expenditure by considering either aggregate public expenditure or health/education expenditure, literature on the convergence hypothesis of STE public expenditure, particularly across Indian states, is scarce. Moreover, this paper is unique, as it examines multiple steady states or club convergence. Finally, this paper contributes to policymaking by suggesting which states should be given a push to achieve social cohesion and sustainable development.

The purpose of this paper is to estimate the impact of the COVID-19 pandemic on the patterns of convergence/divergence among the districts in India. Specifically, this paper investigates if the impact is heterogeneous among different cohorts of districts (based on income distribution). The differential impact may lead to heterogeneous long-run growth paths, resulting in unbalanced development across regions within the country. A study of convergence can ascertain the possible trajectory of such development across regions. Investigation of this phenomenon is the primary aim of this study.

This paper uses the panel regression method for estimation. This paper uses high-frequency nighttime light intensity data as a proxy for aggregate output.

The authors observe a significant reduction in the convergence rate as a result of the pandemic. Across the cluster of districts, the drop in ß-convergence rate, compared to the pre-pandemic period, varied from approximately 33% for the poorer districts to close to zero for the richest group of districts. These findings suggest that the pandemic may lead to a wider disparity among different regions within the country.

This paper contributes to the literature in the following ways. First, to the best of the authors’ knowledge, this is the first paper to investigate the impact of COVID-19 on the convergence rate. A detailed look into the possible disparity in convergence among various regions is critical because a larger drop in convergence, especially among the poorer regions, may call for policy attention to attain long-term equitable development. The authors perform this exercise by dividing the districts into four quantile groups based on the distribution of night-light intensity. Second, while previous studies on convergence using nighttime light data have used a cross-sectional approach, this study is possibly the first attempt to use the panel regression method on this data. The application of this method can be useful in tackling district-level omitted variables bias. Finally, the heterogeneity analysis using different quantiles of the distribution of night-light intensity may help in designing targeted policies to mitigate the disparity across districts due to the shock.

The purpose of this study is to examine the club convergence of Financial integration (FI) in the case of 60 countries from 1970 to 2015. FI plays a vital role in economic growth through sharing the risk between countries, cross-border capital association, investment and financial information. It also leads to the efficient allocation of capital and capital accumulation, thereby improving the systematic growth and productivity of the economy. Literature on examining the convergence hypothesis of FI is scarce.

This study applies the clustering algorithm to identify club convergence, advanced by the Phillips and Sul test, which enables the identification of multiple steady states or club convergence, unlike beta and sigma convergences.

The findings indicate the non-convergence when all 60 countries were taken together. This highlights that the selected countries' have unique transition paths in terms of FI. Hence, the authors implement the clustering algorithm, and the estimation shows that 56 countries are categorised into three different clubs. However, for the rest of four countries, the results are sort of ambiguous, favouring neither convergence nor divergence.

On the basis of three country clubs, Club 1 presents the model countries such as the Netherlands, Singapore and Switzerland. The Club 2 and Club 3 countries can start making moves towards the model countries by making policy adaptations for trade, finance and business facilitation.

The existing literature provides a plethora of studies investigating the convergence of stock markets, exchange rates and equity markets, but studies on the convergence of FI, particularly across the countries, are scarce. This study contributes by bridging this gap. The study is unique in its type as it takes into account the multiple steady states or club convergence. This study also contributes in policymaking by suggesting Club 1 countries (the Netherlands, Singapore and Switzerland) as the model ones for the FI.

The study aims to compare India's public health expenditure at the international and state levels. The paper also empirically examines the regional disparities in NRHM spending across the 21 selected states of India.

The tools of absolute β-and σ-convergence are used in the analysis to test the regional convergence. The average annual growth rate across the states is the dependent variable for β-convergence, and time is the second dependent variable but is used for s-convergence. In contrast, the initial value of NRHM expenditure and the coefficient of variation of NRHM expenditure are used as independent variables, respectively. Descriptive statistics are also used for the study. The data are annual and cover the panel from 2007 to 2020.

The study attests to the hypothesis of β-and σ-convergence for the selected states in the period mentioned. The observed convergence in NRHM expenditure is due to the shift in the government's attention from the non-high focus high focus states to high states through the national rural health mission policy. The coefficient of variation across the states also shows a declining trend and provides the robustness of the σ-convergence.

As far as the literature is concerned, none of the existing studies examines the convergence of a public health expenditure scheme like the National Rural Health Mission across the Indian states by applying the techniques of β-and σ-convergence. The novelty of the study is using the newly updated dataset and validating the convergence hypotheses in the National Rural Health Mission expenditure case.