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ABSTRACTR&D projects in high‐tech organizations bring together diverse knowledge domains to quickly develop new products and processes. The fast‐paced context of high‐tech organizations makes it challenging to create new knowledge and solve complex problems. Managing these R&D projects requires understanding both the mechanisms and the type of knowledge created to achieve project objectives. This research conducts a two‐phased multimethod study to understand knowledge creation in high‐tech R&D projects. The first phase uses qualitative data to develop a theory on knowledge creation in R&D projects. The second phase involves a survey that collects data from R&D projects to test the theory. Results from the case study find that R&D projects benefit from two types of knowledge – objective and intuitive. The case analyses show that intuitive and objective knowledge creation in high‐tech organizations occurs by creating not only diverse but also psychological safe project teams. The large‐scale survey finds that team diversity positively influences objective knowledge creation while psychological safety affects intuitive knowledge creation. Surprisingly, the results show that team diversity negatively affects intuitive knowledge creation. A post hoc analysis takes a more granular look at diversity and shows that different kinds of diversity have different effects on knowledge creation. This helps to better explain how to manage innovation across boundaries. Finally, the analysis shows that both objective and intuitive knowledge influence R&D project performance. Taken together, these results help explain how to manage innovation across functional boundaries to create knowledge and enhance R&D project performance.

ABSTRACTMany organizations that were once quality leaders have had challenges sustaining high‐quality performance. Although research has examined frameworks and concepts that lead to high‐quality performance, few studies examine how to sustain high‐quality performance. Sustaining performance may require additional capabilities from what it takes to achieve it. Drawing on quality management literature, organizational resilience literature, and the theory of dynamic capabilities in the strategy literature, this study empirically investigates the effects of four capabilities that help sustain high‐quality performance. The analysis shows that capabilities in improvement, innovation, sensing weak signals, and responsiveness all help sustain high‐quality performance. This suggests that what it takes to achieve high‐quality performance is different, in part, from what it takes to sustain it. The data comes from a survey of 147 manufacturing business units. The analysis shows that the relative benefits of these capabilities may depend on the level of competitive intensity and environmental uncertainty. The findings provide empirical support for a theoretical model and practical guidance for sustaining quality performance.

AbstractWhen 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, noncentral 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.

Purpose
– Much of the practitioner literature touts the universal benefits of process management and its impact on operational performance. However, in academic literature, empirical evidence is mixed. The purpose of this study is to investigate the role of the competitive intensity on the effectiveness of process management.


Design/methodology/approach
– Survey data from manufacturing plants were collected from through a global research project. Regression analysis was used to test hypotheses.


Findings
– The influence of process design on efficiency and innovation performance is not dependent on competitive intensity; however, the impact of process improvement and process control on efficiency and innovation performance is in some instances moderated by competitive intensity.


Research limitations/implications
– The inclusion of competitive intensity as a contingency variable helps to explain the contextual impact of process management on efficiency and innovation.


Practical implications
– Process management can be an effective tool if the levels of process design, control, and improvement are customized to fit with the competitive environment.


Originality/value
– This is one of the few studies to empirically examine process management as three core elements. Previous studies utilized a single construct of process management or multiple manufacturing practices such as customer/supplier involvement, statistical quality control, process focus, and cross-functional teams to measure process management. Using this measurement approach demonstrates how process management can influence both efficiency and innovation.

ABSTRACTQuality management (QM) has often been promoted as a universal remedy, where organizations adopt these practices to enhance performance. However, implementation of QM has led to mixed results with some high‐profile failures. Some suggest that customizing QM practices to fit the organization's situational context can help avoid implementation failure and improve performance. However, research has not fully investigated how organizations should go about customizing quality practices. This article addresses this question by conceptualizing two fundamental yet different aspects of QM practices that have different learning objectives: quality exploitation (QEI) and quality exploration (QER). Drawing on experts and empirical data, we develop a reliable and valid set of measures for QEI and QER. Furthermore, the analysis shows the performance differences in the two sets of QM practices across different contextual settings. Specifically, the empirical results show that the benefits of different QM orientations depend on the level of competition and rate of product change. This research challenges prior conceptualizations of QM, and suggests a practical framework to guide decision makers in customizing QM practices.

ABSTRACTOrganizations are increasingly implementing process‐improvement techniques like Six Sigma, total quality management, lean, and business process re‐engineering to improve organizational performance. These techniques are part of a process management system that includes the organizational infrastructure to support the improvement techniques. The knowledge‐based view of a firm argues that organizational knowledge is the source of competitive advantage. To the extent that the process management system enables knowledge creation it should be a source of competitive advantage. This study investigates the underlying framework and factors of a process management system that lead to organizational knowledge creation. Prior studies have considered knowledge creation in process improvement, but none have considered the role of the process management system. Specifically, the study uses the case study method to investigate multiple levels (organization level and project level) of two firms using Six Sigma as their chosen process management system. Analysis of the cases reveals that the leadership creates a supportive infrastructure enabling process‐improvement techniques to effectively create organizational knowledge. Interestingly, focusing on decision‐making tools and methods may not be effective without developing a supportive infrastructure. The proposed framework provides a basis for organizational leaders to think about how to design and implement a process management system to better enable knowledge creation in organizations.

PurposeThe authors empirically determine the stages and leadership styles that enhance the effectiveness of firm response and recovery efforts during each stage.Design/methodology/approachThe authors use an inductive exploratory approach and mixed-method research design. Study 1 uses a combination of qualitative data gathered through two rounds of exploratory focus groups (26 managers and executives), Q-sorting (60 participants) and a confirmatory focus group (6 experts) to highlight how expert practitioners perceive the staged progression of a supply chain disruption. Study 2 uses responses from 90 experienced managers in an experimental vignette to determine the most effective leadership style during each stage.FindingsExpert practitioners are strongly partial to a two-staged disruption model that includes an early/response and late/recovery stage. They consider decisiveness to be the most effective style in the response stage. However, in the recovery stage, a style that combines decisiveness and task-centered leadership is perceived to be the most effective. Further, effective leadership hinges on applying distinct styles depending on the progression of events during supply chain disruptions.Originality/valueEmpirical evidence and validation of conceptual models on leadership behavior during crises are essentially nonexistent in the literature. This study is likely the first to pursue the subject of leadership during stages of crises and the first to offer empirical evidence thereof. Relatedly, the authors contribute to the growing research on crisis management, which is likely to receive even more attention as the frequency and size of crises facing organizations increase.

AbstractRetail inventory shrinkage, resulting primarily from employee theft and shoplifting, costs retailers nearly $70 billion annually. With brick‐and‐mortar retailers today confronting increased competition and low future growth expectations, reducing inventory shrinkage is becoming even more critical to becoming profitable. This paper analyzes a unique dataset that combines both primary survey and objective archival data from a Fortune 500 retailer to test a theoretical model associating retail inventory shrinkage, the capacity of a retail store to sense weak security breach signals, centralization of decision making, and formalization of security breach management. The analysis builds on insights from high reliability organization theory and the literature on organizational structure. Results reveal that as a retail store increases its capacity to sense weak security breach signals, it observes decreases in store‐level inventory shrinkage, with this negative association amplified (dampened) when the retail store has formalized procedures and protocols for managing security breaches (has centralized decision making within the retail store). Moreover, while the establishment of formalized procedures and protocols for managing security breaches bolsters the capacity of a retail store to sense weak security breach signals, centralizing decision making has the opposite effect. Our findings contribute to the retail operations literature by introducing a new store‐level organizational capability to guard against theft‐based retail inventory shrinkage and by offering novel insights into how and why organizational structure at the level of a retail store deters or facilitates the capacity to sense weak security breach signals. From a practical perspective, these findings advise retailers to develop the capability to become aware of and to mitigate security breaches. Further, to support this capacity, retailers are urged to decentralize decision making to retail store personnel and to invest in formalizing procedures and protocols for managing security breaches in order to deter retail thefts that shrink retail store inventory.

AbstractFirms increasingly engage in mergers and acquisitions (M&As) to improve their network positions and enhance performance. Yet, how the fundamental structure of the merged supply base changes after the M&A and how the structural changes affect the performance are largely unknown. Building upon the strategy‐structure‐performance framework, this study investigates dual roles of supply base structural changes in M&A events, namely, as an outcome and as a moderator to post‐M&A performance. In particular, we examine how the size and the country diversity of the merged supply base change after M&As, as well as how these structural changes affect the merged firm's operational performance. We conduct a difference‐in‐differences analysis by comparing firms that engaged in M&A events (treatment group) with those comparable firms that did not engage in any M&A events (control group). The results show that the merged firms tend to reduce the size of their supply bases after M&As. In addition, our results demonstrate that both supply base consolidation (i.e., reducing the number of suppliers) and country diversification (i.e., spreading suppliers across multiple countries) improve the merged firms' post‐M&A operational performance, an effect that becomes stronger for horizontal M&As. We also explore how the type of M&As (i.e., horizontal vs. nonhorizontal), industry relatedness between the two merging firms, and the purposes of M&As affect the post‐M&A structural changes to the supply bases. This study helps inform supply managers the important roles of supply base in M&As to enhance post‐M&A operational performance or to limit the synergies when not properly done.

PurposeThe purpose of this study is to discover the learning mechanisms and temporal dynamics of implementing systems (Six Sigma) as it unfolds over time.Design/methodology/approachThe data come from a European engineering company that was implementing a Six Sigma-based quality management system (QMS) over a seven-year period. The analysis is based on an event-sequence reconstruction of the implementation process as it unfolded over time and discovers four different learning mechanisms that emerged: programmatic, persistent, adaptive and dialectical learning mechanisms. The research follows a process design study, where the authors study how the process unfolds over time.FindingsMuch of the literature on implementing management systems suggests that implementation follows a prescribed sequence of "turn-key" steps. However, the findings show that only 40% of all events were driven by prescribed "turn-key" generic practices, while 56% of events required constructing new practices via adaptive and dialectical learning. Moreover, the implementation process did not proceed in a linear programmatic fashion, but instead followed a punctuated equilibrium pattern, which alternated between periods of incremental change and major organizational change. The study also found that implementation required changing many complementary organizational structures and practices that were interdependent with the management system (i.e. Six Sigma). By understanding the implementation process, managers can better assess the time and effort involved, better adapt the system to their situated context and predict critical junctures where implementation could break down.Originality/valueThis research complements the few studies that have examined the process of implementing management systems. Most studies examine factors or conditions that result in implementation success (the what of implementing systems), but few examine the process of implementation and the learning that takes place during implementation (the how of implementing systems), which is a complex nonlinear process that involves different modes of learning.