Understanding manager resistance to blockchain systems

Blockchain technology has received much attention in the media and there is an increasing interest amongst organizations within financial services due to the potential benefits. As blockchain-based systems are a nascent technology, the requirements of the technology need to be understood, to allow blockchain systems to be successfully integrated within financial service organizations. There are gaps in academic research in understanding how managers evaluate the value of a blockchain-based system. This study develops a model to explain manager resistance to implementing blockchain-based systems in financial services organizations. This research advances the theoretical understanding of managers’ perspectives on blockchain-based systems and models their resistance to blockchain technology.     

Sampling from spatial databases

This paper deals with techniques for obtaining random point samples from spatial databases. We seek random points from a continuous domain (usually ²) which satisfy a spatial predicate that is represented in the database as a collection of polygons. Several applications of spatial sampling (e.g. environmental monitoring, agronomy, forestry, etc) are described. Sampling problems are characterized in terms of two key parameters: coverage (selectivity), and expected stabbing number (overlap). We discuss two fundamental approaches to sampling with spatial predicates, depending on whether we sample first or evaluate the predicate first. The approaches are described in the context of both quadtrees and R-trees, detailing the sample first, acceptance/rejection tree, and partial area tree algorithms. A sequential algorithm, the one-pass spatial reservoir algorithm is also described. The relative performance of the various sampling algorithms is compared and choice of preferred algorithms is suggested. We conclude with a short discussion of possible extensions.     

Cybernetic Risk Analysis

The Pearl Harbor case study reveals that risk analysis failure may be caused by any of a number of factors. However, the most important variables are system load, gain, lead time, and lag time. The dynamics of such cybernetic systems analysis constitute an important aspect in this regard. Four different risk management strategies, or organization designs, have been proposed in this paper. Each has a unique combination of the imputed variables and each has a unique cause of surprise, risk analysis failure, and crisis.     

On the effectiveness of cognitive feedback from an interface agent

The objective of this study was to determine the impact of task information (TI) provided by an interface agent during the idea evaluation and integration step of the problem formulation stage of the problem solving process. The effectiveness assessment was based on solving diagnostic decision problems in the domain of complex industrial machinery. Ten domain experts participated in this study. Decision support was provided by a case-based reasoning system. Findings suggest that TI provided by the interface agent had no effect on the decision maker's performance, nor on the associated cognitive effort. However, a verbal protocol analysis revealed that the ten subjects used the interface agent to verify their decision processes. The results and their implications are discussed with respect to current findings in the area of decision support systems.     

Adaptive Build-up and Breakdown of Trust: An Agent Based Computational Approach

This article employs Agent-Based Computational Economics (ACE) to investigate whether, and under what conditions, trust is viable in markets. The emergence and breakdown of trust is modeled in a context of multiple buyers and suppliers. Agents develop trust in a partner as a function of observed loyalty. They select partners on the basis of their trust in the partner and potential profit, with adaptive weights. On the basis of realized profits, they adapt the weight they attach to trust relative to profitability, and their own trustworthiness, modeled as a threshold of defection. Trust and loyalty turn out to be viable under fairly general conditions.     

自组织建模方法和GDP增长模型研究

经济系统的复杂性决定了经济变动及影响因素解释的困难性。本文阐述了一种经济系统复杂性研究的有效方法-自组织建模方法,同时应用此方法建立一个解释我国GDP增长的自组织模型,分析影响我国经济增长的主要因素,并在此基础上提出相应的对策思路。     

生存理性如何影响农户的差别化生产

在食品安全威胁下,农户重新定义了“为自家生产”和“为市场生产”的差别化生产行为。基于经济理性行为假设认为农户存在以确保自家食品安全为动机的生存理性。根据在5省区收集的827份农村入户调研数据,对农户差别化生产行为进行具体分析,描述了差别化生产行为总体特征,并测量农户食品安全自我保护意识、威胁感知程度和信息渠道等因素。运用Probit模型验证了命题：以食品安全自我保护意识为特征的生存理性,支配了农户为确保自家消费安全而进行的差别化生产。     

Early Pregnancy Assessment Services in Australia: What psychosocial support is available? A qualitative study

ProblemWomen commonly experience emotional distress following miscarriage but do not receive the support they need from healthcare providers.BackgroundMiscarriage can result in psychological morbidity; however, appropriate support at the time of a miscarriage can lead to better psychological outcomes. Early Pregnancy Assessment Services (EPASs) are dedicated outpatient services considered the “gold standard” for miscarriage care. Little is known about the psychosocial support EPASs provide in Australia.AimsThe aim of this study was to explore the provision of psychosocial support in Australian EPASs.MethodsSemi-structured interviews were conducted with 29 purposively sampled key-informants from 13 EPASs. Interviews were audio-recorded, transcribed, and thematically analysed.FindingsConsiderable variation was found in how EPASs functioned and their provision of psychosocial support. Many services were co-located with antenatal services, run by doctors with limited experience and most did not offer any psychosocial training to staff specific to EPAS. Referrals for additional support were generally not offered for first trimester miscarriages, and follow-up typically focused on physical management rather than emotional wellbeing. All EPAS staff demonstrated a strong commitment to providing best possible care to women within their own clinical setting and acknowledged the need for improved psychosocial support.ConclusionThis study provides the first exploration of Australian EPASs’ provision of psychosocial support. It has shown that while health care professionals working in EPASs are dedicated to providing the best possible care to women within their clinical setting, psychosocial support is very limited and could be improved.     

Sensitivity,uncertainty, and decision analyses in the prioritization of research

The evaluation of hazards from complex, large scale, technologically advanced systems often requires the construction of computer implemented mathematical models. These models are used to evaluate the safety of the systems and to evaluate the consequences of modifications to the systems. These evaluations, however, are normally surrounded by significant uncertainties related to the uncertainty inherent in natural phenomena such as the weather and those related to uncertainties in the parameters and models used in the evaluation.

Another use of these models is to evaluate strategies for improving information used in the modeling process itself. While sensitivity analysis is useful in defining variables in the model that are important, uncertainty analysis provides a tool for assessing the importance of uncertainty about these variables. A third complementary technique, is decision analysis. It provides a methodology for explicitly evaluating and ranking potential improvements to the model. Its use in the development of information gathering strategies for a nuclear waste repository are discussed in this paper.     

State of the Art in Risk Analysis of Workforce Criticality Influencing Disaster Preparedness for Interdependent Systems

The objective of this article is to discuss a needed paradigm shift in disaster risk analysis to emphasize the role of the workforce in managing the recovery of interdependent infrastructure and economic systems. Much of the work that has been done on disaster risk analysis has focused primarily on preparedness and recovery strategies for disrupted infrastructure systems. The reliability of systems such as transportation, electric power, and telecommunications is crucial in sustaining business processes, supply chains, and regional livelihoods, as well as ensuring the availability of vital services in the aftermath of disasters. There has been a growing momentum in recognizing workforce criticality in the aftermath of disasters; nevertheless, significant gaps still remain in modeling, assessing, and managing workforce disruptions and their associated ripple effects to other interdependent systems. The workforce plays a pivotal role in ensuring that a disrupted region continues to function and subsequently recover from the adverse effects of disasters. With this in mind, this article presents a review of recent studies that have underscored the criticality of workforce sectors in formulating synergistic preparedness and recovery policies for interdependent infrastructure and regional economic systems.