Bill McKelvey

Populations, Natural Selection, and Applied Organizational Science.

? 1983 by Cornell University 0001-8392/83/2801-01 01 /

Guidelines for the Empirical Classification of Organizations.

00 75 This paper proposes that organizational science could be applied more widely if the field were more concerned with the conditions under which research findings are valid. Papers in the field generalize about organizations as if they were all alike, or refrain from generalizing at all, as if they were all unique. The population perspective presented de-emphasizes the all-alike and all-unique approaches, placing emphasis instead on research methods that improve the description and classification of organizational forms, define more homogeneous groupings, and specify the limited conditions under which predictions may be expected to hold true. The principles of the population perspective are reviewed, and an outline is presented for developing a classification of organizational forms. Suggestions are then made on how to use the perspective to increase and improve the application of organizational research.

Using Coevolutionary and Complexity Theories to Improve IS Alignment: A Multi-Level Approach

Bill McKelvey After a brief review of organization classification, multivariate approaches toward the empirical identification of such classifications are discussed. Ten guidelines for conducting future multivariate classificatory studies are presented, supported by a critique of two published largescale empirical studies. Taxonomic development is viewed as a critical element in the future health of organization science.

Toward a Complexity Theory of Information Systems Development

The misalignment of information systems (IS) components with the rest of an organization remains a critical and chronic unsolved problem in todays complex and turbulent world. This paper argues that the coevolutionary and emergent nature of alignment has rarely been taken into consideration in IS research and that this is the reason behind why IS alignment is so difficult. A view of IS alignment is presented about organizations that draws and builds on complexity theory and especially its focus on coevolution-based self-organized emergent behaviour and structure, which provides important insights for dealing with the emergent nature of IS alignment. This view considers Business/IS alignment as a series of adjustments at three levels of analysis: individual, operational, and strategic, and suggests several enabling conditions – principles of adaptation and scale-free dynamics – aimed at speeding up the adaptive coevolutionary dynamics among the three levels.

Perspective---From Gaussian to Paretian Thinking: Causes and Implications of Power Laws in Organizations

Purpose – Existing literature acknowledges information systems development (ISD) to be a complex activity. This complexity is magnified by the continuous changes in user requirements due to changing organizational needs in changing external competitive environments. Research findings show that, if this increasing complexity is not managed appropriately, information systems fail. The paper thus aims to portray the sources of complexity related to ISD and to suggest the use of complexity theory as a frame of reference, analyzing its implications on information system design and development to deal with the emergent nature of IS.Design/methodology/approach – Conceptual analysis and review of relevant literature.Findings – This article provides a conceptual model explaining how top‐down “official” and bottom‐up “emergent” co‐evolutionary adaptations of information systems design with changing user requirements will result in more effective system design and operation. At the heart of this model are seven firs...

“Smart parts” supply networks as complex adaptive systems: analysis and implications

Although normal distributions and related current quantitative methods are still relevant for some organizational research, the growing ubiquity of power laws signifies that Pareto rank/frequency distributions, fractals, and underlying scale-free theories are increasingly pervasive and valid characterizations of organizational dynamics. When they apply, researchers ignoring power-law effects risk drawing false conclusions and promulgating useless advice to practitioners. This is because what is important to most managers are the extremes they face, not the averages. We show that power laws are pervasive in the organizational world and present 15 scale-free theories that apply to organizations. Next we discuss research implications embedded in Pareto rank/frequency distributions and draw statistical and methodological implications.

Why Gaussian statistics are mostly wrong for strategic organization

Purpose – The purpose of this paper is to critically analyze whether supply networks may be validly treated as complex adaptive systems (CAS). Finding this to be true, the paper turns into the latest concerns of complexity science like Pareto distributions to explain well‐known phenomena of extreme events in logistics, like the bullwhip effect. It aims to introduce a possible solution to handle these effects.Design/methodology/approach – The method is a comparative analysis of current literature in the fields of logistics and complexity science. The discussion of CAS in supply networks is updated to include recent complexity research on power laws, non‐linear dynamics, extreme events, Pareto distribution, and long tails.Findings – Based on recent findings of complexity science, the paper concludes that it is valid to call supply networks CAS. It then finds that supply networks are vulnerable to all the nonlinear and extreme dynamics found in CAS within the business world. These possible outcomes have to b...

Using Complexity Science to effect a paradigm shift in Information Systems for the 21st century

Consider the coasts of England and Norway. They appear jagged no matter what kind of measure is used: miles, kilometers, meters, centimeters, millimeters. This is called ‘scalability’: no matter what the scale of measurement, the phenomenon appears the same. Scalability results from what Benoit Mandelbrot (1983) called ‘fractal geometry’. A cauliflower is an obvious example. Cut off a branch; cut a smaller branch from the first branch; then an even smaller one; and then even another, etc. Now set them all on a table, in line. Each fractal subcomponent is smaller than the former; each has the same shape and structure. They exhibit a ‘power law effect’ because they shrink by a fixed ratio. Power laws underlie fractal geometry. They are ‘indicative of correlated, cooperative phenomena between groups of interacting agents at the microscopic level’ (Cook et al., 2004). They often take the form of rank/size expressions such as F ~ N-β, where F is frequency, N is rank (the variable) and β, the exponent, is constant. In most exponential equations the exponent is a variable. Power laws call for ‘scale-free theories’ because the same theory applies to each of the different levels, that is, the explanation of the generative process is the same across all levels of analysis. The cauliflower is an obvious example of this as well. STRATEGIC ORGANIZATION Vol 3(2): 219–228 DOI: 10.1177/1476127005052700 Copyright ©2005 Sage Publications (London,Thousand Oaks, CA and New Delhi) http://soq.sagepub.com

Nirvana efficiency: a comparative test of residual claims and routines

T homas Kuhn (1962) is famous for his descriptions of science as consisting of long periods of ‘normal puzzle solving’ separated by brief periods of ‘paradigm shift’. Computers have been around for half a century, with Information Systems (IS) in firms existing for several decades. Increasingly, we see various observers complaining about normal puzzle solving in IS (Ciborra, 1994; Orlikowski and Iacono, 2001) at a time when people increasingly spend time in virtual worlds – business people work more and more in virtual teams (VTs), while there are now special programs to rescue teenagers from total emersion in virtual worlds. In the tradition of exploratory learning, this Special Issue is intended to act as a catalyst to stimulate discussion and debate among those who see the need for a paradigm shift in the IS community. To this end, we explore the contribution that complexity science can make to fostering such a shift in the IS discipline and its re-positioning in the management field. The motivation for this Special Issue comes from our observation that the IS and the information technology (IT) landscape is characterized by network dominance and increasing complexity, coupled with the possibility that this heralds a paradigm shift for IS research and practice. For those who are championing the paradigm shift, we think complexity science applications to IS, such as those presented in this Special Issue, offer hope. The network motif is a recursive one. First, the potency of discrete advances in hardware and software capabilities to generate significant change in business and society is realized through the mobilization of network effects. Second, technological advances escalate the potency of network effects by continually enhancing the connectivity and bandwidth of networks. Third, the growth of ITenabled socio-economic networks is accompanied by globalization and an increase in the number and heterogeneity of players who can affect the dynamics of networks. Recent work elucidating the relationship between network topologies and network dynamics illustrates that the low cost of connectivity supported by the internet means that emergent new network order is cheap. ‘Almost free’ network changes can bring about transformational changes in the state of the world. (Barabási, 2002; Newman et al., 2006). The net effect of this is a perception that individuals and organizations have to deal with a world that is increasingly dynamical, complex and uncertain, and that their actions may have unintended consequences that impact on other parts of the world. This is reflected in the management literature where there has been a discernible shift from focusing solely on the firm as a unit of organization to focusing on networks of firms, from considerations of industry-specific value systems to considerations of networks of value systems, and from the concept of discrete industry structures to the concept of ecologies. The fact that the terms ‘network economy’ and ‘network society’ (Castells, 1996) have become integrated into the management lexicon highlights the extent to which networking developments in the IS domain are implicated in the development of the wider management arena. In particular, this shows up in the literature on competitive dynamics where the network economy is characterized by competition in high-velocity environments, speed of technological change and uncertainty (Eisenhardt, 1990, Li and Atuahene-Gima, 2002). Organizations, needing to shape and redefine their own competitive arena (Hayton, 2005), are confronted with the need to continually innovate (Tushman and O’Reilly, 1996; Autio et al., 2000, Hayton 2005). This brings with it the challenges of working towards radical and incremental innovation, (Nambisan, 2002) while dealing with resource constraints (Barney, 1991; McDougall et al. 1994; Stevenson, 1999) to achieve an efficacious balance of risk and return. The quest for coherent integration of social, economic, and IT networks has resulted in the convergence of strategy, OD and IS research on issues of information and informating, connectivity, coordination, competition, collaboration, learning and transformation at multiple levels of analysis in the networked world. These developments highlight the importance of trans-disciplinary Journal of Information Technology (2006) 21, 211–215 & 2006 JIT Palgrave Macmillan Ltd. All rights reserved 0268-3962/06

Toward a Career-Based Theory of Job Involvement: A Study of Scientists and Engineers.

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