唧唧堂：MISQ管理信息系统季刊2020年3月刊论文摘要
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特刊：新兴数字世界的复杂性与信息系统研究
在这个日益数字化的世界里，复杂性是无处不在的。全球数字基础设施、社交媒体、物联网等由数字支持的网络和生态系统，通过在个人、技术工件、流程、组织和机构之间建立超连接和相互依赖，加剧了复杂性。复杂性会影响人类各方面的能力和经验。个人和组织求助于数字化解决方案以应对数字化带来的邪恶问题。在这篇文章中，我们讨论了复杂性科学的关键理论和方法，并说明了在复杂的社会技术系统中出现的新的IS研究挑战和机遇。我们还概述了本次特刊中的五篇文章。这些文章说明了研究人员如何使用复杂性科学的理论和方法去研究新兴数字世界的邪恶问题，还说明了研究人员如何利用IS环境的独特性来产生新的见解，从而为复杂性科学做出贡献。
特刊论文：
1. 数字化过程中的漂移动力学
本文利用模拟方法建立了关于数字化过程的复杂性和阶段变化的新理论。我们知道数字化过程会漂移（随着时间渐进地改变）。我们通过渐进地添加和删除代表该过程的网络的边缘来模拟这种现象。模拟结果表明，增量变化会导致自组织的临界状态。当接近这种状态时，进一步的增量变化会导致过程复杂性的非线性爆发和过程结构的显著变化。数字技术可以被设计和用来影响这些变革性阶段变化的可能性和严重性。例如，具有自适应规划的系统容易发生阶段性变化，而具有确定性规划的系统则不会。我们使用模拟产生了一套关于数字化影响的理论命题，这些理论命题将在实证研究中得到验证。
This paper uses a simulation to build new theory about complexity and phase change in processes that are supported by digital technologies. We know that digitized processes can drift (change incrementally over time). We simulate this phenomenon by incrementally adding and removing edges from a network that represents the process. The simulation demonstrates that incremental change can lead to a state of self-organized criticality. As the process approaches this state, further incremental change can precipitate nonlinear bursts in process complexity and significant changes in process structure. Digital technology can be designed and used to influence the likelihood and severity of these transformative phase changes. For example, the simulation predicts that systems with adaptive programming are prone to phase changes, while systems with deterministic programming are not. We use the simulation to generate a set of theoretical propositions about the effects of digitization that will be testable in empirical research.
参考文献：Pentland B. T., Peng L., Kremser W. and Hrem T. (2020). The Dynamics of Drift in Digitized Processes. MIS Quarterly 44(1): 19-47.
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2. 驯化搜索匹配的复杂性：数字平台上的双边推荐系统
数字多边平台的多个边具有不同且不断发展的目标、偏好和约束，我们将其作为复杂的自适应业务系统(CABS)进行研究。CABS具有不可减少的不确定性，导致了agent与增值事务之间的复杂搜索匹配问题，这是传统的数据采集和处理方法无法解决的。本文提出了一种基于推荐系统的方法，通过允许agent在系统中协同进化和学习来驯化系统的复杂性。我们提出了一种新的双边推荐系统框架，该框架考虑了平台两边的涌现性，能够适应环境的变化进而影响agent。基于当前流行的基于网络的教育平台，我们建立了一个基于agent的仿真模型来研究这个复杂的系统，并验证了我们的假设。我们的结果显示了双边推荐系统在处理复杂搜索匹配问题的价值。最后，我们讨论本文对信息系统和复杂性科学研究的意义。
We study digital multisided platforms as complex adaptive business systems (CABS) where multiple sides have different and evolving objectives, preferences, and constraints. CABS are characterized by irreducible uncertainty, which cannot be reduced by the traditional approaches of collecting and processing data. Irreducible uncertainty in the system gives rise to a complex search matching problem between agents and value enhancing transactions. This paper presents a recommender systems-based approach for taming the complexity by allowing agents to coevolve and learn in the system. We propose a novel two-sided recommender system framework, which considers emergence on both sides of the platform and adapts to the changing environment to influence agents. An agent-based simulation model is developed based on popular internet-based educational platforms to study this complex system and test our hypotheses. Our results show the value of a two-sided recommender system to tame complex search matching in platforms. We discuss implications for information systems and complexity science research.
参考文献：Malgonde O., He Z., Padmanabhan B. and Limayem M. (2020). Taming Complexity in Search Matching: Two-Sided Recommender Systems on Digital Platforms. MIS Quarterly 44(1): 49-84.
3. 数据业务战略的组织复杂性：一个配置视角
企业应如何配置组织能力以在复杂的数字环境中获得竞争优势? 为了回答这个问题，我们研究了数字环境中企业的配置情况。我们采用配置视角并结合模糊集定性比较分析来解释关键的数字和非数字能力在产生绩效时的复杂非线性关系。通过这种方法，我们将注意力从单个功能转移到功能的配置，以更好地理解IT在数字世界中的复杂角色。我们的分析使用了美国医疗、教育、制造和服务行业的376个组织的罕见和独特的数据集，揭示了三个关键发现。首先，IT支持的信息分析功能对于实现高绩效配置来说既不必要也不充分；然而，它是配置的重要组成部分，可以扮演多方面的角色，在某些场景中起支持作用，在某些场景中又会不起作用或起反作用。其次，我们记录了从六种组织能力之间复杂的非线性交互中产生的一些简约配置。有趣的是，这些配置通常具有同构结构，可以同时产生高财务绩效和高客户绩效。最后，高绩效与非高绩效配置的结构不同，这表明了支持组织绩效的因果关系的不对称观点。总之，这些发现为数字业务战略复杂性理论的进一步研究提供了启示，并为管理者将数字业务战略视为IT和组织能力的配置并重新设计提供了参考。
How should firms configure organizational capabilities to achieve competitive advantage in complex digital environments? To answer this question, we investigate parsimonious configurations for high firm performance in digital environments characterized by organized complexity. We adopt a configurational perspective accompanied by a fuzzy-set qualitative comparative analysis (fsQCA) to explicate complex nonlinear relationships among key digital and non-digital capabilities in the form of conjunction, equifinality, and asymmetry in producing the outcome. With this approach, we shift attention from individual capabilities to configurations of capabilities to develop a better understanding of the complex role of IT in the digital world. Our analyses, using a rare and unique dataset of 376 observations for organizations in healthcare, education, manufacturing, and service sectors in the United States, reveal three key findings. First, IT-enabled information analytics capability alone is neither necessary nor sufficient in any configuration for high performance; however, it is an important component of the configurations in which it plays multifaceted roles varying from an enabling role in some contexts, to no role or a counterproductive role in other contexts. Second, we document a few parsimonious configurations emergent from complex nonlinear interactions among six organizational capabilities. Interestingly, these configurations often have an isomorphic structure that produces both high financial performance and high customer performance simultaneously. Third, the structures of configurations for high performance differ from those of not-high performance, suggesting an asymmetric view of causality that underpins organizational performance. Together, the findings provide implications for further research on complexity theory in digital business strategy, and for managers to view and redesign digital business strategy as configurations of IT and organizational capabilities.
参考文献：YoungKi P. and Mithas S. (2020). Organized Complexity of Digital Business Strategy: A Configurational Perspective. MIS Quarterly 44(1): 85-127.
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4. 信息系统架构的演变：基于agent的仿真模型
信息系统(IS)架构是组织的IS组件及其依赖关系的集合。理解IS架构的演变过程以及预期结果对研究和实践都是一个相当大的挑战。IS架构的演变通常会服务于本地参与者的需求，但为了让本地和短期的IS投资能够符合企业范围和长期的发展目标，管理层经常采用强制机制将企业范围的考虑强加于本地参与者。然而，组织是由大量异构的本地参与者形成的，这些参与者会根据他们自己的目标、规范和价值去行动，有时是相互冲突的。本研究提供了一个基于理论的仿真模型，一方面以制度理论为基础去模拟强制、规范和模仿这三种制度压力的不同组合，另一方面以复杂自适应系统理论为基础去捕获IS架构的演变过程和结果。最后，我们概述了仿真实验的见解，然后基于仿真模型和理论见解讨论了研究和实践的意义。
Understanding how information systems (IS) architecture evolves and what outcomes can be expected from the evolution of IS architecture presents a considerable challenge for both research and practice. The evolution of IS architecture is marked by management’s efforts to keep local and short-term IS investments in line with enterprise-wide and long-term objectives, so they often employ coercive mechanisms to enforce enterprise-wide considerations on local actors. However, an organization is shaped by a multitude of heterogeneous local actors’ actions that pursue their own, sometimes conflicting, goals, norms, and values. This study offers a theory-informed simulation model that explores how IS architecture evolves and with what outcomes in various types of organizations. The simulation model is informed by institutional theory to capture various types of organizations that are characterized by different combinations of coercive, normative, and mimetic pressures, and by complex adaptive systems theory to capture the emergent character of IS architecture’s evolution. First, we outline the insights from simulation experiments. Then, building on the simulation model and theoretical insights, we discuss implications for both research and practice.
参考文献：Haki K., Beese J., Aier S. and Winter R. (2020). The Evolution of Information Systems Architecture: An Agent-Based Simulation Model. MIS Quarterly 44(1): 155-184.
5. 数字化与平台组织逻辑的阶段转换：来自过程自动化行业的证据
本文基于复杂自适应系统(CAS)理论探索了一家自动化产品平台在1983年至2016年的数字化过程。我们的案例展示了组件和功能的深度数字化如何通过将平台连接到多个社会和技术环境并产生新的交互和信息交换来驱动复杂性。增加的连通性和动态性招致了意想不到和重要的变化，将平台推向一个以生态系统为中心的组织逻辑。CAS理论及其约束生成过程(CGPs)的概念被用来分析新的连接和交互是如何在平台组织中产生多层次和非线性变化的。我们提供两项主要贡献。首先，我们提供了一个关于产品平台数字化如何导致阶段变化的新颖的实证分析，并展示了在这一过程中作为CGPs的三种机制的中介作用：交互规则、设计控制和激励响应变化。其次，我们演示了数字驱动增长在实体产品平台上的多层次和递归性质。
This paper draws on complex adaptive systems (CAS) theory to explore the transformation of an analog automation product platform as it was infused with extensive and deepening digital capacities over a 40-year period. Our case demonstrates how the deepening digitization of components and functions drives complexity by connecting the platform to multiple social and technical settings and producing new interactions and information exchanges. The increased connectivity and dynamism invited unexpected and significant architectural and organizational shifts that moved the platform toward an ecosystem-centered organizing logic. CAS theory and its notion of constrained generating procedures (CGPs) are used to analyze how new connections and interactions produced a multilevel and nonlinear change in the platform organization. We offer two main contributions. First, we provide a novel empirical analysis of how product platform digitization leads to phase transitions and show the mediating role of three mechanisms in this process treated as CGPs: interaction rules, design control, and stimuli-response variety. Second, we demonstrate the multilevel and recursive nature of digitally driven growth in physical product platforms.
参考文献：Sandberg J., Holmstrm J. and Lyytinen K. (2020). Digitization and Phase Transitions in Platform Organizing Logics: Evidence from the Process Automation Industry. MIS Quarterly 44(1): 129-153.
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特刊：信息系统与分析在慢性病防治中的作用
慢性疾病在死亡原因和医疗成本负担中都占据主要地位，而信息系统和分析研究可以在提出创新的医疗战略和解决方案方面发挥关键作用。电子健康记录、可穿戴设备等的广泛使用以及AI等数据分析技术的发展也给慢性疾病管理的信息系统研究带来了新的机遇和挑战。在本文中，我们首先简要概述了慢性病管理中出现的新主题，比如在线健康社区和健康社交媒体分析。然后，我们利用了一个连接系统、数据和人的框架，为这一领域的未来研究提供一个路线图。最后，我们概述了本次特刊中的9篇文章，它们提供了不同的理论和方法论的角度，侧重于解决不同的问题，利用不同的数据源，并检查不同的慢性疾病，反映了利用信息系统和分析来管理和预防慢性病的丰富性和多面性。
特刊论文：
6. 慢性疾病患者重复再入院的轨迹：风险分层、特征分析和预测
由于护理质量、健康结果和经济问题，复发性、计划外再入院的问题已经成为全世界的一个挑战。预测频繁的、可预防的再入院和理解相关的影响因素是一个正在被广泛研究的关键问题。然而，很少有研究进行了多病、异质患者群体的纵向风险分层、特征分析和预测。我们研究了慢性疾病患者的再入院风险在多次就诊中的变化，他们如何分层到不同的轨迹，以及这些轨迹与患者特征的关系。我们进一步研究了时不变和时变的协变量对再入院预测的影响。结果表明，纵向风险分层可以根据急诊护理的表现，根据不同的轨迹，早期识别特定的患者群体。我们提出的预测模型表现良好，并展示了轨迹建模方法与先进的预测模型相结合的前景，可以进行纵向风险评估以应对再入院的挑战。本研究的方法和见解可推广到其他重要的信息系统问题。
The problem of recurrent, unplanned readmissions, where some patients return shortly after discharge from the hospital and are readmitted for the same or a related condition, has become a challenge worldwide due to care quality, health outcomes, and financial concerns. Predicting frequent, preventable readmissions and understanding the contributing factors is a critical problem that is being widely studied. However, few studies have examined longitudinal risk stratification, profiling, and prediction of multi-morbid, heterogeneous patient populations. We examine how readmission risk may progress over multiple emergency department visits of chronic disease patients, their early stratification into distinct trajectories with related frequencies, and the relationship of these trajectories to patient characteristics. We further extend this analysis to investigate the impact of time-stable and time-varying covariates in predicting future readmission conditional on latent class membership. Results indicate that longitudinal risk stratification can enable early identification of specific patient groups following distinct trajectories based on their presentation for emergency care. Prediction models that incorporate latent classes perform well and demonstrate the promise of trajectory modeling methods combined with advanced prediction models for longitudinal risk assessment in addressing readmission challenges. The methodology and insights from this study are generalizable to other important Information Systems problems.
参考文献：Ben-Assuli O. and Padman R. (2020). Trajectories of Repeated Readmissions of Chronic Disease Patients: Risk Stratification, Profiling, and Prediction. MIS Quarterly 44(1): 201-227.
7. 慢性疾病管理：IT和分析如何通过护理临时替代来创造医疗保健价值
治疗慢性疾病消耗了美国86%的医疗成本。医疗组织的传统重点是治疗慢性疾病的并发症，但信息技术(IT)和分析的进步可以帮助医生和患者管理和减缓慢性疾病的进展。我们引入了护理临时替代(TDC)的概念，即利用IT和分析技术来识别出对患者进行干预的时机来替代目前较为滞后的干预时间。我们使用来自美国佛蒙特州的45000名心脏代谢患者的四年数据来验证我们的假设，这些患者参与了一个护理项目。我们的研究包括四个组，它们的IT和分析水平逐渐提高：(1)non-PCMH，(2)PCMH，(3)DQS，(4)VHIE。研究发现，在实施后的第1年，DQS组的预防性程序的使用显著增加，在第2年和第3年的增加更加明显，而VHIE组的增加甚至更大。随着预防性程序使用的增加，急诊部门的使用率下降，VHIE组比DQS组下降更明显。第2年，DQS和VHIE组的总医疗成本下降，VHIE组的下降幅度大于DQS组。第3年，血红蛋白A1c (HbA1c)水平的医疗结果指标在统计学上显著降低，VHIE组较DQS组下降幅度更大。
The treatment of chronic diseases consumes 86% of U.S. healthcare costs. While healthcare organizations have traditionally focused on treating the complications of chronic diseases, advances in information technology (IT) and analytics can help clinicians and patients manage and slow the progression of chronic diseases to result in higher quality of life for patients and lower healthcare costs.
We build on prior research to introduce the notion of temporal displacement of care (TDC), in which IT and analytics create healthcare value by displacing the time at which providers and patients make interventions to improve healthcare outcomes and reduce costs. We propose that healthcare value is created by strategic actions taken at specific points-in-time during the treatment process. Our theoretical development identifies TDC mechanisms through which IT and analytics displace later high cost interventions in favor of earlier preventative procedures.
We test our hypotheses using four years of data on 45,000 cardio-metabolic patients from the U.S. state of Vermont, which implemented a Patient-Centered Medical Home (PCMH) program. Our study includes four cohorts with increasing levels of IT and analytics use: (1) non-PCMH practices, (2) PCMH practices with basic IT systems installed, (3) practices that completed data quality sprints (DQS) to increase use of IT systems, and (4) practices that use analytics through the Vermont Healthcare Information Exchange (VHIE).
Our results provide insights into how TDC effects develop over time. In Year 1 after implementation, the DQS cohort demonstrates a marked increase in the use of preventative procedures such as eye exams and neuropathy screenings, the increase becomes more pronounced in Years 2 and 3, and the increase is even greater for the VHIE cohort. As the use of preventative procedures increases, emergency department utilization decreases, with a more pronounced decrease for the VHIE cohort than the DQS cohort. By Year 2, the DQS and VHIE cohorts experience a decrease in total healthcare costs, with a greater decrease for the VHIE cohort than the DQS cohort. By Year 3, the healthcare outcomes indicator of Hemoglobin A1c (HbA1c) level is statistically significantly lower, with a greater decrease for the VHIE cohort than the DQS cohort. The increased use of low-intervention healthcare treatments earlier in the process leads to a decrease in overall healthcare costs, which then leads to an improvement in healthcare indicators.
参考文献：Thompson S., Whitaker J., Kohli R. and Jones C. (2020). Chronic Disease Management: How It and Analytics Create Healthcare Value through the Temporal Displacement of Care. MIS Quarterly 44(1): 227-256.
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8. 早上去YouTube呼唤我：用社交媒体治疗慢性疾病
视频社交媒体平台，如YouTube，提供了一种传递医疗信息的有效方式。很少有研究发现有证据支持的数字疗法，以改善患者检索医疗信息来管理慢性疾病的便利性。我们提出了一种跨学科的视角，将深度学习方法与信息系统和医疗信息研究中强调的主题相结合，以检查用户对视频中的医疗信息的参与。我们首先使用双向长短期记忆的方法来识别视频中的医学术语，然后根据其医学信息的高低对视频进行分类。然后，我们对视频数据进行主成分分析，以发现集体参与的三个维度：不参与、选择性注意力驱动的参与和持续性注意力驱动的参与。研究发现，医疗信息低的视频导致不参与，医疗信息高的视频很难保持持续性注意力驱动的参与。我们的研究为医疗从业者和决策者提供了一个微妙的理解，即用户如何参与视频格式的医疗信息。我们的研究还有助于加强当前的公共卫生实践，促进教育视频内容的规范性指导方针，使慢性病管理成为可能。
Video sharing social media platforms, such as YouTube, offer an effective way to deliver medical information. Few studies have identified evidence-backed digital therapeutics with technology-enabled interventions to improve the ease with which patients can retrieve medical information to manage chronic conditions. We propose an interdisciplinary lens that synthesizes deep learning methods with themes emphasized in Information Systems and Healthcare Informatics research to examine user engagement with encoded medical information in YouTube videos. We first use a bidirectional long short-term memory method to identify medical terms in videos and then classify videos based on whether they encode a high or low degree of medical information. We then employ principal component analysis on aggregate video data to discover three dimensions of collective engagement with videos: nonengagement, selective attention-driven engagement, and sustained attention-driven engagement. Videos with low medical information result in nonengagement; at the same time, videos with a greater amount of encoded medical information struggle to maintain sustained attention-driven engagement. Our study provides healthcare practitioners and policymakers with a nuanced understanding of how users engage with medical information in video format. Our research also contributes to enhancing current public health practices by promoting normative guidelines for educational video content enabling management of chronic conditions.
参考文献：Xiao L., Bin Z., Susarla A. and Padman R. (2020). Go to Youtube and Call Me in the Morning: Use of Social Media for Chronic Conditions. MIS Quarterly 44(1): 257-283.
9. 一个基于远程健康信息系统的智能哮喘管理的数据分析框架
哮喘是一种流行的呼吸道慢性疾病，影响着全球大部分人口。如果哮喘没有得到适当的控制，哮喘患者的生活质量可能会显著下降。为了促进更好的自我管理，哮喘专家和工程师开发了智能哮喘管理系统(SAM)。SAM提供的蓝牙吸入器可以收集患者每次使用救援吸入器的时间。这种详细的使用记录对研究呼吸器的使用模式至关重要，但在传统的临床试验中无法获得。利用SAM系统的患者监测能力，我们开发了一个数据分析框架，用于检测不正常的呼吸器使用情况。本文建立的新的统计模型可以处理从SAM系统收集的数据的关键特征，如环境因素对吸入器使用行为的异质性影响，以及患者重复日常操作所控制的相关结构。通过与各种基准测试方法的严格比较，我们的数据分析框架展示了令人满意的性能。此外，我们还深入讨论了我们对信息系统(IS)知识库的贡献，以及我们的分析框架对数据驱动的哮喘管理实践的实际影响。
Asthma is a prevalent respiratory chronic disease affecting a large portion of the global population. Patients diagnosed with asthma may experience significantly reduced quality of life if their asthma is not properly controlled. To facilitate better asthma self-management, asthma specialists and engineers have developed the smart asthma management system (SAM). This new health information system provides Bluetooth-enabled inhalers and collects time stamps of every rescue inhaler use. Such detailed inhaler usage logs, which are crucial for investigating patterns of inhaler usage, were not available in traditional clinical trials because clinical trials acquire data only periodically. Due to the low data collection resolution of clinical trials, quantitative asthma studies based on trial data have been focusing mainly on capturing the increasing trend in the number of rescue inhaler uses. Taking advantage of the patient monitoring capability of the SAM system, we developed a data analytics framework for detecting abnormal inhaler use that is out of the patient’s normal usage pattern. The new statistical model developed in this paper can address the key features of the data collected from the SAM system such as the heterogeneous impact of environmental factors on inhaler usage behavior and the correlation structure governed by the patient’s repetitive routines. We show the satisfactory performance of our data analytics framework through rigorous comparison with various benchmark methods. Furthermore, we give an in-depth discussion on our contribution to the information systems (IS) knowledge base and practical implications of our analytics framework to data-driven asthma management practice.
参考文献：Junbo S., Flatley Brennan P. and Shiyu Z. (2020). A Data Analytics Framework for Smart Asthma Management Based on Remote Health Information Systems with Bluetooth-Enabled Personal Inhalers. MIS Quarterly 44(1): 285-303.
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10. 基于机器学习和大型异构数据源的哮喘诱发因素和危险因素的综合分析
哮喘是一种常见的慢性疾病，影响着美国数百万人的健康。虽然哮喘不能治愈，但如果我们确定并了解引起哮喘恶化的诱发因素和危险因素，就可以控制哮喘。然而，这是具有挑战性的，因为这些因素是复杂和相互关联的，而且目前识别它们的主流方法存在局限性。近年来，大量异质性数据的可用性为哮喘的诱发因素和危险因素分析开辟了新的可能性。在这项研究中，我们将介绍一个数据驱动的分析框架，它适应和集成了多个先进的机器学习技术，能够(1)从社交媒体中获得自我报告的哮喘患者的特征，(2)集成和重用来自多个开放源的高度异构的数据，(3)揭示哮喘触发因素和危险因素的序列模式，以及它们的相对重要性，而这两者很难通过基于群组的回顾性研究来实现。我们的方法和结果可为制定针对特定亚群的哮喘管理计划和干预措施提供指导，并最终有可能减轻哮喘的社会负担。
Asthma is a common chronic health condition affecting millions of people in the United States. While asthma cannot be cured, it can be managed if we identify and understand triggers and risk factors that cause asthma exacerbations. However, this is challenging because these triggers and risk factors are complex and interconnected, and there are limitations to current mainstream approaches for identifying them. The recent availability of massive amounts of heterogeneous data has opened up new possibilities for asthma triggers and risk factors analyses. In this study, we introduce a data-driven framework, adapt and integrate multiple advanced machine learning techniques, and perform an empirical analysis to (1) derive characteristics of self-reported asthma patients from social media, (2) enable integration and repurposing of highly heterogeneous and commonly available datasets, and (3) uncover the sequential patterns of asthma triggers and risk factors, and their relative importance, both of which are difficult to achieve via retrospective cohort-based studies. Our methods and results can provide guidance for developing asthma management plans and interventions for specific subpopulations and, eventually, have the potential to reduce the societal burden of asthma.
参考文献：Wenli Z. and Ram S. (2020). A Comprehensive Analysis of Triggers and Risk Factors for Asthma Based on Machine Learning and Large Heterogeneous Data Sources. MIS Quarterly 44(1): 305-349.