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Editorial: Intervention‐based research (IBR)—What, where, and how to use it in operations management
Journal of Operations Management ( IF 6.5 ) Pub Date : 2020-05-15 , DOI: 10.1002/joom.1093
Aravind Chandrasekaran 1 , Suzanne Treville 2 , Tyson Browning 3
Affiliation  

1 INTRODUCTION

It has been 4.5 years since the establishment of the Design Science (DS) department in the Journal of Operations Management (JOM). Even with the recent name change to the department of Intervention‐based Research (IBR), its mission remains as discussed in the initial essay (Van Aken, Chandrasekaran, & Halman, 2016, p. 1): “to publish high quality research articles that derive new theoretical and managerial insights by engaging with practice and solving complex field problems.” JOM has received over 65 DS/IBR submissions and accepted 8 of these papers on topics that include sourcing, healthcare delivery, product development, and humanitarian operations. Table 1 lists these published articles. The objective of this editorial is to share with prospective authors and reviewers the insights gained from this experience.

TABLE 1. Papers published in JOM that use either IBR or design science/IBR
Paper Context Synthesis
Information sharing for sales and operational planning: Contextualized solutions and mechanisms (Kaipia, Holmström, Småros, & Rajala, 2017) Supply chain

Problem: Sharing point of sale (PoS) data is potentially useful only where conventional demand planning is inadequate such as product introductions, promotions, and seasonal peaks. The determinants of successful information sharing are difficult to assess agnostic to context.

Intervention: Researchers and key stakeholders codesigned and observed a collaborative product introduction process that used PoS data.

Contributions: Identify multiple contextual factors and three mechanisms that allow organizations to develop and benefit from collaborative sales and operational planning.

Improving home care: Knowledge creations through engagement and design (Groop, Ketokivi, Gupta, & Holmström, 2017)

Healthcare delivery

Problem: Increased need for homecare nurses to serve an ageing population in Finland. Theoretical objectives are often assumed and lead to impractical solutions.

Intervention: Initial design for solving this as a problem to minimize transportation (travelling salesperson problem) was not viable. Iteratively codesigned a solution by resolving conflicting objectives between stakeholders.

Contributions: Providing insights on how field problems may have different objectives that are invisible for the researcher or the practitioner. It is when these two agents come together that these problems are solved and sustained.

Hedging weather risks and coordination in supply chains (Brusset & Bertrand, 2018) Supply chain

Problem: Fluctuations in weather due to climate change creates financial losses for manufacturers when they incur lower‐than‐expected sales due to adverse weather conditions. These indirect effects of weather impact manufacturers differently.

Intervention: Develop a mechanism to determine weather‐related supply risk specific to product characteristics and then design varying forms of financial compensation based on the weather index‐based instrument to improve coordination among supply chain partners.

Contributions: Insights into how traditional financial instruments such as futures, swaps, and options can help supply chain managers make better weather‐related decisions by providing actionable weather‐sensitive models to help understand the disruptive effects of weather variability.

Contracting outsourced services with collaborative key performance indicators (Akkermans, van Oppen, Wynstra, & Voss, 2019) Outsourcing services

Problem: Performance‐based contracts are challenging to design and implement in the context of outsourced services due to the coproduction problem. Intervention: Traditional output or process controls did not work in service‐outsourcing contexts.

Intervention: A new contracting approach involving collaborative KPIs wherein supplier's performance, and hence, the rewards and penalties is a function of buyer behaviors. Tested and refined this solution across three cases.

Contributions: Newer insights on contract design that is different from the traditional approaches discussed in the literature. Identified four mechanisms that explain the outcomes of the design intervention.

Creativity and productivity in product design for additive manufacturing: Mechanisms and platform outcomes of remixing (Friesike, Flath, Wirth, & Thiesse, 2018) Product design and additive manufacturing

Problem: What are the mechanisms and outcomes of remixing 3D models in the context of additive manufacturing performance? Each remixing opportunity requires contextual analysis.

Intervention: Worked with designers from Thingiverse—a social community sharing digital designs—to understand different purposes for remixing and its effect compared to not‐remixing these designs.

Contributions: Insights on how organizations can create appropriate structures for their designers to effectively use remixing strategies that can help improve productivity and creativity during the design process.

Fleet sizing for UNHCR country offices (Kunz & Van Wassenhove, 2019) Humanitarian operations

Problem: Relief organizations do not always have the appropriate fleets for supporting their missions.

Intervention: Traditional approaches to making centralized decisions fail, while decentralized decision‐making leads to inefficiencies or excess fleets when not needed. Developed a step‐wise linear regression model to determine the fleet sizes based on number of locations, small partners, and large partners to accurately predict fleet sizes and worked with several agencies from the United Nations High Commissioner for Refugees (UNHCR) to implement the model with decentralized decision‐makers.

Contributions: Developed design propositions on how to determine fleet sizes for different humanitarian organizations based on the operating context of the humanitarian organization.

Economies of collaboration in build‐to‐model operations (Hedenstierna et al., 2019) Outsourcing services and additive manufacturing

Problem: The nature of 3D printing or additive manufacturing allows for different levels of outsourcing that require nontraditional coordination and supply management practices.

Intervention: Emergence of a bidirectional partial outsourcing model through the practice of order‐book smoothing wherein the 3D printers alternate between the roles of an outsourcer and a subcontractor.

Contributions: Additive manufacturing operations can benefit from different level of outsourcing depending on the demand level and commonality of the technology. The benefits of bidirectional partial outsourcing are dependent on collaboration that may reduce traditional risk in supply chain relationships.

Improving Customer Routing in Contact Centers: An Automated Triage Design based on Text‐Analytics (Ilk, Shang, & Goes, 2020) Service delivery

Problem: How to match the wide‐range service inquiries to the right service agents in a call center to minimize service times and improve service quality?

Intervention: Developed a new mechanism to triage customer service calls that was better than existing models used in practice based on existing theories. The newer triage model was developed using machine learning technique and was developed in conjunction with the experts from an organization.

Contributions: Theoretical understanding on how machine learning triage technique can improve accessibility—effectiveness interaction in service settings.

We first observed that the articles making it through the peer‐review process to acceptance in JOM tended to deviate from common DS practices as applied in neighboring disciplines such as information systems (for an in‐depth review of DS in some other disciplines, see March & Smith, 1995; Hevner, March, Park, & Ram, 2004; Wieringa, 2014; Baskerville, Baiyere, Gregor, Hevner, & Rossie, 2018; Rai, 2017). Solutions to problems of information systems, for example, often involve a design artifact such as an algorithm or process model—a man‐made solution that can then be made available more widely. Designed artifacts usually make a practical rather than a theoretical contribution. Given JOM's emphasis on theoretical contributions, we discovered that most DS articles were not a good fit with the journal. As we reflected on these published articles, we realized that the element of their contributions that benefited from being incubated in the review process was that which stemmed from the active involvement of the researchers in deploying operations management (OM) theories and tools, along the lines described by Simon (1996) in distinguishing between natural sciences and the sciences of the artificial. We thus made the decision to change the department's name to IBR to reflect this evolution in thinking at the editorial level. The change was announced during the 2019 Academy of Management meetings.

Oliva (2019) drew on Checkland's (1985) approach to provide direction in the use of intervention as an OM research method. Interventions are defined as the use of a method (M) to apply a basket of theories (T) to bring a problem situation (S) to S*. If the intervention succeeds in moving the problem situation from S to S*, then the theory has been confirmed. However, a successful move from S to S* often requires adjustments to either T or M. If the adjustments are to M—as applies to a traditional DS contribution—what is learned tends to be practical in nature and is likely to be atheoretical. If, however, the required adjustment concerns T, the resulting insights about T may produce a theoretical contribution. We have also witnessed occasions where what emerges is that S*—where everyone had agreed to head—turns out to be the wrong place to go. Answering the question “Why did we end up in the wrong place?” also offers interesting theoretical insights. Adding guidance to calls that researchers step outside their ivory tower (e.g., Van de Ven & Johnson, 2006; Van Mieghem, 2013), IBR guides how to formalize the kind of surprise that such mixing with practice is able to provide and how to form that surprise into a theoretical contribution.



中文翻译:

社论:基于干预的研究(IBR)-在运营管理中使用什么,在哪里以及如何使用它

1引言

自《运营管理杂志》JOM)中的设计科学(DS)部门成立以来已有4.5年。即使最近将名称更改为基于干预的研究(IBR)部门,其任务仍然如最初论文中所述(Van Aken,Chandrasekaran和Halman,2016年,第1页):“发表高质量的研究文章通过与实践接触并解决复杂的现场问题来获得新的理论和管理见解。” 乔姆已收到超过65份DS / IBR提交的材料,并接受了其中8篇有关采购,医疗保健交付,产品开发和人道主义行动的论文。表1列出了这些已发布的文章。这篇社论的目的是与潜在的作者和评论者分享从这次经历中获得的见解。

表1.JOM上发表的使用IBR或Design science / IBR的论文
语境 合成
用于销售和运营计划的信息共享:上下文相关的解决方案和机制(Kaipia,Holmström,Småros和Rajala,2017年 供应链

问题:仅当常规需求计划(例如产品介绍,促销和季节性高峰)不足时,共享销售点(PoS)数据才有用。成功信息共享的决定因素很难评估与上下文无关的信息。

干预:研究人员和关键利益相关者进行了代码签名,并观察了使用PoS数据的协作产品引入过程。

贡献:确定多个上下文因素和三种机制,使组织能够开发协作销售和运营计划并从中受益。

改善家庭护理:通过参与和设计创造知识(Groop,Ketokivi,Gupta和Holmström,2017年

医疗保健交付

问题:为芬兰老龄化人口提供服务的家庭护理护士的需求增加。通常假设理论目标,并导致不切实际的解决方案。

干预:最初的设计无法解决这个问题,以最大程度地减少运输(行销员问题)。通过解决利益相关者之间相互矛盾的目标,对代码进行迭代编码。

贡献:提供有关现场问题可能具有不同目标的见解,这些目标对于研究人员或从业人员是看不见的。当这两个因素汇聚在一起时,这些问题才得以解决和持续。

对冲天气风险和供应链中的协调(Brusset&Bertrand,2018 供应链

问题:由于气候变化导致的天气波动会给制造商带来不利的经济损失,原因是制造商由于不利的天气条件而导致其销售低于预期。天气的这些间接影响对制造商的影响不同。

干预:建立一种机制来确定特定于产品特性的与天气相关的供应风险,然后基于基于天气指数的工具设计不同形式的财务补偿,以改善供应链合作伙伴之间的协调。

贡献:洞悉传统金融工具(例如期货,掉期和期权)如何通过提供可操作的天气敏感模型来帮助理解天气变化的破坏性影响,从而帮助供应链经理做出更好的天气相关决策。

通过协作关键绩效指标外包服务(Akkermans,van Oppen,Wynstra和Voss,2019年 外包服务

问题:由于协同生产问题,基于绩效的合同在外包服务的环境中设计和实施具有挑战性。干预:传统的输出或流程控制在服务外包的环境中不起作用。

干预:一种涉及合作KPI的新合同方式,其中,供应商的绩效以及由此产生的奖励和惩罚是买方行为的函数。在三种情况下测试并完善了该解决方案。

贡献:对合同设计的新见解与文献中讨论的传统方法不同。确定了四种解释设计干预结果的机制。

增材制造产品设计中的创造力和生产力:再混合的机制和平台成果(Friesike,Flath,Wirth和Thiesse,2018年 产品设计与增材制造

问题:在增材制造性能方面,重新混合3D模型的机制和结果是什么?每个混音机会都需要进行上下文分析。

干预:与Thingiverse(共享数字设计的社会社区)的设计师合作,以了解重新混合的不同目的及其效果(与不重新混合这些设计相比)。

贡献:对组织如何为设计师创建合适的结构以有效使用重新混合策略的见解,这些策略可以帮助提高设计过程中的生产率和创造力。

难民署驻国家代表处的机队规模(Kunz和Van Wassenhove,2019年 人道主义行动

问题:救援组织并不总是拥有适当的机队来支持其任务。

干预:传统的集中决策方法失败,而分散决策会导致效率低下或不必要时机队过多。开发了逐步线性回归模型,以根据地点,小伙伴和大伙伴的数量确定船队规模,以准确预测船队规模,并与联合国难民事务高级专员办事处(UNHCR)的多个机构合作实施该模型与分散的决策者。

贡献:就如何根据人道主义组织的运作情况确定不同人道主义组织的机队规模制定了设计方案。

建立模型运营中的合作经济(Hedenstierna et al。,2019 外包服务和增材制造

问题:3D打印或增材制造的性质允许不同级别的外包,这需要非传统的协调和供应管理实践。

干预:通过订单簿平滑的实践,双向局部外包模型的出现,其中3D打印机在外包商和分包商的角色之间交替。

贡献:增材制造业务可以从不同水平的外包中受益,具体取决于需求水平和技术的通用性。双向部分外包的好处取决于协作,这种协作可以减少供应链关系中的传统风险。

改善联络中心的客户路由:基于文本分析的自动分类设计(Ilk,Shang和Goes,2020年 服务提供

问题:如何将广泛的服务查询与呼叫中心中的正确服务代理相匹配,以缩短服务时间并提高服务质量?

干预:开发了一种新的机制来分类客户服务呼叫,该机制比基于现有理论的实践中使用的现有模型更好。较新的分类模型是使用机器学习技术开发的,并与组织的专家共同开发。

贡献:对机器学习分类技术如何改善可访问性(服务设置中的有效性交互)的理论理解。

我们首先观察到,通过同行评审过程获得JOM认可的文章倾向于偏离在信息系统等相邻学科中应用的通用DS惯例(有关在其他一些学科中对DS进行的深入研究,请参阅March &Smith,1995 ; Hevner,March,Park,&Ram,2004 ; Wieringa,2014 ; Baskerville,Baiyere,Gregor,Hevner,&Rossie,2018 ; Rai,2017)。例如,信息系统问题的解决方案通常涉及诸如算法或过程模型之类的设计工件,这是一种人造解决方案,可以在以后得到更广泛的应用。设计的工件通常会做出实际而不是理论上的贡献。给定JOM强调理论贡献,我们发现大多数DS文章都不适合该期刊。正如我们在这些已发表文章中所反映的那样,我们意识到,他们的贡献得益于在评审过程中的孵化,这是由于研究人员积极参与了按部就班地部署运营管理(OM)理论和工具的结果西蒙(Simon(1996))在区分自然科学和人工科学方面进行了描述。因此,我们决定将部门名称更改为IBR,以反映编辑思想上的这种演变。该变化是在2019年管理学院会议期间宣布的。

Oliva(2019)借鉴了Checkland(1985)的方法,为使用干预作为OM研究方法提供了指导。干预被定义为使用方法(M)运用一揽子理论(T)将问题情境(S)引入S *。如果干预活动的问题情境,从成功小号S *,那么理论得到了证实。然而,从一个成功的举动小号S *经常需要调整,要么牛逼中号。如果调整为M就像传统的DS贡献一样,所学到的东西在本质上往往是实用的,而且很可能是理论上的。然而,如果所需要的调整涉及牛逼,对产生的见解牛逼可能产生的理论贡献。我们还目睹了出现以下情况的情况,那就是所有人都同意前往的S *变成了错误的去向。回答问题“我们为什么会在错误的地方结束?” 还提供了有趣的理论见解。为研究人员走出象牙塔的电话增加指导(例如Van de Ven&Johnson,2006; Van Mieghem,2013)),IBR指导如何将这种与实践相结合所能提供的惊喜形式化,以及如何将这种惊喜形成为理论贡献。

更新日期:2020-05-15
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