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"Research and development management"
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Drivers and Barriers to Industrial Energy Efficiency in Textile Industries of Bangladesh
Bangladesh faced a substantial growth in primary energy demand in the last few years. According to several studies, energy generation is not the only means to address energy demand; efficient energy management practices are also very critical. A pertinent contribution in the energy management at the industrial sector ensures the proper utilization of energy. Energy management and its efficiency in the textile industries of Bangladesh are studied in this paper. The outcomes demonstrate several barriers to energy management practices which are inadequate technical cost-effective measures, inadequate capital expenditure, and poor research and development. However, this study also demonstrates that the risk of high energy prices in the future, assistance from energy professionals, and an energy management scheme constitute the important drivers for the implementation of energy efficiency measures in the studied textile mills. The studied textile industries seem unaccustomed to the dedicated energy service company concept, and insufficient information regarding energy service companies (ESCOs) and the shortage of trained professionals in energy management seem to be the reasons behind this. This paper likewise finds that 3–4% energy efficiency improvements can be gained with the help of energy management practices in these industries.
Journal Article
Standing on the Shoulders of Giants
The 11th edition of Research Methodology in Strategy and Management focuses on understanding cutting edge methodological approaches to the study of organizations, managers, and strategy. To this end, the chapters are intended to give readers a sense of new approaches as well as retrospective accounts by Kathy Eisenhardt and Denny Gioia.
eBook
Commercializing Knowledge: University Science, Knowledge Capture, and Firm Performance in Biotechnology
Commercializing knowledge involves transfer from discovering scientists to those who will develop it commercially. New codes and formulae describing discoveries develop slowly-with little incentive if value is low and many competing opportunities if high. Hence new knowledge remains naturally excludable and appropriable. Team production allows more knowledge capture of tacit, complex discoveries by firm scientists. A robust indicator of a firm's tacit knowledge capture (and strong predictor of its success) is the number of research articles written jointly by firm scientists and discovering, \"star\" scientists, nearly all working at top universities. An operationally attractive generalization of our star measure-collaborative research articles between firm scientists and top research university scientists-replicates the impact on firm success. In panel analyses, publications by firm scientists with stars and/or top 112 university scientists increase the number and citation rate for firm patents. Further, star articles increase these rates significantly more than other top 112 university scientists' articles. Cross-sectional analyses of products and employment show a similar pattern of positive effects on firms' success of collaborations with stars or top university scientists, but estimates of differential effects are nonrobust due to multicollinearity. Venture capital funding has significant, usually positive effects on firm success.
Journal Article
Convergenomics
Convergenomics is about the megatrends that are shaping how people behave and organizations work. In this insightful analysis, Sang Lee and David Olson describe how globalization, digitization, changing demographics, changing industry mix, deregulation and privatization, commoditization of processes, new value chains, emerging new economies, deteriorating environment, and cultural conflicts have led to what they define as a convergence revolution. Lee and Olson discuss this convergence revolution from the perspectives of technology, industry, knowledge, open-source networking and bio-artificial convergence, and they explain how human systems are transformed by what they have named convergenomics. Understanding convergenomics can lead to innovative strategic approaches and, the authors contend, more agile businesses are already employing these approaches to become and remain competitive and to generate greater value in a world radically changed by e-commerce. Business leaders and 'students' of strategy at all levels will learn from this book how revolutionary developments can be embraced rather than feared, and how technology that is potentially frightening in its complexity can be harnessed and used to enable productive collaboration and gain competitive advantage.
eBook
Income smoothing through R&D management and credit ratings
Purpose Prior studies generally focus on income smoothing through discretionary accruals and document that managers have incentives to smooth earnings due to various reasons. This paper aims to focus on income smoothing through research and development (R&D) management and examine whether and how income smoothing through R&D management affects credit rating agencies’ perception of firm risk. Design/methodology/approach The authors use financial statement data from the CRSP/Compustat Merged data set universe for the period from 1992 to 2019 after excluding financial and utility industries. The authors follow the model for credit ratings used in previous literature to test the hypothesis. Specifically, the authors use an ordered probit model to express credit ratings as a function of income smoothing attributes. Findings The authors find that R&D-based income smoothing improves a firm’s credit rating. However, the positive effect of R&D-based income smoothing on credit ratings is less than that of accruals-based income smoothing. This study also shows that the positive effect of R&D-based income smoothing is more pronounced for firms less subject to opportunistic incentives, further strengthening the notion that managers smooth earnings through R&D management to provide more informative earnings. Originality/value This study contributes to the income smoothing literature in several ways. First, the authors contribute to the research by showing that managers’ income smoothing activity through R&D management positively affects firms’ credit rating. Second, the authors also document the relative benefits of the two different income smoothing techniques in terms of improving credit agencies’ perception of firms’ creditworthiness.
Journal Article
Potential for the use of large unstructured data resources by public innovation support institutions
Effective programming of research and development (R&D) support, adjusted to the actual potential of beneficiaries, requires the use of modern analytical tools. An efficient R&D support system requires up-to-date data on technological trends, ongoing (and planning) research, market needs and developing innovation. The most popular programming methods were based on the analysis of data with a 4 to 5-year time delay until recently. Having described the method of refining information from unstructured data, we explore how to make it possible not only to solve the issue of up-to-date data but to identify of the latest trends in R&D activities.The analytical tools we describe were already fully functional in 2018 and are constantly being improved. The article presents the potential of one tool that can be applied in public support institutions. Methods of identifying and diagnosing technology trends are presented within the case study of the electric car technology trend. The presented case study shows the effectiveness of the method we developed for identifying and diagnosing areas requiring support from public funds. Public institutions, including public institutions supporting R&D and innovation processes, can apply tools that allow an increase in the quality of public support programmes offered, but also beneficial for the quality of strategic resources management within the institution itself. The comparison of the predictions made by the described tools with the classifications made by experts, the former are more accurate and precise. Moreover, the results of the analyses performed by the presented model are not influenced by distorting factors—fads, trends, political pressures, or processes with an unidentified, non-substantive background. It should be emphasized that the accuracy of the whole model is 0.84. The described tools and methods are already directly applicable in many areas related to the support of R&D activity worldwide. The article presents a solution that effectively enables the management of more precise programmes supporting innovative activities used for the first time in Poland. It is also one of the first uses of these methods by public administration in the world. Our approach not only strengthens improved adjustment of the support offered for R&D activity, but also makes it possible to apply and improve management methods in public institutions.
Journal Article
Landscape of Research Areas for Zeolites and Metal-Organic Frameworks Using Computational Classification Based on Citation Networks
The field of porous materials is widely spreading nowadays, and researchers need to read tremendous numbers of papers to obtain a “bird’s eye” view of a given research area. However, it is difficult for researchers to obtain an objective database based on statistical data without any relation to subjective knowledge related to individual research interests. Here, citation network analysis was applied for a comparative analysis of the research areas for zeolites and metal-organic frameworks as examples for porous materials. The statistical and objective data contributed to the analysis of: (1) the computational screening of research areas; (2) classification of research stages to a certain domain; (3) “well-cited” research areas; and (4) research area preferences of specific countries. Moreover, we proposed a methodology to assist researchers to gain potential research ideas by reviewing related research areas, which is based on the detection of unfocused ideas in one area but focused in the other area by a bibliometric approach.
Journal Article
Bridging the Skill Gap in Robotics: Global and National Environment
This article focuses on the demand for skills of highly qualified scientific and technical professionals (engineers and researchers) in robotics, on both a global and national level. Information is collected using the text-mining of open-access vacancies for understanding the global trends and in-depth interviews with experts for a more detailed study of national trends. The study explores the combination of hard and soft skills, as well as interdisciplinary skills. Soft skill requirements play an important role in the demanded skill set of the specialist, but the claims for hard skills (including digital) are not becoming less strict. Programming and the knowledge of specialized software packages are the most important skills, but must be combined with practical skills (assembly, welding, soldering). The broad range of application areas for robotic systems creates demand for new multidisciplinary skills (knowledge of artificial intelligence, new materials, and biology). Rapid technological development underlines the growing importance of soft skills, such as communication skills, self-motivation, and a willingness to learn. Lists of the most demanded skills in different countries principally coincide. Results can be applied for developing policies aimed at eliminating the skill gap in prospective technological areas.
Journal Article
A Comparison of U.S. and European University-Industry Relations in the Life Sciences
We draw on diverse data sets to compare the institutional organization of upstream life science research across the United States and Europe. Understanding cross-national differences in the organization of innovative labor in the life sciences requires attention to the structure and evolution of biomedical networks involving public research organizations (universities, government laboratories, nonprofit research institutes, and research hospitals), science-based biotechnology firms, and multinational pharmaceutical corporations. We use network visualization methods and correspondence analyses to demonstrate that innovative research in biomedicine has its origins in regional clusters in the United States and in European nations. But the scientific and organizational composition of these regions varies in consequential ways. In the United States, public research organizations and small firms conduct R&D across multiple therapeutic areas and stages of the development process. Ties within and across these regions link small firms and diverse public institutions, contributing to the development of a robust national network. In contrast, the European story is one of regional specialization with a less diverse group of public research organizations working in a smaller number of therapeutic areas. European institutes develop local connections to small firms working on similar scientific problems, while cross-national linkages of European regional clusters typically involve large pharmaceutical corporations. We show that the roles of large and small firms differ in the United States and Europe, arguing that the greater heterogeneity of the U.S. system is based on much closer integration of basic science and clinical development.
Journal Article