Disaster risk and artificial intelligence: A framework to characterize conceptual synergies and future opportunities

Artificial intelligence (AI) methods have revolutionized and redefined the landscape of data analysis in business, healthcare, and technology. These methods have innovated the applied mathematics, computer science, and engineering fields and are showing considerable potential for risk science, especially in the disaster risk domain. The disaster risk field has yet to define itself as a necessary application domain for AI implementation by defining how to responsibly balance AI and disaster risk. (1) How is AI being used for disaster risk applications; and how are these applications addressing the principles and assumptions of risk science, (2) What are the benefits of AI being used for risk applications; and what are the benefits of applying risk principles and assumptions for AI-based applications, (3) What are the synergies between AI and risk science applications, and (4) What are the characteristics of effective use of fundamental risk principles and assumptions for AI-based applications? This study develops and disseminates an online survey questionnaire that leverages expertise from risk and AI professionals to identify the most important characteristics related to AI and risk, then presents a framework for gauging how AI and disaster risk can be balanced. This study is the first to develop a classification system for applying risk principles for AI-based applications. This classification contributes to understanding of AI and risk by exploring how AI can be used to manage risk, how AI methods introduce new or additional risk, and whether fundamental risk principles and assumptions are sufficient for AI-based applications.     

Artificial Intelligence for Natural Hazards Risk Analysis: Potential,Challenges, and Research Needs

Artificial intelligence (AI) methods have seen increasingly widespread use in everything from consumer products and driverless cars to fraud detection and weather forecasting. The use of AI has transformed many of these application domains. There are ongoing efforts at leveraging AI for disaster risk analysis. This article takes a critical look at the use of AI for disaster risk analysis. What is the potential? How is the use of AI in this field different from its use in nondisaster fields? What challenges need to be overcome for this potential to be realized? And, what are the potential pitfalls of an AI-based approach for disaster risk analysis that we as a society must be cautious of?     

策略延迟下众筹项目的定价和激励决策

本文研究了投资者的策略延迟行为对众筹项目的定价以及激励决策的影响。策略延迟是指投资者在投资过程中自动按照估值在相应阶段投资,并且部分投资者会刻意延迟投资来搭便车的行为。本文采用了一个两阶段模型来刻画投资者的投资行为,并进一步对比序列到来模式（投资者没有策略延迟）与同时到来模式（投资者有策略延迟）中的贝叶斯均衡。研究结果表明,当发起人采用价格激励的方式提高成功率时,投资者的策略延迟行为可能会影响最优的激励策略。当存在固定目标约束时,如果投资者没有策略延迟行为,发起人应该激励前期投资者,通过弥补他们等待成本的方式提高成功率;反之如果投资者出现策略延迟行为,对项目估值较高的投资者会自动在前期投资并且愿意承受更高的价格,此时发起人应该反过来激励后期投资者。当不存在目标约束时,不论投资者是否有策略延迟行为,发起人都应该始终激励前期投资者以获得更高的成功率以及期望收益。     

Investigating investment decisions in equity crowdfunding: The role of projects' intellectual capital

The study aims to investigate the signalling role played by the intellectual capital of entrepreneurial projects towards crowdfunders. The study argues that information on; the intellectual capital of entrepreneurial projects posted on equity crowdfunding platforms can be perceived by external small investors or crowdfunders as signals of the venture's quality and can induce them to invest. By leveraging on the role of signalling theory in the mitigation of information asymmetries, the study argues that the intellectual capital of projects looking for equity crowdfunding is a powerful signal that positively affects the investment decisions of crowdfunders. Three components of entrepreneurial projects' intellectual capital – human, structural, and relational capital – are considered as factors affecting the success of equity crowdfunding campaigns, measured in terms of funding collected and the number of investors. The findings reveal that relational capital positively affects the investment decisions of equity crowdfunders and thus explains the success of equity crowdfunding campaigns. Factors related to human capital and structural capital have a positive impact on investment decisions, but only to a limited extent. This study provides valid implications for entrepreneurs, platform managers, and policy-makers/authorities.     

Why do users trust algorithms? A review and conceptualization of initial trust and trust over time

Algorithms are increasingly playing a pivotal role in organizations' day-to-day operations; however, a general distrust of artificial intelligence-based algorithms and automated processes persists. This aversion to algorithms raises questions about the drivers that lead managers to trust or reject their use. This conceptual paper aims to provide an integrated review of how users experience the encounter with AI-based algorithms over time. This is important for two reasons: first, their functional activities change over the course of time through machine learning; and second, users' trust develops with their level of knowledge of a particular algorithm. Based on our review, we propose an integrative framework to explain how users’ perceptions of trust change over time. This framework extends current understandings of trust in AI-based algorithms in two areas: First, it distinguishes between the formation of initial trust and trust over time in AI-based algorithms, and specifies the determinants of trust in each phase. Second, it links the transition between initial trust in AI-based algorithms and trust over time to representations of the technology as either human-like or system-like. Finally, it considers the additional determinants that intervene during this transition phase.     

The knowledge management of micro-firms in the crowd: key challenges for successful operations*

Abstract

Crowdfunding platforms are increasingly being used by small and micro-firms to fund the development and initial promotion of their new products. The transition from a crowdfunding campaign to the subsequent operational phase is critical to successfully fulfil the expectations of the backers who supported the micro-firm and expect to receive the new product. This paper analyzes the main challenges that must be faced by micro-firms during this transition, adopting the perspective of knowledge management theory. Based on an exploratory case study analysis, the paper highlights the particularities of these knowledge management challenges in terms of knowledge diversity, dependence and novelty. Asymmetry, dispersion, synchronization, a lack of a common understanding and backer lock-in are the main knowledge-based challenges for the operations of micro-firms that use crowdfunding. Various theoretical and practical implications of the findings are offered.     

What do we loose when machines take the decisions?

This paper concerns the technical issues raised when humans are replaced by artificial intelligence (AI) in organisational decision making, or decision making in general. Such automation of human tasks and decision making can of course be beneficial through saving human resources, and through (ideally) leading to better solutions and decisions. However, to guarantee better decisions, the current AI techniques still have some way to go in most areas, and many of the techniques also suffer from weaknesses such as lack of transparency and explainability. The goal of the paper is not to argue against using any kind of AI in organisational decision making. AI techniques have a lot to offer, and can for instance assess a lot more possible decisions—and much faster—than any human can. The purpose is just to point to the weaknesses that AI techniques still have, and that one should be aware of when considering to implement AI to automate human decisions. Significant current AI research goes into reducing its limitations and weaknesses, but this is likely to become a fairly long-term effort. People and organisations might be tempted to fully automate certain crucial aspects of decision making without waiting for these limitations and weaknesses to be reduced—or, even worse, not even being aware of those weaknesses and what is lost in the automatisation process.

     

产品众筹中价格歧视策略的优化研究

产品众筹是一种常见的众筹形式,它要求企业为支持者提供创新型产品或服务作为回报。合理的定价策略是产品众筹的关键,本文分别从项目成功率和利润最大化角度研究价格歧视的优化问题。针对产品众筹全有或全无（All-or-Nothing,AoN）的机制下采用价格歧视策略时,价格差值和低价销售定额的最优决策问题。本文首先采用随机模型定义购买概率函数,分析支持者在购买过程中的影响因素;然后从项目支持者效用角度出发,应用两阶段模型讨论价格差值的相关影响因素,研究发现两级价格差值会受到级联效应、项目的特征以及支持者特征的影响。并且从支持者估值类型方向对基础模型进行了扩展,讨论了不同估值类型的支持者在不同价格差值范围内的选择行为;再则从项目的利润最大化角度出发讨论价格差值问题,研究发现价格差值受支持者数量和项目目标值的影响;最后通过计算相对利润函数解出最优低价销售定额的数量。     

预售众筹产品质量夸大行为及其预防措施分析

运用理论模型分析了预售众筹中创业者夸大产品质量的行为及其预防措施.首先,构建了预售众筹发起阶段与销售阶段的理论决策模型;其次,求解模型得到了创业者的最优众筹价格及向投资者承诺的产品质量,分析了创业者夸大产品质量的动机;再次,在此基础上设计了由保证金与信用约束组成的预防措施,分析了预防措施对创业者夸大产品质量行为的预防效果.研究结果表明:在无预防措施情形下,创业者会向投资者夸大产品质量以获得众筹成功与追求收益最大化;众筹平台收取保证金虽能对创业者夸大产品质量行为起到预防作用,但预防效果有限;增加信用约束能弥补保证金措施的缺点,提高预防措施的预防效果.最后,通过数值算例进一步阐述了理论模型所得到的相关结论.     

Applying Co‐occurrence Text Analysis with ALCESTE to Studies of Impression Management

This paper reviews the potential role of co‐occurrence text analysis using ALCESTE, a computerized text analysis program. Using an illustrative case study from the biometric industry, we demonstrate that this method offers a number of advantageous features, including the provision of visual outputs which are useful for interpreting results, the ability to study longitudinally the effectiveness of impression management at the inter‐organizational level of analysis and the possibility of studying large textual data sets without using predefined dictionaries. Meanwhile, key limitations of the method include its limited versatility, its tedious data‐cleaning process and its ineffectiveness in identifying the centrality or tonality of the discourse. Our overall conclusion is that the introduction and more widespread use of this method in management is timely, particularly for scholars interested in studying narrative fidelity and frame amplification.     

Leaders' impression management during organizational decline: The roles of publicity,image concerns,and incentive compensation

In this study, we develop and examine a model of leaders' impression management during organizational decline by elaborating on the roles of publicity, image concerns, and incentive compensation. We propose that the publicity of decline is an important antecedent of leaders' impression management during decline. We also examine how leaders' image concerns mediate this positive relationship. In addition, we consider the relative influence of incentive compensation and fixed compensation on the relationship between leaders' image concerns and their impression management during decline. Our results, based on a specially-designed management simulation game conducted with experienced Chinese managers, show that high publicity of decline elevates leaders' image concerns, which in turn increases their impression management during decline. In addition, incentive compensation strengthens rather than weakens the effects of leaders' image concerns on their impression management. We discuss the implications of leaders' impression management during organizational decline.     

AON众筹模式下产品线设计与信息发布策略研究

针对众筹模式下如何激励消费者投资以实现众筹项目成功的问题，从信息发布和产品线设计的角度，通过两阶段博弈的理论模型，考虑了AON（all-or-nothing）模式下众筹方采用顺序发布和同时发布两种不同信息发布方式时，产品线的菜单价格和质量设计。研究表明：在顺序发布策略下产品线的质量差异化程度依赖于消费者异质性程度和高价值消费者的比例，和传统模式下产品质量相比，当消费者异质性很大同时高保留价格消费者的比例很高时，产品线质量差异和传统模式相同；当消费者异质性较小并且高保留价格消费者的比例较低时，产品线质量差异更小；当消费者异质性较小而高保留价格消费者比例较高时，产品线质量差异更大；而在同时发布策略下，产品线质量的差异化程度和传统模式相同，但价格差异与传统模式相比更大；相对于顺序发布策略而言，同时发布策略下由于极大程度的降低了消费者可能搭便车倾向，企业可以获取更多收益。这些结果将有助于采用AON众筹模式的企业在不同信息框架下做出最优的产品线质量设计和定价决策。     

基于演化博弈的农村环境治理众筹机制研究

农村环境治理已经成为乡村振兴战略的一项重要任务,仅依靠政府单一治理主体无力应对全国70多万行政村的环境治理需求,发挥农户治理主体作用成为一种新的农村环境治理机制。本文将众筹模式引入环境治理中,采用演化博弈理论,在公平贡献和利他偏好两种情景下,分析有限理性农户决策行为演化动态,研究风险发生概率、亲环境偏好、团体效用、初始财富、融资目标、众筹份额等对环境治理众筹融资成功的影响。研究发现：公平贡献和利他偏好两种情形下,考虑环境污染给农户初始财富带来风险时,当初始财富期望损失、团体效用与声誉损失之和大于参与众筹的支出时,参与环境治理众筹成为农户的演化稳定策略。风险发生的概率越大、初始财富越多、参与众筹获得的群体认同价值越大、不参与时声誉损失越大,越有利于参与众筹策略成为农户的演化稳定策略。而在公平贡献模式下,当初始财富期望损失、团体效用与声誉损失之和小于参与众筹的支出时,农户群体中会出现不参与和不参与环境治理众筹两种策略共存的稳定均衡状态。通过对农户参与环境治理众筹成为演化稳定策略的内在机理分析,为农村环境治理众筹融资实践提供决策参考。     

Hitting the Target…but Missing the Point: Resolving the Paradox of Strategic Transition

Many firms are undertaking a strategic shift from cost leadership (through process management) to differentiation based on radical product innovation. Success in such transitions has been mixed, as have findings on the role of performance measurement and management in the process. This study explores the challenges of managing this transition, with specific focus on the role of performance metrics. Conventional wisdom indicates that top management can use metrics - measures, standards and rewards - to communicate new directions and priorities. Based on findings reported in this paper, this approach is found to be potentially fatally flawed when applied to a situation where both the corporate goals and the means of achieving these goals have changed. Using detailed data drawn from a multi-level analysis of a major international corporation undertaking such a strategic shift, this study explores the process by which metrics are formed and deployed, and the impact of this process on the ability of the firm to successfully achieve the change. Using measures such as the percentage of sales from new products, top management in the case study had the impression that the strategy was being successfully carried out by the various operating divisions. However, radical innovation (the desired result) had been replaced by incremental innovation. This study identifies the reasons for this situation. A major finding is that the performance measurement and management system can both allow and conceal this failure. Firms trying to significantly change their strategic directions must change their selection of performance metrics to focus less on the intended outcomes and more on the means by which these outcomes are to be achieved.     

Open about organizational failure: A communication perspective on postmortem impression management

Being open about failure as an entrepreneur is an increasingly common practice in and beyond startup communities, for example by proactively and strategically crafting public statements to frame subsequent failure conversations. Combining an impression management perspective with an analysis of communicative genres of failure narratives, we empirically investigate postmortem statements of failed entrepreneurs. Shifting the discourse from the (content of the) failure narratives towards considering its broader communicative context, we show how genres emerge from patterns of failure narratives and impression management strategies. Our analysis suggests that subgenres of postmortem statements represent different forms of openness about failure, and some subgenres in particular contribute to establishing an ‘organizational afterlife’ as a potentially long-lasting impression management strategy.     

在线投资行为的本地偏好:基于在线融资市场的实证研究

传统的市场交易存在本地偏好，交易双方的地理位置趋同。然而，在线众筹平台打破了空间局限，地理位置的影响理应比传统市场小得多。为此提出三个问题：（1）众筹投资行为是否存在本地偏好？以及不同层次本地偏好有何差异？（2）本地偏好对投资行为和项目融资效果的影响；（3）对投资者的本地偏好进行机理分析和理论解释。以Kickstarter为研究对象，从国家级、区域级以及微观三个层次，分别构建了本地偏好模型以分析用户投资行为。研究表明，众筹项目的投资行为存在本地偏好，投资者偏好投资距离较近的项目，并且三个层次的本地偏好呈现不同模式。戏剧类项目的投资意愿受本地偏好的影响最强烈，其次是食品类，影响最弱的是游戏类。对于投融双方的距离来说，戏剧类项目的平均距离最小，为1474公里；而游戏类项目的平均距离最大，达到4624公里。众筹投资的本地偏好具有叠加效用，即融资者在异地进行融资的话，可以获得更高的融资成功率。最后，从信息传递理论、心理学、行为学等角度解释了本地偏好存在的原因以及影响。本文丰富了互联网金融研究以及用户行为模式研究，从投资行为角度为众筹项目研究和实践提供了新视角。     

The Impact of Quality Management Practices on Performance and Competitive Advantage

As decision makers become more involved in implementing Total Quality Management, questions are raised about which management practices should be emphasized. In this exploratory investigation of the relationship of specific quality management practices to quality performance, a framework was constructed. It focuses on both core quality management practices and on the infrastructure that creates an environment supportive of their use. In addition, it incorporates two measures of quality performance and their role in establishing and sustaining a competitive advantage. Path analysis was used to test the proposed model, with multiple regression analysis determining the path coefficients, which were decomposed into their various effects. Weak linkages were eliminated. The trimmed model indicated that perceived quality market outcomes were primarily related to statistical control/feedback and the product design process, while the internal measure of percent that passed final inspection without requiring rework was strongly related to process flow management and to statistical control/feedback, to a lesser extent. Both measures of quality performance were related to competitive advantage. Important infrastructure components included top management support and workforce management. Supplier relationships and work attitudes were also related to some of the core quality practices and quality performance measures. The results were interpreted in light of Hill's concept of order winners and order qualifiers and Garvin's eight dimensions of quality. They indicate that different core quality management practices lead to success in different dimensions of quality, and that those dimensions function differently as order winners and order qualifiers.     

Anesthesia Patient Risk: A Quantitative Approach to Organizational Factors and Risk Management Options

The risk of death or brain damage to anesthesia patients is relatively low, particularly for healthy patients in modern hospitals. When an accident does occur, its cause is usually an error made by the anesthesiologist, either in triggering the accident sequence, or failing to take timely corrective measures. This paper presents a pilot study which explores the feasibility of extending probabilistic risk analysis (PRA) of anesthesia accidents to assess the effects of human and management components on the patient risk. We develop first a classic PRA model for the patient risk per operation. We then link the probabilities of the different accident types to their root causes using a probabilistic analysis of the performance shaping factors. These factors are described here as the "state of the anesthesiologist" characterized both in terms of alertness and competence. We then analyze the effects of different management factors that affect the state of the anesthesiologist and we compute the risk reduction benefits of several risk management policies. Our data sources include the published version of the Australian Incident Monitoring Study as well as expert opinions. We conclude that patient risk could be reduced substantially by closer supervision of residents, the use of anesthesia simulators both in training and for periodic recertification, and regular medical examinations for all anesthesiologists.     

An Examination of Procedural and Object-oriented Systems Analysis Methods: Does Prior Experience Help or Hinder Performance?*

Interest in object-oriented analysis (OOA) and object-oriented design (OOD) has expanded rapidly over the last several years. Proponents of OOA and OOD have called the shift to these methods “revolutionary” and have cited a number of impressive claims with respect to their use. However, empirical research investigating these claims remains in its infancy. Moreover, an examination of the literature reveals inconclusive and often conflicting results for OOA and OOD methods relative to traditional data and/or procedural techniques. This paper presents the results of an empirical study that examined both experienced and novice systems analysts using both procedural and object-oriented techniques. This research examined whether experience in using procedural methods helped or hindered performance using OOA and compared procedural and OOA methods on the subjective mental workload induced. A human problem-solving model adopted from Newell and Simon (1972) provided the theoretical framework for this study. Dependent variables include subjective mental workload, solution quality, time to perform task, and attitudinal measures. Although some of these dependent variables have been used in past research, we believe this is the first time that subjective mental workload (SMW) has been examined in an IS context. Our results indicate that both novice and experienced subjects demonstrate higher SMW when using OOA. In addition, as a group, novices prefer object-oriented techniques and find these techniques easier as compared to experienced subjects.     

Equity Crowdfunding: The Influence of Perceived Innovativeness on Campaign Success

This paper examines the impact of perceived innovativeness on the success of equity crowdfunding campaigns. Building on the investor perspective, we hypothesize a positive impact of perceived innovativeness on the campaign outcome. Our database covers 191 campaigns launched in France on different platforms, drawing on over 2,000 individual assessments of the perceived innovativeness of the start-ups involved, carried out by 176 participants with diverse backgrounds. We find support for our hypothesis from the investor perspective in that highly innovative projects attract more crowd investors and, in turn, raise more capital. We contribute to the understanding of how the crowd makes investment choices.