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The paper examines contingent liabilities' effect on the firm's dividend decisions.

Fixed-effects regression and logit model results estimate the influence of contingent liabilities on firms' dividend decisions using a sample of 2,288 firm-year observations of S&P 500 firms from 2012 until 2022. Robustness checks and results from the 2SLS model further support the authors’ findings.

The results show that contingent liabilities negatively affect dividend payment decisions. This analysis further demonstrates that the stated effect of contingent liabilities on dividend decisions is more substantial for firms with financing deficits and those with above-industry-average corporate governance scores.

There needs to be more systematic conceptual reason for measuring uncertainty for firms and its influence on dividend decisions. Future research should use other measures of firm uncertainty to examine the relation of the firm's uncertainty with dividend decisions.

The authors suggest that contingent liabilities create uncertainty for future cash flows, influence a firm's agency costs and provide credible signals on a firm's prospects to the market. The findings support existing literature that measurable firm-specific variables significantly influence a firm's dividend decisions. The results are robust for an alternative explanation.

By investigating the impact of the influence of contingent liabilities on dividends, the authors extend research on dividend decisions and attempt to provide insights into a firm's dividend decisions by incorporating an off-the-balance sheet item (contingent liabilities) as a significant predictor for dividend decisions.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.

Option pricing theory enables computation of the price of an option using different variables associated with the underlying security and options contract. The purpose of this study is to assess research trends that emerged in the field of option pricing. This study reviews existing literature of the option pricing domain, both qualitatively and quantitatively, and identifies potential themes for future research.

This study adopts bibliometric analysis method to explore literature published in the option pricing domain. As part of bibliometric analysis, this study considers both descriptive and network analysis to assess publication trends. For descriptive analysis, the “bibliometrix” package proposed by Aria and Cuccurullo (2017) is used and for network analysis, VOS viewer (Van Eck and Waltman, 2017) and Gephi (Bastian et al., 2009) are used.

This study identifies research trends, top researchers, articles, journals and contributions from institutions and countries in the option pricing domain. It identifies four clusters that show different directions and also focuses on past studies on the same subject. It explores research gaps by performing an in-depth analysis of existing literature on option pricing and suggests the way forward for research in this area.

To the best of the authors’ knowledge, no previous studies have attempted to analyze the literature published in the option pricing domain. This study fulfils this research gap by conducting a comprehensive analysis of studies in the option pricing area. This study identifies quality research work published in the domain, research trends, contribution by most relevant researchers, contributions across geographies and institutions and the connections among these aspects. This study also identifies important themes and provides directions for future research.

This study aims to examine the nexus of corporate governance with firms' financial risk-taking behavior under the corporate social responsibility (CSR) disclosures in the context of non-financial listed firms of an emerging economy.

This study investigates the relationship between corporate governance as evaluated by an index and several financial risks, including idiosyncratic, default and systematic risks. The connection of corporate governance with financial risks is also studied while considering the moderation of CSR disclosures. The data are collected from 2014 to 2018 of 73 top 100-index listed non-financial firms of Pakistan Stock Exchange (PSX). Panel regression fixed effect and 2-step generalized method of moments techniques are applied to confirm the hypothesis along with the diagnostic tests to confirm that all outcomes of models must be authentic and reliable.

The study’s findings confirm that enhancing the overall corporate governance measures resulted in an augment in the firm’s risk due to weak control and regulations prevailing in emerging economies. Moreover, CSR disclosures enhance stakeholder information, lessen information asymmetry about management policies and mitigate the risk associated with operational uncertainties.

This study has a practical implementation to policymakers that effective monitoring and controlling measures facilitate the corporate management for minimizing the financial risks. Further, the study’s findings shed light that implementing corporate governance measures is not enough to mitigate financial risks until supervisory measures in the form of CSR disclosures are not taken to analyse corporate governance effectiveness.

This paper enhances the key findings in the literature by examining the role of corporate governance measures with respect to firms’ financial risks considering the moderating role of CSR disclosures. Furthermore, this research adds to the body of knowledge regarding the implementation of monitoring measures that assist in the mitigation of firms’ financial risks hence firm value.

This study aims to investigate disclosure of asbestos-related liabilities in corporate accounts and counter-accounts to examine whether and how accounting contributes to corporate accountability for asbestos-contaminated products.

This study uses the Goffmanesque perspective on impression management to examine instances of concealed asbestos-related liabilities in corporate accounts vis-à-vis the revealing of such liabilities in counter-accounts.

The findings show counter-accounts provide significant information on liabilities originating from the exposure of employees and consumers to asbestos. By contrast, the malleability of accounting tools enables companies to eschew accounting disclosures. While the frontstage positive performance of companies served an impression management role, their backstage concealing actions enabled companies to cover up asbestos-related liabilities. These companies used three categories of mechanisms to avoid disclosure of asbestos-related liabilities: concealing via a “cloak of competence”, impression management via epistemic work and a silent strategy of concealment frontstage with strategic reorganisation backstage.

This study has policy relevance as regulators need to consider the limits of corporate disclosures as an accountability tool. The findings may also initiate academic and practitioner conversations about accounting standards for long-term liabilities.

This study highlights the strategies companies use both frontstage and backstage to avoid disclosing asbestos-related liabilities. Through analysis of accounts and counter-accounts, this study identifies the limits of accounting as an accountability tool regarding asbestos-induced diseases and deaths.

This study aims to explore the potential dynamics between performance measurement at the organisational level and emerging urban development projects at the macro-institutional field level of sustainability governance and accountability.

Using a theoretical triangulation between three theories, namely contingency theory, institutional theory and social cognitive theory, this study investigates not only the macro-micro dynamics, but also the (recursive) micro-macro dynamics between performance measurement and urban development. Using an Egyptian public sector urban development organisation and its sustainable energy project as an empirical example, interviews, documents and observations were collected.

The dynamics emerged between field urban development projects and the (unintended) organisational implementation of the performance measurement system, the sustainability key performance indicators (KPIs) reporting system. Contributing to previous literature, these dynamics have been institutionalised through (three) interrelated levels: the (macro-field) urban development contingencies and pressures for sustainability KPIs reporting, the (organisational) institutionalisation of the urban development performance measurement system and then the (micro-organisational) cognitive role of sustainability KPIs reports in (re)making political urban development decisions.

This study faced some limitations that paved the way for future research axes. For political and security reasons, difficulties were encountered in conducting interviews with government actors in the sustainable energy project under study. Also, due to the practical separation of the environmental sustainability system from the sustainability KPIs reporting system in this case study, environmental sustainability is outside the scope.

Sustainability reports may influence public sector decision-making processes in a specific urban development context. These KPIs reports may also increase public sector management opportunities for urban auditing, transparency, accountability and sustainability governance. These KPIs may also guide public sector management to lower prices in poor villages to increase smart energy consumption and improve community health.

Sustainability reports may increase decision-makers' understanding of consumer behaviours and societal changes. This may help in making appropriate political decisions to improve their welfare and regular smart energy consumption. Not only urban citizens, but this social advantage may also extend to urban development employees through employees' promotion, training and access to government-funded academic and professional scholarships.

This study is an attempt to develop current public sector performance measurement analyses in the emerging urban development field using a triadic analytical approach. This study also fed the literature with an extended case study that clarified the (multi-level) and (two-way) dynamics between performance measurement and urban development.

This paper provides a structural model to value startup companies and determine the optimal level of research and development (R&D) spending by these companies.

This paper describes a new variant of float-the-money options, which can act as a financial instrument for financing R&D expenses for a specific time horizon or development stage, allowing the investor to share in the startup's value appreciation over that duration. Another innovation of this paper is that it develops a structural model for evaluating optimal level of R&D spending over a given time horizon. The paper deploys the Gompertz-Cox model for the R&D project outcomes, which facilitates investigation of how increased level of R&D input can enhance the company's value growth.

The author first introduces a time-varying drift term into standard Black-Scholes model to account for the varying growth rates of the startup at different stages, and the author interprets venture capital's investment in the startup as a “float-the-money” option. The author then incorporates the probabilities of startup failures at multiple stages into their financial valuation. The author gets a closed-form pricing formula for the contingent option of value appreciation. Finally, the author utilizes Cox proportional hazards model to analyze the optimal level of R&D input that maximizes the return on investment.

The integrated contingent claims model links the change in the financial valuation of startups with the incremental R&D spending. The Gompertz-Cox contingency model for R&D success rate is used to quantify the optimal level of R&D input. This model assumption may be simplistic, but nevertheless illustrative.

Once supplemented with actual transaction data, the model can serve as a reference benchmark valuation of new project deals and previously invested projects seeking exit.

The integrated structural model can potentially have much wider applications beyond valuation of startup companies. For instance, in valuing a company's risk management, the level of R&D spending in the model can be replaced by the company's budget for risk management. As another promising application, in evaluating a country's economic growth rate in the face of rising climate risks, the level of R&D spending in this paper can be replaced by a country's investment in addressing climate risks.

This paper is the first to develop an integrated valuation model for startups by combining the real-world R&D project contingencies with risk-neutral valuation of the potential payoffs.

This study is a radical interactionist analysis of family conflict. Drawing on both a negotiated order perspective and Athen's theory of complex dominative encounters, this study analyzes the role that domination plays in conflicts among intimates. As the family engages in repeated conflicts over roles, the family also engages in negotiations over the family order, what role each party should play, interpretations of past events, and plans for the future. These conflicts take place against a backdrop of patriarchy that asymmetrically distributes power in the family to determine the family order. The data from this study come from a content analysis of mothers with substance use problems as depicted in the reality television show Intervention. The conflicts in these families reveal that these families develop a grinding family order in which families engaged in repeated conflict but also continued to operate as and identify as a family. These conflicts are shaped by and reinforce patriarchal expectations that mothers are central to family operation. The intervention at the end of each episode offered an opportunity for the family to engage in a concerted campaign to try to force the mother into treatment and reestablish the family order.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?