What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

Complex networks have been studied intensively for a decade, but research still focuses on the limited case of a single, non-interacting network. Modern systems are coupled together and therefore should be modelled as interdependent networks. A fundamental property of interdependent networks is that failure of nodes in one network may lead to failure of dependent nodes in other networks. This may happen recursively and can lead to a cascade of failures. In fact, a failure of a very small fraction of nodes in one network may lead to the complete fragmentation of a system of several interdependent networks. A dramatic real-world example of a cascade of failures (‘concurrent malfunction’) is the electrical blackout that affected much of Italy on 28 September 2003: the shutdown of power stations directly led to the failure of nodes in the Internet communication network, which in turn caused further breakdown of power stations. Here we develop a framework for understanding the robustness of interacting networks subject to such cascading failures. We present exact analytical solutions for the critical fraction of nodes that, on removal, will lead to a failure cascade and to a complete fragmentation of two interdependent networks. Surprisingly, a broader degree distribution increases the vulnerability of interdependent networks to random failure, which is opposite to how a single network behaves. Our findings highlight the need to consider interdependent network properties in designing robust networks.

http://absimage.aps.org/image/MAR10/MWS_MAR10-2009-001087.pdf

Catastrophic cascade of failures in interdependent networks

This study examines both incremental learning curves as well as "revolutionary" learning and innovation in the area of product quality. One implication of the findings is that knowledge gained from...

/pdf/organizational-learning-and-the-transfer-of-knowledge-an-3gpy21k916.pdf

Organizational learning and the transfer of knowledge: an investigation of quality improvement.

Particularly because of the great amount of information that a social memory can contain, relevant information is quite often difficult to find and these difficulties become even larger when the needed information is dispersed widely in time and in space or when special barriers are erected to protect such information from being discoverd. I like to consider search procedures as those processes that are employed to locate relevant information in time, in space, and in kind, often against apparently insurmountable odds. Research and development problems provide the most prototypical examples of situations in which efficient search procedures are decisive in bridging an existing information gap. In order to incorporate into a design as much information as possible, it is quite common that a very large number of reports may have to be read, most being irrelevant in fact. Finding a solution then depends not so much on the retrieval of information rather on the efficiency of the search procedure available. Because research reports tend to be somewhat more standardized (at least clearly distinct and written in the same medium) computers have already provided useful selection aids for literature references. Another problem of search is criminal detection. This may involve identifying one out of thousands of widely dispersed and highly mobile suspects. Among the many clues that may become available during an investigation, most are likely to be unproductive and the successful conclusion of a case presumably depends on following the right clues early enough and without being sidetracked. Related to such situations is the problem which many intelligence departments face when trying to obtain information that someone else deliberately hides or encodes into an unrecognizable cipher. Less extreme though socially probably more

/pdf/some-principles-of-information-storage-and-retrieval-in-32camd3g85.pdf

Some Principles of Information Storage and Retrieval in Society

This paper reviews the 2009 Nobel Prize in Economics jointly awarded to Oliver Williamson for his work on governance in organizations and the boundaries of the firm, and to Elinor Ostrom for her work on the governance of common pool resources. We review the careers and the research contributions of Williamson and Ostrom to the theory and analysis of economic institutions of governance. Both winners of this Prize for 'economic governance' are thoroughly deserved, yet like the Hayek- Myrdal Prize of 1974 their respective approaches, methods and findings are almost diametrically opposed. Williamson offers a top-down contracts-based solution to the incentive problems of opportunism in corporate governance, whereas Ostrom offers a bottom-up communication-based solution to the governance opportunities of community resources. We offer some critical comments on Williamson's analytic work and discussion of the potential for further application of Ostrom's case-study based experimental methodology. We conclude with a suggested third nominee to make better sense of how these two great scholars' works fit together, namely George Richardson'

A Nobel Prize for governance and institutions : Oliver Williamson and Elinor Ostrom

Purpose




This paper aims to develop conceptual arguments questioning the efficacy of administration by the transaction cost economics (TCE) approach in an organization undergoing a major change.




Design/methodology/approach




The focus is on three distinct dimensions of organizational life where, as per prior research, TCE is likely to be inadequate: interdependence across transactions, high reliance on managerial foresight and inseparability of administrative decisions made at different points in time.




Findings




The climate of coercion and surveillance engendered by administration based on TCE approaches – that punishes deviation from goals, even when they are framed on inadequate knowledge – forestalls creative problem-solving that is necessary to address unforeseen developments that arise during change implementation. Fiat accomplishes within-group compliance in the change project sub-teams, but between-group interdependencies tend to be neglected, hampering organizational effectiveness. Moreover, attempts to create independent spheres of accountability for concurrent fiats regarding pre-existing and new commitments breed inefficiency and wastage.




Research limitations/implications




The malevolent aspects of TCE-based administration contribute to organizational dysfunctions like escalation of commitment and developing of silos in organizations.




Practical implications




To succeed in effecting a major organizational change, meaningful relaxation of demands for delivering on prior goals is required, along with forbearance of errors made during trial-and-error learning.




Originality/value




TCE-based administration is deleterious to an organization attempting a major change. Supremacy accorded to resolution of conflicts in distinct hierarchical relationships by the mechanism of fiat fails to address the needs of an organizational reality where multiple groups are engaged in a set of interdependent activities and where multiple, interdependent organizational imperatives need to be concurrently served.

Administration of an organization undergoing change: Some limitations of the transaction cost economics approach

Under high complexity - given by pervasive interdependence between constituent elements of a decision in an NK landscape - our algorithm obtains fitness superior to that reported in extant research. We distribute the decision elements comprising a decision into clusters. When a change in value of a decision element is considered, a forward move is made if the aggregate fitness of the cluster members residing alongside the decision element is higher. The decision configuration with the highest fitness in the path is selected. Increasing the number of clusters obtains even higher fitness. Further, implementing moves comprising of up to two changes in a cluster also obtains higher fitness. Our algorithm obtains superior outcomes by enabling more extensive search, allowing inspection of more distant configurations. We name this algorithm the muddling through algorithm, in memory of Charles Lindblom who spotted the efficacy of the process long before sophisticated computer simulations came into being.

An Algorithm to find Superior Fitness on NK Landscapes under High Complexity: Muddling Through.

Cognitive considerations arising from the functions of the Chief Executive Officer appear to have been ignored in strategy research. Taking a cue from Freeman’s stakeholder theory, I discuss the constituencies addressed by the CEO in performing his/her job function. I present a set of propositions based on extant research. I endeavor to commence a conversation that ultimately shapes the lines of inquiry regarding the contribution of managerial cognition to strategy.

CEO Cognition in Strategy Research

Instances of Artificial Intelligence (AI) systems failing to deliver consistent, satisfactory performance are legion. We investigate why AI failures occur. We address only a narrow subset of the broader field of AI Safety. We focus on AI failures on account of flaws in conceptualization, design and deployment. Other AI Safety issues like trade-offs between privacy and security or convenience, bad actors hacking into AI systems to create mayhem or bad actors deploying AI for purposes harmful to humanity and are out of scope of our discussion. We find that AI systems fail on account of omission and commission errors in the design of the AI system, as well as upon failure to develop an appropriate interpretation of input information. Moreover, even when there is no significant flaw in the AI software, an AI system may fail because the hardware is incapable of robust performance across environments. Finally an AI system is quite likely to fail in situations where, in effect, it is called upon to deliver moral judgments -- a capability AI does not possess. We observe certain trade-offs in measures to mitigate a subset of AI failures and provide some recommendations.

AI failures: A review of underlying issues

Computational simulation modeling is an important approach to formal theory development. It has all the advantages of mathematical models, and is additionally able to overcome problems related to discontinuities and disequilibrium conditions that mathematical models do not handle well. In social science research, a good deal of emphasis is placed on leveraging pioneering models, to further knowledge smoothly. However, two important philosophical paradigms, that of critical realism and scientific realism, sharply differ in terms of what is considered worth preserving and what is considered up for change, in work that follows that of the pioneer. Scientific Realists value knowledge accumulation. Models contradicting key assumptions of a pioneering model may not readily find favor with Scientific Realists. Critical Realists focus on generating new theory by the quickest possible means, particularly in areas where there is a paucity of theory. They favor leveraging the ontological aspects of pioneering models, while being open to contradicting its key assumptions. Thus, notwithstanding the surface similarity of both traditions promoting research by computational simulation modeling, knowledge advancement accomplished is of very different kinds, each with its own distinctive set of implications.

Sasanka Sekhar Chanda

Papers

Administration of an organization undergoing change: Some limitations of the transaction cost economics approach

An Algorithm to find Superior Fitness on NK Landscapes under High Complexity: Muddling Through.

CEO Cognition in Strategy Research

AI failures: A review of underlying issues

Formal theory development by computational simulation modeling: a tale of two philosophical approaches