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Trade‐offs among logistics cost and service elements often make transport selection analysis difficult, especially when demand is uncertain and carriers offer different rates and services. The spreadsheet environment offers a powerful, manager‐friendly medium for analysing these trade‐offs. This microcomputer application exploits some of the recent advances in spreadsheet technology to provide transport buyers with a tool for evaluating such complex logistical trade‐offs. This tool demonstrates how the emerging spreadsheet technology makes it relatively easy to develop a computer‐based model that can capture a rich level of detail that is beyond the scope of the current transport selection models using analytical approaches.

This article aims to report on the development and validation of a bribery measurement index for the business sector, which, based on institutional theory, seeks to overcome the limitations of traditional measurements, recognizing the dynamics that originate the phenomenon and identifying process components.

To construct the index, correlational and principal component analysis techniques were used, as well as rigorous statistical tests, validating the instrument in a sample of 2,963 companies in Latin America, including Argentina, Colombia, Chile, Ecuador, Guatemala, Mexico and Peru.

The result was an instrument composed of two dimensions: (1) anti-bribery game rules, composed of regulations knowledge and anti-bribery efforts, and (2) bribery as a perceived habit, allowing an objective representation of reality due to its internal consistency, concurrent and discriminant validity.

This instrument is one of the few that focuses on measuring bribery in the business sector in terms of corrupt practices, applicable for both public and private institutions to promote game rules against bribery. Additionally, the proposed theoretical model can be used to measure other phenomena with similar characteristics.

This article empirically highlights different variables that make bribery possible. The results can be helpful in the design of strategies to prevent this type of behavior. It also highlights the importance of designing mechanisms to record information related to bribery and the different expressions of corruption in order to explain its different nuances.

Este artículo informa sobre el desarrollo y validación de un índice de medición de soborno para el sector empresarial, que, basado en la teoría institucional, busca superar las limitaciones de las mediciones tradicionales, reconociendo las dinámicas que originan el fenómeno e identificando los componentes del proceso.

Para la construcción del índice se utilizaron técnicas de análisis correlacional y de componentes principales, así como rigurosas pruebas estadísticas, validando el instrumento en una muestra de 2.963 empresas de América Latina, entre ellas Argentina, Colombia, Chile, Ecuador, Guatemala, México y Perú.

El resultado fue un instrumento compuesto por dos dimensiones: (1) reglas de juego antisoborno, compuestas por conocimiento normativo y esfuerzo antisoborno (2) soborno como hábito percibido, permitiendo una representación objetiva de la realidad debido a su consistencia interna, validez concurrente y discriminante.

Este artículo pone en evidencia empírica diferentes variables que hacen posible el soborno. Los resultados pueden ser útiles en el diseño de estrategias para prevenir este tipo comportamiento, también destaca la importancia de diseñar mecanismos para registrar la información relacionada con la lucha contra el soborno.

Este instrumento es uno de los pocos que se enfoca en medir el soborno en el sector empresarial en términos de prácticas de corrupción, útil para instituciones tanto públicas como privadas para promover mejores reglas de juego en contra del soborno. Adicionalmente el modelo teórico propuesto puede ser utilizado para medir otros fenómenos con características similares.

Although sustainability is a popular topic in the past decade, there is a lack of research to identify the driving factors for developing countries. The purpose of this paper is to investigate the driving factors for achieving eco-innovation.

An in-depth case study is employed to address the objective outlined above. A Chinese company with more than 1,200 employees was selected to address the research question.

By fuzzy decision-making trial and evaluation laboratory and interpretive structural modelling analysis, the driving factors for eco-innovation are identified, and the priority of different factors has also been extracted.

This is among the first studies to carry similar analysis regarding eco-innovation. More specifically, this is perhaps the first study to take this approach and to analyse this topic in a developing country.

This paper aims to investigate feedback trading and autocorrelation behavior in the cryptocurrency market.

It uses the GJR-GARCH model to investigate feedback trading in the cryptocurrency market.

The findings show a negative relationship between trading volume and autocorrelation in the cryptocurrency market. The GJR-GARCH model shows that only the USD Coin and Binance USD show an asymmetric effect or leverage effect. Interestingly, other cryptocurrencies such as Ethereum, Binance Coin, Ripple, Solana, Cardano and Bitcoin Cash show the opposite behavior of the leverage effect. The findings of the GJR-GARCH model also show positive feedback trading for USD Coin, Binance USD, Ripple, Solana and Bitcoin Cash and negative feedback trading for Ethereum and Cardano only.

This paper contributes to the literature by extending Sentana and Wadhwani (1992) to explore the presence of feedback trading in the cryptocurrency market using a sample of the most active cryptocurrencies other than Bitcoin, namely, Ethereum, USD coin, Binance Coin, Binance USD, Ripple, Cardano, Solana and Bitcoin Cash.

This work aims to establish the relationship between painting art and sustainability, which allows for highlighting implications likely to improve sustainability for humanity's welfare.

To achieve this objective, painting art is measured by a composite index aggregating the quantity and quality represented by the market value. As for sustainable development, it is represented by a composite index comprising three variables: the climate change performance index (ecological dimension), the wage index reflecting distributive justice (social dimension) and the gross domestic product (economic dimension). The composite indices were determined through adjusted data envelopment analysis. In addition, two other methods are used in this work: correlation analysis and a neural network method. These methods are applied to data from 2007 to 2021 across the world.

The correlation method highlighted a perfect positive correlation between painting art and sustainability. As for the neural network method, it revealed that the quality of painting has the greatest impact on sustainability. The neural network method also showed that the most positively impacted variable of sustainability by painting art is the social variable, with a pseudo-probability of 0.90.

The relationship between painting art and sustainability is underexplored, in particular in terms of statistical analysis. Therefore, this research intends to fill this gap. Moreover, analysis of the relationship between both using composite indices computed via an original method (adjusted data envelopment analysis) and a neural network method is nonexistent, which constitutes the novelty of this work.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0006

The 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.

This 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.

The 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).

Although 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.

Investors 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.

The 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.

This 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.

The purpose of this paper is to compute an aggregate misalignment index using a multiple indicator approach to identify under- or over-valuation of house prices in Malta based on fundamentals.

A total of six indicators are used that capture households, investors and system-wide factors: the house price-to-Retail Price Index ratio, the price-to-hypothetical borrowing volume ratio, price-to-construction costs ratio, price-to-rent ratio, dwelling investment-to-GDP ratio and the loan bearing capacity. The weights are derived using principal component analysis. The analysis is performed using both the house price indices of the National Statistics Office (NSO) and the Central Bank of Malta (CBM), which are based on contract and advertised prices, respectively.

House prices in Malta were overvalued by around 20 to 25 per cent in the pre-crisis boom. This disequilibrium started to be corrected following the decline in house prices, with the CBM and NSO house price cycles reaching a trough in 2013 and 2014, respectively. At the trough, house prices were undervalued by around 10 to 15 per cent. Since then, house prices started to recover although the recovery in advertised prices was more pronounced compared to that based on contract prices. In mid-2017, advertised house prices were slightly overvalued, while contract prices still have to reach their equilibrium level. The dynamics from the misalignment index, including its peaks and troughs, are remarkably similar to the range derived from statistical filters.

Estimates of house price misalignment have both economic and financial stability implications.

This paper allows for a decomposition of the house price cycle, tailored for the particular characteristics of the Maltese housing market. It also takes into account the relationship between house prices and private sector rents, which in recent years have been buoyed, among other factors, by the high inflow of foreign workers and changing patterns in the tourism industry.

The purpose of this paper is to extend the literature on the spillovers across economic policy uncertainty (EPU) and cryptocurrency uncertainty indices.

This paper uses cross-country economic policy uncertainty indices and the novel data measuring the cryptocurrency price uncertainties over the period 2013–2021 to construct a sample of 946 observations and applies the time-varying parameter vector autoregression (TVP-VAR) model to do an empirical study.

The findings suggest that there are cross-country spillovers of economic policy uncertainty. In addition, the total uncertainty spillover between economic policies and cryptocurrency peaked in 2015 before gradually decreasing in the following periods. Concomitantly, the cryptocurrency uncertainty has acted as the “receiver.” More importantly, the authors found the predictive power of economic policy uncertainty to predict the cryptocurrency uncertainty index. This paper’s results hold robust when using alternative measurement of cryptocurrency policy uncertainty.

This study is the first research that deeply investigates the association between two uncertainty indicators, namely economic policy uncertainty and the cryptocurrency uncertainty index. We provide fresh evidence about the dynamic connectedness between country-level economic policy uncertainty and the cryptocurrency index. Our work contributes a new channel driving the variants of uncertainties in the cryptocurrency market.

The purpose of this study is to examine the relationship between financial strength or condition and managerial practices in preparing financial statements of public limited companies. The objectives of this study are threefold – to measure the financial strength, to measure integrity index and to examine the relationship between management practices and financial strength.

Financial ratios, Altman’s Z-Score, integrity index, ranking approach and chi-square test are used to achieve the objectives. A multi-year cross-country analysis is done by considering sample of seven Asian countries, namely, Malaysia, Singapore, Thailand, Indonesia, Hong Kong, China and Japan.

The study catches the relationship between management practices and financial strength across sample countries. Management practices is one of the responsible factors for this relationship. They use discretionary power in preparing financial statements to control the trading results. The principles of accounting do not support the alteration of financial data to look the company better on paper. The cost of financial statement fraud is higher than other occupational fraud.

This study does not cover factors other than management practices and further study could be conducted to look for the other reasons that may also responsible for the deviations.

Conflict of interest between shareholders and board of directors is not a new phenomenon. Auditing system is introduced to minimize this conflict of interest, but they failed to uphold their position in reality. Management also needs to prove their integrity in financial statements. Ethical consideration is the highest priority.

Stakeholders, especially regulators, professional bodies and academics, should concentrate on the issue on ‘how to reduce the manipulation in financial statements’ to create a safe investments avenue for the nation.

This study provides empirical evidences regarding the influence of management practices on financial statements and financial strength of listed companies across countries. The culture, attitudes, beliefs, perceptions, etc., are different from country to country. The aim is to contribute empirical evidence about the relationship between management practices and financial health in different settings. This study is first of its kind.

The purpose of this paper is to construct indices on Indonesia’s economic infrastructure. The components of infrastructure include transportation, communications and electricity. In constructing the indices, the authors use the longest available data covering the period 1970-2015. The indices of each component of infrastructure are aggregated linearly with the weights calculated using principal component analysis (PCA). The infrastructure index for Indonesia has had a positive increasing trend since 1970, particularly supported by the increase in the infrastructure indices of electricity and telecommunication. Meanwhile, the infrastructure index of transportation has been relatively stable. The infrastructure index constructed shows positive relation with Indonesia’s GDP growth and GDP per capita.

In constructing the indices, the authors use the longest available data covering the period 1970-2015. The indices of each components of infrastructure are aggregated linearly with the weights calculated using PCA.

The infrastructure index for Indonesia has a positive increasing trend since 1970, particularly supported by the increase in the infrastructure indices of electricity and telecommunication. Meanwhile, the infrastructure index of transportation has been relatively stable. The infrastructure index constructed shows positive relation with Indonesia’s GDP growth and GDP per capita.

The novelty of this research is a construction of the infrastructure index for Indonesia. The infrastructure index is important to benchmark the level of infrastructure development and to understand its connection to economic growth. It is also an important barometer used by policymakers for infrastructure investment and planning purposes.