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Learning-before-Doing in the Development of New Process Technology
Abstract
The concept of learning-by-doing has featured prominently in the literature on manufacturing improvement and technological innovation. Much of the focus of this literature is on the ‘doing’ or ‘using’ that takes place in an actual commercial production or usage environment. But problem-solving can also occur long before a new product or process design is introduced into the factory through computer simulations, laboratory experiments, prototype testing, pilot production runs, and other experiments. These approaches to problem-solving are referred to in this paper as ‘learning-before-doing.’ Although there is an extensive literature on prototyping and technical problem-solving in R&D, there have been few attempts to determine the type of conditions under which different approaches to learning are most effective. This paper explores the impact of different learning strategies on development performance with detailed data on 23 process development projects from pharmaceuticals and biotechnology. The empirical analysis focuses specifically on how the timing of technology transfer to the factory influences development costs. The results of the analysis indicate learning-by-doing is essential for efficient development in an environment like biotechnology where underlying theoretical and practical knowledge is relatively thin. In contrast, the need for learning-by-doing is far lower in environments like chemical synthesis where underlying theoretical and practical knowledge is deep enough to enable the design of laboratory experiments that effectively model future production experience. The paper concludes with a discussion of the implication of these findings for the management of process development and learning.
... The findings offer several key contributions. First, it extends the often-cited but rarely tested distinction between learning before versus learning after doing (Pisano, 1994 and1996); exporting is a type of experience in which this distinction may be particularly important. Second, in doing so, it sheds new light on whether firms indeed learn by exporting (Wagner, 2007) by considering the likely processes underlying such learning. ...
... Indeed, empirical studies measure learning by exporting in terms of the productivity gains in the time periods after exporting commences (e.g., Salomon & Jin, 2008, 2010Salomon & Shaver, 2005). However, foundational work on organizational learning curves points to the idea that firms might learn before as well as after doing (Pisano, 1994 and1996). Prior to experience, firms might learn via forward-looking processes of planning, prototyping, piloting, and so on. After experience, firms might learn via a backwardlooking process of sensemaking (also see Gavetti & Levinthal, 2000;Maitlis & Christianson, 2014). ...
... First, it contributes to the wide-ranging body of literature on experiential learning (see Argote et al., 2021;Argote & Levine, 2020;Argote & Miron-Spektor, 2011) by extending the notion of learning before versus after doing. This distinction was initially offered and tested in the context of problem-solving in R&D, noting that "in certain environments…most of the learning that needs to take place can be done before the process is moved to the [manufacturing] plant" (Pisano, 1996(Pisano, : 1117. Although this distinction is often cited, most studies of experiential learning have implicitly focused on the latter to the exclusion of the former (see Lapre et al., 2000; for seminal work, see Argote & Epple, 1991;Wright, 1936). ...
Organizational learning begins with experience. However, it remains an open question whether firms learn from a particular type of experience: exporting. This study aims to speak into this debate by examining when learning by exporting occurs. Our core thesis is that the timing of learning by exporting depends on a firm’s home market economic development. Drawing on classic theories of organizational learning, we posit that firms in more developed home markets will enjoy greater opportunities for learning before exporting whereas firms in less developed home markets will enjoy greater opportunities for learning after exporting. The former will be observed as a divergence in productivity among firms from different home markets, whereas the latter will be observed as convergence over time. The proposed hypotheses were tested and supported using longitudinal data from the World Bank Enterprise Survey. A range of theoretical and practical contributions are discussed.
... Another, closely related concept to the "learning curve" is Pisano's concept of "learningbefore-doing" (Pisano, 1994(Pisano, , 1996(Pisano, , 1997. It describes the way and conditions how efficiency gains can be achieved through a forward-looking innovation process that incorporates routines like computer simulations, scale-up experiments, prototype testing, pilot production runs, and other experiments before a new product is transferred from the laboratory to the producing plant (Pisano, 1996). ...
... Another, closely related concept to the "learning curve" is Pisano's concept of "learningbefore-doing" (Pisano, 1994(Pisano, , 1996(Pisano, , 1997. It describes the way and conditions how efficiency gains can be achieved through a forward-looking innovation process that incorporates routines like computer simulations, scale-up experiments, prototype testing, pilot production runs, and other experiments before a new product is transferred from the laboratory to the producing plant (Pisano, 1996). The efficiency increase materializes through cost savings from shorter time-to-market periods, reliability increase at production ramp-up, or less capital expenditures for production technologies. ...
... For instance, if a firm has a high new product development capability intensity because it invests heavily in product R&D, it is likely that it produces a large number of new products in a rather short time. Operations, however, usually needs to adjust their production processes according to the requirements of each new product which requires process development capabilities (Pisano, 1996). Consequently, new product development and new process development capabilities need to be executed with aligned intensity. ...
... For example, Toyota and Honda have long been engaging in various programs for leveraging supplier learning and improvement (MacDuffie and Helper 2007). Since the seminal work of Arrow (1962), there is also an extensive literature on learning in various industries, for example, airframes (Wright 1936), automobile assembly (Baloff 1966), pharmaceuticals (Pisano 1996), and semiconductors (Hatch and Mowery 1998). The basic idea is simple-unit cost falls with cumulative production experience (Fine and Porteus 1989, Mazzola and McCardle 1997, Li and Rajagopalan 1998, Gray et al. 2009, Li et al. 2015, Li 2019. ...
... (ii) Learning is often stochastic (Adler and Clark 1991), for example, due to technical changes (Acemoglu 2012), input price fluctuation (Wei et al. 2021), strategic behavior (Li 2020), and organizational forgetting (Besanko et al. 2010). (iii) Learning is often lumpy and episodic (Tyre and Orlikowski 1993, 1994, 1996. Although production knowledge accumulates continuously, the exploitation of that knowledge requires technical and managerial changes. ...
Problem definition: We study a procurement problem, where the supplier holds superior cost information and can learn to improve efficiency over time. Despite its prevalence, the supply chain literature provides limited guidance on how to manage learning suppliers with evolving private information. Methodology/results: We use mechanism design. We show that supplier learning has both efficiency and agency effects, it can induce countervailing incentives, and the agency effect can overwhelm the efficiency effect. As a result, (i) supplier learning can hurt profits, (ii) information asymmetry can improve efficiency, (iii) production distortion can go upward, and (iv) ignoring the agency effect of learning can mislead contract design and inflict severe losses. Managerial implications: Our results suggest that previous studies may have overlooked the downside of learning and overestimated the harm of information asymmetry. Moreover, our results help explain when and why firms should overproduce output and disclose private information voluntarily. By highlighting the strategic role of supplier learning, this study sharpens our understanding of supply chain management.
Funding: L. Gao is partly supported by the CoR research grant at University of California, Riverside. W. Zhang is partly supported by the National Natural Science Foundation of China [Grant 71821002].
Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0285 .
... Learning plays a significant role in product adoption [1,2]. In this context of eLearning innovative MOOC (Massive Open Online Courses) platforms are driving new approaches in the eLearning space by offering everything from eLearning replacing any classroom course, short ad-hoc learnings, to months long learning programs with certification. ...
... There is also first exploratory research that learning artefacts could be of interest in the future [19]. Other research suggests that, especially, learning prior to any usage will ease the transfer overall, but more research in this area is needed [1]. Similar results are suggested already also around eLearning, research proposing that upfront learning in multimedia is helpful as well as short snippets afterwards. ...
Innovation in eLearning has been discussed in academic research for more than 30 years. Current research around eLearning even questions if former product adoption models are still valid, and new alternative formats are tested. In times of subscriptions and anonymous selling via the internet the question on how users in organisations perceive innovation in eLearning and product adoption is addressed in this research.This single-case approach in the cloud and AI industry presented here investigates what users expect from their Human Resources department around eLearning.The findings provide insights into how users see current trends in short and immediate eLearning. The findings not only underline recent research of the existing lifecycle model by integrating eLearning into the product, but also provide insights on what is expected from AI in an eLearning context. The need to link corporate eLearning with academic micro-credits support the life-long learning concept at IBM.KeywordseLearningInnovationSingle-case approachCloudAIEmbedding designMicro-credits
... In our research, most interviewees suggested that a small piece of eLearning should be positioned much earlier, for example, during the hiring process was mentioned, such as university or school. This statement, in general, is supported by the research of Pisano [54], who saw indication in the production process that early exposure to new technologies could increase the adoption speed later on. Besides the early work on Pisano [54], there is also more recent research [55] indicating that additional points in time besides the traditional findings are helpful. ...
... This statement, in general, is supported by the research of Pisano [54], who saw indication in the production process that early exposure to new technologies could increase the adoption speed later on. Besides the early work on Pisano [54], there is also more recent research [55] indicating that additional points in time besides the traditional findings are helpful. The fact that this topic comes up in research around eLearning can lead to the conclusion that eLearning is currently dramatically changing the product adoption process. ...
The need to link eLearning and innovation has been discussed in depth in education and entrepreneurship since its inception 30 years ago. In times of subscriptions and anonymous selling via the internet organisations have one need prior to adopting a product: they need to acquire the right skills to accept the innovation a new product brings them.
... PDPs are important arenas for collaboration among various types of actors, i.e., industrial firms, academia, government agencies, and equipment suppliers (e.g., Br€ oring and Herzog, 2008). The managerial and organizational challenges are therefore often rooted in various types of heterogeneous organizations that must work together (Pisano, 1996). In a recent article, a large number of sustainability transition scholars called for new knowledge about micro-level phenomena such as how different groups and organizations interact over time to develop sustainable and clean technologies (K€ ohler et al., 2019). ...
... There may also be equipment suppliers involved, i.e., actors that supply the actual hardware and software that constitute the PDP. Finally, plant contractors and individual consultants are often involved (Pisano, 1996). ...
Pilot and demonstration plants (PDPs) perform critical tasks in the development of new sustainable technology by bridging basic knowledge generation and large-scale commercialization. Significant private and public funding has therefore been allocated to PDPs addressing climate change, pollution abatement technology and/or increased resource efficiency. After technology verification, PDPs typically struggle with evolving objectives, and reports of stalled or delayed development are common. Key problems may center on technical difficulties, but challenges of a non-technical nature are equally important, not least for the development of clean technology. This paper draws on a longitudinal case study of four PDPs used for advanced biorefinery technology development in Sweden and delineates the key managerial and organizational challenges that arise in and around such plants. By taking the actor networks around PDPs as the main unit of analysis, this paper gives a detailed description of various challenges, such as the division of responsibility for the operation and ownership of the PDPs, unclear roles and objectives, and the lack of specific competences and resources in the actor networks. One important conclusion is that improved knowledge about such challenges should increase the resilience of actor networks in and around PDPs, and also help shorten the formative phase of developing sustainable technology.
... The first series of production plants are necessary and deliver what laboratories and prototypes cannot bring, but are costly [219]. The first production plants often experience difficulties in transferring what has been learned into the full commercial and operational series of plants [127]. But when experience grows via trial-and-error, the participating organizations enter into a learning curve wherein cost-efficiency grows. ...
... A small network of architects, real estate agents, and contractors joined all relevant sustainable construction demonstration projects in the country, which made these firms the national frontrunners in the new emerging business of energy-efficient building. Like the technical learning processes, also these organizational learning processes initially cost more money than these generate [46,127,219]. The basic idea about further investing in the development of the production plants in demonstration projects is that learning curves will become active and make the production plant and its output more effective and efficient over time [49,114,192,198]. ...
This literature review study presents and discusses the learning strategies of organizations participating in sustainable energy demonstration projects. It finds that academic, commercial, and governmental organizations build on six major learning strategies. The first learning strategy is to capture intellectual property and benefit from knowledge spillovers. The second learning strategy comprises the building of a series of prototypes that are technically and commercially fit for purpose. The third learning strategy aims at operating production plants that produce the prototypes on a large scale. The fourth learning strategy concentrates on exploiting learning curves in these production plants. The fifth learning strategy focuses on creating supply-demand networks that serve increasing markets. Finally, the sixth learning strategy is to develop governmental regulation and funding schemes that support the emergence of an industrial and societal institutional infrastructure for sustainable energy technology, based on the lessons learned from the demonstration projects. This study also finds that the six learning strategies are facilitated by four key behaviors of participants in demonstration projects, which are mutual trust-building, decision-making in favor of sustainable energy technology, learning-network building, and demonstration program development. To academics, this study provides a comprehensive insight into organizations’ learning strategies in sustainable energy demonstration projects, regarding learning directions and outcomes. Its contribution to practice is that it supports academic, commercial, and governmental organizations in managing their portfolio of learning strategies in new sustainable energy demonstration projects.
... In this work we define an innovation as a successful commercial implementation of a new idea (including a firstof-a-kind idea as well as an existing idea that is rearranged or repurposed) that improves technology performance [28,29,30,31]. Innovations represent significant changes in products or processes that often require deliberate efforts, such as research and development (R&D), to be developed and implemented [29,32,33]. In the cost modeling framework used here, where we refer to changes in the cost equation variables as 'low-level mechanisms' [12], innovations represent the detailed origins of changes to one or more variables. ...
... how things are done) that is relatively inarticulate. Therefore, as an organization learns and increases its efficiency by repeating a set of activities, deepened competence arises from storing and applying tacit knowledge (Pisano, 1996;Benner and Tushman, 2003). ...
... In particular, it remains unclear to what extent different functional areas (such as R&D, manufacturing, and marketing) contribute to a firm's external search strategy and in turn its overall innovation performance (Baldwin and Johnson, 1996;Jansen et al., 2005). Further, more research is needed to explore how such relationships are different for product and process innovation as these two types of innovation are characterized by fundamentally different attributes and determinants (Pisano, 1996(Pisano, , 1997Reichstein and Salter, 2006). ...
... Desde el enfoque de los sistemas de innovación con perspectiva de aprendizaje social, las diferencias en el aprendizaje, que se enfocan en lograr innovaciones en el sistema por medio de redes de actores dispuestos a trabajar por un desarrollo sostenible, pueden explicarse por la existencia o ausencia de condiciones para el aprendizaje (van Mierlo, Leeuwis, Smits, y Woolthuis, 2010). De otro lado, Pisano (1996) trae la reflexión al campo de la mejora de fabricación e innovación tecnológica, en donde especifica que, el aprender haciendo ha ocupado un lugar destacado. El autor menciona que el aprendizaje práctico es esencial para un desarrollo eficiente en entornos donde subyacen aspectos teóricos y prácticos. ...
La presente investigación entiende que la Smart City se manifiesta en una estructura social y organizacional que mejora su desempeño en función no solo de sus tecnologías, sino también, de la acumulación de capital social. Se analizó el capital social desde la teoría de los recursos y las capacidades, entendiéndolo como una capacidad que incide en el desempeño de la SC, este, se relaciona con las capacidades tecnológicas para la innovación y el proceso de aprendizaje tecnológico.
La metodología utilizada fue de tipo mixto secuencial exploratorio y se presentó en tres momentos: el primero de tipo cualitativo, donde se realizó una revisión sistemática de la literatura especializada a través del método de razonamiento deductivo. El segundo, de tipo cuantitativo, donde se usó el método PLS-SEM, y se presentó un modelo que representó el Capital Social en una Smart City. El Tercero, de tipo cualitativo, donde se complementó el modelo a partir de un estudio de caso singularizado y, soportado en el método de la teoría fundamentada como forma análisis hermenéutico, se analizó a un Smart City incluida dentro del IMD Smart City Index: Medellín.
Se concluyó, primero, la SC tiene un asiento en las teorías de la ciudad contemporánea y se expresa en una estructura social/organizacional que consolida el uso sus recursos: tiene una relación intrínseca con la teoría de los recursos y las capacidades; segundo, la capacidad de capital social tiene recursos tales como la visión compartida, la confianza y la interacción social que se relacionan con el aprendizaje tecnológico, el cual es fuente del capital social; tercero, hay una relación significativa entre la interacción Social, la confianza y la visión compartida con el aprendizaje tecnológico, demostrada en el modelo PLS-SEM (construido con la data de los usuarios finales); cuarto, se concluyó, en el estudio de caso, que dentro de la narrativa de otros niveles de usuarios (institucionales) hay prevalencia de los constructos y las variables
configuradas en momentos previos de la investigación, por lo que hay consistencia deductiva traída desde la literatura y da lugar al montaje de los modelos exploratorios.
De esta manera, esta investigación, aporta un modelo PLS-SEM que permite representar los recursos del capital social y el aprendizaje tecnológico de sistemas tecnológicos en una SC. En términos teóricos se aporta en la construcción de conocimiento asociado a los estudios de la SC; en términos metodológicos, aporta un método replicable para el análisis de sistemas tecnológicos de SC cuando sea necesario representar recursos del capital social y su relación con el aprendizaje tecnológico, porque la metodología no solo permitió la construcción del modelo propuesto, sino su expansión y posterior descripción tras el establecimiento de la relación entre lo cualitativo, lo cuantitativo y la teoría fundamentada.
La investigación espera aportar en los ejercicios de tomadores/as de decisión (decision-making) y en las políticas y estrategias en ciencia, tecnología e innovación de las SC objeto de estudio.
... In so doing, the firm accomplishes industrial scale and mass production (Tambunlertchai, 2015). Many of the academic developers have neglected the NPD activities in the back-end group (Lorenz, Raven, & Blind, 2017;Pisano, 1996). The study of Gerwin and Barrowman (2002) The practical NPD literature commonly distinguishes between product development part and production process development part (Brown & Eisenhardt, 1995;Lorenz et al., 2017). ...
The purpose of this research was to provide an appropriate academic and practical guideline for understanding open innovation (OI) in new product development (NPD) among Thai small and medium enterprises (SMEs). However, only a few studies have demonstrated that OI is used by Food SMEs. Their OI generative mechanism (GM) remains poorly understood.
To understand the role of OI in this change, specifically OI logics and practices in food SME’s NPD, and the Food-Machinery framework by Bigliardi and Galati (2013a) have been chosen to analyze 109 NPDs of 2 Thai food machinery SMEs using a critical realistic (CR) perspective. Five rounds of semi-structured interview and document review methods were utilized for data collection.
This research identified evidence that dynamic capabilities (DCs) mobilized in OI NPD is the OI GM. The results also demonstrated the Food-Machinery Flexibility Model and its six distinctive patterns within the same model, were successfully implemented by the integration of 3 OI logics (i.e., coupled OI logic with outbound dominance, coupled OI logic with inbound dominance, and no OI logic) and 8 OI practices (i.e., employee involvement, outward IP licensing, customer involvement, outsourcing R&D, inward IP licensing, insourcing R&D, supplier involvement, and regulatory body involvement) to reveal the OI knowledge in empirical domain, and consequence the analysis of 9 DCs (i.e., sensing, seizing, inventive capacity, transformative capacity, innovative capacity, absorptive capacity, connective capacity, desorptive capacity, and legally compliance capacity) revealed the underlying OI GM in the real domain. The knowledge flows have been analyzed by focusing on food recipe development at two levels of the NPD process, namely laboratory scale and industrial scale.
Finally, the identification of OI GM demonstrated the relationship between OI and DCs. The development of DCs can strengthen OI practice within the organization. They are mutually reinforcing each other. Six distinctive patterns within the same model demonstrated the ability of investigated food SMEs to develop their 14 mechanisms (DC sequences) to ensure the efficacious implementation of OI logics and practices in food NPDs, and flexibility to the nature of the collaborative strategy associated with each NPD. The results exposed Thai SMEs switching their business from generic food machinery companies to the innovation intermediary. The contribution of this research supported both academic’s view on OI literature; understanding OI GM through the OI logics, OI practices and associated DCs mechanisms in the NPD process, and food practitioner’s view by providing an appropriate 6 OI guidelines for the food innovation intermediary. The research had a limitation due to a comparison between 2 SMEs’ NPDs. Future research could benefit from exploring additional food SMEs.
... All these information are helpful, particularly when the rivals need more pertinent information in a hazy business climate. Additionally, participating in R&D activities is fundamentally a "learning-before-doing" strategy that produces beneficial information (Pisano, 1996). Companies typically "learn by doing" via cumulative commercial output, which suggests that productivity increases as business produces more and more and unit production costs decrease. ...
Long-term economic development requires R&D, and countries develop economic policies that envision innovation development programs. However, economic policy uncertainty frequently distracts from economic outcomes. The study aims to investigate the long-term impact of economic policy uncertainty on R&D, with a particular emphasis on Asian countries. Because the selected countries possess typical dynamics, such as bilateral trade associations, technological expertise, and economic activities, the study employs the second-generation panel cointegration method from 2003 to 2018. The cointegration results of Westerlund (Oxford Bulletin of Economics and Statistics 69:709-748, 2007) confirmed a stable, long-run relationship between R&D, economic policy uncertainty, economic growth, and trade openness. According to the CS-ARDL findings, an increased economic policy uncertainty reduces R&D. Due to great economic collaboration among Asian countries; the effects are transmitted to R&D, especially international trade, business confidence, and economic growth. As a result, countries divert their resources to deal with the consequences, and investment suffers, whereas economic growth and trade openness help to expand R&D in the long run. It is evident that as economic growth accelerates, countries tend to invest more in R&D, and international trade encourages R&D. To promote prosperity in Asian countries, policymakers must design sound economic policies to counter unexpected events.
... 4 For an overview of the learning curve literature, see Yelle (1979), , Syverson (2011). For empirical studies in other sectors, see, e.g., airframes (Wright 1936), automobile assembly (Baloff 1966), chemical processing (Lieberman 1984), construction (De Jong 1957), machine tools (Hirsch 1952), petroleum refining (Hirschmann 1964), pharmaceuticals (Pisano 1996), and semiconductors (Hatch and Mowery 1998). 5 Most learning models focus on manufacturing; see, e.g., Fine and Porteus (1989), Li and Rajagopalan (1998), Mazzola and McCardle (1997), Li et al. (2015), Bavafa and Jónasson (2021), Gao et al. (2022). ...
... 4 For an overview of the learning curve literature, see Yelle (1979), Argote and Epple (1990), Syverson (2011). For empirical studies in other sectors, see, e.g., airframes (Wright 1936), automobile assembly (Baloff 1966), chemical processing (Lieberman 1984), construction (De Jong 1957), machine tools (Hirsch 1952), petroleum refining (Hirschmann 1964), pharmaceuticals (Pisano 1996), and semiconductors (Hatch and Mowery 1998). ...
The rise of contract farming has transformed millions of farmers' lives. We study a new class of contract farming problems, where the farmer holds superior information and can invest effort to improve productivity over time. Despite their prevalence, the literature offers little guidance on how to manage such farmers with dynamic incentives. We build a game‐theoretic model that captures the dynamic incentives of learning and gaming, with hidden action and information. We characterize the optimal contract: it internalizes both the vertical and intertemporal externalities, with performance pay and deferred payment; the performance pay is to motivate the farmer to invest and improve the relationship‐specific productivity; the deferred payment is to ensure that the farmer is willing to share information and behave honestly over time. Even with random yield, the optimal contract can still have a simple implementation of yield‐adjusted revenue sharing policy. Using real data, we show that the learning effect is significant. We then quantify when and how contract farming can improve smallholder farmers' productivity and income, creating shared value. We find when buyers have a long‐term perspective and can internalize the benefit of farmer improvement, they will pay higher prices to ensure farmers' long‐term viability. Our results inform the policy debate on contract farming: traditional pro‐competitive policies (based on spot transactions) can be counterproductive for modern agrifood value chains, hurting both buyers and farmers. This article is protected by copyright. All rights reserved
... The need for further research on the early phases of production development has been previously highlighted (Lager 2002;Lim et al. 2006;Pisano 1996), with particular emphasis on the knowledge gap relating to early phases and activities (Frishammar et al. 2013;Kurkkio et al. 2011). This issue was initially raised in the context of the process industry. ...
Assembly systems require to be designed considering flexibility from a holistic perspective to produce the variety of current and future product generations. Reactive ad hoc changes after realizing both the product and assembly system designs require considerable effort and may even be impossible. A systematic collaborative approach that concurrently considers the early phases of product and assembly system development appears to be essential for working with long-term changes. To this end, a greater understanding of the working procedures and design activities concerning flexibility is required. In this paper, this is investigated based on a theoretical framework and a multiple case study at a world-leading manufacturer of heavy-duty vehicles. As a result, a developed early phase design process to enable long-term flexibility in assembly systems is presented. The theoretical implications provided and the findings are also relevant to those involved in the design process of flexible assembly systems.
... Firms move from intention to outcome by deploying routines (Nelson and Winter, 1982), and the ability to reliably perform and adapt these routines best describes the firm's dynamic capabilities (Helfat and Winter, 2011;Winter, 2003). Capabilities develop over time through learning (Teece, 2009;Winter, 2000;Zollo and Winter, 2002); knowledge is developed throughout the firm with the purpose of doing useful things, and sometimes transforming what is done, or how (Cohen et al., 1996;Pisano, 1996Pisano, , 2000. Learning tends to occur in the teams that populate the firm because individual team members' work-related interactions among themselves can enable them to make sense of complex situations and attain insights that they cannot reach on their own (Edmondson, 2002;Senge, 1990). ...
Scanning the environment for information about competitors, technology trends, or customer needs allows firms to sense opportunities and threats, which supports dynamic capabilities and helps firms remain competitive over time. There has been significant theoretical development on the cognitive antecedents of dynamic capabilities—so-called dynamic managerial capabilities. In this study, I propose a novel mechanism through which managerial cognition can scale to a collective level in support of sensing capabilities and consider how organizational design may influence this relationship. Specifically, I posit that high-construal managers engage in more environmental scanning than low-construal managers do, because their mental horizons are broader and encompass further alternatives, and that over time their behavior is modeled by their team. I also suggest that managers’ degree of task-related interdependence with peer managers across the firm influences the direction of this relationship, with low interdependence reversing it. I find support for my theory using multiple-source, time-lagged data gathered from 88 managers and their team, thereby offering key implications for theory and practice.
... A study suggests that the type of innovation, stage of innovation, scope of innovation, and type of organisation are important factors influencing the innovation management approach (Damanpour, 1991). Tidd proposed a model for innovation management (Tidd, 2001), saying that past innovation research has mainly been conducted on US high technology firms (Pisano, 1996;Christensen, 1997) and with regard product development based on the practices of Japanese manufacturers of consumer durables such as electronics or automobiles (Clark and Fujimoto, 1991). Tidd (2001) suggests an innovation space model of categorising innovation on the axes of degree of innovation (i.e., disruptive, radical, incremental) and type of innovation (i.e., process, product, service). ...
Start-ups have gained media attention since Google, Facebook and Amazon were
launched in the 1990s. The book Lean Start-up, published in 2011, was another important
milestone for digital start-up literature. As unicorn companies emerge around the world,
topics highlighted in the news include the vast amount of capital that digital start-ups are
raising, the ways in which these digital ventures are disrupting industries, and their global
impact on digital economy. However, digital start-ups, digital venture ideas, and their
venture creation process lack a unified venture creation model, as there is a gap in the re-
search on entrepreneurial processes in a digital context. This research is an explorative
study of the venture creation process of innovative digital start-ups that examines what is
missing from entrepreneurial process models in a digital technology context and investi-
gates how early stage digital start-ups conduct the venture creation process, starting with
the pre-phase of antecedents and ending with the launch and scaling of the venture.
The research proposes a novel process model of innovative digital start-up venture crea-
tion and describes the nature and patterns of the process. A conceptual model was devel-
oped based on the entrepreneurship, information systems, and digital innovation litera-
ture and empirically assessed with a multi-method qualitative research design. The data
collected from semi-structured interviews, internet sources, and observation field notes
covered 34 innovative digital start-ups and their founders. Interviews were conducted in-
ternationally in high-ranking start-up ecosystems, and the data were analysed with the-
matic analysis and fact-checked by triangulating internet data sources. The contribution
to entrepreneurship theory is a new illustrative model of the venture creation process of
innovative digital start-ups, including the emergent outcome of the process having a digi-
tal artefact at its core (e.g., mobile apps, web-based solutions, digital platforms, software
solutions, and digital ecosystems). Digital platforms and their multiple roles in the process
are presented, as well as the role of critical events as moderators of the process which
trigger new development cycles. During the venture creation process, the recombining of
digital technologies, modules, and components enabled by digital infrastructures, plat-
forms, and ecosystem partners represent digital technology affordances. This recombina-
tion provides opportunities for asset-free development of digital venture ideas.
... In the process industries, the development of functional prototypes is replaced by test runs in pilot plants or full-scale production [Frishammar et al. (2014)]. During pilot plant work, processability (manufacturability) is secured, test batches for B2B customers are produced, and adequate process conditions are ascertained [Lager (2000); Pisano (1996)]. In the process industries, the lead-time for product development is often long from ideation to implementation in production plants [Bergfors and Lager (2011)], since the product development cycles are often extended in order to protect B2B customers and consumers from unexpected problems, often necessitating time-consuming pilot plant testing or full-scale production trials for validation [Pisano (1997)]. ...
In an exploratory inquiry, involving informants in 19 global manufacturing companies in six sectors of the process industries, ideation, and concept integration during the pre-development of non-assembled products was studied. New and previously deployed constructs and concepts related to innovation in a process-industrial context have initially been developed, refined, and empirically tested. The findings demonstrate the importance of an early integration of constructs and concepts for raw material innovation, innovation-related process technology, and product innovation, as a prerequisite for successful ideation of new or improved products in the process industries. Companies in different sectors of the process industries can implement and use the novel “integrated framework” for contextualization and conceptualization of new product ideas in their development or reconfiguration of an enhanced work process for non-assembled products.
... Remanufacturing process innovation has been regarded as the essential means to seek sustainable development and improve the competitiveness of enterprises [11,12]. Taking Apple's progress report [13], for example, Daisy, the traditional disassembling robot, can disassemble an iPhone into various parts, whereas Dave, the latest disassembling robot, can further disassemble the touch engine to recover magnets containing rare earth elements. ...
Efficient and low-cost remanufacturing can be achieved through process innovation. Consequently, the question of whether government subsidies for remanufacturing process innovation will stimulate improvement in this area and thus affect the closed-loop supply chain is worth discussing. To answer this question, we establish a closed-loop supply chain model consisting of a manufacturer and a retailer, taking into account both remanufacturing process innovation and government subsidy. This is done in order to explore the impact of remanufacturing process innovation on the closed-loop supply chain from the perspective of government subsidies. Moreover, the government subsidizes the manufacturer according to the improvement of remanufacturing process innovation levels. Specifically, we analyze the optimal decisions and the social welfare in two models—the benchmark model without government subsidy, and the government subsidy model. Our main findings are threefold. The optimal decisions of the two models vary with the proportion of new products’ production cost and remanufactured products’ production cost. The government subsidy for process innovation does not necessarily improve the profits of the manufacturer, the retailer, and the supply chain system. Moreover, there is a threshold; the government subsidy can hurt the retailer’s profits, and the retailer has no motivation to participate in the sale of new products when the government subsidy is below that threshold. The government subsidy for process innovation does improve overall social welfare and has a lesser environmental impact. The conclusions are also verified by numerical analysis.
... Firms move from intention to outcome by deploying routines (Nelson and Winter, 1982), and the ability to reliably perform and adapt these routines best describes the firm's dynamic capabilities (Helfat and Winter, 2011;Winter, 2003). Capabilities develop over time through learning (Teece, 2009;Winter, 2000;Zollo and Winter, 2002); knowledge is developed throughout the firm with the purpose of doing useful things, and sometimes transforming what is done, or how (Cohen et al., 1996;Pisano, 1996Pisano, , 2000. Learning tends to occur in the teams that populate the firm because individual team members' work-related interactions among themselves can enable them to make sense of complex situations and attain insights that they cannot reach on their own (Edmondson, 2002;Senge, 1990). ...
... This finding supports learning theories about the benefits of codification and feedback (Adler and Clark, 1991;Di Stefano et al., 2016;Edmondson et al., 2003;Pisano, 1996;Zollo and Winter, 2002). While this result is relatively straightforward from the perspective of management research, it contradicts prior wisdom about EOP techniques impeding waste reduction. ...
... We argue here that tacit and explicit knowledge are complements rather than substitutes. Pisano [10,17] distinguished problem solving as learning-before-doing, appropriate in a situation with an established knowledge base, and learning-by-doing, suitable in a setting with little reliable knowledge. He contended that both have merits depending on the knowledge environment. ...
Knowledge has not generated the gains in efficiency and competitive advantage promised over the past three decades. One reason lies in the existing taxonomies which remain both abstract and difficult to apply. This research examines knowledge from the perspective of economics. It discusses tacit and explicit knowledge in terms of complements, substitutes, and normal or inferior goods, and consider their elasticity of demand and of supply.
This new model offers a practical matrix based on depth and breadth of knowledge, which can be readily applied by firms in any industry. The proposed model can be used to diagnose the existing stock of knowledge, recognize shortages and the cost to fill them, and identify essential knowledge that should be protected.
... The use of small-scale laboratory experiments to model future product performance resulted in a lower cost per experiment, an effective learning model (cf. Pisano, 1996). In their pursuit to reduce technology uncertainty by interacting with co-innovators as well as using a variety of lowcost probes, enabled successful ventures also to strategically select (and execute) new alternatives in an opportunistic manner. ...
Prior research on venture acceleration has in particular examined the impact of accelerators and their design on venture learning. As many accelerators are predominantly catering to digital start-ups, we know little about how typical accelerator mechanisms affect important outcomes like investor readiness and attractiveness in the context of science-based, or deep-tech ventures, i.e. ventures that commercialize technological developments and innovations. We investigate this largely unexplored question by looking at the relationship between accelerator-based experimental learning and outcomes across three indicators of venture performance. While all ventures in our sample received the same accelerator treatment, we identified the emergence of two distinctly different learning paths over time, culminating in different venture outcomes upon exit of the accelerator. We explore linkages between these two learning paths and two venture conditions of technological readiness and prior market knowledge in the team. Our findings contribute to the acceleration literature by revealing a more nuanced view of how learning occurs in an accelerator and how respective strategies may link to venture performance. Our insights are important for accelerator design and practice.
... All these items of information are useful, especially when the competitors lack relevant knowledge in an uncertain business environment. In addition, engagement in R&D activities is essentially an approach of "learning-before-doing" to generate useful knowledge [38]. In normal times, firms "learn by doing" from cumulative commercial production, which means that the productivity increases and unit production cost declines as firms produce more and more. ...
Previous studies have not provided consistent conclusions regarding the impact of uncertainty on research and development (R&D) investment. While most of the previous literature has focused only on one or a small group of countries, this study examines the effect of uncertainty on R&D on the basis of a sample covering 109 countries from 1996 to 2018. The country-level uncertainty is measured using the “World Uncertainty Index”, which has recently been developed by Ahir et al. (2018). By estimating a panel data fixed-effects regression model, it is found that uncertainty has a significantly negative impact on R&D investment at the country-level aggregate scale. We also find that uncertainty depresses the number of R&D personnel and patent applications, although the effect on R&D personnel is not statistically significant. These findings imply that high uncertainty poses a considerable threat to global innovation and technological progress. Heterogeneity analyses across different country groups demonstrate that, although the impact of uncertainty on R&D is not statistically significant in some country groups, its effect is always negative and no positive effect is observed.
... Second, we employed a 5-point Likert-scale in comparison to the lowest 20% of firms in the industry, and the top 20% of firms in the industry [Pisano (1996) argues that capabilities are activities that a firm can do better than its competitors] (CAPA2). • We apply technology with excellence. ...
Purpose of the paper: By proposing a model of SMEs’ entry in foreign markets characterised by uncertainty, we test the relationships among the implementation of a global niche strategy, the perception of lower competition, and international performance. Methodology: Hypotheses are tested on a sample of 110 Australian firms by applying structural equation modelling through the PLS-SEM technique. Results: Our results support the idea that entrepreneurial firms need to create their own environment and, at the same time, control it by exerting high levels of control on manufacturing and technological capabilities and by vertically integrating production processes. Research limitations: More samples from more countries would increase the generalisability of the results. The operationalisation of the components of the global niche strategy which resulted as non-significant need further refinement. Longitudinal studies are required to measure the sustainability of the global niche strategy over time. Practical implications: A customer focus instead of a country focus can help manage perceived uncertainty while growing internationally. Furthermore, decision makers should leverage on product uniqueness through a continuous refinement of technology thanks to insourced production processes. Originality of the paper. To date, no study has advanced a model to represent firms’ internationalisation by considering a process that starts with the formation of strategic antecedents - here represented by the components of the global niche strategy - of international performance.
... Innovation in supply networks should be understood not only as firm-level or product/service innovation but also as process innovation (Pisano, 1997) or administrative innovation, such as the adoption of total quality management (TQM) among a set of network actors (Westphal, Gulati, & Shortell, 1997;Young, Charns, & Shortell, 2001). Studying how network characteristics may drive process innovation, rather than just product innovation, is essential because in many settings the two types of innovations are largely independent-e.g., the automotive, electronics, or defense industries (Pisano, 1996). Process innovation involving buyer and supplier has been studied in the past, for example, in the cases of electronic data interchange systems (Narayanan, Marucheck, & Handfield, 2009) and inter-firm product configuration systems . ...
... Technical competencies refer to intangible resources that assist in attaining competitive advantage (Prahalad & Hamel, 1994;Galunic & Rodan, 1997;Rahman et al. 2016). As stated by Pisano (1996), entrepreneurs use of technical competencies in sustaining competitive advantage and increasing venture performance. Martin and Staines (1994) emphasised that technical competencies include the ability to use and adopt technical skills, techniques and tool-handlings applicable to the business. ...
SMEs financial success contributes to the nation`s GDP and helps in jobs creation, while SMEs financial failure will lead to issues, such as low job creation and Non-Performing Loans. From the perspective of the Sultanate of Oman, the SMEs financial performance is one of the government major concerns due to its significance and implications on the future of the national economy. Thus, it is worthwhile to assess the SMEs financial literacy and entrepreneurs' competencies (EC) as enablers of SMEs financial performance betterment. However, review of the literature and the practical evidence available give the impression that each sub-dimensions of entrepreneur competencies (EC) does not affect identically on SMEs financial performance. Therefore, it has become important to understand the financial literacy and entrepreneur competencies (EC) sub-dimensions effect on SMEs financial performance so that their significance and importance can be identified. This study aims to provide empirical evidence about the effect of financial literacy and each sub-dimensions of entrepreneur competencies (EC) on SMEs financial performance in the Sultanate of Oman. Besides, this research tends to examine the role of firm resources availability and government support as moderators. Resource-Based View Theory (RBV) will be adopted to extend the existing literature on SMEs financial performance determinants from SMEs entrepreneurial perspective. As research novelty and theoretical contribution, this research study's the interactions of financial literacy and each sub-dimensions of entrepreneur competencies (EC) with firm resources availability and government support, as moderators. The convenience sampling method will be used with SMEs sample size of 200 and 300 questionnaires will be distributed to SMEs founders/owners in Sultanate of Oman. The structural equation modelling (SEM) through partial least square (PLS) approach will be used to test the study hypotheses. The present research findings are expected to broader the picture of entrepreneur competencies (EC) and SMEs performance researches by revealing the financial literacy and each sub-dimensions of entrepreneur competencies (EC) effect on SMEs financial performance. Further, it may confirm the moderating role of firm resources availability and government support on SMEs financial performance.
... Technical competencies refer to intangible resources that assist in attaining competitive advantage (Prahalad & Hamel, 1994;Galunic & Rodan, 1997;Rahman et al. 2016). As stated by Pisano (1996), entrepreneurs use of technical competencies in sustaining competitive advantage and increasing venture performance. Martin and Staines (1994) emphasised that technical competencies include the ability to use and adopt technical skills, techniques and tool-handlings applicable to the business. ...
SMEs financial success contributes to the nation`s GDP and helps in jobs creation, while SMEs financial failure will lead to issues, such as low job creation and Non-Performing Loans. From the perspective of the Sultanate of Oman, the SMEs financial performance is one of the government major concerns due to its significance and implications on the future of the national economy. Thus, it is worthwhile to assess the SMEs financial literacy and entrepreneurs' competencies (EC) as enablers of SMEs financial performance betterment. However, review of the literature and the practical evidence available give the impression that each sub-dimensions of entrepreneur competencies (EC) does not effect identically on SMEs financial performance. Therefore, it has become important to understand the financial literacy and entrepreneur competencies (EC) sub-dimensions effect on SMEs financial performance so that their significance and importance can be identified. This study aims to provide empirical evidence about the effect of financial literacy and each sub-dimensions of entrepreneur competencies (EC) on SMEs financial performance in the Sultanate of Oman. Besides, this research tends to examine the role of firm resources availability and government support as moderators. Resource-Based View Theory (RBV) will be adopted to extend the existing literature on SMEs financial performance determinants from SMEs entrepreneurial perspective. As research novelty and theoretical contribution, this research study's the interactions of financial literacy and each sub-dimensions of entrepreneur competencies (EC) with firm resources availability and government support, as moderators. The convenience sampling method will be used with SMEs sample size of 200 and 300 questionnaires will be distributed to SMEs founders/owners in Sultanate of Oman. The structural equation modelling (SEM) through partial least square (PLS) approach will be used to test the study hypotheses. The present research findings are expected to broader the picture of entrepreneur competencies (EC) and SMEs performance researches by revealing the financial literacy and each sub-dimensions of entrepreneur competencies (EC) effect on SMEs financial performance. Further, it may confirm the moderating role of firm resources availability and government support on SMEs financial performance.
... LBD is documented in an extensive literature on learning or experience curves in manufacturing improvement and technological innovation domains (Epple, Argote, & Devadas, 1991;Macher & Mowery, 2003;Pisano, 1996;Von Hippel & Tyre, 1995), and is rooted in the basic assumption that performance is explained by knowledge accumulation from historic experience (Barrios & Strobl, 2004). Generally, LBD is identified as a dynamic process for accumulating experience, knowledge, or know-how as a by-product of repeated processessuch as manufacturing -that improve process efficiency and consistency. ...
The concept of absorptive capacity (AC) of firms (Cohen and Levinthal 1989 and 1990) is a foundational feature of organizational learning and adaptation that has had enormous influence in international business (IB), and innovation studies and management research in general. In this tribute to Dan Levinthal, we discuss the close connection between AC and learning – two areas central to Dan Levinthal’s research – in relation to different contexts where AC comes into play in extant IB research. We discuss four specific aspects of the nexus of AC and learning in the context of IB: (1) bridging between intra- and inter-firm learning; (2) a routine-based framing of AC that emphasizes processes and capabilities underlying seeking, assimilating, and innovation in a global setting; (3) the role of socially enabling mechanisms, and (4) the logic of learning through trial and error experiments within firms and countries.
... Investigating experimentation is also relevant because its role is fundamental to innovation and operations management. Experimentation accounts for most of the innovation time and costs (Thomke, 1998), providing a key mechanism for greater agility (Eisenhardt & Tabrizi, 1995;Thomke, 1998), and enabling improved product quality and accelerated learning (Adler & Clark, 1991;Pisano, 1996;Lapré, Mukherjee, & Van Wassenhove, 2000;Bohn & Lapré, 2011). Firms experiment for one reason: to learn. ...
Digital technology is fundamental to experimentation, learning, and the rate of innovation. Digital technology facilitates the rapid distribution of experimental design and debug information. However, we should consider how this fundamentally changes organizational learning and experimentation when managing the rate of product innovation. We address this issue by investigating what drives experimentation‐based learning in high‐tech product innovation and production. The longitudinal dataset in our study consists of 216 projects over a period of almost 5 years, involving thousands of digitally recorded design iterations and design debugs. Based on a time series linear regression analysis, we demonstrate that learning from an accumulation of completed projects drives learning in experimentation more than failure experience in successfully completed design debugs. Furthermore, we show that processing iterations and debugs rapidly enhances the speed of product innovation learning as this allows for short‐loop experimentation that restricts superstitious learning when conditions change over time. The results also show this can be achieved using digital tools as a source of agility.
This study aims to analyze the conditions of green organizational management and technological-innovation. The analysis departs from assuming that green organizational management innovation and technological innovation has a direct influence on sustainable green organizational performance under the assumption that sustainability mediates the relationship between green management and green technological innovation and green organizational performance. The method used is the meta-analytical-reflective based on the conceptual, theoretical and empirical review of the literature. It is concluded that green organizational management and technological innovation have a direct effect on sustainable organizational performance.
We are increasingly challenged to operate within our planetary boundaries, while delivering on United Nations (UN) Sustainable Development Goal (SDG) 2030 targets, and net-zero emissions by 2050. Failure to solve these challenges risks economic, social, political, climate, food, water, and fuel security. Therefore, new, scalable, and adoptable circular economy solutions are urgently required. The ability of plants to use light, capture CO2, and drive complex biochemistry is pivotal to delivering these solutions. However, harnessing this capability efficiently also requires robust accompanying economic, financial, market, and strategic analytics. A framework for this is presented here in the Commercialization Tourbillon. It supports the delivery of emerging plant biotechnologies and bio-inspired light-driven industry solutions within the critical 2030-2050 timeframe, to achieve validated economic, social, and environmental benefits.
Organizational learning scholarship has shown that experience accumulates in manufacturing operations over time, affecting organizational productivity. To date, we have a limited understanding of how the loss of this experience by decay conditions R&D productivity. We advance this research by developing a model in which a scientist's R&D productivity is a function of her or his technological expertise. This technological expertise is subject to loss over time. Using a long panel (1970–2007) of data from the U.S. biotechnology industry, we find that knowledge loss decreases a scientist's R&D productivity because it reduces the technological expertise the scientist possesses and uses in R&D projects. Knowledge loss also affects R&D productivity through spillovers of knowledge. In our model, spillovers of external knowledge jointly depend on a scientist's network centrality and cohesion, the scientists' prior knowledge, and the extent to which external knowledge is available. Our analysis indicates that since knowledge loss limits decreases the scientist's prior knowledge, it diminishes her or his ability to assimilate and use external knowledge present in a firm and an industry. This in turn decreases the scientists' R&D productivity. Knowledge loss thus is critical to understand R&D productivity and knowledge spillovers.
Purpose
This study aims to investigate how radio frequency identification (RFID) is used and opinions about RFID in two world-leading logistics companies and four organisations in their supply network. Operations strategy was used to understand the sources of operations improvement and associated competitive advantage. However, the complexity of operations strategy hampers an evaluation of the benefits of RFID for logistics processes. We can evaluate RFID applied in logistics processes by thoroughly applying the theories of operations strategy.
Design/methodology/approach
Participants were recruited based on their roles and level of experience using non-probability purposive sampling. The findings were checked with participants to confirm interpretations and to ask confirming questions as necessary. Interviews were conducted as video chats. NVivo Pro was used for the fragmentation, classification, management and analysis of the primary and secondary data, allowing themes and relationships to emerge inductively. The literature was compared with the primary data.
Findings
The findings reinforce the argument that a firm can improve more than one performance objective at a time; show the relevance of technology and an operations performance objective; support the argument that top management strategies to implement technology should be aligned with the operations strategy and business aspirations.
Research limitations/implications
This research area would benefit from more detailed investigation to strengthen the arguments for the relationships between RFID capabilities and elements of operations strategy for logistics processes. The findings indicate that top management support of strategically aligned RFID projects will have the best chance of success if they create and leverage valuable data whilst addressing identified competitive priorities.
Practical implications
Smart connected devices, such as RFID, give firms access to big data, which can be used to develop long-term processes, to achieve competitive advantage and access new forms of economic value. RFID cumulatively influences the operations performance objectives of cost, quality, flexibility, speed, dependability and technology. Business strategies based on technology should align with operations strategy.
Social implications
The sharing of operational performance results, both before and after the implementation of RFID, will help to build learning within operations, increase the support of senior management and improve the performance of logistics processes with the associated benefits for society at large.
Originality/value
RFID is often evaluated in terms of theoretical technical or cost benefits. This research evaluates RFID by assessing and suggesting how it can contribute to operations strategy.
We elucidate why lithium-ion battery costs declined. We disentangle cost change mechanisms and quantify their effects, and find that research and development, especially in chemistry and materials science, played an outsized role in cost reduction.
Although one school of thought in the university-industry interactive literature is that universities learn from prior collaboration, we posit that any potential knowledge learning effects depend on the type of collaboration. Our empirical findings confirm that the use of collaboration exploitation, exploration and balancing strategy of ambidexterity all improve a university’s innovation. We also posit that proactive searching allows universities to leverage their collaboration exploitation and exploration. In contrast, when universities combine ambidexterity with a proactive search strategy, the negative consequences for university innovation become more pronounced. To test this integrative model of U-I collaboration, we leverage a unique and detailed longitudinal dataset on the 110 top U.S. research universities and the top 200 R&D performing firms to account for a large share of research papers published in the U.S. in the last 19 years. Poisson and negative binomial regression models are used to test the hypotheses in panel data of 2090 university-year cases. We find support for our theoretical model.
Basic materials such as steel and cement have been instrumental to modern society, but the production requires high energy inputs and is associated with significant CO2 emissions. Long investment cycles, slow turnover rate of the capital stock, and high capital intensity mean that basic materials industries are among the economic activities that will be the most difficult to decarbonize. Although the importance of addressing industrial emissions has been increasingly recognized, the development of measures and technologies that could deliver deeper emissions cuts has been relatively slow. In this paper, we present a conceptual framework focusing on four categories of barriers—market, technology, regulatory, and coordination—that hamper deep decarbonization in the basic materials industries. We use the Swedish basic materials industries and policy context to illustrate how the proposed framework can be understood and applied and broadly discuss policies that can facilitate the climate transition.
This study examines proactive decision-making and design flexibilities in new product development (NPD) as critical forms of strategic flexibility. The conceptual framework identifies market and technological alignment as drivers of proactive strategic flexibility, and examines their association with strategic NPD performance and fit with market demands. The model is tested using data collected from a sample of 103 European manufacturing firms. The results suggest that market and technological alignment are important in developing proactive decision-making and design flexibilities, which in turn have significant effects on strategic NPD performance and NPD fit with market demands. Overall, the study will help managers develop a better understanding of key similarities and differences in proactive strategic flexibility practices and decide how to allocate resources to achieve market and technological alignment supporting their NPD activities. The paper provides novel insights into proactive strategic flexibility in NPD, its alignment with market and technological environments, and its effects on product development performance.
The aims of this study are to gain further insight into the contingent performance effects of repository knowledge management systems (KMS) use. While prior research has laid the foundations, a nuanced understanding of the interplay between the individual's personal and social knowledge bases and KMS usage behaviors is missing. Drawing from prior information systems literature, we identify two components of KMS use, usage frequency and usage intensity. We examine the influence of knowledge bases on individual performance, and the moderating influence of the usage behaviors. We test the hypothesized research model on usage and performance data from 18,219 real estate agents. We find support for different pathways to individual performance based on configurations of knowledge bases and usage behavior. Overall, the study provides an integrated view of the interplay between the three constituents of technology-based learning – cognition, behavior, and performance.
Research Summary
That capability development is subject to time compression diseconomies (TCD) is well-known in the strategy literature. However, so far, there is limited attention paid to its origins, i.e., why it exists, and demonstrating it empirically. In the context of fertility clinics in the UK, we show that faster experience accumulation is associated with lower success rates; i.e., time compression in experience accumulation results in shallower learning curves. We also show that TCD is exacerbated for clinics that mainly treat complex cases and is mitigated for clinics that employ an integrator to coordinate across the different specialist functions involved in the treatment process. We propose differential learning rate as the mechanism that underlies TCD, and develop implications for firm capabilities and sources of competitive advantage.
Managerial Summary
As firms pursue new opportunities, it is intuitive to grow fast. Rapid growth has many advantages, including a quicker payback on investment as well as garner first mover advantages. However, there can also be a dark side to such high paced growth. By analyzing data on in-vitro fertilization clinics in the UK, we show that clinics that grew the fastest were slow in improving their level of successful outcomes, while slower growing clinics improved more with increasing experience. This penalty of rapid growth is more severe for clinics that treat more complex cases, but it can be ameliorated by better coordination between specialist activities. Our research serves as a warning that faster isn't always better.
In recent years, emerging markets have come to represent the largest share of global GDP and have made gains in economic development and political influence. In turn, emerging market companies have taken on a new level of importance in driving innovation, local development and global competition. Advancing an integrative view that captures the diversity of innovation among companies in emerging markets, this book highlights the rapid evolution of emerging markets from imitators to innovation leaders. Building upon research conducted by the Emerging Multinational Research Network (EMRN) in collaboration with several universities in North and South America, Europe and China, this rich and expansive collection includes studies of innovation in regions yet to receive focused analysis in the field. The authors also re-examine dominant theories of innovation and capability creation based on a broad range of case studies and research insights. Offering a taxonomy of emerging market innovations, this collection reveals the unique drivers, types, and outcomes of innovation in emerging markets.
We study how becoming an entrepreneur affects an academic scientist’s research. We propose that entrepreneurship will shift scientists’ attention away from intra-disciplinary research questions and toward new bodies of knowledge relevant for downstream technology development. This will propel scientists to engage in exploration, meaning they work on topics new to them. In turn, this shift toward exploration will enhance the impact of the entrepreneurial scientist’s subsequent research, as concepts and models from other bodies of knowledge are combined in novel ways. Entrepreneurship leads to more impactful research, mediated by exploration. Using panel data on the full population of scientists at a large research university, we find support for this argument. Our study is novel in that it identifies a shift of attention as the mechanism underpinning the beneficial spill-over effects from founding a venture on the production of public science. A key implication of our study is that commercial work by academics can drive fundamental advances in science.
When companies in process industries take radical leaps in product innovation, these new products often fall outside the “process window” of existing production processes and hence require extensive production line modifications and radical process change. Consequently, firms need to deal with high degrees of uncertainty, complexity, equivocality and ambiguity in the front-end. These four knowledge problems constitute important challenges to managers and engineers when a new process definition is created. Prior research into the front end of process innovation is limited, and for radical projects close to non-existent. We analyse six radical process innovation projects situated in the food processing industry in the United Kingdom and provide three key contributions. First, we uncover the underlying sources of knowledge problems, and the specific coping mechanisms used to address them. Second, we offer a framework that delineates the relationships between the sources of knowledge problems, the knowledge problems per se, and the coping mechanisms which enable more effective decision-making regarding the creation of process concepts and definitions. Finally, we extend prior studies of the front end by revealing the challenges faced with respect to ambiguity, thus providing a more granular understanding of fuzziness. Altogether, these findings provide important theoretical and practical implications.
The literature on learning in new product development (NPD) documents the processes globally but is short on specifics. Knowledge levels are not clearly conceptualized, nor are there clear devices for documenting knowledge transfers in terms of knowledge levels. This paper presents the methods of a qualitative research approach for measuring knowledge transfer directly in terms of knowledge. The paper specifically addresses the commonly avoided dimension of knowledge, depth. The methods are derived from a real-life comparative case study exploring knowledge sharing in product development. Our focused interview approach has been refined to avoid unproductive digressions by the subjects and certain forms of bias, yet still obtain rich accounts of project events. Evidence of transfer obtained by the interviews is analysed in terms of three knowledge dimensions: scope, depth and action. Methods for aggregating and interpreting data are discussed and an operational flowchart for knowledge transfer coding is proposed.
Problem definition: How much, if at all, does training in product features increase a sales associate’s sales productivity? Academic/practical relevance: A knowledgeable retail sales associate (SA) can explain the features of available product variants and give a customer sufficient confidence in the customer’s choice or suggest alternatives so that the customer becomes willing to purchase. Although it is plausible that increasing an SA’s product knowledge will increase sales, training is not without cost and turnover is high in retail, so most retailers provide little product-knowledge training. Methodology: We partner with two firms and collect data on more than 50,000 SAs who had access to training. We assemble a detailed data set of the training history and individual sales productivity over a two-year period. We conduct econometric analysis to quantify the causal effect of training on sales. Results: For SAs who engaged in training, the sales rate increases by 1.8% for every online module taken, which is a much higher benefit than the direct or indirect costs associated with this training. Brand-specific training has a larger effect on the focal brand; however, there is a positive effect on other brands the SA sells. We also assess how the training benefit varies depending on the SA’s tenure, sales rate prior to training, and number of modules taken. Managerial implications: We present evidence of a novel training mechanism that can be extremely attractive to retailers. Online training tools, such as the one we study, have two characteristics that should not be overlooked. First, it is the brands, not the retailers, that create, develop, and pay for the training content. Second, the incentives are such that SAs invest their own time, rather than time on the job, to train, and this makes the retailer’s investment in the training a profitable proposition.
The literature highlights the importance of corporate entrepreneurship (CE) for improving a company's market and financial performance. This paper extends the literature by focusing on the knowledge-creation processes within a firm's formal and informal CE activities. This multifaceted knowledge, which encompasses organizational, technical, and social dimensions, is developed by individuals or groups and diffused throughout the organization. Whether radical or incremental, this knowledge can generate new skills, which a company can then use to reconfigure the sources of its competitive advantage. This paper also discusses the role of intrapreneurs and CE champions, particularly in the creation and use of social capital, in the development of dynamic competencies.
How should we understand why firms exist? A prevailing view has been that they serve to keep in check the transaction costs arising from the self-interested motivations of individuals. We develop in this article the argument that what firms do better than markets is the sharing and transfer of the knowledge of individuals and groups within an organization. This knowledge consists of information (e.g., who knows what) and of know-how (e.g., how to organize a research team). What is central to our argument is that knowledge is held by individuals, but is also expressed in regularities by which members cooperate in a social community (i.e., group, organization, or network). If knowledge is only held at the individual level, then firms could change simply by employee turnover. Because we know that hiring new workers is not equivalent to changing the skills of a firm, an analysis of what firms can do must understand knowledge as embedded in the organizing principles by which people cooperate within organizations.
Based on this discussion, a paradox is identified: efforts by a firm to grow by the replication of its technology enhances the potential for imitation. By considering how firms can deter imitation by innovation, we develop a more dynamic view of how firms create new knowledge. We build up this dynamic perspective by suggesting that firms learn new skills by recombining their current capabilities. Because new ways of cooperating cannot be easily acquired, growth occurs by building on the social relationships that currently exist in a firm. What a firm has done before tends to predict what it can do in the future. In this sense, the cumulative knowledge of the firm provides options to expand in new but uncertain markets in the future.
We discuss at length the example of the make/buy decision and propose several testable hypotheses regarding the boundaries of the firm, without appealing to the notion of “opportunism.”
This exploratory paper sketches some of the behavioral processes that give rise to the learning curve. Using data from two manufacturing departments in an electronic equipment company, we construct a model of productivity improvement as a function of cumulative output and two managerial variables---engineering changes and workforce training. Exploration of this model highlights the complex relationship between first-order and second-order learning.
Data on 37 chemical products are used to test a number of hypotheses about the learning curve and industrial price behavior. The results document a strong and consistent learning effect. Learning is found to be a function of cumulated industry output and cumulated investment rather than calendar time. Standard economies of scale appear significant but small in magnitude relative to the learning effect. Variations in the slope of the learning curve are linked to differences in R&D expenditures and capital intensity. Market concentration is found to be a strong influence on price flexibility and the timing of learning-related price changes.
Consistent declines in "value added" by manufacturers of petrochemicals (for which price is used as a proxy) is caused by the competitive factors of number of manufacturers and product standardization and the technological factors of production experience and static scale. These relationships imply strategic options available in the pricing of petrochemicals.
Three sets of parallel R&D projects are examined. The data analyzed were gathered by means of Solution Development Records — a form which provides a weekly estimate of the probability of adoption of the approaches under consideration as possible solutions to a technical problem. It is found that the longer an approach is held in a favored position, the more difficult it is to reject. Furthermore, the number of alternative technical approaches considered bears a relation to judged solution quality. Groups producing higher rated solutions generated fewer approaches during the course of the project, and they more closely approach an ideal strategy of trading approaches off on a two-at-a-time basis than do their poorer performing rivals.
We investigate the impact of two kinds of integration-internal and external-on dynamic capability. We use product development activities as a lens with which to focus on the capability-building process in a firm. We first develop a conceptual model of the capability-building process that relates specific problem-solving activities to the generation of organizational capabilities. We derive a measure, 'ynamic performance', that estimates the level of dynamic capability in an organization based on the consistency of its performance. Furthermore, we use the model to motivate a series of hypotheses which link specific processes to the achievement of high dynamic performance. We conjecture that the capacity to integrate diverse knowledge bases through problem solving is the basic foundation of knowledge building in an organization, and is therefore a critical driver of dynamic performance. The hypotheses are tested by drawing on extensive cross-sectional empirical studies of product development in the automobile and mainframe computer industries. The work follows by providing detailed longitudinal cases describing the impact of integration on competence-building processes at Nissan and NEC.
A study seeks to examine the mechanics of international corporate technology transfer and to provide evidence on the level and determinants of technology transfer costs. A rather precise ''resource cost'' definition of costs is employed. The focus of the study is limited to transfers both outward from and inward to but one country: the U.S.A. The transferors are corporations, generally U.S. multinational corporations. The study covers a range of corporate transfers, including the licensing of technology to independent corporations and to governments, to joint ventures, and to wholly owned subsidiaries. It does not include the transfer of technology that might occur, for instance, through the export of capital goods. The analysis highlights features common to transfers that are domestic in scope. The domain of this study is restricted to horizontal transfers falling into the design phase. Data on twenty-nine international technology transfer projects are given in briefs in Appendix A. (MCW)
It is the aim of this article to report on certain phases of the beginning and rise of industrial chemical development in its European cradle, particularly in England, Germany, and France. Keywords (Audience): General Public
Demonstrates that technical change is attributable to experience. The cumulative production of capital goods is used as the index of experience. New capital goods are assumed to completely embody technical change. The assumption is made that the model will be operating in an environment of full employment although reference is made throughout to the case of capital shortage. The implications of this model on wage earners are discussed, and profits and investments are examined. The rate of return is determined by the expected rate of increase in wages, current labor costs per unit output, and the physical lifetime of the investment. Learning is an act of investment that benefits future investors. Further analysis shows that the socially optimal ratio of gross investment to output is higher than the competitive level. (SRD)
Three years ago, I read Michael Polanyi's contribution—as a philosopher—to a symposium entitled Scientific Outlook: Its Sickness and Cure. In a brilliant, penetrating, and delightfully humorous criticism of R. W. Gerard's1 biological contribution, he unerringly diagnosed the sickness of medicine:
The fact that a so learned, ingenious and imaginative survey of living beings should deal so perfunctorily with some of the most important questions concerning them shows a fundamental deficiency of human thinking.... If a rat laps up a solution of saccharine, the rational explanation of this lies in the act that the solution tastes sweet and that the rat likes that. The tasting and liking are facts that physics and chemistry as known today cannot explain. Nothing is relevant to biology, even at the lowest level of life, unless it bears on the achievements of living beings... and distinctions unknown to physics and chemistry... The current idea of
Two examples of plant design are described and an abstract model of the process of design is suggested. The model is used to discuss the search for possible solutions, the strategies for their examination, and the rules for choosing between them. It seems likely that the model applies only to problems requiring novel solutions and not to those for which the form of solution is known, but the choice of parameters to meet conflicting objectives is difficult.
The purpose of the paper is to describe and explain sectoral patterns of technical change as revealed by data on about 2000 significant innovations in Britain since 1945. Most technological knowledge turns out not to be “information” that is generally applicable and easily reproducible, but specific to firms and applications, cumulative in development and varied amongst sectors in source and direction. Innovating firms principally in electronics and chemicals, are relatively big, and they develop innovations over a wide range of specific product groups within their principal sector, but relatively few outside. Firms principally in mechanical and instrument engineering are relatively small and specialised, and they exist in symbiosis with large firms, in scale intensive sectors like metal manufacture and vehicles, who make a significant contribution to their own process technology. In textile firms, on the other hand. most process innovations come from suppliers.These characteristics and variations can be classified in a three part taxonomy based on firms: (1) supplier dominated; (2) production intensive; (3) science based. They can be explained by sources of technology, requirements of users, and possibilities for appropriation. This explanation has implications for our understanding of the sources and directions of technical change, firms' diversification behaviour, the dynamic relationship between technology and industrial structure, and the formation of technological skills and advantages at the level of the firm. the region and the country.
Tape-recorded weekly protocols were gathered from three different engineers engaged on the same problem in a three-way parallel R&D project. Based on these protocols and a post-project interview with each engineer, a model of the individual technical problem solving process is developed. The model is in the form of a process flow chart and details the engineer's interaction with sources of technical information. The results of the study indicate that the problem solver need not view the process as one in which the best solution is to be found for a fixed problem. Often the best approach lies in the direction of adapting to existing solutions the criteria which must be met.
Includes bibliographical references (p. 33-35). Research supported by the Sloan Foundation. Eric von Hippel.
Past research has recognized that both demand and capability influence the allocation of R&D resources. Scholars have had
an easier time getting a grip on demand than on capability. While it has been recognized that knowledge is an important part
of capability, to date, formalization of knowledge and its role in R&D activity has been unsatisfactory. This paper models
the role of knowledge in R&D. Various sources of such knowledge are considered. The model throws a different light on analyses
that employ a “knowledge capital stock,” and also illuminates the dual private and public nature of technological knowledge.
We develop an endogenous growth model with R&D spillovers to study the long-run consequences of offshoring with firm heterogeneity and incomplete contracts. In so doing, we model offshoring as the geographical fragmentation of a firm's production chain between a home upstream division and a foreign downstream division. While there is always a positive correlation between upstream bargaining weight and offshoring activities, there is an inverted U-shaped relationship between these and growth. Whether offshoring with incomplete contracts also increases consumption depends on firm heterogeneity. As for welfare, whereas with complete contracts an R&D subsidy is enough to solve the inefficiency due to R&D spillovers, with incomplete contracts a production subsidy is also needed. Copyright © The editors of the "Scandinavian Journal of Economics" 2009 .
This essay presents an overview of the prevailing theoretical literature on innovation, probes the adequacy of existing theory to guide policy regarding innovation, and sketches some directions for more fruitful theorizing. The focus is on the vast interindustry differences in rates of productivity growth, and other manifestations of differential rates of technological progress across industries. It is argued that the most important policy issues involve finding ways to make the currently lagging sectors more progressive, if in fact that can be done. Theory, to be useful, therefore must organize knowledge and guide research regarding what lies behind the uneven performance of the different economic sectors. In fact prevailing theory cannot do this, for two basic reasons. One is that theory is fragmented, and knowledge and research fall into a number of disjoint intellectual traditions. The second is that the strongest of the research traditions that bear on the differential innovation puzzle, research by economists organized around trying to ‘fit’ production functions and explain how production functions ‘shift’, neglects two central aspects of the problem; that innovation involves uncertainty in an essential way, and that the institutional structure supporting innovation varies greatly from sector to sector. The bulk of the paper is concerned with sketching a theoretical structure that appears to bridge a number of presently separate subfields of study of innovation, and which treats uncertainty and institutional diversity centrally.
The analysis of decision making under uncertainty has again become a major focus of interest. This volume presents contributions from leading specialists in different fields and provides a summary and synthesis of work in this area. It is based on a conference held at the Harvard Business School. The book brings together the different approaches to decision making - normative, descriptive, and prescriptive - which largely correspond to different disciplinary interests. Mathematicians have concentrated on rational procedures for decision making - how people should make decisions. Psychologists have examined how poeple do make decisions, and how far their behaviour is compatible with any rational model. Operations researchers study the application of decision models to actual problems. Throughout, the aim is to present the current state of research and its application and also to show how the different disciplinary approaches can inform one another and thus lay the foundations for the integrated analysis of decision making. The book will be of interest to researchers, teachers - for use as background reading for a decision theory course - students, and consultants and others involved in the practical application of the analysis of decision making. It will be of interest to specialists and students in statistics, mathematics, economics, psychology and the behavioural sciences, operations research, and management science.
This article describes recent developments and prototype software that will extend the range of the three-dimensional (3D) modeler CATIA. CATIA started out as an aerospace industry product but recently has made major inroads in the car industry. New software plans include providing object-oriented databases; using free-form 3D sketchers; providing the ability to manipulate constraints, engineering equations, and tolerances; and modeling assembly processes. A new and quite large European Strategic Programme for Research and Development in Information Technology (ESPRIT) project on assembly has just begun. It's a turning point in computer-aided design (CAD) capabilities.
Product Development Perfor-mance: Strategy, Organization, and Management in the World Auto Industry
- K Clark
- T Fujimoto
Clark, K. and T. Fujimoto, 1991, Product Development Perfor-mance: Strategy, Organization, and Management in the World Auto Industry (Harvard Business School Press, Boston).
The structure of technological knowledge in manufacturing
- R Bohn
- R Jaikumar
Bohn, R. and R. Jaikumar, 1992, The structure of technological knowledge in manufacturing, Working Paper (November).
Manufacturing by design
- D Whitney
Whitney, D., 1988, Manufacturing by design, Harvard Business Review 66, 83-91.
Mastering the Dynamics of Innovations
- J M Utterback
Utterback, J.M., 1994, Mastering the Dynamics of Innovations (Harvard Business School Press, Boston, MA).
Manufacturing progress function Integration and dynamic capabil-ity: evidence from product development in automobiles and mainframe computers
- W Hirsch
Hirsch, W., 1952, Manufacturing progress function, Review of Economics and Statistics 34, 143-155. lansiti, M. and K.B. Clark, 1994, Integration and dynamic capabil-ity: evidence from product development in automobiles and mainframe computers, Industrial and Corporate Change 3(3), 557-605.
The Productivity Dilemma
- W J Abemathy
Abemathy, W.J., 1978, The Productivity Dilemma (The Johns Hopkins University Press, Baltimore, MD).
Evolutionary Innovation
- McElvey
McElvey, M., 1994, Evolutionary Innovation, Ph.D Thesis, Linkopings Universitet, Sweden.
Knowledge and competence as strategic as-sets The Competitive Challenge
- S G Winter
Winter, S.G., 1987, Knowledge and competence as strategic as-sets, in: D.J. Teece (Editors), The Competitive Challenge (Ballinger Publishing Company, Cambridge, MA).
The Development Factory: Unlocking the Poten-tial of Process Innovation
- G Pisano
Pisano, G., 1996, The Development Factory: Unlocking the Poten-tial of Process Innovation (Harvard Business School Press, Boston).
Behind the learning curve
- Adler