Yao Chen

Bio: Yao Chen is an academic researcher from University of Massachusetts Amherst. The author has contributed to research in topics: Data envelopment analysis & Returns to scale. The author has an hindex of 30, co-authored 87 publications receiving 4189 citations. Previous affiliations of Yao Chen include Nanjing Audit University & Beihang University.

Efficiency Evaluation of Knowledge Flow in University-Industry Collaborative Innovation in China

Abstract: Under economic globalization, innovation is increasingly more open, and the creation, innovation, and application sectors of technological knowledge need to build an open collaborative innovation. Collaborative innovation is a transdisciplinary approach for developing global synergy to improve the competitiveness of an organization through holistic, competitive, and complementary interactions between and among innovation participants in a specific environment (Swink 2006). A collaborative innovation system essentially consists of three sectors: industry, universities, and the government, with each one interacting with the other two, while at the same time playing its own role.

Cellular Automaton and Tacit Knowledge Sharing

Abstract: With the advent of the knowledge economy era, knowledge has become the major source for an organization to gain its core competence, and the full absorption and utilization of knowledge resources outside the organization are the key to increasing productivity and gaining a competitive advantage. An organization’s knowledge stocks determine its core competitiveness directly. Polanyi (2015) divides knowledge into two types, explicit knowledge and tacit knowledge, while Allee (1997) analogizes tacit knowledge and explicit knowledge to oceans and icebergs, respectively. In a traditional economic society, people only give credit to the role of explicit knowledge and focus on the management and utilization of themselves in their daily work. As a matter of fact, explicit knowledge is merely the “iceberg” above the water. With the advent of the knowledge economic society, people have started to draw attention to the enormous tacit knowledge under the water. Polanyi (2015) points out that in modern industries, knowledge is hard to describe as an indispensable part of technologies, thus making the sharing of tacit knowledge hard to codify as an essential component of knowledge sharing. The formation of tacit knowledge is a long-term accumulation process of personal experience, insights, and deep comprehension, which are extremely difficult to imitate and steal; therefore, tacit knowledge is the basis and source for an organization to build up its core competitiveness. Knowledge possesses abstractness and externality, which makes it possible to share, i.e., knowledge’s externalities allow it to be shared at a low cost, and the more it is shared, the more valuable it becomes; on the other hand, such qualities of knowledge serve also as the obstacles to knowledge sharing. More specifically, the high cost, high risk, and uncertainty of income distributions of the knowledge innovation processes determine knowledge owners’ monopolistic attitudes toward knowledge out of their own selfishness and needs for competition, which deter the dissemination and spreading of knowledge.

Congestion in Commodity Trading Advisors

Abstract: Congestion is often used in the operations area to investigate the excessive effect of inputs on outputs. In finance, and more specifically in the derivatives area, leverage is embedded in options and futures contracts. Commodity Trading Advisors (CTAs) use leverage (margin-to-equity ratio) to magnify returns through the use of these futures contracts. However, excessive leverage may hamper performance. This paper aims to show that a related data envelopment analysis (DEA) called the “congestion model” can offer a more precise picture of identifying CTAs suffering from congestion. In other words, if congestion is present then a reduction in input(s) may generate an increase in output. However, the opposite effect can arise. Although traditional DEA does an excellent job at ranking efficient CTAs, congestion on the other hand sizes up which CTAs are using too much (overuse) of each input, thereby reducing their performance/compound return (output). We measure the congestion of the largest (in term...

Two-Stage Network Processes: DEA Frontier Identification

Abstract: The current chapter focuses on how to identify DEA frontier when decision making units (DMUs) are in forms of two-stage network processes. In these two stage network processes, all the outputs from the first stage are intermediate measures that make up the inputs to the second stage. Due to the existence of intermediate measures, the usual procedure of adjusting the inputs or outputs by the efficiency scores, as in the standard DEA approach, does not necessarily yield a frontier projection. The current chapter presents an approach for determining the frontier points for inefficient DMUs within the framework of two-stage network processes.

Big Five Personality Traits and Knowledge Flow in University-Industry Collaborative Innovation

Abstract: The knowledge flow along with the whole process of the collaborative innovation of industry, academia, and research essentially defines that innovation subjects gain the advantages of knowledge in the way that they acquire, transfer, apply, and get feedbacks so as to promote the sharing, transfer, and creation of knowledge. At the same time, they exert the “externalities” and “spillover effects” of it.

Conceptualising sustainability assessment

Abstract: Sustainability assessment is being increasingly viewed as an important tool to aid in the shift towards sustainability. However, this is a new and evolving concept and there remain very few examples of effective sustainability assessment processes implemented anywhere in the world. Sustainability assessment is often described as a process by which the implications of an initiative on sustainability are evaluated, where the initiative can be a proposed or existing policy, plan, programme, project, piece of legislation, or a current practice or activity. However, this generic definition covers a broad range of different processes, many of which have been described in the literature as 'sustainability assessment'. This article seeks to provide some clarification by reflecting on the different approaches described in the literature as being forms of sustainability assessment, and evaluating them in terms of their potential contributions to sustainability. Many of these are actually examples of 'integrated assessment', derived from environmental impact assessment (EIA) and strategic environmental assessment (SEA), but which have been extended to incorporate social and economic considerations as well as environmental ones, reflecting a 'triple bottom line' (TBL) approach to sustainability. These integrated assessment processes typically either seek to minimise 'unsustainability', or to achieve TBL objectives. Both aims may, or may not, result in sustainable practice. We present an alternative conception of sustainability assessment, with the more ambitious aim of seeking to determine whether or not an initiative is actually sustainable. We term such processes 'assessment for sustainability'. 'Assessment for sustainability' firstly requires that the concept of sustainability be well-defined. The article compares TBL approaches and principles-based approaches to developing such sustainability criteria, concluding that the latter are more appropriate, since they avoid many of the inherent limitations of the triple-bottom-line as a conception of sustainability.

A survey of DEA applications

Abstract: The literature of data envelopment analysis (DEA) encompasses many surveys, yet all either emphasize methodologies or do not make a distinction between methodological and application papers. This study is the first literature survey that focuses on DEA applications, covering DEA papers published in journals indexed by the Web of Science database from 1978 through August 2010. The results show that on the whole around two-thirds (63.6%) of DEA papers embed empirical data, while the remaining one-third are purely-methodological. Purely-methodological articles dominated the first 20 years of DEA development, but the accumulated number of application-embedded papers caught up to purely-methodological papers in 1999. Among the multifaceted applications, the top-five industries addressed are: banking, health care, agriculture and farm, transportation, and education. The applications that have the highest growth momentum recently are energy and environment as well as finance. In addition to the basic statistics, we uncover the development trajectory in each application area through the main path analysis. An observation from these works suggests that the two-step contextual analysis and network DEA are the recent trends across applications and that the two-step contextual analysis is the prevailing approach.

A global Malmquist-Luenberger productivity index

Abstract: This paper introduces an alternative environmentally sensitive productivity growth index, which is circular and free from the infeasibility problem. In doing so, we integrated the concept of the global production possibility set and the directional distance function. Like the conventional Malmquist-Luenberger productivity index, it can also be decomposed into sources of productivity growth. The suggested index is employed in analyzing 26 OECD countries for the period 1990–2003. We also employed the conventional Malmquist-Luenberger productivity index, the global Malmquist productivity index and the conventional Malmquist productivity index for comparative purposes in this empirical investigation.