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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.

The purpose of this study aims to synthesize a novel donor–acceptor dye based on phenothiazine as a donor (D) and nonconjugated spacer was devised and synthesized by condensing of 2,2'-(1H-indene-1,3(2H)-diylidene) dimalononitrile with aldehyde and the practical synthesis methodology as given in Scheme 1.

The prepared phenothiazine dye was systematically experimentally and theoretically examined and characterized using nuclear magnetic resonance spectroscopy (1H,13C NMR), Fourier-transform infrared spectroscopy (IR) and high-resolution mass spectrometry. Density functional theory (DFT) and time-dependent density functional theory DT-DFT calculations were implemented to determine the electronic properties of the new dye

The UV-Vis absorption and fluorescence spectroscopy of the synthesized dye was investigated in a variety of solvents with varying polarities to demonstrate positive solvatochromism correlated with intramolecular charge transfer (ICT). The probe’s quantum yields (Фf) are experimentally measured in ethanol, and the Stokes shifts are found to be in the 4846–9430 cm⁻¹ range.

The findings depicted that the novel (D-π-A) chromophores may act as a significant factor in the organic optoelectronics.

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 study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

We examine the cardinal gap between wage distributions of the incumbents and newly hired workers based on entropic distances which are well-defined welfare theoretic measures. Decomposition of several effects is achieved by identifying several counterfactual distributions of different groups. These go beyond the usual Oaxaca–Blinder decompositions at the (linear) conditional means. Much like quantiles, these entropic distances are well-defined inferential objects and functions whose statistical properties have recently been developed. Going beyond these strong rankings and distances, we consider weak uniform ranking of these wage outcomes based on statistical tests for stochastic dominance. The empirical analysis is focused on employees with at least 35 hours of work in the 1996–2012 monthly Current Population Survey (CPS). Among others, we find incumbent workers enjoy a better distribution of wages, but the attribution of the gap to wage inequality and human capital characteristics varies between quantiles. For instance, highly paid new workers are mainly due to human capital components, and in some years, even better wage structure.

Empirical studies on household-level inflation inequality have so far only focused on periods with positive inflation rates. However, the major concern on the policy agenda since the most recent financial crisis has been deflation rather than inflation. This naturally raises the question regarding the effect of deflation on the distribution of real income when households spend their budget on different consumption bundles. This chapter compiles annual household-level inflation rates in Denmark from 1930 to 1935 based on microdata from the Expenditure and Saving Survey of 1931 and price data from the official Retail Price Index. The results indicate that lower-income households faced a larger decline in prices on their consumption of goods and services during the deflation years 1930–1932 than higher-income households did. The deflation thus contributed to narrowing the difference in real incomes between the top and bottom parts of the income distribution during the recession. In the years 1933–1935 with positive inflation rates, the lower-income households experienced higher inflation rates than higher-income households. Over the period 1930–1935 seen as a whole, the price development contributed slightly to reducing real income inequality. The low degree of medium-term persistence of differences in household-specific inflation rates is consistent with previous findings in various time periods from the 1960s to the 2000s without any persistent deflation events. The chapter at hand is the first empirical study of the direct distributional effects of price developments at the household level in a period with persistent deflation.

Claims and disputes are often unavoidable in the construction industry due to its unique and complex characteristics involving the massive investment of capital, lengthy project duration, and multiple project stakeholders. This chapter intends to identify the critical construction claims attributes, compare the perceptions of major stakeholders on different claim attributes, and investigate the contrast of the top five claim attributes between this study and previous ones. The literature review resulted in 48 claim attributes responsible for the construction project schedule delays. These attributes were then presented to Vietnam construction industry (VCI) practitioners in the form of a questionnaire survey. Data analysis was done based on the collected 113 qualified samples. Relative importance index (RII) was applied to determine the ranking of claim attributes. The results were that the top five causes of claims, that is, payment delays, mistakes by contractor during construction stage, delays in work progress by the contractor, financial failure of the contractor, and frequently changing requirements by the owner, lead to the schedule delays in VCI. These findings can assist the local industry practitioners and foreign companies seeking a share in the VCI market in understanding the causes of construction claims comprehensively and formulating the countermeasures to minimise their impacts and hence reduce the unnecessary losses and raise the likelihood of success as well as maintain sustainable relationships among stakeholders.

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