Search results

The relevance of finance for strategy is probably never greater than during a recession. We argue that the strategy literature has been virtually silent on the issue of recessions, and that this constitutes a regrettable sin of omission. Recessions are also periods when the commonly held view of financial markets in the strategy literature – efficient, and therefore strategically irrelevant – is particularly misplaced. A key route to rectify this omission is to focus on how recessions affect investment behavior, and thereby firms’ stocks of assets and capabilities which ultimately will affect competitive outcomes. In the present chapter, we aim to contribute by analyzing how two key aspects of recessions, demand reductions and reductions in credit availability, affect three different types of investments: physical capital, R&D and innovation, and human- and organizational capital. We synthesize and conceptualize insights from finance- and macroeconomics about how recessions affect different types of investments and find that recessions not only affect the level of investment, but also the composition of investments. Some of these effects are quite counterintuitive. For example, investments in R&D are both more and less sensitive to credit constraints than physical capital is, depending on available internal finance. Investments in human capital grow as demand falls, and both R&D and human capital investments show important nonlinearities with respect to changes in demand.

This study aims to explain the effect of research and development (R&D) incentives on economic growth, focusing on the case of Türkiye. A one-sector endogenous growth model has been constructed. The model includes three actors: firm, consumer and government. The consumer derives utility from consumption, supplies human capital and engages in saving. The representative firm invests in R&D to maximize the current value of profit flows by choosing how much input it will use and how much R&D it will undertake. The public sector provides incentives for labor and capital used in R&D production. R&D has been defined as a function that endogenously increases total factor productivity (TFP).

In line with the stated purpose, this study presents a dynamic general equilibrium model. Then, this study calibrates the model parameters with Türkiye's data.

The results imply that incentives for R&D personnel instead of physical capital have a stronger impact on economic growth.

The findings of this study point to an important conclusion on how to distribute R&D incentives across the two main factors in R&D production, labor and capital. Incentives given to R&D personnel are more effective in Türkiye.

This study shows that the R&D incentives provided by the public sector can be important in emerging countries where many firms have just started their R&D activities. In this study, the authors worked on Türkiye as an emerging country. This study discusses policies on how the R&D incentives will be more effective on economic growth in Türkiye. This study considers that these policies may apply to all emerging countries, due to similar R&D activities in countries that cannot export technology and mostly import technology.

本研究擬以土耳其的實例為焦點, 探討研究與開發 (研發) 的激勵如何影響經濟的增長;具體地說, 研究旨在探討透過不同生產要素所提供的研發激勵所產生的影響存在著什麼差異。

為達研究目的, 研究人員構建了一部門內生增長模型。模型內有三個參與者: 公司、消費者和政府。消費者從消費中得到他們所需要的, 提供人力資本, 並參與儲蓄的活動。為了要把利潤的現值儘量提高, 代表公司透過調控投入的數量和研發的承擔, 投資在研發上。公共部門會為研發生產上使用的勞工和資本提供激勵。研究與開發被解釋為一個以內生方式增加全要素生產率的功能。構建的模型是因應土耳其的經濟狀況而調整出來的, 當中也進行了仿真模擬。

研究結果暗示, 為研發人員提供的激勵, 而不是物質資本, 更能推動經濟增長。

研究結果, 就如何於研發生產的兩個主要因素之間, 即勞工與資本之間, 分配研發激勵的問題上, 提供了重要的結論;就土耳其而言, 分配給研發人員的激勵是更為有效的。

我們展示了在新興國家裏, 公共部門提供的研發激勵是重要的, 而在這些國家裏, 剛開始進行研發活動的公司為數不少。在本研究裏, 我們把土耳其當作新興國家看待。我們討論了若要在土耳其使研發激勵更有效地幫助推動經濟增長, 什麼政策是最合適的呢? 因為那些不能把技術出口到其它地方, 而主要靠引進技術的國家均進行相似的研發活動, 所以我們認為討論得來的政策是可應用於所有新興國家的。

This paper aims to examine the contribution of physical capital, skilled labor, research and development (R&D), and imports to the productivity of ten Canadian food and beverage manufacturing sectors.

A Cobb‐Douglas production function is estimated to discern the relative contribution of physical versus R&D knowledge capital in fostering productivity growth. The paper uses a balanced panel dataset and is based on pooled cross‐sectional time series data for ten food and beverage manufacturing industries over the period 1994‐2005. The methodological framework adopted in this paper is a cross‐sectionally correlated and time‐wise autoregressive model. Data employed in this paper are from Statistics Canada's annual survey of manufacturing industries and Canadian Socio‐economic Information Management computerized database.

The results show that food manufacturing productivity for ten food and beverage sectors is more responsive to physical capital than R&D knowledge capital. Some of the other determinants of labor productivity in food manufacturing included the contribution from university‐educated workers.

The paper is useful to both policy makers and academics in the research fields of R&D and productivity. It provides some interesting insights into the contribution of physical and knowledge capital to food manufacturing industry productivity.

The purpose of this study is to examine whether and how internal capital markets mitigate financial constraints and enhance firms' willingness to engage in R&D projects.

The study uses panel data relating to 2,095 publicly traded firms in the Chinese A-share market for the period 2007–2019. The tobit regression method is applied to explore R&D investment–cash flow sensitivity of group affiliates, while the systematic generalised method of moments and dynamic ordinary least squares models are adopted to address the endogeneity problem in the robustness test.

This study finds that firms affiliated with business groups demonstrate lower R&D investment–cash flow sensitivity than non-affiliated firms do and that R&D investments are significantly influenced by the cash reserves of other group members. In terms of financing channels, this study demonstrates that group firms use internal cash and equity financing to support other members' R&D investments, while debt financing does not influence member firms' R&D investments. In addition, this study discovers that R&D spending harms the stock and operating performance of some group members.

The findings of this study enable business groups to focus on resource allocation and investment efficiency.

Although prior studies indicate that internal capital markets can enhance R&D spending, few studies reveal the mechanisms through which internal capital markets benefit R&D. This study uses a unique methodology to test the ability of the internal capital market to enhance R&D spending. In addition, group firms use internal cash flow and equity financing to support partners' R&D projects.

The purpose of this paper is to examine the relationship of CEO compensation plans and the risk of managerial equity portfolios with the extent of strategic investments in advertising, capital expenditures and research and development (R&D). The elements of compensation are salary, bonuses, options and restricted stock grants. The authors proxy the design of CEO equity portfolios by the price performance sensitivity of the holdings and the portfolio deltas.

The authors use the components of executive compensation and portfolio risk as the dependent variables, regressing these against measures for the level of strategic investment. The authors test for non-linear relationships between the components of CEO compensation and strategic investments. The sample is a broad cross-section from 1992 to 2016.

The authors find strong support for non-linear relationships of capital expenditures and R&D with CEO bonuses, option grants and restricted stock grants. There are very complex relationships between the components of executive compensation and R&D expenditures, but little evidence of a relationship with advertising expenditures. The authors also find strong complex relationships in the design of CEO equity portfolios with advertising and R&D.

Little earlier research has considered advertising, capital expenditures and R&D in a unified framework. Also, testing for non-linear associations provides much greater insight into the relationship between the components of executive compensation and strategic investment. The findings represent a valuable incremental contribution to the executive compensation literature. The results also have normative policy implications for compensation committees’ design of optimal annual CEO compensation packages to incentivize or discourage particular strategic investment behavior.

This paper aims to examine the short-term structure of the impact of R&D investments on turnover growth, indicating differences between tangible and intangible investments. The main questions are whether R&D and capital investments accompany firms' growth in the subsequent periods and how this relationship depends on other characteristics of the firms, such as size and industry. In addition, the authors study the relationship between R&D investments and the autocorrelation dynamics of firm growth.

The paper uses the European Industrial R&D Investment Scoreboard as data source. This data source includes 1,000 European companies with information on employees, turnover, sector affiliation and details on capital expenditure and R&D expenditure.

The authors find that R&D activities have, on average, a positive effect on turnover growth, while capital investments show both, positive and negative, relationships with firm growth. The relationship and its temporal structure strongly depend on firm size and industry affiliation as well as whether investments are considered as one-time or permanent activities.

Usually, the impacts of firm characteristics on firm growth are studied without explicitly considering time. Firm characteristics and firm growth are usually measured and examined at the same point in time. In contrast, the study will focus on the short-term structure of the influence of firm characteristics on turnover growth, especially the impact of R&D investments.

This paper investigates the extent to which formal capital budgeting methods are used in small high-tech firms. We define high-tech firms by their R&D intensity. In addition, we define software industry as a special type of R&D-intensive firm. We focus on the methods that are used by the small high-tech firms in evaluating the profitability of investment projects, estimating the cost of capital and making decisions related to the capital structure. Our results based on two surveys of Finnish firms indicate that the high-tech firms use similar capital budgeting methods and estimate their cost of capital in a similar way to other small-sized firms in other industries. Moreover, high-tech firms seek external financing and co-owners.

This study aims to focus on the optimal green R&D of a capital-constrained supply chain under different channel power structures as well as the impact of capital constraint, financing cost, channel power structure and cost-reducing efficiency on green R&D and supply chain profitability.

A two-echelon supply chain is considered. The upstream firm engages in green R&D but has capital constraints that can be overcome by external financing. Green R&D is beneficial to reduce production costs and increase consumer demand. Based on whether or not the upstream firm is capital constrained and dominates the supply chain, four models are developed.

Capital constraints significantly lower green R&D and supply chain profitability. Transferring leadership from the upstream to the downstream firms leads to higher green R&D levels and downstream firm profitability, whereas the upstream firm's profitability is increased (decreased) if green R&D investment efficiency is high (low) enough. Greater financing costs reduce green R&D and downstream firm profitability; however, the upstream firm's profitability under the model in which it functions as the follower increases if the initial capital is sufficient. More importantly, empirical analysis based on practice data is used to verify the theoretical results reported above.

This study reveals how upstream firms in supply chains decide green R&D decisions in situations with capital constraints, providing managers and governments with an understanding of the impact of capital constraint, channel power structure, financing cost and cost-reducing efficiency on supply chain green R&D and profitability.

The major contributions are the exploration of supply chain green R&D by taking into consideration channel power structures and cost-reducing efficiency and the validation of theoretical results using practice data.

This paper analyzes the productivity effects of structural capital such as research and development (R&D) and organizational capital (OC). Innovation work also produces innovation-labor-biased technical change (IBTC) and knowledge spillovers. Analyses use full register-based dataset of Finnish firms for the period 1994–2014 from Statistics Finland.

Intangibles are derived from the labor costs of innovation-type occupations using linked employer-employee data. The approach is consistent with National Accounting and offered as one method in OECD (2010) and applied in statistical offices, e.g. in measuring software. The EU 7th framework Innodrive project 2008–2011 extended this method to cover R&D and OC.

Methodology is implementable at firm-level and offers way to link personnel reporting to intangible assets. The OC-IBTC as well as total resources allocated to OC are relevant for productivity growth. The R&D stock is relatively higher but R&D-IBTC is smaller than OC-IBTC. Public policy should, besides technology policy, account for OC and OC-IBTC and related knowledge spillovers in the industries that are most important among the SMEs (low market-share-firms).

The data are based on remote access to Statistics Finland; the data cannot be disseminated.

Intangible assets are measured from innovation work that encompasses not only R&D work. IBTC is proxied in production function estimation by relative compensations on IA work. The non-competing nature of IAs is captured by IA knowledge spillovers. The sample sizes are much higher than in earlier studies on horizontal knowledge spillovers (such as for SMEs,) thus bringing additional generality to the results.