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This study proposes a novel measure for management’s horizon (short-termism or myopia vs long-termism or hyperopia) derived from easily obtainable firm-level accounting and stock market performance data. The authors use the measure to explore the impact of managements’ horizon on firms’ investment efficiency.

The authors rely on two commonly used but uncorrelated measures of management performance: accounting performance (return on capital employed, ROCE) and stock market performance (average abnormal return, AAR). The authors combine these measures to develop a multidimensional framework for performance, which classifies firms into four groups: efficient (high accounting and high market performance), poor (low accounting and low market performance), myopic (high accounting and low market performance) and hyperopic (low accounting and high market performance). The authors validate this framework and deploy it to explore the relationship between horizon and firms’ investment efficiency.

In validation tests, the authors show that management myopia (hyperopia) explains firms’ decision to cut (grow) research and development investments. Further, as expected, myopic (hyperopic) firms are associated with significantly more (less) accrual and real earnings management. The empirical tests on the link between horizon and investment efficiency suggest that myopic managers cut new investments while their hyperopic counterparts grow the same. Ultimately, the authors find that myopia (hyperopia) exacerbates(mitigates) the over-investment of free cash flow problem.

The authors introduce a framework for assessing management’s horizon using easily obtainable measures of performance. The framework explains inconsistencies in prior empirical research using different measures of performance (accounting versus market). The authors demonstrate its utility by showing that the measure explains decisions around research and development investment, earnings management and firm investments.

The paper examines whether, along with the financial performance, the disclosure of research and development (R&D) expenses, patent portfolios, patent citations and innovation activities affect the market capitalization of Russian companies.

The paper opted for a set of techniques including bag-of-words (BoW) to retrieve additional innovation-related data from companies' annual reports, self-organizing maps (SOM) to perform visual exploratory analysis and panel data regression (PDR) to conduct confirmatory analysis using data on 74 Russian publicly traded companies for the period 2013–2019.

The paper observes that the disclosure of nonfinancial data on R&D, patents and primarily product and marketing innovations positively affects the market capitalization of the largest Russian companies, which are mainly focused on energy, raw materials and utilities and are operating on international markets. The study suggests that these companies are financially well-resourced to innovate at risk and thus to provide positive signals to stakeholders and external agents.

Our findings are important to management, investors, financial analysts, regulators and various agencies providing guidance on corporate governance and sustainability reporting. However, the authors acknowledge that the research results may lack generalizability due to the sample covering a single national context. Researchers are encouraged to test the proposed approach further on other countries' data by using the compiled lexicons.

The study aims to expand the domains of signaling theory and market valuation by providing new insights into the impact that companies' reporting on R&D, patents and innovation activities has on market capitalization. New nonfinancial factors that previous research does not investigate – innovation disclosure indicators (IDI) – are tested.

This study aims to exploit Tobin’s Q model of investment to examine the relationship between corporate governance and green innovation.

The study is based on a sample of 3,896 firms from 2002 to 2021, covering 45 countries worldwide. The authors adopt Tobin’s Q model to conceptualize the relationship between corporate governance and investment in green research and development (R&D). The authors argue that agency costs and financial market frictions affect corporate investment and are fundamental factors in R&D activities. By limiting agency conflicts, effective governance favors efficiency, facilitates access to external financing and encourages green innovation. The authors analyzed the causal effect by using the system-generalized method of moments (system-GMM).

The results reveal that the better the corporate governance, the more the firm invests in green R&D. A 1%-point increase in the corporate governance ratings leads to an increase in green R&D expenses to the total asset ratio of about 0.77 percentage points. In addition, an increase in the score of each dimension (strategy, management and shareholder) of corporate governance results in an increase in the probability of green product innovation. Finally, green innovation is positively related to firm environmental performance, including emission reduction and resource use efficiency.

The findings provide implications to support managers and policymakers on how to improve sustainability through corporate governance. Governance mechanisms will help resolve agency problems and, in turn, encourage green innovation.

Understanding the impact of corporate governance on green innovation may help firms combat climate change, a crucial societal concern. The present study helps achieve one of the precious UN’s sustainable development goals: Goal 13 on climate action.

This study goes beyond previous research by adopting Tobin’s Q model to examine the relationship between corporate governance and green R&D investment. Overall, the results suggest that effective corporate governance is necessary for environmental efficiency.

The authors examine the spillover effects of CEO removal on the corporate financial policies of competing firms among S&P 1500 firms.

The authors used generalized estimating equations (GEE) on a sample of S&P 1,500 firms from 2000 to 2018 to test this study's research hypotheses. Return on assets (ROA), investment policy, and payout policy are used as proxies for corporate policies.

The authors found an increase in ROA and dividend payout in the immediate aftermath. Further, this study's hypothesis does not hold for R&D expenditure and net-working capital as the authors found an insignificant change in them in the immediate aftermath. However, the authors found a significant reduction in capital expenditure, supporting this study's hypothesis in the context of investment policy. Institutional investors and product similarity moderated the spillover effect on corporate policies (ROA, dividend payout, and capital expenditure).

The authors address a novel aspect of CEO performance-induced removal due to poor performance, i.e., the response of other CEOs to CEO performance-induced removal. This study's findings add to the literature supporting the bright side of CEOs' response to CEO performance-induced removal in peer firms due to poor performance.

This study aims to investigate the association of FinTech innovation (FinTechINN) and firm performance (FP) by considering the role of knowledge assets (KA) as a causal mechanism underlying the FinTechINN – FP association.

In this study, the authors consider panel data of 1,049 Chinese A-listed firm and construct a structural model for corporate FinTech innovation, knowledge assets and firm performance while considering endogeneity issues in analyses over the period of 2014–2022. The modified value added intellectual capital (VAIC) and research and development (R&D) expenses are used as a proxy measure for knowledge assets, considering governance and corporate performance measures.

According to the findings of this study FinTech innovation (FinTechINN) has a positive significant effect on firm performance. Particularly; the findings disclose that FinTech innovations has a link with knowledge assets, FinTech innovations indirectly affects firm performance, and the association between FinTech innovation and firm performance is partially mediated by knowledge assets (MVAIC and R&D expenses).

Rooted in the dynamic capability and resource-based view, this study pioneers an empirical exploration of the association of FinTech innovation with firm performance. Moreover, it introduces the novel dimension of knowledge assets (on firm-level), acting as a mediating factor with in this relationship.

This paper aims to explore the effects of two drivers, namely, the received fundings and its interaction with the specialized competences owned by the managerial board, on the R&D activities performed by start-ups.

This paper tests hypotheses on a sample of 405 innovative start-ups established in Italy and registered into the Chamber of Commerce official database. This study uses the R&D expenses as a measure of the innovative performance of start-up, and the authors also collected the number and total amount of grants received by them and the presence of high qualified team in their management board.

The analysis reveals that both the number and total amount of grants received by start-ups positively impact the innovative performance. The same is for the integration of the total amount of grants with the presence of high qualified team in the management board.

This study did not distinguish between different types of grants adopted by start-ups, while it would be interesting to study whether any difference does exist among them in terms of their influence on innovative performance. Also, this paper considers the total number of specialized people in the team while it would certainly be interesting to analyze people’s background and competences in relation to the innovative performances.

This paper allows us to offer some provisional conclusions such as having funds in the preliminary phase of start-up life cycle, and investments mainly for R&D expenses. The start-up must also leverage its skills and therefore it is necessary to invest in human capital.

Findings suggest that policymakers should introduce integrated measures to support start-ups throughout the entire life cycle, from the creation of the idea to incubation up to industrial consolidation.

This paper focuses on the determinants of start-up innovative performance because both external (such as political, economic, social and technological) and internal (such as organizational) influencing factors have to be considered as crucial for start-ups innovation and growth. Finally, this study is one of the few attempts exploring the phenomenon by using an empirical methodology based on real and certificated data.

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.

The study aims at examining the relationship between the forms of misclassification practices, namely expense shifting and revenue shifting. In particular, the study aims at identifying the form of shifting that has been preferred by firms to meet the industry average profitability.

Core earnings and operating revenue expectation models are used to measure expense shifting and revenue shifting, respectively. The panel fixed-effects models are used to control for unobserved heterogeneity across industries and time.

Based on a sample of Bombay Stock Exchange-listed firms, the author finds that firms prefer expense shifting over revenue shifting to meet industry average profitability, implying that firms choose the shifting tool based on the relative advantage. Further, the findings deduced from the empirical results demonstrate that firm life cycle and mandatory adoption of International Financial Reporting Standards (IFRS) moderates the relationship between shifting forms and industry average profitability. However, the negative impact of IFRS on shifting practices is found to be less pronounced among BigN audit firms.

The study is among the pioneering attempt to document the substitution relationship between shifting forms. It is the first study that examines a form of classification shifting, where gross profit and core earnings both change as an effect of misclassification.

This research investigates the impact of strategic research and development (R&D) (one led by a firm’s innovation orientation) on stock market performance during the economic disruption caused by the 2016 demonetization of high-value currency notes in India. It shows how firms’ strategic focus on innovation and integrated R&D initiatives can help mitigate shareholders’ losses and protect market value during negative macroeconomic shocks.

We analyzed financial and administrative data from firms listed in the Bombay Stock Exchange (BSE) 500 index and used the Fama French market model with appropriate instruments accounting for possible endogeneity to identify the impact. To ensure the reliability of our findings, we conducted robustness checks with alternate event windows, estimation methods, and variable measurements.

Strategic R&D plays a crucial role in building resilience against macroeconomic shocks. It effectively mitigated shareholders’ losses in the immediate aftermath of the shock, with an elasticity of abnormal returns of 7.65% on day zero, 13.1% during the first five days and 10.5% after the first fortnight. We also find that firms that are business-to-business (B2B), as well as those that are older and less leveraged, are better able to combat such a shock.

The study looked at one shock, namely demonetization. Future research is needed to demonstrate the generalizability of results during other macroeconomic shocks, like the COVID-19 pandemic. The study focuses on relatively near-term impacts, leaving the long-term value-creation effects of strategic R&D unexplored.

Innovation orientation acts as a structural enabler, allowing firms to make strategic R&D investments that mitigate losses during macroeconomic shocks. It explains that managers should avoid myopically managing R&D investments and align them with the firm’s innovation focus to enhance value creation.

While the currency demonetization was widely considered to be detrimental for firms as an unannounced negative monetary shock, our research shows that firms with high levels of strategic R&D were successfully able to counteract such a shock.

This is the first study to examine the short-term loss mitigation impact of firms’ focus on innovation and strategic R&D. It emphasizes the role of innovation-focused strategies during economic crises.

The objective of this work is to demonstrate the relationships between the two main processes of research and development (R&D) activities: the knowledge generation phase (KPP) and the knowledge commercialization, or transfer, phase (KCP), in a sector that is intensive in this type of activity, such as the pharmaceutical sector. In addition, within the framework of the general objective of this work, the authors propose two other objectives: (1) make advances in network efficiency measurement models, and (2) determine the factors associated with efficiency in the KPP and in the KCP in companies of the pharmaceutical sector in Spain.

A Network Data Envelopment Analysis (NDEA) model (Färe and Grosskopf, 2000) with categorical variables (Lee et al., 2020; Yeh and Chang, 2020) has been applied, and a sensitivity analysis of the obtained results has been performed through a DEA model of categorical variables, in accordance with the work of Banker and Morey (1986), to corroborate the results of the proposed model. The sample is made up of 77 companies in the pharmaceutical sector in Spain.

The results obtained point to a greater efficiency of pharmaceutical companies in the KPP, rather than in the KCP. Furthermore, the study finds that 1) alliances between companies have been the accelerating factors of efficiency in the KCP (but patents have slowed this down the most); 2) the quality of R&D and the number of R&D personnel are the factors that most affect efficiency in the KPP; and 3) the quality of R&D again, the benefits obtained and the position in the market are the factors that most affect efficiency in the KCP.

The authors have not found studies that show whether the efficiency obtained by R&D-intensive companies in the KPP phase is related to better results in terms of efficiency in the KCP phase. No papers have been found that analyse the role of alliances between R&D-intensive companies and patents, as agents that facilitate efficiency in the KCP phase, covering the gap in the research on both problems. Notwithstanding, this work opens up a research path which is related to the improvement of network efficiency models (since it includes categorical variables) and the assessment of the opinions of those who are responsible for R&D departments; it can be applied to decision-making on the aspects to improve efficiency in R&D-intensive companies.