The development of organizational knowledge and the depreciation of knowledge within organizations are processes that invariably occur concurrently. In the quality domain, many researchers have examined how the development of organizational knowledge (organizational learning) enhances quality performance. We build on this literature and investigate how the depreciation of organizational knowledge (organizational forgetting) affects quality performance. We analyze information on 2,732 quality improvement initiatives implemented at 295 vendors of a car manufacturer, and find that organizational forgetting affects quality gains obtained from learning-by-doing (autonomous learning)
and from quality improvement initiatives (induced learning); over 16% of quality gains from autonomous learning and 13% of quality gains from induced learning depreciate every year. Further, the impact of organizational forgetting i) differs across the types of quality improvement efforts (quality gains from process improvement initiatives depreciate while those from quality assurance initiatives do not), and ii) depends on where quality knowledge was embedded (depreciation is lower for knowledge embedded in
technology than for knowledge embedded in organizational routines or organizational members). Our results highlight the ubiquity of organizational forgetting and suggest the need for continued attention to sustain and enhance quality performance in supply chains.
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... Forgetting" The classic learning curve model asserts that knowledge accumulated from prior learning does not depreciate. Lately, researchers have empirically examined the element of organizational forgetting (OF) in the learning process, thereby developing a new approach incorporating both aspects, i.e., learning and forgetting (Agrawal and Muthulingam 2015;Argote 2013;Carmona and Grönlund 1998;Causholli 2016;Kim and Seo 2009;Thompson 2007). Forgetting is defined as an inadvertent loss of knowledge, routines, or practices from organizational memory due to personnel turnover, disuse of knowledge, and failure to capture/ codify new knowledge (Agrawal and Muthulingam 2015;Argote 2013;Easterby-Smith and Lyles 2011;Fernandez and Sune 2009;López and Sune 2013;Martin de Holan and Phillips 2004a;Meschi and Métais 2013). ...
... Lately, researchers have empirically examined the element of organizational forgetting (OF) in the learning process, thereby developing a new approach incorporating both aspects, i.e., learning and forgetting (Agrawal and Muthulingam 2015;Argote 2013;Carmona and Grönlund 1998;Causholli 2016;Kim and Seo 2009;Thompson 2007). Forgetting is defined as an inadvertent loss of knowledge, routines, or practices from organizational memory due to personnel turnover, disuse of knowledge, and failure to capture/ codify new knowledge (Agrawal and Muthulingam 2015;Argote 2013;Easterby-Smith and Lyles 2011;Fernandez and Sune 2009;López and Sune 2013;Martin de Holan and Phillips 2004a;Meschi and Métais 2013). Easterby-Smith and Lyles (2011) analyze OF from cognitive, behavioral, and social perspectives. ...
... In contrast, forgetting does not involve replacing existing practices with better ones since it is accidental in nature. Consequently, unlearning is a functional process leading to higher learning levels, whereas forgetting is a dysfunctional process leading to an adverse impact on organizational performance (Agrawal and Muthulingam 2015;Azmi 2008;Causholli 2016;López and Sune 2013;Meschi and Métais 2013). ...
Unlearning has evinced immense traction and opportunity in debates pertaining to organizational learning, innovation, management of change, knowledge management, and new product development, to name but a few. Provided the diversity and expansiveness of the phenomenon, past studies have undertaken both narrative and systematic reviews to synthesize the field of organizational unlearning (OU). Although highly commendable and enlightening, these scholarly efforts would be augmented by contemplating the share of leading management journals towards furthering the research on unlearning. Moreover, a systematic comprehension of the research themes of OU can be instrumental in representing the intellectual structure of the field. For this purpose, we undertake a combination of bibliometric and thematic analysis to identify critical trends that have helped shape unlearning research. The results discern the main scientific actors (articles, authors, journals, universities), research design, and dimensions of OU. In addition, eight clusters of unlearning along with underlying theoretical perspectives are analyzed, which may help scholars integrate the development of one domain to another, formulate pertinent research questions related to OU, and encourage interdisciplinary research.
... Second, we assume constant learning rates over time-a common assumption in the learning curve literature, although the learning rates could vary over time (Lapré & Nembhard, 2010). Third, we assume suppliers learn from the entirety of their prior disruption experiences, although in reality, suppliers could potentially forget what they learned, a process known as "organizational forgetting" (Agrawal & Muthulingam, 2015;Argote, 2012). Finally, we assume suppliers learn through their own disruption experiences rather than through the experiences of other organizations (Håkansson et al., 1999;Hora & Klassen, 2013). ...
When a supplier experiences a disruption, it learns how to better prevent and recover from future disruptions. As suppliers learn to become more resilient, the overall supply network also learns to become more resilient. This research draws on the organizational learning literature to introduce the concept of supply network resilience learning, which we define as the improvement of supply network resilience when suppliers learn from their own disruptions. The analysis integrates agent-based modeling, experimental design, data analytics, and analytical modeling to investigate how supplier learning improves supply network learning. We examine how two types of supplier learning, namely learning-to-prevent and learning-to-recover, affect supply network learning. The results show that suppliers' learning-to-prevent results in a disruption-free supply network when time approaches infinity. However, the results differ across a more realistic finite time horizon. In this setting, learning-to-recover improves network learning when suppliers face a lower chance of disruption. The analysis also shows that centrally located suppliers enhance network learning, except when the risk of a disruption is high and the chance of diffusing a disruption to another supplier is high. In this setting, non-central suppliers become more critical to supply network learning. This research provides a framework that will help practitioners understand the contingencies that influence the effect of supplier learning on the overall supply network resilience learning.
... For these devices, as the days since the previous usage increase, the duration of the surgery significantly increases, suggesting that the knowledge about how to use the devices depreciates. Agrawal and Muthulingam (2015) compare the extent to which knowledge embedded in three different repositories in the supply chain of a manufacturing facility depreciates. The researchers find that knowledge embedded in technology exhibits the least depreciation over time, knowledge embedded in routines evidences intermediate depreciation, and knowledge embedded in individuals exhibits the most depreciation. ...
We trace the evolution of research on organizational learning. As organizations acquire experience, their performance typically improves at a decreasing rate. Although this learning-curve pattern is found in many industries, organizations vary in the rate at which they learn. In order to understand this variation, we separate organizational learning into four processes: search, knowledge creation, knowledge retention, and knowledge transfer. Within each process, we present research on how dimensions of experience and of the organizational context affect learning processes and outcomes. Our goals are to describe major findings and to identify opportunities for future research. The article concludes with a discussion of research directions that are likely to be productive in the future. These directions include investigating how new technological and organizational developments are likely to affect organizational learning.
This paper was accepted by David Simchi-Levi, finance.
... Unlike the above papers, we study both autonomous cost reduction due to learning-by-doing and induced cost reduction due to process improvement investment. Closest to our work, Agrawal and Muthulingam (2015) used a data set from an automobile company to study the impact of organizational forgetting on quality improvement due to learning-bydoing and improvement investment. Unlike them, we use the analytical modeling approach to study the competition between the vendors to win the client's secondperiod requirements. ...
In this article, we study the scenario under which two information technology (IT) vendor firms compete for the outsourcing requirements of a client firm. The vendors' cost structures are private information. In addition, the vendors can improve their unit costs through learning‐by‐doing and by making investments in process improvement, that is, induced learning. We study the impacts of vendor‐based learning and process improvement in the asymmetric cost setting on the client firm's outsourcing strategy and the vendor firms' process improvement investments. Our analysis reveals that the client firm may adopt the single‐sourcing strategy or a combination of dual and single‐sourcing strategies depending on the learning efficiency of the vendor base. We also find that high heterogeneity in the vendor cost structure increases the first‐period outsourcing requirements of the client firm. Our findings provide interesting managerial implications for the IT outsourcing industry.
The increase in the frequency and impact of automotive recalls has had broad reaching economic and social consequences. Recent examples of automotive recalls suggest that some are due to deliberate actions of firms to subvert processes designed to ensure quality. Such controls are dependent on partners acting in good faith in the relationship and abiding by relational norms and so do not recognize the risks of firms lying, falsifying data, or intentionally circumventing process‐based controls. Data on automotive recalls shows that recalls exhibit a statistically significant oscillatory pattern with an estimated period of around 3.6 years. We argue that the cyclical pattern in automotive recalls is due, in part, to opportunistic behavior within a network, which is likely to spread and be reciprocated. To test whether opportunism can lead to similar network effects, we develop an agent‐based simulation to model opportunism within a network of connected firms. The simulation is based on an extension of the prisoner's dilemma where the cooperate/defect decision is based on a dyadic relational model driven by trust, knowledge, and dependence levels within each relationship. The results from the simulation suggest that cyclical patterns, similar to those in automotive recalls, emerge as well as “behavioral clustering” within the network, where connected firms exhibit highly similar behaviors that tend to cycle within small clusters. Therefore, opportunistic behavior in supply networks might be an important, relational determinant of product recalls. Our dynamic modeling approach differs from current perspectives on understanding product recalls, contributing to the current literature.
The purpose of this two-part paper is to provide a summary of current research opportunities in organizational forgetting literature and a future research agenda.
The summary of current research opportunities and future research agenda is drawn from the systematic literature review and synthesis reported in Part I.
Two broad areas for future research are proposed: A first area that highlights a need to address integrative theoretical challenges that include issues of temporality, history, power dynamics, and organizational context. A second area that highlights a need to reconcile contradicting explanations – such as whether technological sophistication and codification practices versus social networks prevent knowledge depreciation and loss – through a multilevel perspective.
Limitations relate to time span coverage and journal article accessibility.
This Part II paper provides a summary of current research opportunities and offers directions for future research on organizational forgetting.
The purpose of this paper is to systematically review and synthesize the literature on organizational forgetting.
A systematic literature review approach was used to synthesize current theoretical and empirical studies on organizational forgetting.
The review and synthesis of the literature revealed that the organizational forgetting literature is fragmented, with studies conducted across disparate fields and using different methodologies; two primary modes (i.e. accidental and purposeful) and three foci (i.e. knowledge depreciation, knowledge loss and unlearning) define current organizational forgetting literature; and the factors that influence organizational forgetting can be grouped into four clusters related to individuals, processes, tools and organizational context.
This literature review has limitations related to time span coverage and journal article accessibility.
This paper offers an integrative view of organizational forgetting that proposes a holistic and multilevel research approach and systematic synthesis of organizational forgetting research.
How might an organization swiftly resolve supplier problems such that the issue does not reoccur? The purpose of this study seeks to understand the impact of different knowledge-sharing routines on measures of effective problem resolution.
Data are collected from an automotive manufacturer's (buyer) database. A hierarchical linear model analyzes dyadic data collected from 155 problems across 24 suppliers.
This study reveals that different ways of communicating have differing impact on measures of effective problem-solving. Communication involving face-to-face interaction slows the process, whereas frequent communication can lead to swift resolution. Furthermore, management teams are more likely to lead to a “better” fix in that these teams are more likely to implement changes in the process or product.
The data are for a tier-one automotive supplier. Hence, the findings are limited by the extent to which other organizations may differ.
The results provide insights for managers experiencing supply issues. Some forms of communication should be encouraged as they enhance the process. Moreover, the findings suggest there are consequences to pressuring a supplier to resolve a complaint quickly.
Very few researchers can claim to have investigated observed collaborative mechanisms that occur between a buyer and its suppliers when resolving a problem. This research adds to the literature on the relational view theory as it applies to supply chain management and problem resolution.
Problem definition: In many service operations, customers have repeated interactions with service providers. This creates two important questions for service design. First, how important is it to maintain the continuity of service for individuals? Second, because maintaining continuity is costly and, at times, operationally impractical for both the organization (because of potentially lower utilization) and providers (because of high effort required), should certain customer types, such as those with complex needs, be prioritized for continuity? These questions are particularly important in healthcare services where patients with chronic conditions visit primary care offices repeatedly. Therefore, we explore these questions in the context of diabetes, a chronic disease. Academic/practical relevance: Although the operations management (OM) and healthcare literatures suggest that higher continuity is better for health outcomes, the possibility that one could have too much continuity has not been explored. We draw on literature on continuity of care from the healthcare literature and learning effects from the OM literature to theorize and then show a curvilinear relationship. In addition, we further the literature on continuity by examining different categories for prioritization. Methodology: We use a detailed and comprehensive data set from the Veterans Health Administration, the largest integrated healthcare delivery system in the United States, which permits us to control for potential sources of heterogeneity. We analyze over 300,000 patients over an 11-year period who suffer from diabetes, a chronic disease whose successful management requires continuity of care, as well as kidney disease, a major complication of diabetes. We use an empirical approach to quantify the relationship between continuity of care and three important health outcomes: inpatient visits, length of stay, and readmission rate. We conduct extensive robustness checks and sensitivity analyses to validate our findings. Results: We find that continuity of care is related to improvements in all three health outcomes. Moreover, we find that the gains are not linearly improving in continuity, but rather the relationship is curvilinear, whereby outcomes improve and then decline in increasing continuity of care, suggesting that there may be value in having multiple providers. Additionally, we find that continuity of care is even more important for patients suffering from more complex conditions. Managerial implications: Identifying the amount of continuity of care to provide and determining which individuals to prioritize are both of interest to practitioners and policymakers because they can help in designing appropriate policies for staffing and work allocation.
This study examines both incremental learning curves as well as "revolutionary" learning and innovation in the area of product quality. One implication of the findings is that knowledge gained from the general environment - e.g., from a technological "march of progress" - may play a crucial role in the area of quality improvement.
The article assesses the effectiveness of induced learning on workgroup performance in an effort to further understand organizational learning in dynamic service settings. A three-year study of 23 hospital neonatal intensive care units and their performance is presented. Emphasis is placed on measurable forms of induced and autonomous learning, such as deliberate learning activities and cumulative experience. Hypotheses are developed about how the use of deliberate learning activities affects workgroup performance given its cumulative experience. Ways in which the effectiveness of deliberate learning activities is changed by a critical interaction in workgroups is also examined.
Two experiments compared collaborative and individual recall. In Experiment 1, participants encoded pictures and words with a deep or shallow processing task, then recalled them twice either individually or collaboratively. Collaborative groups recalled more than individuals, but less than nominal groups (pooled individuals), thus exhibiting collaborative inhibition. However, group recall appeared to be more stable over time than individual recall. Groups and individuals both showed a picture-superiority effect, a level-of-processing effect, and hypermnesia. In Experiment 2, participants recalled the story ''War of the Ghosts'' (from F. C. Bartlett, 1932), and again collaborative groups recalled more than individuals, but less than nominal groups. Both the individual and collaborative recalls were highly organized. There was evidence that the collaborative groups tended to rely on the best individual to a greater extent in story than in list recall. Possible social and cognitive mechanisms are considered.
Knowledge management promises to improve business performance by using technology to share the lessons of experience. One way to make organizational learning more tractable is to consider it as the development of an organization's memory. Explicit knowledge is essential for the ability of an organization to solve problems and create new knowledge. Technology can be a tool for building relationships. Important learning events are often critical, often a kind of business initiatives. The social bonding among a group's members is more important, while technology helps supports communities.