Interference Phenomena in Temporal Evolution of Accident Probability in Workplaces

The aim of this article is to investigate some implications of complexity in workplace risk assessment. Workplace is examined as a complex system, and some of its attributes and aspects of its behavior are investigated. Failure probability of various workplace elements is examined as a time variable and interference phenomena of these probabilities are presented. Potential inefficiencies of common perceptions in applying probabilistic risk assessment models are also discussed. This investigation is conducted through mathematical modeling and qualitative examples of workplace situations. A mathematical model for simulation of the evolution of workplace accident probability in time is developed. Its findings are then attempted to be translated in real-world terms and discussed through simple examples of workplace situations. The mathematical model indicates that workplace is more likely to exhibit an unpredictable behavior. Such a behavior raises issues about usual key assumptions for the workplace, such as aggregation. Chaotic phenomena (nonlinear feedback mechanisms) are also investigated for in simple workplace systems cases. The main conclusions are (1) that time is an important variable for risk assessment, since behavior patterns are complex and unpredictable in the long term and (2) that workplace risk identification should take place in a holistic view (not by work post).     

Complexity Science: Understanding Research Processes and Improving Research Practice

ABSTRACT

Reflecting on experiences of coresearching with young people aged 13 to 15 in evaluating a government-funded initiative within their own communities, the author explores both some of the consequences of this endeavor and learnings from reflections on research processes therein. Reflections upon lessons learned are analyzed through applying some key concepts from complexity science to the research. It is argued that complexity science assists in reflection and in reaching more in-depth understandings of research processes. The author outlines how these concepts could be applied in research more generally and concludes that learnings from this experience are relevant to researchers everywhere.     

古印度哲学的信息、系统、复杂性思想的基本特质(下)

古印度哲学中蕴涵着丰富而深刻的信息、系统与复杂性思想,可以归纳为十二个方面的特质:丰富的宇宙及其事物自生性的过程论思想;以大梵为本体的世界整体统一性理论;形形色色的多元实在论的本体论观念;明确的信息自在显现思想;丰富的宇宙、事物的全息思想;深刻的信息认识中介论思想;差异整体论和差异认识论的复杂性观念;和合论中的整体涌现论的复杂性思想;事物自然因、无目的、非决定论的复杂性观念;无常无我论、空论中的变易、无主宰、无主体的复杂性思想;"中道论"中两极兼容、对立互补的复杂性思想;具有直观性、猜测性、神秘性、神学性等缺陷.     

Managing structural and dynamic complexity in supply chains: insights from four case studies

Complexity is regarded a major impediment to Supply Chain (SC) performance. However, very few studies aid SC managers adopt adequate practices in response to structural and dynamic complexity. This study offers a comprehensive review of the practices that four manufacturing companies employ in their SC function to manage the structural and dynamic complexity of their product portfolio, internal SC, and supplier and customer bases. Moreover, leveraging the results of the inductive in-depth case studies, a classification of complexity management practices consisting of four clusters is advanced: variety reducing, confinement and decoupling, coordination and collaboration and decision support and knowledge generation. Each cluster’s distinctive logic and limitations are discussed and propositions on their managerial scope are introduced, therefore providing managers with relevant insights to design effective complexity management approaches in their organisations.     

Testing the Interaction Effects of Task Complexity in Computer Training Using the Social Cognitive Model

Using a Modified Social Cognitive Theory framework, this study examines the behavior modeling and lecture‐based training approaches to computer training. It extends the existing Social Cognitive Model for computer training by adding the task complexity construct to training method, prior performance, computer self‐efficacy, outcome expectations, and performance. A sample of 249 students from a large state university served as participants in a laboratory experiment that was conducted to determine the task complexity*training method and task complexity* self‐efficacy interaction effects on performance. Structural equation modeling with interaction effects was used to analyze the data. The results show that behavior modeling outperforms lecture‐based training in a measure of final performance when task complexity is high. Further, it is found that computer self‐efficacy has a greater positive effect on performance when task complexity is high than when task complexity is low. Prior performance is also found to be an important variable in the model.     

Leadership for organizational adaptability: A theoretical synthesis and integrative framework

One of the biggest challenges facing leaders today is the need to position and enable organizations and people for adaptability in the face of increasingly dynamic and demanding environments. Despite this we know surprisingly little about this topic. In this paper we provide a theoretical synthesis and integrative review of research from strategy, organization theory, innovation, networks, and complexity to provide a framework of leadership for organizational adaptability. Our review shows that leadership for organizational adaptability is different from traditional leadership or leading change. It involves enabling the adaptive process by creating space for ideas advanced by entrepreneurial leaders to engage in tension with the operational system and generate innovations that scale into the system to meet the adaptive needs of the organization and its environment. Leadership for organizational adaptability calls for scholars and practitioners to recognize organizational adaptability as an important organizational outcome, and enabling leadership (i.e., enabling the adaptive process through adaptive space) as a critical form of leadership for adaptive organizations.     

Developing a conceptual evaluation framework for gender equality interventions in research and innovation

In this article, we discuss the development of a conceptual evaluation framework to design and assess gender equality interventions and their effects in research and innovation. The conceptual framework presented herewith embraces the complexity, gender-sensitive and theory-based evaluation approaches ensuring that design and evaluation of gender equality interventions consider the complex systems that constitute the context in which the interventions operate. The evaluation framework offers a non-linear concept, where the notion of contribution - not attribution - to achieve impact is central to the integration of team, organizational and system factors in policy design and evaluation. The paper opens the “black box” to address the question of how and why a policy intervention works and in which context and discusses a systematic process on how to approach the interwoven linkages between input, implementation and effects in gender equality interventions in research and innovation, accounting for context sensitivity and methodological pluralism. The evaluation framework may serve as reference for researchers, evaluators, policymakers and other stakeholders in designing and assessing gender equality interventions, and in further developing their evidence, and theoretical and methodological base.     

城市地铁网络复杂性研究

城市地铁网络属于空间复杂网络,其中的节点与边对应于地理空间中的特定位置。文中首先应用Pajek与Ucinet分析了世界主要城市地铁网络的拓扑特性,发现它们拥有如下共性：倾向于选择短边、平均度数接近于2、聚集系数接近于0,直径较大。进而从网络连通性、特征路径长度与直径的变化趋势三方面分析了北京地铁网络的鲁棒性,研究发现北京地铁网络在节点随机故障情况下具有较好的鲁棒性,但在恶意攻击情况下整个网络很快就会瘫痪。     

Partitioning 2-edge-colored complete multipartite graphs into monochromatic cycles, paths and trees

In this paper we consider the problem of partitioning complete multipartite graphs with edges colored by 2 colors into the minimum number of vertex disjoint monochromatic cycles, paths and trees, respectively. For general graphs we simply address the decision version of these three problems the 2-PGMC, 2-PGMP and 2-PGMT problems, respectively. We show that both 2-PGMC and 2-PGMP problems are NP-complete for complete multipartite graphs and the 2-PGMT problem is NP-complete for bipartite graphs. This also implies that all these three problems are NP-complete for general graphs, which solves a question proposed by the authors in a previous paper. Nevertheless, we show that the 2-PGMT problem can be solved in polynomial time for complete multipartite graphs. Research supported by NSFC.     

论复杂性科学视野下的科技进步与生态文明

在复杂性科学视野下,科技进步与生态文明两大系统之间存在着非线性复杂关系。对科技进步与生态文明的研究需要有系统思想作为支撑,科技进步在生态变迁和推动生态文明建设中的具有临界＂涨落＂作用,用复杂性思维方式构建科技进步与生态文明是一种必然的选择。