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The Hierarchy-Niche Model for Supply Networks
Abstract
Contemporary products are usually designed and produced in large inter‐firm supply networks rather than by single firms. However, our understanding of such networks is still limited due to the lack of network‐wide empirical data as well as the complexity and nonlinearity of supply networks. Herein, we introduce a network formation model to extend and generalize the prior empirical studies that have revealed variable hierarchy topologies and firm‐level transaction specificities across the supply networks for automobiles and electronics. We call it the “hierarchy‐niche model”. With tuning the parameters for transaction specificity and transaction breadth, the model can generate a wide spectrum of stochastic networks that comply with the production hierarchy to varied degrees. Our simulation analyses show that the model‐generated stochastic networks capture hierarchical and cyclic topologies of real‐world automobile and electronics supply networks. The model, which relates firm‐level transaction patterns to network‐wide emergent topologies, can be further utilized to inform and guide firms’ transaction strategies concerning the overall supply network.
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Purpose
Developing a lean supply chain is a continuous improvement effort, so it requires tracking the implementation progress by assessing the achieved level of leanness. However, lean supply chain practices depend on firm-to-firm relationships and an assessment method should consider these network interactions. Given the absence of such a method, this study aims to propose an alternative approach for assessing the leanness level of supply chains.
Design/methodology/approach
The authors extracted 18 typical lean supply chain practices from the literature, constituting the leanness assessment parameters. Then, the authors developed an assessment method based on the graph-theoretic approach due to its properties of capturing the interdependencies between elements of a system. The authors tested the proposed method in an automotive supply chain, selecting the focal firm and three of its first-tier suppliers.
Findings
The authors positioned partial and overall results in a visual classification scale and the supply chain presented a moderate leanness level. After empirical testing, the proposed method demonstrated its practical feasibility.
Research limitations/implications
This paper contributes to the literature with a novel approach for supply chain leanness assessment. However, to increase its generalizability, it would be beneficial to test the method in non-automotive supply chains, extending the assessment scope to downstream firms and second-tier customers and suppliers.
Practical implications
For practitioners, this paper provides a self-assessment tool to monitor the supply chain leanness and set priorities for improvement.
Originality/value
Besides tackling the interrelationships between firms, the proposed method considers the interdependencies between lean practices, providing partial and overall feedback to enable a systemic assessment.
Increasing awareness of the intrinsically complex nature of supply networks has brought the field of supply chain management into the domain of network science. However, due to the difficulties of acquiring large-scale and consistent empirical data sets, a more complete picture of a real-world supply network has remained remarkably elusive. In this paper, we present novel data that characterize the Toyota supply network, and identify key structural features using measures from social network analysis and the more recent field of network science. We show that the network structure for the Toyota supply network departs widely from the simplified models on which much previous work is based. Our analysis reveals the heterogeneous composition of the network and identifies key firms. Further analysis reveals the existence of constituent sub-networks, and we show that their structures reflect various factors, such as product categorization, geographical closeness and business alignment. Mapping the topology, geography, and distribution of productive capabilities for this supply network provides a critical first step for developing a more empirically-grounded theory of distributed production.
Industrial firms survive, sustain and co-evolve by participating in the sector of innovation and production through industrial transactions with each other. However, it is difficult for specialized firms to be aware of and manage accordingly the kind of systemic constraints and opportunities induced by relevant but indirect transactions, as well as the technological and economic requirements of their value chains, which they cannot control or even sufficiently observe. The myopia may cause specialized firms to implement incorrect strategies, leave them vulnerable to system failures or ignorant of emerging opportunities. This implies a paradox: the simultaneous needs to specialize and to understand and manage the big picture of the ecosystem. Previous industry studies have focused on the question if a transaction with an external firm is needed rather than in-house production, and on empirical work from single industries or bilateral relationships between firms. Meanwhile, the firms' positions in the sectoral transaction network are also influential to the success and performance of firms. In this dissertation, I conduct transaction network analysis to explore how firms are organized in the sector of aggregated industries, in order to shed light on the set of previously ignored knowledge on industrial transactions, which is valuable to single firms in designing strategies and managing operations but is not available from firm- and industry-level analysis. At the sector level, existing theories often assumed hierarchical or non-hierarchical relationships among industrial firms, and quantitative evidence on variable degrees of hierarchy in industry sectors is lacking. This dissertation first identifies and defines the type of hierarchy relevant to industry studies -flow hierarchy, develops a network-based metric on the degree of hierarchy (one-way flow of transactions), and applies it to the transaction data from two industrial sectors in Japan. The empirical results show that the electronics sector exhibits a significantly lower degree of hierarchy than the automotive sector due to the presence of many transaction cycles. It shows that the simplistic hierarchy hypothesis for production sectors does not always hold. I further create a network simulation model with random networks to relate sector-level hierarchy degrees to firm-level behavioral variables, and infer transaction specificity, i.e. the extent to which a firm is captive to a niche of customers positioned closely in the industrial network hierarchy. The model builds on three basic rules on market structures, i.e. hierarchy, niche, and the mapping relationship between roles and positions. Transaction specificity provides a way to quantify the tendency of a firm to fix or institutionalize its role according to its relative network position, or where the transactions of a firm are oriented in the value chains, whereas traditional studies analyze whether a transaction versus in-house production is needed. The result shows that transaction specificity in the electronics sector is quantitatively much lower than that in the automotive sector. I further conducted interviews with nine firms in the two sectors and found that, with decision rationales related to product modularity, innovation dynamics and asset specificity, the major electronics firms take the permeable vertical boundary strategy and diversified horizontal boundary strategy, which decrease transaction specificity so that many transaction cycles emerge in the electronics sector. My analysis shows the permeability of a firm's vertical boundary, i.e. playing multiple value chain roles, is the necessary condition for transaction cycles to emerge. Meanwhile, these two strategies are not feasible in the automotive sector according to interviews. They are also not observed in the American electronics sector. My data show the American electronics firms tend to be vertically specialized in the value chains. Linking network analysis results, interview data, and the prior work on the physical limits to product modularity, I argue that higher power level of a sector's technologies leads to higher transaction specificity, and more hierarchical transaction lows across the sector. High power technologies constrain strategic transaction choices, while lower power technologies enable a larger option space of transaction strategies, for companies to explore and exploit. For academics, the use of network analysis permits transaction cost analysis, or more general analysis of transaction-related decisions, to be extended from the boundary of a firm to the architecture of a sector comprising related industries. It gives us a bird's-eye view to observe firm-level transaction behaviors and create new knowledge on transaction specificity. In addition, the analysis of the physical properties of product technologies allows us to interpret the difference in transaction specificities and hierarchy degrees of different sectors, which economic and sociology theories cannot explain. For industry practitioners, this research suggests that firms' choices for industrial transactions are under some predictable constraints from product technologies. A better understanding of the linkages between industry architecture, firm transaction strategy, and product technology, in turn can guide companies to tailor transaction strategies to implicit technological constraints and to adequately explore strategic options made feasible by technologies.
Emergence, the creation of structures, organizations, and social entities, is increasingly important, but it can only be understood by integrating research from dozens of disciplines. This book accomplishes that goal, by providing the most complete set of emergents ever published, and introducing a discipline of emergence. Moreover, it focuses on a common type of emergence that has until now been unidentified, namely emergence that is intentional, called generative emergence. The book reveals the scientific foundations of generative emergence—dissipative structures theory—in the context of a summary of all 15 complexity sciences. By making a rigorous analogy between emergence in dissipative structures and emergence of organizations, the book develops a five-phase process of generative emergence, a cycle of emergence that explains order creation in groups, entrepreneurial companies, organizations, alliances, and clusters. The book then presents unpublished findings about emergence and re-emergence in high-tech ventures. These data and analyses confirm the five-phase model of generative emergence in and of organizations, and applies it to several other social ecologies.
Co-opetition, or simultaneous competition and cooperation, in the supply chain management literature has been treated as a dyadic relational phenomenon where the buyer's strategy is considered to be the primary driver. In this paper, we move beyond the dyadic view and propose a theory of co-opetition in supply networks. We argue that as firms within a supply network interact over time to access, share, and transform resources, new ties between firms are formed and existing ties dissolve, giving rise to co-opetition dynamics at the network level. Taking a configurational approach, we employ the inter-related dimensions of ties between firm, firm-level task, network-level objective, and governance to specify four practical supply network archetypes that cover a wide range of economic activities. We then explain how coopetitive relationships may evolve in these supply network archetypes. Specifically, we discuss how relationships form or dissolve in these archetypes and how local structural changes lead to co-opetition dynamics at the network level. We also discuss the implications of such dynamics from a managerial perspective.
Previous studies suggest that food-web theory has yet to account for major differences in food-web properties of marine versus other types of ecosystems. We examined this issue by analyzing the network structure of food webs for the Northeast US Shelf, a Caribbean reef, and Benguela, off South Africa. The values of connectance (links per species2), link density (links per species), mean chain length, and fractions of intermediate, omnivorous, and cannibalistic taxa of these marine webs are somewhat high but still within the ranges observed in other webs. We further compared the marine webs by using the empirically corroborated ‘niche model’ that accounts for observed variation in diversity (taxon number) and complexity (connectance). Our results substantiate previously reported results for estuarine, fresh-water, and terrestrial datasets, which suggests that food webs from different types of ecosystems with variable diversity and complexity share fundamental structural and ordering characteristics. Analyses of potential secondary extinctions resulting from species loss show that the structural robustness of marine food webs is also consistent with trends from other food webs. As expected, given their relatively high connectance, marine food webs appear fairly robust to loss of most-connected taxa as well as random taxa. Still, the short average path length between marine taxa (1.6 links) suggests that effects from perturbations, such as overfishing, can be transmitted more widely throughout marine ecosystems than previously appreciated.
Our purpose in this note is to make explicit how two lines of work in sociology — the population ecology of organizations and the structural hole theory behind network studies of markets — are based on the same unit of analysis. The unit is a set of structurally equivalent producers; termed a niche in population ecology and a market in structural hole theory. Making the market niche analogy explicit puts a bridge in place for what we believe and begin to explain here, should be productive exchange between the two lines of work.
The modern corporation has long been the central focus of the field of organization design. Such firms can be likened to nation-states: they have boundaries that circumscribe citizen-employees, and they engage in production and trade. But individual corporations are no longer adequate to serve as the primary unit of analysis. Over the years, systems of distributed innovation – so-called business ecosystems – have become increasingly prevalent in many industries (Adner & Kapoor, 2010; Iansiti & Levien, 2004; von Hippel, 1988). Ecosystems generally encompass numerous corporations, individuals, and communities that might be individually autonomous but related through their connection with an underlying, evolving technical system.In the future, I believe the key problem for organization design will be the management of distributed innovation in such dynamic ecosystems. Specifically, how should diverse entities be integrated into a coherent network that generates goods in the present and new designs for the future? To answer that question, organization designers must think about how to distribute property rights, people, and activities across numerous self-governing enterprises in ways that are advantageous for the group (ecosystem) as well as for the designer’s own firm or community.
In this era, information technology is revolutionizing almost every domain of technology and society, whereas the ‘complexity revolution’ is occurring in science at a silent pace. In this paper, we look at the impact of the two, in the context of supply-chain networks. With the advent of information technology, supply chains have acquired a complexity almost equivalent to that of biological systems. However, one of the major challenges that we are facing in supply-chain management is the deployment of coordination strategies that lead to adaptive, flexible and coherent collective behaviour in supply chains. The main hurdle has been the lack of the principles that govern how supply chains with complex organizational structure and function arise and develop, and what organizations and functionality are attainable, given specific kinds of lower-level constituent entities. The study of Complex Adaptive Systems (CAS), has been a research effort attempting to find common characteristics and/or formal distinctions among complex systems arising in diverse domains (like biology, social systems, ecology and technology) that might lead to a better understanding of how complexity occurs, whether it follows any general scientific laws of nature, and how it might be related to simplicity. In this paper, we argue that supply chains should be treated as a CAS. With this recognition, we propose how various concepts, tools and techniques used in the study of CAS can be exploited to characterize and model supply-chain networks. These tools and techniques are based on the fields of nonlinear dynamics, statistical physics and information theory.
In this study we examine the relationship between supply network's topology and its robustness in the presence of random failures and targeted attacks. The agent-based model developed in this paper uses the basic framework and parameters in the experimental game presented in Sterman [1989, Modeling managerial behavior: Misperceptions of feedback in a dynamic decision making context. Management Science, 35 (3), 321–339] for modelling adaptive managerial decision making in an inventory management context. The study extends the linear supply chain context to a complex supply network and undertakes a rigorous examination of robustness of these supply networks that are characterised by distinct network characteristics. We theorise that network characteristics such as average path length, clustering coefficient, size of the largest connected component in the network and the maximum distance between nodes in the largest connected component are related to the robustness of supply networks, and test the research hypotheses using data from several simulation runs. Simulations were carried out using 20 distinct network topologies where 10 of these topologies were generated using preferential attachment approach (based on the theory of scale-free networks) and the remaining 10 topologies were generated using random attachment approach (using random graph theory as a foundation). These 20 supply networks were subjected to random demand and their performances were evaluated by considering varying probabilities of random failures of nodes and targeted attacks on nodes. We also consider the severity of these disruptions by considering the downtime of the affected nodes. Using the data collected from a series of simulation experiments, we test the research hypotheses by means of binomial logistic regression analysis. The results point towards a significant association between network characteristics and supply network robustness assessed using multiple performance measures. We discuss the implications of the study and present directions for future research.
Food webs hold a central place in ecology. They describe which organisms feed on which others in natural habitats. This book describes recently discovered empirical regularities in real food webs and proposes a novel theory unifying many of these regularities, as well as extensive empirical data. After reviewing the empirical and theoretical discoveries about food webs, the second portion of the book shows that community food webs obey several striking phenomenological regularities. Some of these unify, regardless of habitat. Others differentiate, showing that habitat significantly influences structure. Following a theoretical analysis of these unifying empirical regularities, the volume presents the matrices of 113 community food webs, which we collected from scattered sources and carefully edited: they form the empirical basis for the results presented here. This collection, the largest set of data on community food webs available, provides a valuable foundation for future studies of community food webs. The book is intended for researchers, teachers and graduate students in ecology, biostatistics and bio-mathematics primarily. The theoretical portions of the book provide materials useful to teachers of applied combinatorics, in particular, random graphs. Researchers in random graphs will find here unsolved mathematical problems. The book is now directly accessible via https://link.springer.com/book/10.1007/978-3-642-83784-5
The decision of a firm to set up a plant network is influenced by a number of factors, including demand fluctuations across its portfolio of products, logistics costs, and service level requirements. Product plant networks offer the benefits of consolidated production and reduced transshipment costs; on the other hand, process plant networks allow intensive dedication to process expertise and economies of scale. In this paper, we show that, aside from these benefits, process plant networks offer significant risk pooling advantages under a wide range of conditions. We analytically demonstrate that, even without accounting for economies of scale advantages, firms may prefer the process plant network configuration due to the risk pooling benefits offered.
This paper documents, summarizes and analyzes the results of interviews with two typical Japanese automotive suppliers with different business focuses. The shared responses from the interviews include: the emphasis on trust and collaboration for product quality and cost instead of new product development for new customers, the pursuit for specificity in products and transactional relationships, perceptions on the maturity of the automotive industry, and the regular tier structure in automotive supply networks. All these issues are intertwined and lead to the lock-in of the current automotive industry landscape. The complex integration of many components and parts in an automobile drives the firms to pursue specificity in design and production process, which improves quality and cost in order to compete. Such pursuit of specificity for high-performance/high-quality integration has emphasized deep relationships and trust in existing transactional relationships, but limited the innovation incentive and innovation capability accumulation, and made the firms either unwilling or unable to diversify their products and transactional relationships with new customers in new market niches. Over years of evolution, automotive suppliers have become compliant to their positions in the sequential hierarchy of assembling from raw materials to components/parts, systems and the entire vehicles. The interviews have provided qualitative insights that may complement and support the related quantitative supply network analysis using archival data, in order to further our understandings on industry architectures.
Japanese industrial firms have developed a system of subcontracting with suppliers that has played a major role in their world-wide success. This book explores the historical evolution of subcontracting in Japan and analyses it in current practice. It develops a theory of ‘strategic dualism’ that after nearly six decades of evolution is a new mode of contractual relations, based on principles of problem-solving collaborative manufacturing. This new form of contractual relations is supported by a range of institutional arrangements that drive prime contractors and subcontractors towards continuous improvement in product quality and cost reduction. It argues that this system is possible in a range of cultures different from Japan.
In much of the current literature on supply chain management, supply networks are recognized as a system. In this paper, we take this observation to the next level by arguing the need to recognize supply networks as a complex adaptive system (CAS). We propose that many supply networks emerge rather than result from purposeful design by a singular entity. Most supply chain management literature emphasizes negative feedback for purposes of control; however, the emergent patterns in a supply network can much better be managed through positive feedback, which allows for autonomous action. Imposing too much control detracts from innovation and flexibility; conversely, allowing too much emergence can undermine managerial predictability and work routines. Therefore, when managing supply networks, managers must appropriately balance how much to control and how much to let emerge.
Three complete supply networks have been mapped in this study. These supply networks pertain to the center console assembly and come from three different product lines—Honda Accord, Acura CL/TL, and DaimlerChrysler (DCX) Grand Cherokee. Based on these three cases of supply networks, propositions are built concerning how the structure of supply networks operates. Based on the extant literature, we frame structure in three dimensions—formalization, centralization, and complexity. As an underlying methodology, we first conduct the within‐case analysis and then expand the analysis to cross‐case context. The three structural dimensions affect one another progressively, and the cost consideration appears to be the overarching force that shapes the supply‐network structure.
The architecture of a firm's network of transactions in its surrounding business ecosystem may affect its innovation performance. Here we proximate a business ecosystem as a transaction network among firms. Specifically, we analyze how the innovation performances of the firms are associated with their network positions and vertical structures in the transaction network, using the data for the Japanese electronics sector in the early 1990s. The results show that, a firm's participation in inter-firm transaction cycles, instead of sequential transactional relationships, is positively and significantly associated with its innovation performance for vertically integrated firms. Within cycles, vertically integrated firms have better innovation performances than vertically specialized firms. Vertically integrated firms that participate in cycles have the best innovation performances in the Japanese electronics sector. These findings provide strategic implications and guidance for firms to design and manage their vertical structure and transaction network position.
Today, value chains design and produce most goods and the value captured as a whole is distributed among the chain’s members through bargaining. For complex products, bargaining typically comprises several individual negotiations structured according to the hierarchical organization of the respective industry. We introduce the notion of “bargaining structure” to describe the sequence and participants of these individual negotiations. Using cooperative game theory—in particular the Shapley value and extensions of it—we show how bargaining structure affects the distribution of value among the constituent firms of the value chain. We find that positions in the bargaining structure most conducive to value capture are those where large complementarity gains are realized and split, ideally, among a small number of negotiators. Since the bargaining structure of a value chain is to some extent malleable, each member firm has an incentive to shape it in such a way as to optimize its own value capture. We suggest that product architecture is a key lever to influence the architecture of the value chain and can be used to shape bargaining structure and enhance value capture. Using examples from the commercial aircraft and the white goods industries, the results of our research posit that bargaining structures are indeed malleable and, to some extent, under the control of the central firm.
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This paper starts from the observation that firms are increasingly engaging in collaborations with their suppliers, even as they are reducing the extent to which they are vertically integrated with those suppliers. This fact seems incompatible with traditional theories of the firm, which argue that integration is necessary to avoid the potential for hold-ups created when non-contractible investments are made. Our view is that pragmatist mechanisms such as benchmarking, simultaneous engineering and "root cause" error detection and correction make possible "learning by monitoring"--a relationship in which firms and their collaborators continuously improve their joint products and processes without the need for a clear division of property rights. We argue that pragmatic collaborations based on "learning by monitoring" both advance knowledge and control opportunism and thus align interests between the collaborators. Copyright 2000 by Oxford University Press.
Although the stylized model of industry evolution suggests that firms transform from vertical integration to specialization over time, many industries still exhibit a continued persistence of integrated firms. In exploring this puzzle, I draw on detailed firm-level data from the semiconductor industry to analyze how integrated incumbents, beyond shifting to the specialized mode, reconfigured in the face of industry's vertical disintegration so as to coexist with the specialized firms. I propose and find that the incumbents who persist with vertical integration increase their emphasis on systemic innovations and transact with specialized firms in both upstream and intermediate markets. The value-creating opportunities associated with integrated incumbents' leveraging (a) their relative superiority in developing systemic innovations and (b) markets to pursue a broader menu of transactional choices may offset their costs of staying integrated. These firm-level factors also determine the pattern of industry's vertical disintegration and the extent of coexistence between integrated and specialized firms.
Increasingly, scholars recognize the importance of understanding supply network disruptions. However, the literature still lacks a clear conceptualization of a network-level understanding of supply disruptions. Not having a network level understanding of supply disruptions prevents firms from fully mitigating the negative effects of a supply disruption. Graph theory helps to conceptualize a supply network and differentiate between disruptions at the node/arc level versus network level. The structure of a supply network consists of a collection of nodes (facilities) and the connecting arcs (transportation). From this perspective, small events that disrupt a node or arc in the network can have major consequences for the network. A failure in a node or arc can potentially stop the flow of material across network. This study conceptualizes supply network disruption and resilience by examining the structural relationships among entities in the network. We compare four fundamental supply network structures to help understand supply network disruption and resilience. The analysis shows that node/arc-level disruptions do not necessarily lead to network-level disruptions, and demonstrates the importance of differentiating a node/arc disruption versus a network disruption. The results also indicate that network structure significantly determines the likelihood of disruption. In general, different structural relationships among network entities have different levels of resilience. More specifically, resilience improves when the structural relationships in a network follow the power-law. This paper not only offers a new perspective of supply network disruption, but also suggests a useful analytical approach to assessing supply network structures for resilience.
From the Internet to networks of friendship, disease transmission, and even terrorism, the concept--and the reality--of networks has come to pervade modern society. But what exactly is a network? What different types of networks are there? Why are they interesting, and what can they tell us? In recent years, scientists from a range of fields--including mathematics, physics, computer science, sociology, and biology--have been pursuing these questions and building a new "science of networks." This book brings together for the first time a set of seminal articles representing research from across these disciplines. It is an ideal sourcebook for the key research in this fast-growing field. The book is organized into four sections, each preceded by an editors' introduction summarizing its contents and general theme. The first section sets the stage by discussing some of the historical antecedents of contemporary research in the area. From there the book moves to the empirical side of the science of networks before turning to the foundational modeling ideas that have been the focus of much subsequent activity. The book closes by taking the reader to the cutting edge of network science--the relationship between network structure and system dynamics. From network robustness to the spread of disease, this section offers a potpourri of topics on this rapidly expanding frontier of the new science.
Modularity is a design property of the architecture of products, organizations, and interfirm networks; modularization is a process that affects those designs while also shaping firm boundaries and industry landscapes; and ‘modularity’ is a cognitive frame that guides categorization and interpretation of a wide array of economic phenomena. Modularity-as-property and modularization-as-process are deeply intertwined; while modularization processes are ubiquitous and perpetual as engineers and managers seek to understand interdependencies across the boundaries of product and organizational architecture, the extent to which modularity-as-property is achieved must be assessed empirically. The framing of ‘modularity’ affects strategy by prompting a particular dynamic—and directionality—in the interplay between modularity-as-property and modularization-as-process. I analyze product architecture initiatives in the global automotive industry, examining first the industry-level antecedents of the emergent production-based definition of modules and then two firm-level modularity initiatives that both were based on this common definition, but framed their strategies differently. In the first case, a ‘modularity’ frame based on a computer industry analogy resulted in overemphasis on achieving modularity-as-property that created barriers to learning about cross-module interdependencies. In the second case, early emphasis on modularization-as-process yielded quasi-integrated organizational arrangements that facilitated long-term design improvements. Overall, this single-industry case study demonstrates the importance of examining the context-specific antecedents of module definition; the multiplicity of potential barriers to modularity that can lead to persistent integrality; the need for longitudinal inquiry into the ‘mirroring’ hypothesis that pays as much attention to process as to property; and the power of modularity as a cognitive frame, which helps explain divergent findings in modularity research.
This paper examines conceptual issues and reviews empirical results bearing on the relationship between research approaches emphasizing organizational capabilities and those based in transaction cost economics (TCE)—or in organizational economics more generally. Following a review of conceptual fundamentals—what capability is and why organizations differ in capability—it assesses recent progress toward an integration of the capabilities and transaction cost approaches, primarily in the context of the analysis of vertical structure and related phenomena. This review suggests that progress has been substantial and that the key elements of a promising dynamic synthesis have been identified. The paper then considers issues that call for attention if further progress is to be achieved. The first of these is the role of agency, which must be seen in expansive terms (relative to standard economic rationality) if its evolutionary significance is to be fully appreciated. The second is the role of structure, or more specifically, industry architecture, which affects capability development by way of its effect on the feedback that firms receive. After drawing on the recent financial crisis for an illustration of these ideas, this paper considers the rise of interest in business models as a useful field of application, and it concludes with a discussion of the role of organizational economics (beyond TCE). We argue that, whatever the theoretical perspective at the level of the firm, analyses must reach beyond that level to grasp the important causal forces affecting capability development, firm boundaries, and structural features more generally.
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1946468
This paper examines the impact of architectural decisions on the level of defects in a product. We view products as collections of components linked together to work as an integrated whole. Previous work has established modularity (how decoupled a component is from other product components) as a critical determinant of defects, and we confirm its importance. Yet our study also provides empirical evidence for a relation between product quality and cyclicality (the extent to which a component depends on itself via other product components). We find cyclicality to be a determinant of quality that is distinct from, and no less important than, modularity. Extending this main result, we show how the cyclicality–quality relation is affected by the centrality of a component in a cycle and the distribution of a cycle across product modules. These findings, which are based on analysis of open source software development projects, have implications for the study and design of complex systems.
The authors develop a conception of an organization-specific niche in a technological network. This niche is defined by two properties: crowding and status. The authors hypothesize that crowding suppresses an organization's life chances and that status enhances life chances, especially for those organizations in uncrowded niches. They operationalize this conception of the niche using patents and patent citations, and they find support for these hypotheses in an examination of technological competition in the worldwide semiconductor industry. In the conclusion, they compare these findings to earlier research and highlight some of the particular advantages of this conception of the niche.
A number of proposals have been advanced in recent years for the development of “general systems theory” which, abstracting from properties peculiar to physical, biological, or social systems, would be applicable to all of them. We might well feel that, while the goal is laudable, systems of such diverse kinds could hardly be expected to have any nontrivial properties in common. Metaphor and analogy can be helpful, or they can be misleading. All depends on whether the similarities the metaphor captures are significant or superficial.
This paper provides an inductive theoretical framework that explains how and why vertical disintegration happens, showing that transaction costs are an incidental feature of industry evolution. I find that gains from intrafirm specialization set off a process of intraorganizational partitioning, which simplifies coordination along parts of the value chain. Likewise, latent gains from trade foster interfirm cospecialization, which leads to information standardization. Given standardized information and simplified coordination, new intermediate markets emerge, breaking up the value chain, allowing new types of vertically specialized firms to participate in an industry, and changing the industry's competitive landscape.
This paper investigates the dynamics of a complex adaptive supply network (CASN), focusing on understanding stability of the structural evolution of a supply network and supplier population emergence. Supply network evolution data collected from simulated responses of the U.S. automobile industry are used in multivariate statistics and time series analysis to identify patterns of network evolution. This analysis reveals that the type of environment a supply network evolves in appears to be a major factor in determining critical timing of structural changes during the evolution of a CASN. Further, time series analysis of firm population evolution highlights how supply networks evolve due to path dependencies in the CASN system. Information about these two aspects of supply network evolution can prove useful to a decision maker in determining how to respond to supply network changes.
Ecology Letters (2010) 13: 891–899
Abstract
Food web structure plays an important role when determining robustness to cascading secondary extinctions. However, existing food web models do not take into account likely changes in trophic interactions (‘rewiring’) following species loss. We investigated structural dynamics in 12 empirically documented food webs by simulating primary species loss using three realistic removal criteria, and measured robustness in terms of subsequent secondary extinctions. In our model, novel trophic interactions can be established between predators and food items not previously consumed following the loss of competing predator species. By considering the increase in robustness conferred through rewiring, we identify a new category of species – overlap species – which promote robustness as shown by comparing simulations incorporating structural dynamics to those with static topologies. The fraction of overlap species in a food web is highly correlated with this increase in robustness; whereas species richness and connectance are uncorrelated with increased robustness. Our findings underline the importance of compensatory mechanisms that may buffer ecosystems against environmental change, and highlight the likely role of particular species that are expected to facilitate this buffering.
The concept of structural embeddedness refers to the importance of framing suppliers as being embedded in larger supply networks rather than in isolation. Such framing helps buying companies create more realistic policies and strategies when managing their suppliers. Simply put, the performance of a supplier is dependent on its own supply networks. By adopting the concept of structural embeddedness, we learn that a buying company needs to look at a supplier's extended supply network to arrive at a more complete evaluation of that supplier's performance. By doing so, a buying company may do a better job of selecting suppliers for long-term relationships and may also find value in maintaining relationships with poorly performing suppliers who may potentially act as a conduit to other companies with technological and innovative resources.
In this paper, we present a review of the models for the management of global supply chains and some evidence concerning current practice. Our review is restricted to the literature on intrafirm global supply chains and is motivated by empirical data concerning the extent of intrafirm globalization. The review of the literature suggests that research has not evolved in a coherent manner, while the data suggest that the extent of globalization is also hard to gauge. Indeed, the journey toward supply chain globalization is far from over. Significant gaps exist between theory and the practice. We conclude with a summary of directions for future research.
A system of interconnected buyers and suppliers is better modeled as a network than as a linear chain. In this paper we demonstrate how to use social network analysis to investigate the structural characteristics of supply networks. Our theoretical framework relates key social network analysis metrics to supply network constructs. We apply this framework to the three automotive supply networks reported in Choi and Hong (2002). Each of the supply networks is analyzed in terms of both materials flow and contractual relationships. We compare the social network analysis results with the case-based interpretations in Choi and Hong (2002) and conclude that our framework can both supplement and complement case-based analysis of supply networks.
This paper examines conceptual issues and reviews empirical results bearing on the relationship between research approaches emphasizing organizational capabilities and analyses based in transaction cost economics (TCE) or in organizational economics more generally. Following a review of conceptual fundamentals what is capability and why do organizations differ in capability it assesses recent progress toward an integration of the capabilities and transaction cost approaches, primarily in the context of the analysis of vertical structure and related pheonomena. This review suggests that progress has been substantial, and that key elements of a promising dynamic synthesis have been identified. The paper then considers issues that call out for attention if further progress is to be achieved. The first of these is the role of agency, which must be seen in expansive terms (relative to standard economic rationality) if its evolutionary significance is to be fully appreciated. The second is the role of structure, or more specifically industry architecture, which affects capability development by way of its effect on the feedback that firms receive. After drawing on the recent financial crisis for an illustration of these ideas, the paper concludes with a brief assessment of recent contributions from organizational economics (beyond TCE), and the proposition that, whatever the perspective on the firm level, analyses must reach above the firm level to grasp the important causal forces affecting capability devlopment, firm boundaries, and structural features more generally.
Examines the correlation between the exploration of new possibilities and the exploitation of old certainties in organizational learning. Also discusses the difficulty in balancing resource management between gaining new information about alternatives to improve future returns (i.e., exploration) and using information currently available to improve present returns (i.e., exploitation). Two models which evaluate the formation and use of knowledge in organizations are developed. The first is a model of mutual learning in a closed system having fixed organizational membership and stability. The second is a model which considers the ways in which competitive advantage is affected by knowledge accumulation. The analysis indicates that the choice to rapidly develop exploitation over exploration might be effective in the short term, but is potentially detrimental to the firm in the long term. (SFL)
Many products are manufactured in networks of firms linked by transactions, but comparatively little is known about how or why such transaction networks differ. This paper investigates the transaction networks of two large sectors in Japan at a single point in time. In characterizing these networks, our primary measure is “hierarchy,” defined as the degree to which transactions flow in one direction, from “upstream” to “downstream.” Our empirical results show that the electronics sector exhibits a much lower degree of hierarchy than the automotive sector because of the presence of numerous inter-firm transaction cycles. These cycles, in turn, reveal that a significant group of firms have two-way “vertically permeable boundaries”: (1) they participate in multiple stages of an industry’s value chain, hence are vertically integrated, but also (2) they allow both downstream units to purchase intermediate inputs from and upstream units to sell intermediate goods to other sector firms. We demonstrate that the 10 largest electronics firms had two-way vertically permeable boundaries while almost no firms in the automotive sector had adopted that practice.
The concept of vertical architecture defines the scope of a firm and the extent to which it is open to final and intermediate markets. A firm can make or buy inputs, and transfer outputs downstream or sell them. Permeable vertical architectures are partly integrated and partly open to the markets along a firm's value chain. Increased permeability enables more effective use of resources and capacities, better matching of capabilities with market needs and benchmarking to improve efficiency. Partial integration promotes a more dynamic, open innovation platform and enhances strategic capabilities by linking key parts of the value chain. This permeable vertical architecture, accompanied by appropriate transfer prices and incentive design, facilitates resource allocation and guides a firm's growth process. Our longitudinal study of a major European manufacturer suggests that to understand how firm boundaries are set and what are their impacts, we need to complement the micro-analytic focus on transactions with a systemic analysis at the level of the firm. It also shows how, over and above transactional alignment, decisions about boundaries can transform a firm's strategic and productive capabilities and prospects.