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The Chinese Telecoms Industry has been rapidly growing over the years since 2001. An analysis of financial performance of the three giants in this industry is very important. However, it is difficult to know how many ratios can be used best with little information loss. The paper aims to discuss this issue.

A total of 18 financial ratios were calculated based on the financial statements for three companies, namely, China Mobile, China Unicom and China Telecom for a period of 17 years. A principal component analysis was run to come up with variables with significance value above 0.5 from each component.

At the end, the authors conclude how financial performance can be analysed using 12 ratios instead of the costly analysis of too many ratios that may be complex to interpret. The results also showed that ratios are all related as they come from the same statements, hence, the authors can use a few to represent the rest with limited loss of information.

This study will help different stakeholders who are interested in the financial performance of each company by giving them a shorter way to analyse performance. It will also assist those who do financial reporting on picking the ratios which matter in reflecting the performance of their companies. The use of PCA gives unbiased ratios that are most significant in assessing performance.

Changes in food retailing (globalization, concentration) have negative impacts on smaller, “traditional” food retail businesses. Their market share decreasing year by year. The purpose of this study is to examine and compare the financial performances of these businesses under the given circumstances and current economic environment in a Hungarian and a Romanian county.

The study is based on two complete databases, including all companies that behoove retail food activity (considering the NACE cod) in the counties of Hajdu-Bihar (Hungary) and Cluj (Romania). The database analyzed contains the financial statements for five consecutive years for 212 and 690 businesses. Databases were examined by the most typical financial indicators using the multivariate and univariate analysis of variance and the k-medoid cluster analysis methods.

The results of the analysis have shown that there are differences in the number of retail food companies in the case of two counties, both in number and in financial performance. Companies in Hajdú-Bihar county perform better in terms of financial ratios than those in Cluj county. The groups created by k-medoids cluster analysis are relatively well distinguished in the case of Hajdú-Bihar county, while the picture is much more mixed in the case of Kolozs county. However, it is also important to note that the companies analyzed should generally perform better to survive.

Among the limitations of the study, it is important to note that the findings are relevant only to the two counties examined. Another limiting factor is that quite several companies had to be excluded from the analysis due to missing data or outliers.

The study presents for the corporate decision-makers the current performance of the companies of the sector examined in the two counties. The results of the study highlight the business areas of concern in management. The findings show that they need to change this performance to strengthen their market position. We believe that it is not enough to complain about the expansion of the supermarket chains, but they should take appropriate actions to improve their situation. Based on the results of the study, it can be concluded that there is a need to improve the financial efficiency of retail food companies in both counties to survive in the long run. This improvement is essential because retailers can play an important role in smaller settlements and narrower residential environments.

Comparative analysis of retail food companies in similar counties in these two neighboring countries has not been conducted using complex financial analysis. The study revealed the common and/or individual characteristics of these companies.

This study aims to examine whether insourcing of processes pays off and verifies key hypotheses regarding the financial ratios of organisations.

This paper randomly selects and then surveys 1996 organisations, of which 9.5% (190) stated that they used insourcing, 1.9% (37) made a decision to implement insourcing in the near future and 88.6% did not use insourcing. Then, for available firm data (100 insourcing firms and 100 firms without it), the financial statements of the surveyed companies were obtained to compare the most important financial ratios. The financial situation was compared at four-time points. The mean and median values of individual indicators were compared with the significance of relevant statistical tests.

A U-shaped curve of financial results in the time of enterprises that implemented insourcing and reverse U-shaped curve for enterprises that did not have insourcing are seen. Thus, the insourcing of processes pays off in the long run.

Limitations exist in the generalisation of the results obtained, due to the limited number of samples qualified for analyses (limited reliable financial data).

The research highlights the importance of effective insourcing projects in the long term.

This study is the first to quantify the financial performance of companies that have used insourcing in comparison with a reference group. This paper defines insourcing and contributes to the growing number of studies on insourcing by bringing attention to the financial outcomes in the long run.

The purpose of this paper is to quantify several measures to examine the determinants of profitability for the listed Indian banks. The authors include both public sector (PSUs) and private sector’s banks in the study. The authors have taken all the banks that are registered on the Bombay stock exchange (BSE) in the sample. This paper also intends to identify the association between the net profit margin (PM) and return on assets (ROA) with the several other independent variables of the Indian banking sector including private banks and public banks over the past six years starting from April 1, 2012 to March 31, 2017. Therefore, a sample of 39 listed banking companies and total 195 balanced observations are selected for the analysis purpose.

The authors have used profitability as a dependent variable represented by net PM, ROA and several financial ratios as independent variables. Financial statement and income statement of all listed banks were obtained from BSE and particular company’s website. Panel data regression has been analyzed with both the descriptive research techniques, i.e., fixed effects and random effects. The authors also verified both panel techniques with Hausman’s specification test, which is a widely used procedure for selecting a panel effect. The authors applied PP – Fisher χ², PP – Choi Z-statistics and Hadri to testing whether the data set is free from unit root problem and data set is a stationary series.

Results imply that interest expended interest earned (IEIE) and credit deposit ratio (CRDR) reduced the profitability of private banks in India. IEIE, CRDR and quick ratio (QR) reduced the profitability of public banks in India, while cash deposit ratio (CDR) and Advances to Loan Funds (ALF) increased the effectiveness of public banks. Under the total banks IEIE, CRDR reduced the profitability, on the other side, CDR, ALF and Total Debt to Owners Fund (TDOF) increased the profitability of total banks in India. Under the dependency of ROA, CRDR and TDOF reduced the return of private banks in India, while CDR, ALF and QR enhanced the profitability of private banks.

No variables found significant under public banks while taking ROA as a dependent variable. Under the overall banking data, CRDR reduced the profitability. On the other side, capital adequacy ratio and ALF increased the profitability of total banks in India. The findings of this study will support policy creators, financial executives and investors in constructing investment decisions.

This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

Purpose – This research study aims to answer the question of how good is the development of the extended regency, and which shows better autonomy of development—before or after expanding. The implications of this study is to answer whether expanding a regent is truly needed to improve the economic development and welfare of the remote regions and their people. This study analyzes the autonomous state of three regencies, North Aceh, Bireuen and Lhokseumawe districts, which have expanded. The analysis takes into consideration the difference in the proportion of their regional revenues, budgeting perfomance, and economic growth as indicators of regional autonomy.

Design/Method/Approach – The data used in this research are secondary data sourced from the budget realization report and the accountability report of North Aceh, Bireuen, and Lhokseumawe districts from 2006 to 2013. The data analysis methods used in this study are the analysis of financial ratios and the comparative mean of one way anova.

Finding – The results showed a significant value or a probability value more than 0.05. Thus, the hypothesis (H1) is rejected, and therefore the hypothesis (H0) is received.

Research Impication – The implication is that there is no difference in the average of regional autonomy of North Aceh Regency, Bireuen, and Lhokseumawe districts as seen from the proportion of local revenue, budgeting perfomance, and regional growth. It means that with regard to financial performance there is no difference in the level of independence in autonomy among the three regions. The proportion of local revenue, financial permormance area, and the development of North Aceh, Bireuen, and Lhokseumawe districts demonstrate no influence on the level of independence in autonomy.

This research investigates the top five pharmaceutical companies in India to determine whether their financial structures are sound and if they face the risk of bankruptcy, highlighting the potential contribution of intellectual capital (IC) to financial stability.

The analysis outlines operating ratios, profitability ratios, possibility of bankruptcy (through Z-scores) and attractiveness of the financial structure (through the F-score), with consequent focus on (IC).

The financial structure of the selected companies seems stable. Changes in the Indian pharmaceutical scenario, above all, regarding the patent system, will force the companies to consider the impact of IC carefully.

Indian pharmaceutical companies need sustainability and development, with increasing focus on patent issues. To enhance innovation capabilities and overcome international competition, they should redesign their business orientation towards IC, mainly when impacting patents.

Using established approaches for predicting potential bankruptcy, this study focuses on the financial performance of top Indian pharmaceutical companies. IC can support financial stability, and this study provides further perspectives for managing their financial structure, both statically and dynamically.

According to the Association of Certified Fraud Examiners, financial statement fraud represents the smallest amount of fraud cases but results in the greatest monetary loss. The researcher previously investigated the characteristics of financial statement fraud and determined the presence of 16 fraud indicators. The purpose of this study is to establish whether investors and other stakeholders can detect and identify financial statement fraud using these characteristics in an analysis of a company’s annual report.

This study analyses a financial statement fraud case, using the same techniques that were previously applied, including horizontal, vertical and ratio analysis. These are preferred because stakeholders have relatively easy access to them.

The findings show several fraud characteristics, with a few additional ones not previously found prevalent. Financial statement fraud thus tends to differ between cases. It is also easier to detect and identify fraud indicators ex post facto.

This study is a practical case showing that financial statement fraud can be detected and identified in the financial statements of companies that commit fraud.

The banking sector in West Asia has always experienced positive growth except for Palestine. Apart from some negligible outlying outcomes in some countries that have faced political crises and war, most West Asian countries have gained bank profitability and efficiency. However, the stability in the banking sector has been rarely examined in the literature. Hence, this study sheds light on examining bank stability by considering 12 countries in West Asia.

A fixed effect panel data regression analysis is employed on strongly balanced panel data using data from 2004 to 2018.

Results reveal that the net interest margin has a positive relationship with bank stability. The bank’s stability rises as the net interest margin improves. Furthermore, the non-interest income reveals a positive significant impact on the stability of banks, depicting that the increase in non-interest income increases the stability of banks. Additionally, the non-interest expense also reveals positive significant results with the stability of banks. Nevertheless, leverage ratio and long-term debt portray a negative significant impact on banks’ stability. The finding reveals that higher long-term debt and leverage ratios may decrease the stability of the banks in West Asia.

Overall, the authors’ findings add to the literature on the stability of the banks by providing some new but significant information. Some of the recommendations may be beneficial to the long-term success of 12 Western Asian countries’ banks.

The study examines the stability of banks by incorporating both profitability and operating efficiency along with net-interest income, which extends to the current literature’s insight.

Technology parks (TPs) are used as a tool to improve economic outlook of the region through innovation generation. This study aims to evaluate the perception of tenants of TPs to determine the gap in the expectation and identify types of firms preferring to locate in a TP.

This is the first study in Pakistan to collect data about perceived benefits of TPs in Pakistan from the decision-makers of 110 tenant firms. The cluster analysis and lift ratios are used to draw statistical inferences.

The firms can be classified into three clusters – commercial-orientation firms, science and technology-oriented firms and young tech firms – with distinct needs for survival and growth in a TP. Moreover, TPs should not just be treated as property projects for providing support services, also knowledge sharing, training and development opportunities and proximity to hubs of knowledge and markets is vital to attract a variety of industry.

Academia and policymakers have been equally interested in the potential impacts of these innovation hubs. However, there have been lack of empirical evidence on how and what to offer the incumbents of these TPs. The government of Pakistan is trying to build more TPs for promoting business activities under CPEC. Therefore, it is extremely important to determine the needs of tenants of TPs for successful utilization of huge amount of public money to be invested in TPs.