Institutional systems inducing R&D in Amazon- the role of an investor surplus toward stakeholder capitalization

Amazon demonstrated a conspicuous increase in R&D and became the world's top R&D firm in 2017 with a skyrocketing increase in market capitalization, making it close to being the world's biggest company.Such a remarkable accomplishment can be attributed to Amazon's institutional systems, which orchestrate techno-financing systems that fuse a unique R&D transformation system and a sophisticated financing system centered on the cash conversion cycle (CCC). These institutional systems support and endorse aggressive investment in R&D that incorporates the characteristics of uncertainty, a long lead time, and successive inflows of very large amounts of funding without interruption.While some of this investment can be endorsed by Amazon's positive business results in terms of a sustained increase in sales and free cash flow, such a large amount of aggressive investment is beyond endorsement. In addition to actual economic performance, investors have been betting on a high level of risky investment with the expectation of Amazon's future success by trusting its R&D-inducing institutional systems.While the former can be considered to be a general reaction to a producer surplus, the latter can be postulated as an investor surplus in which investors bet on overly optimistic future prospects instead of actual accomplishments. This is similar to a consumer surplus in which consumers pay more than the actual market price for attractive goods and services.By introducing a concept of gross market value consisting of a producer surplus and an investor surplus, this paper attempts to elucidate the institutional systems that enable Amazon to invest a very large amount of financing resources in aggressive R&D.An intensive empirical analysis focusing on the development trajectory of Amazon's techno-financing system over the last two decades was conducted, together with comparative analyses of the performance of the big four online service companies, Google, Apple, Facebook, and Amazon (GAFA).It was identified that among GAFA, Amazon demonstrated the highest dependence on an investor surplus, which suggests that investors are betting on the continuation of Amazon's solid growth by means of its aggressive investment in R&D, supported and endorsed by its institutional systems. This idea is supported by the high elasticity of its investor surplus to R&D investment.Noteworthy is that investors incorporate not only shareholders but also broad stakeholders centered on users, and that they expect not only economic value but also supra-functionality beyond such value.A broadly applicable practical approach for measuring an investor surplus and an insightful suggestion highlighting the significance of an investor surplus toward stakeholder capitalism are thus provided.     

Amazon's initiative transforming a non-contact society - Digital disruptionleads the way to stakeholder capitalization

Contrary to the decisive role of R&D centered on information and communication technology (ICT) in the digital economy, its excessive expansion has resulted in declining productivity due to the two-faced nature of ICT.Consequently, the novel concept emerges of innovation that maintains sustainable growth by harnessing the vigor of soft innovation resources (SIRs).Pioneering endeavors can be observed at the forefront of the global ICT leaders. World R&D leader Amazon has been harnessing the power of users that seek SIRs. This functions as a virtuous cycle, leading to the transformation of R&D by fusing a unique R&D system with a sophisticated financing system. With this orchestration, Amazon leverages the expectations of a wide range of stakeholders, and takes the initiative of stakeholder capitalism in which stakeholders bet on Amazon's prospecting future.This paper attempts to elucidate the driving force of this notable accomplishment, taking Amazon's recent challenge in developing advanced digital fashions (ADFs) successively as prospecting SIRs. Since fashion reflects the change in socio-economic and cultural life, the fashion industry is in the midst of dynamic global change in the digital economy, which necessitates a digital solution.Based on a co-evolution analysis of the development trajectories of Amazon and the fashion industry, it was demonstrated that Amazon has secured a digital solution by developing ADFs successively, and that this success can be attributed to learning orchestration externality. Thus, broad stakeholders’ involvement betting on its challenge, expecting the future prospects of Amazon and the fashion industry, can be expected. Non-contact society accelerates this expectation toward on-demand ADFs manufacturing.These findings give rise to suggestions regarding a new concept of R&D and subsequent neo -open innovation in the digital economy.     

Policy-Induced Environmental Technology and Inventive Efforts: Is There a Crowding Out?

Substantial policy effort is devoted to stimulate environmentally friendly technology through regulation and subsidies. Since innovation is a crucial productivity driver, a potential crowding out of inventive efforts in affected firms may increase the cost of regulation. We study the effects of regulation-induced environmental technology on innovation activities for a sample of firms in Germany. We find some evidence for a crowding out of firms' in-house R&D, especially for firms facing financing constraints. Innovation outcomes and investments in innovation-related fixed assets are not affected. Moreover, subsidy-backed environmental technology does not crowd out R&D.     

Co-evolutionary coupling leads a way to a novel concept of R&D - Lessons from digitalized bioeconomy

Given the increasing role of research and development (R&D) in competitive markets in the digital economy while confronting the dilemma between R&D expansion and a productivity decline, transformation of the R&D model has become a crucial subject for global digital leaders.The authors of this paper postulate that neo open innovation harnessing the vigor of external innovation resources which then developed into a new concept of R&D that self-transforms during an R&D process initiated by Amazon by coupling with users.The authors further develop these postulates by proposing the embedding of a growth characteristic identical to biological coupling.An empirical analysis focusing on the forefront endeavors of global bioeconomy firms and also by Amazon was conducted.A notable endeavor toward a circular economy initiated by its global leader UPM- Kymmene Corporation (UPM) demonstrated the significance of a coupling effect with downstream digital commerce leader Amazon. This effect can be attributed to harnessing the function of the growth characteristic identical to biological coupling through co-evolution of the dual coupling of bioeconomy and digitalization and of upstream and downstream operations.This co-evolutionary coupling is expected to provide a novel concept of R&D that grows its function in a self-propagating way during the R&D process.An insightful suggestion supporting to a novel concept of R&D in the digital economy is thus proposed.     

TFT-LCD industry performance analysis and evaluation using GRA and DEA models

In this study we propose a four-stage approach, which includes data envelopment analysis, Malmquist productivity index (MPI), entropy method and grey relation analysis (GRA), to investigate the operational performance of six thin film transistor liquid crystal display (TFT-LCD) companies in Taiwan during 2009–2012. The input variables are fixed assets, operating expenses, R&D expenses and number of employees, while the output variables are cash flow and net sales. The empirical results showed that companies AUO and HannStar could increase their operation efficiency by improving their VRS efficiency and scale efficiency. When using the MPI model to measure the productivity changes for these TFT-LCD companies, we found that the technology changes in most of the companies are downward tendencies during 2009–2012 except for Ampire. Thus, not only could the proposed GRA with entropy weights evaluate the current performances of each firm effectively, it can also predict their future performances.     

Effective R&D investment planning based on technology spillovers: the case of Korea

This study was performed to discuss an R&D investment planning method based on the technology spillover among R&D fields, from the point of view of technology convergence. The empirical analysis focused on a particular R&D group, such as university departments and specialized research institutes, since local technology combinations are more effective than distant combinations to create a new technology, according to previous research. In addition, worldwide technology competition is increasing, and with the recent convergence of various technologies and industries, strategies for R&D selection and resources allocation of particular R&D groups are becoming increasingly important. The empirical analysis uses a modified Decision Making Trial and Evaluation Laboratory method combined with information on patent citations to resolve the latent problems of the existing model, using as an empirical example the case of the Korea Institute of Geoscience and Mineral Resources (KIGAM), specialized in the geology and resources development R&D area. Through the empirical analysis, the KIGAM’s current R&D investment status is considered, and a reasonable R&D investment planning is suggested from the perspective of technology spillover. By using this framework, the magnitude of technology spillover from the R&D investment planning within a particular R&D group can be measured based on objective quantitative data, and the current R&D investment can be compared with recent global trends.     

The effects and time lags of R&D spillovers in Brazil

Government's innovation investments for science intensive sectors, such as the capital goods industry for developing countries play an important role in technology dissemination; however, few studies have addressed this issue. This study is conducted in the framework of a developing economy (Brazil), and aims to estimate the spillover effects throughout the industry resulting from public investment in innovation, as well as the spillovers of R&D and management investment performed by the capital goods industry through the rest of the industrial sector, and also the time lapse between the occurrence of innovative investment and output growth due to such expenditures. The results of the estimated econometric model exhibit significant and positive spillover effects by the government R&D expenditures for the capital goods industry with a three-year lapse, as well as a one-year lag for the occurrence of output effects on the other companies of the manufacturing sector, resulting from innovative investments by the capital goods industry.     

HRM practices, R&D expenditure and innovative investment: evidence from the UK's 1990 workplace industrial relations survey (WIRS)

Labour 'flexibility' is often portrayed as necessary for aninnovative economy. Using evidence from the UK's 1990 WorkplaceIndustrial Relations Survey we investigate the relationshipsbetween firms' human resource management practices and innovation.Our results suggest that 'low road' HRM practices - short termcontracts, etc. - are negatively correlated with investmentin R&D and new technology. 'High road' work practices -'high commitment' organization and other systems - are positivelycorrelated with investment in R&D and new technology.     

Performance evaluation of China's innovation during the industry-university-research collaboration process—an analysis basis on the dynamic network slacks-based measurement model

This study deploys the Dynamic Network Slacks-based Measurement (DNSBM) model to analyze the dynamic changes of industry-university-research institute's collaboration from static perspectives and deconstructs the “black box”. We present the following findings. 1) The overall innovation efficiency of industry-university-research institute's collaboration in China is 0.6305, and compared to R&D process efficiency, industrialization process efficiency is lower. 2) The links between the R&D process and industrialization process are weak, and the carry-overs between adjacent terms are insufficient, thus forming a low transformation rate of scientific and technological achievements. 3) Total factor productivity shows that universities mainly depend on technical efficiency improvement, while R&D institutions and industries hinge on technology progress.     

When does the diverse partnership of R&D alliances promote new product development? The contingent effect of the knowledge base

Diverse R&D alliance partnerships not only provide access to broad external knowledge but also bring considerable expenses caused by transaction costs and absorption problems. The effective utilization of external knowledge in developing new products is closely related to the internal knowledge base. This study examines how firms' knowledge base properties influence the relationship between diverse R&D alliance partnerships and NPD performance. We empirically find that increases in firms' knowledge complementarity reinforce the positive impact of diverse alliance partners on NPD performance, but increases in firms’ knowledge substitutability attenuate. These findings offer valuable managerial implications that firms should commit more seriously to their internal knowledge base so that they can achieve higher NPD performance when establishing R&D alliances with external actors.     

Increasing the return on investment from federally-funded research and development

Abstract

Each year, the United States invests approximately $495 billion in research and development (R&D) – about a quarter of the total global investment. While the private sector accounts for about 67% of U.S. investment, the Federal government plays a critical role in funding R&D, particularly in areas that address societal needs in which the private sector does not yet have sufficient clear or strong incentive to make the required investments. The Federal government invests approximately $150 billion each year in R&D conducted at Federal laboratories, universities and other research organizations. As Federal R&D investments wind down or are completed, additional work is often still needed to translate the knowledge accrued from that R&D into products and services that will improve lives and provide economic growth. Technology transfer is the process by which existing knowledge, facilities or capabilities developed through R&D are utilised to fulfill public and private need. The transfer of technology from federally-funded R&D to the private sector is crucial to realising the taxpayer’s return on investment in the Federal R&D ecosystem. However, moving innovations from the lab to the market is more than inventing products for people to buy. Technology transfer is about creating jobs and growing the economy; ensuring a strong, secure, and resilient Nation; and improving Americans’ health and environment, fostering the conditions for America to maintain leadership in global innovation.     

Optimal diversification for R&;D project portfolios

Diversification of R&D projects not only can reduce overall risk, but also can create value-enhancement effect. A useful guideline for optimal diversification of R&D projects is important to R&D organizations. This paper extends financial portfolio analyses for R&D management particularly incorporating the technology risk. This study uses a survival model to describe the technology risk since termination of an R&D project can be caused by any technology risk factors. A formula of optimal R&D resource allocation that can dynamically achieve the greatest diversification effect is offered. Furthermore we provide an alternative method for estimating correlations between R&D portfolios, which has a critical influence on diversification effect. The method can be useful in risk assessment when measure the exposure of R&D portfolio to particular sources of uncertainty. The evaluation framework for R&D portfolios optimization also can be applied in project-selection decisions.     

Business Cycles and Investment in Productivity-Enhancing Activities: Evidence from Spanish Firms

This paper tests the opportunity-cost theory on the long-run effects of business cycles using a panel of Spanish firms during the period 1991–2010. Under this theory, the share of productivity-enhancing activities (PEAs), such as R&D investment or on-the-job training, relative to production activities should increase during downturns because of the fall in their relative cost — in terms of forgone output. This would imply that business cycles may have a (positive) long-term impact on firms' productivity growth. In the spirit of Aghion et al. (2008), we allow the impact of the cycle on PEA to vary between firms with different access to external funding. We find that, in accordance with the opportunity-cost approach, the share of R&D investment and training expenditures on total investment outlays follow a countercyclical pattern, which in the case of R&D may be reversed by the presence of credit constraints. However, the share of investment in other non-R&D-related intangible investments is found to be acyclical, which could suggest some kind of substitution across different PEAs over the cycle.     

Business Group Affiliation and R&D

This paper analyzes whether belonging to a business group enhances firms' propensity for and intensity of R&D based on the greater opportunities to finance and co-ordinate R&D strategies and internalize knowledge spillovers. Compared with the existing literature, this paper has the following novelties: (a) it examines how the organization and diversification of business groups influence the R&D investment of affiliated firms; (b) it analyzes the role of R&D spillovers among affiliated firms; and (c) it distinguishes between propensity for and intensity of R&D. We find that less diversified groups are more likely to centralize R&D, while in more diversified groups firms are more likely to be autonomous. We find that controlled companies are more likely to benefit from knowledge spillovers than firms at the head of the group. Finally, we find that R&D autonomy is significantly associated with both a higher propensity for and intensity of R&D in controlled companies.     

Induced technological change and the timing of public R&D investment in the Japanese electricity sector considering a two-factor learning curve

The UNFCCC has stated that energy policies and measures to address climate change should be cost-effective to ensure global benefits at the lowest possible cost. To mitigate the bulk of carbon emission from the electricity sector, a large market penetration of renewable energy technologies with as low cost as possible is a key research topic. The energy-related R&D policy in Japan aims to achieve a green economy. In our study, based on this context, we demonstrated how to optimize the timing of public R&D investment within the framework of a bottom-up partial equilibrium model. The developed optimization model represents the Japanese electricity sector and minimizes the total system cost subject to an accumulated carbon emission constraint. Our main research focus is the role of R&D activity, especially in the innovation stage of renewable technologies. We employ a two-factor learning curve and quantify the impact of the learning effect on the dynamic diffusion of major renewable technologies. The study shows a dynamic technology transition in the Japanese electricity sector and the optimized R&D investment schedule for each renewable technology. With the first-best energy policy, an R&D budget of more than 2000 million USD would be allocated to PV in 2050, which corresponds to 45% of the energy-related Japanese R&D budget in 2050. Because some have criticized the uncertainty problems with dynamic simulations and learning models, supplemental sensitivity analyses are included.     

R&D vs. Other Factor Inputs in a High-Tech Industry

According to knowledge-based growth theories, catch-up with the global technology frontier calls for a shift from physical investment to innovation. This prevailing premise in Finland is tested with an unbalanced panel of firms in Finnish information and communications technology (ICT) manufacturing, over a period of rapid growth, 1990–2003. Stochastic frontier model estimation results are overwhelmed by scale elasticity associated productivity growth. Contrary to beliefs, R&D productivity was relatively low, regardless if measured by efficiency impacts of R&D intensity, technical change or R&D elasticity of output. Results are consistent with industry outcomes and reveal internal causes to the subsequent downfall of ICT manufacturing in Finland.     

R&D and Productivity in High-Tech Manufacturing: A Comparison between Italy and Spain

Using data for 12 manufacturing industries over the period 1980–2006, we perform for Italy and Spain a dynamic panel estimation of the long-run elasticity of total factor productivity (TFP) with respect to R&D capital. In spite of recording a level of R&D capital lower than Italian industries, the technology-based industries in Spain have experienced a similar or higher long-run impact on TFP. This is mainly attributable to what occurred from the mid-1990s onwards when, thanks to increasing R&D efforts, the Spanish industries have been able to catch up with respect to the Italian ones. These findings suggest that, also in countries classified as technology followers, R&D investment is a crucial condition for boosting manufacturing productivity.     

生物制药产业现状分析及我国企业的发展战略

2003-2004年生物技术产业普遍的复苏给我国生物制药企业带来前所未有的机遇和广阔的市场前景.通过中外生物制药企业的对比分析发现,我国企业在自主创新、资金融集、规范管理等各方面与国际水平均存在一定差距.国外制药企业将会在产品研制、专利申请、药品生产以及销售流通等环节对并不强大的中国生物制药业造成冲击.建议我国企业应当明确发展战略,加大研发投入,实现创新、模仿并举;拓宽融资渠道,有效融合金融资本与生物制药技术;积极实施标准化管理;寻求战略合作,从而增强技术优势,降低市场风险,创造更高价值.     

Optimal R&D investments of the firm

This paper examines irreversible decisions on innovative activities where it takes time to complete an R&D project. The total amount of R&D investments that the firm needs to undertake in order to obtain the breakthrough in the innovation process is uncertain. R&D investments are limited by the restriction that they must be self-financed. It is shown that R&D investments are more valuable when the level of uncertainty is large. Especially, it is very attractive to undertake R&D investments if a project faces many uncertainties during its early phases. Furthermore we study how R&D behavior is influenced by different levels of the discount rate and the financing limit. Moreover, the effects of R&D subsidies, spillover benefits and a payoff that decreases over time are analyzed. Received: 9 October 1997 / Accepted: 19 March 1998     

Vaccine R&D in Brazil: The effectiveness of push and pull regulations

Government regulations can guide the technological progress, investment in research and development (R&D), and institutional organization of a specific sector. In this context, using patent data, this study aimed to analyze the effectiveness of three laws that pertain to R&D in Brazilian pharmaceutical market for vaccines. The results reveal an increasing international interest in the Brazilian market since the promulgation of the Industrial Property Law. Despite its limitations, this study reveals significant efforts and promising results in Brazil with respect to ensuring that technological and industrial policies and strategies incorporate innovation in vaccine R&D and change the economy's competitive circumstances.