循环效应及其在能源消耗与经济增长关系中的实证分析

一些变量相互影响,在相互作用过程中可能形成循环效应,已有研究表明能源消耗与经济增长呈正相关或存在双向因果关系;现做进一步深入研究,目的是研究能源消耗与经济增长之间的相互作用路径,即循环效应.包括技术进步在此循环过程中的中介效应,固定资产投资在此循环过程中的调节作用;采用二阶最小二乘(2LS)算法进行模型估计.采集1990-2012年数据,进行循环过程中的中介效应检验和有中介的调节效应检验.实证表明能源消耗和经济增长之间存在循环效应,技术进步在能源消耗和经济增长之间起循环的中介作用;固定资产投资在能源消耗引起经济增长过程中的调节作用部分地通过技术进步发挥作用,在经济增长引起能源消耗过程中的调节作用完全地通过技术进步发挥作用.     

Adoption as a social marker: Innovation diffusion with outgroup aversion

Social identities are among the key factors driving behavior in complex societies. Signals of social identity are known to influence individual behaviors in the adoption of innovations. Yet the population-level consequences of identity signaling on the diffusion of innovations are largely unknown. Here we use both analytical and agent-based modeling to consider the spread of a beneficial innovation in a structured population in which there exist two groups who are averse to being mistaken for each other. We investigate the dynamics of adoption and consider the role of structural factors such as demographic skew and communication scale on population-level outcomes. We find that outgroup aversion can lead to adoption being delayed or suppressed in one group, and that population-wide underadoption is common. Comparing the two models, we find that differential adoption can arise due to structural constraints on information flow even in the absence of intrinsic between-group differences in adoption rates. Further, we find that patterns of polarization in adoption at both local and global scales depend on the details of demographic organization and the scale of communication. This research has particular relevance to widely beneficial but identity-relevant products and behaviors, such as green technologies, where overall levels of adoption determine the positive benefits that accrue to society at large.     

Can tools help unify organization theory? Perspectives on the state of computational modeling

Scholars engaged in the study of work group and organizational behavior are increasingly calling for the use of integrated methods in conducting research, including the wider adoption of computational models for generating and testing new theory. Our review of the state of modern computational modeling incorporating social structures reveals steady increases in the incorporation of dynamic, adaptive, and realistic behaviors of agents in network settings, yet exposes gaps that must be addressed in the next generation of organizational simulation systems. We compare 28 models according to more than two hundred evaluation criteria, ranging from simple representations of agent demographic and performance characteristics, to more richly defined instantiations of behavioral attributes, interaction with non-agent entities, model flexibility, communication channels, simulation types, knowledge, transactive memory, task complexity, and resource networks. Our survey assesses trends across the wide set of criteria, discusses practical applications, and proposes an agenda for future research and development. Michael J. Ashworth is a doctoral candidate in computational organization science at Carnegie Mellon University, where he conducts research on social, knowledge, and transactive memory networks along with their effects on group and organizational learning and performance. Practical outcomes of his work include improved understanding of the impact of technology, offshoring, and turnover on organizational performance. Mr. Ashworth has won several prestigious grants from the Sloan Foundation and the National Science Foundation to pursue his research on transactive memory networks. Journals in which his research has appeared include Journal of Mathematical Sociology, International Journal of Human Resource Management, and Proceedings of the International Conference on Information Systems. His recent work on managing human resource challenges in the electric power industry has been featured in the Wall Street Journal and on National Public Radio's ``Morning Edition.' Mr. Ashworth received his undergraduate degree in systems engineering from the Georgia Institute of Technology. Kathleen M. Carley is a professor at the Institute for Software Research International in the School of Computer Science at Carnegie Mellon University. She is the director of the center for Computational Analysis of Social and Organizational Systems (CASOS), a university-wide interdisciplinary center that brings together network analysis, computer science and organization science (www.casos.ece.cmu.edu). Prof. Carley carries out research that combines cognitive science, dynamic social networks, text processing, organizations, social and computer science in a variety of theoretical and applied venues. Her specific research areas are computational social and organization theory; dynamic social networks; multi-agent network models; group, organizational, and social adaptation, and evolution; statistical models for dynamic network analysis and evolution, computational text analysis, and the impact of telecommunication technologies on communication and information diffusion within and among groups. Prof. Carley has undergraduate degrees in economics and political science from MIT and a doctorate in sociology from Harvard University.     

The Cyclical Relationship Between Research and Standards: The Case of Principles and Standards for School Mathematics

The link between standards and research may not be clearcut. However, in this article the authors argue that there is a notable relationship between standards and research, one that is cyclical in nature. Using the standards for school mathematics developed by the National Council of Teachers of Mathematics (NCTM) as a case in point, the authors examine how NCTM's standards have influenced the agenda for mathematics education research and stimulated research on the impact of those standards. In turn, this and other research played a significant role in the development of NCTM's new Principles and Standards for School Mathematics. The authors conclude with a discussion of ways in which the Principles and Standards may continue this cyclical relationship in coming years, potentially promoting investigation of new research areas and systematic research on the impact of standards.     

Scheduling unit — time tasks on flow — shops under resource constraints

We consider the problem of scheduling tasks on flow shops when each task may also require the use of additional resources. It is assumed that all operations have unit lengths, the resource requirements are of 0–1 type and there is one type of the additional resource in the system. It is proved that when the number of machines is arbitrary, the problem of minimizing schedule length is NP-hard, even when only one unit of the additional resource is available in the system. On the other hand, when the number of machines is fixed, then the problem is solvable in polynomial time, even for an arbitrary number of resource units available. For the two machine case anO(n log ₂ ² n) algorithm minimizing maximum lateness is also given. The presented results are also of importance in some message transmission systems.     

Approximating queue size and waiting time distributions in general polling systems

Polling system models are extensively used to model a large variety of computer and communication networks as well as production and service systems in which multiple customer classes or a number of distinct items compete for the capacity of a common server or production facility. In this paper we describe an efficient approximation method for the steady state distributions of the queue sizes and waiting times. This method is highly accurate as demonstrated by an extensive numerical study. In addition, it is highly adaptable to a variety of arrival patterns and switching protocols, including exhaustive and gated regimes, simple cyclical systems as well as general polling tables. For a system withN stations, one finds the firstK probability density function values of the steady state queue size in any given station inO(max(N, K ²) time only. When executed on an IBM system RS/6000, we have observed an average CPU time of less than 1 second for systems with as many as 50 stations over a large variety of parameter settings.     

Online Scheduling with Hard Deadlines

We study non-preemptive, online admission control in the hard deadline model: each job must either be serviced prior to its deadline or be rejected. Our setting consists of a single resource that services an online sequence of jobs; each job has a length indicating the length of time for which it needs the resource and a delay indicating the maximum time it can wait for the service to be started. The goal is to maximize total resource utilization. The jobs are non-preemptive and exclusive, meaning once a job begins, it runs to completion, and at most one job can use the resource at any time. We obtain a series of results, under varying assumptions of job lengths and delays.     

A Model of Vacancy Chains as a Mechanism for Resource Allocation

Vacancy chains can be tracked in any context where the availability of a desirable resource triggers a cascade of occupations through which the scarce resource flows through different owners. However, under certain conditions, vacancy chains, rather than markets or other forms of competition, determine the allocation of the resource. This article develops a formal and computational model of vacancy chains as a mechanism for resource allocation in order to find out their properties with respect to organizational forms.

We find that hierarchies with few middle managers are particularly prone to make use of vacancy chains in order to allocate resources that originate at the top, such as employment positions. In fact, vacancy chains often disappear when information is widely available, because information is likely to attract applicants who engage in a competition. Thus, the many middle managers of a thick organization may compete for a resource that originates at the top. On the contrary, organizations that are thick at the bottom and at the top, but thin in the middle, are most likely to regulate resource allocation by means of vacancy chains.     

Limit cycles in an optimal control problem of diabetes

This article examines the behaviour of an individual diagnosed with diabetes. It is shown that the medical treatment of the disease creates incentives that make a diabetic's consumption, weight, and labour supply display cyclical patterns. The existence of a limit cycle is proved using an adaptation of the Hopf bifurcation theorem for optimal control problems.     

A new model for cycles in retail petrol prices

This paper explores the way that retail petrol prices may vary in a cyclical way as a result of competitive behavior by petrol retailers when some drivers choose to fill up early when a low petrol price is available. We include a stochastic model for an individual driver’s use of petrol and consider what happens as the expected future price of petrol is adjusted either according to observed prices or in anticipation of cyclical behavior. This model is different from most previous work on petrol price cycles that has focussed on Edgeworth cycles.     

Adoption and use of AI tools: a research agenda grounded in UTAUT

This paper is motivated by the widespread availability of AI tools, whose adoption and consequent benefits are still not well understood. As a first step, some critical issues that relate to AI tools in general, humans in the context of AI tools, and AI tools in the context of operations management are identified. A discussion of how these issues could hinder employee adoption and use of AI tools is presented. Building on this discussion, the unified theory of acceptance and use of technology is used as a theoretical basis to propose individual characteristics, technology characteristics, environmental characteristics and interventions as viable research directions that could not only contribute to the adoption literature, particularly as it relates to AI tools, but also, if pursued, such research could help organizations positively influence the adoption of AI tools.

     

Dynastic cycle: a generic structure describing resource allocation in political economies,markets and firms

A generic system embodies basic principles and insights that are common to a set of diverse cases and situations. This paper presents a new generic system that we name the dynastic cycle structure. It is based on a stylized model of events from the Chinese history. The model describes resource allocation between social, asocial and control uses in political economies, markets and firms that experience cyclical behaviour and homeostasis symbolizing low levels of performance. Numerical simulations with the model are used to understand the internal dynamics and to test several policy scenarios.     

Benchmarking physician practice patterns with DEA: A multi-stage approach for cost containment

Physician practice patterns in a Health Maintenance Organization (HMO) are analyzed using single and multi-stage applications of Data Envelopment Analysis (DEA). Best practice (BP) patterns are identified, which can serve as benchmark targets for inefficient physicians. Results suggest three health policy — resource utilization control strategies:

1. If managed care organizations could motivate primary care physicians to adopt the practice styles of the best practice primary care physicians, substantial clinical resource savings could be achieved, ranging from 12% to over 30% in the HMO that is the focus of this study;
2. some specialists who practice as primary care physicians (PCPs) provide more efficient care than some general practitioner PCPs, modifying the current perception that reducing specialists is the most effective way to achieve low cost practice patterns; and
3. groups of physicians in the HMO exhibit different resource use patterns, which may present opportunities to manage high cost groups as another path to contain costs.

The results suggest specific new paths which may prove effective at reducing health care costs within managed care organizations, the health care providers most likely to dominate the U.S. health system in the future. A multi-stage DEA technique is used to locate specific types of inefficient physicians. Methods to test the clinical viability of using DEA to realize the potential cost savings and extensions of this research are discussed.     

On generalized semi-infinite optimization of genetic networks

Since some years, the emerging area of computational biology is looking for its mathematical foundations. Based on modern contributions given to this area, our paper approaches modeling and prediction of gene-expression patterns by optimization theory, with a special emphasis on generalized semi-infinite optimization. Based on experimental data, nonlinear ordinary differential equations are obtained by the optimization of least-squares errors. The genetic process can be investigated by a time-discretization and a utilization of a combinatorial algorithm to detect the stability regions. We represent the dynamical systems by means of matrices which allow biological-medical interpretations, and by genetic or new gene-environment networks. For evaluating these networks we optimize them under constraints imposed. For controlling the connectedness structure of the network, we introduce GSIP into this modern application field which can lead to important services in medicine and biotechnology, including energy production and material science.      

Competition for limited critical resources and the adoption of environmentally sustainable strategies

We develop a game-theoretical methodology that incorporates competition for limited resources to explicitly model a firm's valuation and, hence, its decision whether to adopt environmentally sustainable strategies (e.g., recycling programs to replace limited natural resources, alternative technologies). Even if switching to environmentally sustainable alternatives proves too expensive for individual firms, or resource costs are expected to remain low, we show that competition for resources would still push firms to incur switching costs as they become more environmentally sustainable. Using a sample of firm-level data from the KLD database which includes firms' sustainability policies, we find empirical support that competition for resources is positively correlated with a firm's adoption of environmental strategies. Tests that use the Chinese government's 2010 rare-earth supply suspension as an exogenous shock to competition for limited resources suggest a causal interpretation for our finding.     

A Goal Programming Model for Staff Scheduling at a Telecommunications Center

In this paper, a mathematical model is developed to solve a staff scheduling problem for a telecommunications center. Currently, weekly schedules are manually produced. The manual nature of the process and the large number of constraints and goals lead to a situation where the used schedules are both inefficient and unfair. A zero-one linear goal programming model is suggested to find an optimized cyclical schedule. The center objectives as well as the engineers’ preferences are taken into account. The developed model had to produce balanced schedules that provide the required coverage while satisfying fairness considerations, in terms of weekends off, working night shifts, isolated days on, and isolated days off. A staffing analysis and mathematical properties have been developed to find the optimal parameters of the staff scheduling model. A 6-week scheduling period has been suggested instead of the current weekly period. Work patterns have been suggested to improve schedules quality. These work patterns have been mathematically formulated as a set of soft constraints. The suggested mathematical model has been implemented using Lingo software. The optimal cyclical schedule has been found. It significantly increases both efficiency and staff satisfaction. The suggested approach can be used for any similar staff scheduling problem.     

Lower bounds for the economic lot scheduling problem using aggregation

The problem considered in this paper is to choose cyclical production patterns for several products which are produced on a common production facility. By aggregating data, dynamic programming can be used to obtain lower bounds which, in general, are much stronger than those obtained when the capacity constraint is not recognized.Lower bounds are of interest when generating possible solutions and also in connection with branch-and-bound methods.     

From design-based research to re-sourcing ‘in the wild’: reflections on studies of the co-evolution of mathematics teaching resources and practices

This commentary paper looks across the studies of the design and use of mathematics teaching resources included in this issue. It analyses everyday and educational notions of resource; particularly how usage of that term varies across the papers. Key characteristics of each study are identified and the studies are organized into five broad groups representing different lines of investigation of resource design and use. Across the studies, the broad notion of appropriation is influential in conceptualizing user/tool relations, with the instrumental/documentational approach particularly prominent, although close inspection shows that researchers draw on this in different ways. A majority of the studies relate to professional development interventions in a context of large-scale reform efforts, offering insights into a range of approaches to providing practical support for teacher appropriation of resources. One study investigates the resource systems established by ordinary teachers: alongside other research, this highlights the challenges of a re-sourcing approach in which teachers collaborate to curate a localized resource system, and points to conditions which are conducive to the success of such efforts.     

COMBINING SOCIAL CAPITAL AND TECHNOLOGY FOR DROUGHT RESILIENCE IN AGRICULTURE

In water‐scarce regions of the world, water‐saving technology adoption augments farm productivity. But so does social capital. In this paper, the issue of ensuring livelihood for farmers through the combined use of social capital and water‐saving technology is modeled in the context of repeated droughts. The model presented here derives optimal resource conservation and accumulation strategies when the farmer must ensure minimum consumption during a set of repeated drought events in the future. Findings indicate that the path to drought resilience presents a complex trade‐off between accumulating one form of capital over another and is influenced by farmers’ wealth and water endowments, level of risk associated with the repeated droughts and the duration of the repeated drought event that the farmer plans to survive. A higher risk of repeated droughts leads to an increase in groundwater conservation efforts but delays technology adoption. Lower water endowments may also delay adoption and reduce social capital, however, a lower social capital or a slow rate of its growth is not a hindrance to adopting water‐saving technology earlier. Finally, social capital evolves to higher levels when farmer is simultaneously faced with a higher level of risks and a longer span of drought events.     

Using the Hill cipher to teach cryptographic principles

The Hill cipher is the simplest example of a block cipher, which takes a block of plaintext as input, and returns a block of ciphertext as output. Although it is insecure by modern standards, its simplicity means that it is well suited for the teaching of such concepts as encryption modes, and properties of cryptographic hash functions. Although these topics are central to modern cryptography, it is hard to find good simple examples of their use. The conceptual and computational simplicity of the Hill cipher means that students can experiment with these topics, see them in action, and obtain a better understanding that would be possible from a theoretical discussion alone. In this article, we define the Hill cipher and demonstrate its use with different modes of encryption, and also show how cryptographic hash functions can be both designed and broken. Finally, we look at some pedagogical considerations.