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This study aims at examining the value relevance of tax-related information in Canada. Tax-related information in this study includes taxable income, tax aggressiveness, and tax risk (i.e., unsustainable tax planning).

This study analyzes the Canadian listed firms covering the period of 2012–2021 using the Feltham–Ohlson valuation model.

The findings are: (1) taxable income provides incremental value relevance information; (2) tax risk reduces the value relevance of both taxable income and accounting income and (3) tax aggressiveness reduces the value relevance of accounting income but not of taxable income. Further tests show that the COVID-19 pandemic increases the value relevance of taxable income but decreases the value relevance of accounting income. An analysis of the association between stock price volatility and tax-related information documents that taxable income and accounting income are both informative. Tax risk reduces the informativeness of taxable income, but tax aggressiveness and the pandemic do not.

The sample in this study covers the period up to 2021. Future research could use more recent data. Additionally, this study examines the Canadian setting. The results may not be generalized to other countries that have different accounting and tax rules.

This study sheds light on whether tax aggressiveness and tax risk affect the value relevance of taxable income and accounting income separately. In addition, to our knowledge, this is the first study that examines whether tax-related information is informative about stock price volatility.

Corporate diversity encompasses the different talents, knowledge, cultures, experiences and values of its employees. This diversity is reflected in multiple characteristics, such as race, age, gender, social class, religion, sexual orientation, ethnicity, culture and disability. The objective of this study is to identify if diversity is a value driver.

We take the diversity score from the Diversity Leaders Index 2023 published by Financial Times (FT) and Statista; this will be our independent variable in linear regression models whose objective variables are relevant fundamental indicators of the Euro Stoxx 50 companies. It is, therefore, a cross-sectional sample with financial data taken as of the current date. We have 37 Euro Stoxx 50 components included in the diversity ranking.

The results indicate that diversity is not a value driver for trading volume, for its revenue, or for systematic risk measured by the beta parameter. However, it is observed, in a confidence interval of 90%, that the most diverse companies are larger (according to their market capitalization). In addition, the most diverse companies are more profitable [return on assets (ROA)] and valued by the market [price to earnings ratio (PER)] in a confidence interval of 95%.

These results indicate that companies should promote corporate diversity as a management strategy, as it is observed that more diverse companies are more profitable and valued by the market. This study provides a quantitative vision in the context of homogeneous companies such as the Euro Stoxx 50 Index on the aspects in which diversity is a value driver.

This study aims to explore the moderating effects of strategy on the relationship between working capital management (WCM) and profitability.

A data sample of 72,444 firm-year observations of US-listed firms during 2000–2020 was used. The research hypotheses were tested using a panel regression analysis and an appropriate research instrument that signifies a firm’s strategic positioning.

The prospecting (defending) strategy has a decreasing (increasing) moderating effect on the relationship between WCM and profitability. The empirical findings are not affected by the level of earnings management, the presence of motives to meet earnings targets or the intensity of unreported intangible assets. Additionally, the reported empirical results remain robust within the context of propensity score matching regression analysis, in the presence of nonlinear effects of WCM on profitability, when alternative measures of WCM are used, and between firms with an increase or decrease in future profitability or different levels of efficiency on net WCM investments.

This study may stimulate future research exploring the moderating effects of various variables on the relationship between WCM and operating performance.

The findings highlight the importance of strategy for improving the performance evaluation of WCM policies and the prediction accuracy of the consequences of a strategy on short-term operating performance.

Prior empirical research has documented either a negative or positive relationship between WCM and profitability, which implies the presence of moderating effects of various factors. This study provides empirical evidence of the moderating effects of strategy on the relationship between WCM and profitability.

This study aims to investigate and test the impact of competitive priorities, in terms of quality, speed, dependability, flexibility, cost and patient engagement, on patient satisfaction with healthcare services. It considers patients’ rather than managers’ points of view to collect responses about competitive priorities.

This research employed a cross-sectional survey design to analyze a sample of customers through an empirical study of 488 patients in Qatar’s healthcare service context.

The confirmatory factor analysis results show that competitive priorities and engagement positively and significantly impact patient satisfaction.

Researchers can use this methodology to explore the role of competitive priorities in different service contexts and sectors. The researchers conducted the study in Qatar; therefore, the results are not generalizable to all healthcare sectors. However, regardless of geographic location, the research approach can be used in healthcare.

Managers can employ the developed scales to diagnose competitive priorities and improve customer service experiences.

The paper is original as it suggests using competitive priorities as a measurement tool for predicting patient satisfaction compared to prior research that mostly measured competitive priorities based on internal perspectives (managers’ perspectives). Further, this paper is original because it depends on the external perspective (customers’ perspective) for the competitive priorities for measuring patient satisfaction.

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors’ behavior.

Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.

This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors’ decision-making. Through thematic analysis, an attribute–consequence–impact framework is proposed that explains different biases leading to individual investors’ irrationality. The study further proposes directions for future research by applying the theory–characteristics–context–methodology framework.

The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.

The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor’s decision-making.

The purpose of this paper is to test if building reputation capital through environmental, social and governance (ESG) investing can mitigate the negative effect of economic policy uncertainty (EPU) on firms’ valuation.

This study uses an unbalanced panel of 591 financial firms between 2005 and 2021 from Canada, France, Germany, Italy, Japan, the United Kingdom (UK) and the USA. Ordinary least square method is used in the empirical tests. To alleviate a potential endogeneity problem, robustness tests are performed using the two-stage least square approach with instrumental variables.

The results of this paper show that sustainable reporting can offset the negative effect of EPU on the valuation of financial firms. Consistent with the stakeholder-based reputation-building hypothesis, sustainability performance may have an insurance-like impact on firms’ valuation during periods of high uncertainty.

According to the findings, during high policy uncertainty periods, investors accept to pay a premium for the stocks of the firms which built social capital through environmental and social investments. Accordingly, it is suggested that regulatory bodies and governments motivate firms to increase their stakeholder orientation to attain higher reputation capital.

Managers can mitigate the negative impact of policy uncertainty on the value of their firms via building social capital, which will increase financial market stability in return, and portfolio investors may use such firms for portfolio optimization decisions.

To the best of the authors’ knowledge, this paper is one of the first to examine the mitigating role of ESG investing on EPU and firm valuation relationships for financial firms. Thus, this study provides new insights related to the impact of ESG performance on valuation during uncertain times.

This study aims to determine the contributing factors to technical knowledge valuation at the related quadruple levels of commercialisation, including the idea, benchtop technical knowledge, prototype technical knowledge and commercialised technical knowledge, and then classify the factors by the valuation objectives.

The study method is descriptive-causal, and documentation tools of published scientific research articles in authentic local and international journals were used to extract the contributing factors to technical knowledge valuation. Moreover, the Likert spectrum-based questionnaire is used to determine the weight of each determined component. On the other hand, hierarchical analysis is used based on the extracted results from the distributed classification questionnaire among scholars to determine the allocable weight of each component.

The results indicate that at the idea step, the highest ranks among the contributing factors to technical knowledge valuation are for the indicators of innovation rate enhancement, novelty, creation of new products, profitability growth and dependence decline. In the benchtop technical knowledge step, the indicators of profitability growth, product quality enhancement, novelty, production risk drop, innovation rate enhancement, production costs drop, product price competitiveness and independence from rare machinery have the highest impact coefficients on valuation. Moreover, the prioritisation of factors in prototype technical knowledge shows that the indicators of productive risk decline, infrastructure, decrease in product delivery time, productivity growth and profitability growth are the most critical factors in technical knowledge valuation. Finally, profitability growth factors, production cost drop, productive risk drop, creating a new product, product price competitiveness and dependence decline determine the most valuable technical knowledge in the commercialisation phase.

The most salient innovation of the study involves the development levels of technical knowledge in the commercialisation cycle for determining the contributing factors to technical knowledge valuation and using multivariate decision-making methods to classify the so-called factors. The major limitation can be the context of the study because the paper was carried out by Iranian assessors and specialists using the experiences, opinions and approaches of opinion leaders based on the dominant social, cultural and accounting background of a developing country, not a developed one.

This paper is applicable because it elucidates the technical knowledge valuation factors for managers and owners of technological and knowledge-based companies to facilitate value determination and register the technical knowledge of innovative products in financial statements for the logical presentation of available intangible assets in the economic unit. Besides, in the high-tech area, collecting information from the contributing factors to technical knowledge valuation provides an opportunity to support intellectual property rights and facilitate transaction processes. Finally, in legal areas, in cases of breaching intellectual property rights relative to technical knowledge, the determination of technical knowledge value provides a solid basis for estimating the damage rate.

The primary objective of this research is to provide evidence that there are two distinct layers of investor sentiments that can affect asset valuation models. The first is general market-wide sentiments, while the second is biased approaches toward specific assets.

To achieve the goal, the authors conducted a multi-step analysis of stock returns and constructed complex sentiment indices that reflect the optimism or pessimism of stock market participants. The authors used panel regression with fixed effects and a sample of the US stock market to improve the explanatory power of the three-factor models.

The analysis showed that both market-level and stock-level sentiments have significant contributions, although they are not equal. The impact of stock-level sentiments is more profound than market-level sentiments, suggesting that neglecting the stock-level sentiment proxies in asset valuation models may lead to severe deficiencies.

In contrast to previous studies, the authors propose that investor sentiments should be measured using a multi-level factor approach rather than a single-factor approach. The authors identified two distinct levels of investor sentiment: general market-wide sentiments and individual stock-specific sentiments.

This study aims to investigate the impact of consumer ethnocentrism on consumers' evaluation of blockchain-based traceability information. It also examined how the use of quick response (QR) codes for traceability affects consumers' evaluation of traceable food products.

An online choice experiment was conducted to determine consumers' evaluation of the blockchain-based traceability of Feta cheese with a quota sample of 715 Greek consumers. Pearson bivariate correlation and mean comparison were used to examine the relationship between consumer ethnocentrism and QR use behaviour. Random parameter logit models were employed to examine consumers’ valuation of the examined attributes and interaction terms.

The results show that ethnocentric consumers are willing to pay more for blockchain-based traceability information. Ethnocentric consumers tend to scan QR codes with traceability information. Spending more time reading traceability information embedded in QR codes does not lead to a higher willingness-to-pay (WTP) for traceable food products.

The findings suggest that patriotic marketing messages can draw consumers' attention to blockchain-based traceability information. The modest WTP for and low familiarity with blockchain-based traceability systems raise the need for educating consumers regarding the benefits of blockchain in traceability systems.

This is the first study to provide timely empirical evidence of a positive WTP for blockchain-based traceability information for a processed dairy product. This study is the first to attempt to distinguish the effects of the intention to scan QR codes and reading information embedded in QR codes on consumers’ valuation of food attributes.

This paper aims to explore the relationship between market pricing and design quality within the development industry. Currently, there is a lack of research that examines real estate at the property level. Development quality is widely believed to have diminished over the past decades, while many investors seem uninterested in the design process. The study aims to address these issues through a pricing model that integrates design attributes. It is hoped that empirical findings will invite broader stakeholder interest in the design process.

The research establishes a framework for assessing spatial compliance across residential developments within London. Compliance is assessed across ten boroughs, with technical space guidelines used as a proxy for design quality. Transaction prices and spatial assessments are aligned within a hedonic pricing model. Empirical findings are used to establish whether undermining spatial standards presents a significant development risk.

Findings suggest a relationship between sale time and unit size, with “compliant” units typically transacting earlier than “non-compliant” units. Almost half of the 1,600 apartments surveyed appear to undermine technical guidelines.

It is suggested that an array of design attributes be explored that extend beyond unit size. Additionally, future studies may consider the long-term implications of design quality via secondary transaction prices.

Practical implications include the development of a more scientific approach to design valuation. This may enhance the position of product design management within the development industry and architectural services.

Social implications may include improvement in residential design.

An innovative approach combines a thorough understanding of both design and economic principles.