Assets Data Research Articles

The changing geographies of financial centres in China: The case of commercial banking

AbstractThis paper discusses the geographies of commercial banking in China. To understand the changing geographies of financial centres, this paper uses an empirical approach to highlight the changing spatial distribution of banking to the existing collection of empirical descriptions, and by an investigation of its spatial concentration over the period between 2006 and 2014. The empirical analysis is based on branch and sub‐branch data, employment data, headquarters data, and banking assets data, all of which are available, allowing a systematic geographical analysis of commercial banking. The findings reveal the status of Beijing and Shanghai as primary banking centres, as well as a hierarchical network of domestic banking centres and a growing spatial concentration within China's banking system. More specifically, Beijing is the predominant banking centre, while Shanghai retains its status as a capital for foreign banking. The rise of provincial banking centres in addition to Beijing, Shanghai, and Shenzhen has contributed to the formation of a hierarchical network of banking centres at national level. Accordingly, the development of first‐ and second‐tier banking centres has led to an ascending geographical concentration within China's banking system.

The gCube system: Delivering Virtual Research Environments as-a-Service

Important changes have characterised research and knowledge production in recent decades. These changes are associated with developments in information technologies and infrastructures. The processes characterising research and knowledge production are changing through the digitalisation of science, the virtualisation of research communities and networks, the offering of underlying systems and services by infrastructures. This paper gives an overview of gCube, a software system promoting elastic and seamless access to research assets (data, services, computing) across the boundaries of institutions, disciplines and providers to favour collaboration-oriented research tasks. gCube’s technology is primarily conceived to enable Hybrid Data Infrastructures facilitating the dynamic definition and operation of Virtual Research Environments. To this end, it offers a comprehensive set of data management commodities on various types of data and a rich array of “mediators” to interface well-established Infrastructures and Information Systems from various domains. Its effectiveness has been proved by operating the D4Science.org infrastructure and serving concrete, multidisciplinary, challenging, and large scale scenarios.

Development of an Asset Management System Integrated with GIS and K-Means Algorithm for Large Industrial Area

The large industrial area has more than a thousand assets that make asset management activities to become more challenging. However, the current asset management in several industrial companies still records the asset information in paper-based documents. Therefore, the technical problems found in current practices in the field are the difficulties in determining the actual position of assets and which group of asset belongs accurately. To overcome those problems and to improve the asset management activities, an asset management system using GIS (Geographic Information System) and K-Means Algorithm is proposed. GIS to visualize the asset coordinate and condition on a geographical map, manage and store the assets detail information and K-Means Clustering Algorithm to cluster the assets based on their coordinate and simplifies the scattered asset. The system is developed using the Waterfall model. The system is native applications built using electron framework and can be accessed within industrial area network only, to keep the user convenience and security of asset data. The Leaflet used as interactive map software frameworks to visualize the industrial map, manage the geospatial data and mapped the industrial asset, including machinery, equipment, land, and building. For the initial operation, the system contains more than 700 assets data with 6 categories and 4 clusters. This system improves the assets accuracy, reduces the time of asset management practices, and the asset clusters can be used as decision support for industrial asset management activities.

Corporate Diversification, Managerial Expansion, Firm Liquidity and Operating Performance: The Role of Segment Disclosure

We investigate the association between corporate international diversification and operating and market performance and firm spread (liquidity). We find, as expected, that foreign fixed assets of US firms are significantly and positively related to firm performance as measured by operating income, cash from operations, and liquidity. This evidence suggests that corporate international diversification reflects a unique dimension that is incremental to operating and market performance. Foreign fixed assets also are significantly and positively related to prices and returns, suggesting that foreign investments are wealth changing corporate decision. This finding not only complements our operating performance results and price regressions findings, but also suggests that a portion of US firms’ investment abroad is timely. Our inferences are robust to change specifications and controlling for previously identified determinants of spread, operating and market performance. Our price and return results suggest that investors incorporate geographic segmental assets data in their valuation model. Extending the analysis on partition sample — high versus low leverage firms, we document that both foreign assets of high and low leverage firms are significantly positively associated with share price and the coefficient on high leverage firms is significantly larger than the coefficient on low leverage firms.

Tracing financial innovation diffusion and substitution trajectories. Recent evidence on exchange-traded funds in Japan and South Korea

Since the rapid growth of the popularity of ETFs, the potential substitution between innovative financial products, exchange-traded funds (ETFs), and traditional investment funds (open-end and closed-end funds) is recognized as one of the most-discussed issues in the financial industry. This is the first study to empirically verify and compare the diffusion and substitution of ETFs using monthly data on their assets in two selected countries. The main aim of this paper is to provide in-depth insights into the development of innovative financial products available in two Asian economies: Japan and South Korea. The empirical study uses monthly total net assets data for 2004–2017. Our methodological framework combines models of innovation diffusion and technological substitution. The results reported in the study show that in both countries the diffusion of ETFs has occurred. The rate of diffusion and the phase of growth reached differed – in Japan the ETF market was in the early exponential growth stage, whereas in South Korea it was closer to achieving the expected maximum saturation. The results of the substitution analysis between the largest category of the innovative funds – equity ETFs and equity open-end funds clearly demonstrate that the process of “switching” from equity open-end funds into ETFs may be easily traced in both countries. Substitution processes were, however, gradual and reversals of the trajectories were noticed.

Understanding the interplay between covariance forecasting factor models and risk‐based portfolio allocations in currency carry trades

AbstractWith the exception of naive methods for portfolio selection, such as the equal weighted approaches, all other methods of portfolio allocation are more or less sensitive to the quality of the inputs considered in constructing the models and risk measures utilized in the allocation framework. The extensively used factor model proposed initially by Sharpe in 1963 has provided a robust backdrop for development of relevant, micro, macro, and context‐specific or asset specific explanatory variables to be incorporated in a statistical manner as inputs to forecasting models that can then be used to obtain risk measures upon which portfolio allocations are based. However, like all statistical models, a set of statistical assumptions accompany this factor model regression framework, one of which has recently been highlighted as seemingly nonvalidated in financial data. This is, of course, the assumption such factor models make on homoskedasticity or weak‐sense covariance stationarity of the returns processes being modeled. Such factor models, therefore, have typically failed to cope with an important and ubiquitous feature of financial assets data, which often demonstrates heteroskedasticity of the returns variances and covariances. We propose a novel generalized multifactor forecasting structure utilizing a covariance regression model, which allows us to incorporate the required heteroskedasticity effects while also admitting potential dependence in the idiosyncratic error terms. We argue that such a modeling approach allows for more explicit relationships to be interpreted between the driving factors and the conditional responses of the portfolio returns. We then compare the forecasting performances of our model with the multifactor model and the time series dynamic conditional correlation model through a currency portfolio application.

A cross-country study on manipulations in financial statements of listed companies

PurposeThe purpose of this study is threefold: first, to detect trends in financial statement manipulation; second, to measure the level of manipulation and to measure the variation in manipulation between countries; and, third, to identify widely used techniques in financial statements manipulation.Design/methodology/approachThis study uses financial data of listed companies from Asia, namely, Japan, Singapore, Malaysia, Indonesia, Thailand, Hong Kong and China. The study adopts financial ratios, financial forensic tool, dichotomous approach and statistical tools to analyze the data (84,000 observations) over a period of four years from 2010 to 2013.FindingsThe results show that 34 per cent of sample companies in selected Asian countries are involved in the manipulation of financial statements; the average level of manipulation (overall manipulation index) is 72 per cent; and there is a significant difference between countries at 5 per cent level. The study also identifies four most commonly used techniques, namely: days’ sales in receivable (DSRI), depreciation (DEPI), assets quality (AQI) and total accruals to total assets (TATA).Research limitations/implicationsAlthough this study found a significant national difference between countries in terms of practicing manipulation in financial statements, it did not address the issue of why some countries have higher level of manipulation and greater fluctuations in manipulation than others. Further study could be conducted to look for the reasons on these issues.Practical implicationsInvestors and other stakeholders are advised to judge the manipulation in financial statements before fixing up for investment. At least they should examine Sales, Accounts Receivable, Depreciation, Value of Fixed Assets and Accruals data before accepting the financial statement in good faith.Social implicationsThe trend of manipulation in financial statements is increasing day by day and that is why it needs to prevent to protect our society from white collar crime. The cost of white collar crime is much higher and key executives are making money at the expense of investors and other stakeholders. This kind of study creates awareness among stakeholders about the manipulation as well as provides techniques to examine the faithfulness of financial statements. Then, managers will not overstate or understate either revenues or expenses easily, as it can damage the goodwill.Originality/valueThis is the first study of its kind addressing measurement of manipulation score, overall manipulation index (OMI) and identification of widely used variables of manipulation in financial statements are new contributions towards existing literature of earnings manipulation.

Optimization Process of Compiling and Researching Archives in Universities Under the Background of Information Sharing

Internet era, mutual sharing, low cost, unlimited time and geographical restrictions on network dissemination, to the public to provide a new way of entertainment experience and sharing in the network information resources at the same time, also highlights important drawbacks, mainly reflected the contradiction between resource sharing and copyright protection, sharing is often cyber source violated the right to network dissemination of information to the original author. With the rapid development of the Internet, the seriousness of this problem is becoming increasingly prominent. Based on the information construction of university archives management as the center to carry out research, improve the service level of university archives from the first two aspects discusses the necessity of the information construction of the archives management, promoting the development of colleges and universities. Secondly introduces specific measures of realizing the informatization construction of university archives management and archives management standardization, digitization, archives information network construction, the archives management personnel to conduct a comprehensive training. The fixed assets of university is an important part of the state-owned assets, and its asset management level is directly related to the safety of state-owned assets, the use efficiency of assets and the promotion of the teaching and research level in universities. The university fixed assets data information management is an important aspect of asset management, it provides decision-making basis for the management of fixed assets in colleges and universities, affecting the efficiency of the entire asset management.

Big data systems: knowledge transfer or intelligence insights?

PurposeThis paper aims to bring together the existing theory from knowledge management (KM), competitive intelligence (CI) and big data analytics to develop a more comprehensive view of the full range of intangible assets (data, information, knowledge and intelligence). By doing so, the interactions of the intangibles are better understood and recommendations can be made for the appropriate structure of big data systems in different circumstances. Metrics are also applied to illustrate how one can identify and understand what these different circumstances might look like.Design/methodology/approachThe approach is chiefly conceptual, combining theory from multiple disciplines enhanced with practical applications. Illustrative data drawn from other empirical work are applied to illustrate some concepts.FindingsTheory suggests that the KM theory is particularly useful in guiding big data system installations that focus primarily on the transfer of data/information. For big data systems focused on analytical insights, the CI theory might be a better match, as the system structures are actually quite similar.Practical implicationsThough the guidelines are general, practitioners should be able to evaluate their own situations and perhaps make better decisions about the direction of their big data systems. One can make the case that all the disciplines have something to add to improving how intangibles are deployed and applied and that improving coordination between KM and analytics/intelligence functions will help all intangibles systems to work more effectively.Originality/valueTo the authors’ knowledge, very few scholars work in this area, at the intersection of multiple types of intangible assets. The metrics are unique, especially in their scale and attachment to theory, allowing insights that provide more clarity to scholars and practical direction to industry.

Incomprehension, dependency, and distrust in the presentation of fixed asset figures: Front stage dramaturgy

This study aims to explore the role of actors in presenting financial statements and those who manage assets in performing the presentation of fixed assets figures in the balance sheet. These actors consist of the major parts in various stories. Dramaturgy was employed as a method to analyze the roles, coupled with an analysis of impression management from John and Pittman Taxonomy. A thorough research review was conducted on the front stage. In some scenes, the actors performed intimidation when forcing other actors to present the asset data instantly. In another time, ingratiation was done to cover the weak-nesses when the assets caretaker felt neglected. The role of self-promotion was performed by the Financial Manager of Regional Work Unit (PPK-SKPD) when he wanted to show that he had worked hard to prepare the balance sheet and refuses to bear the errors when the balance sheet presenting assets data was in trouble. Impression management techniques were used entirely by the actors to show the desired self-image, at certain time and in cer-tain circumstances. The roles played by the actors give rise to the phenomenon that the fixed assets figures presented in the balance sheet rest on the condition of incomprehension, dependency, and distrust between the actors. The presentation of fixed assets figures in the balance sheet shows a series of accounting process filled by conflict, as seen throughout the show. This research is expected to increase the study in the context of academic on the topic of fixed assets, particularly in the public sector (government).

Assessment of economic status in trauma registries: A new algorithm for generating population-specific clustering-based models of economic status for time-constrained low-resource settings

ObjectivesLow and middle-income countries (LMICs) and the world’s poor bear a disproportionate share of the global burden of injury. Data regarding disparities in injury are vital to inform injury prevention and trauma systems strengthening interventions targeted towards vulnerable populations, but are limited in LMICs. We aim to facilitate injury disparities research by generating a standardized methodology for assessing economic status in resource-limited country trauma registries where complex metrics such as income, expenditures, and wealth index are infeasible to assess. MethodsTo address this need, we developed a cluster analysis-based algorithm for generating simple population-specific metrics of economic status using nationally representative Demographic and Health Surveys (DHS) household assets data. For a limited number of variables, g, our algorithm performs weighted k-medoids clustering of the population using all combinations of g asset variables and selects the combination of variables and number of clusters that maximize average silhouette width (ASW). ResultsIn simulated datasets containing both randomly distributed variables and “true” population clusters defined by correlated categorical variables, the algorithm selected the correct variable combination and appropriate cluster numbers unless variable correlation was very weak. When used with 2011 Cameroonian DHS data, our algorithm identified twenty economic clusters with ASW 0.80, indicating well-defined population clusters. ConclusionsThis economic model for assessing health disparities will be used in the new Cameroonian six-hospital centralized trauma registry. By describing our standardized methodology and algorithm for generating economic clustering models, we aim to facilitate measurement of health disparities in other trauma registries in resource-limited countries.

Perceived Benefits of Livestock Ownership among Female Smallholder Farmers of Mixed HIV Status in Nyanza Province, Kenya

BackgroundAlthough livestock is thought to contribute to household food security, dietary quality, and income, the extent of these benefits is highly variable. To date, evaluations of livestock programs have failed to clearly elucidate the pathways by which livestock affect the welfare of smallholder farmers in low‐income settings. One important reason for this may be that many livestock interventions fail to consider and adequately measure the outcomes that matter most to smallholder farmers themselves. We therefore 1) explored the benefits and disadvantages of livestock ownership as perceived by urban and peri‐urban smallholder farmers in Nyanza Province, Kenya, and 2) characterized how gender modified these benefits.MethodsTo achieve these objectives, we used a mixed‐methods approach with a subpopulation of pregnant and lactating women of mixed HIV status participating in an ongoing cohort study (Pith Moromo). We conducted a secondary analysis of in‐depth interviews with 24 women in the cohort who owned livestock, 10 of their household members, and one key informant who discussed the role of livestock in livelihoods (from the National Environment Management Authority). We then expanded on emergent themes with other women from the cohort using PhotoVoice (a participatory photo elicitation method, n=20), focus group discussions (n=20), and pile sorting (n=20).ResultsOf the 364 women in the cohort with household assets data, 28.0% owned livestock; among them chickens were most commonly owned(82.7%). The most commonly mentioned reason for owning livestock was to sell the animals; however, animals were typically said to be sold in response to an urgent need for cash rather than for regular income generation. While the majority of participants responded that animals were eaten at home, livestock did not appear to comprise a regular portion of their diets; rather, they were most commonly consumed to honor a visitor, as part of a celebration, or when other foods were unavailable. Additionally, livestock played an important role in the maintenance of social relationships and reinforcement of social status. Most participants agreed that women are highly involved in livestock care but rarely have equal input in decision‐making around selling or slaughtering animals, especially for larger livestock. Most women also agreed that when animals were slaughtered for home consumption, men were preferentially allocated the most desirable portions.ConclusionsOur results suggest that pathways between livestock ownership and household welfare are indirect and complex. Participants in this study valued livestock primarily as an economic and social safety net to strengthen household resilience, rather than as a regular source of income or food. Our results additionally suggest that cultural norms limit the benefits that female farmers obtain from livestock. Future livestock interventions must therefore take into account how livestock is used and valued by farmers and carefully consider the modifying effect of gender norms to maximize livestock ownership benefits for women.Support or Funding InformationNIH T32 OD011000 (SED)NIH K01 MH098902 (SLY)

The measurement of intellectual capital and the effects on firm value:an application in cement industry

Improvement in knowledge and technology increase the importance of Intangible Assets or Intellectual Capital for today’s companies. Intellectual capital or intangible assets played a huge important role over being sold of the companies at a very high price of their market values. In this study, at first, the definition of intellectual capital or intangible assets is made; also its measuring techniques are explained. And then the Intellectual Capital of 5 companies, which are operating in cement industry in Marmara Region, are tried to calculate by “Calculated The Method of Intangible Assets”. In this study we studied with 5 firms which ones operating in the Marmara region and listed in Istanbul Stock Exchange (BIST). We used their data between 2010-2011, 2011-2012 and 2012-2013 which are explained by their financial statements. We took their financial statements from The Public Disclosure Platform (KAP). First, we calculated to firms’ profit before interest and taxes by using their data. After that we calculated to average intellectual capital value with using to tangible assets data.

Security in cloud computing: Opportunities and challenges

The cloud computing exhibits, remarkable potential to provide cost effective, easy to manage, elastic, and powerful resources on the fly, over the Internet. The cloud computing, upsurges the capabilities of the hardware resources by optimal and shared utilization. The above mentioned features encourage the organizations and individual users to shift their applications and services to the cloud. Even the critical infrastructure, for example, power generation and distribution plants are being migrated to the cloud computing paradigm. However, the services provided by third-party cloud service providers entail additional security threats. The migration of user’s assets (data, applications, etc.) outside the administrative control in a shared environment where numerous users are collocated escalates the security concerns. This survey details the security issues that arise due to the very nature of cloud computing. Moreover, the survey presents the recent solutions presented in the literature to counter the security issues. Furthermore, a brief view of security vulnerabilities in the mobile cloud computing are also highlighted. In the end, the discussion on the open issues and future research directions is also presented.

Job Security in the Cloud Computing

 Abstract—Cloud computing is a burgeoning Internet computing paradigm. The convenient, cheap and elastic resources in the cloud are attracting the users to migrate their assets (data, computing and software, etc.) into it. However, cloud also caused the serious worry about the security of those assets, since the resources are not under the control of the users. Traditional security mechanisms are usually aimed at single autonomous domain and are not suitable for protection of those assets migrating between autonomous domains. This paper caters to the security of aforesaid migrated assets, defines them as job, studies their security demands, analyses the security threats to them, and proposes the essential protecting mechanisms for it. Our work is from the point of view of the users, and thus will be more suitable for solving the security problem of their assets. 

The dynamics of regional and global multinationals, 1999-2008

Purpose – This paper aims to analyze regional versus global activities of large firms. We assemble longitudinal data over the 1999-2008 period. Design/methodology/approach – Sales and assets data for the Fortune 500 firms from 1999-2008 were compiled from annual reports of the firms, by triad region. The definition of the triad regions is based on international accounting standards. The classifications of firms are based upon the new metric of regional-to-total sales rather than the traditional metric of foreign-to-total sales. Findings – In an extension of the original study of Rugman and Verbeke (2004), no trend toward globalization is found, as nearly 80 per cent of the world’s largest firms are classified as home-region oriented, and only 4 per cent are classified as global. Only a few firms change classifications over the ten-year period. Overall, the world’s largest firms average 70 per cent of their sales and 72 per cent of their assets in their home region of the triad. Originality/value – This paper is the first one to use longitudinal data in the analysis of regional versus global firms, with ten years of data on the regional sales and assets of the world’s 500 largest firms.

The Size Distribution of US Banks and Credit Unions

This study examines the firm size distribution of US banks and credit unions. A truncated lognormal distribution describes the size distribution, measured using assets data, of a large population of small, community-based commercial banks. The size distribution of a smaller but increasingly dominant cohort of large banks, which operate a high-volume low-cost retail banking model, exhibits power-law behaviour. There is a progressive increase in skewness over time, and Zipf’s Law is rejected as a descriptor of the size distribution in the upper tail. By contrast, the asset size distribution of the population of credit unions conforms closely to the lognormal distribution.

An Ideal Schema Design of an Industrialized PL-ISEE Database Platform

Using the automation production and management system of modern manufacturing industry product line for reference, a new industrialized PL-ISEE (product line based integrated software engineering environment) model was proposed by us in reference [4]. In the new model, the middle part in the PL-ISEE architecture is data layer which is composed of the software components bus and environment database platform to achieve the storage and managements of product line core assets data. In this paper, the environment database platform architecture and its schema design as well as implementation mechanism are further researched. Whole database platform architecture consists of the product line asset objects management service and core assets database system. The data model and database schema of the database system are designed and created by using a united core asset concept model and data organization model. The database supporting platform with the model and schema can well satisfy all the requirements of interfaces, tools and data integration as well as product line assembling production in the PL-ISEE. Therefore, the design and realizing ideas of the PL-ISEE database platform will be useful for researching on product line engineering and methodology in the future.

Research on the Realizing Mechanism of an Industrialized PL-ISEE Database Platform

Using the automation production mode of modern manufacturing industry for reference, a new industrialized PL-ISEE (product line based integrated software engineering environment) model was proposed by us in reference [8]. The middle part of the PL-ISEE architecture is data layer which is composed of the software components bus and core assets database platform to achieve the storage and managements of product line core assets data. In this paper, the architecture and its implementation mechanism of the PL-ISEE database platform is further researched. Whole platform architecture consists of core asset objects management service and assets database system. The data model and database schema as well as database views of the database platform are designed and created by using united product line concept model and data model. So, the database supporting platform’s functions and configuration also well satisfy the requirements of interfaces, tools and data integration as well as product line assembling production in the PL-ISEE. Therefore, the design and realizing ideas of the PL-ISEE database platform will be valuable to research product line engineering and methodology in future.

Framework and CORBA Implementation of A New Industrialized PL-ISEE Database Platform

Using the automated production and management system of modern manufacturing industry production line for reference, a new industrialized PL-ISEE model was proposed by authors in article [8]. In the new model, the middle part of the PL-ISEE architecture, data layer, is composed of the software components bus and environment database supporting platform which achieves the storage and managements of product line core assets data. According to the organisation structure and assembling needs of product line core asset components, the PL-ISEE database platform framework and its schema and view design as well as implementation methods are further researched in the paper. The data model, database schema and application views of the database platform are designed and created by using a united core asset data model and product line assembling evolution model. The schema and views based the database platform can well satisfy all the ability requirements of the core asset data integration and assembling producing mode of software product line engineering. Finally, the realizing method of the new industrialized PL-ISEE database support platform based on the CORBA architecture is also proposed and discussed in detail.