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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 examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

Good management strives to align and corporate processes for more attention being paid to supply chain management. Firms realize that greater co-operation and improved coordination can help to manage the entire supply chain more efficiently. The imperfect quality item is one of the most important issues that affect the expected profit of green supply chain. The imprecise cost with screening process of poor quality items posed in supply chain is the subject of this study.

The present study explores production model for imperfect items having uncertain cost parameters with three-layer supply chain encompassing supplier, manufacturer and retailer. The model is considering the impact of business tactics such as order size, production rate, production cost and appropriate times in various sectors on collaborative marketing systems. Due to imprecise cost parameters, the pentagonal fuzzy numbers are set to fuzzify the total cost and defuzzifition by using graded mean integration.

This study offers an explicit condition in uncertain environment to manage the imperfect quality item to increase the potential profit of the supply chain. The influence of changes in parameter values on the optimal inventory policy under fuzziness is provided managerial insights.

This model makes a significant contribution to fuzzy inference. The results of the study provide a trading strategy for the industry to avoid losses. The prescribed study can be suitable for the industries like sculpture, jewelry, pottery, etc.

Channel coordination has become an essential part of researching hotel supply chain management practices. This paper develops an improved channel coordination approach to coordinate the profit distribution between hotels and online travel agencies (OTAs) achieved through an introduction of advertising fees. This direction further improves the decentralization of cooperation and achieves Pareto improvement to achieve mutual profitability.

The methodology used in this study involves Stackelberg game theory employed for the decision-making and analysis of both the hotel and OTA. The OTA, acting as the leader, offers a hotel a contract specifying the commission rate that the hotel will pay to the respective OTA. The hotel, acting as a follower, sets a self-interested room rate as a given response. A deterministic, price-sensitive linear demand function is utilized to derive possible analytical solutions once centralized, noncooperative decentralization and cooperative decentralized channel occurs.

Results show that a new channel coordination approach is possible, namely via advertising fees. Prior to channel coordination, the OTA tends to set a higher commission rate, and the hotel sets a higher room rate in response under noncooperative decentralization. As such, this results in a lower channel-wide profit for all. One way to reduce channel-wide profit loss is to use a method of cooperative decentralization, which can, and will result in optimal profit as centralization takes place. However, the lack of incentives makes cooperative decentralization unfeasible. Further improvement is possible by using advertising fees based on a cooperative decentralization agreement, which can reach Pareto improvement.

This paper helps the OTA industry and hotel owners cooperate by way of smoother coordination. This study provides practitioners with two important practical implications. The first one is that the coordination between the hotel industry and OTA through cooperative decentralization allows for the achievement of higher profitability than that of noncooperative decentralization. The second one is that this paper solves the outstanding problem of insufficient incentives characteristic of cooperative decentralization by means of an advertising fee as a new supply chain coordination approach.

This paper offers both the problem and solution regarding the lack of incentives that hamper cooperative decentralization without the use of advertising fees. This paper is unique in that it derives analytical solutions regarding commissions levied in a typical hotel supply chain under noncooperative decentralization.

Emerging economies have been highlighted as an important growth source of the global economy. However, this group of countries has not received enough academic attention yet. Therefore, this study aims to identify the impact of research and development (R&D) expenditure on economic growth in emerging economies.

The theoretical framework of the production function is applied to quantitatively analyse the impact of R&D expenditure on economic growth with a sample of 29 emerging economies in the period between 1996 and 2019.

The panel cointegration test confirms the existence of long-run cointegration relationships between economic growth and independent variables in these emerging economies. Besides, the estimated results show that the national R&D expenditure has positive effects on economic growth from both direct and interaction dimensions. This evidence has filled the empirical research gap in the R&D-growth nexus in the case of emerging economies. Finally, while gross capital and education have positive impacts on growth, corruption has a harmful effect on economic growth in these countries.

The results highlight that policymakers should enhance R&D expenditure and R&D activities as the key national development strategy. The investment in R&D not only helps emerging economies avoid the middle-income trap but also pushes these countries to successfully join the group of developed countries.

To the best of the authors’ knowledge, this research is among the first to examine the impact of R&D expenditure on economic growth with a homogeneous sample of emerging economies. The results are obviously helpful for policymakers to use R&D as the key development strategy for supporting economic growth in emerging economies in the future.

This paper examines the sluggish adjustment of deposit interest rate categories with response to policy rate changes in a developing economy.

Symmetric and asymmetric error correction models (ECMs) are employed to test the pass-through effect and adjustment speed of deposit rates when above or below their equilibrium levels.

The findings reveal an incomplete pass-through effect in both the short run and long run while mixed results of symmetric and asymmetric adjustment speed across the different deposit rate categories are observed. Collusive pricing arrangement behavior is supported by deposit rate categories that adjust more rigidly upwards than downwards, while negative customer reaction behavior is supported by deposit rate categories that adjust more rigidly downwards than upwards.

Even though the findings indicate an aspect of increased responsiveness over the period, the sluggish adjustment of deposit rates imply that monetary policy is still ineffective and not uniform across the different deposit rate categories.

To the best of the authors' knowledge, this is the first study to empirically examine both symmetric and asymmetric adjustment behavior of deposit interest rate categories in Kenya. The findings are key to policy makers as they provide insights on how long it takes to adjust different deposit rate categories to monetary policy decisions. In addition, the behavior of deposit rates partly explains why interest rates capping was imposed in Kenya in 2016.

The European Union’s Digital Markets Act (DMA) calls for far-reaching changes to the way economic activity will occur in EU digital markets. Before its remedies are imposed, it is critical to assess their impacts on individual markets, the digital sector, and the overall European economy. The European Commission (EC) released an Impact Assessment in support of the DMA that purports to evaluate it using cost/benefit analysis.

An economic evaluation of the DMA should consider its full impacts on dynamic competition. The Impact Assessment neither assesses the DMA's impact on dynamic competition in the digital economy nor evaluates the impacts of specific DMA prohibitions and obligations. Instead, it considers benefits in general and largely ignores costs. We study its benefit assessments and find they are based on highly inappropriate methodologies and assumptions. A cost/benefit study using inappropriate methodologies and largely ignoring costs cannot provide a sound policy assessment.

Instead of promoting dynamic competition between platforms, the DMA will likely reinforce existing market structures, ossify market boundaries, and stunt European innovation. The DMA is likely to chill R&D by encouraging free riding on the investments of others, which discourages making those investments. Avoiding harm to innovation is critical because innovation delivers large, positive spillover benefits, driving increases in productivity, employment, wages, and prosperity.

The DMA prioritizes static over dynamic competition, with the potential to harm the European economy. Given this, the Impact Assessment does not demonstrate that the DMA will be beneficial overall, and its implementation must be carefully tailored to alleviate or lessen its potential to harm Europe’s economic performance.

This study contributes to the literature on eco-innovation (EI) and the circular economy (CE) by providing insights into the factors of external knowledge absorption that facilitate the adoption of a subset of EIss called proactive-EIs. Proactive-EIs involve collaborations among multiple stakeholders, the use of technical knowledge and a greater level of investment than other innovations. In this study, the environmental actions taken by small and medium-sized enterprises (SMEs) in resource-intensive sectors in the European Union (EU) were observed, and elements related to the national context were compared.

The national innovation system (NIS) perspective was adopted using a multilevel framework to assess the determinants of proactive-EIs among SMEs in the EU. The framework involves three levels: micro- (environmental awareness), meso- (external collaboration and intra-industry agglomeration) and macro- (economic complexity, trade openness and government research and development [R&D]). The survey data of 6,188 SMEs in resource-intensive sectors were analysed using a binary logistic regression.

The results showed that public awareness, economic complexity and public sector R&D positively influenced SMEs' adoption of proactive-EIs, whereas external collaboration and sectoral agglomeration negatively influenced adoption.

Among the existing empirical studies on EI, areas related to external knowledge-based innovations and systematic assessments of heterogeneity among EU member states remain underexplored. This study contributed to the literature by assessing the conditions surrounding external knowledge absorption. The findings contribute to the green entrepreneurship literature in the context of developed economies and offer insights for managers and policymakers seeking to promote EIs.

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.

This chapter deals with the issue of the role of imitation and innovation in explaining economic growth in the context of the Polish economy, taking the endogenous growth theory and the technology catch-up theory as guidelines. This issue is extremely important as Poland faces the urgent need to reduce productivity gap through investments in R&D and/or the absorption of foreign technologies.

The aim of this chapter is to find the effects of innovation and imitation on economic performance of Poland and shed light on possible outcome differences between these two kinds of activities.

The empirical analysis uses data on innovation, imitation and Gross Domestic Product (GDP) of the Polish economy between 2005 and 2021, collected from a few statistical sources. We apply the autoregressive distributed lag (ARDL) model to find the impact of innovation and imitation on economic growth.

The results suggest that R&D investments positively affect economic performance of the Polish economy, whereas the impact of imitation activities on GDP appears to be insignificant.