R&D project evaluation: An integrated DEA and balanced scorecard approach

We present and demonstrate a multi-criteria approach for evaluating R&D projects in different stages of their life cycle. Our approach integrates the balanced scorecard (BSC) and data envelopment analysis (DEA) and develops an extended DEA model. The input and output measures for the integrated DEA–BSC model are grouped in “cards” which are associated with a “BSC for R&D projects”. The BSC is embedded in the DEA model through a hierarchical structure of constraints that reflect the BSC balance considerations. We illustrate the proposed approach with a case study involving an industrial research laboratory that selects and executes dozens of R&D projects every year.     

Within-cluster determinants of output efficiency of R&D in the space industry

Dynamic slacks-based data envelopment analysis is applied to measure output performance efficiency of space R&D active private firms. Fractional logit panel analysis is used to identify associations between this firm level R&D output efficiency and space industry level R&D specialisation, presence of anchor firms, and public R&D capacity within geographical clusters.Primary data collected for the entire population of space R&D active firms in Belgium for the period 2011–2015 reveals that an environment specialized in the focus firm's space activities exerts a positive influence on R&D output efficiency. The public space R&D capacity and the presence of space anchor firms within the cluster do not influence R&D output efficiency. Firm age, a mixture of space and non-space R&D, and larger amounts of public funding positively affect R&D output efficiency. These findings should be seen in a context of a space industry dominated by SMEs and in a five year time-span.     

DEA and ranking with the network-based approach: a case of R&D performance

This study enhances the network-based approach, which is a novel method to increase discrimination in data envelopment analysis. The enhancements include removing the bias caused by a scale difference among organizations and highlighting the approach's ability to identify the strengths and weaknesses of each organization. The former makes the approach applicable to both the constant returns of scale (CRS) and the variable returns of scale (VRS) models. The network-based approach applies the centrality concept developed in social network analysis to discriminate efficient decision making organizations as determined by standard data envelopment analysis (DEA). More specifically, the results of data envelopment analysis are transformed into a directed and weighted network in which each node represents a decision making organization and the link between a pair of node represents the referencing relationship between the pair. The centrality value for each efficient organization provides the base for discrimination and ranking. This network-based approach suggests aggregating DEA results of different input/output combinations such that the merits of each organization under various situations can be considered. The final ranking of this approach favors organizations that have their strengths evenly spread and tends to screen out specialized efficient organizations. As a real world example, the approach is applied to evaluate and rank the R&D (research and development) performance of Taiwan's government-supported research institutes. The cross-organizations and within-organization strengths for each efficient research institute are identified after applying the approach. A two-stage R&D evaluation model separates the R&D process into the technology development and technology diffusion stage. The resulting performance map differentiates the research institutes into four categories—Achievers, Marketers, Innovators, and Underdogs.     

Managing uncertainty and ambiguity in frontier R&D projects: A Korean case study

One of the important tasks in planning large, frontier R&D projects is to minimize innate uncertainties and ambiguities in the early stages of the project. This case study is an attempt to provide a framework to handle such problems in R&D planning. In it we analyze various elements that define planning conditions, classify them into basic constructs, and suggest tools and methods to deal with uncertainty and ambiguity. We utilize two case studies to approach the research questions. Our findings suggest that both initial planning conditions and the effectiveness of front-end planning management affect the performance of R&D planning and the later R&D process.     

R&D,productivity, and market value: An empirical study from high-technology firms

Although prior research has addressed the influence of production activity and research and development (R&D) on productivity, it is not clear whether production and R&D affect the market value of a firm. This study proposes and verifies an R&D value chain framework to explore the relationship among productivity, R&D, and firm market values, as measured by Tobin's q theory. By doing so, we attempt to link new theoretical insights and empirical evidence on the effects of R&D efforts and basic production activities to the market valuations of high-technology firms. The value chain data envelopment analysis approach was proposed to estimate parallel-serial processes of basic operations and R&D efforts. This approach can be used to simultaneously estimate the profitability efficiency and marketability efficiency of high-technology firms. This area has rarely been studied, but it is particularly important for high-technology R&D policies and for further industrial development. Using the R&D value chain perspectives of model innovations and extensions proposed in several previous studies, we examined the appropriate levels of intermediate outputs. Production efficiency and R&D were combined to estimate the appropriate levels of intermediate outputs for high-technology firms. Based on the intermediate output analyses, we developed an R&D efforts decision matrix to explore and identify operational and R&D efficiency for high-technology firms. Our sample firms are displayed on a four-quadrant action grid that provides visual information on current short-term operational efficiency and decision making on long-term R&D strategic positions. The empirical findings from the R&D value chain model can provide information for policymakers and managers and suggest the adoption of various policies that place more emphasis on profitability and marketability strategies.     

Evaluating the efficiency of dual-use technology development programs from the R&D and socio-economic perspectives

This study applies a network data envelopment analysis model called network slacks-based measure (NSBM) to examine the R&D efficiency and socio-economic efficiency of Taiwan's dual-use (military and general public) technology development programs. We also employ the additive super-efficiency model to distinguish programs at different stages and conduct an analysis on the strengths and weaknesses of internal resource utilization. The results of this study show that the R&D efficiency is substantially higher than the socio-economic efficiency. Among the dual-use technology development programs, material and chemical engineering programs demonstrate relatively higher performance. This study provides insights into the policy of resource utilization.     

风险条件下研发项目改进DEA选择模型

研发项目是企业提高竞争力的关键，研发项目选择关系到企业的战略和未来发展趋势。研发项目在生命周期内面临技术风险、突发风险和市场风险，本文考虑到研发项目的风险特征，结合企业战略，构建了基于效率排序的研发项目选择模型。首先，本文对研发项目的有效性和相对于其它备选项目的相对优势进行分析；然后针对数据包络分析模型排序的不足，结合平衡计分卡理念，规范研发项目投入的比例，引入实物期权理论，改进数据包络分析模型，实现了对研发项目的效率排序；最后通过实际算例对模型进行验证、横向对比和敏感性分析，结果表明：相对于标准数据包络分析模型，本文提出的模型具有更高的效率区分度，并且能够敏感地捕捉到研发项目投入和产出的变化对效率影响的演变过程。     

Structural Constraints,Strategic Interactions and Innovative Processes: Measuring Network Effects in New Product Development Projects

In this paper I approach the analysis of innovation activities as relational processes first deriving the econometric specification of an endogenous model of network effect on individual outcome, and then using data on innovation projects to empirically test the impact on actors' performance of relational activities in new product development. A complete relational set of inter-unit relationships in 173 new product development projects among 24 R&D units of a profit oriented R&D organization is analyzed using mixed regressive-autoregressive models. Results show the importance of a network effects on unit's performance, after controlling for unit's attributional characteristics. The magnitude and directionality of these effects are sensitive to project characteristics, but not to the directionality of the ties. Implications for theory and research in innovation management are discussed by elaborating on the importance of the content of the ties to assess the impact of relational activities, and to examine client (i.e. ties sent) and server (i.e. ties received) relational options as complementary aspects of interaction strategies.     

The Role of Project and Organizational Context in Managing High‐tech R&D Projects

High‐tech organizations often struggle to manage different types of R&D projects. Evidence from research and practice suggests that managers frequently categorize and manage projects based on the extent of change triggered in product, process, technology, and market dimensions. However, this can create challenges in high‐tech organizations. This study investigates how high‐tech organizations manage R&D projects based on their learning goals. First, we argue for the benefits of categorizing R&D projects based on the degree of exploration and exploitation learning goals. A qualitative case study from four high‐tech business units involving 10 R&D projects helps understand the different types of projects based on their learning goals. The case study shows that R&D projects in high‐tech organizations typically fall into three categories based on their learning goals: Radical innovation projects, Incremental innovation projects, and Hybrid projects. Second, we iterate between literature and evidence from our qualitative data to theorize how project context and organizational context affect project performance depending on the type of project. The data for the empirical analysis come from a multilevel survey of 110 R&D projects across 34 high‐tech business units. Results show the importance of designing project and organizational context differently for the three types of R&D projects. Collectively, this study offers a new perspective on how to manage high‐tech R&D projects.     

Managing Knowledge Creation in High‐Tech R&D Projects: A Multimethod Study

R&D projects in high‐tech organizations bring together diverse knowledge domains to quickly develop new products and processes. The fast‐paced context of high‐tech organizations makes it challenging to create new knowledge and solve complex problems. Managing these R&D projects requires understanding both the mechanisms and the type of knowledge created to achieve project objectives. This research conducts a two‐phased multimethod study to understand knowledge creation in high‐tech R&D projects. The first phase uses qualitative data to develop a theory on knowledge creation in R&D projects. The second phase involves a survey that collects data from R&D projects to test the theory. Results from the case study find that R&D projects benefit from two types of knowledge – objective and intuitive. The case analyses show that intuitive and objective knowledge creation in high‐tech organizations occurs by creating not only diverse but also psychological safe project teams. The large‐scale survey finds that team diversity positively influences objective knowledge creation while psychological safety affects intuitive knowledge creation. Surprisingly, the results show that team diversity negatively affects intuitive knowledge creation. A post hoc analysis takes a more granular look at diversity and shows that different kinds of diversity have different effects on knowledge creation. This helps to better explain how to manage innovation across boundaries. Finally, the analysis shows that both objective and intuitive knowledge influence R&D project performance. Taken together, these results help explain how to manage innovation across functional boundaries to create knowledge and enhance R&D project performance.      

Technology development control styles in multinational corporations: a case study

Multinational firms tend to geographically disperse their R&D activities to a larger extent than in the past. International R&D seems to play an increasingly important role within the global process of technological innovation taking place in multinational corporations. As a consequence, firms are challenged to design global R&D organisations and manage foreign units playing a central role in their innovation process. A key managerial aspect is the balance between autonomy and control of foreign R&D units. This case study deals with management control styles over foreign R&D units. It is based on the results of an empirical analysis of 16 multinational firms operating in technology-intensive industries. It proposes a taxonomy of management control styles in foreign R&D and gives the cue for further research in the area of technology development control.     

Explaining performing R&D through alliances: Implications for the business model of Italian dedicated biotech firms

In recent years management scholars and practitioners have been interested in Research and Development (R&D) partnering, especially in high-tech industries. While the motivations of research partnership formation have been widely explored in literature, little attempt has been undertaken to examine the effects of research partnerships on R&D productivity and the implications for business models of the new ventures. In this paper we try to shed some light on the business models of the young ventures involved in R&D partnerships and their effect on R&D productivity. Our hypotheses are that experience in previous alliances, repeated partnerships and tight relationships have positive effects on R&D productivity while rigid governance structures and public R&D subsidies have negative effects on such productivity. We discuss how these aspects affect the business models of biotech firms. We test our hypotheses on a sample of 55 Italian DBFs (Dedicated Biotech Firms). Results support our hypotheses. Managerial implications and further issues for future research are discussed.     

A fuzzy set approach for R&D portfolio selection using a real options valuation model

Making R&D portfolio decision is difficult, because long lead times of R&D and market and technology dynamics lead to unavailable and unreliable collected data for portfolio management. The objective of this research is to develop a fuzzy R&D portfolio selection model to hedge against the R&D uncertainty. Fuzzy set theory is applied to model uncertain and flexible project information. Since traditional project valuation methods often underestimate the risky project, a fuzzy compound-options model is used to evaluate the value of each R&D project. The R&D portfolio selection problem is formulated as a fuzzy zero–one integer programming model that can handle both uncertain and flexible parameters to determine the optimal project portfolio. A new transformation method based on qualitative possibility theory is developed to convert the fuzzy portfolio selection model into a crisp mathematical model from the risk-averse perspective. The transformed model can be solved by an optimization technique. An example is used to illustrate the proposed approach. We conclude that the proposed approach can assist decision makers in selecting suitable R&D portfolios, while there is a lack of reliable project information.     

The performance evaluation of regional R&D investments in China: An application of DEA based on the first official China economic census data

R&D (Research and Development) activities represent the basic core of corporate science and technology activities, and play a crucial role in enhancing the ability of companies to achieve rapid and sustainable growth. In recent years, the total R&D investments in China have increased significantly and the proportion of the industrial investments in R&D activities relative to national R&D investments has increased rapidly. In order to investigate the effectiveness of these R&D investments, we utilize Data Envelopment Analysis (DEA) models to evaluate the relative efficiencies of 30 regional R&D investments using the First Official China Economic Census Data in 2004. Our investigation and study indicate the following: (1) Only six provinces are global technical efficient and the performance of regional R&D investments in China needs to improve dramatically. (2) Increasing returns to scale have not yet occurred in any province. Constant returns to scale have prevailed in most provinces in the Western region, and decreasing returns to scale have prevailed in most provinces in the Eastern and Central regions. (3) There are no direct relationships between global technical efficiency and the amount of R&D investment. The Western region has the highest average radial efficiency score, followed by the Eastern region, and then by the Central region. (4) The Eastern region has advantages in local technical efficiency, the Western region has advantages in scale efficiency, while the Central region has neither technical efficiency advantages nor scale efficiency advantages. Suggestions are proposed to improve efficiencies of regional R&D investments.     

Identifying key performance indicators in food technology contract R&D

Innovating companies increasingly rely on outsourcing to Contract Research Organisations (CROs) for their Research and Development (R&D), which are largely understudied. This paper presents the outcome of a case study in the field of food technology contract research, identifying context specific Key Performance Indicators (KPIs) for a CRO. KPIs were identified with a modified version of the Wageningen Innovation Assessment Tool, with which 72 finished successful and less successful projects were analysed. We developed a benchmarking tool to evaluate starting or running innovation project quality, which allows for direct, in situ project improvements by project leaders at CROs.     

The Processes of New Product Development Recentralization towards a Transnational Emphasis in Multinational Corporations

Studies on R&D internationalization have identified the decentralization-recentralization pattern of many multinational corporations (MNCs). Studies have also indicated that MNCs tend to pursue a transnational emphasis during R&D recentralization. This research focuses on recentralization of new product development (NPD) in MNCs and aims to reveal different processes of it towards a transnational emphasis. Through a qualitative case study of four MNCs, the NPD recentralization process was explored in two important dimensions – power centralization and pluralistic input. Four process variants were discovered, showing different approaches to power centralization and pluralistic input. The processes of recentralization are novel to the area of R&D internationalization. This study also advances our understanding of R&D recentralization with a focus on NPD fulfilling market demand, which has not been well addressed in prior studies. In addition, this study generates some insights into transnational management.     

Managing Internal R&D Networks in Global Firms: What Sort of Knowledge is Involved?

How should a global firm manage its network of R&D centres in an effective manner? Some have developed an Integrated Network model in which the R&D centres around the world are tightly integrated into a coherent whole. Others have adopted a Loosely-Coupled Network model in which individual “centres of excellence” are given considerable autonomy. In this paper we argue that the way individual R&D units are structured, and the way the entire network is managed, should be based not on administrative heritage, environmental turbulence or management style, but on the basis of the underlying characteristics of the firm’s knowledge assets. In particular we focus on the observability and mobility of the firm’s knowledge assets, the impact these factors have on the way individual R&D centres are structured, and how they relate to one another in the international network. The argument is supported using examples and data from Swedish firms including ABB, Alfa Laval and Ericsson.     

The impact of service R&D on the performance of Korean information communication technology small and medium enterprises

In recent years, research and development (R&D) in the service industry has attracted a great deal of attention from both academia and industrial firms. However, compared to the manufacturing sector, little research exists on the implications of R&D for the financial and/or non-financial performance of firms in the service industry. The purpose of this study is to examine the impact of service R&D on the performance of information communication technology (ICT) firms. We identify five categories of R&D activities and investigate their impact on the financial and non-financial performance of 100 ICT firms, with a focus on small and medium enterprises (SMEs) in South Korea. We postulate positive relationships between R&D efforts and a firm's performance. However, the findings only partially support our hypotheses; unexpected results demonstrate that the presence of R&D management negatively influences a firm's performance. We present detailed statistical results and discuss the implications of the study.     

The integration of TQM and technology/R&D management in determining quality and innovation performance

This paper presents an empirical study which examines the co-alignment between Total Quality Management (TQM) and technology/research and development (R&D) management in predicting organizational performance in terms of quality and innovation. This study improves our understanding of the relationship between TQM and innovation based on the following two major issues. First, this study contributes to the understanding of the co-alignment between TQM and technology management along with R&D management by bridging the gap between the two areas which are often addressed in a separate fashion. Second, this study also examines the impact of the integration between TQM and technology/R&D on quality and innovation performance which have been considered as the primary sources of a competitive advantage. The empirical data was drawn from 194 Australian organizations and analyzed using the Structural Equation Modeling (SEM) technique. The findings indicate that TQM shows a strong predictive power against quality performance but no significant relationship against innovation performance. On the other hand, technology and R&D management shows a significant relationship with quality performance but at a lower level than that of TQM, and shows much stronger relationship with innovation performance. In addition, there is strong and positive correlation between TQM and technology/R&D management. The major implication of this study is that technology/R&D management is an appropriate resource to be used in harmony with TQM to enhance organizational performance, particularly innovation.     

Development of absorptive capacity over time and across boundaries: The case of R&D consortia

Absorptive capacity (AC) has been identified as the ability of firms to acquire, assimilate, and apply external knowledge, and thus as a pre-condition for learning from knowledge environment. However, extant literature has focused on AC as (1) a static and (2) a firm-centred concept. In particular, there is little conceptual framing and empirical evidence of how AC develops over time and across boundaries. Taking R&D consortia as the unit of analysis and based on insights from three in-depth case studies of collaborative R&D, our contribution is a framework for AC development over time and across inter-organizational, intra-organizational, and practice boundaries at different stages of collaboration in R&D consortia. Using this framework, we identify a set of mechanisms which enable the development of AC and we discuss the preconditions for these mechanisms. For R&D managers, our research implies that in order to enhance effectiveness of knowledge transfer and learning in R&D consortia they need to develop a strategy that (1) supports learning and AC development throughout the whole cycle of the collaboration, not only by focusing on intra-firm capabilities, but in particular by providing flexible interfaces for overcoming a variety of interaction and learning boundaries between heterogeneous R&D partners, and (2) enables the integration of created and acquired knowledge within the organization once the collaboration is over.